Modelling soil erosion in a Mediterranean watershed: Comparison between SWAT and AnnAGNPS models

Sediment yield estimation and evaluating the best management practices in Nashe watershed, Blue Nile Basin, Ethiopia

Sediment yield estimation along with identification of soil erosion mechanisms is essential for developing sophisticated management approaches, assessing, and balancing different management scenarios and prioritizing better soil and water conservation planning and management. At the watershed scale, land management practices are commonly utilized to minimize sediment loads. The goal of this research was to estimate sediment yield and prioritize the spatial dispersion of sediment-producing hotspot areas in the Nashe catchment using the Soil and Water Assessment Tool (SWAT). Moreover, to reduce catchment sediment output, this study also aims to assess the effectiveness of certain management practices. For calibration and validation of the model, monthly stream flow and sediment data were utilized. The model performance indicators show good agreement between measured and simulated stream flow and sediment yields. The study examined four best management practice (BMP) scenarios for the catchment's designated sub-watersheds: S0 (baseline scenario), S1 (filter strip), S2 (stone/soil bunds), S3 (contouring), and S4 (terracing). According to the SWAT model result, the watershed's mean yearly sediment output was 25.96 t/ha. yr. under baseline circumstances. The model also revealed areas producing the maximum sediment quantities indicating the model's effectiveness for implementing and evaluating the sensitivity of sediment yield to various management strategies. At the watershed scale, treating the watershed with various management scenarios S1, S2, S3, and S4 decreased average annual sediment yield by 34.88%, 57.98%, 39.55%, and 54.77%, respectively. The implementations of the soil/stone bund and terracing scenarios resulted in the maximum sediment yield reduction. The findings of this study will help policymakers to make better and well-informed decisions regarding suitable land use activities and best management strategies.

The evaluation of N/P fate using the SPARROW model: a case study in an arid and semi-arid region, northern China

The assessment of nutrients' fate from source to sink is critical to water quality control. As an important ecological reserve in the arid and semi-arid regions of China, the Luanhe River Basin (LRB) has suffered from the deterioration of water quality, thus leading to the urgent management and control. However, few studies have devoted to exploring the fate of N/P contaminations for the entire watershed, due possibly to the large drainage area and heterogeneous watershed composition. Here, we attempt to illustrate N/P contaminations delivery and retention processes using the SPAtially Referenced Regression On Watershed attributes (SPARROW) model. The model reveals 97% of the spatial variability in the TN load and 81% in the TP load, verifying its availability and credibility. The results indicate that anthropogenic sources are dominating the N/P load, which account for 68.5% of N and 74.6% of P inputs. The results highlight the significant retention effects of streams and reservoirs, with 16.4% of N and 13.4% of P removals by streams and 24.3% of N and 10.7% of P removals by reservoirs, respectively. Ultimately, only 49,045.2 t yr^-1 (or 16.9%) of N and 1668.7 t yr^-1 (or 17.1%) of P being transported to the Bohai Sea. In addition, the analysis of influencing factors showed that regional characteristics (e.g., topography, rainfall), stream size, and delivery distance are potential factors affecting the riverine transport, whereas flow rate and surface area are primarily affecting the reservoirs attenuation. In the future, the watershed water quality management should pay more attention to source management and pollution legacy risks to achieve sustainable and healthy watershed development.

Load quantification and effect evaluation of urban non-point source pollution in the Licun River based on SWAT model

With the gradual control of point source pollution, the impact of urban nonpoint source pollution on river water quality is becoming more prominent. Regarding the current problem that nonpoint source pollution loads in urban basins are difficult to quantify and the impact on water quality is difficult to analyze, the Licun River basin in Qingdao was selected as the research object. Through the field survey and surface accumulation sampling analysis of the basin, the evaluation model of urban nonpoint source pollution was constructed by revising the land type data of the basin and the urban database of the SWAT model. The results showed that concentration of nitrate in precipitation was most sensitive to the simulation of nitrogen loading; organic P in baseflow was most sensitive to the simulation of phosphorus loading. The Nash-Sutcliffe efficiency coefficient (E_NS) and the coefficients of determination (R²) of the SWAT model for runoff, total phosphorus (TP), and total nitrogen (TN) in the simulation validation period meet the model requirements,indicating a good model fit. In addition, the spatial and temporal distribution characteristics of urban nonpoint source pollution of TN and TP in 2021 were analyzed. In July, rainfall-runoff from the Licun River basin was the most polluted.

A review of Soil and Water Assessment Tool (SWAT) studies of Mediterranean catchments: Applications, feasibility, and future directions

The Soil and Water Assessment Tool (SWAT) is a well-established eco-hydrological model that has been extensively applied to watersheds across the globe. This work reviews over two decades (2002-2022) of SWAT studies conducted on Mediterranean watersheds. A total of 260 articles have been identified since the earliest documented use of the model in a Mediterranean catchment back in 2002; of which 62% were carried out in Greece, Italy, or Spain. SWAT applications increased significantly in recent years since 86% of the reviewed papers were published in the past decade. A major objective for most of the reviewed works was to check the applicability of SWAT to specific watersheds. A great number of publications included procedures of calibration and validation and reported performance results. SWAT applications in the Mediterranean region mainly cover water resources quantity and quality assessment and hydrologic and environmental impacts evaluation of land use and climate changes. Nevertheless, a tendency towards a multi-purpose use of SWAT is revealed. The numerous examples of SWAT combined with other tools and techniques outline the model's flexibility. Several studies performed constructive comparisons between Mediterranean watersheds' responses or compared SWAT to other models or methods. The effects of inputs on SWAT outputs and innovative model modifications and improvements were also the focus of some of the surveyed articles. However, a significant number of studies reported difficulties regarding data availability, as these are either scarce, have poor resolution or are not freely available. Therefore, it is highly recommended to identify and develop accurate model inputs and testing data to optimize the SWAT performance.

