Google Scholar: Pratiman Patel | Sabyasachi Swain | Saswata Nandi
Journal Articles
2023
- Patel, P., Kalyanam, R., He, L., Aliaga, D., & Niyogi, D. (2023). Deep Learning based Urban Morphology for City-scale Environmental Modeling. PNAS Nexus. https://doi.org/10.1093/pnasnexus/pgad027
Herein, we introduce a novel methodology to generate urban morphometric parameters that takes advantage of deep neural networks and inverse modeling. We take the example of Chicago, USA, where the Urban Canopy Parameters (UCPs) available from the National Urban Database and Access Portal Tool (NUDAPT) are used as input to the Weather Research and Forecasting (WRF) model. Next, the WRF simulations are carried out with Local Climate Zones (LCZs) as part of the World Urban Data Analysis and Portal Tools (WUDAPT) approach. Lastly, a third novel simulation, Digital Synthetic City (DSC), was undertaken where urban morphometry was generated using deep neural networks and inverse modeling, following which UCPs are re-calculated for the LCZs. The three experiments (NUDAPT, WUDAPT, and DSC) were compared against Mesowest observation stations. The results suggest that the introduction of LCZs improves the overall model simulation of urban air temperature. The DSC simulations yielded equal to or better results than the WUDAPT simulation. Furthermore, the change in the UCPs led to a notable difference in the simulated temperature gradients and wind speed within the urban region and the local convergence/divergence zones. These results provide the first successful implementation of the digital urban visualization dataset within an NWP system. This development now can lead the way for a more scalable and widespread ability to perform more accurate urban meteorological modeling and forecasting, especially in developing cities. Additionally, city planners will be able to generate synthetic cities and study their actual impact on the environment.
@article{patel2023pnasnexus, author = {Patel, Pratiman and Kalyanam, Rajesh and He, Liu and Aliaga, Daniel and Niyogi, Dev}, title = {{Deep Learning based Urban Morphology for City-scale Environmental Modeling}}, journal = {PNAS Nexus}, year = {2023}, month = feb, issn = {2752-6542}, doi = {10.1093/pnasnexus/pgad027}, url = {https://doi.org/10.1093/pnasnexus/pgad027}, note = {pgad027}, eprint = {https://academic.oup.com/pnasnexus/advance-article-pdf/doi/10.1093/pnasnexus/pgad027/49087757/pgad027.pdf} } - Singh, M., Acharya, N., Patel, P., Jamshidi, S., Yang, Z.-L., Kumar, B., Rao, S., Gill, S. S., Chattopadhyay, R., Nanjundiah, R. S., & others. (2023). A modified deep learning weather prediction using cubed sphere for global precipitation. Frontiers in Climate. https://doi.org/10.3389/fclim.2022.1022624
Deep learning (DL), a potent technology to develop Digital Twin (DT), for weather prediction using cubed spheres (DLWP-CS) was recently proposed to facilitate data-driven simulations of global weather fields. DLWP-CS is a temporal mapping algorithm wherein time-stepping is performed through U-NET. Although DLWP-CS has shown impressive results for fields, such as temperature and geopotential height, this technique is complicated and computationally challenging for a complex, non-linear field, such as precipitation, which depends on other prognostic environmental co-variables. To address this challenge, we modify the DLWP-CS and call our technique “modified DLWP-CS” (MDLWP-CS). In this study, we transform the architecture from a temporal to a spatio-temporal mapping (multivariate setup), wherein precursor(s) of precipitation can be used as input. As a proof of concept, as a first simple case, a 2-m surface air temperature is used to predict precipitation using MDLWP-CS. The model is trained using hourly ERA-5 reanalysis and the resulting experimental findings are compared to two benchmark models, viz, the linear regression and an operational numerical weather prediction model, which is the Global Forecast System (GFS). The fidelity of MDLWP-CS is much better compared to linear regression and the results are equivalent to GFS output in terms of daily precipitation prediction with 1 day lag. These results provide an encouraging framework for an efficient DT that can facilitate speedy, high fidelity precipitation predictions.
@article{singh2023modified, title = {A modified deep learning weather prediction using cubed sphere for global precipitation}, author = {Singh, Manmeet and Acharya, Nachiketa and Patel, Pratiman and Jamshidi, Sajad and Yang, Zong-Liang and Kumar, Bipin and Rao, Suryachandra and Gill, Sukhpal Singh and Chattopadhyay, Rajib and Nanjundiah, Ravi S and others}, journal = {Frontiers in Climate}, year = {2023}, doi = {10.3389/fclim.2022.1022624}, publisher = {Frontiers Media SA} } - Mohanty, S., Swain, M., Nadimpalli, R., Osuri, K. K., Mohanty, U. C., Patel, P., & Niyogi, D. (2023). Meteorological Conditions of Extreme Heavy Rains over Coastal City Mumbai. Journal of Applied Meteorology and Climatology, 62(2), 191–208. https://doi.org/10.1175/JAMC-D-21-0223.1
The city of Mumbai, India, frequently receives extreme rainfall (>204.5 mm/day) during the summer monsoonal period (June–September), causing flash floods and other hazards. An assessment of the meteorological conditions that lead to these rain events is carried out for 15 previous cases from 1980 to 2020. The moisture source for such rain events over Mumbai is generally an offshore trough, a midtropospheric cyclone, or a Bay of Bengal depression. The analysis shows that almost all of the extreme rain events are associated with at least two of these conditions co-occurring. The presence of a narrow zone of high sea surface temperature approximately along the latitude of Mumbai over the Arabian Sea can favor mesoscale convergence and is observed at least 3 days before the event. Anomalous wind remotely supplying copious moisture from the Bay of Bengal adds to the intensity of the rain event. The presence of midtropospheric circulation and offshore trough, along with the orographic lifting of the moisture, give a unique meteorological setup to bring about highly localized catastrophic extreme rainfall events over Mumbai. The approach adopted in this study can be utilized for other such locales to develop location-specific guidance that can aid the local forecasting and emergency response communities. Further, it also provides promise for using data-driven/machine learning–based pattern analysis for developing warning triggers.
@article{Mohanty2023Meteorological, author = {Mohanty, Shyama and Swain, Madhusmita and Nadimpalli, Raghu and Osuri, K. K. and Mohanty, U. C. and Patel, Pratiman and Niyogi, Dev}, title = {Meteorological Conditions of Extreme Heavy Rains over Coastal City Mumbai}, journal = {Journal of Applied Meteorology and Climatology}, year = {2023}, publisher = {American Meteorological Society}, address = {Boston MA, USA}, volume = {62}, number = {2}, doi = {10.1175/JAMC-D-21-0223.1}, pages = {191 - 208}, url = {https://journals.ametsoc.org/view/journals/apme/62/2/JAMC-D-21-0223.1.xml} }
2022
- Patel, P., Thakur, P. K., Aggarwal, S. P., Garg, V., Dhote, P. R., Nikam, B. R., Swain, S., & Al-Ansari, N. (2022). Revisiting 2013 Uttarakhand flash floods through hydrological evaluation of precipitation data sources and morphometric prioritization. Geomatics, Natural Hazards and Risk, 13(1), 646–666. https://doi.org/10.1080/19475705.2022.2038696
With advancements in computational technology, data assimilation techniques, high-resolution remote sensing, and complex climate models, numerous precipitation products are available with different spatiotemporal resolutions; however, their evaluation, especially in the Himalayan region, is unexplored. Therefore, this study attempts to assess four sources (gridded observation dataset, reanalysis, satellite, and numerical weather prediction models) of precipitation through hydrological modelling for the catastrophic 2013 floods of Uttarakhand, India. The Upper Ganga Basin located in Western Himalayas is selected as the study area consisting of Alaknanda and Bhagirathi streams in the eastern and western parts. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is employed for rainfall-runoff modelling. The rainfall from IMD, ERA-5, GPM-IMERG-Final, and WRF model outputs are forced into the calibrated HEC-HMS model for assessing their performance in hydrological simulations. The correlation coefficient of IMD, ERA-5, GPM-IMERG-Final, and WRF simulations with respect to the observed flow is 0.89, 0.88, 0.55, and 0.89, respectively, whereas their corresponding Modified Kling-Gupta Efficiency (KGE) is 0.66, 0.72, 0.48, and 0.71. Flash flood prioritization of the sub-watersheds based on morphometric characteristics suggests that the Alaknanda basin is relatively more vulnerable to flash floods due to their elongated nature, highest relative relief, and high mean slope.
@article{patel2022revisiting, title = {{Revisiting 2013 Uttarakhand flash floods through hydrological evaluation of precipitation data sources and morphometric prioritization}}, author = {Patel, Pratiman and Thakur, Praveen Kumar and Aggarwal, Shiv Prasad and Garg, Vaibhav and Dhote, Pankaj Ramji and Nikam, Bhaskar Ramachandra and Swain, Sabyasachi and Al-Ansari, Nadhir}, doi = {10.1080/19475705.2022.2038696}, year = {2022}, journal = {{Geomatics, Natural Hazards and Risk}}, publisher = {Taylor \& Francis}, volume = {13}, number = {1}, pages = {646--666} } - Patel, P., Jamshidi, S., Nadimpalli, R., Aliaga, D. G., Mills, G., Chen, F., Demuzere, M., & Niyogi, D. (2022). Modeling Large-Scale Heatwave by Incorporating Enhanced Urban Representation. Journal of Geophysical Research: Atmospheres, 127(2), e2021JD035316. https://doi.org/10.1029/2021JD035316
This study evaluates the impact of land surface models (LSMs) and urban heterogeneity [using local climate zones (LCZs)] on air temperature simulated by the Weather Research and Forecasting model (WRF) during a regional extreme event. We simulated the 2017 heatwave over Europe considering four scenarios, using WRF coupled with two LSMs (i.e., Noah and Noah-MP) with default land use/land cover (LULC) and with LCZs from the World Urban Database and Access Portal Tools (WUDAPT). The results showed that implementing the LCZs significantly improves the WRF simulations of the daily temperature regardless of the LSMs. Implementing the LCZs altered the surface energy balance partitioning in the simulations (i.e., the sensible heat flux was reduced and latent heat flux was increased) primarily due to a higher vegetation feedback in the LCZs. The changes in the surface flux translated into an increase in the simulated 2-m relative humidity and 10-m wind speed as well as changed air temperature within cities section and generated a temperature gradient that affected the temperatures beyond the urban regions. Despite these changes, the factor separation analysis indicated that the impact of LSM selection was more significant than the inclusion of LCZs. Interestingly, the lowest bias in temperature simulations was achieved when WRF was coupled with the Noah as the LSM and used WUDAPT as the LULC/urban representation.
@article{patel2022modeling, title = {{Modeling Large-Scale Heatwave by Incorporating Enhanced Urban Representation}}, author = {Patel, Pratiman and Jamshidi, Sajad and Nadimpalli, Raghu and Aliaga, Daniel G and Mills, Gerald and Chen, Fei and Demuzere, Matthias and Niyogi, Dev}, year = {2022}, journal = {{Journal of Geophysical Research: Atmospheres}}, publisher = {Wiley Online Library}, volume = {127}, number = {2}, doi = {10.1029/2021JD035316}, pages = {e2021JD035316} } - Dhal, L., & Swain, S. (2022). Understanding and modeling the process of seawater intrusion: a review. Advances in Remediation Techniques for Polluted Soils and Groundwater, 269–290. https://doi.org/10.1016/B978-0-12-823830-1.00009-2
Seawater intrusion (SI) has risen as a major challenge to the current world. With rise in population and rapid industrialization, the water demand has increased drastically. It is also predicted that the climate change will be adversely affecting the freshwater availability, as evident from manifold studies. In such circumstances the saline water intrusion becomes a thought-provoking issue, especially in coastal regions, which is aggravated by anthropogenic activities. This chapter presents an overview of the process of SI and its consequences. The effects are more pronounced over groundwater, which remains the primary source of quality and adequate water supply in the world for domestic, agricultural, and industrial usage. The factors influencing SI are briefly discussed. The measurement and monitoring practices for SI all around the globe are presented, with a special focus on the modeling and prediction techniques. The necessity of providing robust solution is emphasized and the salient measures adopted around the globe to combat the SI are also presented. The interrelationship between climate change, sea level rise, and SI is also briefly discussed.
@article{dhal2022understanding, title = {Understanding and modeling the process of seawater intrusion: a review}, author = {Dhal, Lingaraj and Swain, Sabyasachi}, journal = {Advances in remediation techniques for polluted soils and groundwater}, pages = {269--290}, year = {2022}, doi = {10.1016/B978-0-12-823830-1.00009-2}, publisher = {Elsevier} } - Swain, S., Mishra, S. K., Pandey, A., & Dayal, D. (2022). Spatiotemporal assessment of precipitation variability, seasonality, and extreme characteristics over a Himalayan catchment. Theoretical and Applied Climatology, 147(1), 817–833. https://doi.org/10.1007/s00704-021-03861-0
This paper presents a detailed spatiotemporal analysis of the rainfall variability, seasonality, and the extreme characteristics of Tehri catchment located in the lower Himalayan region in India. To this end, the daily rainfall data is extracted from 22 grids for 117 years (1901–2017) from the high-resolution (0.25° × 0.25°) gridded observation dataset. Monthly rainfall distribution is evaluated using precipitation concentration index (PCI) and seasonality index. The extreme rainfall indices, viz., maximum 1-day rainfall (Rx1Day), maximum 5-day rainfall (Rx5Day), number of rainy days (NxRainy), total precipitation in rainy days (PRCPTOT), number of heavy rainfall events (NxHeavy), maximum consecutive wet days (CWD), and simple daily intensity index (SDII) are computed for each year considering the thresholds suggested by India Meteorological Department (IMD). The Mann–Whitney-Pettitt test when applied to the annual rainfall time series revealed the year 1958 to be the statistically significant change point. The non-parametric modified Mann–Kendall and Sen’s slope tests are employed to detect the trend in monthly, seasonal, annual rainfall time series, extreme precipitation indices, and seasonality indices for both the pre- and post-1958 periods. The annual rainfall over the grids mostly possessed higher negative trends during 1959–2017 than those during 1901–1958, mainly due to the decreasing trends in post-monsoon and winter seasons. Compared to 1901–1958, NxRainy, CWD, and PRCPTOT exhibited a remarkable decreasing trend whereas NxHeavy, Rx1Day, Rx5Day, and SDII exhibited higher positive trends during 1959–2017, indicating intensification of precipitation. The precipitation over the catchment has been more concentrated in the latter epochs of monsoon season and annual rainfall and it is also evident from the increasing trends of the seasonality indices. There is no such study dealing comprehensively with identification of extreme characteristics, seasonality/concentration characteristics, and various categorical trends of precipitation in a Himalayan region reported in literature. This study will be useful in understanding the decreasing trend of precipitation volume coupled with increasing intensity and concentration and it is quite critical for a Himalayan catchment.
