The Silala is a small river, originating in the Andean Altiplano, which flows from Bolivia into Chile. Prior to a legal dispute between Chile and Bolivia over the status and use of the waters of the ...Silala, few hydrological studies had been performed in the basin. Further insights were required to better understand the surface‐water and groundwater discharges from Bolivia to Chile, and the effects of historical channelization of the Bolivian wetlands on these flows. A semi‐distributed hydrological model was therefore developed to estimate the discharges from the basin and provide recharge inputs to a groundwater model used to investigate the effects of channelization. Long‐term temperature and precipitation data were available for 1969–1992, while more detailed data were available for 2018–2019. 1969–1992 was selected as a suitable length of record for long‐term groundwater recharge estimation, and the recent data were reserved for model validation, reported in a companion paper. Prior model parameter ranges were identified based on field observations and scientific literature, and sampling of both input and parameter uncertainty allowed determination of representative, lower and upper groundwater recharge scenarios. Results show strong inter‐annual and seasonal variability, the largest groundwater recharge being observed during the Austral summer. A representative groundwater recharge rate of 39.5 mm/year was obtained for the basin to the international border, with feasible lower and upper bounds of 34.9 and 50.2 mm/year, respectively. This lies within the range of 21–51 mm/year estimated by Bolivia for 1969–2017, albeit higher than their best estimate (24 mm/year).
This article is categorized under:
Science of Water > Hydrological Processes
Spatial distribution of representative long‐term annual recharge for the Silala River basin.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Measured rainfall is strongly biased by the fractality of the measuring networks.•Rain gauge networks’ distributions lead to partial information on the rainfall fields.•Semi-distributed models ...statistically reduce rainfall fields into virtual rain gauges.•The size of the sub-catchments should be comparable to the rainfall data resolution.•A rain gauges’ conditioning may be rather counterproductive for some rainfall events.
Precipitation risk and water management is a key challenge for densely populated urban areas. Applications derived from high spatio-temporal resolution observation of precipitations are to make our cities more weather-ready. Finer resolution data available from dual polarised X-band radar measurements enhance engineering tools as used for urban planning policies as well as protection (mitigation/adaptation) strategies to tackle climate-change related weather events. For decades engineering tools have been developed to work conveniently either with very local rain gauge networks, or with mainly C-band radars that have gradually been set up for space-time remote sensing of precipitation. Most of the time, the C-band radars continue to be calibrated by the existing rain gauge networks. Inhomogeneous distributions of these networks lead to only a partial information on the rainfall fields. Here we show that the statistics of measured rainfall is strongly biased by the fractality of the measuring networks and that this fractality needs to be properly taken into account to retrieve the original properties of the rainfall fields, in spite of the radar data calibration. In this work, we use the semi-distributed hydrological modelling over the Bièvre catchment to generate a virtual rain gauges’ network. And, firstly, performing a fractal analysis of this network distribution, we demonstrate that the semi-distributed hydrological models statistically reduce the distributed (weather radar) rainfall fields into rainfall measured by a much scarcer network of virtual rain gauges. Then, with the help of the Intersection Theorem and multifractal theory, we statistically compare the virtual rain gauges’ data with the rainfall data measured by the dual-polarimetric X-band radar operated at Ecole des Ponts with a spatial resolution of 250 m, providing pre-factors that indicate the need of a proper re-normalisation of rain gauge rainfall data when comparing (or calibrating) with radar data and the possible counter productivity of this conditioning.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Surveys allow to calculate water abstractions when there is no available information.•A water stress indicator is able to evaluate water scarcity and groundwater sustainability.•Alternatives to ...reduce water stress indicators allow food and energy security.