A review of modeling pesticides in freshwaters: Current status, progress achieved and desirable improvements

This study comprises a critical review of modeling of pesticides in surface waters. The aim was to update the status of the use of models to simulate the fate of pesticides from diffuse sources. ISI papers were selected on Scopus and the information concerning the study areas, type of pesticides (herbicides, fungicides and insecticides), the model, and the methodology adopted (i.e., calibration and/or validation, spatial and temporal scales) were analyzed. The studies were carried out in Europe (55.5%), North America (22.3%), Asia (13.9%) and South America (8.3%). The Soil and Water Assessment Tool proved to be the most used model (45.95%). Herbicides were the most modeled pesticides (71.4%), followed by insecticides (18.2%) and fungicides (10.4%). The main herbicides modeled were atrazine, metolachlor, isoproturon, glyphosate, and acetochlor. Insecticides such as chlorpyrifos and metaldehyde. Chlorothalonil, and fungicides (i.e., tebuconazole) were the most widely investigated. Based on published studies, it was found that modeling approaches for assessing the fate of pesticides are constantly evolving and the model algorithms work well with diverse watershed conditions, management strategies, and pesticide properties. Several papers reported concentrations of pesticides exceeding ecotoxicological thresholds revealing that water contamination with pesticides used in agriculture and urban areas is a priority issue of current global concern.

Geospatial technology for assessment of soil erosion and prioritization of watersheds using RUSLE model for lower Sutlej sub-basin of Punjab, India

Erosion of soil by water coupled with human activities is considered as one of the most serious agents of land degradation, posing severe threat to agricultural productivity, soil health, water quality, and ecological setup. The assessment of soil erosion and recognition of problematic watersheds are pre-requisite for management of erosion hazards. In the present study, Revised Universal Soil Loss Equation (RUSLE) integrated with remote sensing (RS) and geographic information system (GIS) has been used to assess the soil erosion in lower Sutlej River basin of Punjab, India, and prioritize the watersheds for implementation of land and water conservation measures. The total basin area was about 8577 km² which was divided into 14 sub-watersheds with the area ranging from 357.8 to 1354 km². The data on rainfall (IMD gridded data), soil characteristics (FAO soil map), topography (ALOS PALSAR DEM) and land use (ESRI land use and land cover map) were prepared in the form of raster layers and overlaid together to determine the average annual soil loss. The results revealed that the average annual soil loss varied from 1.26 to 25 t ha^-1, whereas total soil loss was estimated to be 2,441,639 tonnes. The spatial distribution map of soil erosion showed that about 94.4% and 4.7% of the total area suffered from very slight erosion (0-5 t ha^-1 year^-1) and slight erosion (5-10 t ha^-1 year^-1), respectively, whereas 0.11% (9.38 km²) experienced very severe soil loss (> 25 t ha^-1 year^-1). Based on estimated average annual soil loss of sub-watersheds, WS8 was assigned the highest priority for implementation of soil and water conservation measures (323.5 t ha^-1 year^-1), followed by WS9 (303.8 t ha^-1 year^-1), whereas WS2 was given last priority owing to its lowest value of soil loss (122.02 t ha^-1 year^-1). The present study urges that conservation strategies should be carried out in accordance with the priority ranking of diverse watersheds. These findings can certainly be used to implement soil conservation plans and management practices in order to diminish soil loss in the river basin.

Modelling Water Flow and Soil Erosion in Mediterranean Headwaters (with or without Check Dams) under Land-Use and Climate Change Scenarios Using SWAT

The use of check dams is a common strategy to reduce soil erosion in the Mediterranean headwaters. However, the effects of these control works on water flow rates and sediment yields have been scarcely investigated under possible scenarios of climate and land-use changes. On this regard, the use of hydrological models, such as SWAT, provide reliable hydrological predictions under variable environmental conditions. To fill this gap, this study has evaluated the effectiveness of check dams on the hydrological response of a forest headwater in Calabria (Southern Italy) in comparison with an unregulated subcatchment with very similar environmental conditions. In this regard, the effects of different combined scenarios of climate change (through three GCMs and two RCPs applied to a time period of the next 80 years) and land use (forest, pasture, and cropland) on water flow rates and sediment yields in the two headwaters were analysed using the SWAT model. The SWAT model was first calibrated in a third headwater with very similar climatic, soil, and land-use conditions, and this verification showed a satisfactory prediction capacity of water flow rate. The water flow rate prediction capacity of the model was satisfactory (coefficients of determination and efficiency of Nash and Sutcliffe equal to 0.71 and 0.67, respectively, and percent bias of 14.9%). No significant differences were detected for the water flow rates and sediment yields between the two subcatchments (with or without check dams) among the different land-use and climate change scenarios. This was linked to the low hydrological response of both headwaters to the forcing actions, which influenced the low effectiveness of the control works. SWAT estimated higher values of both mean and maximum values of water flow rates and sediment yields under RCP2.6 compared with RCP8.5. Both water flow rates and sediment yields were predicted to be very low under all climate and land-use scenarios. The regulated headwater with check dams was predicted to always produce more runoff and erosion compared with the subcatchment without check dams. The increases were predicted to be up to 60% for the maximum flow rate and 30–35% for the sediment yield in forest land use under RCP2.6. Although there was a limitation in this study due to the lack of validation of the erosion data (due to unavailable records of sediment yield), this study demonstrated how the use of check dams in headwater catchments may be not effective for soil conservation purposes several decades after their installation in Mediterranean semiarid areas, where the water flow and erosion rate are limited.

