Using Sentinel 1A (SAR) and Sentinel 2 Data for Assessing Water Spread Dynamics and Crop Diversification in Lower Palar Sub Basin, Tamil Nadu, India

Abstract

Sentinel-1A Synthetic Aperture Radar (SAR) satellite is highly beneficial for continuously monitoring the evaluating changes in agricultural areas and water spread area assessment. Having reliable information about water availability is crucial for effective regional planning. By analyzing water spread dynamics using SAR satellite data at the tank level, farmers can access more accurate and timely information, aiding in crop planning locally and regionally and improving water management practices. Utilizing SAR satellite data to track water spread is essential for addressing these challenges and enhancing agricultural productivity. This approach allows stakeholders to make better decisions about water resource allocation, promoting sustainable agriculture and water conservation. This study focused on the water spread area in Lower Palar tanks by analyzing multi-temporal Sentinel-1A SAR data, linking it to rainfall and cropping pattern changes in and around the command areas. The years 2020-2023 showed increased water spread compared to 2018-2019, suggesting improved rainfall distribution and potential for year-round cropping using Northeast monsoon rainfall for subsequent seasons. The study applied Random Forest machine learning for crop classification across seasons using Sentinel-2 optical datasets, leveraging the algorithm's accuracy and efficient handling of large datasets to understand how water availability affects crop diversification in the Lower Palar Sub-Basin. The crop diversification confirmed through diversity index. The SID value of 0.59 was obtained in the Summer 2018, due to the even distribution of (n) number of crops like paddy, groundnut, sugarcane and watermelon. The lowest SID value (0.21) was observed in Rabi 2021 due to higher water spread and the adoption of mono cropping in larger areas.