Assessing and mapping soil erosion risk zone in Ratlam District, central India

Evaluation of physical and quantitative data of soil erosion is crucial to the sustainable development of the environment. The extreme form of land degradation through different forms of erosion is one of the major problems in the sub-tropical monsoon-dominated region. In India, tackling soil erosion is one of the major geo-environmental issues for its environment. Thus, identifying soil erosion risk zones and taking preventative actions are vital for crop production management. Soil erosion is induced by climate change, topographic conditions, soil texture, agricultural systems, and land management. In this research, the soil erosion risk zones of Ratlam District was determined by employing the Geographic Information System(GIS), Revised Universal Soil Loss Equation(RUSLE), Analytic Hierarchy Process(AHP), and machine learning algorithms(Random Forest and Reduced Error Pruning(REP) tree). RUSLE measured the rainfall eosivity(R), soil erodibility(K), length of slope and steepness(LS), land cover and management(C), and support practices(P) factors. Kappa statistic was used to configure model reliability and it was found that Random Forest and AHP have higher reliability than other models. About 14.73%(715.94 km^(2)) of the study area has very low risk to soil erosion, with an average soil erosion rate of 0.00-7.00×10^(3)kg/(hm^(2)·a), while about 7.46%(362.52 km^(2)) of the study area has very high risk to soil erosion, with an average soil erosion rate of 30.00×10^(3)-48.00×10^(3)kg/(hm^(2)·a). Slope, elevation, stream density, Stream Power Index(SPI), rainfall, and land use and land cover(LULC) all affect soil erosion. The current study could help the government and non-government agencies to employ developmental projects and policies accordingly. However, the outcomes of the present research also could be used to prevent, monitor, and control soil erosion in the study area by employing restoration measures.

Soil erosion risk evaluation using GIS in the Yuanmou County,a dry-hot valley of Yunnan, China

Soil erosion is a major threat to sustainable agriculture. Evaluating regional erosion risk is increasingly needed by national and in-ternational environmental agencies. This study elaborates a model (using spatial principal component analysis [SPCA]) method for the evaluation of soil erosion risk in a representative area of dry-hot valley (Yuanmou County) at a scale of 1:100,000 using a spatial database and GIS. The model contains seven factors: elevation, slope, annual precipitation, land use, vegetation, soil, and population density. The evaluation results show that five grades of soil erosion risk: very low, low, medium, high, and very high. These are divided in the study area, and a soil erosion risk evaluation map is created. The model may be applicable to other areas of China because it utilizes spatial data that are generally available.

Dynamic identification of soil erosion risk in the middle reaches of the Yellow River Basin in China from 1978 to 2010

Soil erosion has become a significant environmental problem that threatens eco- systems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and conservation priority level in the middle reaches of the Yellow River Basin were identified from 1978 to 2010. This study employed a multi-criteria evaluation method integrated with GIS and multi-source remote sensing data including land use, slope gradient and vegetation fractional coverage （VFC）. The erosion status in the study region improved from 1978 to 2010; areas of extremely severe, more severe, and severe soil erosion decreased from 0.05%, 0.94%, and 11.25% in 1978 to 0.04%, 0.81%, and 10.28% in 1998, respectively, and to 0.03%, 0.59%, and 6.87% in 2010, respectively. Compared to the period from 1978 to 1998, the area classed as improvement grade erosion increased by about 47,210.18 km2 from 1998 to 2010, while the area classed as deterioration grade ero- sion decreased by about 17,738.29 km2. Almost all severe erosion regions fall in the 1st and 2rid conservation priority levels, which areas accounted for 3.86% and 1.11% of the study area in the two periods, respectively. This study identified regions where soil erosion control is required and the results provide a reference for policymakers to implement soil conservation measures in the future.

SOTER-Based Soil Water Erosion Simulation in Hainan Island

The actual and potential water erosion rates of soils with different landcovers in Hainan Island, China, were estimated based on the universal soil loss equation (USLE) anda 1:200000 Soils and Terrain Digital Database (SOTER) database, from which soil water erosionfactors could be extracted. 92.8% of the whole island had a current erosion rate of lower than 500 tkm^(-2) a^(-1). Soil erosion risk was considered to be high because of its abundant rainfall.Without vegetation cover, the potential soil erosion rate would be extremely high and 90.8% of theisland would have a soil erosion rate higher than 2500 t km^(-2) a^(-1). Relative erosionvulnerability of different soil zones, landform types, and lithological regions of the island wascompared by introducing a relative erosion hazard parameter a. Cambosols developed from siltstoneand mudstone in low hill regions were pinpointed as soils with the highest erosion risk in theisland.

Managing Soil Erosion Potential by Integrating Digital Elevation Models with the Southern China's Revised Universal Soil Loss Equation——A Case Study for the West Lake Scenic Spots Area of Hangzhou,China

In China, many scenic and tourism areas are suffering from the urbanization that results from physical development of tourism projects, leading to the removal of the vegetative cover, the creation of areas impermeable to water, in-stream modifications, and other problems. In this paper, the risk of soil erosion and its ecological risks in the West Lake Scenic Spots （WLSS） area were quantitatively evaluated by integrating the revised universal soil loss equation （RUSLE） with a digital elevation model （DEM） and geographical information system （GIS） software. The standard RUSLE factors were modified to account for local climatic and topographic characteristics reflected in the DEM maps, and for the soil types and vegetation cover types. An interface was created between the Areinfo software and RUSLE so that the level of soil erosion and its ecological risk in the WLSS area could be mapped immediately once the model factors were defined for the area. The results from an analysis using the Areinfo-RUSLE interface showed that the risk value in 93 % of the expanding western part of the WLSS area was moderate or more severe and the soil erosion risk in this area was thus large compared with that in the rest of the area. This paper mainly aimed to increase the awareness of the soil erosion risk in urbanizing areas and suggest that the local governments should consider the probable ecological risk resulting from soil erosion when enlarging and developing tourism areas.

Development of a landscape index to link landscape pattern to runoff and sediment

Linking landscape indexes to ecological processes is the key topic of landscape ecology.However,traditional landscape metrics based on the Patch-Mosaic Model have no ecological significance.In this study,the runoff-sediment landscape index coupling land use,topography,soil,and vegetation factors was constructed to link landscape patterns to runoff and sediment.In the study area,the runoffsediment landscape index at the class scale showed an increasing trend from 0.10 in 1995 to 0.26 in 2015.Cropland had a higher runoff-sediment landscape index compared to grassland or forestland.At the landscape scale,the runoff-sediment landscape index showed a decreasing trend since 1995;furthermore,it decreased by 36.24%in 2015 compared with the index in 1990.The runoff-sediment landscape index had higher correlations with runoff and sediment compared with traditional landscape metrics.Redundancy analysis showed that the runoffsediment landscape index had a higher contribution to runoff and sediment compared to traditional landscape metrics,explaining 90.1%of the variability.The soil erosion risk assessed by the runoff-sediment landscape index showed an increasing trend upstream of the Dali River watershed.More attention should be paid to this area in future vegetation restoration attempts,as exploring the impact of landscape pattern changes on ecological processes,especially hydrological processes,plays an important role in comprehensive watershed management.