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This study explored the influence of the spatial resolution of a gridded weather dataset when inputted in the soil and water assessment tool (SWAT) over the Garonne River watershed. Several datasets are compared: ground-based weather stations, the 8-km SAFRAN product (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie), the 0.5 • CFSR product (Climate Forecasting System Reanalysis) and several derived SAFRAN grids upscaled to 16, 32, 64 and 128 km. The SWAT model, calibrated on weather stations, was successively run with each gridded weather dataset. Performances with SAFRAN up to 64 or 128 km were poor, due to a contraction of the spatial variance of daily precipitation. Performances with 8-km SAFRAN are similar to that of the aggregated 16-and 32-km SAFRAN grids. The~30-km CFSR product was found to perform well at some sites, while in others, its performance was considerably inferior because of grid points where precipitation was overestimated. The same problem was found in the calibration, where data at some weather stations did not appear to be representative of the subwatershed in which they are used to compute hydrology. These results suggest that the difference in the representation of the climate was more influential than its spatial resolution, an analysis that was confirmed by similar performances obtained with the SWAT model calibrated on the 16-and 32-km SAFRAN grids. However, the better performances obtained from these two weather datasets than from the ground-based stations' dataset confirmed the advantage of using the SAFRAN product in SWAT modelling.

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Numerous studies have pointed out the importance of groundwater and surface water interaction (SW-GW) in a river system. However; those functions have rarely been considered in large scale hydrological models. The SWAT-LUD model has been developed based on the Soil and Water Assessment Tool (SWAT) model; and it integrates a new type of subbasin; which is called subbasin-LU (SL); to represent the floodplain area. New modules representing SW-GW exchanges and shallow aquifer denitrification are developed in the SWAT-LUD model. In this study; the SWAT-LUD model was applied to the middle floodplain area of the Garonne catchment in France. The results showed that the SWAT-LUD model could represent the SW-GW exchange and shallow aquifer denitrification appropriately. An annual 44.1 × 10 7 m 3 of water flowed into the river from the study area; but the annual exchanged water volume was 6.4 × 10 7 m 3 ; which represented just 1% of the river discharge. A total of 384 tons of N-NO 3 − (0.023 t·ha −1 ) was consumed by denitrification in the floodplain shallow aquifer annually. The nitrate concentration (N-NO 3 − ) decrease in the channel was 0.12 mg·L −1 ; but in the shallow aquifer it reached 11.40 mg·L −1 ; 8.05 mg·L −1 ; and 5.41 mg·L −1 in LU1; LU2; and LU3; respectively. Our study reveals that; in the Garonne floodplain; denitrification plays a significant role in the attenuation of nitrate associated with groundwater; but the impacts of denitrification on nitrate associated with river water is much less significant.

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Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and −31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources.

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