Remote Sensing & GIS in identifying areas vulnerable to soil erosion

Remote Sensing & GIS in identifying areas vulnerable to soil erosion


Vimal Garg & Ritu Seth
WAPCOS, 9, Community Centre, Saket, New Delhi
[email protected]

Economic viability of dam based projects depends upon the life span of the reservoir which is adversely affected by the fragility of the catchment. Rates of soil erosion in Himalayas are very high in comparison to those in most parts of the world. The rates of soil erosion observed in the region are related to natural and human factors. The human impacts on the soil erosion can be interpreted from landuse changes over long periods and large areas.

The most important factors those contribute to soil erosion are played by landuse/land cover, slope, lithology, soils, drainage, lineaments, geomorphology, rainfall intensity and current management methods those are being practiced to avoid soil erosion.

Using the existing models, the areas vulnerable to soil erosion can be identified where appropriate treatment and management measures can be formulated. Since the models assume uniform characteristics within an area/sub-catchment, accuracy is enhanced, as the area of interest is sub-divided in as smaller sizes/grids. Use of remote sensing and GIS techniques can greatly help in doing this exercise.

In the present exercise, a similar attempt has been made in the catchment of one of the tributaries of Satluj River in Himachal Pradesh. Various thematic layers for landuse, slope, soil, rainfall etc. were prepared using IRS 1D/LISS & PAN data, SOI toposheets, soil survey data and rainfall data from IMD which were used for estimating soil loss using Universal Soil Loss Equation (USLE). To enhance the accuracy in estimation the entire catchment area was divided in grids of 0.0002 degrees on lat/long which were updated using various thematic layers. Based on the soil loss estimations, vulnerable areas were identified for undertaking various treatment measures.

Planning for treatment measures takes into consideration a detailed database on natural resources, soil type, rainfall data, topography, socio-economic conditions etc. before formulating a beneficial and feasible plan. The various factors to be considered are input as thematic layers to the model. To ensure that the data used is recent and accurate, satellite data has been used for interpretation of present landuse in the area. Manual checks are performed and data is collected from reliable sources for authentication. In this case soil data has been collected from AIS&LS and rainfall data has been collected from IMD.

Since the amount of data to be handled in the database becomes enormous as it contains spatial sources alongwith maps and the data usually covers a large geographical region, a Geographic Information System is used to store, retrieve, manipulate, analyze and display data. The GIS is designed to carry out operations on the data stored in its database, according to a set of user specifications without the user needing to be knowledgeable about how the data is stored and what data handling and processing procedures are utilized to retrieve and present the information required. The various layers of data are of mixed types (resolution, scale, units, coordinates) and are to be brought to common coordinates before being processed together.