Determination of soil quality index in areas with high erosion risk and usability in watershed rehabilitation applications.

Erosion is an important environmental issue threatening natural resources and ecosystems, especially soil and water. Soil losses occur in many parts of the world due to erosion at different degrees, and various rehabilitation plans have been carried out to reduce these losses. However, soil protection applications are generally carried out by considering only the essential characteristics of the soil. This may decrease the chance of success of rehabilitation applications. The present study aimed to determine the soil quality index (SQI) by weighting the soil quality parameters according to the analytical hierarchy process (AHP) in the Çapakçur microcatchment (Bingöl, Türkiye) where soil loss is high. Accordingly, 428 soil samples were taken from the study area and analyzed. The soil losses in the Çapakçur watershed were calculated employing the revised universal soil loss equation (RUSLE). To determine the soil quality index, a total of 20 indicators were used, including (i) physical soil properties, (ii) chemical soil properties, and (iii) soil nutrient content. Soil quality index results are divided into classes between 1 and 5. As a result of the study, the annual total amount of soil lost from the microcatchment was calculated as 96,915.20 tons, and the yearly average amount of soil lost from the unit area was calculated as 10.14 tons ha-1. According to SQI, the largest area in the microcatchment was Class-2 (weak), with 39.49%, whereas the smallest area was 1.4% (the most suitable). However, it was determined that there was a significant negative relationship between SQI and soil erodibility. Considering the SQI distribution of the area in the planning of soil protection and erosion prevention practices in watershed rehabilitation studies may increase success.

Using the Remote Sensing and GIS Technology for Erosion Risk Mapping of Kartalkaya Dam Watershed in Kahramanmaras, Turkey.

The soil erosion is the most serious environmental problem in watershed areas in Turkey. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to develop adequate erosion prevention measures in the watersheds of dams, erosion risk maps should be generated considering these factors. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used for erosion risk mapping in Kartalkaya Dam Watershed of Kahramanmaras, Turkey, based on the methodology implemented in COoRdination of INformation on the Environment (CORINE) model. ASTER imagery was used to generate a land use/cover classification in ERDAS Imagine. The digital maps of the other factors (topography, soil types, and climate) were generated in ArcGIS v9.2, and were then integrated as CORINE input files to produce erosion risk maps. The results indicate that 33.82%, 35.44%, and 30.74% of the study area were under low, moderate, and high actual erosion risks, respectively. The CORINE model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion risk maps in Turkey.

Application of GeoWEPP for Determining Sediment Yield and Runoff in the Orcan Creek Watershed in Kahramanmaras, Turkey.

The geo-spatial interface of the WEPP model called GeoWEPP uses digital geo-referenced information integrated with the most common GIS tools to predict sedimentyield and runoff. The model determines where and when the sediment yield and runoffoccurs and locates possible deposition places. In this study, the sediment yield and runofffrom Orcan Creek watershed in Kahramanmaras region was estimated by using GeoWEPPmodel. To investigate the performance of the model, the sediment yield and runoff resultsfrom the GeoWEPP model were compared with the observed monthly data collected fromthe sample watershed. The average Root Mean Square Errors (RMSE) between observedand predicted average annual sediment yield and runoff were 2.96 and 8.43, respectively.The index of agreement was 0.98 and 0.99 for sediment yield and runoff, respectively,which indicated that the model predictions provided good results.

Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project.

The satellite imagery has been effectively utilized for classifying land covertypes and detecting land cover conditions. The Advanced Spaceborne Thermal Emissionand Reflection Radiometer (ASTER) sensor imagery has been widely used in classificationprocess of land cover. However, atmospheric corrections have to be made by preprocessingsatellite sensor imagery since the electromagnetic radiation signals received by the satellitesensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study,an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance(TOA), was used to classify the land use/cover types, according to COoRdination ofINformation on the Environment (CORINE) land cover nomenclature, for an arearepresenting the heterogonous characteristics of eastern Mediterranean regions inKahramanmaras, Turkey. The results indicated that using the surface reflectance data ofASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of83.2% and 0.79, respectively) and low-cost cover mapping as a part of inventory forCORINE Land Cover Project.