IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i6p3677-d776042.html
   My bibliography  Save this article

Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment

Author

Listed:
  • Hengxu Jin

    (School of Geomatics, Liaoning Technical University, Fuxin 123000, China)

  • Xiaoping Rui

    (College of Earth and Engineering, Hohai University, Nanjing 211100, China)

  • Xiaoyan Li

    (School of Geomatics, Liaoning Technical University, Fuxin 123000, China)

Abstract

Frequent flood hazards in the Raoyang River Basin in western Liaoning, China, have posed serious threats to people’s lives and property. In an effort to study the simulation efficiencies of hydrological models in this arid and semi-arid catchment, this study examined the performance of the Xin’anjiang model, the Liaoning unsaturated model, and the DHF model in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China. Additionally, this paper proposed an improved DHF model, which considers the impoundment and regulation of small- and medium-sized reservoirs in the upper reaches of the basin. The flood simulation results demonstrated that the Xin’anjiang model was difficult to apply in this area because the average value of its Nash–Sutcliffe efficiency (NSE) was as low as 0.31. Meanwhile, the simulation efficiencies of the Liaoning unsaturated model and the DHF model were higher than that of the Xin’anjiang model, but the relative error of flood peak discharge and runoff depth for most floods were still high and could not meet the actual forecast requirements by the Reservoir Administration Bureau of Liaoning Province. Overall, the improved DHF model showed the best efficiency, and the mean value of the NSE reached 0.79. Therefore, the improved DHF model has good applicability in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China.

Suggested Citation

  • Hengxu Jin & Xiaoping Rui & Xiaoyan Li, 2022. "Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3677-:d:776042
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/6/3677/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/6/3677/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yun Xing & Huili Chen & Qiuhua Liang & Xieyao Ma, 2022. "Improving the performance of city-scale hydrodynamic flood modelling through a GIS-based DEM correction method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2313-2335, July.
    2. Bin Guo & Weihong Li & Jinyun Guo & Chuanfa Chen, 2015. "Risk Assessment of Regional Irrigation Water Demand and Supply in an Arid Inland River Basin of Northwestern China," Sustainability, MDPI, vol. 7(9), pages 1-16, September.
    3. Binquan Li & Zhongmin Liang & Qingrui Chang & Wei Zhou & Huan Wang & Jun Wang & Yiming Hu, 2020. "On the Operational Flood Forecasting Practices Using Low-Quality Data Input of a Distributed Hydrological Model," Sustainability, MDPI, vol. 12(19), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenying Zeng & Songbai Song & Yan Kang & Xuan Gao & Rui Ma, 2022. "Response of Runoff to Meteorological Factors Based on Time-Varying Parameter Vector Autoregressive Model with Stochastic Volatility in Arid and Semi-Arid Area of Weihe River Basin," Sustainability, MDPI, vol. 14(12), pages 1-12, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan Zhou & Zhongmin Liang & Binquan Li & Yixin Huang & Kai Wang & Yiming Hu, 2021. "Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    2. Mengya Hua & Yuyan Zhou & Cailian Hao & Qiang Yan, 2023. "Analyzing the Drivers of Agricultural Irrigation Water Demand in Water-Scarce Areas: A Comparative Study of Two Regions with Different Levels of Irrigated Agricultural Development," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    3. Joško Trošelj & Han Soo Lee & Lena Hobohm, 2023. "Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations," Sustainability, MDPI, vol. 15(18), pages 1-33, September.
    4. Jingyu Li & Yangbo Chen & Yanzheng Zhu & Jun Liu, 2023. "Study of Flood Simulation in Small and Medium-Sized Basins Based on the Liuxihe Model," Sustainability, MDPI, vol. 15(14), pages 1-16, July.
    5. Mengran Fu & Bin Guo & Weijiao Wang & Juan Wang & Lihua Zhao & Jianlin Wang, 2019. "Comprehensive Assessment of Water Footprints and Water Scarcity Pressure for Main Crops in Shandong Province, China," Sustainability, MDPI, vol. 11(7), pages 1-18, March.
    6. Zhenzhen Zhao & Aiwen Lin & Jiandi Feng & Qian Yang & Ling Zou, 2016. "Analysis of Water Resources in Horqin Sandy Land Using Multisource Data from 2003 to 2010," Sustainability, MDPI, vol. 8(4), pages 1-18, April.
    7. Fei Wang & Yaning Chen & Zhi Li & Gonghuan Fang & Yupeng Li & Zhenhua Xia, 2019. "Assessment of the Irrigation Water Requirement and Water Supply Risk in the Tarim River Basin, Northwest China," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    8. Yang Wang & Shuai Zhang & Xueer Chang, 2020. "Evapotranspiration Estimation Based on Remote Sensing and the SEBAL Model in the Bosten Lake Basin of China," Sustainability, MDPI, vol. 12(18), pages 1-17, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3677-:d:776042. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.