Impact of distributed meteorological forcing on snow dynamic and induced water fluxes over a mid-elevation alpine micro-scale catchment

From the micro to mesoscale, water and energy budgets of mountainous catchments are largely driven by topographic features such as terrain orientation, slope, steepness, elevation together with associated meteorological forcings such as precipitation, solar radiation and wind. This impact the snow deposition, melting and transport, which further impact the overall water cycle. However, this microscale variability is not well represented in Earth System Models due to coarse resolutions, and impacts of such resolution assumptions on simulated water and energy budget lack quantification. This study aims at exploring these effects on a 15.28 ha small mid-elevation (2000–2200 m) alpine catchment at Col du Lautaret (France). This grass-dominated catchment remains covered with snow for 5 to 6 months per year. The surface-subsurface coupled hyper-resolution (10 m) distributed hydrological model ParFLOW-CLM is used to simulate the impacts of meteorological variability at spatio-temporal micro-scale on the water cycle. These include 3D simulations with spatially distributed forcing of precipitation, solar radiation and wind compared to 3D simulations with non-distributed forcing simulation. Our precipitation distribution method encapsulates the spatial snow distribution along with snow transport. The model simulates the snow cover dynamics and spatial variability through the CLM energy balance module and under the different combinations of distributed forcing. The resulting subsurface and surface water transfers are solved by the ParFLOW module. Distributed forcing induce a snowpack with a more spatially heterogeneous thickness, which becomes patchy during the melt season and shows a good agreement with the remote sensing images. This asynchronous melting results in a longer melting period and smoother hydrological response than the non-distributed forcing, which does not generate any patchiness. Amongst the tested distributed meteorological forcing that impacts the hydrology, precipitation distribution, including snow transportation, is the most important. Solar insolation distribution has an important impact in reducing evapotranspiration depending on the slope orientation. For the studied catchment mainly facing east, it adds small differential melting effect. Wind distribution in the energy budget calculation has a more complicated impact on our catchment as it participate to accelerate the melting when meteorological conditions are favourable but does not generate patchiness at the end in our test case.

Hybrid Gravimetry to Map Water Storage Dynamics in a Mountain Catchment

In mountain areas, both the ecosystem and the local population highly depend on water availability. However, water storage dynamics in mountains is challenging to assess because it is highly variable both in time and space. This calls for innovative observation methods that can tackle such measurement challenge. Among them, gravimetry is particularly well-suited as it is directly sensitive–in the sense it does not require any petrophysical relationship–to temporal changes in water content occurring at surface or underground at an intermediate spatial scale (i.e., in a radius of 100 m). To provide constrains on water storage changes in a small headwater catchment (Strengbach catchment, France), we implemented a hybrid gravity approach combining in-situ precise continuous gravity monitoring using a superconducting gravimeter, with relative time-lapse gravity made with a portable Scintrex CG5 gravimeter over a network of 16 stations. This paper presents the resulting spatio-temporal changes in gravity and discusses them in terms of spatial heterogeneities of water storage. We interpret the spatio-temporal changes in gravity by means of: (i) a topography model which assumes spatially homogeneous water storage changes within the catchment, (ii) the topographic wetness index, and (iii) for the first time to our knowledge in a mountain context, by means of a physically based distributed hydrological model. This study therefore demonstrates the ability of hybrid gravimetry to assess the water storage dynamics in a mountain hydrosystem and shows that it provides observations not presumed by the applied physically based distributed hydrological model.

High resolution satellite products improve hydrological modeling in northern Italy

Satellite Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing spatial and temporal resolution, as well as the seamless availability over ungauged regions, make them appealing for hydrological modeling. This work shows recent advances in the use of high-resolution satellite-based Earth observation data in hydrological modelling. In a set of experiments, the distributed hydrological model Continuum is set up for the Po River Basin (Italy) and forced, in turn, by satellite precipitation and evaporation, while satellite-derived soil moisture and snow depths are ingested into the model structure through a data-assimilation scheme. Further, satellite-based estimates of precipitation, evaporation and river discharge are used for hydrological model calibration, and results are compared with those based on ground observations. Despite the high density of conventional ground measurements and the strong human influence in the focus region, all satellite products show strong potential for operational hydrological applications, with skillful estimates of river discharge throughout the model domain. Satellite-based evaporation and snow depths marginally improve (by 2 % and 4 %) the mean Kling-Gupta efficiency (KGE) at 27 river gauges, compared to a baseline simulation (KGEmean = 0.51) forced by high-quality conventional data. Precipitation has the largest impact on the model output, though the satellite dataset on average shows poorer skills compared to conventional data. Interestingly, a model calibration heavily relying on satellite data, as opposed to conventional data, provides a skillful reconstruction of river discharges, paving the way to fully satellite-driven hydrological applications.