@article{swain2022spatiotemporal, title = {Spatiotemporal assessment of precipitation variability, seasonality, and extreme characteristics over a Himalayan catchment}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish and Dayal, Deen}, journal = {Theoretical and Applied Climatology}, volume = {147}, number = {1}, pages = {817--833}, year = {2022}, doi = {10.1007/s00704-021-03861-0}, publisher = {Springer} } - Guptha, G. C., Swain, S., Al-Ansari, N., Taloor, A. K., & Dayal, D. (2022). Assessing the role of SuDS in resilience enhancement of urban drainage system: A case study of Gurugram City, India. Urban Climate, 41, 101075. https://doi.org/10.1016/j.uclim.2021.101075
The increasing frequency of urban floods worldwide due to rapid urbanization, frequent climatic extremes, or poor drainage conditions necessitates evaluating the performance of the urban drainage systems (UDS) and enhancing their resilience. In this study, a comprehensive assessment of the UDS of Gurugram City, India, through the concepts of sustainable drainage systems (SuDS) is presented. A stormwater management model (SWMM) was set up to model the existing UDS response to a design storm of a 5-year return period. The increase in percentage imperviousness (due to urbanization) and rainfall intensity (due to climate change) are considered the governing factors for functional failures. The results revealed climate change to be a more severe threat to UDS than urbanization, while their combinations can further worsen the repercussions. The structural failure was modelled using the single link-failure scenarios, where 3 and 12 conduits possessed low resilience and no resilience (severe), respectively. The role of SuDS in enhancing the resilience of UDS was assessed by simulating all these functional and structural failure scenarios for three SuDS-implemented conditions, i.e., only infiltration trenches (SuDSIT), only retention ponds (SuDSRP), and both of them together (SuDSIT+RP). The SuDS abated the flood magnitudes, delayed the time to peak flow, and stored an additional volume of water within the catchment, thereby justifying their efficacy to mitigate the pluvial flood and enhance the resilience of UDS. The findings of this study encourage implementing SuDS over the developing countries to bring down the frequency of urban floods.
@article{guptha2022assessing, title = {Assessing the role of SuDS in resilience enhancement of urban drainage system: A case study of Gurugram City, India}, author = {Guptha, Guru Chythanya and Swain, Sabyasachi and Al-Ansari, Nadhir and Taloor, Ajay Kumar and Dayal, Deen}, journal = {Urban Climate}, volume = {41}, pages = {101075}, year = {2022}, doi = {10.1016/j.uclim.2021.101075}, publisher = {Elsevier} } - Swain, S., Mishra, S. K., Pandey, A., & Kalura, P. (2022). Inclusion of groundwater and socio-economic factors for assessing comprehensive drought vulnerability over Narmada River Basin, India: a geospatial approach. Applied Water Science, 12(2), 1–16. https://doi.org/10.1007/s13201-021-01529-8
Drought is amongst the most precarious natural hazards associated with severe repercussions. The characterization of droughts is usually carried out by the sector-specific (meteorological/agricultural/hydrological) indices that are mostly based on hydroclimatic variables. Groundwater is the major source of water supply during drought periods, and the socio-economic factors control the aftermaths of droughts; however, they are often ignored by the sector-specific indices, thereby failing to capture the overall impacts of droughts. This study aims to circumvent this issue by incorporating hydroclimatic, socio-economic and physiographic information to assess the overall drought vulnerability over Narmada River Basin, India, which is an agriculture-dominated basin highly dependent on groundwater resources. A Comprehensive Drought Vulnerability Indicator (CDVI) is proposed that assimilates the information on meteorological fluctuations, depth to groundwater level, slope, distance from river reach, population density, land use/land cover, soil type, and elevation through a geospatial approach. The CDVI showed a remarkable geospatial variation over the basin, with a majority (66.4%) of the area under highly to extremely vulnerable conditions. Out of 35 constituent districts of the basin, 9, 22, and 4 districts exhibited moderate, high, and extreme vulnerability to droughts, respectively. These results urge an immediate attention towards reducing drought vulnerability and enhancing resilience towards drought occurrences. The proposed multi-dimensional approach for drought vulnerability mapping would certainly help policy-makers to proactively plan and manage water resources over the basin, especially to ameliorate the pernicious impacts of droughts.
@article{swain2022inclusion, title = {Inclusion of groundwater and socio-economic factors for assessing comprehensive drought vulnerability over Narmada River Basin, India: a geospatial approach}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish and Kalura, Praveen}, journal = {Applied Water Science}, volume = {12}, number = {2}, pages = {1--16}, year = {2022}, doi = {10.1007/s13201-021-01529-8}, publisher = {Springer} } - Swain, S., Sahoo, S., & Taloor, A. K. (2022). Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India. Applied Water Science, 12(4), 1–14. https://doi.org/10.1007/s13201-022-01604-8
This study presents an assessment of groundwater quality over the two constituent districts (Faridabad and Gurgaon) of the National Capital Region (NCR), India, using geospatial and statistical approaches. These districts have been subjected to rapid urbanization and industrialization in recent years. The groundwater quality parameters viz., pH, electrical conductivity (EC), carbonate (CO32−), bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), nitrate (NO3−), fluoride (F−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), silica (SiO2), and total hardness (TH) are obtained for the year of 2017 from 28 sites over the study area. The suitability for human drinking purposes is assessed by comparing the concentration of parameters at each site with respect to their permissible limits recommended by the Bureau of Indian Standards (IS 10500: 2012). The geospatial mapping of the water quality parameters is carried out to visualize their variations, whereas their risk assessment is accomplished by the statistical approaches viz., water quality index (WQI), correlation, and principal component analysis (PCA). The number of sites exceeding the permissible limits of pH, EC, Cl−, SO42−, NO3−, F−, Ca2+, Mg2+, Na+, K+, and TH is obtained to be 7, 15, 5, 6, 8, 3, 5, 7, 18, 3, and 8, respectively. The WQI analysis revealed 10 out of the 28 sites to be unsuitable for drinking purposes. The parameters mostly exhibited positive correlations except for pH that showed a negative correlation with other parameters. The results of PCA revealed the first principal component (PC1) to explain more than 95% of the total variance, thereby significantly reducing the dimensionality. The deteriorated water quality may be mainly attributed to anthropogenic activities, i.e., reckless industrial growth, population explosion, and rapid urbanization. This study emphasizes the need for regular water quality monitoring, and the information reported will certainly help for water resources planning and management, especially over the industrial regions of NCR, India.
@article{swain2022groundwater, title = {Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India}, author = {Swain, Sabyasachi and Sahoo, Sashikanta and Taloor, Ajay Kumar}, journal = {Applied Water Science}, volume = {12}, number = {4}, pages = {1--14}, year = {2022}, doi = {10.1007/s13201-022-01604-8}, publisher = {Springer} } - Swain, S., Sahoo, S., Taloor, A. K., Mishra, S. K., & Pandey, A. (2022). Exploring recent groundwater level changes using Innovative Trend Analysis (ITA) technique over three districts of Jharkhand, India. Groundwater for Sustainable Development, 100783. https://doi.org/10.1016/j.gsd.2022.100783
Groundwater is the largest store of available freshwater in the world. With the increasing impact of climate change and human activities, assessment of variations in groundwater levels is essential. This study presents the trend of groundwater levels in three districts (Purbi Singhbhum, Ranchi and Saraikela) of Jharkhand State, India. The depth to groundwater level (DGWL) data from 24 wells over the three districts for 1996–2018 is collected for both pre-monsoon and post-monsoon seasons. The conventional non-parametric trend analysis techniques (e.g., Mann-Kendall, Sen’s Slope, Spearman’s Rho tests) have several restrictive assumptions, such as Gaussian distributed time series and absence of serial correlation. Innovative Trend Analysis (ITA) technique does not have these restrictive assumptions and therefore, can be effectively used to detect trends in a time series of shorter length. Moreover, ITA is a slope-based technique that provides visual interpretations as well as the statistical significance of trends in a time series, thereby comprehensively acquiring the benefits of multiple conventional methods. Therefore, ITA is employed in this study to investigate the trends in groundwater levels. The results reveal a significantly increasing trend of DGWL for 17 sites in pre-monsoon and 14 sites in post-monsoon seasons. On the other hand, only four and six stations showed negative trends during pre- and post-monsoon seasons, respectively. The increasing DGWL trends at a majority of the sites imply a serious decline in the groundwater levels over the years. This study will be helpful to water resources managers to identify the causes of the declining groundwater levels, take necessary actions to control them, and efficiently manage groundwater at local levels.
@article{swain2022exploring, title = {Exploring recent groundwater level changes using Innovative Trend Analysis (ITA) technique over three districts of Jharkhand, India}, author = {Swain, Sabyasachi and Sahoo, Sashikanta and Taloor, Ajay Kumar and Mishra, SK and Pandey, Ashish}, journal = {Groundwater for Sustainable Development}, pages = {100783}, year = {2022}, doi = {10.1016/j.gsd.2022.100783}, publisher = {Elsevier} } - Swain, S., Taloor, A. K., Dhal, L., Sahoo, S., & Al-Ansari, N. (2022). Impact of climate change on groundwater hydrology: a comprehensive review and current status of the Indian hydrogeology. Applied Water Science, 12(6), 1–25. https://doi.org/10.1007/s13201-022-01652-0
Groundwater is the second largest store of freshwater in the world. The sustainability of the ecosystem is largely dependent on groundwater availability, and groundwater has already been under tremendous pressure to fulfill human needs owing to anthropogenic activities around various parts of the world. The footprints of human activities can be witnessed in terms of looming climate change, water pollution, and changes in available water resources. This paper provides a comprehensive view of the linkage between groundwater, climate system, and anthropogenic activities, with a focus on the Indian region. The significant prior works addressing the groundwater-induced response on the climatic system and the impacts of climate on groundwater through natural and human-instigated processes are reviewed. The condition of groundwater quality in India with respect to various physicochemical, heavy metal and biological contamination is discussed. The utility of remote sensing and GIS in groundwater-related studies is discussed, focusing on Gravity Recovery and Climate Experiment (GRACE) applications over the Indian region. GRACE-based estimates of terrestrial water storage have been instrumental in numerous groundwater studies in recent times. Based on the literature review, the sustainable practices adopted for optimum utilization of groundwater for different purposes and the possible groundwater-based adaptation strategies for climate change are also enunciated.
@article{swain2022impact, title = {Impact of climate change on groundwater hydrology: a comprehensive review and current status of the Indian hydrogeology}, author = {Swain, Sabyasachi and Taloor, Ajay Kumar and Dhal, Lingaraj and Sahoo, Sashikanta and Al-Ansari, Nadhir}, journal = {Applied Water Science}, volume = {12}, number = {6}, pages = {1--25}, year = {2022}, doi = {10.1007/s13201-022-01652-0}, publisher = {Springer} } - Swain, S., Mishra, S. K., Pandey, A., Pandey, A. C., Jain, A., Chauhan, S. K., & Badoni, A. K. (2022). Hydrological modelling through SWAT over a Himalayan catchment using high-resolution geospatial inputs. Environmental Challenges, 8, 100579. https://doi.org/10.1016/j.envc.2022.100579
The concerns of water availability have been increasing due to population explosion, rapid industrialization, and other anthropogenic activities. This urges for an accurate estimation of streamflow at the river basin scale, which is typically carried out by the application of rainfall-runoff models. Though numerous models exist in hydrology literature, their efficiency over the mountainous catchments is generally observed to be poor, mostly due to the lack of high-quality data over such regions. This study presents an application of the widely used soil and water assessment tool (SWAT)-based hydrological modelling using high-resolution geospatial inputs over the Tehri reservoir catchment (India) located in the lower Himalayan region. The Resourcesat-2 Linear Imaging Self-Scanning System (LISS)-IV imageries of land use/land cover (LULC) and the Cartosat-1 digital elevation model (DEM) are procured from National Remote Sensing Centre (NRSC), Indian Space Research Organization (ISRO), India. The LULC and DEM have a spatial resolution of 5.8 m and 2.5 m, respectively. SWAT model is applied for a duration of 12 years (2006-2017) with 2006, 2007-2013 and 2014-2017 as the warm-up, calibration and validation periods, respectively. The results reveal an excellent performance of the model in streamflow simulation. The efficacy measures viz., Nash–Sutcliffe efficiency (NSE) and Coefficient of determination (R2) are obtained to be 0.83 and 0.84, respectively. The information reported in this study will be helpful to the water resources engineers for hydrologic modelling over the mountainous catchments.
@article{swain2022hydrological, title = {Hydrological modelling through SWAT over a Himalayan catchment using high-resolution geospatial inputs}, author = {Swain, Sabyasachi and Mishra, SK and Pandey, Ashish and Pandey, AC and Jain, Atul and Chauhan, SK and Badoni, Anil Kumar}, journal = {Environmental Challenges}, volume = {8}, pages = {100579}, year = {2022}, doi = {10.1016/j.envc.2022.100579}, publisher = {Elsevier} } - Sahoo, S., Majumder, A., Swain, S., Pateriya, B., & Al-Ansari, N. (2022). Analysis of Decadal Land Use Changes and Its Impacts on Urban Heat Island (UHI) Using Remote Sensing-Based Approach: A Smart City Perspective. Sustainability, 14(19), 11892. https://doi.org/10.3390/su141911892
The land surface temperature (LST) pattern is regarded as one of the most important indicators of the environmental consequences of land use/land cover change. The possible contribution of land surface to the warming phenomenon is being investigated by scientists across the world. This research focuses on variations in surface temperature and urban heat islands (UHIs) over the course of two seasons, i.e., winter and summer. Using remotely sensed datasets and geospatial techniques, an attempt was made to analyze the spatiotemporal variation in urban heat islands (UHIs) and its association with LULC over Chandigarh from 2000 to 2020. The Enhanced Built-up and Bareness Index (EBBI), Dry Built-up Index (DBI), and Dry Bare-Soil Index (DBSI) were used to identify built-up areas in the city. The results revealed an increase of 10.08% in BA, whereas the vegetation decreased by 4.5% over the study period, which is in close agreement with the EBBI, DBI, and DBSI assessments. From 2000 to 2020, the UHI intensities increased steadily in both the summer and winter seasons. Dense built-up areas such as the industrial unit of the city possessed the highest UHIindex (>0.7) values.
@article{sahoo2022analysis, title = {Analysis of Decadal Land Use Changes and Its Impacts on Urban Heat Island (UHI) Using Remote Sensing-Based Approach: A Smart City Perspective}, author = {Sahoo, Sashikanta and Majumder, Atin and Swain, Sabyasachi and Pateriya, Brijendra and Al-Ansari, Nadhir}, journal = {Sustainability}, volume = {14}, number = {19}, pages = {11892}, year = {2022}, doi = {10.3390/su141911892}, publisher = {MDPI} } - Swain, S., Mishra, S. K., Pandey, A., Dayal, D., & Srivastava, P. K. (2022). Appraisal of historical trends in maximum and minimum temperature using multiple non-parametric techniques over the agriculture-dominated Narmada Basin, India. Environmental Monitoring and Assessment, 194(12), 1–23. https://doi.org/10.1007/s10661-022-10534-6
In this study, the long-term trends in climatological parameters, viz., maximum temperature (TMAX) and minimum temperature (TMIN), are determined over 68 years (i.e., June 1951 to May 2019) using the gridded observation datasets (1° × 1° spatial resolution) of India Meteorological Department over the Narmada river basin, India. Multiple non-parametric techniques, viz., modified Mann-Kendall (MMK), Sen’s slope (SS), and Spearman’s rho (SR) tests, are used to determine monthly, seasonal, and annual trends over individual grids. The trends are also analyzed for the climatic variables spatially averaged over the entire basin to draw general conclusions on historical climate change. The results reveal a significant spatiotemporal variation in trends of TMAX and TMIN over the basin. In general, both the parameters are found to be increasing. Furthermore, the hottest months (April and May) have become hotter, and the coldest month (January) has become colder, implying a higher probability of increasing temperature extremes. Furthermore, the entire duration of 68 years is divided into two epochs of 34 years, i.e., 1951–1984 and 1985–2018, and the trend analysis of TMAX and TMIN is also carried out epoch-wise to better understand/assess the signals of climate change in recent years. In general, a relatively higher warming trend was observed in the latter epoch. As a majority of the basin area is dominated by agricultural lands, the implications of the temperature trends and their impacts on agriculture are succinctly discussed. The information reported in this study will be helpful for proper planning and management of water resources over the basin under the changing climatic conditions.
