Response of Variation of Water and Sediment to Landscape Pattern in the Dapoling Watershed

文献类型： 外文期刊

第一作者： Wei, Chong

作者： Wei, Chong;Zhang, Zhiqiang;Cao, Lianhai;Wei, Yichang;Zhao, Rongqin;Xiao, Liangang;Wu, Qing;Wang, Zhiguo;Zhang, Xiangning

作者机构：

关键词： watershed modeling; hydrological model; SWAT-VRR; landscape pattern; carbon emission

期刊名称：SUSTAINABILITY （ 影响因子：3.889； 五年影响因子：4.089 ）

ISSN：

年卷期： 2022 年 14 卷 2 期

页码：

收录情况： SCI

摘要： The relationship between water-sediment processes and landscape pattern changes has currently become a research hotspot in low-carbon water and land resource optimization research. The SWAT-VRR model is a distributed hydrological model which better shows the effect of land use landscape change on hydrological processes in the watershed. In this paper, the hydrological models of the Dapoling watershed were built, the runoff and sediment yield from 2006 to 2011 were simulated, and the relationship between landscape patterns and water-sediment yield was analyzed. The results show that the SWAT-VRR model is more accurate and reasonable in describing runoff and sediment yield than the SWAT model. The sub-basins whose soil erosion is relatively light are mostly concentrated in the middle reaches with a slope mainly between 0-5 degrees. The NP, PD, ED, SPIIT, SHEI, and SHDI of the watershed increased slightly, and the COHESION, AI, CONTAG, and LPI showed a certain decrease. The landscape pattern is further fragmented, with the degree of landscape heterogeneity increasing and the connection reducing. The runoff, sediment yield and surface runoff are all extremely significantly negatively correlated with forest, which implies that for more complicated patch shapes of forest which have longer boundaries connecting with the patches of other landscape types, the water and sediment processes are regulated more effectively. Therefore, it can be more productive to carry out research on the optimization of water and soil resources under the constraint of carbon emission based on the SWAT-VRR model.

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