Relationship between drought and soil erosion based on the normalized differential water index(NDWI)and revised universal soil loss equation(RUSLE)model

The Langat River Basin in Malaysia is vulnerable to soil erosion risks because of its exposure to intensive land use activities and its topography,which primarily consists of steep slopes and mountainous areas.Furthermore,climate change frequently exposes this basin to drought,which negatively affects soil and water conservation.However,recent studies have rarely shown how soil reacts to drought,such as soil erosion.Therefore,the purpose of this study is to evaluate the relationship between drought and soil erosion in the Langat River Basin.We analyzed drought indices using Landsat 8 satellite images in November 2021,and created the normalized differential water index(NDWI)via Landsat 8 data to produce a drought map.We used the revised universal soil loss equation(RUSLE)model to predict soil erosion.We verified an association between the NDWI and soil erosion data using a correlation analysis.The results revealed that the southern and northern regions of the study area experienced drought events.We predicted an average annual soil erosion of approximately 58.11 t/(hm^(2)·a).Analysis of the association between the NDWI and soil erosion revealed a strong positive correlation,with a Pearson correlation coefficient of 0.86.We assumed that the slope length and steepness factor was the primary contributor to soil erosion in the study area.As a result,these findings can help authorities plan effective measures to reduce the impacts of drought and soil erosion in the future.

Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala,India,using Revised Universal Soil Loss Equation(RUSLE) and geo-information technology

A comprehensive methodology that integrates Revised Universal Soil Loss Equation （RUSLE） model and Geographic Information System （GIS） techniques was adopted to determine the soil erosion vulner- ability of a forested mountainous sub-watershed in Kerala, India. The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method. GIS data layers including, rainfall erosivity （R）, soil erodability （K）, slope length and steepness （LS）, cover management （C） and conservation practice （P） factors were computed to determine their effects on average annual soil loss in the area. The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h-1 y i with a close relation to grass land areas, degraded forests and deciduous forests on the steep side-slopes （with high LS ）. The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.

Integrated Approach of Universal Soil Loss Equation (USLE) and Geographical Information System (GIS) for Soil Loss Risk Assessment in Upper South Koel Basin, Jharkhand

Soil erosion is a growing problem especially in areas of agricultural activity where soil erosion not only leads to decreased agricultural productivity but also reduces water availability. Universal Soil Loss Equation (USLE) is the most popular empirically based model used globally for erosion prediction and control. Remote sensing and GIS techniques have become valuable tools specially when assessing erosion at larger scales due to the amount of data needed and the greater area coverage. The present study area is a part of Chotanagpur plateau with undulating topography, with a very high risk of soil erosion. In the present study an attempt has been made to assess the annual soil loss in Upper South Koel basin using Universal Soil Loss Equation (USLE) in GIS framework. Such information can be of immense help in identifying priority areas for implementation of erosion control measures. The soil erosion rate was determined as a function of land topography, soil texture, land use/land cover, rainfall erosivity, and crop management and practice in the watershed using the Universal Soil Loss Equation (for Indian conditions), remote sensing imagery, and GIS techniques. The rainfall erosivity R-factor of USLE was found as 546 MJ mm/ha/hr/yr and the soil erodibility K-factor varied from 0.23 - 0.37. Slopes in the catchment varied between 0% and 42% having LS factor values ranging from 0 - 21. The C factor was computed from NDVI (Normalized Difference Vegetative Index) values derived from Landsat-TM data. The P value was computed from existing cropping patterns in the catchment. The annual soil loss estimated in the watershed using USLE is 12.2 ton/ha/yr.

