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Catchment Variability and Parameter Estimation in Multi-Objective Regionalisation of a Rainfall–Runoff Model

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  • Dave Deckers
  • Martijn Booij
  • Tom Rientjes
  • Maarten Krol

Abstract

This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and physical catchment characteristics (PCCs). The objective is to test robustness of regionalisation by assessing if generalisation of a wide range of climatic, topographic and physiographic settings in a regional model favours simulation of stream flow at ungauged catchments. Constraints in this work are very stringent performance measures for selection of catchments to establish the regional model and the selection of only PCCs that are available through the database of the National River Flow Archive in the United Kingdom. As such some PCCs have been ignored that have proven to be effective in other studies. For this study 56 well-gauged catchments in England and Wales are used. For model calibration and runoff simulation of ungauged catchments the HBV model is applied. Optimum parameter sets are derived for 48 catchments through Monte Carlo Simulation using an 8-year simulation period. This study aims to adequately simulate all aspects of the hydrograph at the ungauged catchment and therefore four single objective functions are combined in a multi-objective function. After calibration, 17 catchments that are widely spread over England and Wales are selected to establish relationships for seven selected model parameters using 14 PCCs (area, mean elevation, hypsometric integral, catchment shape, standard average annual rainfall, five types of land use and four classes of hydrogeology). Single and multiple regression analysis are applied to identify these relationships. For six model parameters statistically significant relationships could be established three of which are plausible on the basis of hydrologic interpretation. The established relationships are validated at eight gauged catchments that are spread over the UK and cover a large range of values of catchment descriptors. These catchments are assumed ungauged and results revealed that, in general, model parameters determined by the established regional relationships do not perform better as compared to default parameter values. Similar results are obtained for additional validation runs using catchments that are not used in the regionalisation procedure. Since these parameters are based on model performance assessments in a wide range of catchment settings, this suggests that large variability in settings of PCCs does not favour regionalisation. Therefore, for selected catchments the applicability of regionalisation by principles of catchment similarity for HBV model parameters may be questioned. Copyright The Author(s) 2010

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  • Dave Deckers & Martijn Booij & Tom Rientjes & Maarten Krol, 2010. "Catchment Variability and Parameter Estimation in Multi-Objective Regionalisation of a Rainfall–Runoff Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3961-3985, November.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:14:p:3961-3985
    DOI: 10.1007/s11269-010-9642-8
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    References listed on IDEAS

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    1. Pasquale Cutore & Gabriella Cristaudo & Alberto Campisano & Carlo Modica & Antonino Cancelliere & Giuseppe Rossi, 2007. "Regional Models for the Estimation of Streamflow Series in Ungauged Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 789-800, May.
    2. K. Engeland & H. Hisdal, 2009. "A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(12), pages 2567-2586, September.
    3. Fayez Abdulla & Tamer Eshtawi & Hamed Assaf, 2009. "Assessment of the Impact of Potential Climate Change on the Water Balance of a Semi-arid Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(10), pages 2051-2068, August.
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    5. Ye Tian & Yue-Ping Xu & Xu-Jie Zhang, 2013. "Assessment of Climate Change Impacts on River High Flows through Comparative Use of GR4J, HBV and Xinanjiang Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2871-2888, June.
    6. Wilfredo Caballero & Ataur Rahman, 2014. "Application of Monte Carlo simulation technique for flood estimation for two catchments in New South Wales, Australia," 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. 74(3), pages 1475-1488, December.
    7. Koppuravuri Ramabrahmam & Venkata Reddy Keesara & Raghavan Srinivasan & Deva Pratap & Venkataramana Sridhar, 2021. "Flow Simulation and Storage Assessment in an Ungauged Irrigation Tank Cascade System Using the SWAT Model," Sustainability, MDPI, vol. 13(23), pages 1-18, November.
    8. Jianzhong Zhou & Shuo Ouyang & Xuemin Wang & Lei Ye & Hao Wang, 2014. "Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 767-783, February.
    9. Minglong Dai & Jianzhong Zhou & Xiang Liao, 2016. "Research on Combination Forecast Mode of Conceptual Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4483-4499, October.
    10. Pao-Shan Yu & Tao-Chang Yang & Chen-Min Kuo & Yi-Tai Wang, 2014. "A Stochastic Approach for Seasonal Water-Shortage Probability Forecasting Based on Seasonal Weather Outlook," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3905-3920, September.
    11. H. Kim, 2014. "Adequacy of a Multi-objective Regional Calibration Method Incorporating a Sequential Regionalisation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5507-5526, December.
    12. Sawano, Shinji & Hotta, Norifumi & Tanaka, Nobuaki & Tsuboyama, Yoshio & Suzuki, Masakazu, 2015. "Development of a simple forest evapotranspiration model using a process-oriented model as a reference to parameterize data from a wide range of environmental conditions," Ecological Modelling, Elsevier, vol. 309, pages 93-109.
    13. Juliana Mendes & Rodrigo Maia, 2016. "Hydrologic Modelling Calibration for Operational Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5671-5685, December.
    14. H. S. Kim, 2016. "Potential Improvement of the Parameter Identifiability in Ungauged Catchments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 3207-3228, July.

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