A RESEARCH INVESTIGATION IN CHINA'S HEIHE RIVER BASIN USING QUANTITATIVE REMOTE SENSING TO EXAMINE ECOHYDROLOGY IN WATER-SCARCE ENVIRONMENTS.

Abstract

As one of the most prominent interior river systems in semi-arid and dry areas, the Heihe River Basin (HRB) in northwest China provides a considerable basis for ecohydrological study. Rapid economic development, heavy agricultural use, and climate change have all put a strain on the basin's already-scarce water supplies in recent decades. By using quantitative remote sensing techniques to investigate ecohydrological dynamics in the water-deficient HRB, this study aims to further the understanding of the relationships between vegetation and water, the distribution of surface water, and the mechanisms that recharge groundwater. Data from many satellite sources, such as Sentinel, MODIS, and Landsat, is used to derive important metrics such as evapotranspiration, vegetation indices, land surface temperature, and soil moisture. When combined with hydrological models and field observations, these datasets allow for the quantitative evaluation of water flows and biological reactions to various hydrological conditions. The findings demonstrate distinct spatial and temporal patterns in plant growth, highlighting the reliance of downstream oasis regions on regulated water delivery from upstream sources. Quantitative studies show that groundwater is more crucial for riparian ecosystem support during droughts when surface water supplies are limited. Remote sensing provides further evidence of how climatic variables and human water use impact plant dynamics, highlighting the importance of using balanced water management strategies. To augment traditional field surveys with precise, large-scale data, ecohydrological research grounded on remote sensing can be useful in regions with sparse monitoring networks. This research contributes to the understanding of ecohydrology in arid basins and demonstrates the usefulness of quantitative remote sensing for interdisciplinary water resource management decision-support.