Evaluation of C and P Factors in Universal Soil Loss Equation on Trapping Sediment: Case Study of Santubong River

Universal Soil Loss Equation (USLE) is the most comprehensive technique available to predict the long term average annual rate of erosion on a field slope. USLE was governed by five factors include soil erodibility factor (K), rainfall and runoff erodibility index (R), crop/vegetation and management factor (C), support practice factor (P) and slope length-gradient factor (LS). In the past, K, R and LS factors are extensively studied. But the impacts of factors C and P to outfall Total Suspended Solid (TSS) and % reduction of TSS are not fully studied yet. Therefore, this study employs Buffer Zone Calculator as a tool to determine the sediment removal efficiency for different C and P factors. The selected study areas are Santubong River, Kuching, Sarawak. Results show that the outfall TSS is increasing with the increase of C values. The most effective and efficient land use for reducing TSS among 17 land uses investigated is found to be forest with undergrowth, followed by mixed dipt. forest, forest with no undergrowth, cultivated grass, logging 30, logging 10^6, wet rice, new shifting agriculture, oil palm, rubber, cocoa, coffee, tea and lastly settlement/cleared land. Besides, results also indicate that the % reduction of TSS is increasing with the decrease of P factor. The most effective support practice to reduce the outfall TSS is found to be terracing, followed by contour-strip cropping, contouring and lastly not implementing any soil conservation practice.

Factor value determination and applicability evaluation of universal soil loss equation in granite gneiss region

Six types of runoff plots were set up and an experimental study was carried out to examine natural rate of soil and water loss in the granite gneiss region of northern Jiangsu Province in China. Through correlation analysis of runoff and soil loss during 364 rainfall events, a simplified and convenient mathematical formula suitable for calculating the rainfall erosivity factor （R） for the local region was established. Other factors of the universal soil loss equation （USLE model） were also determined. Relative error analysis of the soil loss of various plots calculated by the USLE model on the basis of the observed values showed that the relative error ranged from -3.5% to 9.9% and the confidence level was more than 90%. In addition, the relative error was 5.64% for the terraced field and 12.36% for the sloping field in the practical application. Thus, the confidence level was above 87.64%. These results provide a scientific basis for forecasting and monitoring soil and water loss, for comprehensive management of small watersheds, and for soil and water conservation planning in the region.

Assessment of Soil Loss in the Mirabah Basin: An Overview of the Potential of Agricultural Terraces as Ancestral Practices (Saudi Arabia)

Water erosion remains the major problem in many countries, especially those with an extension in the arid and semi-arid area and those marked by a long dry season. The intensification of land degradation which is a result of the strong erosive dynamics on a global scale has stimulated the initiative of multidisciplinary researchers investigate the issue of water erosion from its various facets [1] [2]. The goal is to preserve water and soil, two resources threatened. Multiple attempts were made to diagnose and implement empirical and experimental methods for quantitative estimation of soil loss caused by diffuse erosion. Indeed, the Eastern slope of the high mountains of Asir (Saudi Arabia), formerly worn and cut by the depression of rivers and undeniable branching of the river system, deserves to be studied in detail given the release of a huge erosive potential that is responsible for soil losses that are increasing gradually and continuously. The purpose of this paper was to validate the suitability of agricultural terraces in terms of soil preservation, using the results of the soil loss application as an indicator of the state of function of these latter. Many studies have addressed the agricultural terraces, however, only a few of them have focused on the relationship between erosion and agricultural terraces through an experimental approach. Previous work has concentrated mainly on their socio-economic impact;whilst the knowledge of their environmental impact remained scarce. In terms of the climate change context, soil erosion is becoming a central problem in Asir region. Thus, in this way, the application of the universal equation of soil loss was very helpful to explain and predict the role of each factor. Nevertheless, extreme caution and great care must be taken because of the application of this model outside its frame.

Contribution of a Geographical Information System to the Study of Soil Loss Dynamics in the Lobo Catchment (Côte d’Ivoire)

The Lobo watershed is highly anthropogenic since it has become the main production area for cocoa and coffee in C?te d’Ivoire. It therefore seems important to quantify soil loss by water erosion in this region. The Wischmeier modeling was used to model the main factors involved in erosive phenomena. Crosscutting of thematic maps and the application of the USLE formulas made possible to evaluate the erosion rate at the watershed scale in 1986 and 2014. Although soil is susceptible to erosion and erosivity is increased, the results indicate a growth in soil loss estimated at 90.12%. Some agroforestry efforts are still possible to help reducing those soil losses.

