Soil erosion vulnerability assessment in district Ganderbal using GIS modeling approach
| dc.contributor.advisor | Wani, Dr. Akhlaq Amin | |
| dc.contributor.author | Shiba Zahoor | |
| dc.date.accessioned | 2022-06-30T07:43:37Z | |
| dc.date.available | 2022-06-30T07:43:37Z | |
| dc.date.issued | 2021 | |
| dc.description | PhD Thesis submitted to SKUAST Kashmir | en_US |
| dc.description.abstract | Soil erosion has become a worldwide concern for sustainable livelihood and is being perceived as a significant issue throughout the world. In order, to keep up the current degree of soil productivity and to fulfill the needs of the future, expanding accentuation is being laid on the characterization of the soils, accurate mapping and interpretation of soil for multifarious land use.The development of remote sensing and GIS techniques has become significant tools particularly while surveying erosion at larger scales. The assessment of soil erosion being a difficult assignment has been embraced through the development of various models dependent on a comprehension of the landscape processes and physical laws like runoff and soil formation happening in the natural environment. An enormous number of soil erosion models that have been developed over time, among which RUSLE (Revised Universal Soil Loss Equation) model is most widely accepted empirical model that can be effortlessly integrated with GIS. The present investigation entitled, “Soil erosion vulnerability assessment in district Ganderbal using GIS modeling approach” was carried out during the year 2018-2020. The study was undertaken with tripartite objectives a) to generate land use/land cover map (LULC) of district Ganderbal b) to assess different factors influencing soil erosion c) to generate soil erodibility map using erodibility modeling approach. The study area was delineated via visual image interpretation technique into 10 Landuse/Landcover classes viz. forest, forest scrub, grassland, snow, wasteland, agriculture, TOF, built-up, water body and wetland. LULC map (2018) revealed that among all the LULC classes, forest occupied maximum area of the map i.e. 33.96% while as wetland with an area of 1.35% occupied minimum portion of the map. The LULC map was also validated using ground truth points. The overall classification accuracy of LULC map came out to be 90.14% with overall kappa coefficient of 0.8897. The entire Himalayan locale is afflicted with a serious issue of soil erosion. In this region, accelerated erosion has happened as aftereffect of escalated deforestation, large scale road construction, mining and cultivation on steep slants. Since intricate and comprehensive estimate of soil erosion is not available in Kashmir Himalayan region, the current study was an attempt to assess various soil erosive factors (R,K, LS, C and P) and generate soil loss map and soil erosion vulnerability map of district Ganderbal using GIS based soil erosion model (RUSLE model). The R factor for the study area varied around 361.75 MJ mm ha-1 h-1 yr-1whereas K factor ranged between 0.024 t ha h ha-1 MJ-1 mm-1to 0.051 t ha h ha-1 MJ-1 mm-1. Three major soil groups were observed in the study area i.e. Be79-2a (Eutric Cambisol, medium textured, level to gentle undulating), GL(Glacier) and I-B-U (Lithosols, Cambisol and Rankers) with I-B-U soil group as dominant soil type. The spatial distribution of LS factor map showed that LS valueswent from 0 to 585.372 whereas C and P factor values for different LULC classes ranged from 0 to 1. The annual soil loss rate in the present study was found to differ somewhere in the range of (0 to 6098.44) t ha-1 yr-1. According to generated soil erodibility map five soil vulnerability classes viz.less vulnerable, moderately vulnerable, highly vulnerable, extremely vulnerable and severely vulnerable with annual soil loss of (0-30) t ha-1 yr-1, (30-60) t ha-1 yr-1, (60-90) t ha-1 yr-1, (90-120) t ha-1 yr-1and (120-6100) t ha-1 yr-1respectively were present in the area.The maximum area (137165.30 ha) of districts total area (146295.142 ha) was under less vulnerable class and minimum area (259.92 ha) under severely vulnerable category with 3054.11 ha, 2891.66 ha, 2924.15 ha