Large-scale Hydrological Models Research Articles

Phosphorus retention in lakes: A critical reassessment of hypotheses and static models

Four pairs of competing hypotheses for phosphorus (P) retention in lakes are assessed and 39 static models in three types, namely mechanistic, semi-mechanistic, and strictly-empirical models, are evaluated. Mechanistic models are only based on the physical representation of lakes and basic hypotheses; hence, we used their pairwise comparison to assess the superiority of the hypotheses. The results showed that (i) simulating lakes as mixed-flow reactor is superior to plug-flow reactor hypothesis; (ii) modeling P loss as a second-order reaction outperforms the first-order reaction; (iii) P loss is better explained as a removal process throughout the lake volume than as a settling process across the sediments; and (iv) considering a fraction of P loading is associated with fast settling particles enhances lake total phosphorus (TP) predictions. The preeminent mechanistic model combines, for the first time, the second-order reaction hypothesis with the hypothesis that a specific proportion of P loading settles rapidly at the lake entrance. The comparison of the three model types showed that semi-mechanistic models outperform both mechanistic and strictly-empirical models since they take the form of a mechanistic model based on the physical representation of the lakes and utilize statistically acquired equations for unknown parameters. The best-fit model is a semi-mechanistic model that adopts the mixed-flow reactor hypothesis with a second-order volumetric reaction rate that is calculated as a non-linear function of inflow TP concentration, lake average depth, and water retention time. This model predicts 77.8% of the variability of log10-transformed lake TP concentration, which is 4.2% higher than the best mechanistic model and 0.8% higher than the best strictly-empirical model. The findings of this study not only shed light on the understanding of P retention in lakes but also can be useful for assessment of data-limited lakes and large-scale hydrological models to simulate the P cycle.

Water storage and release policies for all large reservoirs of conterminous United States

Large-scale hydrological and water resource models (LHMs) require water storage and release schemes to represent flow regulation by reservoirs. Owing to a lack of observed reservoir operations, state-of-the-art LHMs deploy a generic reservoir scheme that may fail to represent local operating behaviors. Here we introduce a new dataset of bespoke water storage and release policies for 1,930 reservoirs of conterminous United States. The Inferred Storage Targets and Release Functions (ISTARF-CONUS) dataset relies on a new inventory of observed daily reservoir operations (ResOpsUS) to generate reservoir operating rules for 595 data-rich reservoirs. These functions are developed in a standardized form that allows for extrapolation of operating schemes to 1,335 data-scarce reservoirs—leading to the first inventory of empirically derived reservoir operating policies for all large CONUS reservoirs documented in the Global Reservoir and Dams (GRanD) database. Evaluation of the new scheme in daily simulations forced with observed inflow demonstrates substantial and robust improvement for both release and storage relative to the popular Hanasaki method. Performance of the extrapolation approach for data-scarce reservoirs is evaluated with leave-one-out validation and is shown to also offer modest gains on average over Hanasaki. ISTARF-CONUS may be readily adopted in any LHM featuring large reservoirs of the conterminous United States.

Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review

New tools and concepts in the form of mathematical models, remote sensing and Geographic Information System (GIS), communication and telemetering have been developed for the complex hydrologic systems that permit a different analysis of processes and allow watershed to be considered as an integrated planning and management unit. Hydrological characteristics can be generated through spatial analysis, and ready for input into a distributed hydrologic models to define adequately the hydrological response of a watershed that can be related back to the specific environmental, climatic, and geomorphic conditions. In the present paper, some recent development in hydrologic modeling will be reviewed with recognition of the role of horizontal routing scheme in large scale hydrologic modeling. Among others, these developments indicated the needs of alternative horizontal routing models at grid scale level that can be coupled to land surface parameterization schemes that presently still employed the linear routing model. Non-linear routing scheme will be presented and discussed in this paper as possible extension.

