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Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement

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Simulating Runoff Under Changing Climatic Conditions : A Framework for Model Improvement. / Fowler, Keirnan; Coxon, Gemma; Freer, Jim; Peel, Muray; Wagener, Thorsten; Weston, Andrew; Woods, Ross; Zhang, Lu.

In: Water Resources Research, 01.10.2018.

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@article{4ec57f9512ca415a9073365e4a5547e9,
title = "Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement",
abstract = "Rainfall‐runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focussing on model intercomparison, input sensitivity and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here, we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterisation, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalise and/or cross‐check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data‐based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.",
keywords = "rainfall‐runoff modeling, model improvement, climate change",
author = "Keirnan Fowler and Gemma Coxon and Jim Freer and Muray Peel and Thorsten Wagener and Andrew Weston and Ross Woods and Lu Zhang",
year = "2018",
month = "10",
day = "1",
doi = "10.1029/2018WR023989",
language = "English",
journal = "Water Resources Research",
issn = "0043-1397",
publisher = "American Geophysical Union",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Simulating Runoff Under Changing Climatic Conditions

T2 - Water Resources Research

AU - Fowler, Keirnan

AU - Coxon, Gemma

AU - Freer, Jim

AU - Peel, Muray

AU - Wagener, Thorsten

AU - Weston, Andrew

AU - Woods, Ross

AU - Zhang, Lu

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Rainfall‐runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focussing on model intercomparison, input sensitivity and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here, we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterisation, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalise and/or cross‐check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data‐based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.

AB - Rainfall‐runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focussing on model intercomparison, input sensitivity and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here, we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterisation, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalise and/or cross‐check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data‐based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.

KW - rainfall‐runoff modeling

KW - model improvement

KW - climate change

U2 - 10.1029/2018WR023989

DO - 10.1029/2018WR023989

M3 - Article

JO - Water Resources Research

JF - Water Resources Research

SN - 0043-1397

ER -