An erosion model using the Revised Universal Soil Loss Equation (RUSLE) equation derived from the Advanced Spaceborne Thermal Emission and Reflection Global Digital Elevation Model (ASTER G-DEM) and LANDSAT 8 is presented in the study. This model can be a cost-effective, quick and less labor-intensive tool for assessing erosion in small watersheds. It can also act as a vital input for the primary assessment of environmental degradation in the region, and can aid the formulation of watershed development planning strategies. The Palar River, which drains into Shanmukha Nadi, is a small mountain watershed. The town of Kodaikanal, a popular tourist attraction in Tamilnadu, forms part of this sub-watershed. This quaint, hill-town has been subjected to intense urbanization and exhaustive changes in its land use practices for the past decade. The consequence of this change is manifested in the intense environmental degradation of the region, which results in problems such as increased numbers of landslides, intense soil erosion, forest fires and land degradation. The nature of the terrain, high precipitation, and intense agriculture exponentially increase the rate of soil erosion. Spatial prediction of soil erosion is thereby a valuable and mandatory tool for sustainable land use practices and economic development of the region. A comprehensive methodology is employed to predict the spatial variation of soil erosion using the revised soil loss equation in a geographic information system (GIS) platform. The soil erosion susceptibility map shows a maximum annual soil loss of 3345 Mg·ha−1·y−1, which correlates with scrub forests, degraded forests, steep slopes, high drainage density and shifting cultivation practices. The erosion map shows that the central region is subjected to intense erosion while the inhabited southern part is less prone to erosion. A small patch of severe soil loss is also visible on the eastern part of the northern fringe. About 4% of the sub-watershed is severely affected by soil erosion and 18% falls within a moderate erosion zone. The growing demand for land and infrastructure development forces the shift of urbanization and agriculture to these less-managed spaces. In light of this scenario, the spatial distribution of erosion combined with terrain and hydro-morphometry can aid in sustainable development and promote healthy land use practices in the region.
This paper reports the use of a GIS based Probabilistic Certainty Factor method to assess the geo-environmental factors that contribute to landslide susceptibility in Tevankarai Ar sub-watershed, Kodaikkanal. Landslide occurrences are a common phenomenon in the Tevankarai Ar sub-watershed, Kodaikkanal owing to rugged terrain at high altitude, high frequency of intense rainfall and rapidly expanding urban growth. The spatial database of the factors influencing landslides are compiled primarily from topographical maps, aerial photographs and satellite images. They are relief, slope, aspect, curvature, weathering, soil, land use, proximity to road and proximity to drainage. Certainty Factor Approach is used to study the interaction between the factors and the landslide, highlighting the importance of each factor in causing landslide. The results show that slope, aspect, soil and proximity to roads play important role in landslide susceptibility. The landslide susceptibility map is classified into five susceptible classes-low, very low, uncertain, high and very high − 93.32% of the study area falls under the stable category and 6.34% falls under the highly and very highly unstable category. The relative landslide density index (R index) is used to validate the landslide susceptibility map. R index increases with the increase in the susceptibility class. This shows that the factors selected for the study and susceptibility mapping using certainty factor are appropriate for the study area. Highly unstable zones show intense anthropogenic activities like high density settlement areas, and busy roads connecting the hill town and the plains.
Morphometric analysis is a key to understand the hydrological process and hence is a prerequisite for the assessment of hydrological characteristics of surface water basin. Morphometric analysis to determine the drainage characteristics of Palar sub-watershed, a part of Shanmukha watershed in the Amaravati sub-catchment is done using Advanced Space-borne Thermal Emission and Reflection Global Digital Elevation Model (ASTER GDEM) data, and is supplemented with topographical maps in geographical information systems platform. This study uses ASTER GDEM data to extract morphometric features of a mountain stream at micro-watershed level. The sub-watershed is divided into six micro-watersheds. The sub-watershed includes a sixth-order stream. Lower stream orders, in particular first-order streams, dominate the sub-watershed. Development of stream segments is controlled by slope and local relief. Drainage pattern of the subwatershed and micro-watersheds is dendritic in general. The mean bifurcation ratio of the sub-watershed is 3.69 but its variation between the various stream orders suggests structural control in the development of stream network. The shape factors reveal the elongation of the sub-watershed and micro-watersheds. The relief ratio reveals the high discharge capability of the sub-watershed and meagre groundwater potential. This study is a useful tool for planning strategies in control of soil erosion and soil conservation.
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