Influence of varied drought types on soil conservation service within the framework of climate change:insights from the Jinghe River Basin,China

Severe soil erosion and drought are the two main factors affecting the ecological security of the Loess Plateau,China.Investigating the influence of drought on soil conservation service is of great importance to regional environmental protection and sustainable development.However,there is little research on the coupling relationship between them.In this study,focusing on the Jinghe River Basin,China as a case study,we conducted a quantitative evaluation on meteorological,hydrological,and agricultural droughts(represented by the Standardized Precipitation Index(SPI),Standardized Runoff Index(SRI),and Standardized Soil Moisture Index(SSMI),respectively)using the Variable Infiltration Capacity(VIC)model,and quantified the soil conservation service using the Revised Universal Soil Loss Equation(RUSLE)in the historical period(2000-2019)and future period(2026-2060)under two Representative Concentration Pathways(RCPs)(RCP4.5 and RCP8.5).We further examined the influence of the three types of drought on soil conservation service at annual and seasonal scales.The NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP)dataset was used to predict and model the hydrometeorological elements in the future period under the RCP4.5 and RCP8.5 scenarios.The results showed that in the historical period,annual-scale meteorological drought exhibited the highest intensity,while seasonal-scale drought was generally weakest in autumn and most severe in summer.Drought intensity of all three types of drought will increase over the next 40 years,with a greater increase under the RCP4.5 scenario than under the RCP8.5 scenario.Furthermore,the intra-annual variation in the drought intensity of the three types of drought becomes smaller under the two future scenarios relative to the historical period(2000-2019).Soil conservation service exhibits a distribution pattern characterized by high levels in the southwest and southeast and lower levels in the north,and this pattern has remained consistent both in the historical and future periods.Over the past 20 years,the intra-annual variation indicated peak soil conservation service in summer and lowest level in winter;the total soil conservation of the Jinghe River Basin displayed an upward trend,with the total soil conservation in 2019 being 1.14 times higher than that in 2000.The most substantial impact on soil conservation service arises from annual-scale meteorological drought,which remains consistent both in the historical and future periods.Additionally,at the seasonal scale,meteorological drought exerts the highest influence on soil conservation service in winter and autumn,particularly under the RCP4.5 and RCP8.5 scenarios.Compared to the historical period,the soil conservation service in the Jinghe River Basin will be significantly more affected by drought in the future period in terms of both the affected area and the magnitude of impact.This study conducted beneficial attempts to evaluate and predict the dynamic characteristics of watershed drought and soil conservation service,as well as the response of soil conservation service to different types of drought.Clarifying the interrelationship between the two is the foundation for achieving sustainable development in a relatively arid and severely eroded area such as the Jinghe River Basin.

An Integrated GIS/RS Approach for Soil Erosion Assessment and Modeling in Syrian Coastal Soils

An integrated remote sensing (RS) and geographic information system (GIS) technique was employed to characterize the spatial distribution of the risk of soil erosion by water on Latakia district, Syria. The universal soil loss equation (USLE) was used to calculate the annual soil loss rates for Latakia soils. Mainly, remote sensing data, soil survey, land use inventory, elevation data and climatic atlases are used as resource data sets to generate USLE factor values. The results revealed that integration of GIS/RS with USLE was a practical and effective approach for monitoring soil erosion over large areas.

Dynamic Monitoring of Soil Erosion for Upper Stream of Miyun Reservoir in the Last 30 Years

