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Quantifying multi-year hydrological memory with Catchment Forgetting Curves

Abstract : A climatic anomaly can potentially affect the hydrological behaviour of a catchment for several years. This article presents a new approach to quantifying this multi-year hydrological memory, using exclusively streamflow and climate data. Rather than providing a single value of catchment memory, we aim to describe how this memory fades over time. The precipitation-runoff relationship is analyzed through the concept of elasticity. Elasticity quantifies the change in one quantity caused by the change in another quantity. We analyze the elasticity of the relation between the annual anomalies of runoff yield and humidity index. We identify Catchment Forgetting Curves (CFC) to quantify multi-year catchment memory, considering not only the current year's humidity anomaly but also the anomalies of the preceding years.

The variability of CFCs is investigated on a set of 158 Swedish and 527 French catchments. As expected, French catchments overlying large aquifers exhibit a long memory, i.e., with the impact of climate anomalies detected over several years. In Sweden, the expected effect of the lakes is less clear. For both countries, a relatively strong relationship between the humidity index and memory is identified, with drier regions exhibiting longer memory. Taking into account the multi-year memory has significantly improved the elasticity analysis for 15 % of the catchments. Our work thus underlines the need to account for catchment memory in order to produce meaningful and geographically coherent elasticity indices.

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Submitted on : Tuesday, June 28, 2022 - 3:38:33 PM
Last modification on : Friday, August 5, 2022 - 11:55:18 AM

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Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, Berit Arheimer. Quantifying multi-year hydrological memory with Catchment Forgetting Curves. Hydrology and Earth System Sciences, 2022, 26, pp.2715-2732. ⟨10.5194/hess-26-2715-2022⟩. ⟨insu-03706373⟩

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