Erosion Prediction Analysis and Landuse Planning in Gunggung Watershed, Bali, Indonesia

Site-adapted production of bioenergy feedstocks on poorly drained cropland through the cultivation of perennial crops. A feasibility study on biomass yield and biochemical methane potential

Soil erosion modelling at European scale by using high resolution input layers

Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed

Assessment of soil erosion hazard and its relation to land use land cover changes: Case study from alage watershed, central Rift Valley of Ethiopia

Land and water degradation due to on-site soil/nutrient loss and off-site pollution/sedimentation are serious environmental problems. Landscape planning and management tools are essential to implement best management practices targeted at locations where they are needed most. Although many soil/water-landscape studies have been published in the last 2 decades, progress in developing operational tools for supporting landscape planning to minimize land and water degradation in developing regions is still modest. Some of the existing tools are data demanding and/or complicated to be useful to data scarce regions. Some require detailed understanding of the hydrological and modelling processes and thus less applicable to local stakeholders involved in land use planning and management. A user-friendly LAndscape Planning and MAnagement Tool (LAPMAT) developed to facilitate land management decision-making. LAPMAT is a menu-oriented interactive graphical user interface that can aid decision makers identify hotspot areas of soil erosion and evaluate the effects of alternative land use management practices at a catchment scale. The modelling framework and its interfaces are designed to guide the user through a series of menus that: 1) allow input model parameters, adjusting coefficients, visualizing input parameters and executing the model; 2) enable changing land use and management practices and re-evaluating potential consequences; 3) allow viewing results in tabular, graphical or map form side-by-side; and 4) (re)-evaluating the respective impacts of management/conservation options. The framework has been applied to assess the severity of soil erosion and simulate the impact of different land management practices using the Revised Universal Soil Loss Equation (RUSLE) adjusted for sediment delivery ratio in an example catchment of northern Ethiopia. The results showed average sediment yield rate of 55 t ha−1 y−1. Conservation measures targeted at high soil loss areas and gullies gave the maximum reduction in sediment yield by about 80 %. Since LAPMAT allows users handle the selection of management/planning options and provide fast and responsive outputs, it can assist in effective multi-stakeholder negotiations over land-use planning where the minimization of land/water degradation is the ultimate goal.

Soil erosion risk map for Swiss grasslands : a dynamic approach to model the spatio-temporal patterns of soil loss

One of the hazards of the erosion is soil infiltration capacity is decreased in the place of occurrence of erosion and increasing the volume of surface flow. It will also lead to the occurrence of the superficiality of the river due to the deposition of materials of soil erosion. These hazards need alternative agrotechnology which could reduce the rate of soil erosion. This research is to know the hazard of soil erosion in the upper watershed of the Aie Limau Kambiang and find out the alternative agrotechnology for reducing the soil erosion. This research was conducted. Soil samples collected was taken in purposive random sampling based on a unit of land. The data were analyzed using the universal soil loss equation. The research results of the largest erosion threat come from the land use of traditional gardens and plant density is low. The highest erosion 151,012.00 ton/ha/year was founded on the plantation blended that have a steep slope over 35% LS value of 9.5. The better of agrotechnology with increasing plant density, that could reduce erosion to 503.40 ton/ha/year. This means that the hazard of soil erosion could be controlled with land management and selected of the better agrotechnology.

Environmental impact assessment of perennial crops cultivation on marginal soils in the Mediterranean Region

The Revised Universal Soil Loss Equation (RUSLE) has enormous potential for integrating remote sensing and Geographical Information System (GIS) technologies for producing accurate and inexpensive assessments of soil erosion. In this study, the RUSLE method was applied to the Esil (Ishim) River basin (ERB), which is situated in Northern and Central Kazakhstan. The northern part of the ERB extends through the Tyumen and Omsk regions of the Russian Federation to the confluence of the Irtysh River. This article may be of interest to experts and specialists in the field of agriculture, as the findings can assist agricultural producers and government entities in making decisions that prevent soil degradation and promote optimal cropping systems for land and crop cultivation. The objective of this research is to detect, estimate and map areas of land plots most vulnerable to potential soil erosion within the ERB, using the RUSLE model under Arc GIS 10.2. The results reveal that average annual soil loss during the study period ranges from 0 to 32 (t y−1) and that 108,007.5 km2 (48%) of the ERB has no erosion. The remainder of the basin is prone to soil erosion ranging from 1 to 32 t ha−1 y−1, which comprises 117,216.9 km2 (52%), and total soil erosion is 565,368.7 (t y−1). Soil erosion in the ERB is relatively moderate due to low hill steepness and low annual precipitation (198–397 mm). Exceptions occur in plots which feature high slope length steepness, which are scattered throughout the region.

