Evaluation of the ERA5 reanalysis as a reference dataset for fine-scale hydrological modelling over alpine basins 

2021 ◽  
Author(s):  
Susen Shrestha ◽  
Mattia Zaramella ◽  
Mattia Callegari ◽  
Felix Greifeneder ◽  
Marco Borga
Keyword(s):  
Spatial Scales ◽  
Hydrological Modelling ◽  
Distributed Hydrological Model ◽  
Reference Dataset ◽  
Time Step ◽  
Hydrological Simulation ◽  
Reanalysis Product ◽  
Precipitation Product ◽  
Flood Simulations ◽  
Moisture Conditions

<p>The European Center for Medium-Range Weather Forecasts (ECMWF) has recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system, and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process. This is obtained by using a semi-distributed hydrological model over basins ranging from 40km<sup>2</sup> to 6900 km<sup>2</sup> over the Upper Adige river basin in the Eastern Italian Alps. This study shows that ERA5-based precipitation product is affected by a significant bias which translates to biased runoff at all spatial scales considered in the study. We observed that ERA5 precipitation product generally overestimate low-intensity rainfall and underestimate high rainfall intensity in the region. We analysed how this affects simulation of annual max floods over the study area. The results show that flood simulations are in general surprisingly good, as they result from the combination of two cascading errors: i) overestimation of the soil moisture conditions at the start of the event and ii) the underestimation of the event forcing rainfall. Differences between ERA5 and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.</p>

scholarly journals Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modeling over North-America

2019 ◽  
Author(s):  
Mostafa Tarek ◽  
François P. Brissette ◽  
Richard Arsenault
Keyword(s):  
North America ◽  
Hydrological Modeling ◽  
Hydrological Modelling ◽  
Reference Dataset ◽  
Time Step ◽  
Hydrological Simulation ◽  
Reanalysis Product ◽  
Weather Forecasts ◽  
Temperature And Precipitation ◽  
The Us

Abstract. The European Center for Medium-Range Weather Forecasts (ECMWF) has recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process, using two lumped hydrological models over 3138 North-American catchments. This study shows that ERA5-based hydrological modeling performance is equivalent to using observations over most of North-America, with the exception of the Eastern half of the US, where observations lead to consistently better performance. ERA5 temperature and precipitation biases are consistently reduced compared to ERA-Interim and systematically more accurate for hydrological modelling. Differences between ERA5, ERA-Interim and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.

scholarly journals Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America

2020 ◽  
Vol 24 (5) ◽  
pp. 2527-2544 ◽  
Author(s):  
Mostafa Tarek ◽  
François P. Brissette ◽  
Richard Arsenault
Keyword(s):  
North America ◽  
Hydrological Modelling ◽  
Reference Dataset ◽  
Time Step ◽  
Hydrological Simulation ◽  
Reanalysis Product ◽  
Weather Forecasts ◽  
Temperature And Precipitation ◽  
The Us ◽  
Modelling Process

Abstract. The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released its most advanced reanalysis product, the ERA5 dataset. It was designed and generated with methods giving it multiple advantages over the previous release, the ERA-Interim reanalysis product. Notably, it has a finer spatial resolution, is archived at the hourly time step, uses a more advanced assimilation system and includes more sources of data. This paper aims to evaluate the ERA5 reanalysis as a potential reference dataset for hydrological modelling by considering the ERA5 precipitation and temperatures as proxies for observations in the hydrological modelling process, using two lumped hydrological models over 3138 North American catchments. This study shows that ERA5-based hydrological modelling performance is equivalent to using observations over most of North America, with the exception of the eastern half of the US, where observations lead to consistently better performance. ERA5 temperature and precipitation biases are consistently reduced compared to ERA-Interim and systematically more accurate for hydrological modelling. Differences between ERA5, ERA-Interim and observation datasets are mostly linked to precipitation, as temperature only marginally influences the hydrological simulation outcomes.

scholarly journals An integration of gauge, satellite and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

2020 ◽  
Author(s):  
Yuanwei Wang ◽  
Lei Wang ◽  
Xiuping Li ◽  
Jing Zhou ◽  
Zhidan Hu
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Spatial Scales ◽  
Water Security ◽  
The Tibetan Plateau ◽  
Brahmaputra River ◽  
Hydrological Simulation ◽  
Precipitation Product ◽  
Basin Scale ◽  
Long Term Trends

