Annual Soil Loss Rate Research Articles

Impacts of land use and soil conservation measures on runoff and soil loss from two contrasted soils in the black soil region, northeastern China

AbstractRunoff and soil loss characteristics on slopes and their responses to soil conservation measures and soil properties have not been fully understood. In the present study, runoff and sediment data from runoff plots with two contrasted soils (i.e., Phaeozenm and Luvisols) at the Liangshigou (LSG) and Erdaogou (EDL) catchments were used to study soil loss characteristics for the black soil region, northeastern China. The implemented soil conservation measures including cross ridge tillage, hedgerow, terrace, level trough, and biological measures can effectively control soil loss at the two sites, whereas the downslope ridge tillage (DRT) and bare plots yielded annual soil loss rates of 1230 t km−2 year−1 in 2014–2015 and 2020 and 580 t km−2 year−1 in 2020 which were much higher than the tolerable value (i.e., 200 t km−2 year−1). Under the same treatments, the Phaeozenm plots yielded much higher soil loss rates than the Luvisols plots, resulting from more erosive rainfall events and higher soil erodibility at the LSG catchment. The typical black region with the Phaeozenm soil should be the priority area to be implemented with soil conservation measures in northeastern China.

Impact of land use/land cover changes on soil erosion risk in upper Mile River sub-watershed, North Eastern highlands of Ethiopia

ABSTRACT Unsustainable management of land resources aggravates land degradation. An accurate assessment of soil erosion is needed to reduce the problem of soil loss in highly fragile mountainous areas. Modeling the impact of LULCC on soil erosion is a vital process for watershed management planning. This study aimed to examine the effect of changing LULC on soil erosion in the upper Mile sub watershed, North Eastern highlands of Ethiopia. It was done by quantifying and evaluating soil erosion over years 1989–2018 in the area. The data was acquired from field surveys and secondary sources. The RUSLE was employed in a GIS environment to create soil erosion maps using the factors’. The soil loss model predicts 58.90%, 12.40%, 8.90%, and 8.89% of the sub-watershed has predicted as low, moderate, high and very high erosion risk, respectively. The mean annual soil loss rate of the area had increased from 16.07 tha−1 y−1 in 1989 to 17.26 tha−1 y−1 in 2003 and decrease to 12.94 tha−1y−1 in 2018. This was attributed to area closure interventions over the last two decades. The differences in soil erosion risk among the three periods suggested that changes in LULC have a significant impact on soil erosion risk.

Soil Loss and Its Impact on Crop Productivity Under Varying Land Uses in Demba-Gofa District, Southern Ethiopia

Soil erosion is the main cause of land degradation in Ethiopia and annually several tons of soil is removed away from the highlands. Thus, the purpose of this study is assessing soil erosion rates under various land uses and identifying the main contributing factors in Demba-Gofa woreda. A multistage random sampling approach was used to identify the research subjects. Questionnaire, key informant interview, FGDs, and field observations were used as data collection instruments to identify the major contributing factors of soil erosion in the studied woredas. Finally, the application of RUSLE model predicted that the lowest annual rate of soil loss observed at forest land is approximately 5.43 t ha-1 year, -1 whereas the highest amount of soil loss in crop land was about 36.01 t ha-1 year-1 and followed by in the grass land 22.10 t ha-1 year-1 and in the shrub land 11.29 t ha-1 year-1. The analysis of multiple linear regression model predicted that deforestation activities, educational level of farm household heads, mismanagement of cultivated lands, perception of local farmers on soil erosion, land size, farm distance, and slope of the land were found to significantly aggravates soil erosions at p < 0.05 level. Land sat satellite image with Arc-GIS 10.3 analysis for the last 15 years (2000-2017) of the three rural kebeles indicated that a total of 489.4 ha (56.3%) forest land was converted into shrub and grasslands. Thus, the national and the local governments should focus on reforestation, awareness creation on soil erosion and how farmers manage farmlands. Keywords: Soil erosion, natural resource degradation, RUSLE, Demba-Gofa