The Revised Universal Soil Loss Equation, Version 2 (RUSLE2), is the primary water erosion prediction tool used by the USDA National Resources Conservation Service (NRCS) for conservation planning across the United States. Despite its widespread adoption, RUSLE2’s current reliance on a personal computer-based model constrains its capacity for large-scale, dynamic applications. This research addresses these limitations by developing a novel cloud-based platform to host and enhance RUSLE2, enabling server-based computations, geospatial data integration, and scalable modeling capabilities. Built on Amazon Web Services (AWS), the platform incorporates web-based user interfaces, spatial databases, and geoprocessing tools to streamline soil erosion modeling. It integrates historical data on soil properties, climate, and land management to support precise assessments of rill and interrill erosion. A redesigned database architecture ensures computational efficiency, reliability, and security while fostering collaborative software development. Scientific advancements in RUSLE2 include quantifying the impacts of rainfall and land management practices on the spatiotemporal variability of dynamic soil properties. Leveraging advanced laboratory and field methods, remote sensing, and machine learning, this platform refines the measurement of soil erodibility and soil loss across diverse U.S. agricultural landscapes. These enhancements enable improved predictions of soil erosion risks under varying climate scenarios and support adaptive land management strategies. This transformative cloud-based platform promotes sustainable agriculture and conservation planning by delivering innovative tools for best management practices. Through the integration of cutting-edge technologies and data-driven approaches, this research addresses critical gaps in soil erosion science and contributes to food security, environmental conservation, and resilience to climate change.

Abstract. Elevated suspended sediment concentrations in fluvial environments have important implications for system ecology and even small concentrations may have serious consequences for sensitive ecosystems or organisms, such as freshwater pearl mussels (Margaritifera margaritifera). Informed decision making is therefore required for land managers to understand and control soil erosion and sediment delivery to the river network. However, given that monitoring of sediment fluxes requires financial and human resources which are often limited at a national scale, sediment mobilisation and delivery models are commonly used for sediment yield estimation and management. The Revised Universal Soil Loss Equation (RUSLE) is the most widely used model for overland flow erosion and can, when combined with a sediment delivery ratio (SDR), provide reasonable sediment load estimations for a catchment. This paper presents RUSLE factors established from extant GIS and rainfall datasets that are incorporated into a flexible catchment modelling approach. We believe that this is the first time that results from a RUSLE application at a national scale are tested against measured sediment yield values available from Ireland. An initial assessment of RUSLE applied to Irish conditions indicates an overestimation of modelled sediment yield values for most of the selected catchments. Improved methods for model and SDR factors estimation are needed to account for Irish conditions and catchment characteristics. Nonetheless, validation and testing of the model in this study using observed values is an important step towards more effective sediment yield modelling tools for nationwide applications.

The Universal Soil Loss Equation (USLE) has been assessed in the present study using Remote Sensing and GIS in order to estimate the potential Soil Loss at watershed level in Wular Catchment. Wular Catchment has an area of 1200.36 km 2 and lies between 34 o 12′24″ and 34 o 36′26″ N latitude and 74 o 26′41″ and 74 o 56′02″E longitude. Its altitudinal range is from 1580 meters near Wular Lake to about 4500 meters in Harmukh range. Maps of the R, K, LS, C and P factors were derived from the precipitation data, soil map, digital elevation model (DEM), land use and field survey respectively. It emerges from the study that about 6% of the area has severe erosion with a soil loss more than 900 t ha −1 yr −1 . The watersheds of 1EE2a, 1EM2a and 1EE1c have the highest percentage share of 19.91%, 17.30% and 14.88% respectively under severe erosion. This is the most susceptible zone to soil erosion primarily due to very steep slope gradient and slope length. The study clearly demonstrates the importance of vegetation cover for watershed management. The Study has proposed soil and water conservation measures in accordance with the spatial distribution of soil loss in the Catchment. Keywords: USLE; Soil Loss; Wular Catchment; Soil Erosion; Rainfall; Erosivity Cite this Article Zahoor-ul-Hassan, M. Imran Malik, T.A. Kanth. GIS Based Assessment of Soil Erosion Using Universal Soil Loss Equation (USLE) in Wular Catchment of Kashmir. Journal of Remote Sensing & GIS . 2017; 8(3): 56–66p.

Assessment of erosion hazard with the USLE and GIS: A case study of the Upper Ewaso Ng'iro North basin of Kenya

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia. The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed. Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%). Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated as having very less to moderate. On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah. The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81]

Towards improved USLE-based soil erosion modelling in India: A review of prevalent pitfalls and implementation of exemplar methods