Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker
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 rat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-06-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/21/2967/2017/hess-21-2967-2017.pdf |
| _version_ | 1818179849612689408 |
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| author | S. Matte M.-A. Boucher V. Boucher T.-C. Fortier Filion |
| author_facet | S. Matte M.-A. Boucher V. Boucher T.-C. Fortier Filion |
| author_sort | S. Matte |
| collection | DOAJ |
| description | 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 of, if
not all, 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 Constant Absolute Risk Aversion
(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 on comparing different types of ensemble forecasts. There are
multiple ways of assessing and representing forecast uncertainty.
Consequently, there exist 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 state variable uncertainty. This comparison takes place for the
Montmorency River, a small flood-prone watershed in southern central Quebec,
Canada. The assessment of forecasts is performed for lead times of 1 to 5
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. Hence, post-processing forecasts to avoid
over-forecasting could help improve both the quality and the value of
forecasts. |
| first_indexed | 2024-12-11T21:10:25Z |
| format | Article |
| id | doaj.art-deafe38d96854048b07c15be3542198a |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-11T21:10:25Z |
| publishDate | 2017-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-deafe38d96854048b07c15be3542198a2022-12-22T00:50:44ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382017-06-01212967298610.5194/hess-21-2967-2017Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision makerS. Matte0M.-A. Boucher1V. Boucher2T.-C. Fortier Filion3Dept. of Applied Sciences, Université du Québec à Chicoutimi, 555, boulevard de l'Université, Chicoutimi, G7H 2B1, CanadaDept. of Applied Sciences, Université du Québec à Chicoutimi, 555, boulevard de l'Université, Chicoutimi, G7H 2B1, CanadaDept. of Economics, Université Laval, 1025, avenue des Sciences-Humaines, Québec, G1V 0A6, CanadaQuébec Government Direction of Hydrologic Expertise, 675, boul. René Lévesque Est., Québec, G1R 5V7, CanadaA 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 of, if not all, 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 Constant Absolute Risk Aversion (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 on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist 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 state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 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. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.http://www.hydrol-earth-syst-sci.net/21/2967/2017/hess-21-2967-2017.pdf |
| spellingShingle | S. Matte M.-A. Boucher V. Boucher T.-C. Fortier Filion Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker Hydrology and Earth System Sciences |
| title | Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker |
| title_full | Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker |
| title_fullStr | Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker |
| title_full_unstemmed | Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker |
| title_short | Moving beyond the cost–loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker |
| title_sort | moving beyond the cost loss ratio economic assessment of streamflow forecasts for a risk averse decision maker |
| url | http://www.hydrol-earth-syst-sci.net/21/2967/2017/hess-21-2967-2017.pdf |
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