Estimation of Soil Erosion Using RUSLE Model and GIS Tools: A Study of Chilika Lake, Odisha

Abstract Chilika Lake is the largest coastal lagoon on the eastern coast of India. The aerial extension of the lake fluctuates between 1165 km2 to 906 km2. The opening of new inlet into the lake has enriched its biodiversity but also has increased the rate of siltation, which inturn affected the lake’s water holding capacity, causing ecological repercussions and impacting its flora and fauna. The RUSLE model integrated with remote sensing and GIS techniques was used to assess the soil loss in watershed of Chilika Lake. The model takes into account various factor viz. Crop /cover management factor (C), Soil erodibility factor (K), slope length (L), Conservation support practice factor (P), Rainfall erosivity factor (R), and steepness factor (S) to estimate potential soil loss. The results of the study reveal that 486.92 km2 i.e., 73.16% area of the Chilika watershed falls under least risk category of soil erosion, 44.17 km2 (6.6%) under moderate category, while, about 11% is at high, 8.8% at very high, and 0.043 at severe risk of soil erosion. The analysis estimates the annual average soil loss rate in the catchment of Chilika Lake to be 32.41 ton/ha/yr. The raster layers developed to study spatial soil loss indicate that the catchment of the lake is under the grip of soil erosion and siltation problems. Therefore, the study recommends immediate action of conservation and management planning processes to save the lake from further degradation.

Estimation of average annual soil loss rates and its prioritization at sub-watershed level using RUSLE: A case of Finca’aa, Oromiya, Western Ethiopia

Background: Because of natural and anthropogenic phenomena, most mountain areas experience significant soil loss. It is critical for watershed management to identify high soil loss rates and prone areas. Therefore, the present research aimed to estimate spatial annual soil loss rates and prioritize soil erosion prone areas of the Finca’aa watershed at sub-watershed level. Methods: The revised universal soil loss equation (RUSLE) model, the extension of geographic information system based on five parameters: rainfall erosivity (R), soil erodibility (K), slope length and slope steepness (LS), vegetation cover (C), and conservation techniques (P), was applied. This study also used weather data, a soil type map, a digital elevation model (DEM), and land use land cover, which were all analyzed using ArcGIS 10.4. Results: Annual soil loss rates ranged from negligible to 234 t ha-1 yr-1. The average rates of soil loss was 33.3 t ha-1 yr-1. Approximately 63.36% of the catchment was within and 36.64% of the catchment was above the maximum permissible level, respectively. Approximately 1.96% were in critical condition. Agricultural practices were the primary cause in the watershed’s mountain and hilly areas. Conclusion: The outcome is critical for planners and resource managers interested in long-term watershed management. Also, it is very important for sustainable growth development of 2030 agendas.

GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia

Land degradation in the form of soil erosion is a worldwide challenge and make environmental problem that affects crop yields, makes livelihoods difficult, and creates crises. The main objective of this study was to measure soil loss using the Revised Universal Soil Loss Equation (RUSLE) Model in Horo district, Western Ethiopia. RUSLE with a Geographical Information System (GIS) was used to quantify soil loss using rainfall, soil, a digital elevation model (DEM), and satellite image datasets as factor value inputs. Those factors are erosivity (R), erodibility (K), topography (LS), cover management (C), and conservation support practice (P) layer values that can be interactively used using weighted overlay in ArcGIS 10.8. The result shows that the maximum and minimum potential annual soil loss of the study area ranged from nil (0.01 t/ha/yr) on plain surfaces to 216.01 t/ha/yr. The average annual soil loss rate in the study area was 13.27 t ha/yr. The highest mean annual soil loss of 216.01 t/ha/yr were observed from farmland and it was the largest portion of the study area, which covered about 64243.02 ha and represented about 73.75% of the total. As a result, forest land (16383.23 ha) was the second-largest, accounting for 18.81% of the total area. Consequently, the study revealed that the farmland was more vulnerable to erosion than other land uses and land cover types. Hence, information on average annual soil loss is important for selecting appropriate conservation measures to reduce on-site soil loss and its off-site effects. Therefore, farmers and other expected bodies should have focused on soil conservation and management practices at the highest soil loss severity classes, which must get priority for conservation by stakeholders, agents, and the government.

