The effect of spatial distribution of small farm reservoirs on their cumulative hydrological impacts in a small agricultural catchment: a modeling exploration

Agriculture has always had to face up climate variability, especially rainfall variability, as water stress can damage crops. In many regions of the world, infrastructures to store runoff and stream water such as small reservoirs are seen as a solution to secure food production. The presence of multiple reservoirs in one catchment leads to cumulative impacts which are not necessarily the sum of the individual impacts. In the literature, their impacts are generally studied through modeling. However, the large size of the studied catchments and the aggregated representation of reservoirs in models do not allow to precisely study their cumulative impacts (Habets et al.,2018, https://doi.org/10.1016/j.scitotenv.2018.06.188).

In this work, the effect of small reservoir spatial distribution on their hydrological impacts in a small catchment is investigated by a modeling approach using the distributed agro-hydrological model MHYDAS-small-reservoir (Lebon et al., 2022, https://doi.org/10.1016/j.envsoft.2022.105409). This model features physically-based modeling of surface hydrological processes coupled with a soil-crop model, a reservoir model, a groundwater model, and a decision model for agricultural practices. Space discretization is done following parcel shapes and topography. The specificity of the model is thus the spatially explicit representation of reservoirs and associated processes such as irrigation. We constructed eightteen situations with contrasted spatial distribution of reservoirs along the stream network, namely i) upstream, ii) balanced, and iii) downstream, and with varying values of reservoir densities and cumulated reservoir volume.

The Gélon catchment (20km², France), for which MHYDAS-small-reservoir had been previously tested and validated, was used as basis for the numerical experiment. We performed the simulations on 20 years at a hourly time step, with multiple repetitions for each situation. We considered a reference situation without any reservoir, and with the spatial crop distribution of the year 2015. For each situation, reservoirs were randomly positioned along the stream network, with different probability distributions for the upstream, balanced, and downstream modalities. Nearby crops were modified compared to reference and connected to the reservoirs to reach a total irrigated area of 1 km² in all tested situations. The impact of reservoirs is thus due to the infrastructure itself and the associated nearby modifications of cultivated species and practices. Impacts are quantified relatively to the reference situation, and based on stream discharges and crop yields at different time horizons.

The first analysis of the results revealed that the mean interannual outlet discharge decreased in all the simulations, with high interannual and seasonal variability. Higher reservoir number, higher total stored volume, and downstream distributions generally led to higher hydrological impacts, with interactive effects of these factors. The main driver for these impacts was found to be the water withdrawals in reservoirs, which depends on irrigation needs and water availability. The spatial distribution of reservoirs thus appears as an important factor to consider in models to evaluate their impacts.