Erosion Risk Map Research Articles

Evaluating erosion risk models in a Scottish catchment using organic carbon fingerprinting

PurposeIdentification of hotspots of accelerated erosion of soil and organic carbon (OC) is critical to the targeting of soil conservation and sediment management measures. The erosion risk map (ERM) developed by Lilly and Baggaley (Soil erosion risk map of Scotland, 2018) for Scotland estimates erosion risk for the specific soil conditions in the region. However, the ERM provides no soil erosion rates. Erosion rates can be estimated by empirical models such as the Revised Universal Soil Loss Equation (RUSLE). Yet, RUSLE was not developed specifically for the soil conditions in Scotland. Therefore, we evaluated the performance of these two erosion models to determine whether RUSLE erosion rate estimates could be used to quantify the amount of soil eroded from high-risk areas identified in the ERM.MethodsThe study was conducted in the catchment of Loch Davan, Aberdeenshire, Scotland. Organic carbon loss models were constructed to compare land use specific OC yields based on RUSLE and ERM using OC fingerprinting as a benchmark. The estimated soil erosion rates in this study were also compared with recently published estimates in Scotland (Rickson et al. in Developing a method to estimate the costs of soil erosion in high-risk Scottish catchments, 2019).ResultsThe region-specific ERM most closely approximated the relative land use OC yields in streambed sediment however, the results of RUSLE were very similar, suggesting that, in this catchment, RUSLE erosion rate estimates could be used to quantify the amount of soil eroded from the high-risk areas identified by ERM. The RUSLE estimates of soil erosion for this catchment were comparable to the soil erosion rates per land use estimated by Rickson et al. (Developing a method to estimate the costs of soil erosion in high-risk Scottish catchments, 2019) in Scottish soils except in the case of pasture/grassland likely due to the pastures in this catchment being grass ley where periods of surface vegetation cover/root network absence are likely to have generated higher rates of erosion.ConclusionSelection of suitable erosion risk models can be improved by the combined use of two sediment origin techniques—erosion risk modelling and OC sediment fingerprinting. These methods could, ultimately, support the development of targeted sediment management strategies to maintain healthy soils within the EU and beyond.

Spatio-Temporal Analysis of Erosion Risk Assessment Using GIS-Based AHP Method: A Case Study of Doğancı Dam Watershed in Bursa (Türkiye)

Soil erosion, one of the most serious phenomena in watershed management, can be estimated based on various criteria. Land use change is one of the most important factors affecting the susceptibility of soil erosion. In this study, the effect of land use change on soil erosion risk in two plan periods (2005 and 2017) was investigated using Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) for the forest planning units in the Doğancı Dam Watershed, located in Bursa, Türkiye. Eight criteria were evaluated including erosion-related slope, bedrock type, land use/land cover, precipitation, relative relief, aspect, drainage frequency, and density. According to the results, the most effective factor in soil erosion was slope (0.29), while bedrock type and land use/land cover ranked second with 0.19. It was found that full closure forests were characterized by high erosion resistance (0.3), while bare land was characterized as the most sensitive area to erosion (0.39). In terms of spatio-temporal changes in a 12-year period, the areas in the medium and high erosion risk decreased, while low and very low-risk areas increased. The ROC method showed a satisfactory accuracy of 72.8% and 80.2% for the 2005 and 2017 erosion risk maps, respectively.

CONTRIBUTION TO THE STUDY OF SOIL VULNERABILITY TO WATER EROSION IN THE THIES PLATEAU

This study was carried out in the watershed located between the municipalities of Tassette and Notto, where soil water erosion is one of the most dangerous threats in the region.This work aims to quantify the degree of soil erodibility in the Thiesplateauand then draw up an erosion risk map using the improved boyoucoss method. Interpretation of the experimental results reveals that the erodibility index varies between 1.62 and 14.10, with an average value of 5.6. This variation in the erodibility index shows areas of high, moderate and very high vulnerability, respectively 59%, 18.2% and 18% of the areas studied. The progressive degradation of soils by water erosion is also amplified by inappropriate human activities, weakening the resilience of ecosystems and communities.