The Effects of Soil Improving Cropping Systems (SICS) on Soil Erosion and Soil Organic Carbon Stocks across Europe: A Simulation Study

Healthy soils are fundamental for sustainable agriculture. Soil Improving Cropping Systems (SICS) aim to make land use and food production more sustainable. To evaluate the effect of SICS at EU scale, a modelling approach was taken. This study simulated the effects of SICS on two principal indicators of soil health (Soil Organic Carbon stocks) and land degradation (soil erosion) across Europe using the spatially explicit PESERA model. Four scenarios with varying levels and combinations of cover crops, mulching, soil compaction alleviation and minimum tillage were implemented and simulated until 2050. Results showed that while in the scenario without SICS, erosion slightly increased on average across Europe, it significantly decreased in the scenario with the highest level of SICS applied, especially in the cropping areas in the central European Loess Belt. Regarding SOC stocks, the simulations show a substantial decrease for the scenario without SICS and a slight overall decrease for the medium level scenario and the scenario with a mix of high, medium and no SICS. The scenario with a high level of SICS implementation showed an overall increase in SOC stocks across Europe. Potential future improvements include incorporating dynamic land use, climate change and an optimal spatial allocation of SICS.

Research on the Non-Point Source Pollution Characteristics of Important Drinking Water Sources

In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this study, we established the modified export coefficient model based on rainfall and terrain to investigate the pollution sources and characteristics of non-point source total nitrogen (TN) and total phosphorus (TP) throughout the Huangqian Reservoir watershed—which serves as an important potable water source for the main tributary of the lower Yellow River. The results showed that: (1) In 2018, the non-point source total nitrogen (TN) and total phosphorus (TP) loads in the Huangqian Reservoir basin were 707.09 t and 114.42 t, respectively. The contribution ratios to TN export were, from high to low, rural life (33.58%), farmland (32.68%), other land use types (20.08%), and livestock and poultry breeding (13.67%). The contribution ratios to TP export were, from high to low, rural life (61.19%), livestock and poultry breeding (21.65%), farmland (12.79%), and other land use types (4.38%). The non-point source pollution primarily originated from the rural life of the water source protection zone. (2) Non-point source TN and TP pollution loads and load intensities showed significantly different spatial distribution patterns throughout the water source protection area. Specifically, their load intensities and loads were the largest in the second-class protected zone, which is the key source area of non-point source pollution. (3) When considering whether to invest in agricultural land fertilizer control or rural domestic sewage, waste, and livestock manure pollution control, the latter is demonstrably more effective. Thus, in addition to putting low-grade control on agricultural fertilizer loss, to rapidly and effectively improve potable water quality, non-point source pollution should, to a larger extent, also be controlled through measures such as establishing household biogas digesters, introducing village sewage treatment plants, and improving the recovery rate of rural domestic garbage. The research results discussed herein provide a theoretical basis for formulating a reasonable and effective protection plan for the Huangqian Reservoir water source and can potentially be used to do the same for other similar freshwater resources.

Response of Variation of Water and Sediment to Landscape Pattern in the Dapoling Watershed

The relationship between water-sediment processes and landscape pattern changes has currently become a research hotspot in low-carbon water and land resource optimization research. The SWAT-VRR model is a distributed hydrological model which better shows the effect of land use landscape change on hydrological processes in the watershed. In this paper, the hydrological models of the Dapoling watershed were built, the runoff and sediment yield from 2006 to 2011 were simulated, and the relationship between landscape patterns and water-sediment yield was analyzed. The results show that the SWAT-VRR model is more accurate and reasonable in describing runoff and sediment yield than the SWAT model. The sub-basins whose soil erosion is relatively light are mostly concentrated in the middle reaches with a slope mainly between 0–5°. The NP, PD, ED, SPIIT, SHEI, and SHDI of the watershed increased slightly, and the COHESION, AI, CONTAG, and LPI showed a certain decrease. The landscape pattern is further fragmented, with the degree of landscape heterogeneity increasing and the connection reducing. The runoff, sediment yield and surface runoff are all extremely significantly negatively correlated with forest, which implies that for more complicated patch shapes of forest which have longer boundaries connecting with the patches of other landscape types, the water and sediment processes are regulated more effectively. Therefore, it can be more productive to carry out research on the optimization of water and soil resources under the constraint of carbon emission based on the SWAT-VRR model.

Water Erosion Monitoring and Prediction in Response to the Effects of Climate Change Using RUSLE and SWAT Equations: Case of R’Dom Watershed in Morocco

Soil erosion is an increasingly issue worldwide, due to several factors including climate variations and humans’ activities, especially in Mediterranean ecosystems. Therefore, the aim of this paper is: (i) to quantify and to predict soil erosion rate for the baseline period (2000–2013) and a future period (2014–2027), using the Revised Universal Soil Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT) model in the R’Dom watershed in Morocco, based on the opportunities of Remote Sensing (RS) techniques and Geographical Information System (GIS) geospatial tools. (ii) we based on classical statistical downscaling model (SDSM) for rainfall prediction. Due to the lack of field data, the model results are validated by expert knowledge. As a result of this study, it is found that both agricultural lands and bare lands are most affected by soil erosion. Moreover, it is showed that soil erosion in the watershed was dominated by very low and low erosion. Although the area of very low erosion and low erosion continued to decrease. Hence, we hereby envisage that our contribution will provide a more complete understanding of the soil degradation in this study area and the results of this research could be a crucial reference in soil erosion studies and also may serve as a valuable guidance for watershed management strategies.

