scholarly journals Value of river discharge data for global-scale hydrological modeling

2007 ◽  
Vol 4 (6) ◽  
pp. 4125-4173 ◽  
Author(s):  
M. Hunger ◽  
P. Döll
Keyword(s):  
Correction Factor ◽  
River Discharge ◽  
Hydrological Modeling ◽  
Model Performance ◽  
Flow Characteristics ◽  
Global Scale ◽  
The Other ◽  
Station Correction ◽  
Discharge Data

Abstract. This paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor.

scholarly journals Value of river discharge data for global-scale hydrological modeling

2008 ◽  
Vol 12 (3) ◽  
pp. 841-861 ◽  
Author(s):  
M. Hunger ◽  
P. Döll
Keyword(s):  
Water Resources ◽  
Correction Factor ◽  
River Discharge ◽  
Hydrological Modeling ◽  
Flow Characteristics ◽  
Global Scale ◽  
Station Correction ◽  
Discharge Data ◽  
Study Results

Abstract. This paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are e.g. required for assessing water resources, flood risk and habitat alteration of aquatic ecosystems. An improved version of the WaterGAP Global Hydrology Model (WGHM) was tuned against measured discharge using either the 724-station dataset (V1) against which former model versions were tuned or an extended dataset (V2) of 1235 stations. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas in order to fit simulated and observed long-term average discharge at tuning stations. In basins where γ does not suffice to tune the model, two correction factors are applied successively: the areal correction factor corrects local runoff in a basin and the station correction factor adjusts discharge directly the gauge. Using station correction is unfavorable, as it makes discharge discontinuous at the gauge and inconsistent with runoff in the upstream basin. The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5% and the area where the model can be tuned by only adjusting γ increases by 8%. However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and in regions where the refined dataset provides a significant subdivision of formerly extended tuning basins (average V2 basin size less than half the V1 basin size). If the additional discharge information were not used for tuning, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 in the formerly untuned basins and 1.3 in the subdivided basins. The benefits tend to be higher in semi-arid and snow-dominated regions where the model is less reliable than in humid areas and refined tuning compensates for uncertainties with regard to climate input data and for specific processes of the water cycle that cannot be represented yet by WGHM. Regarding other flow characteristics like low flow, inter-annual variability and seasonality, the deviation between simulated and observed values also decreases significantly, which, however, is mainly due to the better representation of average discharge but not of variability. (3) The choice of the optimal sub-basin size for tuning depends on the modeling purpose. While basins over 60 000 km2 are performing best, improvements in V2 model performance are strongest in small basins between 9000 and 20 000 km2, which is primarily related to a low level of V1 performance. Increasing the density of tuning stations provides a better spatial representation of discharge, but it also decreases model consistency, as almost half of the basins below 20 000 km2 require station correction.

scholarly journals Toward continental hydrologic–hydrodynamic modeling in South America

2018 ◽  
Vol 22 (9) ◽  
pp. 4815-4842 ◽  
Author(s):  
Vinícius A. Siqueira ◽  
Rodrigo C. D. Paiva ◽  
Ayan S. Fleischmann ◽  
Fernando M. Fan ◽  
Anderson L. Ruhoff ◽  
...  
Keyword(s):  
South America ◽  
Land Surface ◽  
River Discharge ◽  
Hydrological Modeling ◽  
Water Levels ◽  
Scale Model ◽  
Global Models ◽  
Discharge Data ◽  
Continental Scale ◽  
Terrestrial Water

Abstract. Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues about parameterization and limitations in representing lowland river systems can place constraints on these models to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic–hydrodynamic model (MGB; Modelo hidrológico de Grandes Bacias) to the continental domain of South America and assessed its performance using daily river discharge, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharge was compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental  ×  global models) that makes use of spatially distributed, daily discharge data. A satisfactory representation of discharge and water levels was obtained (Nash–Sutcliffe efficiency, NSE > 0.6 in 55 % of the cases) and the continental model was able to capture patterns of seasonality and magnitude of TWS and ET, especially over the largest basins of South America. After the comparison with global models, we found that it is possible to obtain considerable improvement on daily river discharge, even by using current global forcing data, just by combining parameterization and better routing physics based on regional experience. Issues about the potential sources of errors related to both global- and continental-scale modeling are discussed, as well as future directions for improving large-scale model applications in this continent. We hope that our study provides important insights to reduce the gap between global and regional hydrological modeling communities.

