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Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction

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  • Jie Chen
  • François Brissette

Abstract

Ensemble streamflow predictions (ESPs) offer great potential benefits for water resource management, as they contain key probabilistic information for analyzing prediction uncertainty. Ensemble weather forecasts (EWFs) are usually incorporated into ESPs to provide climate information. However, there is no simple way to combine both of them, since EWFs are generally biased and under-dispersed. This study presents a new short-term (1 to 7 lead days) probabilistic streamflow prediction system combining stochastic weather generation and EWFs. The bias and under-dispersion of EWFs were first corrected using a weather generator-based post-processing approach (GPP). The corrected weather forecasts were then coupled with a hydrological model for streamflow forecasts. The proposed GPP forecast was compared against two other forecasts, one using the raw EWF (GFS), and the other using a stochastic weather generator (WG). The comparison was carried out over two Quebec watersheds, using a set of deterministic and probabilistic verification metrics. The deterministic metrics showed that the GPP forecast is consistently the best at predicting the ensemble mean streamflow for both watersheds and for all the leads ranging between 1 and 7 days, followed by the WG forecast. The probabilistic metrics showed negative or near zero skill retained by the GFS forecast for the first 7 lead days. The WG system was much more skillful than the GFS. The GPP forecast consistently displayed the highest skill and reliability in terms of all the metrics applied. With increasing lead days, the skill and reliability of the GPP forecast tend to converge toward that of the WG forecast, indicating that the short-term GPP forecast could easily be linked to a pure WG forecast to extend the forecast horizon. Copyright Springer Science+Business Media Dordrecht 2015

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  • Jie Chen & François Brissette, 2015. "Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3329-3342, July.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:9:p:3329-3342
    DOI: 10.1007/s11269-015-1001-3
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    References listed on IDEAS

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    1. Marie Minville & François Brissette & Stéphane Krau & Robert Leconte, 2009. "Adaptation to Climate Change in the Management of a Canadian Water-Resources System Exploited for Hydropower," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(14), pages 2965-2986, November.
    2. Aynur Şensoy & Gökçen Uysal, 2012. "The Value of Snow Depletion Forecasting Methods Towards Operational Snowmelt Runoff Estimation Using MODIS and Numerical Weather Prediction Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3415-3440, September.
    3. Dushmanta Dutta & Wendy Welsh & Jai Vaze & Shaun Kim & David Nicholls, 2012. "A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(15), pages 4397-4415, December.
    4. Yonas Ghile & Roland Schulze, 2010. "Evaluation of Three Numerical Weather Prediction Models for Short and Medium Range Agrohydrological Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 1005-1028, March.
    5. Guolei Tang & Huicheng Zhou & Ningning Li & Feng Wang & Yajun Wang & Deping Jian, 2010. "Value of Medium-range Precipitation Forecasts in Inflow Prediction and Hydropower Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2721-2742, September.
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    1. Crescenzo Pepe & Silvia Maria Zanoli, 2024. "Digitalization, Industry 4.0, Data, KPIs, Modelization and Forecast for Energy Production in Hydroelectric Power Plants: A Review," Energies, MDPI, vol. 17(4), pages 1-35, February.
    2. Richard Arsenault & Marco Latraverse & Thierry Duchesne, 2016. "An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4363-4380, September.
    3. Đurica Marković & Jasna Plavšić & Nesa Ilich & Siniša Ilić, 2015. "Non-parametric Stochastic Generation of Streamflow Series at Multiple Locations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4787-4801, October.

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