Modelling Potential Soil Erosion and Sediment Delivery Risk in Plantations of Sri Lanka

The current trend in agricultural practices is expected to have a detrimental impact in terms of accelerating soil erosion. Assessment of the cumulative impact of various management strategies in a major plantation is a measure of the sustainably of soil resources. Thus, the current study aimed to develop the potential soil erosion map for a selected plantation (8734 ha in size) in tropical Sri Lanka using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Sediment Delivery Ratio (SDR) model. The estimated mean annual soil loss rate of the selected plantation was 124.2 t ha−1 ranging from 0.1 to 6903.3 t ha−1. Out of the total extent, ~49.5% of the area belongs to the low soil erosion hazard category (0–5 t ha−1 year−1) while ~7.8% falls into very high (25–60 t ha−1 year−1) and ~1.3% into extremely high (60 < t ha−1 year−1) soil erosion hazard classes. The rainfall erosivity factor (R) for the entire study area is 364.5 ± 98.3 MJ mm ha−1 hr−1. Moreover, a relatively higher correlation was recorded between total soil loss and R factor (0.3) followed by C factor (0.2), P factor (0.2), LS factor (0.1), and K factor (<0.1). It is evident that rainfall plays a significant role in soil erosion in the study area. The findings of this study would help in formulating soil conservation measures in the plantation sector in Sri Lanka, which will contribute to the country’s meeting of the UN Sustainable Development Goals (SDGs).

Quantify soil erosion and sediment export in response to land use/cover change in the Suha watershed, northwestern highlands of Ethiopia: implications for watershed management

Soil erosion accelerated by human activities is a critical challenge affecting soil health, agricultural productivity, food security and environmental sustainability in the highlands of Ethiopia. The aim of this study was to examine the dynamics of soil loss and sediment yield potential, and identify soil erosion hotspots using RUSLE with GIS in the Suha watershed, north western highlands of Ethiopia. Digital Elevation Model, LU/LC, rainfall, soil, and conservation practice were used as input data for RUSLE model. The estimated total annual soil loss for the entire watershed increased from 1.22 million tons in 1985 to 2.43 million tons in 2019, with average annual soil loss rates of 15.2 t ha−1 yr−1 and 31.4 t ha−1 yr−1 respectively. Total sediment yield also increased from 317.52 to 630.85 thousand tons over the past 35 years. In addition, the area of soil erosion hotspots changed from 15.2% (12,708 ha) to 32% (25,660 ha) during the same periods. Sub watershed 1, 2, 15, 17, 18, and 23 are severely degraded parts of the watershed. Expansion of agriculture and bare land as the expenses of other land use types over the past 35 years could be the major causes of extensive soil erosion risk in the watershed. Besides its temporal variability, soil loss and sediment export also showed variation between land use/cover classes. The estimated results of soil loss and sediment yield as well as soil erosion hotspots revealed that the soil erosion risk is progressively increasing during the study periods. Unless action is taken and the current condition is reversed, it will critically threat the livelihoods of the community in the watershed. Generally, the results underscore urgent demand for integrated and effective watershed management strategies.

Prediction of soil erosion and sediment transport in a mountainous basin of Taiwan

