RESUMO
Identifying the most critical sub-watershed or reservoir catchment in relation to water spread, pattern of soil erosion and aquifer recharge in a basin can be highly useful for implementing conservation measures. Thus, a study was undertaken to (i) review the various parameters used in watershed morphometric analysis with their appropriate mathematical expressions, (ii) discuss their importance in watershed prioritization and conservation planning, (iii) formulate mathematical relationship between important morphometric parameters, and (iv) discuss the different tools and techniques used for sub-watershed prioritization. All the morphometric parameters are important for hydrologic characterization and watershed prioritization. However, some of them are highly significant for better understanding of the watershed drainage network, geometry, drainage texture and relief parameters. The smaller values of shape parameters viz. form factor (Ff < 0.78), elongation ratio (Re < 0.80) and circularity ratio (Rc < 0.50) indicate a basin having elongated shape and flatter peak for extended period and permit a greater soil erosion/loss as these are inversely related with erodibility. Whereas, the greater values of Ff (>0.78), Re (>0.80) and Rc (>0.50) indicate a basin having circular shape and higher peak for smaller period. The higher values of drainage density (Dd > 0.60), drainage texture (Dt > 0.6) and stream frequency (Fs > 10) also indicate higher erosion due to their direct relationship with erodibility. As per this review, watersheds can be prioritized by several techniques including morphometric analysis, LULC change analysis and soil loss estimation. However, the morphometric analysis-based watershed prioritization is found to be laborious and time consuming as it involves numerous parameters, and hence can be replaced by modern data reduction methods like principal component analysis (PCA) using suitable software's like R, SPSS and XLSTAT. Thus, geospatial techniques-based catchment/watershed prioritization supported with an appropriate data dimension reduction technique (e.g. PCA) would be highly significant for planning conservation measures and management in a watershed.'
