scholarly journals Assessment of soil erosion in the Dongting Lake Basin, China: Patterns, drivers, and implications

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261842
Author(s):  
Jianyong Xiao ◽  
Binggeng Xie ◽  
Kaichun Zhou ◽  
Shana Shi ◽  
Junhan Li ◽  
...  

Soil loss caused by erosion is a global problem. Therefore, the assessment of soil erosion and the its driving mechanism are of great significance to soil conservation. However, soil erosion is affected by both climate change and human activities, which have not been quantified, and few researchers studied the differences in the driving mechanisms of soil erosion depending on the land use type. Therefore, the spatiotemporal characteristics and changing trends of soil erosion in the Dongting Lake Basin were analyzed in this study. Geographic detectors were used to identify the dominant factors affecting soil erosion in different land use types. In this study, a sensitivity experiment was conducted to clarify the relative contributions of climate change and human activities to soil erosion changes. In addition, we studied the effects of different land use types and vegetation cover restoration on soil erosion. The results show that soil erosion in the Dongting Lake Basin decreased from 2000 to 2018. Human activities represented by land use types and vegetation coverage significantly contributed to the alleviation of soil erosion in the Dongting Lake Basin, whereas climate change represented by rainfall slightly aggravated soil erosion in the study area. The restoration of grassland vegetation and transfer of cultivated land to woodlands in the study area improved the soil erosion. The slope steepness is the key factor affecting the intensity of soil erosion in dry land, paddy fields, and unused land, whereas the vegetation coverage is the key factor affecting the intensity of soil erosion in woodland, garden land, and grassland. Detailed spatiotemporally mapping of soil erosion was used to determine the connections between soil erosion and potential drivers, which have important implications for vegetation restoration and the optimization of land use planning.

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 604
Author(s):  
Yonghua Zhao ◽  
Li Liu ◽  
Shuaizhi Kang ◽  
Yong Ao ◽  
Lei Han ◽  
...  

The Loess Plateau of China suffers from severe erosion, which results in a great variety of economic and ecological problems. For scientific control of soil erosion, the key questions urgently to be addressed in this paper are: (1) Which are the driving factors under diverse geomorphological types? (2) Do these driving factors operate independently or by interacting? (3) Which zones under diverse geomorphological types suffer from severe erosion and need more attention? In this paper, the RUSLE model was applied here to demonstrate the spatio-temporal variations in soil erosion from 2010 to 2017 in Yan’an City, and the Geo-detector model proved to be a useful tool to solve the questions mentioned above. The results showed that the average erosion modulus in Yan’an City decreased by 1927.36 t/km2·a from 2010 to 2017. The intensity of soil erosion in the northern Baota District, central Ganquan County, Luochuan County, Ansai County, and Zhidan County decreased to varying degrees. The effect size of driving factors affecting soil erosion varied significantly in diverse geomorphological types. The effect size of interaction between land-use types and vegetation coverage, land-use types and slope, slope and precipitation was higher than that of a single factor. High-risk zones with severe erosion were closer to cultivated land and forest land with steep slopes (>25°) in the mid-elevation hills of Yan’an City. Additionally, based on the specificity of the study area, the Geo-detector model performed better in a relatively flat region, and factors with macroscopic spatial distributions weaken its explanatory power on soil erosion on a regional scale. Based on data selection, data of different accuracy sparked the issue of “data coupling”, which led to the enormous deviation of model results in mid-elevation plains. Results from our analysis provide insights for a more ecologically sound development of Yan’an City and provide references for the scientific use of the Geo-detector model.


