The role of conceptual hydrologic model calibration in climate change impact on water resources assessment

Todorović, Andrijana; Plavšić, Jasna

doi:10.2166/wcc.2015.086

Cited by 15 publications

(8 citation statements)

References 45 publications

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“…Figure For the benchmark calibration, the model performance in the validation period decreases, compared with the calibration period. The decrease in model performance is consistent with other studies (e.g., Todorovic and Plavsic, 2016), in which model efficiency also decreases if the calibration period is wetter than the validation period. When using only 1-year data for calibration, the performances in the validation period are similar to the benchmark calibration.…”

Section: Evaluation Of the Jinjiang Basin Casesupporting

confidence: 91%

Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins

Sun

Wang

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Physically based distributed hydrological models are widely used for hydrological simulations in various environments. As with conceptual models, they are limited in data-sparse basins by the lack of streamflow data for calibration. Short periods of observational data (less than 1 year) may be obtained from fragmentary historical records of previously existing gauging stations or from temporary gauging during field surveys, which might be of value for model calibration. However, unlike lumped conceptual models, such an approach has not been explored sufficiently for physically based distributed models. This study explored how the use of limited continuous daily streamflow data might support the application of a physically based distributed model in datasparse basins. The influence of the length of the observation period on the calibration of the widely applied soil and water assessment tool model was evaluated in four Chinese basins with differing climatic and geophysical characteristics. The evaluations were conducted by comparing calibrations based on short periods of data with calibrations based on data from a 3-year period, which were treated as benchmark calibrations of the four basins, respectively. To ensure the differences in the model simulations solely come from differences in the calibration data, the generalized likelihood uncertainty analysis scheme was employed for the automatic calibration and uncertainty analysis. In the four basins, contrary to the common understanding of the need for observations over a period of several years, data records with lengths of less than 1 year were shown to calibrate the model effectively, i.e., performances similar to the benchmark calibrations were achieved. The models of the wet Jinjiang and Donghe basins could be effectively calibrated using a shorter data record (1 month), compared with the dry Heihe and upstream Yalongjiang basins (6 months). Even though the four basins are very different, when using 1-year or 6-month (covering a whole dry season or rainy season) data, the results show that data from wet seasons and wet years are generally more reliable than data from dry seasons and dry years, especially for the two dry basins. The results demonstrated that this idea could be a promising approach to the problem of calibration of physically based distributed hydrological models in datasparse basins, and findings from the discussion in this study are valuable for assessing the effectiveness of short-period data for model calibration in real-world applications.

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Section: Evaluation Of the Jinjiang Basin Casesupporting

confidence: 91%

Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins

Sun

Wang

et al. 2017

Hydrol. Earth Syst. Sci.

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“…In scheme 5, (1) Q s , XH U Z and XC U Z are lower in the dry period and higher in rainfall period II than those in scheme 1. The results indicate that the performance of the model run is better in the dry period and rainfall period II because the runoff is usually overestimated in the dry period (Pool et al, 2017;Wang et al, 2017a;Tongal and Booij, 2018;Xiong et al, 2018) and underestimated in the wettest period (Guo et al, 2018;Höge et al, 2018;Pande and Moayeri, 2018;Wang et al, 2018). It is observed that the state variable X s and the flux Q s have larger effects on simulating runoff than the quick-flow (Q q and X q ) mode in rainfall period II.…”

Section: State Variables and Fluxesmentioning

confidence: 95%

Dynamics of hydrological-model parameters: mechanisms, problems and solutions

Lan

Lin

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. It has been demonstrated that the application of time-varying hydrological-model parameters based on dynamic catchment behavior significantly improves the accuracy and robustness of conventional models. However, the fundamental problems for calibrating dynamic parameters still need to be addressed. In this study, five calibration schemes for dynamic parameters in hydrological models were designed to investigate the underlying causes of poor model performance. The five schemes were assessed with respect to the model performance in different flow phases, the transferability of the dynamic parameters to different time periods, the state variables and fluxes time series, and the response of the dynamic parameter set to the dynamic catchment characteristics. Furthermore, the potential reasons for the poor response of the dynamic parameter set to the catchment dynamics were investigated. The results showed that the underlying causes of poor model performance included time-invariant parameters, “compensation” among parameters, high dimensionality and abrupt shifts in the parameters. The recommended calibration scheme exhibited good performance and overcame these problems by characterizing the dynamic behavior of the catchments. The main reason for the poor response of the dynamic parameter set to the catchment dynamics may be the poor convergence performance of the parameters. In addition, the assessment results of the state variables and fluxes and the convergence performance of the parameters provided robust indications of the dominant response modes of the hydrological models in different sub-periods or catchments with distinguishing catchment characteristics.

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“…Sagar et al (2017) acquired prognoses from the PRECIS-RCM and sourced them as feedback to the HBV model for estimation of imminent flow magnitudes of Karnali river watershed in Nepal for the period between 2030 and 2060 under A1B of Special Report on Emission Scenarios (SRES). Todorovic and Plavsic (2016) applied outputs of five GCM-RCM sequences, described by Langshot et al (2013) as feedback in the HBV model to foresee impending flow magnitudes of Kolubara river basin, Serbia. Similarly, Usman et al (2019) employed the HBV to simulate future streamflow in the Soan river basin of Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Prognosis of Hydro-Meteorological Attributes based on Simulation and Projection of Streamflow in a High-Altitude Basin using Hydrologiska Byråns Vattenbalansavdelning (HBV) Model

Burhan¹,

Usman²,

Bukhari³

et al. 2020

AQUADEMIA

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Subsistence of freshwater resources at high altitude regions has remained a paradox for stakeholder communities at both regional and global levels. To address such an issue, Hydrologiska Byråns Vattenbalansavdelning Light (hereafter HBV) model was used to assess hydro-meteorological shifts triggered under climate change scenarios in snow dominant region of Chitral river basin. The model performed well both during calibration and validation periods with Nash Sutcliffe Efficiency values of 0.91 and 0.81 respectively on daily time scale in the basin. The HBV was thereafter engaged for the projection of streamflow in the Chitral river basin using projected data of four statistically downscaled climate models with four emission scenarios for the 21st century. Multi-model ensemble projections of precipitation revealed an increase of up to 165% in monsoon inception period and an increase in temperature of up to 9.5°C in winter to summer transitioning period for the 2070-2099 time slice under a high-end emission scenario. An increase of up to 122% in evapotranspiration was projected in the peak winter months for the 2070-2099 time slice under the high-end emission scenario. Attributed to the significant increases in the temperature and the liquid precipitation, it was projected that basin streamflow had potential to increase by up to 182 % in the monsoon inception period for the 2070-2099 time slice under the high-end emission scenario. It further indicated that precipitation might be falling as liquid rain most of the year, and snow will hardly accumulate in prognosticated future environements of the basin.

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The role of conceptual hydrologic model calibration in climate change impact on water resources assessment

Cited by 15 publications

References 45 publications

Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins

Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins

Dynamics of hydrological-model parameters: mechanisms, problems and solutions

Prognosis of Hydro-Meteorological Attributes based on Simulation and Projection of Streamflow in a High-Altitude Basin using Hydrologiska Byråns Vattenbalansavdelning (HBV) Model

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