Dynamic Changes of Soil Erosion in the Taohe River Basin Using the RUSLE Model and Google Earth Engine

Abstract

The Taohe River Basin is the largest tributary and an important water conservation area in the upper reaches of the Yellow River. In order to investigate the status of soil erosion in this region, we conducted a research of soil erosion. In our study, several parameters of the revised universal soil loss equation (RUSLE) model are extracted by using Google Earth Engine. The soil erosion modulus of the Taohe River Basin was calculated based on multi-source data, and the spatio-temporal variation characteristics of the soil erosion intensity were analyzed. The results showed the following: (1) the average soil erosion modulus of the Taohe River Basin in 2000, 2005, 2010, 2015 and 2018 were 1424, 1195, 1129, 1099 and 1124 t·ha−1·year−1, respectively, and the overall downward trend was obvious. (2) The ranges of soil erosion in the Taohe River Basin in 2000, 2005, 2010, 2015 and 2018 are basically the same—mainly with slight erosion—and the soil erosion in the middle and lower reaches was more serious. (3) When dealing with the vegetation cover factor and conservation practice factor in the RUSLE model, Google Earth Engine provided a new approach for soil erosion investigation and monitoring over a large area.

Impact of Conservation Agriculture on Soil Erosion in the Annual Cropland of the Apulia Region (Southern Italy) Based on the RUSLE-GIS-GEE Framework

“…Table 1 reports the number of images that have a cloudy pixel percentage lower than 20% and are processed for the calculation of each NDVI. Finally, the calculation of the two factors, C crop [38,74] and C management, and their multiplication, is possible in GEE environment.…”

“…Moreover, increase of temperatures and consequently drier conditions (summer) caused by more and more evident effects of climate change and CM pose an additional threat to Apulian cropland [36,37]. Our approach is based on the RUSLE-GIS-GEE framework [3,38], using more suited databases at regional scale. This could provide greater detail and accuracy in calculating soil loss rate for ACL, separately for the two management systems: CM and CA for the period 2016-2020, following the introduction in 2016 of the specific sub-measure M10.1 "Conservation Agriculture", in which only a part of the farmers participated, being a voluntary measure.…”

Assessment of Water-Induced Soil Erosion as a Threat to Natura 2000 Protected Areas in Crete Island, Greece

“…It is well-accepted that erosion prediction models play a primary role in erosion mitigation strategies [46][47][48]. The increasing use of geoinformatics technologies, as well as the ever-growing availability of high-resolution geospatial data, has increased the efficiency and accuracy of the output of erosion models [26,[49][50][51][52], and has facilitated quantitative assessments of soil loss rates in large areas [48,53,54].…”

Satellite observations reveal decreasing soil erosion in Northeast Inner Mongolia, China, over the past four decades

“…Currently, remote sensing technology is a unique means used to investigate long time series dynamic changes in soil erosion at the regional scale (Zhou et al, 2016;Alexakis et al, 2019;Long et al, 2019;Wang and Zhao, 2020). Various soil erosion parameters, including digital elevation models, vegetation cover and land use, can be extracted from multisource satellite imagery to calculate the soil erosion intensity using a soil erosion model (Jiang et al, 2016;Xiao et al, 2021;Lin and Zhao, 2022).…”