2020 ◽  
Vol 12 (21) ◽  
pp. 3525
Author(s):  
Fu-hong Liu ◽  
Chong-Yu Xu ◽  
Xiao-xia Yang ◽  
Xu-chun Ye

Knowledge of vegetation dynamics in relation to climatic changes and human activities is essential for addressing the terrestrial carbon cycle in the context of global warming. Scientific detection and quantitative attribution of vegetation dynamic changes in different climatic zones and human activities are the focus and challenge of the relevant research. Taking the Poyang Lake basin as the research area, this study aimed to reveal how climate and land use drive changes in net primary productivity (NPP) in the subtropical humid basin. Change patterns of vegetation NPP and their relationships with meteorological factors across the basin were first investigated based on the estimation of 18 year (2000–2017 year) NPP by using a typical light energy utilization model, the Carnegie-Ames-Stanford Approach (CASA) model. Quantitative analysis was then conducted to explicitly distinguish the driving effects of climate change and land-use change on NPP dynamics in two different periods. Results show that annual NPP and total production (TP) of the Poyang Lake basin increased significantly from 2000 to 2017. During this period, land-use change in the basin was driven by the process of urbanization expansion and the efforts of ecological protection. Climatically, the temperature is the major influencing climatic factor in determining vegetation productivity in the subtropical humid basin, followed by precipitation and solar radiation. In addition, our investigation also revealed that with comparison to the period of 2000s, the increased TP of the Poyang Lake basin due to climate change in 2010s was much bigger than the decreased TP due to land-use change. However, in the areas where the land-use change occurred, the decreased TP was mainly attributed to the impact of land-use change, even though climate change showed a positive effect of increasing productivity.


2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1085 ◽  
Author(s):  
Shanshan Guo ◽  
Zhengru Zhu ◽  
Leting Lyu

Climate change and human activities are the major factors affecting runoff and sediment load. We analyzed the inter-annual variation trend of the average rainfall, air temperature, runoff and sediment load in the Xihe River Basin from 1969–2015. Pettitt’s test and the Soil and Water Assessment Tool (SWAT) model were used to detect sudden change in hydro-meteorological variables and simulate the basin hydrological cycle, respectively. According to the simulation results, we explored spatial distribution of soil erosion in the watershed by utilizing ArcGIS10.0, analyzed the average erosion modulus by different type of land use, and quantified the contributions of climate change and human activities to runoff and sediment load in changes. The results showed that: (1) From 1969–2015, both rainfall and air temperature increased, and air temperature increased significantly (p < 0.01) at 0.326 °C/10 a (annual). Runoff and sediment load decreased, and sediment load decreased significantly (p < 0.01) at 1.63 × 105 t/10 a. In 1988, air temperature experienced a sudden increase and sediment load decreased. (2) For runoff, R2 and Nash and Sutcliffe efficiency coefficient (Ens) were 0.92 and 0.91 during the calibration period and 0.90 and 0.87 during the validation period, for sediment load, R2 and Ens were 0.60 and 0.55 during the calibration period and 0.70 and 0.69 during the validation period, meeting the model’s applicability requirements. (3) Soil erosion was worse in the upper basin than other regions, and highest in cultivated land. Climate change exacerbates runoff and sediment load with overall contribution to the total change of −26.54% and −8.8%, respectively. Human activities decreased runoff and sediment load with overall contribution to the total change of 126.54% and 108.8% respectively. Runoff and sediment load change in the Xihe River Basin are largely caused by human activities.


2013 ◽  
Vol 5 (8) ◽  
pp. 3244-3274 ◽  
Author(s):  
Pheerawat Plangoen ◽  
Mukand Babel ◽  
Roberto Clemente ◽  
Sangam Shrestha ◽  
Nitin Tripathi

2021 ◽  
Author(s):  
Morteza Akbari ◽  
Ehsan Neamatollahi ◽  
Hadi Memarian ◽  
Mohammad Alizadeh Noughani

Abstract Floods cause great damage to ecosystems and are among the main agents of soil erosion. Given the importance of soils for the functioning of ecosystems and development and improvement of bio-economic conditions, the risk and rate of soil erosion was assessed using the RUSLE model in Iran’s Lorestan province before and after a period of major floods in late 2018 and early 2019. Furthermore, soil erosion was calculated for current and future conditions based on the Global Soil Erosion Modeling Database (GloSEM). The results showed that agricultural development and land use change are the main causes of land degradation in the southern and central parts of the study area. The impact of floods was also significant since our evaluations showed that soil erosion increased from 4.12 t ha-1 yr-1 before the floods to 10.93 t ha-1 yr-1 afterwards. Field surveying using 64 ground control points determined that erodibility varies from 0.17 to 0.49% in the study area. Orchards, farms, rangelands and forests with moderate or low vegetation cover were the most vulnerable land uses to soil erosion. The GloSEM modeling results revealed that climate change is the main cause of change in the rate of soil erosion. Combined land use change-climate change simulation showed that soil erosion will increase considerably in the future under SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios. In the study area, both natural factors, i.e. climate change and human factors such as agricultural development, population growth, and overgrazing are the main drivers of soil erosion.