From local measures to regional impacts: Modelling changes in nutrient loads to the Baltic Sea

Study RegionOur study region is the Baltic Sea Drainage Basin (BSDB), which covers an area of 1.8 Mio km2 distributed over 14 countries in northern Europe. Study FocusWe use a large-scale hydrological and nutrient transport model (E-HYPE) to model basin-wide impacts of measure scenarios on the Baltic Sea, where eutrophication is a critical issue for the marine ecosystem. We constructed measure scenarios based on stakeholder acceptance, established in workshops in different regions around the Baltic. These measures include local stream reach to catchment scale measures aiming to reduce nutrient transport into the stream network (buffer strips, stormwater ponds) and measures aiming to reduce regional nutrient source releases (fertiliser leaching rates, rural household emissions). New Hydrological Insights for the RegionNutrient load reductions are often needed to reduce eutrophication and improve overall surface water quality in fresh-water and enclosed bays and seas, where dilution is limited and load emissions have long residence times. To reduce riverine nutrient loads, remediation measures are necessary, e.g. establishment of buffer strips or improved wastewater treatment. Such measures are, however, typically not designed to target nutrient load reductions at sea outlets, but rather focus on local improvements. Here, we show that measures, notwithstanding other meliorating ecosystem benefits, must include reductions in load emissions across large basin areas to impact integrated net loads into coastal sea basins, because reduction measures that only target nutrient delivery to the stream network typically cannot be implemented in a significant enough proportion of the total drainage area of large coastal river basins. Our impact scenarios show BSDB-wide nutrient reductions of up to 9 % for nitrogen and phosphorus compared to a reference scenario, if load emissions are reduced in the scenario assumptions.

Continental-scale streamflow modeling of basins with reservoirs: Towards a coherent deep-learning-based strategy

A large fraction of major waterways have dams influencing streamflow, which must be accounted for in large-scale hydrologic modeling. However, daily streamflow prediction for basins with dams is challenging for various modeling approaches, especially at large scales. Here we examined which types of dammed basins could be well represented by long short-term memory (LSTM) models using readily-available information, and delineated the remaining challenges. We analyzed data from 3557 basins (83% dammed) over the contiguous United States and noted strong impacts of reservoir purposes, degree of regulation (dor), and diversion on streamflow modeling. While a model trained on a widely-used reference-basin dataset performed poorly for non-reference basins, the model trained on the whole dataset presented a median Nash-Sutcliffe efficiency coefficient (NSE) of 0.74. The zero-dor, small-dor (with storage of approximately a month of average streamflow or less), and large-dor basins were found to have distinct behaviors, so migrating models between categories yielded catastrophic results, which means we must not treat small-dor basins as reference ones. However, training with pooled data from different sets yielded optimal median NSEs of 0.72, 0.79, and 0.64 for these respective groups, noticeably stronger than existing models. These results support a coherent modeling strategy where smaller dams (storing about a month of average streamflow or less) are modeled implicitly as part of basin rainfall-runoff processes; then, large-dor reservoirs of certain types can be represented explicitly. However, dammed basins must be present in the training dataset. Future work should examine separate modeling of large reservoirs for fire protection and irrigation, hydroelectric power generation, and flood control.

Hydrological projections in the upper reaches of the Yangtze River Basin from 2020 to 2050

Understanding the impact of climate change on runoff is essential for effective water resource management and planning. In this study, the regional climate model (RCM) RegCM4.5 was used to dynamically downscale near-future climate projections from two global climate models to a 50-km horizontal resolution over the upper reaches of the Yangtze River (UYRB). Based on the bias-corrected climate projection results, the impacts of climate change on mid-twenty-first century precipitation and temperature in the UYRB were assessed. Then, through the coupling of a large-scale hydrological model with RegCM4.5, the impacts of climate change on river flows at the outlets of the UYRB were assessed. According to the projections, the eastern UYRB will tend to be warm-dry in the near-future relative to the reference period, whereas the western UYRB will tend to be warm-humid. Precipitation will decreases at a rate of 19.05–19.25 mm/10 a, and the multiyear average annual precipitation will vary between − 0.5 and 0.5 mm/day. Temperature is projected to increases significantly at a rate of 0.38–0.52 °C/10 a, and the projected multiyear average air temperature increase is approximately 1.3–1.5 ℃. The contribution of snowmelt runoff to the annual runoff in the UYBR is only approximately 4%, whereas that to the spring runoff is approximately 9.2%. Affected by climate warming, the annual average snowmelt runoff in the basin will be reduced by 36–39%, whereas the total annual runoff will be reduced by 4.1–5%, and the extreme runoff will be slightly reduced. Areas of projected decreased runoff depth are mainly concentrated in the southeast region of the basin. The decrease in precipitation is driving this decrease in the southeast, whereas the decreased runoff depth in the northwest is mainly driven by the increase in evaporation.