Soil Erosion Assessment of Alpine Grassland in the Source Park of the Yellow River on the Qinghai-Tibetan Plateau, China

The source park of the Yellow River (SPYR), as a vital ecological shelter on the Qinghai-Tibetan Plateau, is suffering different degrees of degradation and desertification, resulting in soil erosion in recent decades. Therefore, studying the mechanism, influencing factors and current situation of soil erosion in the alpine grassland ecosystems of the SPYR are significant for protecting the ecological and productive functions. Based on the 137Cs element tracing technique and machine learning algorithms, five strategic variable selection algorithms based on machine learning algorithms are used to identify the minimal optimal set and analyze the main factors that influence soil erosion in the SPYR. The optimal model for estimating soil erosion in the SPYR is obtained by comparisons model outputs between the RUSLE and machine learning algorithms combined with variable selection models. We identify the spatial distribution pattern of soil erosion in the study area by the optimal model. The results indicated that: (1) A comprehensive set of variables is more objective than the RUSLE model. In terms of verification accuracy, the simulated annealing -Cubist model (R = 0.67, RMSD = 1,368 t km–2⋅a–1) simulation results represents the best while the RUSLE model (R = 0.49, RMSD = 1,769 t⋅km–2⋅a–1) goes on the worst. (2) The soil erosion is more severe in the north than the southeast of the SPYR. The average erosion modulus is 6,460.95 t⋅km–2⋅a–1 and roughly 99% of the survey region has an intensive erosion modulus (5,000–8,000 t⋅km–2⋅a–1). (3) Total erosion loss is relatively 8.45⋅108 t⋅a–1 in the SPYR, which is commonly 12.64 times greater than the allowable soil erosion loss. The economic monetization of SOC loss caused by soil erosion in the entire research area was almost $47.90 billion in 2014. These results will help provide scientific evidences not only for farmers and herdsmen but also for environmental science managers and administrators. In addition, a new ecological policy recommendation was proposed to balance grassland protection and animal husbandry economic production based on the value of soil erosion reclassification.

Combining Methods to Estimate Post-Fire Soil Erosion Using Remote Sensing Data

The increasing number of wildfires in southern Europe is making our ecosystem more vulnerable to water erosion; i.e., the loss of vegetation and subsequent runoff increase cause a shift in large quantities of sediment. Fire severity has been recognized as one of the most important parameters controlling the magnitude of post-fire soil erosion. In this paper, we adopted a combination of methods to easily assess post-fire erosion and prevent potential risk in subsequent rain events. The model presented is structured into three modules that were implemented in a GIS environment. The first module estimates fire severity with the Monitoring Trends in Burn Severity (MTBS) method; the second estimates runoff with rainfall depth–duration curves and the Soil Conservation Service Curve Number (SCS-CN) method; and the third estimates pre- and post-fire soil erosion. In addition, two post-fire scenarios were analyzed to assess the influence of fire severity on soil erosion: the former based on the Normalized Difference Vegetation Index (NDVI) and the latter on the Relative differenced Normalized Burn Index (RdNBR). The results obtained in both scenarios are quite similar and demonstrate that transitional areas, such as rangelands and rangelands with bush, are the most vulnerable because they show a significant increase in erosion following a fire event. The study findings are of secondary importance to the combined approach devised because the focal point of the study is to create the basis for a future tool to facilitate decision making in landscape management.

Impacts and social implications of landuse-environment conflicts in a typical Mediterranean watershed

In coastal watersheds, services and landuse favour coastal tourism and urbanization, depriving rural upstream of infrastructure and attention. This unbalanced management leads to an intensification of socioeconomic changes that generate a structural heterogeneity of the landscape and a reduction in the livelihoods of the rural population. The incessant dissociation between the objectives of the stakeholders triggers landuse-environment-economy conflicts which threaten to mutate large-scale development programs. Here, we used multi-assessment techniques in a Mediterranean watershed from Morocco to evaluate the effects of landuse change on water, vegetation, and perception of the rural population towards environmental issues. We combined complementary vegetation indexes (NDVI and EVI) to study long-term landuse change and phenological statistical pixel-based trends. We assessed the exposure of rural households to the risk of groundwater pollution through a water analysis supplemented by the calculation of an Integrated Water Quality Index. Later, we contrasted the findings with the results of a social survey with a representative sample of 401 households from 7 villages. We found that rapid coastal linear urbanization has resulted in a 12-fold increase in construction over the past 35 years, to the detriment of natural spaces and the lack of equipment and means in rural areas upstream. We show that the worst water qualities are linked to the negative impact of anthropogenic activities on immediately accessible water points. We observe that rural households are aware of the existence and gravity of environmental issues but act confusedly because of their low education level which generates a weak capacity to understand cause and effect relationships. We anticipate the pressing need to improve the well-being and education of the population and synergistically correct management plans to target the watershed as a consolidated system. Broadly, stakeholders should restore lost territorial harmony and reallocate landuse according to a sustainable environment-socioeconomic vision.

