A comparison of single- and multi-gauge based calibrations for hydrological modeling of the Upper Daning River Watershed in China's Three Gorges Reservoir Region

Gong, Ya Dong; Shen, Zhenyao; Liu, Ruimin; Qian, Hong; Xing, Wu

doi:10.2166/nh.2012.021

Cited by 29 publications

(7 citation statements)

References 30 publications

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“…Assessment of the sediment flux of a river system is predominantly dependent upon the number and locations of measuring stations, the amount of available data, reliability, accuracy, the temporal resolution of the data, and finally, the length of the records (Walling, ). A number of key SWAT parameters (for example, SPCON, SPEXP, and PRF) can only have single values across the whole watershed; however, in a large watershed, these parameters may vary considerably and this restriction could affect modeling performance (Gong, Shen, Liu, Hong, & Wu, ). The PBIAS for flow tends to be higher in the validation period as compared to the calibration period, which might be due to over fitting of volume‐sensitive parameters (Bennett, Werner, & Schnorbus, ), assumptions that the calibrated parameters are stationary (and valid for both calibration and validation periods), or not incorporating dynamic land cover.…”

Section: Resultsmentioning

confidence: 99%

Land use change uncertainty impacts on streamflow and sediment projections in areas undergoing rapid development: A case study in the Mekong Basin

et al. 2017

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Quantitative understanding of potential changes in streamflow and sediment load is complicated by uncertainty related to land use change projections, which is characterized by a high uncertainty in terms of demand (quantity) and location of changes (spatial distribution). We simulate the Sesan, Srepok, and Sekong Rivers (3S), the most important tributaries of the lower Mekong River, with the Soil and Water Assessment Tool (SWAT) to investigate the implications of conversion of forest to agricultural lands. Multiple land use transitions in the 3S basin are projected using the Land Change Modeler. The uncertainty in land use projection was addressed using an ensemble forecasting approach for 2060, combining (a) three land demand scenarios, (b) two transition potential modeling approaches (i.e., approach to create maps of the likelihood for areas to transition from one land use type to another), and (c) retaining or not protected areas. Land demand leads to the greatest uncertainty in land use change projections. Transition potential modeling approaches do not make much difference in the total change, but can result in spatial variations of change. Retaining protected areas can contribute significantly to uncertainty in land use change projections. Decrease in annual streamflow of the 3S basin varied from 3% to 21%, and changes in annual sediment outflux from the basin ranged from −8% to 249% for simulated scenarios. Land use demand uncertainty results in the highest streamflow and sediment load changes and can thus have major consequences for water and sediment management strategies in areas undergoing rapid development.

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Section: Resultsmentioning

confidence: 99%

Land use change uncertainty impacts on streamflow and sediment projections in areas undergoing rapid development: A case study in the Mekong Basin

et al. 2017

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“…Assessment of the sediment flux of a river system is predominantly dependent upon the number and locations of measuring stations, the amount of available data, reliability, accuracy, the temporal resolution of the data, and, finally, the length of the records (Walling, 2008). A number of key SWAT parameters (for example, SPCON, SPEXP and PRF) can only have single values across the whole watershed; however, in a large watershed these parameters may vary considerably and this restriction could affect modeling performance (Gong et al, 2012). The PBIAS for flow tends to be higher in the validation period as compared to the calibration period, which might be due to over fitting of volume-sensitive parameters (Bennett et al, 2012), assumptions that the calibrated parameters are stationary (and valid for both calibration and validation periods), or not incorporating dynamic land cover.…”

Section: Calibration and Validation Of The Swat Modelmentioning

confidence: 99%

Uncertainty in flow and sediment projections due to future climate scenarios for the 3S Rivers in the Mekong Basin

Shrestha

Cochrane

Caruso

et al. 2016

Journal of Hydrology

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Reliable projections of discharge and sediment are essential for future water and sediment management plans under climate change, but these are subject to numerous uncertainties. This study assessed the uncertainty in flow and sediment projections using the Soil and Water Assessment Tool (SWAT) associated with three Global Climate Models (GCMs), three Representative Concentration Pathways (RCPs) and three model parameter (MP) sets for the 3S Rivers in the Mekong River Basin. The uncertainty was analyzed for the near-term future (2021-2040 or 2030s) and medium-term future (2051-2070 or 2060s) time horizons. Results show that dominant sources of uncertainty in flow and sediment constituents vary spatially across the 3S basin. For peak flow, peak sediment, and wet seasonal flows projection, the greatest uncertainty sources also vary with time horizon. For 95% low flows and for seasonal and annual flow projections, GCM and MP were the major sources of uncertainty, whereas RCPs had less of an effect. The uncertainty due to RCPs is large for annual sediment load projections. While model parameterization is the major source of uncertainty in the short term (2030s), GCMs and RCPs are the major contributors to uncertainty in flow and sediment projections in the longer term (2060s). Overall, the uncertainty in sediment load projections is larger than the uncertainty in flow projections. In general, our results suggest the need to investigate the major contributing sources of uncertainty in large basins temporally and at different scales, as this can have major consequences for water and sediment management decisions. Further, since model parameterization uncertainty can play a significant role for flow and sediment projections, there is a need to incorporate hydrological model parameter uncertainty in climate change studies and efforts to reduce the parameter uncertainty as much as possible should be considered through a careful calibration and validation process.

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“…In particular, the need for automatic calibration has been broadly recognized and increasingly emphasized for many years, and calibrations with multiple objective functions or criteria have been widely adopted [2]. Therefore, in recent years, several automatic routines that use a multi-objective formulation of the calibration problem that has been introduced to rainfall-runoff modeling [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Robust Parameter Estimation Framework of a Rainfall-Runoff Model Using Pareto Optimum and Minimax Regret Approach

Kim

Chung

Won

et al. 2015

Water

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This study developed a robust parameter set (ROPS) selection framework for a rainfall-runoff model that considers multi-events using the Pareto optimum and minimax regret approach (MRA). The calibrated parameter sets based on the Nash-Sutcliffe coefficient (NSE) for two events were derived using a genetic algorithm. We generated 41 combinations for weighting values between two events for the multi-event objective function and derived 41 Pareto optimum points that were considered as the ROPS candidates. Then, two different approaches for parameter selection were proposed to determine the ROPS among the candidates: one uses NSE only and the other uses four performance measures (NSE, peak flow error, root mean square error and percentage of bias). In the NSE-only method, five events, including two events from the calibration set and three events from the evaluation set, were used, and the ROPS was selected based on the regrets of both the calibration and the evaluation sets. In the multiple (i.e., four) performance measure method, only three events from the evaluation set were used and the ROPS was determined based on the regrets of twelve different cases, including three events with four measures. As a result, while single-and multi-event optimizations produced satisfying results for the calibration events, the optimized parameters from the single-event calibration do not perform well for another event, even one with the same criteria, such as NSE. The results of this study suggest that the optimized parameter set from the well-weighted objective function can successfully simulate not only hydrographs

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A comparison of single- and multi-gauge based calibrations for hydrological modeling of the Upper Daning River Watershed in China's Three Gorges Reservoir Region

Cited by 29 publications

References 30 publications

Land use change uncertainty impacts on streamflow and sediment projections in areas undergoing rapid development: A case study in the Mekong Basin

Land use change uncertainty impacts on streamflow and sediment projections in areas undergoing rapid development: A case study in the Mekong Basin

Uncertainty in flow and sediment projections due to future climate scenarios for the 3S Rivers in the Mekong Basin

Robust Parameter Estimation Framework of a Rainfall-Runoff Model Using Pareto Optimum and Minimax Regret Approach

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