Impact of forest landscape restoration in combating soil erosion in the Lake Abaya catchment, Southern Ethiopia

As an effect of forest degradation, soil erosion is among Ethiopia’s most pressing environmental challenges and a major threat to food security where it could potentially compromise the ecosystem functions and services. As the effects of soil erosion intensify, the landscape’s capacity to support ecosystem functions and services is compromised. Exploring the ecological implications of soil erosion is crucial. This study investigated the soil loss and land degradation in the Lake Abaya catchment to explore forest landscape restoration (FLR) implementation as a possible countermeasure to the effects. The study used a geographic information system (GIS)-based approach of the Revised Universal Soil Loss Equation (RUSLE) to determine the potential annual soil loss and develop an erosion risk map. Results show that 13% of the catchment, which accounts for approximately 110,000 ha, is under high erosion risk of exceeding the average annual tolerable soil loss of 10 t/ha/year. Allocation of land on steep slopes to crop production is the major reason for the calculated high erosion risk in the catchment. A scenario-based analysis was implemented following the slope-based land-use allocation proposal indicated in the Rural Land Use Proclamation 456/2005 of Ethiopia. The scenario analysis resulted in a reversal erosion effect whereby an estimated 3000 t/ha/year of soil loss in the catchment. Thus, FLR activities hold great potential for minimizing soil loss and contributing to supporting functioning and providing ecosystem services. Tree-based agroforestry systems are among the key FLR measures championed in highly degraded landscapes in Ethiopia. This study helps policymakers and FLR implementors identify erosion risk areas for future FLR activities. Thereby, it contributes to achieving the country’s restoration commitment.

Spatial assessment of soil erosion by water using RUSLE model, remote sensing and GIS: a case study of Mellegue Watershed, Algeria-Tunisia.

Soil erosion is an important global phenomenon that can cause many impacts, like morphometry and hydrology alteration, land degradation and landslides. Moreover, soil loss has a significant effect on agricultural production by removing the most valuable and productive top soil's profile, leading to a reduction in yields, which requires a high production budget. The detrimental impact of soil erosion has reached alarming levels due to the exacerbation of global warming and drought, particularly in the arid climates prevalent in Tunisia and Algeria and other regions of North Africa. The influence of these environmental factors has been especially evident in the catchment of Mellegue, where profound vegetation loss and drastic changes in land use and cover, including the expansion of urban areas and altered agricultural practices, have played a significant role in accelerating water-induced soil loss between 2002 and 2018. The ramifications of these developments on the fragile ecosystems of the region cannot be overlooked. Accordingly, this study aimed to compare soil losses between 2002 and 2018 in the catchment of Mellegue, which is a large cross-border basin commonly shared by Tunisian-Algerian countries. The assessment and mapping of soil erosion risk were carried out by employing the Revised Universal Soil Loss Equation (RUSLE). This widely recognised equation provided valuable insights into the potential for erosion. Additionally, changes in land use and land cover during the same period were thoroughly analysed to identify any factors that may have contributed to the observed risk. By integrating these various elements, a comprehensive understanding of soil erosion dynamics was achieved, facilitating informed decision-making for effective land management and conservation efforts. It requires diverse factors that are integrated into the erosion process, such as topography, soil erodibility, rainfall erosivity, anti-erosion cultivation practice and vegetation cover. The computation of the various equation factors was applied in a GIS environment, using ArcGIS desktop 10.4. The results show that the catchment has undergone significant soil water erosion where it exhibits the appearance of approximately 14,000 new areas vulnerable to erosion by water in 2018 compared to 2002. Average erosion risk has also increased from 1.58 t/ha/year in 2002 to 1.78 in 2018, leading to an increase in total estimated soil loss of 54,000 t/ha in 2018 compared to around 25,500 t/ha in 2002. Maps of erosion risk show that highly eroded areas are more frequent downstream of the basin. These maps can be helpful for decision-makers to make better sustainable management plans and for land use preservation.