Ecological restoration is not sufficient for reconciling the trade-off between soil retention and water yield: A contrasting study from catchment governance perspective

Ecological restoration program (ERP) is widely recognized as an effective measure to combat land degradation and improve environmental quality. However, inappropriate ERPs lead to trade-offs between soil retention and water yield as well as conflicts of soil and water resources between the midstream and the downstream of catchment. This study aims to assess the efficiency of ERPs in soil erosion control and identify the trade-offs between soil retention and water yield through the lens of runoff and sediment regimes in contrasting catchments of the Loess Plateau (LP) and the Karst Plateau (KP). Although favorable climate and rapid vegetation restoration substantially reduced water erosion in both these areas, the hydrological responses were not the same because of climate differences. In the arid LP, water and energy variables correlated closely with vegetation cover. Excessive afforestation programs in drylands increased vegetation transpiration and soil evaporation, further exhausting soil water resources, and eventually causing water yield reduction. However, soil and water conservation programs (SWCPs) in the humid KP reduced sediment yield substantially, and the runoff remained stable. Significant runoff reduction in the midstream of the Yellow River aggravated water scarcity and threatened the downstream water demand. Meanwhile, sediment load decline in the LP and the KP impacted sediment deposition in the downstream and estuary formation. From the perspective of integrated catchment governance, human interventions including ERP and SWCP should be more sustainable and consider not only the target process at the local scale (intracoupling effect), but also unprecedented non-target process at the regional scale (telecoupling effect). In addition, it should allow for the supply-demand balance of competing soil and water resources to achieve the coordinated development of resources, environment, and production.

Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast

Runoff modeling of glaciated watersheds is required to predict runoff for water supply, aquatic ecosystem management and flood prediction, and to deal with questions concerning the impact of climate and land use change on the hydrological system and watershed export of contaminants of glaciated watersheds. A widely used pollutant loading model, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) was applied to simulate runoff from three watersheds in glaciated geomorphic settings. The objective of this study was to evaluate the suitability of the AnnAGNPS model in glaciated landscapes for the prediction of runoff volume. The study area included Sugar Creek watershed, Indiana; Fall Creek watershed, New York; and Pawcatuck River watershed, Rhode Island, USA. The AnnAGNPS model was developed, calibrated and validated for runoff estimation for these watersheds. The daily and monthly calibration and validation statistics (NSE > 0.50 and RSR < 0.70, and PBIAS ± 25%) of the developed model were satisfactory for runoff simulation for all the studied watersheds. Once AnnAGNPS successfully simulated runoff, a parameter sensitivity analysis was carried out for runoff simulation in all three watersheds. The output from our hydrological models applied to glaciated areas will provide the capacity to couple edge-of-field hydrologic modeling with the examination of riparian or riverine functions and behaviors.

Impact of Land Cover Change Due to Armed Conflicts on Soil Erosion in the Basin of the Northern Al-Kabeer River in Syria Using the RUSLE Model

Due to armed conflicts, the sudden changes in land cover are among the most drastic and recurring shocks on an international scale, and thus, have become a major source of threat to soil and water conservation. Throughout this analysis, the impact of land cover change on spatio-temporal variations of soil erosion from 2009/2010 to 2018/2019 was investigated using the Revised Universal Soil Loss Equation (RUSLE) model. The goal was to identify the characteristics and variations of soil erosion under armed conflicts in the basin of the Northern Al-Kabeer river in Syria. The soil erosion rate is 4 t ha−1 year−1 with a standard deviation of 6.4 t ha−1 year−1. In addition, the spatial distribution of erosion classes was estimated. Only about 10.1% of the basin is subject to a tolerable soil erosion rate and 79.9% of the study area experienced erosion at different levels. The soil erosion area of regions with no changes was 10%. The results revealed an increase in soil erosion until 2013/2014 and a decrease during the period from 20013/2014 to 2018/2019. This increase is a result of forest fires under armed conflict, particularly toward the steeper slopes. Coniferous forest as well as transitional woodland and scrub are the dominant land cover types in the upper part of the basin, for which the average post-fire soil loss rates (caused by factor C) were 200% to 800% higher than in the pre-fire situation. In the period from 2013/2014 to 2019/2020, soil erosion was mitigated due to a ceasefire that was agreed upon after 2016, resulting in decreased human pressures on soils in contested areas. By comparing 2009/2010 (before war) with 2018/2019 (at the end of the war stage), it can be concluded that the change in C factors slowed down the deterioration trend of soil erosion and reduced the average soil erosion rate in more than half of the basin by about 10–75%. The area concerned is located in the western part of the basin and is relatively far from the centers of armed conflicts. In contrast, the areas with increased soil erosion by about 60–400% are situated in the northeast and east, with shorter distances to armed conflict centers. These findings can be explained by forest fires, after which the burned forests were turned into agricultural land or refugee camps and road areas. Understanding the complex biophysical and socio-economic interactions of exposure to land loss is a key to guarantee regional environmental protection and to conserve the ecological quality of soil and forest systems.

Evaluating SWAT model performance, considering different soils data input, to quantify actual and future runoff susceptibility in a highly urbanized basin

The Soil and Water Assessment Tool (SWAT) is a physical model designed to predict the hydrological processes that could characterize natural and anthropized watersheds. The model can be forced using input data of climate prediction models, soil characteristics and land use scenarios to forecast their effect on hydrological processes. In this study, the SWAT model has been applied in the Aspio basin, a small watershed, highly anthropized and characterized by a short runoff generation. Three simulations setup, named SL1, SL2 and SL3, were investigated using different soil resolution to identify the best model performance. An increase of space requirement and calibration time has been registered in conjunction with the increasing soil resolution. Among all simulations, SL1 has been chosen as the best one in describing watershed streamflow, despite it was characterized by the lower soil resolution. A map of susceptibility to runoff for the entire basin was so created reclassifying the runoff amount of four years in five classes of susceptibility, from very low to very high. Eleven sub-basins, coinciding with the main urban settlements, were identified as highly susceptible to runoff generation. Considering future climate predictions, a slight increase of runoff has been forecasted during summer and autumn. The map of susceptibility successfully identified as highly prone to runoff those sub-basins where extreme flood events were yet recorded in the past, remarking the reliability of the proposed assessment and suggesting that this methodology could represent a useful tool in flood managing plan.

