Assessment of the Water Level Changes Based on Optical Satellite Images Analysis

Abstract. The combination of Geographic Information Systems (GIS) and Remote Sensing (RS) technologies has drastically increased the efficiency of mapping and evaluating changes in water bodies. Surface water areas confront significant challenges due to changing environmental conditions and declining water levels, which are further aggravated by human activities and climate change. The decreasing water surface area of Lake Hamrin, one of the largest lakes in Diyala Province, Iraq, is a major issue locally and regionally. This study examines changes in Land Use and Land Cover (LULC), lake area, water-holding capacity, and levels using ESA Sentinel-2 imagery and a deep-learning AI land classification model. The categorical change detection method was applied to the classified LULC maps to detect the changes in the lake area over five years. The extracted changes depending on time series datasets from 2018 to 2022 were quantified and analysed by developing a new strategy. The results showed changes in Lake Hamrin by 1.88% in 2018, 35.9% in 2019, 25.8% in 2020, 81.17% in 2021, and 84.58% in 2022. Comparing the lake's change values with the actual measured values yielded an overall accuracy of around 94.85%, indicating the promise of our enhanced change detection technique. The findings of this research can help promote sustainable water management techniques in the area and provide insightful information about the dynamics of Lake Hamrin. Also, our study will help the area's sustainable water management techniques.