Soil Erosion Risk Assessment Using Corine Model: A Case Study in Shwan Sub basin, Kirkuk, Iraq

Water erosion is one of the most important problems and challenges facing the optimal management of natural resources, especially soil and water resources, because of its impact on soil degradation. This study aimed to classify the risk of soil water erosion and clarify its distribution in the Shwan Basin in Kirkuk Governorate - Iraq based on the Corine model.In the first stage of the work, the soil erodibilty, erosivity and slope factors were determined, classified and mapped according to the degree of their impact on soil erosion.The potential soil erosion risk map was prepared using Arc GIS 10.4.1.In the second stage, the land cover factor was calculated and classified according to the degree of protection. In the last stage, the actual soil erosion risk map was prepared by multiplying the class of land cover with the map of potential soil erosion risk over the entire study area.The study showed that 28.18% of the studied area is classified under a high risk, 39.57% represents as a medium risk and 32.25% is a low risk .The areas of severe soil erosion risk were concentrated in the southwestern part and some northern and central parts, and the areas of medium risk were concentrated in the northern, central and southern parts, while regarding the low actual risk, they were concentrated in the western parts and in random areas in the center and east of the study area.The results also showed that the Corine model for soil water erosion risk mapping is a highly effective and cost-effective approach.

Soil Erosion Risk Assessment Using Revised Universal Soil Loss Equation RUSLE Model: a Case Study in Shwan Sub basin, Kirkuk, Iraq

The revised universal soil loss equation (RUSLE) was used in order to predict the amounts of soil lost by water erosion in the study area. The equation depends mainly on the factors that affect soil erosion represented by soil characteristics, rain fall, topography, vegetation cover, and conservation factor. The study showed that the study area was divided into three classes according to the degree of severity. The class1, the low risk of soil erosion, concentrated in all western parts and some central parts of the study area, occupying an area of 42525.61 hectares, at a rate of 41% of the total area. The class 2, a moderate risk of soil erosion, occupied an area estimated at (40451.19) hectares (39%), spread in the northern, northeastern, some central and southern parts of the study area, while the class 3, the high risk of erosion, had an area of 20744.20 hectares (20% of the area of the region), concentrated in the eastern and southeastern parts of the study area. Generally, the total amounts of soil lost annually due to water erosion in the study area amounted to 1,570,748 tons. The results also showed that the RUSLE model of soil water erosion risk mapping is a highly effective and cost-effective approach.

RUSLE and AHP based soil erosion risk mapping for Jalpaiguri district of West Bengal, India

RUSLE and AHP based soil erosion risk mapping for Jalpaiguri district of West Bengal, India

Mapping sediment mobilization risks: Prioritizing results obtained at watershed and sub-watershed scales

Soils are key natural resources for the Earth’s system; however, human impacts, especially, soil erosion are considered serious threats. Therefore, identifying and assessing effective factors to understand erosion hot spots at different scales is critical to developing effective land management plans and ensuring the sustainability of the territory. This study was conducted to determine and prepare an erosion risk map, but to prioritize the survey at different scales, such as sub-basin and watershed ones. To achieve this goal, geographic information system (GIS) and remote sensing data (RS) were used combining the analysis network process method (ANP) and ICONA model (Institute for the Conservation of Nature). As study case, we selected the degraded areas of the Gorganrood watershed located in the north of Iran. The study area was obtained for very low, low, medium, high, and very high-risk classifications of 14.0, 21.4, 17.9, 31.3, and 15.4%, respectively. Results from the ICONA model also indicated that 12.8, 28.8, 22.1, 27.9, 8.5, and 0.03% belong to very low, low, medium, high, very high, and without risk of erosion, respectively. According to the validation results, it was found that the accuracy of ANP and ICONA models are 0.83 and 0.80, respectively, which indicates the suitability of the models for preparing the erosion map of the region is appropriate and useful for designing land management plans. We conclude that both models can be used to develop the erosion map potential and to prioritize sub-basins if a complete database of geomorphological characteriscs and human activities are accurate previously defined.

