Temporal Spatial Mutations of Soil Erosion in the Middle and Lower Reaches of the Lancang River Basin and Its Influencing Mechanisms

Abstract

As a major threat to ecosystem functions and national food security, soil erosion also exerts an influence on the water quality in basins and the operation and maintenance of hydropower plants. Existing discussions about trends of soil erosion focus mainly on its variation and mutation over time. Few studies have addressed the spatial mutation of soil erosion and its influence mechanism. In this research, Sen’s slope estimation was coupled with a Mann–Kendall model to explore the spatiotemporal distribution, spatial mutation characteristics and influence mechanisms of soil erosion, and conduct a case study on the Middle and Lower reaches of the Lancang River Basin (ML-LRB) in China. There are three main conclusions from this study: (1) During 2000–2019, the annual soil erosion in the ML-LRB variation ranged from 0 to 7.00 × 103 t/(km2·a) with a multi-year mean of 1.53 × 103 t/(km2·a), decreasing year by year from north to south, while an increasing trend began to appear in the central above region after 2015. (2) The areas with decreased soil erosion were much larger than those with increased soil erosion during 2000–2019, and there was a concentrated increase in soil erosion in Dali and in Xishuangbanna. (3) The mutation of the soil erosion intensity was spatially consistent with that of the Normalized Difference Vegetation Index (NDVI). Overall, this paper provides a new perspective for the study of factors affecting the trends and spatial mutation of soil erosion.

Can restoring water and sediment fluxes across a mega-dam cascade alleviate a sinking river delta?

“…While natural drivers such as typhoon activity ( 44 ) or El Niño–Southern Oscillation variability ( 45 ) could reduce sediment supply, anthropogenic activities were major contributors too. Land-use changes ( 46 ), sand mining ( 24 , 47 , 48 ), and upstream dams ( 20 , 21 ) had all been shown to contribute to the sediment reduction. When sediment loads decrease but flows are still geomorphically competent, the river has excess energy with which to erode and degrade the riverbanks ( 49 ).…”

Spatiotemporal Variability in Rainfall Erosivity and Its Teleconnection with Atmospheric Circulation Indices in China

“…However, acquiring continuous high-resolution precipitation data is difficult, and despite data availability, calculating RE from this type of data is challenging due to the intricate and laborious calculation process involved. To overcome these limitations, several uncomplicated RE algorithms have been developed that use readily available low-resolution rainfall data, such as annual precipitation data [61], monthly precipitation data [62], and daily precipitation data [54,63]. Zhang and Fu attempted to estimate RE by utilizing annual, monthly, and daily precipitation amounts [64].…”