@article{swain2022appraisam, title = {Appraisal of historical trends in maximum and minimum temperature using multiple non-parametric techniques over the agriculture-dominated Narmada Basin, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish and Dayal, Deen and Srivastava, Prashant Kumar}, journal = {Environmental Monitoring and Assessment}, volume = {194}, number = {12}, pages = {1--23}, year = {2022}, doi = {10.1007/s10661-022-10534-6}, publisher = {Springer} } - Swain, S., Mishra, S. K., Pandey, A., & Dayal, D. (2022). Assessment of drought trends and variabilities over the agriculture-dominated Marathwada Region, India. Environmental Monitoring and Assessment, 194(12), 1–18. https://doi.org/10.1007/s10661-022-10532-8
Drought is considered among the most perilous events with catastrophic consequences, particularly from the agro-economic point of view. These consequences are expected to exacerbate under the increasing meteorological aberrations due to changing climate, which necessitates investigating drought variabilities. This study presents a thorough spatiotemporal assessment of drought trends and variabilities over the agriculture-dominated Marathwada Region, Maharashtra, India. The precipitation data is extracted from the India Meteorological Department (IMD) gridded product, whereas actual evapotranspiration (ET) and Evaporative Stress Index (ESI) are obtained from Global Land Evaporation Amsterdam Model (GLEAM) datasets. Standardized Precipitation Index (SPI) is used to characterize drought occurrences at multiple time frames, whereas non-parametric tests, i.e., modified Mann–Kendall (MMK) and Sen’s slope (SS) tests, are employed to detect trends. The results reveal the region to be prone to droughts, and SPI at a longer time frame (i.e., 12-monthly moving frame) can capture drought occurrences better than the shorter time frames, which can be attributed to the lesser randomness in the time series in the longer frame. A mix of positive/negative trends of SPI series are found for the monsoonal months; however, they are relatively more concentrated towards negative ZMMK. Hence, the Marathwada Region can be inferred to have exhibited a relatively increased tendency towards drought occurrences. The seasonal differences in mean values and trends of rainfall, ET, and ESI are discussed in detail. Since the Marathwada Region has a monsoon-dominated climate with high agricultural importance, the information reported in this study will help in devising water management strategies to minimize the repercussions of droughts.
@article{swain2022assessment, title = {Assessment of drought trends and variabilities over the agriculture-dominated Marathwada Region, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish and Dayal, Deen}, journal = {Environmental Monitoring and Assessment}, volume = {194}, number = {12}, pages = {1--18}, year = {2022}, doi = {10.1007/s10661-022-10532-8}, publisher = {Springer} } - Swain, S., Mishra, S. K., & Pandey, A. (2022). Assessing spatiotemporal variation in drought characteristics and their dependence on timescales over Vidarbha Region, India. Geocarto International, 1–23. https://doi.org/10.1080/10106049.2022.2136260
In this study, a detailed spatiotemporal assessment of meteorological drought characteristics (viz., persistence, severity, and frequency) is carried out for the Vidarbha Region of Maharashtra, India, which has been infamous for the increasing number of farmer suicides there in the recent past. Using the long-term rainfall data from 11 districts for 62 years (1951–2012), the droughts in different severity classes are characterized by SPI. A detailed investigation of SPI-3, SPI-6, and SPI-12 is also done to assess the dependence of the drought characteristics at different timescales. The results reveal that the Vidarbha region is prone to meteorological droughts with frequency from once in 5 to 8 years. However, the frequency and severity of droughts have significantly increased in 1982–2012 compared to 1951–1981. The persistence of droughts is well captured by SPI at longer timescales. The trend analysis reveals the drought severities to be increasing over 10 out of 11 districts.
@article{swain2022assessing, title = {Assessing spatiotemporal variation in drought characteristics and their dependence on timescales over Vidarbha Region, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, journal = {Geocarto International}, pages = {1--23}, year = {2022}, doi = {10.1080/10106049.2022.2136260}, publisher = {Taylor \& Francis} } - Nandi, S., & Swain, S. (2022). Analysis of heatwave characteristics under climate change over three highly populated cities of South India: a CMIP6-based assessment. Environmental Science and Pollution Research, 1–13. https://doi.org/10.1007/s11356-022-22398-x
Climate change is arguably the most alarming global concern of the twenty-first century, particularly due to the increased frequency of meteorological extremes, e.g., heatwaves, droughts, and floods. Heatwaves are considered a potential health risk and urge further study, robust preparedness, and policy framing. This study presents an analysis of heatwave characteristics for historical (1980–2014), near-future (2021–2055), and far-future (2056–2090) scenarios over three highly populated cities of South India, i.e., Bangalore, Chennai, and Hyderabad. Two different approaches, i.e., the India Meteorological Department (IMD) criterion and the percentile-based criterion, are considered for defining the threshold of a heatwave day. Nine general circulation models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) experiment are selected, evaluated after bias correction, and the best performer was utilized to obtain the temperature projections corresponding to two shared socioeconomic pathways (SSP 2–4.5 and 5–8.5) for the future periods. The results reveal a high frequency of heatwave days over the cities in recent years from both approaches, which may further exacerbate in the future, thereby putting a large population at risk. The number of heatwave days is much higher for SSP5-8.5 than that for SSP2-4.5, depicting the direct effects of anthropogenic activities on the frequency of heatwaves. The detailed analysis of heatwave projections will help develop equitable heat resilient mitigation and adaptation strategies for the future, thereby alleviating their pernicious impacts.
@article{nandi2022analysis, title = {Analysis of heatwave characteristics under climate change over three highly populated cities of South India: a CMIP6-based assessment}, author = {Nandi, Saswata and Swain, Sabyasachi}, journal = {Environmental Science and Pollution Research}, pages = {1--13}, year = {2022}, doi = {10.1007/s11356-022-22398-x}, publisher = {Springer} } - Nandi, S., & Reddy, M. J. (2022). An integrated approach to streamflow estimation and flood inundation mapping using VIC, RAPID and LISFLOOD-FP. Journal of Hydrology, 610, 127842. https://doi.org/10.1016/j.jhydrol.2022.127842
Controlling the damaging effects of fluvial flood events has been a major challenge for mankind. Integrated hydrologic-hydrodynamic models are often employed to estimate the flow and vital flood inundation information for mitigating such damages. The most important criterion for their implementation is that they should offer large-scale applicability with a finer resolution to have local relevance and practicability. This study presented an integrated modeling framework, VIC-RAPID-LISFP that couples a hydrological model (VIC), a river routing model (RAPID) and a hydrodynamic model (LISFLOOD-FP) for fast generation of high-resolution flow and flood inundation extent. The utility of the model is tested and demonstrated for a case study in the Upper Krishna River basin in India. The results showed that the simulated hourly streamflows from the calibrated model match reasonably well with the observations in terms of various efficiency measures. Also, the generated flood inundation maps from the model can reliably capture more than 80% of the satellite-derived flood inundation extent during both the low and high flow events. The proposed modeling framework is based on readily available open-source hydrographic data, and minimum meteorological information, so it has global applicability for supporting a flood management system with local relevance, especially for the data-scarce regions.
@article{nandi2022integrated, title = {An integrated approach to streamflow estimation and flood inundation mapping using VIC, RAPID and LISFLOOD-FP}, author = {Nandi, Saswata and Reddy, Manne Janga}, journal = {Journal of Hydrology}, volume = {610}, pages = {127842}, year = {2022}, doi = {10.1016/j.jhydrol.2022.127842}, publisher = {Elsevier} } - Nandi, S., & Janga Reddy, M. (2022). Evaluating the performance of bias-corrected IMERG satellite rainfall estimates for hydrological simulation over the Upper Bhima River basin, India. Geocarto International, 1–25. https://doi.org/10.1080/10106049.2022.2101695
In this study, the performance and hydrological utility of IMERG rainfall estimates over the Upper Bhima River basin, India, are comprehensively evaluated using a VIC-RAPID hydrologic model. Moreover, a bias-correction scheme based on the long short-term memory (LSTM) neural network method is proposed, and the results are compared with two commonly used bias-correction techniques. Results indicated that the spatial distribution of observed rainfall is well captured by IMERG; however, it showed a general tendency of overestimation, especially on a daily timescale. The LSTM-based approach showed notable improvements against the other bias-correction techniques substantiating its utility for accurately estimating rainfall amount and skillful detection of rainfall events in the study area. The VIC-RAPID model simulations for hydrological variables revealed a significant improvement in the performance of the bias-corrected IMERG product. In addition, the effect of the hydrological model recalibration with the different rainfall input datasets has also been elucidated.
@article{nandi2022evaluating, title = {Evaluating the performance of bias-corrected IMERG satellite rainfall estimates for hydrological simulation over the Upper Bhima River basin, India}, author = {Nandi, Saswata and Janga Reddy, Manne}, journal = {Geocarto International}, pages = {1--25}, year = {2022}, doi = {10.1080/10106049.2022.2101695}, publisher = {Taylor \& Francis} } - Nadimpalli, R., Patel, P., Mohanty, U. C., Attri, S. D., & Niyogi, D. (2022). Impact of urban parameterization and integration of WUDAPT on the severe convection. Computational Urban Science, 2(1), 41. https://doi.org/10.1007/s43762-022-00071-w
Amplified rates of urban convective systems pose a severe peril to the life and property of the inhabitants over urban regions, requiring a reliable urban weather forecasting system. However, the city scale’s accurate rainfall forecast has constantly been a challenge, as they are significantly affected by land use/ land cover changes (LULCC). Therefore, an attempt has been made to improve the forecast of the severe convective event by employing the comprehensive urban LULC map using Local Climate Zone (LCZ) classification from the World Urban Database and Access Portal Tools (WUDAPT) over the tropical city of Bhubaneswar in the eastern coast of India. These LCZs denote specific land cover classes based on urban morphology characteristics. It can be used in the Advanced Research version of the Weather Research and Forecasting (ARW) model, which also encapsulates the Building Effect Parameterization (BEP) scheme. The BEP scheme considers the buildings’ 3D structure and allows complex land–atmosphere interaction for an urban area. The temple city Bhubaneswar, the capital of eastern state Odisha, possesses significant rapid urbanization during the recent decade. The LCZs are generated at 500 m grids using supervised classification and are ingested into the ARW model. Two different LULC dataset, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and WUDAPT derived LCZs and initial, and boundary conditions from NCEP GFS 6-h interval are used for two pre-monsoon severe convective events of the year 2016. The results from WUDAPT based LCZ have shown an improvement in spatial variability and reduction in overall BIAS over MODIS LULC experiments. The WUDAPT based LCZ map enhances high-resolution forecast from ARW by incorporating the details of building height, terrain roughness, and urban fraction.
@article{nadimpalli2022impact, title = {Impact of urban parameterization and integration of WUDAPT on the severe convection}, author = {Nadimpalli, Raghu and Patel, Pratiman and Mohanty, UC and Attri, SD and Niyogi, Dev}, journal = {Computational Urban Science}, volume = {2}, number = {1}, pages = {41}, year = {2022}, doi = {10.1007/s43762-022-00071-w}, publisher = {Springer} }
2021
- Patel, P., Karmakar, S., Ghosh, S., Aliaga, D. G., & Niyogi, D. (2021). Impact of green roofs on heavy rainfall in tropical, coastal urban area. Environmental Research Letters, 16(7), 074051. https://doi.org/10.1088/1748-9326/ac1011
Green Roofs (GRs) are one of the measures considered for Urban Heat Island (UHI) mitigation. The cooling effects of GRs are well studied in the literature. However, previous work has not addressed the impacts of GRs on heavy rainfall in cities. This study develops and tests the hypothesis that incorporating green roofs in urban areas enhances the magnitude of rain for heavy rainfall events. To test this, examples of heavy rainfall events over three different years are examined over Mumbai, India, one of the megapoleis that continues to witness heavy rains and urban flooding. The heavy rain events are simulated using Weather Research and Forecasting (WRF) model for different green roof fraction (GF) scenarios (10%, 25%, 50%, 75%, and 100%) over the urban area. The GF simulations are compared to the ’no GF’ simulation (control run). The results indicate a consistent increase (1%–72%) in the total accumulated precipitation in all GF scenarios. Additional moisture and increased equivalent potential temperature aided the formation and sustenance of localized pockets of enhanced rain occurrences, contributing to the total amount of rainfall for the rain events for the domain. The increase in rainfall amounts leads to higher runoff and can increase the risk of flash floods. Thus, it is necessary to account for this rainfall-based feedback of GR before adopting it as a mitigation option. The results of this work may be helpful in effective urban planning and managing the urban climate extremes.
@article{patel2021impact, title = {{Impact of green roofs on heavy rainfall in tropical, coastal urban area}}, author = {Patel, Pratiman and Karmakar, Subhankar and Ghosh, Subimal and Aliaga, Daniel G and Niyogi, Dev}, year = {2021}, journal = {{Environmental Research Letters}}, publisher = {IOP Publishing}, volume = {16}, number = {7}, doi = {10.1088/1748-9326/ac1011}, pages = {074051} } - Swain, S., Mishra, S. K., & Pandey, A. (2021). A detailed assessment of meteorological drought characteristics using simplified rainfall index over Narmada River Basin, India. Environmental Earth Sciences, 80(6), 1–15. https://doi.org/10.1007/s12665-021-09523-8
Drought is amongst the most precarious phenomena that cause serious repercussions, especially over the agriculture-dominated regions. A detailed assessment of droughts is necessary to develop robust frameworks for combating its ill effects. This study presents an analysis of meteorological drought characteristics (frequency, severity and persistence) using precipitation data of twenty-four districts for 1954–2013 over the Narmada River Basin, which is located in the core of the Indian Monsoon region and has great agricultural importance. Further, the entire duration is divided into two epochs, i.e. 1954–83 and 1984–2013, for comparative analysis. A simplified rainfall index (RIS) is proposed, which is based on the concept of percentage deviation from normal monsoon rainfall along with the uniform transition from moderate to severe and severe to extreme droughts. The basin is found to be prone to droughts and the drought frequency varied from once in three to 8 years over different districts. The droughts are more frequent and severe in the western portions of the basin as compared to the eastern portions. The majority of the districts have undergone droughts persisting for 3 years at least once. The epoch-wise analysis reveals a significantly higher frequency, severity and persistence of droughts in the recent epoch. The results of trend analysis using the Modified Mann–Kendall test indicate an increasing trend of droughts over twenty-one districts and significantly increasing over eleven districts. The information reported in this study will be helpful for proper planning and management of water resources over the basin and hence, reduce the pernicious effects of droughts.