under moderately vulnerable, highly vulnerable and extremely vulnerable class respectively. The mean soil loss under less vulnerable, moderately vulnerable, highly vulnerable, extremely vulnerable and severely vulnerable categories was found to be 15 t ha-1, 45 t ha-1, 75 t ha-1, 105 t ha-1 and 810 t ha-1 whereas total soil loss under the aforementioned categories was found to be around 2057479.50 t, 137434.98 t, 216874.35 t, 307035.60 t and 210538.70 t respectively. According to soil erosion vulnerability classes, it was observed that around 70.24% area was under less vulnerable class followed by extremely vulnerable class (10.48%) >highly vulnerable (7.40%)> severely vulnerable (7.19%)> moderately vulnerable (4.69%). The generated soil erosion vulnerability map of the present study areas revealed that the maximum portion of area was under less vulnerability class (0-30) t ha-1 yr-1 and some areas under severely vulnerable class which require special attention to prevent further degradation of this valuable asset. The delineated LULC practices were assessed further for soil physico-chemical analysis. Stratified random sampling was adopted within the mapped LULC areas for sample collection. Four samples were taken from each TOF practice in the replicates of three. In general, the studied soils of project area were found to be loam to sandy clay loam in texture with slightly acidic to alkaline pH with lowest mean value of pH under forestry (6.27) and highest under wastelands (8.38). The electrical conductively was found within the normal range under all land uses with highest value under wasteland (0.36) and lowest under forest (0.10). The bulk density and particle density varied from 1.06 g cm-3 to 1.47 g cm-3 and 2.25 g cm-3 and 2.45 g cm-3 in forest and wasteland LULC class respectively. Carbon proved to be a critical element which influenced other properties like pH, bulk density, nitrogen and phosphorus and hence assumes an important role in soil amelioration. The soil organic carbon (%) and soil organic carbon stock show wide variation under different LUSs with highest value under forests (2.80%; 89.74 t ha-1) fallowed by TOF (mixed) (1.69%; 57.32 t ha-1) and lowest value under wastelands (0.48%; 13.90 t ha-1). The available nitrogen ranged from medium to high with highest nitrogen content under forest (597.35 kg ha-1) and lowest under wasteland (248.47 kg ha-1). The available phosphorous and available potassium showed highest mean value under forest (47.01 kg ha-1, 239.63 kg ha-1) and lowest under wasteland (14.58 kg ha-1, 187.60 kg ha-1) respectively. Thesoils of the district in general were high in organic carbon, medium to high in available N and P and medium in available K status. Based on the afore mentioned soil parameters, forest land use system showed the highest values of soil organic carbon and available nutrients and hence is the best LULC practice in terms of soil function. The outcomes of present study will assist in studying the effect of land use on soil quality and will pave a way for efficient and effective management of particular LULC practice which will thrust in transfer of agro-technology suitability of soil for particular land use. | en_US |
| dc.identifier.uri | https://krishikosh.egranth.ac.in/handle/1/5810184980 | |
| dc.keywords | Landuse/Landcover, GIS, Landsat 8 OLI, Soil erosion, RUSLE, Soil map, Soil erosion vulnerability map, Soil parameters | en_US |
| dc.language.iso | English | en_US |
| dc.publisher | SKUAST Kashmir | en_US |
| dc.research.problem | Soil erosion vulnerability assessment in district Ganderbal using GIS modeling approach | en_US |
| dc.sub | Forestry | en_US |
| dc.subject | Landuse/Landcover, GIS, Landsat 8 OLI, Soil erosion | en_US |
| dc.subject | RUSLE, Soil map, Soil erosion vulnerability map, Soil parameters | en_US |
| dc.subject | Natural Resource Management | en_US |
| dc.subject | Forestry | en_US |
| dc.theme | Soil erosion vulnerability assessment in district Ganderbal using GIS modeling approach | en_US |
| dc.these.type | Ph.D | en_US |
| dc.title | Soil erosion vulnerability assessment in district Ganderbal using GIS modeling approach | en_US |
| dc.type | Thesis | en_US |