HydroGFD3.0 (Hydrological Global Forcing Data): a 25 km global precipitation and temperature data set updated in near-real time

Abstract. HydroGFD3 (Hydrological Global Forcing Data) is a data set of bias-adjusted reanalysis data for daily precipitation and minimum, mean, and maximum temperature. It is mainly intended for large-scale hydrological modelling but is also suitable for other impact modelling. The data set has an almost global land area coverage, excluding the Antarctic continent and small islands, at a horizontal resolution of 0.25∘, i.e. about 25 km. It is available for the complete ERA5 reanalysis time period, currently 1979 until 5 d ago. This period will be extended back to 1950 once the back catalogue of ERA5 is available. The historical period is adjusted using global gridded observational data sets, and to acquire real-time data, a collection of several reference data sets is used. Consistency in time is attempted by relying on a background climatology and only making use of anomalies from the different data sets. Precipitation is adjusted for mean bias as well as the number of wet days in a month. The latter is relying on a calibrated statistical method with input only of the monthly precipitation anomaly such that no additional input data about the number of wet days are necessary. The daily mean temperature is adjusted toward the monthly mean of the observations and applied to 1 h time steps of the ERA5 reanalysis. Daily mean, minimum, and maximum temperature are then calculated. The performance of the HydroGFD3 data set is on par with other similar products, although there are significant differences in different parts of the globe, especially where observations are uncertain. Further, HydroGFD3 tends to have higher precipitation extremes, partly due to its higher spatial resolution. In this paper, we present the methodology, evaluation results, and how to access the data set at https://doi.org/10.5281/zenodo.3871707 (Berg et al., 2020).

Selecting the most suitable pedotransfer functions for estimating saturated hydraulic conductivity according to the available soil inputs

Direct measurements of saturated hydraulic conductivity (Ksat) are costly and time-consuming. Alternatively, pedotransfer functions (PTFs) have been developed to estimate Ksat in terms of readily available soil properties. The goal of this study is to evaluate forty-five PTFs of Ksat. The functions were divided into four groups according to their input requirements: EP-Ksat group (F1.1-F1.9) require the effective porosity as inputs; SSC-Ksat group (F2.1-F2.12) require (sand, silt, clay contents); SSCBD-Ksat group (F3.1-F3.8) require (sand, silt, clay contents), bulk density; and SSCBDOM-Ksat group (F4.1-F4.16) require (sand, silt, clay contents), bulk density, and organic matter content. The results showed that the best PTFs were F1.9 and F1.5 in EP-Ksat group. For the SSC-Ksat group, the PTFs F2.1, F2.11. For the SSCBD-Ksat group, the PTFs F3.5, F3.6. For SSCBDOM-Ksat group, the PTFs F4.13 and F4.8. Results of this study are helpful for predicting Ksat inputs required for large scale hydrologic models with reliability.

Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling

Abstract. Major multi-reservoir cascades represent a primary mechanism for dealing with hydrologic variability and extremes within institutionally complex river basins worldwide. These coordinated management processes fundamentally reshape water balance dynamics. Yet, multi-reservoir coordination processes have been largely ignored in the increasingly sophisticated representations of reservoir operations within large-scale hydrological models. The aim of this paper is twofold, namely (i) to provide evidence that the common modeling practice of parameterizing each reservoir in a cascade independently from the others is a significant approximation and (ii) to demonstrate potential unintended consequences of this independence approximation when simulating the dynamics of hydrological extremes in complex reservoir cascades. We explore these questions using the Water Balance Model, which features detailed representations of the human infrastructure coupled to the natural processes that shape water balance dynamics. It is applied to the Upper Snake River basin in the western US and its heavily regulated multi-reservoir cascade. We employ a time-varying sensitivity analysis that utilizes the method of Morris factor screening to explicitly track how the dominant release rule parameters evolve both along the cascade and in time according to seasonal high- and low-flow events. This enables us to address aim (i) by demonstrating how the progressive and cumulative dominance of upstream releases significantly dampens the ability of downstream reservoir rules' parameters to influence flow conditions. We address aim (ii) by comparing simulation results with observed reservoir operations during critical low-flow and high-flow events in the basin. Our time-varying parameter sensitivity analysis with the method of Morris clarifies how independent single-reservoir parameterizations and their tacit assumption of independence leads to reservoir release behaviors that generate artificial water shortages and flooding, whereas the observed coordinated cascade operations avoided these outcomes for the same events. To further explore the role of (non-)coordination in the large deviations from the observed operations, we use an offline multi-reservoir water balance model in which adding basic coordination mechanisms drawn from the observed emergency operations is sufficient to correct the deficiencies of the independently parameterized reservoir rules from the hydrological model. These results demonstrate the importance of understanding the state–space context in which reservoir releases occur and where operational coordination plays a crucial role in avoiding or mitigating water-related extremes. Understanding how major infrastructure is coordinated and controlled in major river basins is essential for properly assessing future flood and drought hazards in a changing world.

