TY - JOUR
T1 - A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework
T2 - Analysis and Toolbox
AU - Sadegh, Mojtaba
AU - AghaKouchak, Amir
AU - Flores, Alejandro
AU - Mallakpour, Iman
AU - Nikoo, Mohammad Reza
N1 - Funding Information:
This study was partially supported by the United States National Science Foundation Award No. CMMI −1635797, ARO’s Environmental Sciences Division Award No. W911NF-14-1-0684, and National Oceanic and Atmospheric Administration (NOAA) Award No. NA14OAR4310222.
Funding Information:
This study was partially supported by the United States National Science Foundation Award No. CMMI −1635797, ARO’s Environmental Sciences Division Award No. W911NF-14-1-0684, and National Oceanic and Atmospheric Administration (NOAA) Award No. NA14OAR4310222.
Publisher Copyright:
© 2019, Springer Nature B.V.
PY - 2019/7/15
Y1 - 2019/7/15
N2 - 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.
AB - 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.
KW - Nonstationarity
KW - NRRT toolbox
KW - Rainfall-runoff modeling
KW - Time-varying models
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U2 - 10.1007/s11269-019-02283-y
DO - 10.1007/s11269-019-02283-y
M3 - Article
AN - SCOPUS:85069040504
SN - 0920-4741
VL - 33
SP - 3011
EP - 3024
JO - Water Resources Management
JF - Water Resources Management
IS - 9
ER -