Modeling Approaches to Assess Soil Erosion by Water at the Field Scale with Special Emphasis on Heterogeneity of Soils and Crops

Information on soil erosion and related sedimentation processes are very important for natural resource management and sustainable farming. Plenty of models are available for studying soil erosion but only a few are suitable for dynamic soil erosion assessments at the field-scale. To date, there are no field-scale dynamic models available considering complex agricultural systems for the simulation of soil erosion. We conducted a review of 51 different models evaluated based on their representation of the processes of soil erosion by water. Secondly, we consider their suitability for assessing soil erosion for more complex field designs, such as patch cropping, strip cropping and agroforestry (alley-cropping systems) and other land management practices. Several models allow daily soil erosion assessments at the sub-field scale, such as EPIC, PERFECT, GUEST, EPM, TCRP, SLEMSA, APSIM, RillGrow, WaNuLCAS, SCUAF, and CREAMS. However, further model development is needed with respect to the interaction of components, i.e., rainfall intensity, overland flow, crop cover, and their scaling limitations. A particular shortcoming of most of the existing field scale models is their one-dimensional nature. We further suggest that platforms with modular structure, such as SIMPLACE and APSIM, offer the possibility to integrate soil erosion as a separate module/component and link to GIS capabilities, and are more flexible to simulate fluxes of matter in the 2D/3D dimensions. Since models operating at daily scales often do not consider a horizontal transfer of matter, such modeling platforms can link erosion components with other environmental components to provide robust estimations of the three-dimensional fluxes and sedimentation processes occurring during soil erosion events.Peer reviewe

Gis-based gully erosion susceptibility mapping: a comparison of computational ensemble data mining models

Gully erosion destroys agricultural and domestic grazing land in many countries, especially those with arid and semi-arid climates and easily eroded rocks and soils. It also generates large amounts of sediment that can adversely impact downstream river channels. The main objective of this research is to accurately detect and predict areas prone to gully erosion. In this paper, we couple hybrid models of a commonly used base classifier (reduced pruning error tree, REPTree) with AdaBoost (AB), bagging (Bag), and random subspace (RS) algorithms to create gully erosion susceptibility maps for a sub-basin of the Shoor River watershed in northwestern Iran. We compare the performance of these models in terms of their ability to predict gully erosion and discuss their potential use in other arid and semi-arid areas. Our database comprises 242 gully erosion locations, which we randomly divided into training and testing sets with a ratio of 70/30. Based on expert knowledge and analysis of aerial photographs and satellite images, we selected 12 conditioning factors for gully erosion. We used multi-collinearity statistical techniques in the modeling process, and checked model performance using statistical indexes including precision, recall, F-measure, Matthew correlation coefficient (MCC), receiver operatic characteristic curve (ROC), precision-recall graph (PRC), Kappa, root mean square error (RMSE), relative absolute error (PRSE), mean absolute error (MAE), and relative absolute error (RAE). Results show that rainfall, elevation, and river density are the most important factors for gully erosion susceptibility mapping in the study area. All three hybrid models that we tested significantly enhanced and improved the predictive power of REPTree (AUC=0.800), but the RS-REPTree (AUC= 0.860) ensemble model outperformed the Bag-REPTree (AUC= 0.841) and the AB-REPTree (AUC= 0.805) models. We suggest that decision makers, planners, and environmental engineers employ the RS-REPTree hybrid model to better manage gully erosion-prone areas in Iran

GIS-Based Soil Erosion Modeling for Assessing Land Suitability in the Urban Watershed of Tallo River, South Sulawesi, Indonesia

Urban watershed is a discrete and complex system where a diverse number of factors govern its quality and health. Soil erosion by water is the most dominant factor that determines a watershed quality, and considered as one of the most significant forms of land degradation that affects sustained productivity of land use. The principal aim of this paper is to utilise spatial-based soil erosion information to assess land suitability at a\ud watershed level. The specific aim is three-fold: (i) to develop techniques based on a GIS in the parameterisation of a soil erosion model, which is designed for use at a large scale assessment; (ii) to assess and map the spatial distribution of average annual rate of soil losses in; (iii) to employ such related concept as soil loss tolerance to\ud determine land suitability at a watershed level. An analytical procedure is used to analyse an urban watershed of Tallo River, in South Sulawesi, Indonesia, with a total area of 43,422 ha. The procedure is executed using RUSLE (Revised Universal Soil Loss Equation), in a GIS environment, utilising available information in the region (including climate, soil, slope, and land use and land conservation practices), and with the assistance of ground surveys. The results indicate that around 56.5% of the area experience annual soil loos of less than 1 ton/ha/year, while erosion rate of more than 25 ton/ha/year covers a total area of 8.9%. Due to a good ground cover in forested land, most of the slopping areas have actual soil losses of 1-5 ton/ha/year. This study reveals\ud that areas categorized as high risk, where only forest cover allowed consist of 9.4%, and those with very low risk cover a total area of 5.4%. Most of the study region (around 84%) experience moderate and low erosion risk, and suitable for cropping with special management practices (CS) + perennial crops (PC) + grass (GR) + and forest (FR). This study suggests that the outputs of this modeling procedure can be used for the identification of land management units based on degradation levels, as well as the most suitable land use to be practiced on individual land units on a sustainable basis

