Global impact of climate change on soil erosion and potential for adaptation through soil conservation

Eekhout, Joris; Vente, Joris de

doi:10.1016/j.earscirev.2022.103921

Cited by 144 publications

(65 citation statements)

References 90 publications

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“…The potential applications of this dataset are as follows. First, this dataset can be used to further clarify the mechanisms of the pattern and the variation of soil conservation in China, including the effects of climate change and human activities (Li and Fang, 2016;Eekhout and de Vente, 2022). Second, this dataset could provide the data basis for comprehensive assessments and trade-offs of other ecosystem service functions (Schroter et al, 2005;Ouyang et al, 2016).…”

Section: Data Accuracy Of the Datasetmentioning

confidence: 99%

Long-time Series Dataset of Soil Conservation Capacity Preventing Water Erosion in China (1992–2019)

Chen

et al. 2022

Preprint

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Abstract. Soil conservation capacity (SC) is defined as the ability of the ecosystem to control soil erosion and protect soil function. A long-term and high-resolution estimation of soil conservation is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution SC dataset in China is established from 1992 to 2019 based on the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE modelling was conducted based on five key parameters, including the rainfall erosivity (interpolation of daily rainfall), land cover management (provincial data), conservation practices (weighted by terrain and crop types), topography (30 m), and soil properties (250 m). The dataset agrees with previous measurements (R2 > 0.5 in all the basins) and other regional simulations. The results show that China's SC decreased before 2003 and then increased up to now. The SC change exhibits the ecological effects of soil and water conservation policies in China, such as the Conversion of Farmland to Forests and Grass (Grain-for-Green), which unfolded many movements after 2000. Compared with current studies, the dataset has long-term, large-scale, and relatively high-resolution characteristics. This dataset will serve as a base to open out the mechanism of SC variations in China and could help assess the ecological effects of land management policies. This dataset is available at https://doi.org/10.11888/Terre.tpdc.272668 (Li et al., 2022).

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Section: Data Accuracy Of the Datasetmentioning

confidence: 99%

Long-time Series Dataset of Soil Conservation Capacity Preventing Water Erosion in China (1992–2019)

Chen

et al. 2022

Preprint

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“…These influencing factors have positive or negative impacts on catchment sediment yield, resulting in different changing trends in the sediment loads of the world's rivers (Li et al, 2020; Walling & Fang, 2003). The sediment load variation has a direct impact on water quality of drinking water, sedimentation of reservoirs and channel (Eekhout & Vente, 2022; Zhang & Shi, 2001). In addition, it has indirect impacts on marine pollution and the evolution of deltas and coastal landforms, resulting in severe threats to the ecosystem sustainability of coastal regions (Kong et al, 2016; Li et al, 2018; Liu, Yuan, Yang, et al, 2014; Walling, 2006).…”

Section: Introductionmentioning

confidence: 99%

Effects of climate variability and anthropogenic factors on sediment load reduction in the Weihe River basin, China

Zhao

et al. 2022

Hydrological Processes

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Sediment load of China's Yellow River has dramatically decreased due to the interplay of climate variability and human activities in the past decades. However, the contribution of individual driving factors and the detailed spatial distribution of sediment load at a catchment scale were not well understood. In the study, we quantitatively assessed the relative contributions of individual climatic (i.e. precipitation) and anthropogenic (i.e. vegetation restoration, terrace construction) driving factors to sediment load variations in the largest tributary of the Yellow River, Weihe River. The employed annual sediment load measurements and rainfall data for 1961-2015 were collected at 15 hydrological and 60 meteorological stations that were widely distributed in the basin.Changing trends, periodicity, and abrupt changes of hydro-climatic variables were detected using the non-parametric Mann-Kendall test, the empirical mode decomposition method, and Pettitt's test. Results showed that annual sediment load presented significantly decreasing trends at 12 hydrological stations. Annual rainfall erosivity showed a mixed tendency, with the changing trends varying among different regions. A 3-year periodicity was identified in the annual sediment load at three main stream gauging stations. Abrupt changing points in sediment load primarily occurred in the 1990s and early 2000s at all of the 15 hydrological stations, which were largely attributed to human activities. The increase in vegetation cover was responsible for approximately 40.6%, 37.4%, and 54.7% of the sediment load reduction in the main stream of the Weihe River, the Jinghe River, and the Beiluohe River, respectively. Meanwhile, terrace construction accounted for 19.7%, 43.8%, and 9.9% of the sediment variation, respectively.Conversely, precipitation change accounted for 5.7%, 12.4%, and 8.3% of sediment load reduction, respectively. Overall, vegetation restoration and terrace construction were found to be the two dominating factors for sediment load reduction in the study area.

