Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

Abstract

Abstract. Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias-correction method should be further investigated to remedy this weakness and take more advantage of the ensemble forecasts produced by the climate model. Overall, in this study, bias-corrected ensemble meteorological forecasts appear to be an interesting source of information for hydrological forecasting for lead times up to 1 month. They could also complement ESP for longer lead times.

Examining controls on peak annual streamflow and floods in the Fraser River Basin of British Columbia

“…Thus, sensible heat inputs to the existing high snowpack in the FRB were large, leading to a rapid and voluminous release of meltwater to lower elevations. The peak flow at Hope on 31 May was measured at 15 200 m 3 s −1 , which remains the highest value in the instrumental record (Septer, 2007;BC MOE, 2008). Apparently, neither the 1894 nor the 1948 event was characterized by excessive rainfall coincident with the meltwater peaks.…”

“…The definition of dT /dt used here is dependent upon the APD, which is of course unknown at the time of SWE max ; however, in a predictive context, one could simply use the most recent daily T observation to compute the warming rate within a window of increasing duration. Better still, if hydrological forecasting on the daily to seasonal timescale is of paramount interest, employing a forecast methodology based on an ensemble of hydrological simulations and multiple initializations would constitute a superior approach (Bazile et al, 2017).…”

“…A description of meteorological precursors to the 1894 and 1948 floods is available from the BC MOE (BC MOE, 2008) and also the historical review, based on newspaper accounts, of Septer (2007). According to limited archival data available at two interior locations in the FRB, snowfall amounts during the winter of 1893 and 1894 were near normal over the FRB as a whole, although the snowpack remaining from the previous summer was reportedly larger than usual.…”

“…The Fraser River at Mission (near Hope) peaked on 5 June, but floodwaters did not subside in many areas until early July. A hydraulic modelling exercise conducted in 2008 estimated a peak discharge at Hope in the range of 16 000 to 18 000 m 3 s −1 , with a best guess of 17 000 m 3 s −1 (BC MOE, 2008). The meteorological record for the FRB in 1948 is considerably more complete than for 1894.…”

Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK

“…However, since ESP is limited to the range of past observations, ESP forecasts can have limited skill under non-stationary climate and where initial conditions do not dominate the seasonal hydrological response (Arnal et al, 2018). Nevertheless, the ESP approach is popular among operational agencies thanks to its simplicity, low cost, efficiency and its intuitively appealing nature (Bazile et al, 2017), i.e. ESP is coherent to the human tendency to examine a situation according to past experiences.…”