A Soil Erosion Indicator for Supporting Agricultural, Environmental and Climate Policies in the European Union

Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016. This small decrease of soil loss was due to a limited increase of applied soil conservation practices and land cover change observed at the EU level. The modelling results suggest that, currently, ca. 25% of the EU land has erosion rates higher than the recommended sustainable threshold (2 t ha−1 yr−1) and more than 6% of agricultural lands suffer from severe erosion (11 t ha−1 yr−1). The results suggest that a more incisive set of measures of soil conservation is needed to mitigate soil erosion across the EU. However, targeted measures are recommendable at regional and national level as soil erosion trends are diverse between countries which show heterogeneous application of conservation practices.

Using Machine Learning-Based Algorithms to Analyze Erosion Rates of a Watershed in Northern Taiwan

This study continues a previous study with further analysis of watershed-scale erosion pin measurements. Three machine learning (ML) algorithms—Support Vector Machine (SVM), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Artificial Neural Network (ANN)—were used to analyze depth of erosion of a watershed (Shihmen reservoir) in northern Taiwan. In addition to three previously used statistical indexes (Mean Absolute Error, Root Mean Square of Error, and R-squared), Nash–Sutcliffe Efficiency (NSE) was calculated to compare the predictive performances of the three models. To see if there was a statistical difference between the three models, the Wilcoxon signed-rank test was used. The research utilized 14 environmental attributes as the input predictors of the ML algorithms. They are distance to river, distance to road, type of slope, sub-watershed, slope direction, elevation, slope class, rainfall, epoch, lithology, and the amount of organic content, clay, sand, and silt in the soil. Additionally, measurements of a total of 550 erosion pins installed on 55 slopes were used as the target variable of the model prediction. The dataset was divided into a training set (70%) and a testing set (30%) using the stratified random sampling with sub-watershed as the stratification variable. The results showed that the ANFIS model outperforms the other two algorithms in predicting the erosion rates of the study area. The average RMSE of the test data is 2.05 mm/yr for ANFIS, compared to 2.36 mm/yr and 2.61 mm/yr for ANN and SVM, respectively. Finally, the results of this study (ANN, ANFIS, and SVM) were compared with the previous study (Random Forest, Decision Tree, and multiple regression). It was found that Random Forest remains the best predictive model, and ANFIS is the second-best among the six ML algorithms.

Source Apportionment of Nutrient Loads to a Mediterranean River and Potential Mitigation Measures

The aims of the study were to quantify nutrient loads from point and diffuse pollution sources in the Rio Mannu stream and to simulate mitigation measures for reducing nutrient loads delivered to the Santa Gilla wetland. The Soil and Water Assessment Tool model was used for simulating hydrology, nutrient balance and water quality. At the basin scale, the input from fertilisers was 80.3 kg ha−1 year−1 total nitrogen (TN) (87.6% of the total input) and 27.6 kg ha−1 year−1 of total phosphorus (TP) (99.8% of the total input). Atmospheric deposition and biological N-fixation together accounted for about 12% of the total TN input. The TN and TP from wastewater treatment plants (WWTPs) were about 14.2 t year−1 and 3.1 t year−1, respectively. Nutrient loads delivered to the river system differed among the sub-basins, with TP ranging from 0.2 kg ha−1 year−1 to 2.7 kg ha−1 year−1, and the sum of organic N and NO3-N ranging from 1.8 kg ha−1 year−1 to 22.9 kg ha−1 year−1. Under high flow conditions, NO3-N and TP accounted for 89% and 99% of the total load, respectively. The low flow contribution to the total load was very low, with NO3-N and TP accounting for 2.8% and 0.7%, respectively. However, the natural hydrological regime in the study area is intermittent, and low flow represents a critical condition for the water quality due to the high concentrations of TP and NO3-N from WWTP discharge. To improve the water quality, the reuse of treated wastewater from three WWTPs for irrigation purposes on olive cultivation, coupled with a 20% reduction in fertiliser application, was simulated. The results showed a reduction in nutrient loads at the outlet for all hydrological conditions. However, additional measures are needed for improving water quality.

Climate and land use change effects on soil erosion in two small agricultural catchment systems Fugnitz - Austria, Can Revull - Spain

Soil erosion represents one of the most important processes of land degradation in the world and is considered a serious threat to the provision of food supply, to human health and to terrestrial ecosystems. In Europe, soil erosion by water and tillage is responsible for the loss of fertile topsoil and therefore productive land. Under Global Change scenarios climate and land use are expected to impact soil loss and sediment discharge rates distinctly in contrasting climatic regions, further influenced by tillage practices. Soil erosion modeling is a valuable tool to estimate future changes and elucidate opportunities to mitigate future threats to soil loss and crop yield, ultimately leading to the development of Best Management Practices (BMPs). In this study, future change of soil erosion processes under the IPCC Representative Concentration Pathways RCP2.6 and RCP6.0, as well as a conventional tillage (CT) and a reduced tillage (RT) practice are investigated in two small agricultural catchments in Europe under contrasting climate; Can Revull in Spain and Fugnitz in Austria. We applied GeoWEPP, the Geospatial Interface for the Water Erosion Prediction Project, to model these two agricultural catchments at a fine spatial resolution. We demonstrate that tillage practice, precipitation and runoff are driving factors for soil erosion at both locations. Furthermore, we illustrate that tillage practices have a greater effect on soil erosion than climate change scenarios. RT could reduce soil erosion by more than 75% compared to CT practices. Under RCP6.0, future changes in runoff, hillslope soil loss and sediment discharge would be greater compared to RCP2.6, with different responses depending on the investigated climatic region. Linking soil erosion models on a fine spatial scale and with different management practices to downscaled global circulation models, can provide valuable input for the development of future BMPs to reduce soil loss in agricultural landscapes.