@article{swain2021detailed, title = {A detailed assessment of meteorological drought characteristics using simplified rainfall index over Narmada River Basin, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, journal = {Environmental Earth Sciences}, volume = {80}, number = {6}, pages = {1--15}, year = {2021}, doi = {10.1007/s12665-021-09523-8}, publisher = {Springer} } - Sahoo, S., Swain, S., Goswami, A., Sharma, R., & Pateriya, B. (2021). Assessment of trends and multi-decadal changes in groundwater level in parts of the Malwa region, Punjab, India. Groundwater for Sustainable Development, 14, 100644. https://doi.org/10.1016/j.gsd.2021.100644
Due to spatial unevenness in rainfall, groundwater dependency for irrigation has increased exponentially, which poses a challenge for its sustainability. Hence, the long-term behaviour of groundwater level (GWL) fluctuations needs to be understood for better management of water resources and formulating a new action plan. Due to semi-arid climatic condition, most of the agricultural lands in Malwa region of Punjab in India depend on the groundwater for irrigation. The present study focuses on multi-decadal trend estimation and spatio-temporal variations of GWL changes using geostatistics and analyzing the groundwater fluctuations using the standardized depth to water level index (SDWLI) method over the Malwa region. For this study, GWL data for 90 observation wells/piezometers for 21 years (1997–2018) were analyzed. The wells were classified into different clusters according to the fluctuation rate using hierarchical cluster analysis. The trend for each well’s GWL changes was analyzed with the Modified Mann–Kendall (MMK) test and Sen’s slope. The trend analysis results show that most of the wells over the Malwa region possess a significantly declining trend of GWL during 1997–2018. The spatio-temporal variation maps reveal that more than 30 % of tubewells in the eastern part of the study region have seen an average depletion rate of about 40 cm/year in both seasons (pre- and post-monsoon). In contrast, GWL in southwestern part of the Malwa region shows an evident rise in water level during the last two decades; this rising water level causes severe waterlogging problems during the monsoon period. Over 21 years, we observed that more than 20 % of wells had increased GWL in the southwestern part of the Malwa region. The present study’s result raises concern about groundwater resources’ future in the highly groundwater-dependent Malwa region.
@article{sahoo2021assessment, title = {Assessment of trends and multi-decadal changes in groundwater level in parts of the Malwa region, Punjab, India}, author = {Sahoo, Sashikanta and Swain, Sabyasachi and Goswami, Ajanta and Sharma, Radhika and Pateriya, Brijendra}, journal = {Groundwater for Sustainable Development}, volume = {14}, pages = {100644}, year = {2021}, doi = {10.1016/j.gsd.2021.100644}, publisher = {Elsevier} } - Guptha, G. C., Swain, S., Al-Ansari, N., Taloor, A. K., & Dayal, D. (2021). Evaluation of an urban drainage system and its resilience using remote sensing and GIS. Remote Sensing Applications: Society and Environment, 23, 100601. https://doi.org/10.1016/j.rsase.2021.100601
The increasing number of pluvial floods due to extreme climatic events or poor maintenance of the drainage networks urge for assessing the performance of the urban drainage system (UDS). This paper presents a comprehensive evaluation of the UDS of Gurugram City, India. While the limited availability of sub-hourly precipitation and finer resolution geospatial data pose major challenges in the detailed analyses through Storm Water Management Model (SWMM), it was circumvented by utilizing the high-resolution remotely sensed datasets viz., IMERG (half-hourly precipitation data from 2000 to 2019), ALOS PALSAR (Digital Elevation Model) and Sentinel-2 (land use/land cover). Functional failure scenarios (i.e., the combinations of climate change and urbanization) were simulated to assess the impacts on the resilience of the UDS. The modelling results showed that individually, climate change would impose a more serious threat than urbanization, whereas their combinations would significantly hamper the resilience of the UDS. The structural failure (only single link-failure) scenarios were analyzed, and 11 out of 25 conduits were identified to be non-resilient. The study highlights the importance of the readily available remote sensing datasets, which fill the gap of non-availability of ground-based datasets at desirable resolutions, especially in developing countries.
@article{guptha2021evaluation, title = {Evaluation of an urban drainage system and its resilience using remote sensing and GIS}, author = {Guptha, Guru Chythanya and Swain, Sabyasachi and Al-Ansari, Nadhir and Taloor, Ajay Kumar and Dayal, Deen}, journal = {Remote Sensing Applications: Society and Environment}, volume = {23}, pages = {100601}, year = {2021}, doi = {10.1016/j.rsase.2021.100601}, publisher = {Elsevier} } - Bahita, T. A., Swain, S., Pandey, P., & Pandey, A. (2021). Assessment of heavy metal contamination in livestock drinking water of Upper Ganga Canal (Roorkee City, India). Arabian Journal of Geosciences, 14(24), 1–13. https://doi.org/10.1007/s12517-021-08874-7
The emphasis upon livestock health requires regular assessment of livestock drinking water quality. The results of this study are based on 12 months of water quality survey over 18 sites in Upper Ganga Canal (UGC) in Roorkee City, India, covering a command area of nearly 450 km2. Conventionally, the water of the UGC provides irrigation to agricultural land, and also it is used as a source of livestock drinking water. In this study, special attention was paid to quantify the major metallic contaminants such as aluminum, arsenic, cadmium, chromium, cobalt, copper, iron, lead, manganese, mercury, and zinc. Subsequently, a suitability analysis was performed by comparing the observed concentrations of heavy metals with the existing water quality guidelines proposed by regulatory agencies, such as the Australian and New Zealand Environment and Conservation Council (ANZECC, 2000), Canadian Council of Ministers of the Environment (CCME, 2008), Department of Water Affairs and Forestry, South Africa (DWAF, 1996), and Food and Agricultural Organization (FAO, 1985). The arithmetic weightage-based heavy metal pollution index (HPI) was also computed considering all the metals together to evaluate the pollution status of the UGC canal. Results of water quality analysis indicate that the levels of mercury and manganese were considerably higher than their permissible limit in water. Concentrations of heavy metals viz., lead, arsenic, chromium, cobalt, cadmium, and copper, along with aluminum, were found to be mostly within their recommended limits. HPI of water in UGC, Roorkee, was found to be suitable for livestock drinking, excluding three sites.
@article{bahita2021assessment, title = {Assessment of heavy metal contamination in livestock drinking water of Upper Ganga Canal (Roorkee City, India)}, author = {Bahita, Tesfamariam Abreha and Swain, Sabyasachi and Pandey, Pramod and Pandey, Ashish}, journal = {Arabian Journal of Geosciences}, volume = {14}, number = {24}, pages = {1--13}, year = {2021}, doi = {10.1007/s12517-021-08874-7}, publisher = {Springer} }
2020
- Patel, P., Karmakar, S., Ghosh, S., & Niyogi, D. (2020). Improved simulation of very heavy rainfall events by incorporating WUDAPT urban land use/land cover in WRF. Urban Climate, 32, 100616. https://doi.org/10.1016/j.uclim.2020.100616
A World Urban Data Analysis and Portal Tool (WUDAPT) based Local Climate Zone (LCZ) classification and mapping is done for Mumbai, India. Prior WUDAPT-based urban studies have primarily focused on urban heat island (UHI) assessment, and this is the first study to assess the impact on rainfall simulations. Accordingly, in this study, the impact of incorporating the LCZ map in the Weather Research and Forecasting (WRF) model for simulating very heavy rainfall events over Mumbai is assessed. The classified LCZ map is incorporated in the WRF model, and the model performance is compared against the Control, for four recent very heavy rain events. Comparing the results from paired simulations reveals that the rainfall amount and spatial variability is significantly different when the LCZ framework is used. Implementation of WUDAPT data, introduces heterogeneity in the morphological characteristics of the city, which contributes to microscale feedbacks that appear to organize and impact the mesoscale convergence/divergence and convection fields in the WRF model. The study results show variability within the cases highlighting the need for additional investigations in different cities. Overall, the incorporation of WUDAPT LCZs in WRF results in notably improving the model performance for heavy rainfall simulation in urban areas.
@article{patel2020improved, title = {{Improved simulation of very heavy rainfall events by incorporating WUDAPT urban land use/land cover in WRF}}, author = {Patel, Pratiman and Karmakar, Subhankar and Ghosh, Subimal and Niyogi, Dev}, year = {2020}, journal = {{Urban Climate}}, publisher = {Elsevier}, volume = {32}, doi = {10.1016/j.uclim.2020.100616}, pages = {100616} } - Nandi, S., & Manne, J. R. (2020). Spatiotemporal analysis of water balance components and their projected changes in near-future under climate change over Sina Basin, India. Water Resources Management, 34(9), 2657–2675. https://doi.org/10.1007/s11269-020-02551-2
Quantification of water-budget components is an essential step in the planning and management of water resources in any river basin. Recently several studies emphasized that climate change would inevitably affect terrestrial hydrology. This study applies distributed hydrological modeling using the Variable Infiltration Capacity (VIC) model to simulate the water balance components in the Sina basin, a drought-prone region in India. We analyzed the long-term spatiotemporal dynamics of precipitation, evapotranspiration, surface runoff, and baseflow components, and their alterations due to impending climate change. The study employed the Mann-Kendall test and Sen’s slope estimators to analyze the spatiotemporal trends of the water balance components during the baseline (1980–2010) and for the near future (2019–2040) periods. For the baseline period, precipitation exhibited an increasing trend, particularly during the monsoon season. On the evaluation of the annual water balance components, it showed that the basin has a low annual rainfall ( 718 mm) and relatively a very high annual evapotranspiration ( 572 mm) during 1980–2010, which might be the main reason for frequent droughts in the study basin. Further, for analyzing the climate change impacts on the water budget in the Sina basin, the VIC model was forced with outputs from a set of global climate models for near future (2019–2040) for two emission scenarios RCP4.5 and RCP8.5. Analysis of the results revealed that the water balance components in the near future would be negatively affected by climate change despite their increasing pattern in the baseline period. In comparison to the baseline (1980–2010), the surface runoff would decrease by as much as 32% for the near future, which stresses for planning and adaptation of appropriate mitigation measures in the basin.
@article{nandi2020spatiotemporal, title = {Spatiotemporal analysis of water balance components and their projected changes in near-future under climate change over Sina Basin, India}, author = {Nandi, Saswata and Manne, Janga Reddy}, journal = {Water Resources Management}, volume = {34}, number = {9}, pages = {2657--2675}, year = {2020}, doi = {10.1007/s11269-020-02551-2}, publisher = {Springer Netherlands} } - Nandi, S., & Janga Reddy, M. (2020). Comparative performance evaluation of self-adaptive differential evolution with GA, SCE and DE algorithms for the automatic calibration of a computationally intensive distributed hydrological model. H2Open Journal, 3(1), 306–327. https://doi.org/10.2166/h2oj.2020.030
Recently, physically-based hydrological models have been gaining much popularity in various activities of water resources planning and management, such as assessment of basin water availability, floods, droughts, and reservoir operation. Every hydrological model contains some parameters that must be tuned to the catchment being studied to obtain reliable estimates from the model. This study evaluated the performance of different evolutionary algorithms, namely genetic algorithm (GA), shuffled complex evolution (SCE), differential evolution (DE), and self-adaptive differential evolution (SaDE) algorithm for the parameter calibration of a computationally intensive distributed hydrological model, variable infiltration capacity (VIC) model. The methodology applied and tested for a case study of the upper Tungabhadra River basin in India and the performance of the algorithms is evaluated in terms of reliability, variability, efficacy measures in a limited number of function evaluations, their ability for achieving global convergence, and also by their capability to produce a skilful simulation of streamflows. The results of the study indicated that SaDE facilitates an effective calibration of the VIC model with higher reliability and faster convergence to optimal solutions as compared to the other methods. Moreover, due to the simplicity of the SaDE, it provides easy implementation and flexibility for the automatic calibration of complex hydrological models.
@article{nandi2020comparative, title = {Comparative performance evaluation of self-adaptive differential evolution with GA, SCE and DE algorithms for the automatic calibration of a computationally intensive distributed hydrological model}, author = {Nandi, Saswata and Janga Reddy, M}, journal = {H2Open Journal}, volume = {3}, number = {1}, pages = {306--327}, year = {2020}, doi = {10.2166/h2oj.2020.030}, publisher = {IWA Publishing} }
2019
- Patel, P., Ghosh, S., Kaginalkar, A., Islam, S., & Karmakar, S. (2019). Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment. Atmospheric Research, 223, 39–48. https://doi.org/10.1016/j.atmosres.2019.03.005
Increasing incidences of flash floods highlight the need for a reliable flood forecasting system to minimize the losses of lives and property. The most formidable challenge of flood forecasting is the availability of high resolution and accurate precipitation forecast despite having a sophisticated 3-ways flood hydrodynamic model. Global rainfall forecasting products are of coarse resolution, which makes them less reliable for urban flood forecasting. Therefore, high-resolution regional weather forecasting models such as the Weather Research and Forecasting (WRF) model are used to generate fine-scale rainfall estimates. Precipitation forecasting from the WRF model is highly dependent on model configuration, especially cumulus (CU) parameterization and microphysics (MP) schemes. In the present study, three physics schemes that include two urban, four CU and three MP schemes of WRF model are investigated for extreme precipitation estimates. The six events comprised of two of the highest rainfall events of the years 2012, 2013 and 2014 have been selected for investigation over Mumbai, India. The events are simulated using initial and boundary conditions from the ERA-Interim Reanalysis dataset. The simulated rainfall events are evaluated against the observations from 28 automatic weather stations over Mumbai. The analysis suggests that building environment parameterization (BEP) scheme influences the spatial pattern of the rainfall along with the reduction in rainfall bias. Further, CU schemes affect the magnitude of the rainfall while MP schemes have a lesser impact than the former. WRF simulations with BEP urban scheme, Grell-Devenyi 3D CU, and Lin MP scheme performs best (out of selected combinations). Besides, the best performing scheme has been tested with initial and boundary conditions from the global forecasting system (GFS) for the same events; the results have shown improved rainfall estimates than the GFS forecasts.
@article{patel2019performance, title = {{Performance evaluation of WRF for extreme flood forecasts in a coastal urban environment}}, author = {Patel, Pratiman and Ghosh, Subimal and Kaginalkar, Akshara and Islam, Sahidul and Karmakar, Subhankar}, year = {2019}, journal = {{Atmospheric Research}}, publisher = {Elsevier}, volume = {223}, doi = {10.1016/j.atmosres.2019.03.005}, pages = {39--48} }
2017
- Nandi, S., Reddy, M. J., & others. (2017). Distributed rainfall runoff modeling over Krishna river basin. European Water, 57, 71–76. http://www.ewra.net/ew/pdf/EW_2017_57_10.pdf
Floods can have catastrophic consequences and can have effects on the economy, environment and people. It initiates comprehensive assessment and forecasting of possible flooding events, which is typically carried out using hydrological models. Thus, the main objective of this study was to present a distributed hydrological model, namely Variable Infiltration Capacity (VIC) model for simulating the hydrological variables over Krishna River Basin, India and evaluating its performance by comparing with observed datasets. The main advantages of the VIC model compared to other physically based hydrological models, are the variable infiltration curve, which implements a nonlinear function of the fractional grid cell area to scale the maximum infiltration for enabling runoff calculations for sub grid-scale areas and the parameterization of baseflow using a nonlinear recession curve. Meteorological forcings at 0.5 degree by 0.5 degree spatial resolution from 1980 to 2005 over the basin were used to run the model at a daily time step. The model showed an acceptable performance during calibration and validation with Nash-Sutcliffe efficiency (NSE) = 0.34 and coefficient of determination (R²) = 0.60 for calibration and NSE = 0.42 and R² = 0.68 for validation periods. The results from VIC model shows that it can handle large-scale variability. However, it has a tendency to overestimate the streamflow in the downstream portion possibly due to not considering the effect of storage structures in the present model.
