Hydrological response-based watershed prioritization in semiarid, basaltic region of western India using frequency ratio, fuzzy logic and AHP method

  • Ajaykumar Kadam
  • Animesh S. Karnewar
  • Bhavana Umrikar
  • R. N. Sankhua


Watersheds from semiarid regions are more sensitive to hydrological processes and sustainability of water resources than humid regions. Hence, it is indispensable to determine the response of watersheds to hydrological processes for water resource management. Thus, the hydrological response-based watershed prioritization study has been undertaken for eight sub-watersheds from semiarid, basaltic region of Western Ghats of India. Intent to this, a novel index has been parameterized using thematic layers such as drainage density, geology, soil, slope, landform classification, land use/land cover, rainfall and runoff (DGSLR). This study evaluates the performance of DGSLR index using three models, namely analytical hierarchy process (AHP), frequency ratio (FR) and fuzzy logic for sub-watershed-wise prioritization. The FR ratio showed the highest value for very high drainage density (8.73) indicating most probability for a high hydrological response. According to AHP weight, most influencing factors to hydrological processes are precipitation (25%), slope (19%) and land use/land cover (14%) followed by landform classification (11%). These three methods are prioritized study area into four classes, i.e., very high, high, moderate and low using area-weighted average method. These models showed that very high-priority area lies near the outlet of the watershed as well as the upper part of the watershed in high to very high priority in all three models. It covers 33.12% of the total area having a high average slope with high drainage density in sub-watersheds 1, 3, 7 and 8. The predictive capability of DGSLR index was computed by the area under the curve (AUC) and receiver operating characteristic (ROC) method, revealed average accuracy for FR method (AUC = 89%) better than AHP method (AUC = 77%) and fuzzy logic (AUC = 76%). This novel index could be used by the water resources researchers and planners in any terrain to understand the hydrological response.


Hydrological response Fuzzy logic Frequency ratio DGSLR AHP ROC 



The authors are thankful to Head, Department of Environmental Sciences, and Head, Department of Geology, S.P. Pune University, for extending their help to use the department laboratory for computing facilities. Authors are thankful to editor and reviewers for evaluating and improving the quality of this manuscript.


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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Environmental SciencesSavitribai Phule Pune UniversityPuneIndia
  2. 2.Department of Computer EngineeringPune Institute of Computer Technology, PICTPuneIndia
  3. 3.Department of GeologySavitribai Phule Pune UniversityPuneIndia
  4. 4.Basin Planning, Central Water CommissionNew DelhiIndia

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