Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data

نویسندگان

چکیده

Abstract. Although integrated water resource models are indispensable tools for management at various scales, it is of primary importance to ensure their proper fitting on hydrological variables, avoiding flaws related equifinality. An innovative stepwise methodology therefore proposed, which can be applied any river basin model, from catchment continental scale as far or land surface concerned. The focuses hydrosystems considering both and groundwater, well internal fluxes such baseflow. It based the thorough analysis signal transformation by components a coupled surface–subsurface hydrosystem in nested approach that considers conditionality parameter fields input forcing fluxes. decomposition frequency domain with HYMIT (HYdrological MInimalist Transfer function) method (Schuite et al., 2019). Parameters derived used fit model CaWaQS3.02 using methodology, relies successive Markov chain Monte Carlo optimizations objective functions representing dependency This new enables significant progress made terms spatial distribution parameters balance regional scale. use many control stations discharge gauging leads coarse then refined CaWaQS its own mesh. exemplified Seine River (∼76 000 km2). In particular, possible spatially identify fundamental values, rainfall partitioning into actual evapotranspiration, runoff aquifer recharge through impluvium, time domains. Such fitted facilitates overall detailed territorial functioning basin, explicitly including system. A reference piezometric map upmost free units budget established, detailing all external up exchanges between eight simulated layers. results showed contribution system network varies within wide range (5 %–96 %), an outlet 67 %. geological substratum greatly influences groundwater discharge.

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ژورنال

عنوان ژورنال: Geoscientific Model Development

سال: 2023

ISSN: ['1991-9603', '1991-959X']

DOI: https://doi.org/10.5194/gmd-16-353-2023