@article{nandi2017distributed, title = {Distributed rainfall runoff modeling over Krishna river basin}, author = {Nandi, S and Reddy, MJ and others}, journal = {European Water}, volume = {57}, pages = {71--76}, year = {2017}, url = {http://www.ewra.net/ew/pdf/EW_2017_57_10.pdf}, publisher = {EW Publications} }
software
2022
- Nandi, S., Patel, P., & Swain, S. (2022). IMDLIB: A python library for IMD gridded data. Zenodo. https://doi.org/10.5281/zenodo.7205414
Produces NetCDF data following CF-1.7 conventions. Added support for converting data into Geo-TIFF format. Improvement in return process of the imd.get_data() functionality Updated the link form new https based data-load protocol.
@software{saswata_nandi_2022_7205414, title = {{IMDLIB: A python library for IMD gridded data}}, author = {Nandi, Saswata and Patel, Pratiman and Swain, Sabyasachi}, year = {2022}, month = oct, publisher = {Zenodo}, doi = {10.5281/zenodo.7205414}, url = {https://doi.org/10.5281/zenodo.7205414} }
dataset
2022
- Patel, P., & Roth, M. (2022). A High-Resolution Dataset of Global Urban Fraction for Mesoscale Urban Modelling (Version 2.0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7298393
Coupled urban-atmospheric models are extensively used to understand the urban environment and its impact on atmospheric processes. A common requirement of these models is information about the “urban fraction” (fraction of model grid covered by impervious surface area (ISA)). The European Space Agency (ESA) WorldCover product provides a global land cover map for the base year of 2020 and 2021 at a spatial resolution of 10 m. The dataset is based on Sentinel-1 and Sentinel-2 data with an overall accuracy of 74.4% (2020) and 76.7% (2021). In this study we process the WorldCover dataset and provide a ready-to-use “urban fraction” that can be incorporated in urban modelling systems. The dataset contains GeoTIFF and Weather Research and Forecasting Pre-processing System (WRF-WPS) format files for 1, 0.5, 0.25, 0.009 ( 1 km), 0.0027 ( 300 m), and 0.0009 ( 100 m) degree spatial resolutions.
@dataset{patel_pratiman_2022_7298393, title = {{A High-Resolution Dataset of Global Urban Fraction for Mesoscale Urban Modelling}}, author = {Patel, Pratiman and Roth, Matthias}, year = {2022}, month = aug, publisher = {Zenodo}, doi = {10.5281/zenodo.7298393}, url = {https://doi.org/10.5281/zenodo.7298393}, version = {2.0.1} }
Book Chapters
2022
- Thakur, P. K., Patel, P., Garg, V., Roy, A., Dhote, P., Bhatt, C. M., Nikam, B. R., Chouksey, A., & Aggarwal, S. P. (2022). Role of Geospatial Technology in Hydrological and Hydrodynamic Modeling-With Focus on Floods Studies. In Geospatial Technologies for Land and Water Resources Management (pp. 483–503). Springer. https://doi.org/10.1007/978-3-030-90479-1_26
Assessment of surface water with higher accuracy is very critical in the present changing environment. Such assessment requires understanding of each and every hydrological process involved in hydrological cycle. The land characteristics along with climate variables make it a daunting task. With the advent of geospatial technology, both land surface and climate parameters may be studied with higher accuracy. Some of the hydrological parameters such as precipitation, soil moisture, evapotranspiration, and water level can now directly be retrieved using remote sensing data. However, other hydrological components such as rainfall-runoff, snowmelt-runoff, peak discharge, or flood hydrograph need modeling approach. Most of the surface and climate inputs required for hydrological and hydrodynamic modeling nowadays can be quantified using the geospatial datasets. It makes modeling more realistic, and hydrological response of large basins can be studied. The models are utilized for studying the hydrological extremes such as flood and droughts. Floods are one of the most naturally re-occurring hazards, which significantly impact the long-term sustainable use of land and water resources of a geographical region. The chapter focuses the use of geospatial technology for H&H modeling with relevant case studies on flood modeling. Further, the improvements in modeling outputs may be done by assimilating the geospatial inputs in near-real time. Moreover, these geospatial inputs are being updated and improved in spatial-temporal domain with the advancement in geospatial technology.
@incollection{thakur2022role, title = {{Role of Geospatial Technology in Hydrological and Hydrodynamic Modeling-With Focus on Floods Studies}}, author = {Thakur, Praveen K and Patel, Pratiman and Garg, Vaibhav and Roy, Adrija and Dhote, Pankaj and Bhatt, CM and Nikam, Bhaskar R and Chouksey, Arpit and Aggarwal, SP}, year = {2022}, booktitle = {{Geospatial Technologies for Land and Water Resources Management}}, publisher = {Springer}, doi = {10.1007/978-3-030-90479-1_26}, pages = {483--503} } - Swain, S., Mishra, S. K., & Pandey, A. (2022). Appraisal of Land Use/Land Cover Change Over Tehri Catchment Using Remote Sensing and GIS. In Geospatial Technologies for Land and Water Resources Management (pp. 37–51). Springer. https://doi.org/10.1007/978-3-030-90479-1_3
The Himalayan reservoirs have immense significance from the point of view of water resources planning and management. However, natural and anthropogenic changes and their effects upon these reservoirs are often not explored, mainly due to limitations of data availability. This chapter presents an appraisal of land use/land cover (LULC) changes over the Tehri catchment located at the lower Himalayan region, using remote sensing and geographic information system (GIS). The imageries are collected for different years, i.e., 2008, 2014, and 2020 from the Landsat 5, Landsat 8, and Sentinel 2 satellites, respectively, with the objective of deriving information on different LULC classes. Following a supervised classification, the catchment area is divided into eight classes, viz. open forest, dense forest, water bodies, shrubland, agricultural land, settlements, barren land, and snow covers. The accuracy of classification is assessed with respect to the Google Earth images and ground truth verification. A comparison between the areal coverage of the LULC classes was analyzed for temporal LULC change detection over the catchment. Comparing 2008 and 2020, it is clear that the dense forests and barren land have decreased. On the other hand, an increase in the open forests, water bodies, shrubland, snow, and settlement is observed. The accuracy assessment results confirm that the LULC changes reported in this study are justifiably accurate and utilizable for further applications. The results reported in this study may be helpful to frame solutions to hydrological problems of the Tehri catchment. Moreover, this study highlights the usefulness of remote sensing and GIS in hydrological applications, even in mountainous catchments.
@incollection{swain2022appraisal, title = {Appraisal of Land Use/Land Cover Change Over Tehri Catchment Using Remote Sensing and GIS}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, booktitle = {Geospatial Technologies for Land and Water Resources Management}, pages = {37--51}, year = {2022}, doi = {10.1007/978-3-030-90479-1_3}, publisher = {Springer} } - Swain, S., Mishra, S. K., Pandey, A., & Dayal, D. (2022). A Stochastic Model-Based Monthly Rainfall Prediction Over a Large River Basin. In Sustainability of Water Resources (pp. 133–144). Springer. https://doi.org/10.1007/978-3-031-13467-8_9
Given the current scenarios of climate change and its impacts, sustainable management of water resources has become a challenging task, especially over the arid and semi-arid regions. An accurate large-scale prediction of rainfall is the key factor to fulfil the sustainability goals in water resources sector. Therefore, in this study, an auto-regressive integrated moving average (ARIMA) model is set up considering both non-seasonal and seasonal components of rainfall over Narmada River Basin, India. Rainfall over the entire basin from June 1951 to May 2005 is used to develop the model for monthly rainfall forecasting, which is validated for fourteen years, i.e., June 2005 to May 2019. ARIMA (2, 0, 0) (4, 1, 4)12 is found to be the best-fit model that showed an excellent agreement with the observed rainfall in the validation period (r = 0.925, NSE = 0.855), which justifies its applicability for future rainfall forecasting over the basin.
@incollection{swain2022stochastic, title = {A Stochastic Model-Based Monthly Rainfall Prediction Over a Large River Basin}, author = {Swain, Sabyasachi and Mishra, SK and Pandey, Ashish and Dayal, Deen}, booktitle = {Sustainability of Water Resources}, pages = {133--144}, year = {2022}, doi = {10.1007/978-3-031-13467-8_9}, publisher = {Springer} }
2021
- Bahita, T. A., Swain, S., Dayal, D., Jha, P. K., & Pandey, A. (2021). Water quality assessment of Upper Ganga canal for human drinking. In Climate Impacts on Water Resources in India (pp. 371–392). Springer. https://doi.org/10.1007/978-3-030-51427-3_28
Water is fundamental need for existence of life. The deterioration in quality of drinking water may lead to severe impacts on human health. Thus, the quality assessment drinking water sources is of paramount concern. This study presents a comprehensive evaluation of water quality of Upper Ganga Canal (UGC) in Roorkee, Haridwar, Uttarakhand, India. The water samples were collected every month from 18 sites of the UGC from November 2014 to October 2015 and assessed at seasonal level (winter, summer and monsoon) for 15 important physicochemical parameters and 10 toxic trace metals. The results were compared with guidelines prescribed by four authentic standards viz., BIS (Bureau of Indian Standards: Drinking water specifications, 2012), EPA (Parameters of water quality: interpretation and standards. Environmental Protection Agency, Ireland, 2001), ICMR (Manual of Standards of Quality for Drinking Water Supplies, 2012) and WHO (Guidelines for drinking-water quality: recommendations, 2004). The arithmetic weightage-based Water Quality Index (WQI) was also computed to evaluate the pollution status of the canal. The results reveal that the UGC water is not suitable for human drinking as the physicochemical parameters and toxic trace metals exceeded the permissible limits of the standards considered, at numerous sites. The parameters also possessed strong seasonal variation in concentration. The overall water quality index was beyond the permissible limits of human drinking at all the sites throughout all the seasons. Therefore, the water samples of the UGC are polluted and unfit for human drinking purpose. The exorbitant concentration of these parameters may be attributed to disposal of industrial effluents, domestic sewages and other human activities.
@incollection{bahita2021water, title = {Water quality assessment of Upper Ganga canal for human drinking}, author = {Bahita, Tesfamariam Abreha and Swain, Sabyasachi and Dayal, Deen and Jha, Pradeep K and Pandey, Ashish}, booktitle = {Climate Impacts on Water Resources in India}, pages = {371--392}, year = {2021}, doi = {10.1007/978-3-030-51427-3_28}, publisher = {Springer} } - Swain, S., Mishra, S. K., Pandey, A., & Dayal, D. (2021). Identification of meteorological extreme years over central division of Odisha using an index-based approach. In Hydrological Extremes (pp. 161–174). Springer. https://doi.org/10.1007/978-3-030-59148-9_12
It is well known that the precipitation is the key factor for occurrence of hydro-meteorological extremes like droughts or floods. These extremes have enormous impacts over agricultural sector, especially in India. This paper aims to identify the meteorological extreme years (both dry and wet) over Central Division (Odisha), India. The historical precipitation data for 113 years (1901–2013) is considered for 11 constituent administrative districts of the division. Only the monsoon season is considered in this study as the season contributes a vast majority of the annual precipitation over the study area. The percent departure from mean precipitation (PDM) is employed to identify the drought (dry) and flood (wet) years, and their properties (i.e., maximum intensity, maximum continuity and return period). It is found from the results that the study area has undergone both drought and flood years frequently. However, the frequency of high-severity wet years is higher than that of dry years. The maximum continuity of a single drought event or a single flood event varies from 2 to 5 years over the districts. The return period of a meteorological extreme year (either drought or flood) varies from over 2 years to less than 5 years over different districts, whereas the maximum continuity varies from 3 to 6 years. This study will be helpful to develop proper coping strategies to minimize the ill effects of the meteorological extremes.
@incollection{swain2021identification, title = {Identification of meteorological extreme years over central division of Odisha using an index-based approach}, author = {Swain, Sabyasachi and Mishra, SK and Pandey, Ashish and Dayal, Deen}, booktitle = {Hydrological Extremes}, pages = {161--174}, year = {2021}, doi = {10.1007/978-3-030-59148-9_12}, publisher = {Springer} } - Swain, S., Mishra, S. K., & Pandey, A. (2021). Assessing contributions of intensity-based rainfall classes to annual rainfall and wet days over Tehri Catchment, India. In Advances in Water Resources and Transportation Engineering (pp. 113–121). Springer. https://doi.org/10.1007/978-981-16-1303-6_9
Rainfall variability has gained significant attention from the global research community, especially after the rising issues of climate change. In the present study, an assessment of the contributions of intensity-based rainfall classes (very low, low, medium, rather heavy, and heavy) to average annual rainfall as well as to the number of wet days over Tehri catchment, Uttarakhand, India, is presented. It is pertinent to mention that the very low rainfall class is not considered among wet days and hence is analyzed only for contributions to annual rainfall and not for contributions to the number of wet days. The daily rainfall data is collected for 119 years (1901–2019) from the IMD 0.25° × 0.25° grids, whose at least 25% fell within the boundary of the catchment. Fifteen grids are selected based on the above-mentioned criteria, and the period of 1901–2019 is divided into two parts, i.e., pre-1960 and post-1960 periods for a comparative assessment. The results reveal that the medium rainfall class contributes a majority of annual rainfall followed by light rainfall, rather heavy, heavy, and very low rainfall classes. Similarly, for wet days, medium (50%) and light (45%) classes are the major contributors followed by rather heavy (4%) and heavy (1%) classes. Regarding these contributions, no significant difference is observed between pre-1960 and post-1960 periods.
@incollection{swain2021assessing, title = {Assessing contributions of intensity-based rainfall classes to annual rainfall and wet days over Tehri Catchment, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, booktitle = {Advances in Water Resources and Transportation Engineering}, pages = {113--121}, year = {2021}, doi = {10.1007/978-981-16-1303-6_9}, publisher = {Springer} } - Nandi, S., & Janga Reddy, M. (2021). Parameter Estimation of a Macroscale Hydrological Model Using an Adaptive Differential Evolution. In Water Management and Water Governance (pp. 243–255). Springer, Cham. https://doi.org/10.1007/978-3-030-58051-3_17
To overcome the drawbacks faced by the traditional manual calibration of hydrological models, this study employs an adaptive differential evolution (DE) algorithm for automatic calibration of Variable Infiltration Capacity (VIC) hydrological model. In the DE algorithm, proper tuning of its control parameters is laborious and generally needs a great amount of time and resources. Therefore, a self-adaptive scheme is presented to enhance the efficacy of the basic DE. The proposed automatic parameter estimation scheme is applied for a case study and evaluated its performance using standard performance measures of coefficient of correlation (R2), Nash–Sutcliffe coefficient (NSE), percent bias (PBIAS), and index of agreement (IoA). The findings from the study revealed that the adaptive DE was successful to optimize the unknown parameters of the VIC model accurately, which signified that the automatic calibration scheme is a credible alternative to the manual approach.
