Abstract
Abstract Xiaolangdi Reservoir is a key control project to control the water and sediment in the lower Yellow River, and a timely and accurate grasp of the reservoir’s water storage status is essential for the function of the reservoir. This study used all available Landsat images (789 scenes) and adopted the modified normalized difference water index, enhanced vegetation index, and normalized difference vegetation index to map the surface water from 1999 to 2019 in Google Earth Engine (GEE) cloud platform. The spatiotemporal characteristics of the surface water body area changes in the Xiaolangdi Reservoir in the past 21 years are analyzed from the water body type division, area change, type conversion, and the driving force of the Xiaolangdi water body area changes was analyzed. The results showed that (1) the overall accuracy of the water body extraction method was 98.86%, and the kappa coefficient was 0.96; (2) the maximum water body area of the Xiaolangdi Reservoir varies greatly between inter-annual and intra-annual, and seasonal water body and permanent water body have uneven spatiotemporal distribution; (3) in the conversion of water body types, the increased seasonal water body area of the Xiaolangdi Reservoir from 1999 to 2019 was mainly formed by the conversion of permanent water body, and the reduced permanent water body area was mainly caused by non-water conversion; and (4) the change of the water body area of the Xiaolangdi Reservoir has a weak negative correlation with natural factors such as precipitation and temperature, and population. It is positively correlated with seven indicators such as runoff and regional gross domestic product (GDP). The findings of the research will provide necessary data support for the management and planning of soil and water resources in the Xiaolangdi Reservoir.
Highlights
Surface water refers to rivers, lakes, ponds, reservoirs, swamps, glaciers, and other water bodies that exist on the Earth’s surface
This study investigated the inter-annual and intra-annual spatial changes in the water body area in the Xiaolangdi Reservoir from 1999 to 2019 based on all available Landsat Thematic Mapper (TM), ETM+, and Operational Land Imager (OLI) images in the Google Earth Engine (GEE) platform
The overall accuracy of Xiaolangdi Reservoir’s water body extraction was 98.86%, the producer’s accuracy was 95.20%, and the Kappa coefficient was 0.96, indicating that the water body extraction results are more accurate and suitable for water body extraction in the Xiaolangdi Reservoir
Summary
Surface water refers to rivers, lakes, ponds, reservoirs, swamps, glaciers, and other water bodies that exist on the Earth’s surface. They are tremendously important water resources for agriculture, aquaculture, industrial production, and terrestrial ecosystems. Xiaolangdi Reservoir is a comprehensive water control project for flood control, ice jam prevention, sediment reduction, runoff regulation, water supply, and power generation in the lower reaches of the reservoir [1,2,4]. It has superior natural conditions and an important strategic position. And accurate acquisition of the reservoir water storage situation is essential to
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