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ABSTRACT:Soil erosion is a widespread environmental challenge faced in Kallar watershed nowadays. Erosion is defined as the movement of soil by water and wind, and it occurs in Kallar watershed under a wide range of land uses. Erosion by water can be dramatic during storm events, resulting in wash-outs and gullies. It can also be insidious, occurring as sheet and rill erosion during heavy rains. Most of the soil lost by water erosion is by the processes of sheet and rill erosion. Land degradation and subsequent soil erosion and sedimentation play a significant role in impairing water resources within sub watersheds, watersheds and basins. Using conventional methods to assess soil erosion risk is expensive and time consuming. A comprehensive methodology that integrates Remote sensing and Geographic Information Systems (GIS), coupled with the use of an empirical model (Revised Universal Soil Loss Equation-RUSLE) to assess risk, can identify and assess soil erosion potential and estimate the value of soil loss. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the study area. The final map of annual soil erosion shows a maximum soil loss of 398.58 t/ h -1 / y -1 . Based on the result soil erosion was classified in to soil erosion severity map with five classes, very low, low, moderate, high and critical respectively. Further RUSLE factors has been broken into two categories, soil erosion susceptibility (A=RKLS), and soil erosion hazard (A=RKLSCP) have been computed. It is understood that functions of C and P are factors that can be controlled and thus can greatly reduce soil loss through management and conservational measures.

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Commission VI, WG VI/4KEY WORDS: Land cover, Markov, Kallar, NDVI, Drought, Geoinformatics ABSTRACT:Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995ETM ( , 2005 and IRS P6-LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

ABSTRACT:Landslides are one of the critical natural phenomena that frequently lead to serious problems in hilly area, resulting to loss of human life and property, as well as causing severe damage to natural resources. The local geology with high degree of slope coupled with high intensity of rainfall along with unplanned human activities of the study area causes many landslides in this region. The present study area is more attracted by tourist throughout the year, so this area must be considered for preventive measures. Geospatial based Multicriteria decision analysis (MCDA) technique is increasingly used for landslide vulnerability and hazard zonation mapping. It enables the integration of different data layers with different levels of uncertainty. In this present study, it is used analytic hierarchy process (AHP) method to prepare landslide hazard zones of the Coonoor and Ooty, part of Kallar watershed, The Nilgiris, Tamil Nadu. The study was carried out using remote sensing data, field surveys and geographic information system (GIS) tools. The ten factors that influence landslide occurrence, such as elevation, slope aspect, slope angle, drainage density, lineament density, soil, precipitation, land use/land cover (LULC), distance from road and NDVI were considered. These factors layers were extracted from the various related spatial data's. These factors were evaluated, and then, the individual factor weight and class weight were assigned to each of the related factors. The Landslide Hazard Zone Index (LHZI) was calculated using Multicriteria decision analysis (MCDA) the technique based on the assigned weight and the rating is given by the Analytical Hierarchy Process (AHP) method. The final cumulative map of the study area was categorized into four hazard zones and classified as zone I to IV. There are 3.56 % of the area comes under the hazard zone IV fallowed by 48.19 % of the area comes under zone III, 43.63 % of the area in zone II and 4.61% of the area comes hazard zone I. Further resulted hazard zone map and landuse/landcover map are overlaid to check the hazard status, and existing inventory of known landslides within the present study area was compared with the resulting vulnerable and hazard zone maps. The landslide hazard zonation map is useful for landslide hazard prevention, mitigation, and improvement to society, and proper planning for land use and construction in the future.. * Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.