A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox

Mojtaba Sadegh, Amir AghaKouchak (), Alejandro Flores, Iman Mallakpour and Mohammad Reza Nikoo
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Mojtaba Sadegh: University of California
Amir AghaKouchak: University of California
Alejandro Flores: Boise State University
Iman Mallakpour: University of California
Mohammad Reza Nikoo: Shiraz University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 9, No 3, 3024 pages

Abstract: Abstract We present a framework and toolbox for multi-model (one at a time) nonstationary modeling of rainfall-runoff (RR) transformation. The designed time-varying nature of the five available conceptual RR models in the toolbox allows for modeling processes that are nonstationary in essence. Nonstationary Rainfall-Runoff Toolbox (NRRT) delivers insights about underlying watershed processes through interactive tuning of model parameters to reflect temporal nonstationarities. The toolbox includes a number of performance metrics, along with visual graphics to evaluate the goodness-of-fit of the model simulations. Our analysis shows that the proposed time-varying RR modeling framework successfully captures the nonstationary behavior of the Wights catchment in Australia. A multi-model analysis of this catchment, that has endured deforestation, provides insights on the functionality of different conceptual modules of RR models, and their representation of the real-world.

Keywords: Nonstationarity; Rainfall-runoff modeling; Time-varying models; NRRT toolbox (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11269-019-02283-y

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