Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Santiago Narbondo,Magdalena Crisci,Christian Chreties,Angela Gorgoglione

doi:10.3390/w12020528

Abstract

Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, this method cannot be applied in large regions characterized by highly variable climatic conditions, such as sub-tropical areas. Therefore, this study aims to develop a new regionalization approach based on an enhanced concept of physical similarity to improve the runoff prediction of ungauged basins at country scale, under highly variable-weather conditions. A clustering method assured that watersheds with different hydrologic and physical characteristics were considered. The novelty of the proposed approach is based on the relationships found between rainfall-runoff model parameters and watershed-physiographic factors. These relationships were successively exported and validated at the ungauged basins. From the overall results, it can be concluded that the runoff prediction in the ungauged basins was very satisfactory. Therefore, the proposed approach can be adopted as an alternative method for runoff prediction in ungauged basins characterized by highly variable-climatic conditions.

Highlights

Runoff simulations have a significant influence on sustainable water resources management and engineering design all over the world
The primary goal of the international Predictions in Ungauged Basins (PUB) initiative was to reduce the uncertainty in the runoff prediction by shifting away from tools that require calibration and curve fitting to tools that need little or no calibration [5,6]
The review study of Hrachowitz et al [7] explained that regionalization is the most common method used to tackle the PUB issue

Summary

Introduction

Runoff simulations have a significant influence on sustainable water resources management and engineering design all over the world. Hydrologic/hydraulic models represent the most used tool to solve this problem These models are calibrated and validated to get the best set of parameters that optimizes the agreement between observations and simulations. This classical method cannot be tackled if the study area lacks observed runoff data [1]. Despite continuous expensive research and efforts to gather hydrologic data, there are still some areas of the world with scarce hydrometric gauging stations [2,3] These areas have been representing a motivating and challenging topic for researchers and decision-makers.

Objectives

Methods

Results