Soil erosion substantially implicates global nutrient and carbon cycling of the land surface. Its monitoring is crucial for assessing and managing global land productivity and socio-economy. The Zhuoshui River Basin, the largest catchment, in Taiwan is highly susceptible to soil erosion by water due to extremely high rainfall, rugged terrain, easily eroded soil, and intensively agricultural cultivation over the steep land. Hence, this study examines the annual soil erosion rate for 2005, 2011, and 2019 and the average long-term soil erosion and sediment yield (SY) during 2005–2019. Coupling of the Revised Universal Soil Loss Equation (RUSLE) and sediment delivery ratio (SDR) models is implemented using remote sensing and GIS techniques. The soil erosion rate is classified into five classes, namely mild (0–10 t ha−1 year−1), moderate (10–50 t ha−1 year−1), moderately severe (50–100 t ha−1 year−1), severe (100–150 t ha−1 year−1), and very severe (> 150 t ha−1 year−1). Over one half of the total area is categorized as moderate and moderately severe classes, and one-third of the whole basin as severe and very severe classes. Recently, mild and moderate classes increase, while moderately severe, severe, and very severe decrease. During 2005–2019, the annual soil loss rate ranges from 0.00 to 6,881.88 t ha−1 year−1 with an average rate of 122.94 t ha−1 year−1. Among the SDR models, the RUSLE combined with the SDR model with the length and slope gradient of mainstream shows satisfactory sediment yield estimation. Predictably, the downstream receives a massive sediment delivery from all upper streams (246.06 × 106 t year−1), and the percent bias values for all sub-basins are below ± 39.0%. The study provides a rapid approach to investigate soil erosion and sediment yield, and it can be applied to the other basins in Taiwan. More importantly, information about spatial patterns of soil erosion and SY is critical to establish suitable measures to achieve effective watershed planning and optimize the regional productivity and socio-economy. The proposed approach is potentially to identify risk areas, conduct scenario estimation for management, and perform spatiotemporal comparison of soil erosion, while adjustment in the empirical formulas of the proposed approach may be needed when it is applied to the other regions, especially outside Taiwan.

Assessing the effectiveness of community-based watershed management practices in reversing land degradation in the Finchwuha watershed, Gojjam, Ethiopia

ABSTRACT Land degradation is an evident and severe environmental problem in Ethiopia. Since 2003 community-based watershed management has been implemented in the study area to reduce land degradation. This study aimed to investigate to what extent the community-based watershed management is effective in rehabilitating the land. Woody vegetative cover, land use/cover (LULC) change and soil erosion rate were selected variables to examine the effectiveness of the management measures. The LULC and woody vegetative cover spatial datasets were created from Landsat satellite images of 2003 and 2019 using ERDAS IMAGINE 2016® and ArcGIS10.8®. The soil loss rate was modelled using geoinformation techniques combined with the Revised Universal Soil Loss Equation. To assess the perception of farmers involved in the watershed rehabilitation activities, qualitative data were collected through Focus Group Discussions and Key Informant interviews. The results showed that the average annual soil loss rate in the study area was 49.5 tonnes (t)/hectare (ha−1)/year(y−1) in 2003 and 23.8 t ha−1y−1 in 2019, which is a 52% decrease over 16 years. Woody vegetative cover and grassland increased by 11% and 103%, respectively. These figures and respondents’ responses, Focus Group Discussants and Key Informants showed that the community-based watershed management measures implemented in the study area were effective for improving vegetation cover and reducing soil loss (reducing land degradation). The sustainability of these achievements is contingent on the availability of a robust local organizational set-up complemented by the provision of natural resources development technologies, capacity building and security of land tenure. In sum, the findings in the study lead to conclude that the active involvement of farmers in land management and security of land tenure are effective approaches to reverse land degradation in the highlands of Ethiopia.

Modeling and Mapping of Soil Water Erosion Risks in the Srou Basin (Middle Atlas, Morocco) Using the EPM Model, GIS and Magnetic Susceptibility