Abstract. As the largest river basin of the Tibetan Plateau, the Upper Brahmaputra River Basin (also called “Yarlung Zangbo” in Chinese) has profound impacts on the water security of local and downstream inhabitants. Precipitation in the basin is mainly controlled by the Indian Summer Monsoon and Westerly, and is the key to understand the water resources available in the basin; however, due to sparse observational data constrained by a harsh environment and complex topography, there remains a lack of reliable information on basin-wide precipitation (there are only nine national meteorological stations with continuous observations). To improve the accuracy of basin-wide precipitation data, we integrate various gauge, satellite and reanalysis precipitation datasets, including GLDAS, ITP-Forcing, MERRA2, TRMM and CMA datasets, to develop a new precipitation product for the 1981–2016 period over the Upper Brahmaputra River Basin, at 3-hour and 5-km resolution. The new product has been rigorously validated at different temporal scales (e.g. extreme events, daily to monthly variability, and long-term trends) and spatial scales (point- and basin-scale) with gauge precipitation observations, showing much improved accuracies compared to previous products. An improved hydrological simulation has been achieved (low relative bias: −5.94 %; highest NSE: 0.643) with the new precipitation inputs, showing reliability and potential for multi-disciplinary studies. This new precipitation product is openly accessible at https://doi.org/10.5281/zenodo.3711155 (Wang et al., 2020) and, additionally at the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn, login required).

scholarly journals Subgrid spatial variability of soil hydraulic functions for hydrological modelling

2016 ◽  
Vol 20 (6) ◽  
pp. 2557-2571 ◽  
Author(s):  
Phillip Kreye ◽  
Günter Meon
Keyword(s):  
Spatial Scales ◽  
Field Studies ◽  
Soil Heterogeneity ◽  
Universal Function ◽  
Hydrological Modelling ◽  
Distributed Hydrological Model ◽  
Strong Correlations ◽  
Wide Range ◽  
Spatially Distributed ◽  
Soil Hydraulic

Abstract. State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

scholarly journals Subgrid spatial variability of soil hydraulic functions for hydrological modelling

2016 ◽  
Author(s):  
Phillip Kreye ◽  
Günter Meon
Keyword(s):  
Spatial Scales ◽  
Field Studies ◽  
Soil Heterogeneity ◽  
Universal Function ◽  
Hydrological Modelling ◽  
Distributed Hydrological Model ◽  
Practical Applications ◽  
Wide Range ◽  
Spatially Distributed ◽  
Soil Hydraulic

Abstract. State of the art hydrological applications require a process-based spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterizations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between ROSETTA generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterize sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system and were used successfully in many practical applications and projects.

scholarly journals An integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

2020 ◽  
Vol 12 (3) ◽  
pp. 1789-1803 ◽  
Author(s):  
Yuanwei Wang ◽  
Lei Wang ◽  
Xiuping Li ◽  
Jing Zhou ◽  
Zhidan Hu
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Spatial Scales ◽  
Water Security ◽  
The Tibetan Plateau ◽  
Brahmaputra River ◽  
Hydrological Simulation ◽  
Precipitation Product ◽  
Basin Scale ◽  
Long Term Trends

Abstract. As the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin (also called “Yarlung Zangbo” in Chinese) has profound impacts on the water security of local and downstream inhabitants. Precipitation in the basin is mainly controlled by the Indian summer monsoon and westerly and is the key to understanding the water resources available in the basin; however, due to sparse observational data constrained by a harsh environment and complex topography, there remains a lack of reliable information on basin-wide precipitation (there are only nine national meteorological stations with continuous observations). To improve the accuracy of basin-wide precipitation data, we integrate various gauge, satellite, and reanalysis precipitation datasets, including GLDAS, ITP-Forcing, MERRA2, TRMM, and CMA datasets, to develop a new precipitation product for the 1981–2016 period over the upper Brahmaputra River basin, at 3 h and 5 km resolution. The new product has been rigorously validated at different temporal scales (e.g., extreme events, daily to monthly variability, and long-term trends) and spatial scales (point and basin scale) with gauge precipitation observations, showing much improved accuracies compared to previous products. An improved hydrological simulation has been achieved (low relative bias: −5.94 %; highest Nash–Sutcliffe coefficient of efficiency (NSE): 0.643) with the new precipitation inputs, showing reliability and potential for multidisciplinary studies. This new precipitation product is openly accessible at https://doi.org/10.5281/zenodo.3711155 (Wang et al., 2020) and additionally at the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn, last access: 10 July 2020, login required).

