Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds

Amirhosein Mosavi,Shahram Khalighi Sigaroodi,Fan Zhang,Mohammad Golshan,Adrienn A Dineva,Bahram Choubin,Alan D Ziegler

doi:10.1038/s41598-021-87691-0

Abstract

This paper proposes a regionalization method for streamflow prediction in ungauged watersheds in the 7461 km2 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.

Highlights

This paper proposes a regionalization method for streamflow prediction in ungauged watersheds in the 7461 km[2] area above the Gharehsoo Hydrometry Station in the Ardabil Province, in the north of Iran
We found that the Soil and Water Assessment Tool (SWAT) model was useful in developing a regionalization method to simulate streamflow in ungauged watersheds in the Gharehsoo watershed in Iran
We used fuzzy c-means clustering to partition the 46 watersheds into three homogenous groups that were similar to seven hydro-geomorphic parameters: area, maximum elevation, minimum elevation, slope length, slope, rainfall, and temperature

Summary

Introduction

This paper proposes a regionalization method for streamflow prediction in ungauged watersheds in the 7461 km[2] area above the Gharehsoo Hydrometry Station in the Ardabil Province, in the north of Iran. The area occupying the center of the Ardabil Province of Iran is a high-yield agriculture production region where recent human activities and land degradation have contributed to accelerated erosion and increased flood frequency[23] These factors have reduced fertility, lowered the volume of available water, and degraded the water resource reservoirs. This study develops a regionalization approach based on the SWAT model for estimating streamflow in the ungauged watersheds in the Ardabil Province, Iran To achieve this objective, we applied the FCM method to group 46 watersheds based on their similarity in a variety of properties (such as area, maximum elevation, minimum elevation, slope length, slope, rainfall, and temperature); and used the SWAT model for streamflow regionalization objectives in each homogenous region

Objectives

Methods

Results

Conclusion