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Remote Sensing based rapid watershed health appraisal – a case study of NWDPRA watersheds of Rajasthan
Composite scoring for remote sensing based watershed health index
To evaluate relative performance of various watersheds in terms of landuse and biomass change the watershed quality indicators (derived through landuse and NDVI) were scaled and weights were assigned depending upon the impact of the health parameter on watershed. For various landuse types and vegetation vigour the weights were assigned as follows (Table 2 and 3).
Where, W B = water body, AF = agricultural plantation, FP = forest plantation, GF = good forest, MF = moderate forest, CL = crop land, F = fallow, LWIS = land with scrub, SF = scrub forest, PF = poor forest, LWOS = land without scrub, SA = sandy area, B/R = barren/rocky, R/G = ravenous/gullied.
The area weighted spatial averaging was done for each watershed for both the years as follows. Where, Wav = average weight, Ai = area under landuse ‘i’, wi = weight of the landuse ‘i’, A = area of the watershed. Database generation in ARC/INFO GIS On line digitization was performed for transport network, settlement location, notified forest boundaries, drainage lines and other features of interest. The arc coverage of drainage layer was used for buffer across it length to visualize the change along the drainage lines which is most critical from run-off and erosion point of view. A threshold of 50 m on either side of the drain was considered for buffer generation. This buffer coverage was subsequently used as mask to extract information through buffer window. These vverages in ARC/INFO were exported to image processing environment. The masks generated from forest boundaries, stony wastes etc. were used for apriori knowledge in classification of image. Overall methodology for watershed monitoring is given in Figure 2. Results and Discussion Landuse/landcover The percent distribution of various landuse types during pre and post treatment years (1988 and 1996) are given in Table 4 and 5 respectively. Based upon the predominant landuse types watersheds could be classified into 3 types viz. agricultural watersheds (w1, w3, w5 and w8), wasteland watersheds (w2, w4, and w7), and forested watershed (w6). The physiography and land characteristics have fabricated the existing landuse with varying degree of biodiversity. The watersheds viz. w1, w5 and w8 are almost flat in topography but in w3 almost half of the area is under hilly undulated terrain interspersed with cultivated lands confined along the valley and channel fills. On the other hand watersheds viz. w2 and w4 are hilly with hardly any soil cover to support intensive agriculture, whereas w7 is almost flat except the central steep ridges, but due to climatic and moisture constraints the cultivation is limited. Only one watershed (w6) is forested, characterized by hilly terrain and sitting over humid south-eastern plain. Large areas of this watershed are under protected forest, besides intensive social forestry programme is evident through large patches of plantation, discernible in satellite image. The valley fills are intensively cultivated which gives high productivity due to better sediment deposit and soil moisture availability.  Fig. 2: Flow chart for watershed monitoring One of the foremost indicators of the watershed development is the increase in the area and number of the water bodies. The extent of water bodies has increased in 4 watersheds viz. w2, w4, w5 and w6 but has decreased in w3 and w8 (Table 6). Out of 6 watersheds (contain water bodies), significant increase in aerial spread was observed in w4 and decrease in w3. The decrease in the extent could be due to less rainfall in the year of 1996 in comparison to 1988. The comparison between 1988 (pre treatment) and 1996 (post treatment) reveals that there is an increase in agricultural activity in w1, w2, w3, w6, w7 and w8 whereas decrease in w4 and w5 (Fig. 3 and Table 6). This increase in agriculture area has been possible as a result of bringing more and more marginal and wastelands under cultivation. Considerable increase in forestlands is also noticeable in w1, w5 and w7 due to large area put under social and farm forestry and allowing natural regeneration in the arid forest. In all the watersheds, wastelands have decreased significantly due to soil conservation, gully plugging and land reclamation. However, in w4 there is a marginal increase, which could be due to mixing of signatures of wastelands with long fallow (both of which appear similar in the image) while interpreting the satellite data.
 Fig. 3: Per cent changes in landuse between 1988 and 1996 Table 5: Percent distribution of various landuse types in 1996
Table 6: Percent changes in various landuse types between 1988 and 1996
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