Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds.
Amirhosein Mosavi, Mohammad Golshan, Bahram Choubin, Alan D Ziegler, Shahram Khalighi Sigaroodi, Fan Zhang, Adrienn A Dineva
Author Information
Amirhosein Mosavi: Environmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Mohammad Golshan: Watershed Management Department, Natural Resources and Watershed Management Office, Astara, Iran.
Bahram Choubin: Soil Conservation and Watershed Management Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Urmia, Iran. b.choubin@areeo.ac.ir.
Alan D Ziegler: Faculty of Fisheries and Aquatic Resources, Mae Jo University, Chiang Mai, Thailand.
Shahram Khalighi Sigaroodi: Reclamation of Arid and Mountainous Regions Department, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
Fan Zhang: Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, P.O. Box 2871, Beijing, 100085, China.
Adrienn A Dineva: Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam. adrienndineva@duytan.edu.vn.
This paper proposes a regionalization method for streamflow prediction in ungauged watersheds in the 7461 km area above the Gharehsoo Hydrometry Station in the Ardabil Province, in the north of Iran. First, the Fuzzy c-means clustering method (FCM) was used to divide 46 gauged (19) and ungauged (27) watersheds into homogenous groups based on a variety of topographical and climatic factors. After identifying the homogenous watersheds, the Soil and Water Assessment Tool (SWAT) was calibrated and validated using data from the gauged watersheds in each group. The calibrated parameters were then tested in another gauged watershed that we considered as a pseudo ungauged watershed in each group. Values of R-Squared and Nash-Sutcliffe efficiency (NSE) were both ≥ 0.70 during the calibration and validation phases; and ≥ 0.80 and ≥ 0.74, respectively, during the testing in the pseudo ungauged watersheds. Based on these metrics, the validated regional models demonstrated a satisfactory result for predicting streamflow in the ungauged watersheds within each group. These models are important for managing stream quantity and quality in the intensive agriculture study area.
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