The Revised Universal Soil Loss Equation （RUSLE） was applied to assess the spatial distribution and dynamic properties of soil loss with geographic information system （GIS） and remote sensing （RS） technologies. To improve the accuracy of soil-erosion estimates, a new C-factor estimation model was developed based on land cover and time series normalized difference vegetation index （NDVI） datasets. The new C-factor was then applied in the RUSLE to integrate rainfall, soil, vegetation, and topography data of different periods, and thus monitor the distribution of soil erosion patterns and their dynamics during a 3o-year period of the upstream watershed of Miynn Reservoir （UWMR）, China. The results showed that the new C-factor estimation method, which considers land cover status and dynamics, and explicitly incorporates within-land cover variability, was more rational, quantitative, and reliable. An average annual soil loss in UWMR of 25.68, 21.04, and 16.8o t ha-1 a-1 was estimated for 1990, 2000 and 2010, respectively, corroborated by comparing spatial and temporal variation in sediment yield. Between 2000 and 2010, a 1.38% average annual increase was observed in the area of lands that lost less than 5 t ha-1 a^-1, while during 1990-2000 such lands only increased on average by o.46%. Areas that classified as severe, very severe and extremely severe accounted for 5.68% of the total UWMR in 2010, and primarily occurred in dry areas or grasslands of sloping fields. The reason for the change in rate of soil loss is explained by an increased appreciation of soil conservation by developers and planners. Moreover,we recommend that UWMR watershed adopt further conservation measures such as terraced plowing of dry land, afforestation, or grassland enclosures as part of a concerted effort to reduce on-going soil erosion.

Addressing soil protection concerns in forest ecosystem management under climate change

Background: Climate change may strongly influence soil erosion risk, namely through variations in the precipitation pattern. Forests may contribute to mitigate the impacts of climate change on soil erosion and forest managers are thus challenged by the need to define strategies that may protect the soil while addressing the demand for other ecosystem services. Our emphasis is on the development of an approach to assess the impact of silvicultural practices and forest management models on soil erosion risks under climate change. Specifically, we consider the annual variation of the cover-management factor(C) in the Revised Universal Soil Loss Equation over a range of alternative forest management models to estimate the corresponding annual soil losses, under both current and changing climate conditions. We report and discuss results of an application of this approach to a forest area in Northwestern Portugal where erosion control is the most relevant water-related ecosystem service.Results: Local climate change scenarios will contribute to water erosion processes, mostly by rainfall erosivity increase.Different forest management models provide varying levels of soil protection by trees, resulting in distinct soil loss potential.Conclusions: Results confirm the suitability of the proposed approach to address soil erosion concerns in forest management planning. This approach may help foresters assess management models and the corresponding silvicultural practices according to the water-related services they provide.

Forest soil conservation based on eco-service provision unit method and its value in Anji County,Huzhou,Zhejiang,China

We propose an eco-service provision unit method for estimating the benefit and spatial differences of forests in controlling soil erosion.A total of 197 eco-service provision units were grouped on 1424.43 km2 of forest according to differences in vegetation,slope,soil,and rainfall.The amount of soil conservation and its economic value were estimated.The forests in Anji County prevent4.08 9 105 tons of soil from eroding annually,thereby avoiding 1.36 9 104 tons of nutrient loss（on-site cost） and preventing 149 tons of nutritive elements from entering water systems（off-site cost）.From an economic perspective,the soil nutrient conservation in the forests of Anji County generated an annual benefit of 43.37 million RMB（Chinese Currency,6.20 RMB = US$1）.On average,each hectare of ecological forest contributed up to 436 RMB annually because of soil conservation.Ecological complexes with higher rainfall intensity,such as broadleaf forest and red soil on slope gradients [25°,contributed the highest soil conservation benefits.This study identified and quantified the dominant contributors and magnitudes of soil conservation provided by forests.This information can benefit decision making regarding differentiated ecological compensation policies.

GIS-based Effect Assessment of Soil Erosion Before and After Gully Land Consolidation: A Case Study of Wangjiagou Project Region, Loess Plateau