Large-Scale Hydrological and Sediment Modeling in Nested Domains under Current and Changing Climate

AbstractContinental and global dynamic hydrological models have emerged recently as tools for large-scale analyses. One such tool is a dynamic process-based rainfall-runoff and water quality model ...

Integration of 2D Lateral Groundwater Flow into the Variable Infiltration Capacity (VIC) Model and Effects on Simulated Fluxes for Different Grid Resolutions and Aquifer Diffusivities

Better representations of groundwater processes need to be incorporated into large-scale hydrological models to improve simulations of regional- to global-scale hydrology and climate, as well as understanding of feedbacks between the human and natural systems. We incorporated a 2D groundwater flow model into the variable infiltration capacity (VIC) hydrological model code to address its lack of a lateral groundwater flow component. The water table was coupled with the variably saturated VIC soil column allowing bi-directional exchange of water between the aquifer and the soil. We then investigated how variations in aquifer properties and grid resolution affect modelled evapotranspiration (ET), runoff and groundwater recharge. We simulated nine idealised, homogenous aquifers with different combinations of transmissivity, storage coefficient, and three grid resolutions. The magnitude of cell ET, runoff, and recharge significantly depends on water table depth. In turn, the distribution of water table depths varied significantly as grid resolution increased from 1° to 0.05° for the medium and high transmissivity systems, resulting in changes of model-average fluxes of up to 12.3% of mean rainfall. For the low transmissivity aquifer, increasing the grid resolution has a minimal effect as lateral groundwater flow is low, and the VIC grid cells behave as vertical columns. The inclusion of the 2D groundwater model in VIC will enable the future representation of irrigation from groundwater pumping, and the feedbacks between groundwater use and the hydrological cycle.

A dual-layer MPI continuous large-scale hydrological model including Human Systems

Large-scale hydrological models are demanding both in term of memory allocation and CPU time, particularly when assessment of modeling uncertainty is required. High Performance Computing offers the opportunity to reach resolutions not achievable with standard serial coding. However, the advantages may be offset by poor scalability of the model due to components that have to be executed in series, such as to simulate the presence of hydraulic infrastructures.Driven by this motivation, we developed HYPERstreamHS, a model that adopts a holistic approach to simulate hydrological processes in large river basins with streamflow altered by hydraulic infrastructures. The model adopts a dual-layer parallelization strategy, where the paralleled version of the hydrological kernel is the first-layer, with the second layer taking care of inverse modeling.The results show that the processors should be carefully organized and grouped in order to achieve the best overall performance and suggests that this subdivision is problem specific.

