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Case Report

Identification of critical watershed using hydrological model and drought indices: a case study of upper Girna, Maharashtra, India

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Pages 471-482 | Received 15 Apr 2018, Accepted 08 Mar 2019, Published online: 29 Mar 2019
 

ABSTRACT

The analysis of runoff and drought is very crucial in the semi-arid ungauged catchment. This research quantifies the characteristics of the meteorological and hydrological drought using the hydrological model and drought indices in the upper Girna subbasin, Nashik, India. In order to identify critical watershed, the semi-distributed Soil and Water Assessment (SWAT) model, Reconnaissance drought index (RDI) and Streamflow drought index (SDI) are adopted in the analysis. To achieve this, the SWAT model is calibrated (1981–2000) and validated (2001–2010) with the observed net inflow of the Girna dam on a monthly scale. Further, the calibration of the developed model was performed using SUFI-2 algorithm. The runoff generated from the calibrated SWAT model is used to find the hydrological drought behaviour at a watershed scale. The present research can be a valuable resource for government agencies and local stakeholders in terms of identification of the critical watershed in the semiarid ungauged region to improve the integrated water resource management. Also, the outcome based upon runoff and drought responses can be a stepping stone to reduce the drought impact and to finalise the mitigation measures, water harvesting schemes in an ungauged semiarid river catchment.

Acknowledgments

The authors are grateful to the Indian Meteorological Department (IMD) Pune for providing necessary the data. The author also thanks the Hydrological Data User Group (HDUG) Nashik, and the Girna irrigation division, Jalgaon, Government of Maharashtra, India for providing the required data for the study. The authors are thankful to the anonymous reviewers for thoughtful comments and constructive suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

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