Modelling and mapping of soil erosion risk based on GIS and PAP/RAC guidelines in the watershed of Tassaoute (Central High-Atlas, Morocco)

Morocco watersheds, which provided many ecosystem services necessary for the socio-economic life of rural communities, are experiencing significant change and environmental problems. Therefore, examining potential soil erosion considered a major problem in the Moroccan highlands is very important to prioritize high erosion severity areas. Keeping in view of the above aspects, the present study aimed to evaluate and map areas at risk of water erosion in the upstream Tassaoute watershed (central High Atlas, Morocco), using the Priority Action Program/Regional Activity Center (PAP/RAC) method associated with Geographic Information Systems (GIS) and remote sensing. The PAP/RAC approach consisted of integrating the natural factors that influence water erosion, namely slope, lithology, vegetation cover and land use. This method provided an accurate cartographic product that reflects the reality of the state of soil degradation and the qualitative assessment of erosion. The generated erosion risk map of the study area showed that the phenomenon of erosion threatens this basin, especially in the middle and downstream, such that 40% of the basin surface has significant erosion and the high and very high degree of erosion represented 27% of the total surface of the study area. These results therefore demonstrated the PAP/CAR model reliability in assessing and mapping of water erosion risks in the upstream Tassaoute basin.

Pemetaan Tingkat Bahaya Erosi dengan Pemanfaatan Teknologi Drone di DTA Cipaheut Sub DAS Cikapundung Hulu

Technology in the field of mapping is constantly evolving to provide convenience for human work. One of the innovations that are developing in today’s modern era is drone or Unmanned Aerial Vehicle (UAV). Erosion mapping and erosion measurements are carried out to determine the potential risk of erosion in certain areas. The erosion risk map shows the distribution of erosion hazard levels in an area. The objective of this research is to determine erosion prediction and erosion hazard levels spatially based on USLE (Universal Soil Loss Equation) method using drone. The used of UAV for collecting data to generate soil erosion risk map at detail scale based on USLE method is relatively infrequently done in Indonesia. The research was conducted in Cipaheut Watershed, Cikapundung Hulu Sub-watershed, Cimenyan, Cimenyan, Bandung Regency, West Java. The results of the study show that the role of drone is very helpful in mapping general conditions and land use spatially. In addition, drones are able to provide actual data sources to identify the physical factors needed in the USLE method of erosion calculations such as LS, C and P factors. Erosion prediction and erosion hazard levels can be calculated using data acquired from drones. There are 8 SPLs with a total land area of ​​225.10 Ha. SPL 5 with the use of dry land and steep slope have the highest erosion prediction values ​​of 703.1207 tons/ha/year and an erosion hazard index of 87.8901 tons/ha/year with a very high level of erosion hazard.

Integrated use of GIS, RS and USLE model for LULC change analysis and soil erosion risk mapping in the Lake Hawassa Watershed, Southern Ethiopia

Soil erosion is a worldwide problem leading to loss of nutrient rich top soil resulting in reduction of agricultural productivity that threatens the livelihood of agrarian societies. Assessment of soil loss due to water-induced erosion using Models is essential to quantify and map erosion prone areas for possible application of soil conservation measures. In the current study, GIS, RS, and USLE model were integrated with the aim to quantify LULC classes, estimate soil loss rates, and identify priority areas for conservation in the Lake Hawassa Watershed for the two temporal instants, 1975 and 2020. The use of thematic recoding and model maker during LULC classification process has improved the accuracy of thematic classes, producing more than 89% for both classified images. The LULC change analysis showed that agricultural land and built-up area expanded by 0.44% and 15.26% per annum, respectively over the last 45 years. The declines in vegetation cover coupled with steep slopes have contributed to the increase in soil loss from 1975 to 2020 by 65%. The model estimated annual soil erosion rate in 1975 that ranged from nil to 158.77 t ha−1 yr−1 with a mean annual soil loss rate of 25.16 t ha−1 yr−1. Likewise, the annual soil loss estimated for the year 2020 varied from zero to 262.48 t ha−1 yr−1 with a mean annual soil loss rate of 28.20 t ha−1 yr−1. Generally, a total of 23,580.59 and 27,783.35 tons of soil have been lost per annum for the year 1975 and 2020, respectively, which is a direct reflection of vegetation clearance. The identified highest three severity classes combined accounted for 50.54% in 1975 and 55.40% of the entire soil loss in 2020 and these losses occurred on areas less than 2% in both 1975 and 2020 periods. Besides, 23.48% and 31.04% of soil loss rates exceeded the established tolerable limit of soil loss for the study area. The integrated use of USLE model, GIS and RS have identified erosion risk areas that could help apply conservation measures.

