Mapping Spatio-Temporal dynamics of irrigated agriculture in Nepal using MODIS NDVI and statistical data with Google Earth Engine: A step towards improved irrigation planning

Abstract

The importance of water resources in supporting food production is ever increasing, especially in the face of climate change, urbanization and population growth. This study aims to map and analyze the spatio-temporal dynamics of irrigated agricultural areas to support improved planning of irrigation water and irrigation sector in Nepal. Using the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) employing Google Earth Engine (GEE) platform, this study classifies and analyzes change in irrigated and rainfed areas over the past two decades. NDVI time series analysis across different physiographic regions uncovered two cropping cycles annually in the Terai and Siwalik regions. In contrast, predominantly a single cropping cycle was observed in the Middle and High Mountain regions. The k-means clustering algorithm was applied to NDVI time series within the agriculture land use database of the International Centre for Integrated Mountain Development (ICIMOD) for Nepal. The obtained irrigated areas distribution were also analyzed across different provinces of Nepal as provinces are the main functional administrative divisions after federal level that are responsible for irrigation development. The produced irrigation areas distribution showed reasonable accuracy as compared to the statistical irrigation areas database of the Department of Water Resources and Irrigation (DWRI), Nepal. The results showed that, on average, approximately 60% (2.18 million hectares) of agricultural land was irrigated annually over the past decade. The findings will provide valuable insights for sustainable irrigation and water resource management, crop productivity enhancement, and strategy formulation to ensure food and water security in Nepal.