Abstract The Oued Srou watershed located in the Middle Atlas Mountain of Morocco has been a subject of serious soil erosion problems due to the combination of natural factors and anthropic activities. Therefore, soil erosion hazard assessment and mapping can be handy to initiate remedial measures in the area. In this study, the improved Erosion Potential Model (EPM) integrated with GIS and remote sensing techniques is employed to map and assess the vulnerability of the Oued Srou watershed to the water erosion phenomenon and its impact on the silting of the Ahmed El Hansali dam. The results of the EPM model showed that the maximum annual soil loss rates were in the range of 5-652 m3/km2/year, with an average of 49 m3/km2/year. The delivery coefficient ratio showed that about 34433 t/year of the sediments reach the outlet of the watershed. The correlation analysis between all erosion factors revealed the following order of their importance in the water erosion control: soil sensitivity to erosion, soil protection, slope, erosive state, temperature, and rainfall. The magnetic susceptibility provided results on the evolution of soils; it showed that the most degraded soils had a high erosion rate. Generally, the stable soils not eroded showed an upward increase of magnetic susceptibility values in soil profiles; the evolution of magnetic susceptibility of degraded soils is disturbed. The magnetic susceptibility has also made it possible to highlight the source zones of sediments that reach the outlet of the watershed.

Soil loss estimation and prioritization using geographic information systems and the RUSLE model: a case study of the Anger River sub-basin, Western Ethiopia

Abstract Soil erosion is a major environmental problem that affects people's livelihoods and environmental health, particularly in developing countries. The present study aimed to identify soil erosion hotspot areas and prioritization in the Anger River sub-basin for conservation planning. The Revised Universal Soil Loss Equation (RUSLE) model and geospatial technologies were adopted to identify soil erosion hotspot areas and prioritization of the sub-watershed for conservation planning. Key parameters such as rainfall data, soil data, slope length and steepness factor, cover management, and conservation practices were used to estimate potential soil erosion risk in the sub-watershed. The results showed that the annual soil loss rate in the Anger River Sub-basin ranged between 0 and 932.6 t/ha/year with a mean annual soil loss of 83.7 t/ha/year. About 1,140.7 km2 (43.6%) and 220.6 km2 (8.4%) were categorized under very severe and severe soil loss types, respectively. The mid- and upstream areas, as well as the steeper parts of the sub-watershed, were highly exposed to soil erosion. This research provides tangible evidence in the decision-making process for soil and water conservation practices at a sub-watershed scale. Moreover, further research should be conducted at a micro-watershed scale to minimize the effects of soil erosion on the health and sustainability of the watershed.

RUSLE-based soil erosion assessment and erosion control evaluation in the Kabul Watershed

The development and conservation of water and soil in the Kabul River Basin are critical for ensuring its sustainable economic, social, and environmental progress. Since the watershed drains across the international borders into the Indus River Basin, it is key for both up- and downstream countries to thoroughly plan their resource development and management. Due to relief, soil and climatic conditions, as well as the recent deforestation the Kabul River Basin has been witnessing significant soil erosion by water, indicating the need for analyzing its specifics and deploying proper control measures. This study was carried out using the combination of the Revised Universal Soil Loss Equation (RUSLE) Model and GIS techniques to investigate the gross soil loss rates and their spatial distribution inside the target basin. Thus, the annual average soil loss rate was estimated at 15.1 tons/ha/year, pointing to severe local soil erosion. As to its spatial distribution, according to the study up to 99% of mean annual soil loss rates fell within the tolerable (0-5 tons/acre/year) category. Considering the soil loss rates, local topography, and community-based participatory approaches, the authors recommend conducting a further detailed diagnostic analysis to inform and support subsequent control measures such as deforestation prevention, construction of small check dams, terracing, trenching in hilly areas, revegetation (reforestation) of open- and grasslands, and rainwater harvesting.

Determination of Soil Characteristics and Degradation Using Geospatial Technologies in the Al Ahsa Oasis

