Nagmati River Sub-watershed Prioritization Using PCA, Integrated PCWS, and AHP: A Case Study

Abstract

Prioritization of potential regions that are severely threatened by soil erosion is a prerequisite for formulating and implementing conservation measures and management practices, particularly in fragile semiarid regions. The present study prioritized eight delineated Nagmati sub-watersheds located in the Kutch District of Gujarat State, India, based on three approaches, namely principal component analysis (PCA), integrated PCA with weighted sum (I-PCWS), and analytical hierarchy process (AHP), and on 10 morphometric erosion risk parameters (ERPs). Sub-watersheds were categorized into three priority classes, namely high, medium, and low. PCA retrieved the three most significant ERPs (i.e., length of overland flow, Lo; drainage texture, Dt; and compactness coefficient, Cc) explaining 86.876% of the variance and exhibiting the highest correlation, i.e., r = 0.961, 0.986, and 0.934 for the first three principal components. Sub-watersheds SW2 and SW7 were rated high priority, SW1 was rated low priority, and the rest were rated medium priority. The I-PCWS approach revealed that sub-watersheds SW2, SW6, and SW7 were in high-priority zone, followed by SW3, SW4, and SW8 in medium-priority zone and SW1 and SW5 in the low-priority zone. The AHP assigned the highest and lowest ranks to “Lo” and “Cc,” respectively, with consistency ratio of 8.1% and principal eigenvalue of 11.075. Results from AHP revealed sub-watershed SW2 to be the highest priority and sub-watersheds SW1 and SW5 to be the lowest priority. Out of eight prioritized sub-watersheds from three approaches, five were found to be the common priority classes, with SW2, SW6, and SW7 demanding urgent implementation of efficient soil conservation measures to prevent further degradation of the identified regions. Results from I-PCWS approach closely complied with the existing landforms within the study area, and this approach was considered more reliable and robust than the other two approaches. The methodology adopted in this study can be applied to different vulnerable, data-scarce regions to sustainably manage and conserve soil erosion through efficiently framed strategies.