Regional scale hydrodynamic modeling of the river-floodplain-reservoir continuum

River floodplains and reservoirs interact throughout a basin drainage network, defining a coupled human-water system with multiple feedbacks. Recent modeling developments have aimed to improve the representation of such processes at regional to continental scales. However, most large-scale hydrological models adopt simplified lumped reservoir schemes, where an offline routine is run with inflows estimated by the model, with limited consideration of the complementarity between floodplains and reservoirs on altering the hydrological regime at regional scale. This paper presents a novel approach that fully couples river-floodplain-reservoir hydrodynamic and hydrological models, significantly improving the representation of reservoir dynamics and operation in the river-floodplain-reservoir continuum at large scale and across multiple dam cascades. The model is applied to the Paraná River Basin with explicit simulation of 31 large dams and river hydraulic variables at basin scale. Three types of reservoir bathymetry representation are compared, from lumped to distributed methods, combined with three reservoir operation schemes and varying degrees of input data requirement within two parameterization scenarios (global and regional setups). The operation schemes were more relevant than the reservoir bathymetry representation to estimate downstream flows and water levels. While the data-driven operation scheme, based on linear regressions between observed water levels and dam outflows, provided the best estimates of both active storage and discharges, the more generic operation reasonably estimated discharges and peak attenuation, albeit not as accurately for active storage. The global parameterization of reservoir operation resulted in poorer performance compared to the regional-based one, but it satisfactorily modeled discharge and peak attenuation. Regarding the reservoir bathymetry representation, a basin scale comparison of the lumped and distributed schemes indicated the inability of the former to represent backwater effects. This was further corroborated by validating the longitudinal water level profile of Itaipu dam with ICESat satellite altimetry data. Finally, the model was used to show the complementarity between floodplains and reservoirs on attenuating floods at regional scale. Large scale models should move beyond offline coupling strategies, and include regional-based, data-driven reservoir operation schemes together with a distributed representation of reservoir bathymetry into river-floodplain hydraulic schemes. This will largely improve the estimation of river discharges, water levels and flood storage, and thus the model ability to represent the regional scale river-floodplain-reservoir continuum.

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Abstract. This study evaluates the ability of different gridded rainfall datasets to plausibly represent the spatio-temporal patterns of multiple hydrological processes (i.e. streamflow, actual evaporation, soil moisture and terrestrial water storage) for large-scale hydrological modelling in the predominantly semi-arid Volta River basin (VRB) in West Africa. Seventeen precipitation products based essentially on gauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP, PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5, PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared as input for the fully distributed mesoscale Hydrologic Model (mHM). To assess the model sensitivity to meteorological forcing during rainfall partitioning into evaporation and runoff, six different temperature reanalysis datasets are used in combination with the precipitation datasets, which results in evaluating 102 combinations of rainfall–temperature input data. The model is recalibrated for each of the 102 input combinations, and the model responses are evaluated by using in situ streamflow data and satellite remote-sensing datasets from GLEAM evaporation, ESA CCI soil moisture and GRACE terrestrial water storage. A bias-insensitive metric is used to assess the impact of meteorological forcing on the simulation of the spatial patterns of hydrological processes. The results of the process-based evaluation show that the rainfall datasets have contrasting performances across the four climatic zones present in the VRB. The top three best-performing rainfall datasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE and CMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC and PGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC for the spatial patterns of soil moisture; ARC, RFE and GSMaP-std for the temporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for the spatial patterns of actual evaporation. No single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes. A dataset that is best in reproducing the temporal dynamics is not necessarily the best for the spatial patterns. In addition, the results suggest that there is more uncertainty in representing the spatial patterns of hydrological processes than their temporal dynamics. Finally, some region-tailored datasets outperform the global datasets, thereby stressing the necessity and importance of regional evaluation studies for satellite and reanalysis meteorological datasets, which are increasingly becoming an alternative to in situ measurements in data-scarce regions.

The relative contribution of vegetation greening to the hydrological cycle in the Three-North region of China: A modelling analysis

China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the north-eastern, northern, and north-western regions, collectively referred to as the Three-North region (TNR), to combat desertification and control dust storms. Although these programs have alleviated environmental problems in the region to a certain extent, the effects of increasing vegetation greenness on the hydrological cycle remain controversial. In this study, the relative effects of afforestation programs on the hydrologic processes in the TNR were identified based on large-scale hydrological modeling and satellite remote sensing data. The model forcing was featured with long-term vegetation dynamics. The study period ranged from 2000 to 2015, during which the greening of vegetation in the TNR was increased after multiple afforestation programs were carried out around 2000. The results indicated that, despite the spatial heterogeneity, the vegetation leaf area index (LAI) exhibited a significant increase across the TNR. Evapotranspiration (ET) increased over the entire region at the rate of 2.9 mm/year from 2000 to 2015, and its spatial pattern was consistent with changes in the LAI and precipitation. However, this does not imply equal contribution by vegetation growth and precipitation change. The results from the simulation scenarios indicated that precipitation change had a more significant influence on the ET, soil moisture and runoff than vegetation growth at the regional scale. Vegetation greening and precipitation increase in the Loess Plateau indicated their approximately equal impacts on ET and soil moisture. Consequently, the hydrological cycle was sensitive to afforestation practices at small-catchment or sub-regional scales where the magnitude of vegetation greening is relatively high. Therefore, the hydrological effect of vegetation greening at large scale may be overestimated by previous studies. To ensure sustainable water resource management at the TNR scale, special attention should be paid to climate change rather than afforestation efforts under the current level of ecological restoration programs.