@incollection{nandi2021parameter, title = {Parameter Estimation of a Macroscale Hydrological Model Using an Adaptive Differential Evolution}, author = {Nandi, Saswata and Janga Reddy, Manne}, booktitle = {Water Management and Water Governance}, pages = {243--255}, year = {2021}, doi = {10.1007/978-3-030-58051-3_17}, publisher = {Springer, Cham} } - Nandi, S., & Reddy, M. J. (2021). Multiobjective Automatic Calibration of a Physically Based Hydrologic Model Using Multiobjective Self-Adaptive Differential Evolution Algorithm. In Climate Change Impacts on Water Resources (pp. 435–448). Springer, Cham. https://doi.org/10.1007/978-3-030-64202-0_37
The physically based hydrological models require the estimation of various model parameters through calibration. Several past studies that focused on parameter estimation of hydrological models have found that no single objective performance criterion is adequate for matching different essential characteristics of the observation data. Since physically based hydrological models simulate many of the catchment hydrological processes, it needs to define multiple performance criteria to effectively use the information from various datasets and application of multiobjective optimization for attaining Pareto optimal solutions. In the present study, a Multiobjective Self-adaptive Differential Evolution algorithm (MOSaDE) is applied to perform multiobjective calibration of hydrological models. MOSaDE is an advancement of well-known Differential Evolution (DE) algorithm, using the notion of Pareto dominance, fast nondominated sorting approach, diversity preservation using crowding distance and elitist strategy of joining parent and offspring population. The parameter self-adaptation strategy in the MOSaDE also increases the robustness of the algorithm and alleviate the needs of computationally demanding sensitivity analysis of the algorithm parameters. The methodology is verified for calibration of Variable Infiltration Capacity (VIC) model, which is a popular physically based hydrological model, for a case study in Krishna basin, in India and the results are found to be promising.
@incollection{nandi2021multiobjective, title = {Multiobjective Automatic Calibration of a Physically Based Hydrologic Model Using Multiobjective Self-Adaptive Differential Evolution Algorithm}, author = {Nandi, Saswata and Reddy, M Janga}, booktitle = {Climate Change Impacts on Water Resources}, pages = {435--448}, year = {2021}, doi = {10.1007/978-3-030-64202-0_37}, publisher = {Springer, Cham} }
2020
- Sharma, I., Mishra, S. K., Pandey, A., Kumre, S. K., & Swain, S. (2020). Determination and verification of antecedent soil moisture using soil conservation service curve number method under various land uses by employing the data of small indian experimental farms. In Watershed Management 2020 (pp. 141–150). American Society of Civil Engineers Reston, VA. https://doi.org/10.1061/9780784483060.013
Antecedent soil moisture (ASM) is one of the most important factors affecting the rainfall-runoff modelling process. Its existence and influence in computing runoff using soil conservation service curve number (SCS-CN) method have been a point of discussion for many decades. In this study, a novel procedure has been proposed to calculate the ASM by modifying the SCS-CN method and verify its applicability by comparing the computed ASM with the observed soil moisture. Natural rainfall, runoff, and soil moisture data from eight small experimental farms with different land-use viz. sugarcane, maize, black gram, and fallow land, located at Roorkee, India, have been utilized. The ASM is computed by optimizing two parameters, i.e., absolute maximum potential retention (Sabs) and initial abstraction coefficient (λ), and the optimization is carried out by minimizing root mean square error (RMSE). Results show that there exists a good correlation between observed and computed ASM for sugarcane, black gram, and maize with maize showing the highest correlation (R2> 0.6). Fallow land shows the least correlation (R2 of 0.32), which may be due to the inadequacy of data. This study will be helpful in calculating ASM for ungauged catchments having different land use and will further broaden the applications of SCS-CN method.
@incollection{sharma2020determination, title = {Determination and verification of antecedent soil moisture using soil conservation service curve number method under various land uses by employing the data of small indian experimental farms}, author = {Sharma, Ishan and Mishra, Surendra Kumar and Pandey, Ashish and Kumre, Shailendra K and Swain, Sabyasachi}, booktitle = {Watershed Management 2020}, pages = {141--150}, year = {2020}, doi = {10.1061/9780784483060.013}, publisher = {American Society of Civil Engineers Reston, VA} }
2018
- Swain, S., Nandi, S., & Patel, P. (2018). Development of an ARIMA model for monthly rainfall forecasting over Khordha district, Odisha, India. In Recent Findings in Intelligent Computing Techniques (pp. 325–331). Springer. https://doi.org/10.1007/978-981-10-8636-6_34
The assessment of climate change, especially in terms of rainfall variability, is of giant concern all over the world at present. Contemplating the high spatiotemporal variation in rainfall distribution, the prior estimation of precipitation is necessary at finer scales too. This study aims to develop an ARIMA model for prediction of monthly rainfall over Khordha district, Odisha, India. Due to the unavailability of recent rainfall data, monthly rainfall records were collected for 1901–2002. The rainfall during 1901–82 was used to train the model and that of 1983–2002 was used for testing and validation purposes. The model selection was made using Akaike information criterion (AIC) and Bayesian information criterion (BIC), and ARIMA (1, 2, 1) (1, 0, 1)12 was found to be the best fit model. The efficiency was evaluated by Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2). The model forecasts produced an excellent match with observed monthly rainfall data. The outstanding accuracy of the model for predicting monthly rainfall for such a long duration of 20 years justifies its future application over the study region, thereby aiding to a better planning and management.
@incollection{swain2018development, title = {{Development of an ARIMA model for monthly rainfall forecasting over Khordha district, Odisha, India}}, author = {Swain, S and Nandi, S and Patel, P}, year = {2018}, booktitle = {{Recent Findings in Intelligent Computing Techniques}}, publisher = {Springer}, doi = {10.1007/978-981-10-8636-6_34}, pages = {325--331} } - Swain, S., Verma, M. K., & Verma, M. K. (2018). Streamflow estimation using SWAT model over Seonath river basin, Chhattisgarh, India. In Hydrologic modeling (pp. 659–665). Springer. https://doi.org/10.1007/978-981-10-5801-1_45
Water availability is one of the major issues that need attention from the present generation across the whole world to attain sustainability. Spatial variation of water resources and further climatic changes are main reasons for extremes such as droughts and floods. This urges for the quantification and forecasting of availability of the basic need of life. At the river basin level, streamflow is considered as the most crucial parameter to assess water availability, which can be estimated by simulation or modelling approaches. This article presents about the hydrological modelling using a semi-distributed model, namely soil and water assessment tool (SWAT), applied to Seonath river basin, Chhattisgarh, India. The climate forecasting system reanalysis (CFSR) meteorological data for the period of 1979–2014 (35 years) is used and the runoff is generated, which is calibrated using the observed flow at the basin outlet. The results reveal the observed flow and modelled flow to be very poorly correlated. The major causes of such mismatch are identified, and possible improvement options are discussed.
@incollection{swain2018streamflow, title = {Streamflow estimation using SWAT model over Seonath river basin, Chhattisgarh, India}, author = {Swain, Sabyasachi and Verma, Mani Kant and Verma, MK}, booktitle = {Hydrologic modeling}, pages = {659--665}, year = {2018}, doi = {10.1007/978-981-10-5801-1_45}, publisher = {Springer} }
Conference Articles
2022
- Chen, S., Patel, P., Dipankar, A., Roth, M., & Moise, A. (2022). The Impact of Urban-scale Grid on the Representation of the Urban Convective Boundary Layer Over Singapore. Asia Oceania Geosciences Society, AS08–A018.
@inproceedings{aogs2022, title = {{The Impact of Urban-scale Grid on the Representation of the Urban Convective Boundary Layer Over Singapore}}, author = {Chen, S. and Patel, Pratiman and Dipankar, A. and Roth, M. and Moise, A.}, year = {2022}, booktitle = {{Asia Oceania Geosciences Society}}, pages = {AS08-A018}, organization = {AOGS} } - Patel, P., Chen, S., Dipankar, A., Roth, M., & Moise, A. (2022). 100m urban simulations over Singapore using uSINGV. International Association for Urban Climate.
@inproceedings{iauc2022_1, title = {{100m urban simulations over Singapore using uSINGV}}, author = {Patel, Pratiman and Chen, S. and Dipankar, A. and Roth, M. and Moise, A.}, year = {2022}, booktitle = {{International Association for Urban Climate}}, organization = {IAUC} } - Aliaga, D. G., He, L., Patel, P., & Nigoyi, D. (2022). AI-Enhanced Generation of Building-Scale Features for Urban Environmental Research. International Association for Urban Climate.
@inproceedings{iauc2022_2, title = {{AI-Enhanced Generation of Building-Scale Features for Urban Environmental Research}}, author = {Aliaga, D.G. and He, L. and Patel, Pratiman and Nigoyi, D.}, year = {2022}, booktitle = {{International Association for Urban Climate}}, organization = {IAUC} }
2021
- Swain, S., Mishra, S., & Pandey, A. (2021). An Innovative Approach for Drought Characterization and Agricultural Vulnerability Analysis Under Climate Change. AGU Fall Meeting Abstracts, 2021, GC45H–0898. https://ui.adsabs.harvard.edu/abs/2021AGUFMGC45H0898S
Drought is amongst the most precarious phenomena that cause serious repercussions, especially to the agrarian economies. A detailed assessment of droughts is necessary to develop robust frameworks, particularly over a country like India, having 18% of the worlds population and 4% of global freshwater, 83% of which is used in agriculture. This study presents an innovative approach to investigate the climate change impacts on drought characteristics and agricultural vulnerability over the Narmada Basin, which is located at the core of the Indian monsoon region. The frequency, severity, and persistence of droughts considering non-stationarity in time series are investigated in three phases, i.e., 1980-2019 (historical), 2020-2059 (near-future), and 2060-2099 (far-future), using observed precipitation and CMIP6 ensembled projections. Further, a composite vulnerability index is developed at a district-scale incorporating the three dimensions of vulnerability, i.e., adaptive capacity, exposure, and sensitivity. The results reveal a significant increase in the frequency and severity of droughts in 2060-2099 with more frequent multi-year droughts as compared to the historical phase, specifically due to the frequently flickering rainfall coupled with the temperature rise. The frequency of a severe or extreme drought is once in 3 to 6 years over different districts in the far-future scenario. The vulnerability analysis reveals 73% of the basin area under high to very high agriculturally vulnerable zones, which is likely to worsen in the future. The variabilities of the vulnerability dimensions at the sub-regional level emphasize the district-wise policy-framing to combat the pernicious effects of droughts on agriculture. Moreover, the information reported in this study will be a step forward to help to fulfill the sustainable development goals in the agriculture-dominated regions in general and the Narmada Basin in particular.
@inproceedings{swain2021innovative, title = {An Innovative Approach for Drought Characterization and Agricultural Vulnerability Analysis Under Climate Change}, author = {Swain, Sabyasachi and Mishra, Surendra and Pandey, Ashish}, booktitle = {AGU Fall Meeting Abstracts}, volume = {2021}, pages = {GC45H--0898}, url = {https://ui.adsabs.harvard.edu/abs/2021AGUFMGC45H0898S}, year = {2021} } - Nandi, S., & Reddy, M. J. (2021). Parameter Estimation of VIC-RAPID Hydrological Model Using Self-adaptive Differential Evolution Algorithm. Proceedings of International Conference on Scientific and Natural Computing, 137–146. https://doi.org/10.1007/978-981-16-1528-3_12
Physically based distributed hydrological models are an invaluable tool for planning and management of water resource projects. However, a reliable prediction from hydrological models can only be expected if their unknown model parameters are estimated accurately. In place of laborious manual calibration of the parameters of the hydrological model, this study presents an automatic calibration scheme for the VIC-RAPID hydrological model using the self-adaptive differential evolution (SaDE) algorithm. The SaDE eliminates the laborious manual tuning of the two control parameters (mutation factor and crossover rate) of the conventional DE algorithm. The proposed approach is demonstrated with a case study in the upper Krishna river sub-basin for estimation of the 15 VIC-RAPID model parameters. The efficacy of the proposed calibration technique for hourly streamflow simulation is evaluated by using standard performance measures such as Nash-Sutcliffe Coefficient (NSE), Coefficient of Correlation (R2), and Percent Bias (PBIAS). Results from this study revealed the potential of SaDE for the parameter estimation of complex hydrological models.
@inproceedings{nandi2021parametes, title = {Parameter Estimation of VIC-RAPID Hydrological Model Using Self-adaptive Differential Evolution Algorithm}, author = {Nandi, Saswata and Reddy, Manne Janga}, booktitle = {Proceedings of International Conference on Scientific and Natural Computing}, pages = {137--146}, year = {2021}, doi = {10.1007/978-981-16-1528-3_12}, organization = {Springer, Singapore} }
2020
- Jamshidi, S., Nayak, H. P., Patel, P., Cammarano, D., & Niyogi, D. (2020). Assessment of Agricultural Feedbacks in Noah-MP-Crop Land Surface Model Under Drought Condition. AGU Fall Meeting Abstracts, 2020, H201–07. https://ui.adsabs.harvard.edu/abs/2020AGUFMH201...07J
@inproceedings{jamshidi2020assessment, title = {{Assessment of Agricultural Feedbacks in Noah-MP-Crop Land Surface Model Under Drought Condition}}, author = {Jamshidi, Sajad and Nayak, Hara Prasad and Patel, Pratiman and Cammarano, Davide and Niyogi, Dev}, year = {2020}, booktitle = {{AGU Fall Meeting Abstracts}}, volume = {2020}, url = {https://ui.adsabs.harvard.edu/abs/2020AGUFMH201...07J}, pages = {H201--07} } - Chakravarty, K., Mohmmad, J., Hosalikar, K. S., Pandithurai, G., Patel, P., Niyogi, D., & others. (2020). Cloud Morphology and Microphysics of Precipitation Events during Interseasonal Phases of Monsoon over Mumbai, India. 100th American Meteorological Society Annual Meeting. https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/370635
Mumbai city situated on the west coast of Indian subcontinent is considered to be one of the most populous city of the world. The city typically experiences heavy rainfall spells during the pre-monsoon and monsoon periods from the cloud systems originating over the eastern and western part of the region respectively. In this study, the vertical structure of clouds and microphysical characteristics of precipitation during the pre-monsoon and monsoon period for 2018 are studied over Mumbai. As per the report of India Meteorological Department (IMD) of 2018, the onset date of monsoon over Mumbai is June 09, 2018. As such, the period from March 01 – June 08 are considered to be pre-monsoon period whereas June 09- September 30 are considered to be the monsoon months. A Joss-Waldvogel Disdrometer was set up at IMD campus in Santacruz (Western Mumbai). These measurements were considered with the reflectivity data from S-band Doppler Weather Radar placed at Colaba in southern Mumbai. The wind direction and corresponding rainfall observation over Santacruz shows that Mumbai receives rain primarily from easterly winds during the pre-monsoon time which then shifts to the south-westerly winds during the monsoon period. There is an interesting difference in characteristics found for the pre-monsoon and monsoon rainfall. In particular, a distinct diurnal variation with three peaks was noted for the pre-monsoon period. The dominance of urban convective environment in the pre-monsoon period and the impact of moisture supply from the marine sources over the city during the monsoon months are considered to be contributing factors for the contrasting diurnal pattern of rainfall for these inter-seasonal phases of monsoon. The corresponding vertical profile of radar reflectivity also shows that the rainfall peaks are complimented with clouds and hydrometeors yielding higher reflectivity during pre-monsoon season. The above observations has been portrayed in Fig. 1 which shows the diurnal variation of rainfall, raindrop size distribution, vertical profile of radar reflectivity and the occurrences of lightning over Santacruz during the pre-monsoon and monsoon period. The figure clearly signifies that the mentioned three peaks of rainfall during the pre-monsoon period are associated with the larger raindrop - the highest being in the range of 1- 4.5 mm during 20:00 - 22:00 hrs. The lightning scenario around 50 km centering the region of study also complemented the above observations with their strong presence during 18:00 -22:00 hrs. All these features clearly signifies that the strong convective environment persists over Mumbai during the pre-monsoon months while such distinct features of clouds and precipitation are not visible for the monsoon period. The microphysical characteristics of rainfall shows, raindrops of larger diameter dominate the total pre-monsoon months in comparison to the monsoon period. The role of urban convection appears to be an important contributor for a relatively higher localized CAPE and convective rainfall dominance (48% in pre-monsoon versus 23% in monsoon). These higher CAPE provide a conductive environment for more vigorous updraft-downdraft leading to smaller drops aloft and larger drops to precipitate locally. A detailed case study of two similar rainfall events during the contrasting inter-seasonal period has been undertaken and will be presented.
