A distributed runoff model for the mountainous region of the Heihe River Basin (China) based on the spatial modeling environment (SME) II: model calibration and validation

Jiao, Wenxian; Xu, Zhenggang

doi:10.1007/s12665-012-2047-7

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…e results showed that the change of land use type in reclamation area had a significant influence on waterlogging frequency, and its influence increased with the shortening of rainfall recurrence interval. Jiao et al combined the SWMM model with Multi_O (Multiobjective Optimization) algorithm, and put forward the technical scheme optimization framework of LID (Low impact development), which was successfully applied to an engineering example [5]. Zhu et al have studied the performance of green roofs in reducing runoff, peak value, and pollution control.…”

Section: Introductionmentioning

confidence: 99%

Research on Multiobjective Optimization of Sponge City Based on SWMM Model

Luo¹,

Hu²,

Sun³

et al. 2022

Mobile Information Systems

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With the acceleration of urbanization, the hardened area of the city is increasing, the rainwater runoff is increasing, and the pressure on the urban drainage network is increasing, resulting in urban waterlogging which seriously endangers people's travel safety. SC (sponge city) should take the city as the catchment area, and through the self-regulation of the water system, reduce the consumption of water resources and the discharge of pollutants into the water environment to the maximum extent, meet the production and life of residents to the maximum extent, adapt to the climate change, and serve the ecological balance. Based on SWMM (stormwater management model) model, this study constructed an SC planning and design method based on the coupling of multiobjective optimization and comprehensive evaluation and established a multi-model based on fast classification and non-dominated genetic algorithm (NSGA-II). The results show that compared with the results calculated by other methods, the multiobjective comprehensive optimization model established in this study and the results calculated by the genetic algorithm NSGA-II shorten the optimization period by 1.44%, improve the quality reliability by 9.86%, reduce the total cost by 0.66%, and reduce the environmental impact by 0.93%. The conclusion shows that it reduces the average discharge flow of the discharge port, relieves the drainage pressure of the pipe network, reduces the risk of waterlogging in the city, etc., and it is more suitable for dealing with rainfall events in medium and small return periods.

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Section: Introductionmentioning

confidence: 99%

Research on Multiobjective Optimization of Sponge City Based on SWMM Model

Luo¹,

Hu²,

Sun³

et al. 2022

Mobile Information Systems

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“…It shows that with the continuous expansion of the cultivated land area in the basin, the runoff has decreased observably since 1967. The shortage of water resource has become a restricting factor in the local economy and society's developments (Jiao et al [7,8]). The runoff from the mountain region accounts for a high proportion of the water resources in Heihe River's midstream and downstream region.…”

Section: Introductionmentioning

confidence: 99%

“…Although it shows some improvement over the simulations using distributed hydrologic models, results still need to improve to agree with the observed series. Jiao et al [8] used a Spatial Modeling Environment (SME) model to simulate the streamflow at Yingluoxia station from the upstream Heihe River Basin model, with the model's simulated flow higher than the observed data. Li et al [25] and Wu et al [26] applied SWAT to simulate daily rainfall runoff in the upper and midstream of the Heihe River Basin, which showed improvement of model accuracy with the correlation coefficient of 0.89.…”

Section: Introductionmentioning

confidence: 99%

Application of Hydrological Model PRMS to Simulate Daily Rainfall Runoff in Zamask-Yingluoxia Subbasin of the Heihe River Basin

Fei

Huang

Cai

et al. 2017

Water

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Abstract:The Precipitation-Runoff Modeling System (PRMS) has been applied to simulate rainfall runoff in Zamask-Yingluoxia subbasin of the Heihe River Basin in this study. By using observed data in the subbasin, the model has been calibrated by comparing model simulations of daily stream flow to observed data at Yinglouxia station for the period of summer in 2004. Then model verification was conducted by keeping the same model parameters for the simulation of the period from 1 January 2003 to 31 December 2006. Results from model verification indicate that the model is able to provide good accuracy of simulations of daily rainfall runoff and river flow at Yinglouxia station, with a Nash-Sutcliffe Efficiency coefficient of 0.90 and the root-mean-square error of 15.7 m 3 /s. The error of maximum peak flow is 6.9 m 3 /s (1.8%) and the error of mean flow is 1.4 m 3 /s (2.5%). Comparing to previous studies, results indicate the improvement of model accuracy in simulations of daily rainfall runoff. The calibrated and verified hydrological model can be used to support flood hazard mitigations and water resource management in the Zamask-Yingluoxia subbasin.

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“…Hydrological modeling has been attempted for both the entire HRB and ZB alone. However, the modeling efforts were focused either on the surface water [ Jiao and Xu , ; Li et al ., ; Z. L. Li et al ., ; Zang and Liu , ] or on the groundwater [ Hu et al ., ; Wen et al ., ]. Fully integrated SW‐GW modeling has not been implemented.…”

Section: Introductionmentioning

confidence: 99%

Systematic assessment of the uncertainty in integrated surface water‐groundwater modeling based on the probabilistic collocation method

Zheng

Tian

et al. 2014

Water Resources Research

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Systematic uncertainty analysis (UA) has rarely been conducted for integrated modeling of surface water-groundwater (SW-GW) systems, which is subject to significant uncertainty, especially at a large basin scale. The main objective of this study was to explore an innovative framework in which a systematic UA can be effectively and efficiently performed for integrated SW-GW models of large river basins and to illuminate how process understanding, model calibration, data collection, and management can benefit from such a systematic UA. The framework is based on the computationally efficient Probabilistic Collocation Method (PCM) linked with a complex simulation model. The applicability and advantages of the framework were evaluated and validated through an integrated SW-GW model for the Zhangye Basin in the middle Heihe River Basin, northwest China. The framework for systematic UA allows for a holistic assessment of the modeling uncertainty, yielding valuable insights into the hydrological processes, model structure, data deficit, and potential effectiveness of management. The study shows that, under the complex SW-GW interactions, the modeling uncertainty has great spatial and temporal variabilities and is highly output-dependent. Overall, this study confirms that a systematic UA should play a critical role in integrated SW-GW modeling of large river basins, and the PCM-based approach is a promising option to fulfill this role.

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A distributed runoff model for the mountainous region of the Heihe River Basin (China) based on the spatial modeling environment (SME) II: model calibration and validation

Cited by 6 publications

References 9 publications

Research on Multiobjective Optimization of Sponge City Based on SWMM Model

Research on Multiobjective Optimization of Sponge City Based on SWMM Model

Application of Hydrological Model PRMS to Simulate Daily Rainfall Runoff in Zamask-Yingluoxia Subbasin of the Heihe River Basin

Systematic assessment of the uncertainty in integrated surface water‐groundwater modeling based on the probabilistic collocation method

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