Kvantificiranje stope erozije vodenog tla korištenjem pristupa RUSLE, GIS i RS za sliv rijeke Al-Qshish, Latakija, Sirija

Soil erosion is one of the most prominent geomorphological hazards threatening environmental sustainability in the coastal region of western Syria. The current war conditions in Syria has led to a lack of field data and measurements related to assessing soil erosion. Mapping the spatial distribution of potential soil erosion is a basic step in implementing soil preservation procedures mainly in the river catchments. The present paper aims to conduct a comprehensive assessment of soil erosion severity using revised universal soil loss equation (RUSLE) and remote sensing (RS) data in geographic information system (GIS) environment across the whole Al-Qshish river basin. Quantitatively, the annual rate of soil erosion in the study basin was 81.1 t ha−1 year−1 with a spatial average reaching 55.2 t ha−1 year−1. Spatially, the soil erosion risk map was produced with classification into five susceptible-zones: very low (41 %), low (40.5%), moderate (8.9%), high (5.4%) and very high (4.2%). The current study presented a reliable assessment of soil loss rates and classification of erosion-susceptible areas within the study basin. These outputs can be relied upon to create measures for maintaining areas with high and very high soil erosion susceptibility under the current war conditions.Erozija tla jedna je od najistaknutijih geomorfoloških opasnosti koja prijeti održivosti okoliša u obalnoj regiji zapadne Sirije. Trenutni ratni uvjeti u Siriji doveli su do nedostatka terenskih podataka i mjerenja vezanih za procjenu erozije tla. Kartiranje prostorne distribucije potencijalne erozije tla osnovni je korak u provedbi postupaka očuvanja tla uglavnom u riječnim slivovima. Ovaj rad ima za cilj provesti sveobuhvatnu procjenu ozbiljnosti erozije tla korištenjem revidirane univerzalne jednadžbe gubitka tla (RUSLE) i podataka daljinske detekcije (RS) u okolišu geografskog informacijskog sustava (GIS) u cijelom slivu rijeke Al-Qshish. Kvantitativno gledano, godišnja stopa erozije tla u istraživanom bazenu iznosila je 81,1 t ha−1 godina−1 s prostornim prosjekom od 55,2 t ha−1 godina−1. Prostorno, izrađena je karta rizika od erozije tla s razvrstavanjem u pet osjetljivih zona: vrlo niska (41 %), niska (40,5 %), umjerena (8,9 %), visoka (5,4 %) i vrlo visoka (4,2 %). Sadašnja studija dala je pouzdanu procjenu stopa gubitka tla i klasifikaciju područja osjetljivih na eroziju unutar istraživanog bazena. Na te se rezultate može osloniti za stvaranje mjera za održavanje područja s visokom i vrlo visokom osjetljivošću tla na eroziju u trenutnim ratnim uvjetima

Soil Loss Estimation for Soil Conservation Planning using Geographic Information System in Guang Watershed, Blue Nile Basin

This research was carried out to spatially predict the soil loss rate of Guang watershed with a Geographic Information System (GIS) and Remote Sensing (RS). Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was used to estimate potential soil losses by utilizing information on  rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map, vegetation cover (C) using satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using satellite images. Based on the analysis, the mean and total annual soil loss potential of the study watershed was 24.95 tons ha-1 year-1 and 8,732.5 tons ha-1 year-1, respectively. About 147.9 ha (64%) of the watershed was categorized none to slight class which under soil loss tolerance (SLT) values ranging from 5 to 11 tons ha-1 year-1 whereas moderate to high soil loss potential covered about 202.1 ha (36%) about several times the maximum tolerable soil loss (11 tons ha-1 year-1). The study demonstrates that the RUSLE using GIS and RS provides great advantage to spatially analyze multi-layer of data. The predicted amount of soil loss and its spatial distribution could facilitate sustainable land use and management. Keywords: soil erosion; RUSLE; GIS; Guang watershed; Ethiopi