The groundwater footprint (GF) is an innovative concept that is used to evaluate groundwater sustainability, and it can be defined as the area required to sustain groundwater use and groundwater-dependent ecosystem services in a region. In this study, we evaluated water scarcity on a sub-regional scale using a water stress indicator defined as the ratio of groundwater footprint to aquifer area GF/A that indicates the sustainability of the aquifers. The higher the stress indicator is, the less sustainable the aquifer is. This study was conducted in the northern part of Colombia; it involves 19 municipalities located in the Sucre department and six main aquifers. Through the use of 5000 interviews, the study calculates water abstractions in the study area, such as cattle, commerce, industry, homes, agro-industry and agriculture; however, only domestic demand associated with groundwater fed aqueducts and groundwater wells was considered because it represents almost 80% of the total abstractions. In addition, the study considered climate change and population growth and how they may affect the GF. The analysis shows that the water stress indicator for the Morroa aquifer has the highest groundwater stress among the six aquifers subject to investigation. GF is considerably higher than many of the world aquifers. Using the same indicator, we compared different mitigation alternatives to increase the sustainability of the Morroa aquifer. Results show that a combination of artificial recharge measures with an alternative source able to supply at least 50% of the domestic consumption appears to be the best choice to make the aquifer more sustainable. GF is a simplified yet robust way to support decision-makers and stakeholders so as they can evaluate water management policies and strategies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Typical basin in humid areas in the Huaihe River
Accurate flood forecasting is essential for making timely decisions regarding flood control and disaster reduction. The theory of watershed runoff ...generation and convergence serves as a crucial foundation for flood forecasting, while the calculation of runoff is necessary to simulate flood discharge. Identifying watershed runoff generation mechanisms has been a challenging task, particularly under complex underlying surface conditions. To improve the accuracy of flood simulation, this study examines the underlying surface information in the watershed, such as particle composition and content, soil bulk density, geological slope, land use, and other spatial attributes, aiming to analyze the mechanisms of runoff generation. In the study of sub-watersheds, various combinations of runoff generation mechanisms are identified to determine the patterns of runoff. Subsequently, a semi-distributed hydrological model is developed, which incorporates both saturation-excess and infiltration-excess runoff, utilizing the information obtained from the underlying surface. The model is validated using rainfall-runoff data from 14 events at the Xiagushan watershed.
The analysis of the fundamental physical conditions of the underlying surface of the watershed revealed that 69.70% of the area is prone to saturation-excess runoff, with an additional 30.30% of the area being susceptible to infiltration-excess runoff. The model considers the spatial distribution of runoff patterns by incorporating complex underlying surface information and demonstrates high accuracy in simulating flood events (NSE= 0.87, Epeak = 12.08%, Wpeak = 13.16%, Tpeak = 0.14 h, R2 = 0.90). The model is straightforward, practical, and exhibits promising potential in terms of timeliness and applicability, thus lending itself well to further application in other watersheds, contributing to the scientific foundation of flood warning and forecasting efforts.
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•Proposed a runoff mechanism discrimination framework.•Developed a semi-distributed spatial hydrological model for flash flood forecast.•The model has parameter adaptive capability and performs well in flash flood forecasting.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Due to the complicated terrain conditions in montane catchments, runoff formation is fast and complicated, making accurate simulation and forecasting a significant hydrological challenge. In this ...study, the spatiotemporal variable source mixed runoff generation module (SVSMRG) was integrated with the long short-term memory (LSTM) method, to develop a semi-distributed model (SVSMRG)-based surface flow and baseflow segmentation (SVSMRG-SBS). Herein, the baseflow was treated as a black box and forecasted using LSTM, while the surface flow was simulated using the SVSMRG module based on hydrological response units (HRUs) constructed using eco-geomorphological units. In the case study, four typical montane catchments with different climatic conditions and high vegetation coverage, located in the topographically varying mountains of the eastern Tibetan Plateau, were selected for runoff and flood process simulations using the proposed SVSMRG-SBS model. The results showed that this model had good performance in hourly runoff and flood process simulations for montane catchments. Regarding runoff simulations, the Nash–Sutcliffe efficiency coefficient (NSE) and correlation coefficient (R2) reached 0.8241 and 0.9097, respectively. Meanwhile, for the flood simulations, the NSE ranged from 0.5923 to 0.7467, and R2 ranged from 0.6669 to 0.8092. For the 1-, 3-, and 5-h baseflow forecasting with the LSTM method, it was found that model performances declined when simulating the runoff processes, wherein the NSE and R2 between the measured and modeled runoff decreased from 0.8216 to 0.8087 and from 0.9095 to 0.8871, respectively. Similar results were found in the flood simulations, the NSE and R2 values declined from 0.7414–0.5885 to 0.7429–0.5716 and from 0.8042–0.6547 to 0.7936–0.6067, respectively. This means that this new model achieved perfect performance in montane catchment runoff and flood simulation and forecasting with 1-, 3-, 5-h steps. Therefore, as it considers vegetation regulation, the SVSMRG-SBS model is expected to improve runoff and flood simulation accuracy in montane high-vegetation-covered catchments.