The Loess Plateau is one typical area of serious soil erosion in the world. China has implemented ′Grain for Green′(GFG) project to restore the eco-environment of the Loess Plateau since 1999. With the GFG project subsidy approaching the end, it is concerned that farmers of fewer subsidies may reclaim land again. Thus, ′Gully Land Consolidation Project′(GLCP) was initiated in 2010. The core of the GLCP was to create more land suitable for farming in gullies so as to reduce land reclamation on the slopes which are ecological vulnerable areas. This paper aims to assess the effect of the GLCP on soil erosion problems by studying Wangjiagou project region located in the central part of Anzi valley in the middle of the Loess Plateau, mainly using the revised universal soil loss equation(RUSLE) based on GIS. The findings show that the GLCP can help to reduce soil shipment by 9.87% and it creates more terraces and river-nearby land suitable for farming which account for 27.41% of the whole study area. Thus, it is feasible to implement the GLCP in places below gradient 15°, though the GLCP also intensifies soil erosion in certain places such as field ridge, village land, floodplain, natural grassland, and shrub land. In short, the GLCP develops new generation dam land and balances the short-term and long-term interests to ease the conflicts between economic development and environmental protection. Furthermore, the GLCP and the GFG could also be combined preferably. On the one hand, the GFG improves the ecological environment, which could offer certain safety to the GLCP, on the other hand, the GLCP creates more farmland favorable for farming in gullies instead of land reclamation on the slopes, which could indirectly protect the GFG project.

Modeling spatial and temporal change of soil erosion based on multi-temporal remotely sensed data

In order to monitor the pattern, distribution, and trend of land use/cover change （LUCC） and its impacts on soil erosion, it is highly appropriate to adopt Remote Sensing （RS） data and Geographic Information System （GIS） to analyze, assess, simulate, and predict the spatial and temporal evolution dynamics. In this paper, multi-temporal Landsat TM/ETM＋ re- motely sensed data are used to generate land cover maps by image classification, and the Cellular Automata Markov （CA_Markov） model is employed to simulate the evolution and trend of landscape pattern change. Furthermore, the Re- vised Universal Soil Loss Equation （RUSLE） is used to evaluate the situation of soil erosion in the case study mining area. The trend of soil erosion is analyzed according to total/average amount of soil erosion, and the rainfall （R）, cover man- agement （C）, and support practice （P） factors in RUSLE relevant to soil erosion are determined. The change trends of soil erosion and the relationship between land cover types and soil erosion amount are analyzed. The results demonstrate that the CA_Markov model is suitable to simulate and predict LUCC trends with good efficiency and accuracy, and RUSLE can calculate the total soil erosion effectively. In the study area, there was minimal erosion grade and this is expected to con- tinue to decline in the next few years, according to our prediction results.

Combining RUSLE model and the vegetation health index to unravel the relationship between soil erosion and droughts in southeastern Tunisia

Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.

Evaluating estimated sediment delivery by Revised Universal Soil Loss Equation(RUSLE)and Sediment Delivery Distributed(SEDD)in the Talar Watershed,Iran

The performance of the Revised Universal Soil Loss Equation(RUSLE)as the most widely used soil erosion model is a challenging issue.Accordingly,the objective of this study is investigating the estimated sediment delivery by the RUSLE method and Sediment Delivery Distributed(SEDD)model.To this end,the Talar watershed in Iran was selected as the study area.Further,700 paired sediment-discharge measurements at Valikbon and Shirgah-Talar hydrometric stations between the years 1991 and 2011 were collected and used in sediment rating curves.Nine procedures were investigated to produce the required RUSLE layers.The estimated soil erosion by RUSLE was evaluated using sediment rating curve data by two methods including least squares and quantile regression.The average annual suspended sediment load was calculated for each sub-watershed of the study area using the SEDD model.Afterwards,a sediment rating curve was estimated by least squares and quantile regression methods using paired discharge-sediment data.The average annual suspended sediment load values were calculated for two hydrometric stations and were further evaluated by the SEDD model.The results indicated that the first considered procedure,which utilized 15-min rainfall measurements for the rainfall factor(R),and the classification method of SENTINEL-2 MSI image for the cover management factor(C),offered the best results in producing RUSLE layers.Furthermore,the results revealed the advantages of utilizing satellite images in producing cover management layer,which is required in the RUSLE method.

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.