scholarly journals The African Database of Hydrometric Indices (ADHI)

2020 ◽  
Author(s):  
Yves Tramblay ◽  
Nathalie Rouché ◽  
Jean-Emmanuel Paturel ◽  
Gil Mahé ◽  
Jean-François Boyer ◽  
...  
Keyword(s):  
Quality Control ◽  
River Discharge ◽  
Scientific Community ◽  
Flow Characteristics ◽  
African Continent ◽  
Mean Flow ◽  
Discharge Data ◽  
Daily Discharge ◽  
The One ◽  
Different Sources

Abstract. The African continent is probably the one with the lowest density of hydrometric stations currently measuring river discharge, despite the fact that the number of operating stations was quite important until the 70s. This new African Database of Hydrometric Indices (ADHI) is compiling data from different sources carefully checked for quality control. It includes about 1500 stations with at least 10 years of daily discharge data over the period 1950–2018. The average record length is 19 years and for over 100 stations complete records are available over 50 years. With this dataset spanning most regions of the African continent, several hydrometric indices have been computed, representing mean flow characteristics and extremes (low flows and floods), and are made accessible to the scientific community. The database will be updated on a regular basis to include more hydrometric stations and longer time series of river discharge. The ADHI database is available for download at: https://doi.org/10.23708/LXGXQ9 (Tramblay and Rouché, 2020).

scholarly journals ADHI: the African Database of Hydrometric Indices (1950–2018)

2021 ◽  
Vol 13 (4) ◽  
pp. 1547-1560
Author(s):  
Yves Tramblay ◽  
Nathalie Rouché ◽  
Jean-Emmanuel Paturel ◽  
Gil Mahé ◽  
Jean-François Boyer ◽  
...  
Keyword(s):  
River Discharge ◽  
Flow Characteristics ◽  
African Continent ◽  
Mean Flow ◽  
Discharge Data ◽  
Climatic Regions ◽  
Wide Range ◽  
Daily Discharge ◽  
The One ◽  
Different Sources

Abstract. The African continent is probably the one with the lowest density of hydrometric stations currently measuring river discharge despite the fact that the number of operating stations was quite important until the 1970s. This new African Database of Hydrometric Indices (ADHI) provides a wide range of hydrometric indices and hydrological signatures computed from different sources of data after a quality control. It includes 1466 stations with at least 10 years of daily discharge data over the period 1950–2018. The average record length is 33 years, and 131 stations have complete records over 50 years. With this new dataset spanning most climatic regions of the African continent, several hydrometric indices have been computed, representing mean flow characteristics and extremes (low flows and floods), and are accessible to the scientific community. The database will be updated on a regular basis to include more hydrometric stations and longer time series of river discharge. The ADHI is available for download at: https://doi.org/10.23708/LXGXQ9 (Tramblay and Rouché, 2020).

Discharge estimation and monitoring extreme events by satellite altimetry

2020 ◽  
Author(s):  
Rossella Belloni ◽  
Stefania Camici ◽  
Angelica Tarpanelli
Keyword(s):  
Time Series ◽  
Water Level ◽  
River Discharge ◽  
Satellite Altimetry ◽  
Global Scale ◽  
Discharge Time ◽  
Discharge Data ◽  
The World ◽  
Daily Discharge ◽  
Rating Curves