Hierarchical sensitivity analysis for a large-scale process-based hydrological model applied to an Amazonian watershed

Abstract. Sensitivity analysis methods have recently received much attention for identifying important uncertainty sources (or uncertain inputs) and improving model calibrations and predictions for hydrological models. However, it is still challenging to apply the quantitative and comprehensive global sensitivity analysis method to complex large-scale process-based hydrological models (PBHMs) because of its variant uncertainty sources and high computational cost. Therefore, a global sensitivity analysis method that is capable of simultaneously analyzing multiple uncertainty sources of PBHMs and providing quantitative sensitivity analysis results is still lacking. In an effort to develop a new tool for overcoming these weaknesses, we improved the hierarchical sensitivity analysis method by defining a new set of sensitivity indices for subdivided parameters. A new binning method and Latin hypercube sampling (LHS) were implemented for estimating these new sensitivity indices. For test and demonstration purposes, this improved global sensitivity analysis method was implemented to quantify three different uncertainty sources (parameters, models, and climate scenarios) of a three-dimensional large-scale process-based hydrologic model (Process-based Adaptive Watershed Simulator, PAWS) with an application case in an ∼ 9000 km2 Amazon catchment. The importance of different uncertainty sources was quantified by sensitivity indices for two hydrologic outputs of interest: evapotranspiration (ET) and groundwater contribution to streamflow (QG). The results show that the parameters, especially the vadose zone parameters, are the most important uncertainty contributors for both outputs. In addition, the influence of climate scenarios on ET predictions is also important. Furthermore, the thickness of the aquifers is important for QG predictions, especially in main stream areas. These sensitivity analysis results provide useful information for modelers, and our method is mathematically rigorous and can be applied to other large-scale hydrological models.

A Modeling Assessment of Large-Scale Hydrologic Alteration in South American Pantanal Due to Upstream Dam Operation

Natural river flow provides the conditions required to sustain freshwater ecosystems, and the greater the departure from the natural regime, the greater the loss of those ecosystems. In South America, new hydropower dams are continuously being constructed and planned in regions within and around the Amazon basin and in the Upper Paraguay river basin, a region notable for the Pantanal, a huge wetland ecosystem that is largely dependent on the flow regime of the Paraguay river and its tributaries. In this context, it is meaningful to examine the hydrological changes caused by the major Manso dam, that is operating since 2001 at the headwaters of one of the major tributaries of the Paraguay river. This was done for the same case study by other authors in previous studies using only gauging stations data. However, those previous assessments were limited due to the confounding effects of climate variability and the necessity of relatively long term observed time series. Here, we applied a modelling approach to evaluate the changes in hydrological regime caused by Manso dam operation. Our modelling approach was based on the combination of the MGB large-scale hydrologic model with the SIRIPLAN large-scale wetland model. The models were applied, using river reaches from 2 to 10 km, in two scenarios during the period from 2003 to 2015. In the first scenario we used naturalized streamflow at the dam site as input to the hydrological model. In the second scenario we used observed reservoir outflow time series as input to the hydrological model. Our results show that Manso dam has a regulation effect that decreases high flows, increases low flows and reduces lateral connectivity. The decrease in high flows is limited to the region upstream of the Pantanal floodplain, while increase in low flows extends into Pantanal. Timing of maximum and minimum flows is less affected, except for the river reach immediately downstream of the dam. Our results improve the assessment of spatial patterns of hydrologic alteration, giving more confidence in the assessment of magnitude and spatial extension of the effects of Manso dam in the Pantanal region.