Impact of climate change on water availability in Tropical Andean catchments: a case study in the Vilcanota catchment, Peru

2021 ◽  
Author(s):  
Selina Meier ◽  
Randy Munoz ◽  
Christian Huggel
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Water Demand ◽  
Climate Models ◽  
Local Population ◽  
Time Step ◽  
Glacier Surface ◽  
Hydrological Simulation ◽  
Sustainable Water Management ◽  
Monthly Runoff

<p>Water scarcity is increasingly becoming a problem in many regions of the world. On the one hand, this can be attributed to changes in precipitation conditions due to climate change. On the other hand, this is also due to population growth and changes in consumer behaviour. In this study, an analysis is carried out for the highly glaciated Vilcanota River catchment (9808 km<sup>2</sup> – 1.2% glacier area) in the Cusco region (Peru). Possible climatic and socioeconomic scenarios up to 2050 were developed including the interests from different water sectors, i.e. agriculture, domestic and energy.</p><p>The analysis consists of the hydrological simulation at a monthly time step from September 2043 to August 2050 using a simple glacio-hydrological model. For historic conditions (1990 to 2006) a combination of gridded data (PISCO precipitation) and weather stations was used. Future scenario simulations were based on three different climate models for both RCP 2.6 and 8.5. Different glacier outlines were used to simulate changes in glacier surface through the time for both historic (from satellite data) and future (from existing literature) scenarios. Furthermore, future water demand simulations were based on the SSP1 and SSP3 scenarios.</p><p>Results from all scenarios suggest an average monthly runoff of about 130 m<sup>3</sup>/s for the Vilcanota catchment between 2043 and 2050. This represents a change of about +5% compared to the historical monthly runoff of about 123 m<sup>3</sup>/s. The reason for the increase in runoff is related to the precipitation data from the selected climate models. However, an average monthly deficit of up to 50 m<sup>3</sup>/s was estimated between April and November with a peak in September. The seasonal deficit is related to the seasonal change in precipitation, while the water demand seems to have a less important influence.</p><p>Due to the great uncertainty of the modelling and changes in the socioeconomic situation, the data should be continuously updated. In order to construct a locally sustainable water management system, the modelling needs to be further downscaled to the different subcatchments in the Vilcanota catchment. To address the projected water deficit, a new dam could partially compensate for the decreasing storage capacity of the melting glaciers. However, the construction of the dam could meet resistance from the local population if they cannot be promised and communicated multiple uses of the new dam. Sustainable water management requires the cooperation of all stakeholders and all stakeholders should be able to benefit from it so that they will support future projects.</p>

Alternative climate data sources for distributed hydrological modelling on a daily time step

2010 ◽  
Vol 25 (10) ◽  
pp. 1542-1557 ◽  
Author(s):  
Ashraf El-Sadek ◽  
Max Bleiweiss ◽  
Manoj Shukla ◽  
Steve Guldan ◽  
Alexander Fernald
Keyword(s):  
Hydrological Modelling ◽  
Data Sources ◽  
Climate Data ◽  
Time Step ◽  
Daily Time Step ◽  
Distributed Hydrological Modelling ◽  
Daily Time

scholarly journals Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps

2020 ◽  
Vol 24 (5) ◽  
pp. 2711-2729 ◽  
Author(s):  
Joseph L. Gutenson ◽  
Ahmad A. Tavakoly ◽  
Mark D. Wahl ◽  
Michael L. Follum
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Army Corps ◽  
Time Step ◽  
Large Spatial Scale ◽  
Reservoir Routing ◽  
Routing Methods ◽  
Improved Model

Abstract. Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Döll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Döll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Döll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

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