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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/hess-2019-659
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-659
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 08 Jan 2020

Submitted as: research article | 08 Jan 2020

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A revised version of this preprint is currently under review for the journal HESS.

From skill to value: isolating the influence of end-user behaviour on seasonal forecast assessment

Matteo Giuliani1, Louise Crochemore2, Ilias Pechlivanidis2, and Andrea Castelletti1 Matteo Giuliani et al.
  • 1Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milano, Italy
  • 2Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research Unit, Folkborgsvagen 17, 601 76, Norrkoping, Sweden

Abstract. Recent improvements in initialization procedures and representation of large scale hydro-meteorological processes contributed in advancing the accuracy of hydroclimatic forecasts, which are progressively more skillful over the seasonal and longer timescales. These forecasts are potentially valuable for informing strategic multisector decisions, including irrigated agriculture, where they can improve crop choices and irrigation scheduling. In this operational context, the accuracy associated with the forecast system setup does not necessarily yield proportional marginal benefit, as this is also affected by how forecasts are employed by end-users. This paper contributes a novel framework to quantify the value of hydroclimatic forecasts by extending traditional accuracy assessments with estimates of potential economic benefit to the end-users. We also explore the sensitivity of this benefit to both forecast system setup and end-user behavioral factors. The approach is demonstrated on the Lake Como system (Italy), a regulated lake operated for flood protection and irrigation supply. Our framework relies on an integrated modeling chain composed of three building blocks: bias-adjusted seasonal meteorological forecasts are used as input to the continentally-calibrated E-HYPE hydrological model; predicted lake inflows are used for conditioning the daily lake operations; the resulting lake releases feed an agricultural model to estimate the net profit of the farmers in a downstream irrigation district. Results suggest that despite the gain on average conditions is negligible, during intense drought episodes informing the operations of Lake Como based on seasonal hydrological forecasts allows gaining about 15 % of the farmers' profit with respect to a baseline solution not informed by any forecast. Moreover, our analysis suggests that behavioral factors capturing different perceptions of risk and uncertainty significantly impact on the quantification of the benefit to the end-users, where the estimated forecast value is potentially undermined by different levels of end-user risk aversion. Lastly, our results show an exponential skill-to-value relation where large gains in forecast skills are necessary to generate moderate gains in end-user profit, with the ratio that becomes less demanding during extreme drought events.

Matteo Giuliani et al.

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Matteo Giuliani et al.

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Short summary
This paper contributes a novel framework to quantify the value of hydroclimatic forecasts by extending traditional accuracy assessments with estimates of potential economic benefit to the end-users in the Lake Como basin (Italy). We also explore the sensitivity of this benefit to both forecast system setup and end-user behavioral factors, showing that the estimated forecast value is potentially undermined by different levels of end-user risk aversion.
This paper contributes a novel framework to quantify the value of hydroclimatic forecasts by...
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