Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India

Alen Shrestha, Md Mafuzur Rahaman, Ajay Kalra, Rohit Jogineedi and Pankaj Maheshwari
Additional contact information
Alen Shrestha: Department of Civil and Environmental Engineering, Southern Illinois University, 1230 Lincoln Drive, Carbondale, IL 62901-6603, USA
Md Mafuzur Rahaman: AECOM, 2380 McGee St Suite 200, Kansas City, MO 64108, USA
Ajay Kalra: Department of Civil and Environmental Engineering, Southern Illinois University, 1230 Lincoln Drive, Carbondale, IL 62901-6603, USA
Rohit Jogineedi: Department of Mechanical Engineering and Energy Processes, Southern Illinois University, 1230 Lincoln Drive, Carbondale, IL 62901-6603, USA
Pankaj Maheshwari: Louis Berger U.S.; Inc.; A WSP Company, 300 S. 4th Street, Suite 1200, Las Vegas, NV 89101, USA

Forecasting, 2020, vol. 2, issue 2, 1-26

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 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.

Keywords: drought index; bias correction; CMIP6; scPDSI; precipitation; temperature; forecast (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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