•EnKF assimilation of streamflow observation in sonw watersheds was evaluated.•We analyze the impact of ensemble size in the EnKF.•EnKF shows an improvement in performance and reliability against ...open-loop scenario.•The updating of snow and soil states together improves the EnKF results.•EnKF forecasts are more reliable than open-loop evenwith a small number of members.
This paper evaluates Ensemble Kalman filter (EnKF) sequential data assimilation on a semi-distributed hydrological model implementation on two snow-dominated watersheds, focussing strictly on snow accumulation and melt periods while assimilating streamflow for the updating of various state variables combinations. Three scenarios are explored in depth: (1) updating the three state variables that were previously identified pertinent for snow-free hydrological processes: soil moisture in the intermediate layer, soil moisture in the deep layer, and the overland routing reservoir, (2) updating the snow water equivalent, and (3) updating all of the above state variables. Inputs (precipitation and temperature) and output (streamflow) perturbation factors are first identified for each scenario, based on their performance and reliability for simulation with assimilation. The three EnKF implementations are next compared to one another and to an open-loop run, in an ensemble forecasting context. The third scenario outperforms the others in most situations and provides the largest gain in reliability. The ensemble size may also be reduced, from 1000 to 50 members, without much loss in performance or reliability.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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.
•EnKF assimilation of streamflow observation in sonw watersheds was evaluated.•We analyze the impact of ensemble size in the EnKF.•EnKF shows an improvement in performance and reliability against ...open-loop scenario.•The updating of snow and soil states together improves the EnKF results.•EnKF forecasts are more reliable than open-loop evenwith a small number of members.
This paper evaluates Ensemble Kalman filter (EnKF) sequential data assimilation on a semi-distributed hydrological model implementation on two snow-dominated watersheds, focussing strictly on snow accumulation and melt periods while assimilating streamflow for the updating of various state variables combinations. Three scenarios are explored in depth: (1) updating the three state variables that were previously identified pertinent for snow-free hydrological processes: soil moisture in the intermediate layer, soil moisture in the deep layer, and the overland routing reservoir, (2) updating the snow water equivalent, and (3) updating all of the above state variables. Inputs (precipitation and temperature) and output (streamflow) perturbation factors are first identified for each scenario, based on their performance and reliability for simulation with assimilation. The three EnKF implementations are next compared to one another and to an open-loop run, in an ensemble forecasting context. The third scenario outperforms the others in most situations and provides the largest gain in reliability. The ensemble size may also be reduced, from 1000 to 50 members, without much loss in performance or reliability.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
High-mountain basins provide a source of valuable water resources. This paper presents hydrological models for the evaluation of water resources in the high-mountain Zêzere river basin in
Serra da ...Estrela
, Central Portugal. Models are solved with VISUAL BALAN v2.0, a code which performs daily water balances in the root zone, the unsaturated zone and the aquifer and requires a small number of parameters. A lumped hydrological model fails to fit measured stream flows. Its limitations are overcome by considering the dependence of the temperature and precipitation data with elevation and the spatial variability in hydrogeomorphological variables with nine sub-basins of uniform parameters. Model parameters are calibrated by fitting stream flow measurements in the Zêzere river. Computed stream flows are highly sensitive to soil thickness, whereas computed groundwater recharge is most sensitive to the interflow and percolation recession coefficients. Interflow is the main component of total runoff, ranging from 41 to 55% of annual precipitation. High interflows are favored by the steep relief of the basin, by the presence of a high permeability soil overlying the fractured low permeability granitic bedrock and by the extensive subhorizontal fracturing at shallow depths. Mean annual groundwater recharge ranges from 11 to 15% of annual precipitation. It has a significant uncertainty due to uncertainties in soil parameters. This methodology proves to be useful to handle the research difficulties regarding a complex mountain basin in a context of data scarcity.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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