The transferability of hydrological models under nonstationary climatic conditions

This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired...

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Main Authors: C. Z. Li, L. Zhang, H. Wang, Y. Q. Zhang, F. L. Yu, D. H. Yan
Format: Article
Language:English
Published: Copernicus Publications 2012-04-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/16/1239/2012/hess-16-1239-2012.pdf
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spelling doaj-19d545d5ad594e92868e60109d7f5c052020-11-25T02:29:55ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382012-04-011641239125410.5194/hess-16-1239-2012The transferability of hydrological models under nonstationary climatic conditionsC. Z. LiL. ZhangH. WangY. Q. ZhangF. L. YuD. H. YanThis paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET), and streamflow data. Nash-Sutcliffe efficiency (NSE), modified index of agreement (<i>d</i><sub>1</sub>) and water balance error (WBE) were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to parameter instability and non-uniqueness.http://www.hydrol-earth-syst-sci.net/16/1239/2012/hess-16-1239-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C. Z. Li
L. Zhang
H. Wang
Y. Q. Zhang
F. L. Yu
D. H. Yan
spellingShingle C. Z. Li
L. Zhang
H. Wang
Y. Q. Zhang
F. L. Yu
D. H. Yan
The transferability of hydrological models under nonstationary climatic conditions
Hydrology and Earth System Sciences
author_facet C. Z. Li
L. Zhang
H. Wang
Y. Q. Zhang
F. L. Yu
D. H. Yan
author_sort C. Z. Li
title The transferability of hydrological models under nonstationary climatic conditions
title_short The transferability of hydrological models under nonstationary climatic conditions
title_full The transferability of hydrological models under nonstationary climatic conditions
title_fullStr The transferability of hydrological models under nonstationary climatic conditions
title_full_unstemmed The transferability of hydrological models under nonstationary climatic conditions
title_sort transferability of hydrological models under nonstationary climatic conditions
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2012-04-01
description This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET), and streamflow data. Nash-Sutcliffe efficiency (NSE), modified index of agreement (<i>d</i><sub>1</sub>) and water balance error (WBE) were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to parameter instability and non-uniqueness.
url http://www.hydrol-earth-syst-sci.net/16/1239/2012/hess-16-1239-2012.pdf
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