Hydrometeorological analysis of the 12 and 13 September 2019 widespread flash flooding in eastern Spain

On 12 and 13 September 2019, a long-lasting heavy precipitation episode (HPE) affected the València, Murcia and Almería regions in eastern Spain. Observed rainfall amounts were close to 500 mm in 48 h, being the highest cumulative precipitation registered in some rain-gauges for the last century. Subsequent widespread flash flooding caused seven fatalities and estimated economical losses above 425 million EUR. High-resolution precipitation estimates from weather radar observations and flood response from stream-gauges are used in combination with a fully-distributed hydrological model to examine the main hydrometeorological processes within the HyMeX program. This HPE was characterized by successive, well-organized convective structures that impacted a spatial extent of 7500 km2, with rainfall amounts equal or larger than 200 mm. The main factors driving the flood response were quasi-stationarity of heavy precipitation, very dry initial soil moisture conditions and large storage capacities. Most of the examined catchments exhibited a dampened and delayed hydrological response to cumulative precipitation: Until runoff thresholds were exceeded, infiltration-excess runoff generation did not start. This threshold-based hydrological behaviour may impact the shape of flood peak distributions, hindering strict flood frequency statistical analysis due to the generally limited lengths of data records in arid and semi-arid catchments. As an alternative, simple scaling theory between flood magnitude and total rainfall amount is explored.

Integration of Forest Growth Component in the FEST-WB Distributed Hydrological Model: The Bonis Catchment Case Study

In this paper, the FEST-FOREST model is presented. A FOREST module is written in the FORTRAN-90 programming language, and was included in the FEST-WB distributed hydrological model delivering the FEST-FOREST model. FEST-FOREST is a process-based dynamic model allowing the simulation at daily basis of gross primary production (GPP) and net primary production (NPP) together with the carbon allocation of a homogeneous population of trees (same age, same species). The model was implemented based on different equations from literature, commonly used in Eco-hydrological models. This model was developed within the framework of the INNOMED project co-funded under the ERA-NET WaterWorks2015 Call of the European Commission. The aim behind the implementation of the model was to simulate in a simplified mode the forest growth under different climate change and management scenarios, together with the impact on the water balance at the catchment. On a first application of the model, the results are considered very promising when compared to field measured data.

Flood Hazard Mapping with Distributed Hydrological Simulations and Remote-Sensed Slackwater Sediments in Ungauged Basins

We present a basin-scale method to assimilate hydrological data from remote-sensed flood evidence and map civil infrastructures with risk of flooding. As in many rural areas with a semi-arid climate, the studied catchments do not contain stream gauge, and precipitation data does not capture the spatial variability of extreme hydrological events. Remote-sensed flood evidence as slackwater sediments were available at the whole basin, allowing the paleohydrological reconstruction at many sites across the catchment. The agreement between the predicted and observed inundation area was excellent, with an error lower than 15% on average. In addition, the simulated elevations overlapped the observed values in the flooded areas, showing the accuracy of the method. The peak discharges that provoked floods recorded the spatial variability of the precipitation. The variation coefficients of the rainfall intensity were 30% and 40% in the two studied basins with a mean precipitation rate of 3.1 and 4.6 mm/h, respectively. The assumption of spatially uniform precipitation leads to a mean error of 20% in evaluating the local water discharges. Satellite-based rainfall underpredicted the accumulated precipitation by 30–85.5%. Elaborating an inventory of the civil infrastructures at risk was straightforward by comparing the water surface elevation and transport network. The reconstructed maps of rainfall rate were used in the distributed hydrological model IBERPLUS to this end. Recent flood events that overtopped the infrastructures at risk verified our predictions. The proposed research methods can be easily applied and tested in basins with similar physical characteristics around the Mediterranean region.