<p>In view of recent dramatic floods and drought events, the detection of trends in the frequency and magnitude of long time series of flood data is of scientific interest and practical importance. It is essential in many fields, from climate change impact assessment to water resources management, from flood forecasting to drought monitoring, for the planning of future water resources and flood protection systems. <br>To detect long-term changes in river discharge a dense, in space and time, network of monitoring stations is required. However, ground hydro-meteorological monitoring networks are often missing or inadequate in many parts of the world and the global supply of the available river discharge data is often restricted, preventing to identify trends over large areas.  <br>The most direct method of deriving such information on a global scale involves satellite earth observation. Over the last two decades, the growing availability of satellite sensors, and the results so far obtained in the estimation of river discharge from the monitoring of the water level through satellite radar altimetry has fostered the interest on this subject.  <br>Therefore, in the attempt to overcome the lack of long continuous observed time series, in this study satellite altimetry water level data are used to set-up a consistent, continuous and up-to-date daily discharge dataset for different sites across the world. Satellite-derived water levels provided by publicly available datasets (Podaac, Dahiti, River& Lake, Hydroweb and Theia) are used along with available ground observed river discharges to estimate rating curves. Once validated, the rating curves are used to fill and extrapolate discharge data over the whole period of altimetry water level observations. The advantage of using water level observations provided by the various datasets allowed to obtain discharge time series with improved spatio-temporal coverages and resolutions, enabling to extend the study on a global scale and to efficiently perform the analysis even for small to medium-sized basins.  <br>Long continuous discharge time series so obtained are used to perform a global trend analysis on extreme flood and drought events. Specifically, annual maximum discharge and peak-over threshold values are extracted from the simulated daily discharge time series, as proxy variables of independent flood events. For flood and drought events, a trend analysis is carried out to identify changes in the frequency and magnitude of extreme events through the Mann-Kendall (M-K) test and a linear regression model between time and the flood magnitude.  <br>The analysis has permitted to identify areas of the world prone to floods and drought, so that appropriate actions for disaster risk mitigation and continuous improvement in disaster preparedness, response, and recovery practices can be adopted. </p>

scholarly journals Development and validation of a global dynamical wetlands extent scheme

2012 ◽  
Vol 9 (1) ◽  
pp. 405-440 ◽  
Author(s):  
T. Stacke ◽  
S. Hagemann
Keyword(s):  
River Discharge ◽  
River Flow ◽  
Central Africa ◽  
Global Scale ◽  
Max Planck ◽  
Discharge Data ◽  
Wetland Extent ◽  
Wetland Processes ◽  
Development And Validation ◽  
Good Agreement

Abstract. In this study we present the development of the dynamical wetland extent scheme (DWES) and its validation against present day wetland observations. The DWES is a simple, global scale hydrological scheme that solves the water balance of wetlands and estimates their extent dynamically. The extent depends on the balance of water flows in the wetlands and the slope distribution within the grid cells. In contrast to most models, the DWES is not directly calibrated against wetland extent observations. Instead, wetland affected river discharge data are used to optimize global parameters of the model. The DWES is not a complete hydrological model by itself but implemented into the Max Planck Institute – Hydrology Model (MPI-HM). However, it can be transferred into other models as well. For present climate, the model validation reveals a good agreement between the occurrence of simulated and observed wetlands on the global scale. The best result is achieved for the northern hemisphere where not only the wetland distribution pattern but also their extent is simulated reasonably well by the DWES. However, the wetland fraction in the tropical parts of South America and Central Africa is strongly overestimated. The simulated extent dynamics correlate well with monthly inundation variations obtained from satellite for most locations. Also, the simulated river discharge is affected by wetlands resulting in a delay and mitigation of peak flows. Compared to simulations without wetlands, we find locally increased evaporation and decreased river flow into the oceans due to the implemented wetland processes. In summary, the validation analysis demonstrates the DWES' ability to simulate the global distribution of wetlands and their seasonal variations. Thus, the dynamical wetland extent scheme can provide hydrological boundary conditions for wetland related studies. In future applications, the DWES should be implemented into an earth system model to study feedbacks between wetlands and climate.

scholarly journals Illustrating a new approach to estimating potential reduction in fish species richness due to flow alteration on a global scale

2013 ◽  
Vol 10 (6) ◽  
pp. 7837-7856 ◽  
Author(s):  
S. Yoshikawa ◽  
A. Yanagawa ◽  
A. Khajuria ◽  
P. Sui ◽  
Y. Iwasaki ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Richness ◽  
Fish Species ◽  
Statistical Models ◽  
River Discharge ◽  
Global Scale ◽  
The Other ◽  
Freshwater Ecosystem ◽  
Global Simulation ◽  
Flow Alteration

