Comprehensive drought risk assessment over the central plain zone of Uttar Pradesh using machine learning approach
Vikas Kumar Singh, Shivam, Mo Akram, Sarvda Nand Tiwari, Ankit, Vipin Kumar Roshan, Akanksha Mathur, Khwahiz Ali and Sakshi Dixit
This study aimed to assess patterns of drought vulnerability over the central plain zone of Uttar Pradesh, India, using the Standardized Precipitation-Evapotranspiration Index (SPEI). The analysis was conducted for the period of 1981-2020 to identify regions within the central plain zone that exhibit high drought vulnerability. The SPEI analysis revealed the central plain zone was the most susceptible to drought conditions. The data indicates that there were multiple periods of severe drought, with SPEI values below -2, signifying severe drought conditions, in 1987, 1991, 2006, and 2015. Number of years had positive SPEI readings, including 1981, 1985, 1990, 1994, and 1996, indicating times of high precipitation and ideal moisture levels. Machine Learning Regression has developed a comprehensive drought risk assessment model. The values of R2, RSME and MAE for training and testing set are 0.9917, 0.0898 & 0.0676 and 0.9744, 0.2068 & 0.1368, respectively.
Vikas Kumar Singh, Shivam, Mo Akram, Sarvda Nand Tiwari, Ankit, Vipin Kumar Roshan, Akanksha Mathur, Khwahiz Ali, Sakshi Dixit. Comprehensive drought risk assessment over the central plain zone of Uttar Pradesh using machine learning approach. Int J Res Agron 2024;7(6S):387-392. DOI: 10.33545/2618060X.2024.v7.i6Sf.882