Soil degradation associated with wind and water erosion and physical and chemical deterioration is increasing at an alarming rate worldwide. This research identified soil characteristics and spatial distribution of soil degradation risks in the Al Ahsa Oasis. Several quantitative analytical approaches used geospatial techniques, namely, ArcGIS, Erdas Imagine10, and ENVI 5.3. Six selected remote sensing indices were used, i.e. the salinity index (SI), normalised difference salinity index (NDSI), brightness index (BI), normalised differential vegetation index (NDVI), vegetation soil salinity index (VSSI), and soil adjusted vegetation index (SAVI) software. Field verification monitored the degradation of different types of soil. Samples were collected in May 2019 and processed using satellite images and mechanical and chemical laboratory analysis for 36 samples. The Universal Soil Loss Equation and climatic data were used to measure the annual soil loss rate in the Al Ahsa Oasis. Integration of these datasets resulted in a map of soil degradation values. The results show that the sampled oasis soils have degraded physically, chemically, and biologically. The average physical degradation was 9.93 g/cm3/year, the average biological degradation was 2.93%/year, and the average chemical degradation was 36.36 mmhos/cm.

Soil Loss Estimation within the Nun River Basin using Revised Universal Soil Loss Equation (RUSLE) integrated in Geographic Information Systems (GIS)

River bank erosion can cause undesired river bank expansion, distortion of the river course thereby slowing the river velocity and hindering the water carrying capacity of the river. Slow velocity of the river course can result in fast sediment accretion and accumulation at the bottom of the river. If these trends are not checked, the river may wind down and at best begin to become a delta at its middle course. The focus of this study is to apply GIS and analytical RUSLE equation to estimate soil loss within the Nun Basin.
 Core sediment samples were collected from relatively undisturbed areas (nine different stations) using Uwitec Triple sediment cutter. The sediment samples were processed in the lab for sediment particle size analysis (PSA) and Pb-210 atmospheric deposition with age using alpha spectrophotometer. Spatial rainfall data of the study location were employed to generate the rainfall erosivity map in order to determine the erosivity factor (R). Particle size distribution analysis was validated using Scanning Electron Micrograph (SEM) and integrated with Geographic Information Systems (GIS) was employed to create the soil erodibility map which was subsequently used to determine the erodibility factor (K). The cover management factor (P) was determined using the land use land cover map and the resulting data were then employed to model the river bank erosion around the study area.
 Result of the study revealed that the maximum annual average soil loss rate was estimated to be 0.66 tons/ha. /year around the Nun River based on GIS application using the Revised Universal Soil Loss Equation (RUSLE).

Impacts of land use/land cover and climate changes on soil erosion in Muga watershed, Upper Blue Nile basin (Abay), Ethiopia

BackgroundSoil erosion is one of the major threats in the Ethiopian highlands. In this study, soil erosion in the Muga watershed of the Upper Blue Nile Basin (Abay) under historical and future climate and land use/land cover (LULC) change was assessed. Future LULC was predicted based on LULC map of 1985, 2002, and 2017. LULC maps of the historical periods were delineated from Landsat images, and future LULC was predicted using the CA–Markov chain model. Precipitation for the future period was projected from six regional circulation models. The RUSLE model was used to estimate the current and future soil erosion rate in Muga watershed.ResultsThe average annual rate of soil erosion in the study area was increased from about 15 t ha−1 year−1 in 1985 to 19 t ha−1 year−1 in 2002, and 19.7 t ha−1 year−1 in 2017. Expansion of crop cultivation and loss of vegetation caused an increase in soil erosion. Unless proper measure is taken against the LULC changes, the rate of soil loss is expected to increase and reach about 20.7 t ha−1 year−1 in 2033. In the 2050s, soil loss is projected to increase by 9.6% and 11.3% under RCP4.5 and RCP8.5, respectively, compared with the baseline period. Thus, the soil loss rate is expected to increase under both scenarios due to the higher erosive power of the future intense rainfall. When both LULC and climate changes act together, the mean annual soil loss rate shows a rise of 13.2% and 15.7% in the future under RCP4.5 and RCP8.5, respectively, which is due to synergistic effects.ConclusionsThe results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse effect of LULC on soil loss. Furthermore, climate change will exacerbate the existing soil erosion problem and would need for vigorous proper conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria

Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.