Determining the Soil Erodibility for an Experimental Basin in the Semi-Arid Region Using Geoprocessing

Erosion is the natural process which has the greatest environmental impact, and is the principal trigger for desertification around the globe. The main model used to estimate soil loss by erosion is the Universal Soil Loss Equation (USLE), which unites the major factors that influence erosion into one equation. The soil erodibility factor (K) is the component of this equation that represents soil physics, and is defined as the inherent capacity of the soil to withstand disintegration of its particles and their subsequent transport. The use of geostatistics is seen as an alternative in spatializing this variable from sampled to non-sampled points. The aim of this study therefore, was to determine the soil erodibility factor for an experimental basin in the semi-arid region of Brazil, in addition to generating the soil erodibility map using geostatistics. Disturbed and undisturbed soil samples were collected from 35 points, and laboratory samples were processed to determine the granulometry, permeability and organic matter of the soil, data which are used to determine the K-factor. Kriging was performed to spatialize the study variable, when spherical, exponential and Gaussian semivariograms were tested for generation of the soil erodibility map, these being evaluated by their respective deviations resulting from cross-validation. The mean value of K for the Haplic Luvisol was 0.0328 ton·ha·h/ha·MJ·mm;for the eutrophic Red-Yellow Argisol it was 0.0258 ton·ha·h/ha·MJ·mm;and for the Fluvic Neosol, it was 0.0424 ton·ha·h/ha·MJ·mm. The experimental basin is classified as highly erodible. The semivariogram that presented the best fit for generating the soil erodibility map of the study area was Gaussian.

1980—2020年延河甘谷驿流域土壤侵蚀评价与驱动因子分析

采用日降雨量、DEM、土壤类型、泥沙含量及多期NDVI等数据,基于修正通用土壤流失方程(RUSLE)和地理探测器,研究了国家生态退耕还林还草工程实施前后近41年延河甘谷驿流域土壤侵蚀动态与驱动因子。结果表明,1980—2020年研究区土壤侵蚀强度总体呈波动变化趋势,1980年、1990年、2000年、2010年和2020年平均侵蚀模数分别为6 746.30、5 740.28、6 389.56、5 450.46、5 480.56 t/(km~2·年)。1980—2000年研究区整体侵蚀强度逐渐增强,强烈及以上等级侵蚀面积占比逐渐增加,表现为“增蚀升级”的特点;2000年后研究区内土壤侵蚀强度开始降低,强烈及以上等级的侵蚀面积减少,总体表现为“减蚀降级”的特点。研究区土壤侵蚀强度随着坡度的升高而加剧,同时发现海拔1 000~1 200 m和1 200~1 400 m是研究区内侵蚀发生的主要高程带。2020年土地利用类型因子解释力最为突出,表明退耕还林还草工程实施效果显著,大面积的耕地向林草地转换是使得研究区2000年后土壤侵蚀强度降低的最主要原因。土壤侵蚀各影响因子的协同作用明显强于单一因子的影响。

基于RUSLE模型的秦岭—大巴山地土壤侵蚀时空特征分析

[目的]秦岭—大巴山地(秦巴山地)是我国重要的南北地理—生态过渡带主体,对秦巴山地的土壤侵蚀研究将有助于该区域的生态保护和水土资源管理。[方法]基于RUSLE模型计算秦巴山地的土壤侵蚀模数,并量化分析了该区域的土壤侵蚀的时空分布格局。[结果](1)2000—2020年秦巴山地的微度侵蚀面积呈上升趋势,轻度侵蚀及其以上等级的土壤侵蚀面积均呈下降趋势;从空间来看,秦巴山地东北和西南部的土壤侵蚀等级较高,中间较低;(2)秦巴山地的土壤侵蚀相对集中在500~1500 m、坡度15°~25°区域内;(3)秦巴山地发生土壤侵蚀最主要的土地利用类型为林地,耕地、林地的微度侵蚀以及草地的微度、剧烈侵蚀面积呈上升趋势;(4)秦巴山地土壤侵蚀主要分布在陕西、四川和甘肃,且甘肃和四川的剧烈侵蚀呈上升趋势。[结论]2000—2020年秦巴山地的侵蚀面积和强度呈“双下降”的态势,其整体侵蚀状况好转,但侵蚀分布存在明显空间差异。