Spatial Assessment of Soil Erosion Risk Using RUSLE Embedded in GIS Environment: A Case Study of Jhelum River Watershed

The watershed area of the Mangla Reservoir spans across the Himalayan region of India and Pakistan, primarily consisting of the Jhelum River basin. The area is rugged with highly elevated, hilly terrain and relatively thin vegetation cover, which significantly increases the river’s sediment output, especially during the monsoon season, leading to a decline in the reservoir’s storage capacity. This work assesses the soil erosion risk in the Jhelum River watershed (Azad Jammu and Kashmir (AJ&K), Pakistan) using the Revised Universal Soil Loss Equation of (RUSLE). The RUSLE components, including the conservation support or erosion control practice factor (P), soil erodibility factor (K), slope length and slope steepness factor (LS), rainfall erosivity factor (R), and crop cover factor (C), were integrated to compute soil erosion. Soil erosion risk and intensity maps were generated by computing the RUSLE parameters, which were then integrated with physical factors such as terrain units, elevation, slope, and land uses/cover to examine how these factors affect the spatial patterns of soil erosion loss. The 2021 rainfall data were utilized to compute the rainfall erosivity factor (R), and the soil erodibility (K) map was created using the world surface soil map prepared by the Food and Agriculture Organization (FAO). The slope length and slope steepness factor (LS) were generated in the highly rough terrain using Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM). The analysis revealed that the primary land use in the watershed was cultivated land, accounting for 27% of the area, and slopes of 30% or higher were present across two-thirds of the watershed. By multiplying the five variables, the study determined that the annual average soil loss was 23.47 t ha−1 yr−1. In areas with dense mixed forest cover, soil erosion rates ranged from 0.23 t ha−1 yr−1 to 25 t ha−1 yr−1. The findings indicated that 55.18% of the research area has a low erosion risk, 18.62% has a medium erosion risk, 13.66% has a high risk, and 11.6% has a very high erosion risk. The study’s findings will provide guidelines to policy/decision makers for better management of the Mangla watershed.

Soil Water Erosion Modeling in Tunisia Using RUSLE and GIS Integrated Approaches and Geospatial Data

Soil erosion is an important environmental problem that can have various negative consequences, such as land degradation, which affects sustainable development and agricultural production, especially in developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. The RUSLE model considers all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity, and anti-erosion farming practices. The equation is, thus, implemented under the Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate, estimated at more than 30 t/ha/year, and 4.20% is affected by high mean annual soil losses, ranging from 20 to 30 t/ha/year. The most eroded areas were identified in the southwestern, central, and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control on the global scale of Tunisia.

Contribution of G.I.S and Remote Sensing for the Risk Mapping of Soil Water Erosion at Saida Province (Western of Algeria)

Abstract Soil water erosion is a major aspect of landscape degradation in sub-wet to semi-arid Mediterranean environments. This problem has not been dealt with in detail in Algeria although it affects large areas. The objective of this study is to develop a methodology using remote sensing, the digital terrain model (DTM) and geographic information systems (GIS) to map areas with a risk of water erosion within the territory of Saida province and to produce a risk map that can be used as a reference document by the local authority. The presented methodology consists to incorporate three factors controlling the erosion: slope, material friability and land use. The resulting erosion risk map shows five areas of vulnerability to water erosion: very low, low, moderate, high and very high. Areas with high and very high risk of erosion cover more than 20% of the mountainous area and are consistent with our field observations. The methodology presented in this study can be generalized to all areas of the foothills of the Tellian Atlas, where erosion risks pose a threat to urban areas. This model is a tool to help implement a soil conservation plan in order to organise the measures to be applied and ensure sustainable soil management.