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“…Soil erosion is a natural phenomenon consisting mainly of water erosion whose action is due to rain and water flow on the Earth's surface [5]. Climate change is expected to drive an ever more irregular hydrologic cycle and more frequent torrential rainfall patterns [6], thus, increasing the intensity of water erosion phenomena and accelerating erosion processes in the near future [7].…”

Section: Introductionmentioning

confidence: 99%

Multi-Decadal Assessment of Soil Loss in a Mediterranean Region Characterized by Contrasting Local Climates

Samela

Imbrenda

Coluzzi

et al. 2022

Land

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Soil erosion is one of the most widespread soil degradation phenomena worldwide. Mediterranean landscapes, due to some peculiar characteristics, such as fragility of soils, steep slopes, and rainfall distribution during the year, are particularly subject to this phenomenon, with severe and complex issues for agricultural production and biodiversity protection. In this paper, we present a diachronic approach to the analysis of soil loss, which aims to account for climate variability and land cover dynamics by using remote data about rainfall and land cover to guarantee sufficient observational continuity. The study area (Basilicata, Southern Italy) is characterized by different local climates and ecosystems (temperate, Csa and Csb; arid steppic, Bsk; and cold, Dsb and Dsc), and is particularly suited to represent the biogeographical complexity of the Mediterranean Italy. The well-known Revised Universal Soil Loss Equation (RUSLE) was applied by integrating information from remote sensing to carry out decadal assessments (1994, 2004, 2014, and 2021) of the annual soil loss. Changes in the rainfall regime and vegetation cover activity were derived from CHIRPS and Landsat data, respectively, to obtain updated information useful for dynamical studies. For the analyzed region, soil loss shows a slight reduction (albeit always remarkable) over the whole period, and distinct spatial patterns between lowland Bsk and Mediterranean mountain Dsb and Dsc climate areas. The most alarming fact is that most of the study area showed soil erosion rates in 2021 greater than 11 t/ha*y, which is considered by the OECD (Organization for Economic Cooperation and Development) the threshold for identifying severe erosion phenomena. A final comparison with local studies shows, on average, differences of about 5 t ha−1 y−1 (minimum 2.5 and maximum 7) with respect to the local estimates obtained with the RUSLE model. The assessment at a regional scale provided an average 9.5% of soil loss difference for the arable lands and about 10% for all cultivated areas. The spatial-temporal patterns enhance the relevance of using the cover management factor C derived from satellite data rather than land cover maps, as remote observations are able to highlight the heterogeneity in vegetation density within the same vegetation cover class, which is particularly relevant for agricultural areas. For mountain areas, the adoption of a satellite-gridded rainfall dataset allowed the detection of erosion rate fluctuations due to rainfall variability, also in the case of sparse or absent ground pluviometric stations. The use of remote data represents a precious added value to obtain a dynamic picture of the spatial-temporal variability of soil loss and new insights into the sustainability of soil use in a region whose economy is mostly based on agriculture and the exploitation of natural resources.

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Global impact of climate change on soil erosion and potential for adaptation through soil conservation

Cited by 144 publications

References 90 publications

Long-time Series Dataset of Soil Conservation Capacity Preventing Water Erosion in China (1992–2019)

Long-time Series Dataset of Soil Conservation Capacity Preventing Water Erosion in China (1992–2019)

Effects of climate variability and anthropogenic factors on sediment load reduction in the Weihe River basin, China

Multi-Decadal Assessment of Soil Loss in a Mediterranean Region Characterized by Contrasting Local Climates

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