A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala, India. The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method. 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 area. The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h -1 y -1 with a close relation to grass land areas, degraded forests and deciduous forests on the steep side-slopes (with high LS ). The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas. ª 2011, China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. All rights reserved.

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Siruvani watershed with a surface area of 205.54 km 2 (20,554 hectare), forming a part of the Western Ghats in Attapady valley, Kerala, was chosen for testing RUSLE methodology in conjunction with remote sensing and GIS for soil loss prediction and identifying areas with high erosion potential. The RUSLE factors (R, K, LS, C and P) were computed from local rainfall, topographic, soil classification and remote sensing data. This study proved that the integration of soil erosion models with GIS and remote sensing is a simple and effective tool for mapping and quantifying areas and rates of soil erosion for the development of better soil conservation plans. The resultant map of annual soil erosion shows a maximum soil loss of 14.917 t h -1 year -1 and the computations suggest that about only 5.76% (1,184 hectares) of the area comes under the severe soil erosion zone followed by the higherosion zone (11.50% of the total area). The dominant high soil erosion areas are located in the central and southern portion of the watershed and it is attributed to the shifting cultivation, and forest degradation along with the combined effect of K, LS and C factor. The RUSLE model in combination with GIS and remote sensing techniques also enables the assessment of pixel based soil erosion rate.

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Objective:To assess the sanitary condition and water quality of household wells and to depict it spatially using Geographic Information System (GIS) in an urban area of Trivandrum, Kerala state, India.Study design:A community-based cross-sectional census-type study.Methods:Study was conducted in an urban area of Trivandrum. All households (n = 449) residing in a 1.05 km2 area were enrolled in the study. Structured questionnaire and Differential Global Positioning System (DGPS) device were used for data collection. Water samples taken were analyzed in an accredited laboratory.Results:Most of the wells were in an intermediate-high contamination risk state, with more than 77% of wells having a septic tank within 7.5 m radius. Coliform contamination was prevalent in 73% of wells, and the groundwater was predominantly acidic with a mean of 5.4, rendering it unfit for drinking. The well chlorination and cleaning practices were inadequate, which were significantly associated with coliform contamination apart from a closely located septic tank. However, water purification practices like boiling were practiced widely in the area.Conclusion:Despite the presence of wells with high risk of contamination and inadequate chlorination practices, the apparent rarity of Water-borne diseases in the area may be attributed to the widespread boiling and water purification practices at the consumption level by the households. GIS technology proves useful in picking environmental determinants like polluting sources near the well and to plan control activities.

Digital elevation model (DEM), deriving conventionally from contour data of topographic maps, provides sufficient information regarding the continuously varying topographic surface of the Earth. Though spaceborne DEMs are increasingly being used in earth-environmental-applications, suitability of various freely available spaceborne DEMs [e.g., advanced spaceborne thermal emission and reflection (ASTER), shuttle radar topography mapping mission (SRTM), global multi-resolution terrain elevation data (GMTED)] for topographic and geomorphometric analyzes in tropical regions is yet to be ascertained. In this paper, comparability of these spaceborne DEMs among themselves and also with the DEM (TOPO) prepared from digital contour data of topographic maps is assessed. Results show that various primary and secondary derivatives of ASTER and SRTM DEMs provide relatively better precision and substantial agreement with the corresponding parameters derived from TOPO. Among the spaceborne DEMs, SRTM has relatively higher vertical accuracy (root mean square error = 17.05 m), compared to ASTER (24.09 m) and GMTED (32.85 m). The vertical accuracy of all the spaceborne DEMs strongly depends on the relief and ruggedness of the terrain as well as the type of vegetation. It is proposed that in the absence of other available and acceptable elevation datasets, SRTM and ASTER are equally competent for geomorphometric analysis in tropical regions, while GMTED shows significant loss of terrain information due to coarser spatial resolution.