Affiliation:
1. Department of Ocean Science, and Department of Mathematics, Center for Ocean Research in Hong Kong and Macau Hong Kong University of Science and Technology Hong Kong China
2. Earth, Ocean and Atmospheric Sciences Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou China
Abstract
AbstractTo advance understanding of the spatiotemporal variability of the streamflow in the Pearl River Basin (PRB), we used the Soil and Water Assessment Tool model to simulate the water fluxes from 2010 to 2020 and to identify the underlying controlling mechanisms. The streamflow in the PRB is highly variable and controlled by complex land surface processes and atmospheric impacts over the heterogeneous terrain. Two key factors primarily govern the streamflow: (1) the location of the active precipitation zone, which is determined by the interaction between the monsoon path and uplifting effect of the terrain, and (2) the redistributions resulting from land use and soil characteristics. We observe distinct patterns in the different water fluxes across the different regions. Specifically, surface flow exhibits the highest activity within the precipitation zone. Lateral flow and actual evapotranspiration (AET) have the greatest intensity in the forests and in agricultural regions, respectively, and the aquifer flow is more active in areas with coarse soil textures. The land surface processes of the AET and aquifer retention significantly govern the temporal variability of the streamflow, contributing to the precipitation and streamflow being out of phase in the PRB. Based on the underlying mechanisms driving streamflow variability, we classify the PRB into three substreams: a drought‐prone upstream, a hydrologically active midstream, and a typhoon‐affected downstream, and each substream exhibits distinct spatiotemporal characteristics of streamflow. We find that the time series and probability distributions of the streamflow at different tributaries within each substream are similar. Each probability distribution is multimodal and can be decomposed into three unimodal distributions representing dry, transitional, and wet conditions. Specifically, the PRB features a large and steep dry mode, a flat transitional mode, and a short wet mode.
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