A European-Scale Investigation of Soil Erosion Threat to Subsurface Archaeological Remains

This communication emanates from the lack of a European-scale study for investigating the potential threats that subsurface archaeological remains face today due to soil loss by water. This research analyses the impact of soil loss on potential subsurface archaeological evidence by integrating open geospatial datasets deriving from two pertinent European studies. The first study’s dataset is related to soil erosion (soil loss provoked by water activity), which was reclassified into three groups alluding the level of threat on potential subsurface archaeological contexts, as follows: (1) areas presenting soil loss from 0 until 5 t/h per year, which are characterised as low threat areas; (2) areas presenting soil loss from 5 until 10 t/h per year, which are characterised as moderated threat; and (3) areas presenting soil loss beyond 10 t/h per year, which are considered as high-risk areas. The second study’s dataset refers to the capacity of soils to preserve specific archaeological materials, classified in four categories based on the properties of the archaeological material (bones, teeth, and shells (bones); organic materials (organics); metals (Cu, bronze, and Fe) (metals); and stratigraphic evidence (strati). Both datasets were imported into a Geographical Information System (GIS) for further synthesis and analysis, while the average threat of soil loss per year was evaluated in a country level (nomenclature of territorial units for statistics (NUTS) level 0). The overall results show that approximately 10% of European soils that potentially preserve archaeological remains are in high threat due to soil loss, while similar patterns—on a European level—are found for areas characterised with moderate to high risk from the soil loss. This study is the first attempt to present a proxy map for subsurface cultural material under threat due to soil loss, covering the entire European continent.

Modelling Impacts of a Municipal Spatial Plan of Land-Use Changes on Surface Water Quality—Example from Goriška Brda in Slovenia

Intensive agriculture causes nutrient leaching and accelerates erosion processes, which threatens the good quality status of surface waters, as proposed by the European Union (EU) Water Framework Directive. The purpose of this study was to define the impact of two alternative agricultural land-use change scenarios defined in a Municipal Spatial Plan on surface water quality by using the Agricultural Policy/Environmental eXtender (APEX) model. As experimental area, we chose a small Kožbanjšček stream catchment (1464 ha) situated in the Goriška Brda region in Slovenia. The area, due to favorable conditions for vineyards, is facing increasing deforestation. The change of 66.3 ha of forests to vineyards would increase the sediment, nitrate, and phosphorus loads in the stream by 24.8%, 17.1%, and 10.7%, respectively. With the implementation of vegetative buffer strips as a mitigation measure of the current situation, we could reduce the sediment, nitrate, and phosphorus loads by 17.9%, 11.1%, and 3.1%, respectively, while a combination of the two land-use change scenarios would result in a slight increase of the above-mentioned loads, corresponding to 0.61%, 2.1%, and 6.6%, respectively, compared to the baseline situation. The results confirm that, as we can increase pollution levels with deforestation, we can also reduce water pollution by choosing proper types of land management measures.

Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985-2009) and monthly suspended sediment load data (1985-2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R ²), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation's standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha^-1year^-1 on riparian lowlands of the Xinjiang main channel to 33 ton ha^-1year^-1 on mountain highlands, with a basin-wide mean of 19 ton ha^-1year^-1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha^-1year^-1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

Changes to soil conservation in the Three Gorges Reservoir Area between 1982 and 2015

Soil erosion is a major threat in the Three Gorges Reservoir Area (TGRA) of China. Since 1990, the Chinese government has launched a series of ecological restoration projects to promote soil conservation in the TGRA. To understand the effects of ecological restoration on soil conservation in the TGRA, we used the abrupt change analysis of soil mass from 1982 to 2015 and its drivers; soil mass was obtained with the universal soil loss equation at continental scale. We found that soil conservation and annual rainfall decreased in the TGRA over the study period. Abrupt change points of soil conservation occurred in 1984 and 2007. Soil conservation in the TGRA showed a dramatic decrease before 1984, a slow increase after 1984 as a result of climate, and a rapid increase after 2007 due to an increase in vegetation cover. From 1982 to 2015, climate change played a primary role in soil conservation changes and was more influential than topography and vegetation. However, ecological restoration was an important factor affecting soil conservation in the TGRA, and it needs to be promoted.

Global soil, landuse, evapotranspiration, historical and future weather databases for SWAT Applications

Large-scale distributed watershed models are data-intensive, and preparing them consumes most of the research resources. We prepared high-resolution global databases of soil, landuse, actual evapotranspiration (AET), and historical and future weather databases that could serve as standard inputs in Soil and Water Assessment Tool (SWAT) models. The data include two global soil maps and their associated databases calculated with a large number of pedotransfer functions, two landuse maps and their correspondence with SWAT's database, historical and future daily temperature and precipitation data from five IPCC models with four scenarios; and finally, global monthly AET data. Weather data are 0.5° global grids text-formatted for direct use in SWAT models. The AET data is formatted for use in SWAT-CUP (SWAT Calibration Uncertainty Procedures) for calibration of SWAT models. The use of these global databases for SWAT models can speed up the model building by 75-80% and are extremely valuable in areas with limited or no physical data. Furthermore, they can facilitate the comparison of model results in different parts of the world.