Fuzzy Postprocessing to Advance the Quality of Continental Seasonal Hydrological Forecasts for River Basin Management

AbstractStreamflow forecasting services driven by seasonal meteorological forecasts from dynamic prediction systems deliver valuable information for decision-making in the water sector. Moving beyond the traditional river basin boundaries, large-scale hydrological models enable a coordinated, efficient, and harmonized anticipation and management of water-related risks (droughts, floods). However, the use of forecasts from such models at the river basin scale remains a challenge, depending on how the model reproduces the hydrological features of each particular river basin. Consequently, postprocessing of forecasts is a crucial step to ensure usefulness at the river basin scale. In this paper we present a methodology to postprocess seasonal streamflow forecasts from large-scale hydrological models and advance their quality for local applications. It consists of fuzzy logic systems that bias-adjust seasonal forecasts from a large-scale hydrological model by comparing its modeled streamflows with local observations. The methodology is demonstrated using forecasts from the pan-European hydrological model E-HYPE at the Jucar River basin (Spain). Fuzzy postprocessed forecasts are compared to postprocessed forecasts derived from a quantile mapping approach as a benchmark. Fuzzy postprocessing was able to provide skillful streamflow forecasts for the Jucar River basin, keeping most of the skill of raw E-HYPE forecasts and also outperforming quantile-mapping-based forecasts. The proposed methodology offers an efficient one-to-one mapping between large-scale modeled streamflows and basin-scale observations preserving its temporal dependence structure and can adapt its input set to increase the skill of postprocessed forecasts.

Discharge Estimation via Assimilation of Multisatellite-Based Discharge Products: Case Study Over the Amazon Basin

River flows are an essential component of the water cycle and are directly accessible for human consumption and activities. River water flux (i.e., river discharge) not only can be measured locally at <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> gauges but also can be estimated at larger scales with the river routing models. However, the number of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> gauges is declining worldwide while emerging river-related products from satellites are becoming more available. Especially, discharge products based on satellite altimetry water elevations are emerging. These altimetry missions provide different spatial and temporal coverages and may not provide the same amount of information. In this study, discharge products from two satellite altimetry missions (ENVISAT and JASON-2) were assimilated into the large-scale hydrologic model Intéractions Sol-Biosphére-Atmosphére-CNRM’s Total Runoff and Integrating Pathways (ISBA-CTRIP) using an ensemble Kalman filter, to correct the simulated discharge. This work investigates whether it is better to assimilate products with a dense spatial coverage but a lower temporal sampling (ENVISAT) or the opposite (JASON-2). Three experiments have been performed: the first two assimilated each product separately, and the last one assimilated the combined product. The open-loop normalized root-mean-square error evaluated against <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> discharge (RMSEn) is 69%. RMSEn is decreased for all experiments. Specifically, it is slightly lower when assimilating ENVISAT-based discharge product (51%) than JASON-2 product (53%) as the ENVISAT-based product spatial coverage is denser. The best results are obtained when both products are assimilated (RMSEn=49%). These results are very encouraging and could be improved when the future Surface Water and Ocean Topography (SWOT) wide swath altimetry mission discharge product will be available.

Large-Scale hydrological modelling of flow and hydropower production, in a Brazilian watershed

Study area: Watershed of the Tocantins-Araguaia River.Focus of the study: Given the large discharge of rivers in Tocantins-Araguaia Watershed (TAW) and consequently a great potential for hydropower generation, we used the SWAT model to simulate the streamflow of the TAW and investigated its energy potential.New approaches to local hydrology: Our goal is to use the flow estimated by SWAT to simulate the energy potential at the Tucuruí hydropower plant in Tocantins-Araguaia River, Pará, Brazil. We identified that in SWAT calibration some parameters are more sensitive to water processes than others, hence allowing the improvement of simulation in the TAW. The validation of the model showed that the simulated results were consistent with the data observed in the dynamic reproduction of flow seasonality. It was possible to generate hydropower potential in the TAW and evaluate its potential when the SWAT streamflow was calibrated and validated. This study may be useful for planning sustainable management and decision-making to create public policies of hydrological basins located in tropical regions.