Estimating water erosion using RUSLE, GIS and remote sensing in Wadi-Qandeel river basin, Lattakia, Syria

Soil erosion is the major prominent ecological risk threatening agricultural sustainability in the coastal region of western Syria. The ongoing war conditions in Syria has led to a lack of field data and measurements related to the spatial evolution of soil loss. Estimating the spatial distribution of potential soil loss is a fundamental procedure in applying the soil conservations measures within the river catchments. The current paper goals to conduct a comprehensive assessment of soil loss risk utilizing revised universal soil loss equation (RUSLE) and remote sensing (RS) data in geographic information system (GIS) environment across the entire Wadi-Qandeel river basin. Results indicate that the annual rate of soil loss in the study area was 93.02 t ha−1 ya−1 with a spatial average reaching 58.22 t ha−1 ya−1. Additionally, the soil loss risk map was generated with classification into five susceptible zones: very low (56.44%), low (24.69%), moderate (20.80%), high (2.98%), and very high (2.22%). The present assessment showed a reliable approach to soil erosion rates and categorization of erosion-sensitive zones within the study area. These outcomes can be relied upon to create mitigation procedures for maintaining zones with high and very high soil loss susceptibility under the ongoing war conditions in Syria.

Evaluation of Costs and Efficiencies of Urban Low Impact Development (LID) Practices on Stormwater Runoff and Soil Erosion in an Urban Watershed Using the Water Erosion Prediction Project (WEPP) Model

Storm events and soil erosion can adversely impact flood control, soil conservation, water quality, the recreation economy, and ecosystem biodiversity in urban systems. Urban Low Impact Development practices (LIDs) can manage stormwater runoff, control soil losses, and improve water quality. The Water Erosion Prediction Project (WEPP) model has been widely applied to assess the responses of hydrology and soil losses to conservation practices in agricultural and forested areas. This research study is the first to calibrate the WEPP model to simulate streamflow discharge in the Brentwood watershed in Austin, Texas and apply the calibrated WEPP model to assess the impacts of LIDs. The costs and impacts of various LID scenarios on annual water balance, and monthly average, and daily runoff volumes, and sediment losses at hillslopes and at the watershed outlet were quantified and compared. The LID scenarios identified that native planting in Critically Eroding Areas (CEAs), native planting in all suitable areas, native planting in CEAs with detention ponds, and native planting in all suitable areas with detention ponds could reduce the predicted average annual stormwater runoff by 20–24% and sediment losses by 86–94% at the watershed outlet, and reduce the average annual soil loss rates on hillslope profiles in sub-watersheds by 86–87% with the lowest costs (USD 2991/yr–USD 5257/yr). Watershed/field characteristics, locations, areas, costs, and the effectiveness of the LID practices were essential in choosing the LID scenarios. These research results can help guide decision-making on the selection and implementation of the most economical and suitable LID practices to strengthen the climate resilience and environmental sustainability of urban systems.

Assessment of water-induced soil erosion as a threat to cultural heritage sites: the case of Chania prefecture, Crete Island, Greece

ABSTRACT Among the environmental threats, the intensification of natural hazards, such as soil erosion may threaten the integrity and value of cultural heritage sites. In this framework, the present study’s main objective was to identify archaeological sites susceptible by soil erosion, taking the case study of Chania prefecture in Crete Island. Remotely sensed and other available geospatial datasets were analyzed in a GIS-based empirical model, namely Unit Stream Power Erosion and Deposition (USPED), to estimate the average annual soil loss and deposition rates due to water-induced erosion in the study area. The resultant erosion map was then intersected with the locations and surrounding zones of the known archaeological sites for identifying the sites and the portions of their vicinity being at risk. The results revealed that Chania prefecture and its cultural heritage are significantly affected by both soil loss and deposition processes. Between the two processes, soil loss was found to be more intensive, influencing a larger part of the prefecture (especially to the west) as well as a higher amount of archaeological sites. The extreme and high soil loss classes were also detected to cover the most considerable portion of the sites’ surrounding area. The identification of the archaeological sites being most exposed to soil erosion hazard can constitute a basis for cultural heritage managers in order to take preventive preservation measures and develop specific risk mitigation strategies.