Quantifying the water soil erosion rate using RUSLE, GIS, and RS approach for Al-Qshish River Basin, Lattakia, Syria

Soil erosion is one of the most prominent geomorphological hazards threatening environmental sustainability in the coastal region of western Syria. The current war conditions in Syria has led to a lack of field data and measurements related to assessing soil erosion. Mapping the spatial distribution of potential soil erosion is a basic step in implementing soil preservation procedures mainly in the river catchments. The present paper aims to conduct a comprehensive assessment of soil erosion severity using revised universal soil loss equation (RUSLE) and remote sensing (RS) data in geographic information system (GIS) environment across the whole Al-Qshish river basin. Quantitatively, the annual rate of soil erosion in the study basin was 81.1 t ha−1 year−1 with a spatial average reaching 55.2 t ha−1 year−1. Spatially, the soil erosion risk map was produced with classification into five susceptible-zones: very low (41 %), low (40.5%), moderate (8.9%), high (5.4%) and very high (4.2%). The current study presented a reliable assessment of soil loss rates and classification of erosion-susceptible areas within the study basin. These outputs can be relied upon to create measures for maintaining areas with high and very high soil erosion susceptibility under the current war conditions.

Spatial-temporal dynamic impact of changes in rainfall erosivity and vegetation coverage on soil erosion in the Eastern Mediterranean.

In Syria, soil erosion (SoEr) by water is one of the major challenges for sustainability. Thus, the main goals of this research were to evaluate the spatial changes of SoEr between 2000 and 2018 in the whole coastal basin (CB) of Syria and to provide a soil water erosion risk map for the study area. For this purpose, monthly rainfall data, the SoilGrids dataset, satellite image derived NDVI layers, and Digital Elevation Model (DEM) were collected. Through the integration of these layers into the Revised Universal Soil Loss Equation (RUSLE), under a Geographic Information System (GIS), soil loss was assessed. Also, the contribution of land cover changes and R factor on SoEr were evaluated. The outcomes of this assessment illustrated that the R factor ranged from 800 to 2600MJmmha-1h-1yr-1, while the soil erodibility factor (K factor) ranged from 0.048 to 0.035 ton ha MJ-1mm-1. The C factor (vegetation coverage) values ranged between 0.07 and 1 with a spatial average value of 0.44 for the 2000-2009 period and 0.39 for the 2010-2018 interval. The output of RUSLE revealed that average annual SoEr was of 21.35 ton ha-1 y-1 (± 38) for 2000-2009 and 22.47 ton ha-1 y-1(± 41.8) for 2010-2018. Interestingly, the increased SoEr caused by the R factor was dominant (34.65%), followed by changes in both C factor and R factor (13.34%). However, decrease of SoEr rates is due to the increase of the C factor accounting for 36.82% of the CB. The outcome of this research can provide constructive spatial insights for rehabilitation plans for the post-war phase of Syria.

DETERMINATION OF THE IMPACT OF FOREST FIRES ON SOIL EROSION RISK BY USING THE ICONA MODEL: A CASE STUDY OF AYVALI DAM WATERSHED

Soil erosion in dam watersheds is a crucial phenomenon since dams have become a critical component of economic development for many countries. Therefore, the expected increase in both forest fires and heavy rains in the Mediterranean region poses a threat to the dam watersheds. The increase of these two phenomena will cause a serious increase in soil erosion after forest fires in dam watersheds. Therefore, revealing the possible effects of forest fires on soil erosion risk will be extremely beneficial for taking proactive measures in the management of dam watersheds. So, the goal of this study is to reveal the soil erosion risk and to determine the effect of possible forest fires on the soil erosion risk in the Ayvalı dam watershed. The ICONA model was used to reveal the soil erosion risk in the study area. The effect of forest fires was determined by scenario analysis. In the forest fire scenario, it is assumed that all forests in the study area are burned. Considering this scenario, a new soil erosion risk map was produced with the model. Then these two maps were compared. The results showed that 70.33% of the study area faced very high erosion risk, while 21.65%, 7.19%, 0.77%, and 0.05% of it had high, medium, low, and very low erosion risk, respectively. This potentially very high risk results from the steep slopes, high soil erodibility, and sparse vegetation density in the study area. As a result of the fire scenario, it was determined that while the areas with the very high risk increased by 18.11%, areas with high, medium, low, and very low risk decreased by 48.55%, 26.36%, 35.43%, and 100%, respectively. The findings can be a guide for decision-makers to prioritize necessary precautions depending on the soil erosion potential before and after forest fires.