Assessment Of Micro-Watershed Vulnerability For Soil Erosion In Ribb Watershed Using GIS And Remote Sensing

The major objective of this study is assessment of the most erosion vulnerable micro-watersheds in Ribb watershed. This is because it is difficult to launch soil and water conservation and other environmental protection projects in all micro-watershed at the same time. So, the most erosion vulnerable micro-watersheds have to be identified. In this study Revised Universal Soil Loss Equation (RUSLE) and Multi-criteria Analysis (MCA) have been applied to quantify the soil erosion risk and identify the most vulnerable micro-watersheds. For this remotely sensed data and other ancillary data in GIS and remote sensing techniques are used. To assess the potential gully areas Topographic threshold concept are used. From The result of RUSLE model the potential average annual soil loss of the micro-watersheds ranges from 10.93 to 95.5 t/ha/year with a mean annual soil loss of 39.8 t/ha/year. The upper five micro-watersheds (MW-16, MW-23, MW-26, MW-27 and MW-29) covering 17.6% of the watershed shows very high mean soil loss rate. In the high mean soil erosion rate classes there are three MWs (MW-3, MW-18 and MW-20) and it covers 8.28% of the study area. Thus, they are above the annual average soil loss of the entire watershed (39.8 ton/ha/year). These micro watersheds under high and very high class demand immediate attention in terms of management and planning perspective. From the total area of the watershed which is 1240.12 km2, 92 km2 are potential areas for gully development. Based on the MCA, the micro- watersheds 3, 16, 23, 26 and 27 covering 19.47% of the study area have a Very high CEI and the largest portion (27.61%) of the study area is under high class of CEI and it includes seven Micro-watersheds. Thus these micro-watersheds are more vulnerable to erosion compared to the others and these needs immediate action. Considering the result of RUSLE model and MCA from the slope, gully, land cover and soil factors, micro-watersheds with large value of mean soil loss rate and CEI value are more soil erosion vulnerable micro- watersheds. Thus they should be prioritized for conservation and other environmental protection activities

The efects of land use and land cover changes (LULCC) in Kuseyr plateau of Turkey on erosion

Erosion is one of the important problems in degradation of agricultural lands and other natural lands. Te most dynamic factor in controlling erosion is land cover, and this factor has been anthropogenically manipulated for ages. Tis study investigates the efect of land use and land cover changes (LULCC) on erosion at Kuseyr Plateau, which is situated in the southernmost part of the eastern Mediterranean basin, Turkey. A geographical information systems-based method using the revised universal soil loss equation (3D) was employed to identify the amount of annual soil loss, erosion risk classes, and distribution generated by LULCC. Landsat satellite images were used to analyze LULCC from 1987 to 2010. Te implementations of both land cover and management factors were made possible by satellite image analysis performed throughout the years. Te results obtained from the study show that there is a rather severe erosion risk covering as much as 30% of the land within the scope of the study for 1987; this rate corresponds to 22% in 2010. Maximum annual soil loss in the plateau was as high as 59.81 t ha 1 per year in 1987 and 48.33 t ha 1 per year in 2010. Te average soil losses in the plateau were 6.19 and 5.00 t ha 1 per year for 1987 and 2010, respectively. Te related processes causing erosion from the past to present have slowed down, and reclamation of the land cover (with the intended purpose of decreasing erosion sensitivity) has always been the key factor in this regard. Despite a considerable decrease in severe erosion, as much as 22% of the study area still requires immediate measures in order to reduce soil loss

A Geographic Information System Based Soil Loss and Sediment Estimation in Gerdi Watershed, Highlands of Ethiopia

This study was carried out to spatially predict the soil loss rate of Gerdi watershed with a Geographic Information System (GIS) and Remote Sensing (RS). RUSLE adapted to Ethiopian conditions was used to estimate potential soil losses by utilizing information on  rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map, vegetation cover (C) using satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using satellite images. Based on the analysis, the total annual soil loss potential of the study watershed was 28,732.5 tons/yr. Out 147.9 ha (64%) of the land’s watershed was categorized none to slight class which under soil loss tolerance (SLT) values ranging from 5 to 11 tons ha-1yr-1. The study results indicated that the rate of potential soil loss in the watershed ranged from very low to extremely high. The area covered by none to slight potential soil loss was about 147.9 ha (64%) whereas moderate to high soil loss potential covered about 202.1 ha (36%) of the study watershed. The study demonstrates that the RUSLE together with GIS provide a good estimate soil loss rate over areas. Keywords: soil erosion; RUSLE; GIS; Gerdi watershed; Ethiopi