Soil erosion modelling: The new challenges as the result of policy developments in Europe

New challenges and policy developments after 2015 (among others, the Common Agricultural Policy (CAP), Sustainable Development Goals (SDGs)) are opportunities for soil scientists and soil erosion modellers to respond with more accurate assessments and solutions as to how to reduce soil erosion and furthermore, how to reach Zero Net Land Degradation targets by 2030. This special issue includes papers concerning the use of fallout for estimating soil erosion, new wind erosion modelling techniques, the importance of extreme events (forest fires, intense rainfall) in accelerating soil erosion, management practices to reduce soil erosion in vineyards, the impact of wildfires in erosion, updated methods for estimating soil erodibility, comparisons between sediment distribution models, the application of the WaTEM/SEDEM model in Europe, a review of the G2 model and a proposal for a land degradation modelling approach. New data produced from field surveys such as LUCAS topsoil and the increasing availability of remote sensing data may facilitate the work of erosion modellers. Finally, better integration with other soil related disciplines (soil carbon, biodiversity, compaction and contamination) and Earth Systems modelling is the way forward for a new generation of erosion process models.

Comparison of the alternative models SOURCE and SWAT for predicting catchment streamflow, sediment and nutrient loads under the effect of land use changes

Quantifying the water quantity and quality variations resulting from human induced activities is important for policy makers in view of increasing water scarcity and water pollution. Simple models can be robust tools in estimating the runoff from catchments, but do they also sufficiently reflect complex physio-chemical processes required for spatially-explicit simulation of soil-water interactions, and the resulting pollutant responses in catchments? Do these models respond sensitive to the impacts of different land use change representations? These questions are considered by applying the semi-distributed process-based catchment models SWAT and SOURCE to the Sixth Creek catchment in South Australia. Both models used similar data whereas inputs for SOURCE were generated from land-use based Functional Units (FUs), while FUs for SWAT were based on land use, soil and slope combinations. After satisfying calibration of both models for the outlet station of the catchment, the simulated flow by SOURCE produced high goodness of fit metrics, while nutrient loads simulated by SWAT were more realistic. Both models benefitted from using locally available Potential Evapotranspiration data for calibrating the hydrology. Scenarios of intensified land uses by two models showed more credible results for sediment and nutrient loads with the static approach when simulating the linear rather than the non-linear land use changes. The study has shown that informing decisions on the hydrology at catchment scale is well suited to less-complex models, whereas decisions on impact of land use change on water quality in catchments are better suited by models with process descriptions for soil-water interactions.

A Spatial Analysis to Define Data Requirements for Hydrological and Water Quality Models in Data-Limited Regions

The objective of the present work is a spatial analysis aimed at supporting hydrological and water quality model applications in the Canale d’Aiedda basin (Puglia, Italy), a data-limited area. The basin is part of the sensitive environmental area of Taranto that requires remediation of the soil, subsoil, surface water, and groundwater. A monitoring plan was defined to record the streamflow and water quality parameters needed for calibrating and validating models, and a database archived in a GIS environment was built, which includes climatic data, soil hydraulic parameters, groundwater data, surface water quality parameters, point-source parameters, and information on agricultural practices. Based on a one-year monitoring of activities, the average annual loads of N-NO3 and P-PO4 delivered to the Mar Piccolo amounted to about 42 t year−1, and 2 t year−1, respectively. Knowledge uncertainty in monthly load estimation was found to be up to 25% for N-NO3 and 40% for P-PO4. The contributions of point sources in terms of N-NO3 and P-PO4 were estimated at 45% and 77%, respectively. This study defines a procedure for supporting modelling activities at the basin scale for data-limited regions.

Simulation of Flow and Agricultural Non-Point Source Pollutant Transport in a Tibetan Plateau Irrigation District

Flow and transport processes in soil and rock play a critical role in agricultural non-point source pollution (ANPS) loads. In this study, we investigated the ANPS load discharged into rivers from an irrigation district in the Tibetan Plateau and simulated ANPS load using a distributed model. Experiments were conducted for two years to measure soil water content and nitrogen concentrations in soil and the quality and quantity of subsurface lateral flow in the rock and at the drainage canal outlet during the highland barley growing period. A distributed model, in which the subsurface lateral flow in the rock was described using a stepwise method, was developed to simulate flow and ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) transport processes. Sobol’s method was used to evaluate the sensitivity of simulated flow and transport processes to the model inputs. The results showed that with a 21.2% increase of rainfall and irrigation in the highland barley growing period, the average NH4+-N and NO3−-N concentrations in the soil layer decreased by 10.8% and 14.3%, respectively, due to increased deep seepage. Deep seepage of rainfall water accounted for 0–52.4% of total rainfall, whereas deep seepage of irrigation water accounted for 36.6–45.3% of total irrigation. NH4+-N and NO3−-N discharged into the drainage canal represented 19.9–30.4% and 19.4–26.7% of the deep seepage, respectively. The mean Nash–Sutcliffe coefficient value, which was close to 0.8, and the lowest values of root mean square errors, the fraction bias, and the fractional gross error indicated that the simulated flow rates and nitrogen concentrations using the proposed method were very accurate. The Sobol’s sensitivity analysis results demonstrated that subsurface lateral flow had the most important first-order and total-order effect on the simulated flow and NH4+-N and NO3−-N concentrations at the surface drainage outlet.

Effects of Climate Change and Human Activities on Soil Erosion in the Xihe River Basin, China

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