Showing papers by "Aaron Boone published in 2023"

Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain

Abstract: Abstract. The prediction of water resource evolution is considered to be a major challenge for the coming century, particularly in the context of climate change and increasing demographic pressure. Water resources are directly linked to the continental water cycle, and the main processes modulating changes can be represented by global hydrological models. However, anthropogenic impacts on water resources, and in particular the effects of dams-reservoirs on river flows, are still poorly known and generally neglected in coupled land surface–river routing models. This paper presents a parameterized reservoir model, DROP (Dam-Reservoir OPeration), based on Hanasaki's scheme to compute monthly releases given inflows, water demands and the management purpose. With its significantly anthropized river basins, Spain has been chosen as a study case for which simulated outflows and water storage variations are evaluated against in situ observations over the period 1979–2014. Using a default configuration of the reservoir model, results reveal its positive contribution in representing the seasonal cycle of discharge and storage variation, specifically for large-storage capacity irrigation reservoirs. Based on a bounded version of the Nash–Sutcliffe efficiency (NSE) index, called C2M, the overall outflow representation is improved by 43 % in the median. For irrigation reservoirs, the improvement rate reaches 80 %. A comprehensive sensitivity analysis of DROP model parameters was conducted based on the performance of C2M on outflows and volumes using the Sobol method. The results show that the most influential parameter is the threshold coefficient describing the demand-controlled release level. The analysis also reveals the parameters that need to be focused on in order to improve river flow or reservoir water storage modeling by highlighting the difference in the individual effects of the parameters and their interactions depending on whether one focuses on outflows or volume mean seasonal patterns. The results of this generic reservoir scheme show promise for modeling present and future reservoir impacts on the continental hydrology within global land surface–river routing models.

Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe

Abstract: The difficulty of calculating the daily water budget of irrigated fields is often due to the uncertainty surrounding irrigation amounts and timing. The automated detection of irrigation events has the potential to greatly simplify this process, and the combination of high-resolution SAR (Sentinel-1) and optical satellite observations (Sentinel-2) makes the detection of irrigation events feasible through the use of a surface soil moisture (SSM) product. The motivation behind this study is to utilize a large irrigation dataset (collected during the ESA Irrigation + project over five sites in three countries over three years) to analyze the performance of an established algorithm and to test potential improvements. The study’s main findings are (1) the scores decrease with SSM observation frequency; (2) scores decrease as irrigation frequency increases, which was supported by better scores in France (more sprinkler irrigation) than in Germany (more localized irrigation); (3) replacing the original SSM model with the force-restore model resulted in an improvement of about 6% in the F-score and narrowed the error on cumulative seasonal irrigation; (4) the Sentinel-1 configuration (incidence angle, trajectory) did not show a significant impact on the retrieval of irrigation, which supposes that the SSM is not affected by these changes. Other aspects did not allow a definitive conclusion on the irrigation retrieval algorithm: (1) the lower scores obtained with small NDVI compared to large NDVI were counter-intuitive but may have been due to the larger number of irrigation events during high vegetation periods; (2) merging different runs and interpolating all SSM data for one run produced comparable F-scores, but the estimated cumulative sum of irrigation was around −20% lower compared to the reference dataset in the best cases.

Modelling snowpack dynamics and surface energy budget in boreal and subarctic peatlands and forests

Abstract: The snowpack has a major influence on the land surface energy budget. Accurate simulation of the snowpack energy budget is challenging due to e.g. vegetation and topography that complicate the radiation budget, and limitations in theoretical understanding of turbulent transfer in the stable boundary layer. Studies that evaluate snow, hydrology and land surface models (LSMs) against detailed observations of all surface energy components at high latitudes are scarce. In this study, we compared different configurations of SURFEX LSM model against surface energy flux, snow depth and soil temperature observations 5 from four eddy covariance stations in Finland. The sites cover two different climate and snow conditions, representing the southern and northern subarctic zones, and the contrasting forest and peatland ecosystems typical for the boreal landscape. We tested the sensitivity of surface energy fluxes to different process parameterizations implemented in the Crocus snowpack model. In addition, we examined common alternative approaches to conceptualize soil and vegetation, and assess their performance in simulating surface energy fluxes, snow conditions and soil thermal regime. Our results show that using a stability 10 correction function that increases the turbulent exchange under stable atmospheric conditions is imperative to simulate sensible and latent heat fluxes over snow. For accurate simulations of surface heat fluxes and snow/soil conditions in forests, an explicit vegetation representation is necessary. Moreover, we found the peat soil temperature profile simulations to be greatly improved with realistic soil texture (soil organic carbon) parameterization. Although we focused on models within the SURFEX LSM platform, the results have broader implications for choosing suitable turbulent flux parameterization and model 15 structures depending on the potential use cases. 1 https://doi.org/10.5194/egusphere-2023-338 Preprint. Discussion started: 8 March 2023 c © Author(s) 2023. CC BY 4.0 License.