Geosciences ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 478 ◽  
Author(s):  
Miriam Marzen ◽  
Thomas Iserloh ◽  
Wolfgang Fister ◽  
Manuel Seeger ◽  
Jesus Rodrigo-Comino ◽  
...  

The relative impact of water and wind on total erosion was investigated by means of an experimental-empirical study. Wind erosion and water erosion were measured at five different sites: (1) Mediterranean fallow, (2) Mediterranean orchard, (3) wheat field, (4) vineyard and (5) sand substrate. Mean erosion rates ranged from 1.55 to 618 g·m−2·h−1 for wind and from 0.09 to 133.90 g·m−2·h−1 for rain eroded material over all tested sites. Percentages (%) of eroded sediment for wind and rain, respectively, were found to be 2:98 on Mediterranean fallow, 11:89 on Mediterranean orchard, 3:97 on wheat field, 98:2 on vineyard and 99:1 on sand substrate. For the special case of soil surface crust destroyed by goat trampling, the measured values emphasize a strong potential impact of herding on total soil erosion. All sites produced erosion by wind and rain, and relations show that both erosive forces may have an impact on total soil erosion depending on site characteristics. The results indicate a strong need to focus on both wind and water erosion particularly concerning soils and substrates in vulnerable environments. Measured rates show a general potential erosion depending on recent developments of land use and climate change and may raise awareness of scientist, farmers and decision makers about potential impact of both erosive forces. Knowledge about exact relationship is key for an adapted land use management, which has great potential to mitigate degradation processes related to climate change.


2019 ◽  
Vol 11 (3) ◽  
pp. 609-622 ◽  
Author(s):  
Saeideh Maleki ◽  
Saeid Soltani Koupaei ◽  
Alireza Soffianian ◽  
Sassan Saatchi ◽  
Saeid Pourmanafi ◽  
...  

Abstract Negative impacts of climate change on ecosystems have been increasing, and both the intensification and the mitigation of these impacts are strongly linked with human activities. Management and reduction of human-induced disturbances on ecosystems can mitigate the effects of climate change and enhance the ecosystem recovery process. Here, we investigate coupled human and climate effects on the wetland ecosystem of the lower Helmand basin from 1977 to 2014. Using time series climate-variable data and land-use changes from Landsat time series imagery, we compared changes in ecosystem status between the upstream and downstream regions. Results show that despite a strong and prolonged drought in the region, the upstream region of the lower Helmand basin remained dominated by agriculture, causing severe water stress on the Hamoun wetlands downstream. The loss of available water in wetlands was followed by large-scale land abandonment in rural areas, migration to the cities, and increasing unemployment and economic hardship. Our results suggest that unsustainable land-use policies in the upstream region, combined with synergistic effects of human activities and climate in lower Helmand basin, have exacerbated the effects of water stress on local inhabitants in the downstream region.


2020 ◽  
Vol 12 (3) ◽  
pp. 399 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Huan Wang ◽  
Liyuan Zuo

Soil conservation and water retention are important metrics for designating key ecological functional areas and ecological red line (ERL) areas. However, research on the quantitative identification of dominant environmental factors in different ecological red line areas remains relatively inadequate, which is unfavorable for the zone-based management of ecological functional areas. This paper presents a case study of Beijing’s ERL areas. In order to objectively reflect the ecological characteristics of ERL areas in Beijing, which is mainly dominated by mountainous areas, the application of remote sensing data at a high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations as well as soil erosion and water yield were calculated using the revised universal soil loss equation (RUSLE) and integrated valuation of ecosystem services and tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type, and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s ERL areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different ERL areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s ERL areas, explaining greater than 30% of its spatial heterogeneity. Land use type could explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various ERL areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in ERL areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ERL areas. Thus, in efforts to enhance ERL protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ERL areas.


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