Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method: A case study of SWAT model applied to Yingluoxia watershed in northwest China

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.

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Identifying Key Hydrological Processes in Highly Urbanized Watersheds for Flood Forecasting with a Distributed Hydrological Model

Water ◽

10.3390/w11081641 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1641 ◽

Cited By ~ 7

Author(s):

Huanyu Wang ◽

Yangbo Chen

Keyword(s):

Water Content ◽

Parameter Uncertainty ◽

Hydrological Model ◽

Flood Forecasting ◽

Hydrological Processes ◽

Model Parameters ◽

Hydrological Models ◽

Distributed Hydrological Model ◽

Physically Based ◽

Distributed Hydrological Models

The world has experienced large-scale urbanization in the past century, and this trend is ongoing. Urbanization not only causes land use/cover (LUC) changes but also changes the flood responses of watersheds. Lumped conceptual hydrological models cannot be effectively used for flood forecasting in watersheds that lack long time series of hydrological data to calibrate model parameters. Thus, physically based distributed hydrological models are used instead in these areas, but considerable uncertainty is associated with model parameter derivation. To reduce model parameter uncertainty in physically based distributed hydrological models for flood forecasting in highly urbanized watersheds, a procedure is proposed to control parameter uncertainty. The core concept of this procedure is to identify the key hydrological and flood processes in the highly urbanized watersheds and the sensitive model parameters related to these processes. Then, the sensitive model parameters are adjusted based on local runoff coefficients to reduce the parameter uncertainty. This procedure includes these steps: collecting the latest LUC information or estimating this information using satellite remote sensing images, analyzing LUC spatial patterns and identifying dominant LUC types and their spatial structures, choosing and establishing a distributed hydrological model as the forecasting tool, and determining the initial model parameters and identifying the key hydrological processes and sensitive model parameters based on a parameter sensitivity analysis. A highly urbanized watershed called Shahe Creek in the Pearl River Delta area was selected as a case study. This study finds that the runoff production processes associated with both the ferric luvisol and acric ferralsol soil types and the runoff routing process on urban land are key hydrological processes. Additionally, the soil water content under saturated conditions, the soil water content under field conditions and the roughness of urban land are sensitive parameters.

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Uncertainty analysis of hydrological model parameters based on the bootstrap method: A case study of the SWAT model applied to the Dongliao River Watershed, Jilin Province, Northeastern China

Science China Technological Sciences ◽

10.1007/s11431-013-5385-0 ◽

2013 ◽

Vol 57 (1) ◽

pp. 219-229 ◽

Cited By ~ 17

Author(s):

Zheng Zhang ◽

WenXi Lu ◽

HaiBo Chu ◽

WeiGuo Cheng ◽

Ying Zhao

Keyword(s):

Uncertainty Analysis ◽

Hydrological Model ◽

Bootstrap Method ◽

Swat Model ◽

Northeastern China ◽

Jilin Province ◽

Model Parameters ◽

River Watershed ◽

The Bootstrap Method

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Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa

Advances in Geosciences ◽

10.5194/adgeo-9-137-2006 ◽

2006 ◽

Vol 9 ◽

pp. 137-143 ◽

Cited By ~ 60

Author(s):

J. Schuol ◽

K. C. Abbaspour

Keyword(s):

West Africa ◽

Model Calibration ◽

Large Scale ◽

Assessment Tool ◽

Hydrological Models ◽

Scale Models ◽

Distributed Hydrological Models ◽

Water Assessment ◽

River Niger

Abstract. Distributed hydrological models like SWAT (Soil and Water Assessment Tool) are often highly over-parameterized, making parameter specification and parameter estimation inevitable steps in model calibration. Manual calibration is almost infeasible due to the complexity of large-scale models with many objectives. Therefore we used a multi-site semi-automated inverse modelling routine (SUFI-2) for calibration and uncertainty analysis. Nevertheless, the question of when a model is sufficiently calibrated remains open, and requires a project dependent definition. Due to the non-uniqueness of effective parameter sets, parameter calibration and prediction uncertainty of a model are intimately related. We address some calibration and uncertainty issues using SWAT to model a four million km2 area in West Africa, including mainly the basins of the river Niger, Volta and Senegal. This model is a case study in a larger project with the goal of quantifying the amount of global country-based available freshwater. Annual and monthly simulations with the "calibrated" model for West Africa show promising results in respect of the freshwater quantification but also point out the importance of evaluating the conceptual model uncertainty as well as the parameter uncertainty.

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Evaluating two GIS-based semi-distributed hydrological models in the Bhagirathi-Alkhnanda River catchment in India

Water Policy ◽

10.2166/wp.2020.159 ◽

2020 ◽

Vol 22 (6) ◽

pp. 991-1014

Author(s):

Dilip Kumar ◽

Rajib Kumar Bhattacharjya

Keyword(s):

Comparative Analysis ◽

Swat Model ◽

Peak Discharge ◽

Climate Change Scenarios ◽

Hydrological Models ◽

Hydrologic Models ◽

Future Prediction ◽

Pass Through ◽

Distributed Hydrological Models ◽

Different Parts

Abstract The hydrological models are used for simulating the runoff of a river basin based on available rainfall data and other parameters. Over the years, several hydrological models have been developed in different parts of the world. Two such semi-distributed hydrologic models are SWAT and HEC-HMS. In this study, a comparative analysis has been carried out to evaluate the performance of these two distributed hydrological models as a flood forecasting tool. The Alkhnanda and Bhagirathi rivers, which flow into the Tehri Reservoir, Uttarakhand and pass through Tehri, Uttarkashi and Chamoli districts of Uttarakhand, India, are selected for the analysis. The performance of these two models is evaluated by using standard statistical methods. The comparative analysis of these two models shows that the SWAT model is performing slightly better in comparison to the HEC-HMS model, especially in the lean period. The underestimation of peak discharge may be due to the contribution of significant snowmelt discharge during the rainy season. The models are also used to predict future discharge under different climate change scenarios. The future prediction shows that the peak discharge of Alkhnanda may be increased by 27 and 47% under RCP4.5 and RCP8.5, respectively.

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