@inproceedings{chakravarty2020cloud, title = {{Cloud Morphology and Microphysics of Precipitation Events during Interseasonal Phases of Monsoon over Mumbai, India}}, author = {Chakravarty, Kaustav and Mohmmad, J and Hosalikar, KS and Pandithurai, G and Patel, P and Niyogi, Dev and others}, year = {2020}, booktitle = {{100th American Meteorological Society Annual Meeting}}, url = {https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/370635}, organization = {AMS} } - Swain, S., Mishra, S. K., & Pandey, A. (2020). Assessment of droughts and their linkage to environmental flow conditions over a large Indian river basin. EGU General Assembly Conference Abstracts, 1048. https://ui.adsabs.harvard.edu/abs/2020EGUGA..22.1048S
A robust characterization and risk assessment of meteorological droughts is the need of the hour considering its pervasiveness and consequences; however, their precise physical quantification is a difficult geophysical endeavor. This becomes a serious issue for India, having 18% of the world’s population and 4% of global freshwater, out of which 83% is used in agriculture. In this study, a detailed spatiotemporal assessment of the meteorological droughts characterized by standardized precipitation index (SPI) at annual scale is carried out over the Narmada Basin, India using the monthly rainfall data from 24 stations for 63 years (1951- 2013). The entire duration was divided into two epochs of 31 years (i.e. 1951-1981 and 1982-2012) for a comparative assessment of drought characteristics. The non- parametric Mann- Kendall (MK) test is applied to investigate the trend of droughts. Further, to predict the environmental Flow (EF) conditions from rainfall data only, the linkage of SPI with the average annual flow (%AAF) is examined over four sub-catchments (Mohegaon, Hridaynagar, Manot, and Sher) of the basin. The results reveal that the Narmada basin is prone to droughts with a frequency of once in 3 to 5 years. The frequency and severity of droughts have significantly increased in 1982-2012 as compared to 1951-1981. The severity of recent droughts shows a more widespread aerial extent in the region. The MK test results indicate an increasing trend in the droughts over most of the stations. An exquisite agreement between SPI and %AAF (used to describe the EF condition) is observed with R2 ranging from 0.757 to 0.988, which shows that coupling SPI with %AAF can be effective for ungauged catchments. This study suggests that appropriate measures must be taken for better management of the water resources in the basin, and also for mitigation droughts, considering the increased risk of the severe drought events in recent decades.
@inproceedings{swain2020assessment, title = {Assessment of droughts and their linkage to environmental flow conditions over a large Indian river basin}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, booktitle = {EGU General Assembly Conference Abstracts}, pages = {1048}, url = {https://ui.adsabs.harvard.edu/abs/2020EGUGA..22.1048S}, year = {2020} } - Swain, S., Sharma, I., Mishra, S. K., Pandey, A., Amrit, K., & Nikam, V. (2020). A framework for managing irrigation water requirements under climatic uncertainties over Beed district, Maharashtra, India. World Environmental and Water Resources Congress 2020: Water Resources Planning and Management and Irrigation and Drainage, 1–8. https://doi.org/10.1061/9780784482957.001
The “water use efficiency” has become a familiar term amongst the researchers and policy makers around the globe. Water use efficiency is of paramount concern for India, as majority of population and land use are dedicated to agriculture. This paper presents a framework for assessing the water demand and irrigation requirements over Beed District (Maharashtra, India), which is notorious for frequent droughts and a very high number of farmer suicides. In this study, standardized precipitation index (SPI) was used to characterize the historical droughts over the district using the long-term rainfall records. Remotely sensed land use maps were obtained and detailed classification was carried out. Additionally, the crop water requirement over the area was estimated by CropWat 8.0 model. From the ground truth verification, it was concluded that the framework is fairly capable in estimating the agricultural water demand over the district. The results were validated for the year 1972, when the district faced a severe water deficit condition. The irrigation network in Maharashtra is ineffectual despite of having highest number of dams in the country. The proposed framework will help to boost the efficiency of agricultural water use and thus, effective planning and management of available water.
@inproceedings{swain2020framework, title = {A framework for managing irrigation water requirements under climatic uncertainties over Beed district, Maharashtra, India}, author = {Swain, Sabyasachi and Sharma, Ishan and Mishra, Surendra Kumar and Pandey, Ashish and Amrit, Kumar and Nikam, Vikrant}, booktitle = {World Environmental and Water Resources Congress 2020: Water Resources Planning and Management and Irrigation and Drainage}, pages = {1--8}, year = {2020}, doi = {10.1061/9780784482957.001}, organization = {American Society of Civil Engineers Reston, VA} } - Swain, S., Mishra, S. K., & Pandey, A. (2020). Assessment of meteorological droughts over Hoshangabad district, India. IOP Conference Series: Earth and Environmental Science, 491(1), 012012. https://doi.org/10.1088/1755-1315/491/1/012012
In this study, the meteorological drought characteristics (severity, frequency, and persistence) over the Hoshangabad district, Madhya Pradesh, India are analyzed. The percent departure from mean (PDM) is employed to describe the drought characteristics, considering the monthly rainfall data for the duration of 62 years (1951-2012). Rainfall during monsoon season contributes over 95% of the annual rainfall and thus, only monsoon season is considered for identifying the drought years. The entire duration of 62 years was divided into two epochs of 31 years i.e. 1951-1981 and 1982-2012. The results revealed that the rainfall over the district possesses remarkable inter-annual variability. The district is prone to droughts with a frequency of once in four years. More importantly, the comparative assessment of two epochs indicates an increase in frequency, severity, and persistence of droughts in the latter epoch. The frequency of droughts has tripled in 1982-2012 as compared to 1951-1981. Since Hoshangabad is a monsoon-dominated district with high agricultural importance, proper management strategies need to be devised to minimize the harmful consequences of droughts.
@inproceedings{swain2020assessmenu, title = {Assessment of meteorological droughts over Hoshangabad district, India}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, booktitle = {IOP conference series: earth and environmental science}, volume = {491}, number = {1}, pages = {012012}, year = {2020}, doi = {10.1088/1755-1315/491/1/012012}, organization = {IOP Publishing} }
2019
- Patel, P., Aliaga, D., Karmakar, S., Ghosh, S., & Niyogi, D. (2019). Green Roofs to mitigate the urban extreme precipitation events? An experimental study over Mumbai, India. AGU Fall Meeting Abstracts, 2019, GC21I–1370. https://ui.adsabs.harvard.edu/abs/2019AGUFMGC21I1370P
Green Roofs are one of the measures to mitigate the Urban Heat Island (UHI) effects. The cooling effects of green roofs are well studied in the literature. Green roofs can change temperatures and modify humidity. Here we postulate that the change in microenvironment due to green roofing may also have a potential to modify mesoscale convection and hence the intensity, distribution and related aspects of heavy (extreme) precipitation. We first develop and present a conceptual thought experiment as to possible pathways of mesoscale convection changes amidst green infrastructure changes. We then evaluate the postulation using the detailed urban WRF modeling system by taking the example of an extreme rainfall case that affected Mumbai city on 29 August 2017. The event while labelled ’extreme’ is typical of the heavy rain events the city has been experiencing in recent years. The event was simulated for different green roof scenarios, viz. 10%, 25%, 50%, as well as 75%, and 100% green roof over the urban area. The green roof simulations are compared with respect to ’no green roof’ simulation (control run). After this a prior green roof specification experiment, a multi-criteria Monte Carlo experiment was undertaken to assess the possible location and magnitude of green roofing that will be required to have 1, 2, and 3 deg C changes for the city. Using the resulting green roof distribution WRF results were regenerated to see whether the temperature effects are similarly obtained when using coupled analysis. Initial results suggest green roofing may further increase the intensity of heavy rainfall and this leads to an interesting question regarding what mitigation pathway should a city consider- when green infrastructure for temperature regulation may cause possibly higher flood potential.
@inproceedings{patel2019green, title = {{Green Roofs to mitigate the urban extreme precipitation events? An experimental study over Mumbai, India}}, author = {Patel, Pratiman and Aliaga, Daniel and Karmakar, Subhankar and Ghosh, Subimal and Niyogi, Dev}, year = {2019}, booktitle = {{AGU Fall Meeting Abstracts}}, volume = {2019}, url = {https://ui.adsabs.harvard.edu/abs/2019AGUFMGC21I1370P}, pages = {GC21I--1370} } - Tiwari, A., Busireddy, N. K. R., Patel, P., Merwade, V., Jamshidi, S., Marks, F., Safaee, S., & Niyogi, D. (2019). Assessing Variability in Multi-sensor Tropical Cyclone Rainfall Estimates and the Impact on Urban Flood Simulation for Hurricane Florence (2018). AGU Fall Meeting Abstracts, 2019, H31D–03. https://ui.adsabs.harvard.edu/abs/2019AGUFM.H31D..03T
Extreme rains from landfalling Tropical Cyclones (TCs) have been causing flooding, especially in the urban watersheds. The majority of prior research on cyclones has been focused on the track and wind forecasts but studies on TC rainfall are also critically needed. Taking recent landfalling Hurricane Florence (2018) that impacted the Carolinas, as a representative example, we investigate and understand the variability in different rainfall products (satellite (GPM/IMERG, TMPA/TRMM) and in-situ) under extreme rain conditions. Taking the rainfall from different sensors and products we then assess how this variability in rainfall translates into flood/inundation estimates when used as an input in hydrologic models. Rainfall error analysis using data fields from AHPS/Stage IV data, mesonet networks, GPM/IMERG, PERSIANN, TRMM/TMPA corresponding to the pre-, landfall, and post-landfall conditions has been undertaken for Hurricane Florence. The analysis obtained from the different multi satellites with the in-situ measurements showed that the high resolution GPM product is able to capture the heavy rainfall events in a reasonable manner followed by Stage IV, TRMM, and PERSIANN products. The findings are expected to be of interest to the broader community because of the need for improving predictions associated with impacts from extreme weather events. The satellite rain products are underutilized for hydrologic/hydraulic analyses and high-resolution flood modeling. The results from this study will demonstrate the value of NASA products for urban flooding using HEC models.
@inproceedings{tiwari2019assessing, title = {{Assessing Variability in Multi-sensor Tropical Cyclone Rainfall Estimates and the Impact on Urban Flood Simulation for Hurricane Florence (2018).}}, author = {Tiwari, Alka and Busireddy, Nanda Kishore Reddy and Patel, Pratiman and Merwade, Venkatesh and Jamshidi, Sajad and Marks, Frank and Safaee, Samira and Niyogi, Dev}, year = {2019}, booktitle = {{AGU Fall Meeting Abstracts}}, volume = {2019}, url = {https://ui.adsabs.harvard.edu/abs/2019AGUFM.H31D..03T}, pages = {H31D--03} } - Aadhar, S., Swain, S., & Rath, D. R. (2019). Application and performance assessment of SWAT hydrological model over Kharun river basin, Chhattisgarh, India. World Environmental and Water Resources Congress 2019: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management, 272–280. https://doi.org/10.1061/9780784482339.028
It is necessary to understand the hydrological processes undergoing at small segments in order to apprehend the complex large river systems and this can be achieved by application of hydrological models. This study aims to check the applicability of soil and water assessment tool (SWAT) model over the Kharun River Basin, Chhattisgarh, India. The limitation of data at proper scales is the major problem that hinders research on this area. The meteorological data were collected from climate forecasting system reanalysis (CFSR) database for 1994–2014. The SWAT simulations generated runoff, which was auto-calibrated with the observed values through SWAT-CUP. Generalized uncertainty likelihood estimation (GLUE) optimization approach was used for sensitivity analysis of various parameters during auto-calibration. The results reveal for a moderate correlation between the observed and modelled values at daily time scale i.e. the Nash-Sutcliffe efficiency and R2 values are close to 0.5. This highlights the fact that model application needs to be carried out carefully with processed and reliable data sets. Also, some of the popular models may as well be not suitable for few basins with multiple complexities. The possible reasons for such moderate performance of the model are also discussed. This work will be helpful to the decision makers for better planning and management of the basin.
@inproceedings{aadhar2019application, title = {Application and performance assessment of SWAT hydrological model over Kharun river basin, Chhattisgarh, India}, author = {Aadhar, Saran and Swain, S and Rath, DR}, booktitle = {World environmental and water resources congress 2019: Watershed management, irrigation and drainage, and water resources planning and management}, pages = {272--280}, year = {2019}, doi = {10.1061/9780784482339.028}, organization = {American Society of Civil Engineers Reston, VA} } - Dayal, D., Swain, S., Gautam, A. K., Palmate, S. S., Pandey, A., & Mishra, S. K. (2019). Development of ARIMA model for monthly rainfall forecasting over an Indian River Basin. World Environmental and Water Resources Congress 2019: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management, 264–271. https://doi.org/10.1061/9780784482339.027
The quantification of climate variability, especially in terms of rainfall patterns, is of vital concern all around the globe at present. Owing to the significant variation of rainfall distribution in both space and time, its precise estimation is crucial at river basin level. In this study, an autoregressive integrated moving average (ARIMA) model is developed for prediction of monthly rainfall over Betwa River Basin, India. The monthly precipitation data for 1960–2012 were obtained from the India Meteorological Department (IMD) Pune. The monthly average precipitation over the whole basin was estimated using Thiessen polygon method. The precipitation time series from 1960 to 2000 was utilized for training purposes in order to frame the most suitable model, and that of 2001 to 2012 was utilized for testing and validation purposes. The metrics viz., Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used for selecting optimum values of the parameters; and the ARIMA (0, 0, 1) (1, 1, 2)12 was established as the parsimonious model. The Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2) were used to evaluate the model efficiency. The model forecasts possessed an excellent match with the observed rainfall data (2001–2012). The outstanding accuracy of the model for predicting monthly rainfall for such a long duration of 23 years justifies its future application over the study region. This study will be helpful in developing a proper management framework for the core of Indian monsoon region.
@inproceedings{dayal2019development, title = {Development of ARIMA model for monthly rainfall forecasting over an Indian River Basin}, author = {Dayal, Deen and Swain, S and Gautam, AK and Palmate, SS and Pandey, Ashish and Mishra, Surendra Kumar}, booktitle = {World environmental and water resources congress 2019: Watershed management, irrigation and drainage, and water resources planning and management}, pages = {264--271}, year = {2019}, doi = {10.1061/9780784482339.027}, organization = {American Society of Civil Engineers Reston, VA} } - Swain, S., Dayal, D., Pandey, A., & Mishra, S. K. (2019). Trend analysis of precipitation and temperature for Bilaspur District, Chhattisgarh, India. World Environmental and Water Resources Congress 2019: Groundwater, Sustainability, Hydro-Climate/Climate Change, and Environmental Engineering, 193–204. https://doi.org/10.1061/9780784482346.020
The impact of climate variability has raised itself as a very challenging issue to the present generation. For assessing this, it is needed to quantify the climatic changes in terms of different hydro-meteorological parameters like rainfall and temperature, as they are the key factors responsible for drought-like or intense flooding situations. In this study, the temporal variability in precipitation and average temperature over a period of 102 years (1901–2002) has been investigated over Bilaspur District, Chhattisgarh, India. The statistical non-parametric Mann-Kendall test has been utilized to detect the monotonic trend whereas, Theil-Sen estimator test was applied to quantify the rate of change at monthly, seasonal (winter, pre-monsoon, monsoon, and post-monsoon), and annual scales. The results reveal for the precipitation trends to be increasing for most of the months and seasons, although they are not significant except for March, May, and pre-monsoon season. The annual rainfall over the district has increased by 10.65% during the past 102 years. The average temperature was found to be significantly decreasing for monsoon season and increasing for non-monsoon seasons. The annual average temperature has increased by 1.44% from 1901 to 2002. This study will be helpful to the local stakeholders and policy makers to encompass the climatic variability aiding to effective decision making for proper water management.
