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Authors = Alen Shrestha

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25 pages, 4810 KiB  
Article
Regional Climatological Drought: An Assessment Using High-Resolution Data
by Alen Shrestha, Md Mafuzur Rahaman, Ajay Kalra, Balbhadra Thakur, Kenneth W. Lamb and Pankaj Maheshwari
Hydrology 2020, 7(2), 33; https://doi.org/10.3390/hydrology7020033 - 12 Jun 2020
Cited by 13 | Viewed by 3797
Abstract
Regional assessments of droughts are limited, and meticulous assessments over larger spatial scales are generally not substantial. Understanding drought variability on a regional scale is crucial for enhancing the resiliency and adaptive ability of water supply and distribution systems. Moreover, it can be [...] Read more.
Regional assessments of droughts are limited, and meticulous assessments over larger spatial scales are generally not substantial. Understanding drought variability on a regional scale is crucial for enhancing the resiliency and adaptive ability of water supply and distribution systems. Moreover, it can be essential for appraising the dynamics and projection of droughts based on regional climate across various spatial and temporal scales. This work focuses on drought analysis using a high-resolution dataset for three drought-prone regions of India between 1950 and 2016. This study also uses monthly values of the self-calibrating Palmer Drought Severity Index (scPDSI), incorporating Penman–Monteith approximation, which is physically based on potential evapotranspiration. Climate data are statistically downscaled and formulated to form a timeline for characterizing major drought events. The downscaled climate data hold a good statistical agreement with station data with correlation coefficients (R) ranging from 0.91 to 0.96. Drought analysis indicates and identifies several major incidences over the analysis time period considered in this work, which truly adheres to the droughts recorded in reports of various literatures for those regions. Full article
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26 pages, 8219 KiB  
Article
Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India
by Alen Shrestha, Md Mafuzur Rahaman, Ajay Kalra, Rohit Jogineedi and Pankaj Maheshwari
Forecasting 2020, 2(2), 59-84; https://doi.org/10.3390/forecast2020004 - 22 Apr 2020
Cited by 44 | Viewed by 8565
Abstract
This study forecasts and assesses drought situations in various regions of India (the Araveli region, the Bundelkhand region, and the Kansabati river basin) based on seven simulated climates in the near future (2015–2044). The self-calibrating Palmer Drought Severity Index (scPDSI) was used based [...] Read more.
This study forecasts and assesses drought situations in various regions of India (the Araveli region, the Bundelkhand region, and the Kansabati river basin) based on seven simulated climates in the near future (2015–2044). The self-calibrating Palmer Drought Severity Index (scPDSI) was used based on its fairness in identifying drought conditions that account for the temperature as well. Gridded temperature and rainfall data of spatial resolution of 1 km were used to bias correct the multi-model ensemble mean of the Global Climatic Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) project. Equidistant quantile-based mapping was adopted to remove the bias in the rainfall and temperature data, which were corrected on a monthly scale. The outcome of the forecast suggests multiple severe-to-extreme drought events of appreciable durations, mostly after the 2030s, under most climate scenarios in all the three study areas. The severe-to-extreme drought duration was found to last at least 20 to 30 months in the near future in all three study areas. A high-resolution drought index was developed and proven to be a key to assessing the drought situation. Full article
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