Abstract. Changes in river discharge due to human activities and climate change would affect the sustainability of freshwater ecosystem. In order to globally assess the future status of freshwater ecosystem under regime shifts in river discharge, global-scale hydrological simulations need to be connected with a model to estimate the soundness of freshwater ecosystem. However, the explicit combination of those two on a global scale is still in its infancy. A couple of statistical models are introduced here to link flow regimes to fish species richness (FSR): one based on a linear relationship between FSR and mean river discharge, and the other based on a relationship between FSR and ecologically relevant flow indices involving other several flow characteristics as well as mean river discharge. The former one has been sometimes used in global simulation studies, but the latter one is newly introduced here in the context of global simulation. These statistical models for estimating FSR were combined with a set of global river discharge simulations to evaluate the potential impact of flow alterations due to climate change on FSR changes. Generally, future reductions in FSR by the latter method are larger and much more scattered rather than by the former method. In arid regions, both models provide reductions in FSR because mean discharge is projected to decrease from past to future, although the magnitude of reduction in FSR is different. On the other hand, large reductions in FSR only by the latter model are detected in heavy-snow regions due to the increases of mean discharge and frequency of low and high flows. Although we need further research to conclude which is more relevant, this study demonstrates that the new model could show a considerably different behavior in assessing the global impact of flow alteration on freshwater ecosystem change.

scholarly journals The Influence of Rainfall and Land Use/Land Cover Changes on River Discharge Variability in the Mountainous Catchment of the Bagmati River

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2444 ◽  
Author(s):  
Dinesh Tuladhar ◽  
Ashraf Dewan ◽  
Michael Kuhn ◽  
Robert J. Corner
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Discharge ◽  
Forest Cover ◽  
Agricultural Land ◽  
Strong Association ◽  
Land Use Land Cover ◽  
Discharge Data ◽  
Bagmati River

Changes in rainfall and land use/land cover (LULC) can influence river discharge from a catchment in many ways. Homogenized river discharge data from three stations and average rainfall records, interpolated from 13 stations, were examined for long-term trends and decadal variations (1970–2017) in the headwater, upper and middle catchments of the Bagmati River. LULC changes over five decades were quantified using multitemporal Landsat images. Mann–Kendall tests on annual time series showed a significant decrease in river discharge (0.61% per year) from the entire Bagmati catchment, although the decrease in rainfall was statistically insignificant. However, declines in river discharge and rainfall were both significant in upper catchment. Decadal departures from long-term means support these trend results. Over tenfold growth in urban area and a decrease in agricultural land were observed in the upper catchment, while forest cover slightly increased in the entire catchment between 1975 and 2015. Correlation analysis showed a strong association between surface runoff, estimated using the curve number method, observed river discharge and rainfall in the upper catchment, while the relationship was weaker in the headwater catchment. These results were also supported by multiple regression analysis, suggesting that human activities together with climate change have contributed to river discharge changes in the Bagmati catchment.

scholarly journals A variable streamflow velocity method for global river routing model: model description and preliminary results

2007 ◽  
Vol 4 (6) ◽  
pp. 4389-4414 ◽  
Author(s):  
T. Ngo-Duc ◽  
T. Oki ◽  
S. Kanae
Keyword(s):  
River Discharge ◽  
River Flow ◽  
Global Scale ◽  
Model Description ◽  
River Channels ◽  
Total Runoff ◽  
Global Soil ◽  
River Mouths ◽  
River Routing

Abstract. This paper presents an attempt of simulating daily fluctuations of river discharge at global scale. Total Runoff Integrating Pathways (TRIP) is a global river routing model which can help to isolate the river basins, inter-basin transport of water through river channels, as well as collect and route runoff to the river mouths for all the major rivers. In the previous version of TRIP (TRIP 1.0), a simple approach of constant river flow velocity is used. In general, that approach is sufficient to model mean long-term discharges. However, to model short-term fluctuations, more sophisticated approach is required. In this study, we implement a variable streamflow velocity method to TRIP (TRIP 2.0) and validate the new approach over the world's 20 major rivers. Two numerical experiments, one with the TRIP 1.0 and another with TRIP 2.0 are performed. Input runoff is taken from the multi-model product provided by the second Global Soil Wetness Project. For the rivers which have clear daily fluctuations of river discharge, TRIP 2.0 shows advantages over TRIP 1.0, suggesting that TRIP 2.0 can be used to model flood events.

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