Assessing soil erosion risk in a peri-urban catchment of the Lake Victoria basin.

Soil erosion and sedimentation contribute to deteriorating water quality, adverse alterations in basin hydrology and overall ecosystem biogeochemistry. Thus, understanding soil erosion patterns in catchments is critical for conservation planning. This study was conducted in a peri-urban Inner Murchison Bay (IMB) catchment on the northern shores of Lake Victoria since most soil erosion studies in Sub-Saharan Africa have been focused on rural landscapes. The study sought to identify sediment sources by mapping erosion hotspots using the revised universal soil loss equation (RUSLE) model in appendage with field walks. RUSLE model was built in ArcGIS 10.5 software with factors including: rainfall erosivity, soil erodibility, slope length and steepness, land cover and support practices. The model was run, producing an erosion risk map and field assessments conducted to ground-truth findings and identify other hotspots. The percentage areas for RUSLE modelled erosion rates were: 66.8% for 0-2 tha-1year-1; 10.8% for 2-5 tha-1year-1; 10.1% for 5-10 tha-1year-1; 9% for 10-50 tha-1year-1 and 3.3% for 50-100 tha-1year-1. Average erosion risk was 7 tha-1year-1 and the total watershed erosion risk was 197,400 tyear-1, with croplands and steep areas (slope factor > 20) as the major hotspots (> 5 tha-1year-1). Field walks revealed exposed soils, marrum (gravel) roads and unlined drainage channels as other sediment sources. This study provided the first assessment of erosion risk in this peri-urban catchment, to serve as a basis for identifying mitigation priorities. It is recommended that tailored soil and water conservation measures be integrated into physical planning, focusing on identified non-conventional hotspots to ameliorate sediment pollution in Lake Victoria.

Assessment of soil erosion risk using an integrated approach of GIS and Analytic Hierarchy Process (AHP) in Erzurum, Turkiye

Assessing soil erosion hazards and mapping the spatial distribution of soil erosion have an essential role in sustainable forest management. In this study, the potential soil erosion risk was evaluated through the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) in the Oltu forest planning unit, Erzurum. Seven erosion-related criteria, including slope, bedrock type, relative relief, drainage density and frequency, rainfall, and land use/land cover (LULC) were used for the present assessment. According to the AHP analysis, the slope was the most influential factor (21%) followed by bedrock type (19%), land cover (17%), and relative relief (14%) in the soil erosion process. The soil erosion risk in the study area was strongly influenced by the LULC where 59.46% is bare land with high erosion risk and 12.07%, with the lowest risk, is in an area with any forest cover. The estimated soil erosion risk was classified into five different classes namely very low, low, moderate, high, and very high. The results showed that this study area is highly prone to soil erosion. The larger proportion of the area (39.16%) is exposed to high to very high erosion, mainly determined by forest cover and geomorphology. To analyze the accuracy of the soil erosion risk map, 40 points were selected randomly in this study area. In these points, predicted values were compared to the real values obtained by Google Earth-colored images. The area under the ROC curve (AUC) method was applied to validate the efficiency of the AHP which showed a satisfactory accuracy of 81.00%. Findings presented that including the more influencing factors with a slope instead of including only the slope contributes to a more accurate erosion risk map. This study highlighted that GIS-based multi-criteria decision-making is a valuable and practical tool for decision-makers and land managers in creating soil erosion susceptibility maps and determining high-priority areas that require conservation measures for sustainable land use management by reducing the economic and ecological impacts of soil loss. Also, this approach can be practically applied in other planning units.