@inproceedings{swain2019trend, title = {Trend analysis of precipitation and temperature for Bilaspur District, Chhattisgarh, India}, author = {Swain, Sabyasachi and Dayal, Deen and Pandey, Ashish and Mishra, Surendra Kumar}, booktitle = {World environmental and water resources congress 2019: Groundwater, sustainability, hydro-climate/climate change, and environmental engineering}, pages = {193--204}, year = {2019}, doi = {10.1061/9780784482346.020}, organization = {American Society of Civil Engineers Reston, VA} } - Swain, S., Mishra, S. K., & Pandey, A. (2019). Spatiotemporal characterization of meteorological droughts and its linkage with environmental flow conditions. AGU Fall Meeting Abstracts, 2019, H13O–1959. https://ui.adsabs.harvard.edu/abs/2019AGUFM.H13O1959S
A robust characterization and risk assessment of droughts is need of the hour considering its pervasiveness and consequences; however, a precise physical quantification of droughts is a difficult geophysical endeavor. This becomes a serious issue for India, having 18% of world’s population and 4% of global freshwater, out of which 83% is used in agriculture. In this study, a detailed spatiotemporal assessment of the meteorological droughts characterized by standardized precipitation index (SPI), have been carried out over Narmada Basin, India for the time scales of 1, 3, 6, and 12 months, using the long-term monthly rainfall data from 28 stations for 63 years (1951-2013). The non-parametric Mann-Kendall (MK) test has been applied to investigate the trend of droughts at a 3-monthly (seasonal) scale. Further, to predict the environmental flow (EF) conditions from rainfall data only, the linkage of SPI with the average annual flow (%AAF) is examined over four sub-catchments (Mohegaon, Hridaynagar, Manot, and Sher) of the basin. The results reveal that the frequency and severity of droughts have increased over the last decades in the basin and varied between once in 3 to 5 years. The spatiotemporal analysis indicates that every drought event has its own unique characteristics, including its onset, severity, frequency, duration, area of influence and the magnitude of the losses caused by it. The severity of recent drought events shows a more widespread aerial extent in the region. The MK test results indicate an increasing trend in the seasonal droughts. An exquisite agreement between SPI and %AAF (used to describe the EF condition) is observed with R2 ranging from 0.757 to 0.988, which shows that coupling SPI with %AAF can be effective for ungauged catchments. This work will be helpful for proper planning and management of droughts over the Narmada basin.
@inproceedings{swain2019spatiotemporal, title = {Spatiotemporal characterization of meteorological droughts and its linkage with environmental flow conditions}, author = {Swain, Sabyasachi and Mishra, Surendra Kumar and Pandey, Ashish}, booktitle = {AGU fall meeting abstracts}, volume = {2019}, pages = {H13O--1959}, url = {https://ui.adsabs.harvard.edu/abs/2019AGUFM.H13O1959S}, year = {2019} }
2018
- Gusain, A., Patel, P., Ghosh, S., & Karmakar, S. (2018). Hydrologic impacts of reservoir operation on flood inundation pattern in a highly flood-prone deltaic region of Mahanadi River Basin, India. EGU General Assembly Conference Abstracts, 9717. https://ui.adsabs.harvard.edu/abs/2018EGUGA..20.9717G
The construction of dams and reservoirs on large rivers pose a myriad of serious long and short-term human implications over downstream river flows and the adjoining floodplains. Whilst such structures aid in reducing socio-economic losses caused by floodwaters, the natural river ecology (aquatic and riparian) is greatly hampered, especially the biodiversity- enriched deltaic region of the river basins. Thus, there is a need to assess the environmental impacts of dams/ reservoirs on the downstream river and floodplains during high flow conditions. Here, a case study of a highly flood-prone deltaic region in Mahanadi River Basin, India has been explored to quantify changes in monthly and seasonal streamflow simulated using Soil and Water Assessment Tool (SWAT). In our analysis, we have performed hydrological simulations at stream gauge stations located in the downstream of Hirakud dam under 2 scenarios: (1) not considering Hirakud reservoir operations; (2) considering reservoir operations in the model. The results show that a significant bias persists in the simulated streamflow in case of no reservoir scenario, leading to the poor simulation of low flows. We find that the operation of Hirakud Dam is responsible for the broad changes in watershed’s hydrology (in terms of runoff and streamflow) at the lower reaches of Mahanadi River. The study also shows an improvement in the simulation of extreme flows during flood season after inclusion of dam/ reservoir operation. Further, the near-future changes in streamflow under different climate change scenarios, i.e., RCP 4.5 and RCP 8.5 to the baseline period (1981-2005) are demonstrated using statistically downscaled GCM simulations. The outcomes of this study demonstrate how a reservoir operation can influence the river flows at the lower reaches and can be used to quantify impacts on the environment over space and time for devising and evaluating alternative basin management strategies in future.
@inproceedings{gusain2018hydrologic, title = {{Hydrologic impacts of reservoir operation on flood inundation pattern in a highly flood-prone deltaic region of Mahanadi River Basin, India}}, author = {Gusain, Aditya and Patel, Pratiman and Ghosh, Subimal and Karmakar, Subhankar}, year = {2018}, booktitle = {{EGU General Assembly Conference Abstracts}}, url = {https://ui.adsabs.harvard.edu/abs/2018EGUGA..20.9717G}, pages = {9717} } - Patel, P., Karmakar, S., Ghosh, S., & Niyogi, D. (2018). Performance evaluation of WRF for extreme precipitation events by integrating WUDAPT. EGU General Assembly Conference Abstracts, 7505. https://ui.adsabs.harvard.edu/abs/2018EGUGA..20.7505P
Increased occurrences of urban flash flood pose a major threat to the life and property of the residents, which urges for a reliable flood forecasting system. However, accurate precipitation forecast at high resolution has always been a challenge as they are substantially affected by land use/ land cover (LULC). Therefore, an attempt has been made to improve the forecast of extreme precipitation event by implementing detailed urban LULC map using Local Climate Zone (LCZ) classification system from World Urban Database and Access Portal Tools (WUDAPT). These LCZs represent specific land cover class based on urban morphology characteristics and can be used in Weather Research and Forecasting (WRF) model which also encapsulates Building Effect Parameterization (BEP) scheme. The BEP scheme considers the 3D structure of the buildings and allows complex land-atmosphere interaction for an urban area. The study is conducted for megacity Mumbai, the financial capital of India, which possesses significant heterogeneity in its building types. The LCZs are generated at 500 m grids using supervised classification and are ingested into WRF model. Two different LULC dataset i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and WUDAPT derived LCZs along with initial and boundary conditions from ERA-Interim (6 hourly) are used for two extreme events of 2014. The results show an improvement in spatial variability and reduction in overall bias when LCZ map is used instead of MODIS LULC. The LCZ map enhances high-resolution forecast from WRF by incorporating the details of building height, terrain roughness and urban fraction. In future, improved forecasts may assist in enhanced flood simulations by capturing the spatial variability.
@inproceedings{patel2018performance, title = {{Performance evaluation of WRF for extreme precipitation events by integrating WUDAPT}}, author = {Patel, Pratiman and Karmakar, Subhankar and Ghosh, Subimal and Niyogi, Dev}, year = {2018}, booktitle = {{EGU General Assembly Conference Abstracts}}, url = {https://ui.adsabs.harvard.edu/abs/2018EGUGA..20.7505P}, pages = {7505} } - Patel, P., & Karmakar, S. (2018). Analysis of Vulnerability to Water Stress at a Nationwide Scale. IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, 2910–2913. https://doi.org/10.1109/IGARSS.2018.8518262
Water stress is amongst one of the largest potential threats that will take over the world in near future. India is currently, under no such stress; however, it is expected to become moderate water scarce country by 2050. Therefore, an analysis has been performed to determine the potential zones of water stress in India. The water stress indices have been used as a tool of vulnerability analysis, which requires population data, water demands and runoff generated from hydrological model. Results indicate that western part of India is more vulnerable than the eastern part. Moreover, western part of Mad-hya Pradesh, central part of Maharashtra, eastern Karnataka and Tamil Nadu are in medium to high vulnerability zones. The results would help in identifying adaptation and mitigation strategies of the states as per their respective vulnerability zones.
@inproceedings{patel2018analysis, title = {{Analysis of Vulnerability to Water Stress at a Nationwide Scale}}, author = {Patel, Pratiman and Karmakar, Subhankar}, year = {2018}, booktitle = {{IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium}}, pages = {2910--2913}, doi = {10.1109/IGARSS.2018.8518262}, organization = {IEEE} } - Nandi, S., & Reddy, M. J. (2018). Assessing suitability of satellite rainfall data for estimation of daily streamflows of a small tropical catchment In India. IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, 5278–5281. https://doi.org/10.1109/IGARSS.2018.8517335
Reliable estimation of streamflow is crucial for developing effective water resources management strategies. However, there are several watersheds in India which are ungauged or contain inconsistent data archives for rainfall and discharge products, particularly for small watersheds at daily scale. This paper investigates the efficacy of the remote sensing rainfall products, precisely Tropical Rainfall Measuring Mission (TRMM) on daily scale over upper Tungabhadra sub-basin, a small tropical catchment in India. This precipitation dataset was corrected with in-situ rainfall data and used as a input to the physically based Variable Infiltration Capacity (VIC) hydrological model for estimation of streamflows. Streamflows generated with original TRMM rainfall data has resulted in larger difference in both the high and low streamflows when compared with observed discharge values, and resulted in high positive bias and low Nash-Sutcliffe efficiency (NSE) at the daily timescale. The corrected TRMM rainfall data enhanced this daily hydrological simulation with significant improvement in different performance indicators (i.e., NSE, bias and ‘goodness of fit’). Thus this study finds that the TRMM data products with appropriate correction can be used for estimation of daily streamflows over small watersheds.
@inproceedings{nandi2018assessing, title = {Assessing suitability of satellite rainfall data for estimation of daily streamflows of a small tropical catchment In India}, author = {Nandi, Saswata and Reddy, M Janga}, booktitle = {IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium}, pages = {5278--5281}, year = {2018}, doi = {10.1109/IGARSS.2018.8517335}, organization = {IEEE} }
2017
- Swain, S., Patel, P., & Nandi, S. (2017). Application of SPI, EDI and PNPI using MSWEP precipitation data over Marathwada, India. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 5505–5507. https://doi.org/10.1109/IGARSS.2017.8128250
Drought is a natural hazard with severe socio-economic consequences. For agro-based country like India, this may further deteriorate the circumstances, thereby urging for precise quantification. This paper is about the application of meteorological drought indices namely Standardized Precipitation Index (SPI), Effective Drought Index (EDI) and Percent Normal Precipitation Index (PNPI) over Marathwada division, Maharashtra, India. The 3-hourly (0.25° x 0.25°) gridded rainfall data is collected from Multi-Source Weighted-Ensemble Precipitation (MSWEP) product for 1979-2014 and is converted to monthly temporal scale. All the three indices give similar results in meteorological drought characterization i.e., most parts of the Marathwada division are affected by frequent moderate or severe droughts while some parts have witnessed extreme drought conditions. However, EDI reveals a majority of the study area affected by extreme droughts, although with low frequency. This study will be helpful to policy makers for effective decision making regarding drought management.
@inproceedings{swain2017application, title = {{Application of SPI, EDI and PNPI using MSWEP precipitation data over Marathwada, India}}, author = {Swain, Sabyasachi and Patel, Pratiman and Nandi, Saswata}, year = {2017}, booktitle = {{2017 IEEE International geoscience and remote sensing symposium (IGARSS)}}, pages = {5505--5507}, doi = {10.1109/IGARSS.2017.8128250}, organization = {IEEE} } - Swain, S., Patel, P., & Nandi, S. (2017). A multiple linear regression model for precipitation forecasting over Cuttack district, Odisha, India. 2017 2nd International Conference for Convergence in Technology (I2CT), 355–357. https://doi.org/10.1109/I2CT.2017.8226150
Estimation of precipitation is necessary for optimum utilization of water resources and their appropriate management. The economy of India being heavily dependent on agriculture becomes vulnerable due to lack of adequate irrigation facilities. In this paper, a multiple linear regression model has been developed to reckon annual precipitation over Cuttack district, Odisha, India. The model forecasts precipitation for a year considering annual precipitation data of its three preceding years. The model testing was performed over a century-long dataset of annual precipitation i.e. for 1904-2002. Assuming the intercept or constant of the multiple linear regression model as zero, the equation developed thereby displayed a superb result. The model predictions showed an excellent association with the observed data i.e. the coefficient of determination (R 2) and adjusted R 2 value was obtained to be 0.974 and 0.963 respectively. This reconciliation justifies the application of the developed model over the study area to forecast rainfall, thereby aiding in proper planning and management.
@inproceedings{swain2017multiple, title = {{A multiple linear regression model for precipitation forecasting over Cuttack district, Odisha, India}}, author = {Swain, S and Patel, P and Nandi, S}, year = {2017}, booktitle = {{2017 2nd international conference for convergence in technology (I2CT)}}, pages = {355--357}, doi = {10.1109/I2CT.2017.8226150}, organization = {IEEE} }
Technical Reports
2022
- Swain, S., Mishra, S., & Pandey, A. (2022). Evaluation of Meteorological Drought Characteristics under Climate Change over the Agriculture-dominated Marathwada Region, India. Copernicus Meetings. https://doi.org/10.5194/iahs2022-327
Drought is one of the most precarious phenomena associated with serious repercussions, especially over the agriculture-dominated regions. This study presents an investigation of drought characteristics over the Marathwada Region, Maharashtra, India, which is infamous for a large number of farmer suicides. The monthly rainfall data for 1951-2020 is collected from Indian Meteorological Department (IMD). Two widely used drought indices, viz., Standardized Precipitation Index (SPI) and Effective Drought Index (EDI) are employed to characterize the drought events. Moreover, droughts under future climate i.e., from 2021 to 2090, are investigated using an ensemble of different CMIP5 models for the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results revealed the Marathwada Region to be prone to droughts due to a remarkable inter-annual variability in rainfall. The droughts are predicted to become more severe, frequent, and persistent in the future. From the comparative assessment of two indices, EDI is found to be superior in capturing the onset of the droughts and hence, can be handy in drought monitoring purposes. Since Marathwada Region has a monsoon-dominated climate with high agricultural importance, the information reported in this study will help devise water management strategies to minimize the repercussions of droughts. Besides, the methodology presented will encourage its replication over different regions of the world that have been affected by climate change and its ramifications, mostly in the form of frequent droughts or lower crop yields.
@techreport{swain2022evaluation, title = {Evaluation of Meteorological Drought Characteristics under Climate Change over the Agriculture-dominated Marathwada Region, India}, author = {Swain, Sabyasachi and Mishra, Surendra and Pandey, Ashish}, year = {2022}, doi = {10.5194/iahs2022-327}, institution = {Copernicus Meetings} }