Rainfall-Runoff Simulation for Water Availability Estimation in Small Island Using Distributed Hydrological Model wflow

Hydrological data in Indonesia, especially in the small islands, is minimal, including spatial distribution and temporal completeness. It will affect the accuracy of water availability estimation for water resources management interest. One of the solutions that can be undertaken is applying rainfall-runoff modeling to obtain the discharge value at a specific location. This study aims to determine surface water availability in each sub-catchment of the small island by implementing the hydrological model. The wflow model is applying to perform the model. This model uses input data including Digital Elevation Model (DEM), landuse, soil, Leaf Area Index (LAI), rainfall, evapotranspiration, and observation of river discharge for the calibration process. As a result, this island consists of 30 catchments with some potential catchments, namely Cao, Sakita, and Tatamo, that have a 90% dependable flow of 4213.3 L/s, 3803.6 L/s 8117 L/s, respectively. The result of water availability in Morotai Island is highly expected to be the reference for water resources management, especially for tourism and urban development.

Comparisons of distributed and lumped rainfall-runoff model for soil moisture estimation

Soil moisture is an important parameter in landslides because of increased pore pressure and decreased shear strength. This research aims to derive soil moisture indicators from two hydrological models: the physically-based distributed hydrological model and the lumped model. Rainfall-Runoff-Inundation (RRI) Model is used to simulate the hydrological response of catchments to the rainfall-induced landslide in a distributed manner. Tank Model as a lumped hydrological model is also used in this study to simulate the dynamic of soil moisture. The study area is the upper Brantas River Basin, prone to landslides due to heavy rainfall and steep slope. Calibration of the model is conducted by tuning the model according to the river discharge data. The simulation indicates that acceptable performance is confirmed. Tank Model can provide the dynamic of the soil moisture. However, by using this approach, the spatial variation of the soil moisture cannot be presented. Regarding the quantitative amount of soil water content, RRI Model could make a reasonable simulation though the temporal variation is not adequately reproduced. Validation of this method with satellite soil moisture as well as ground measurement is also presented. The challenges of using these approaches to develop landslide hazard assessment are discussed.

Incorporating Advanced Scatterometer Surface and Root Zone Soil Moisture Products into the Calibration of a Conceptual Semi-Distributed Hydrological Model

The role of soil moisture is widely accepted as a significant factor in the mass and energy balance of catchments as a controller in surface and subsurface runoff generation. The paper examines the potential of a new dataset based on advanced scatterometer satellite remote sensing of soil moisture (ASCAT) for multiple objective calibrations of a dual-layer, conceptual, semi-distributed hydrological model. The surface and root zone soil moisture indexes based on ASCAT data were implemented into calibration of the hydrological model. Improvements not only in the instrument specifications, i.e., better temporal and spatial sampling, but also in the higher radiometric accuracy and retrieval algorithm, were applied. The analysis was performed in 209 catchments situated in different physiographic and climate zones of Austria for the period 2007–2018. We validated the model for two validation periods. The results show that multiple objective calibrations have a substantial positive effect on constraining the model parameters. The combined use of soil moisture and discharges in the calibration improved the soil moisture simulation in more than 73% of the catchments, except for the catchments with higher forest cover percentages. Improvements also occurred in the runoff model efficiency, in more than 27% of the catchments, mostly in the watersheds with a lower mean elevation and a higher proportion of farming land use, as well as in the Alpine catchments where the runoff is not significantly influenced by snowmelt and glacier runoff.

Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and downscaled to drive a distributed hydrological model. Then, the spatial variations of runoff changes under the future climate conditions in the Amur River Basin were quantified. The results suggest that runoffs will tend to increase in the future period (2021–2070) compared with the baseline period (1961–2010), particularly in August and September. Differences were also found among different GCMs and scenarios. The ensemble mean of the GCMs suggests that the basin-averaged annual precipitation will increase by 14.6% and 15.2% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The increase in the annual runoff under the SSP2-4.5 scenario (22.5%) is projected to be larger than that under the SSP5-8.5 scenario (19.2%) at the lower reach of the main channel. Future climate changes also tend to enhance the flood peak and flood volume. The findings of this study bring new understandings of the hydrological response to future climate changes and are helpful for water resource management in Eurasia.