Moving beyond the cost-loss ratio: Economic assessment of
streamflow forecasts for a risk-averse decision maker
Simon Matte1, Marie-Amélie Boucher1, Vincent Boucher2, and Thomas-Charles Fortier Filion31Dept. of Applied Sciences, Université du Québec à Chicoutimi, 555, boulevard de l’Université, Chicoutimi, G7H 2B1, Canada 2Dept. of Economics, Université Laval, 1025, avenue des Sciences-Humaines, Québec, G1V 0A6, Canada 3Québec Government Direction of Hydrologic Expertise, 675, boul. René Lévesque Est., Québec, G1R 5V7, Canad
Abstract. A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority, if not all, of existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known CARA utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses rather on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exists many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles and a variant of the latter that also includes an estimation of variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in south central Quebec, Canada. The assessment of forecasts is performed for lead times of one to five days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution.
Matte, S., Boucher, M.-A., Boucher, V., and Fortier Filion, T.-C.: Moving beyond the cost-loss ratio: Economic assessment of
streamflow forecasts for a risk-averse decision maker, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-495, in review, 2016.