Continental-scale River Basins Research Articles

CABra: a novel large-sample dataset for Brazilian catchments

Abstract. In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) of data and less than 10 % of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9 mm d−1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continental-scale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/ (last access: 7 June 2021).

Towards observation-based gridded runoff estimates for Europe

Abstract. Terrestrial water variables are the key to understanding ecosystem processes, feed back on weather and climate, and are a prerequisite for human activities. To provide context for local investigations and to better understand phenomena that only emerge at large spatial scales, reliable information on continental-scale freshwater dynamics is necessary. To date streamflow is among the best-observed variables of terrestrial water systems. However, observation networks have a limited station density and often incomplete temporal coverage, limiting investigations to locations and times with observations. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid with monthly resolution. The methodology is based on statistical upscaling of observed streamflow from small catchments in Europe and exploits readily available gridded atmospheric forcing data combined with the capability of machine learning techniques. The resulting runoff estimates are validated against (1) runoff from small catchments that were not used for model training, (2) river discharge from nine continental-scale river basins and (3) independent estimates of long-term mean evapotranspiration at the pan-European scale. In addition it is shown that the produced gridded runoff compares on average better to observations than a multi-model ensemble of comprehensive land surface models (LSMs), making it an ideal candidate for model evaluation and model development. In particular, the presented machine learning approach may help determining which factors are most relevant for an efficient modelling of runoff at regional scales. Finally, the resulting data product is used to derive a comprehensive runoff climatology for Europe and its potential for drought monitoring is illustrated.

Evaluation of nine large‐scale hydrological models with respect to the seasonal runoff climatology in Europe

Large‐scale hydrological models, simulating the terrestrial water cycle on continental and global scales, are fundamental for many studies in earth system sciences. However, due to imperfect knowledge of real world systems, the models cannot be expected to capture all aspects of large‐scale hydrology equally well. To gain insights in the strengths and shortcomings of nine large‐scale hydrological models, we assessed their ability to capture the mean annual runoff cycle. Unlike most other studies that rely on discharge observations from continental scale river basins, our study is based on observed runoff from a large number of small, near‐natural catchments in Europe. We evaluated the models' ability to capture the average magnitude, the amplitude, as well as the timing of the mean annual runoff cycle. Our study revealed large uncertainties when modeling runoff from these small catchments. We identified large differences in model performance, however, the ensemble mean (mean of all model simulations) yielded rather robust predictions. Model performance varied systematically with climatic conditions and was best in regions with little influence of snow. In cold regions, many models exhibited low correlations between observed and simulated mean annual cycles, which can be associated with shortcomings in simulating the timing of snow accumulation and melt. Local (grid cell) scale differences between observed and simulated runoff can be large and local biases often exceeded 100%. These local uncertainties are contrasted by a relatively good regional average performance, ultimately reflecting the purpose of the models, i.e., to capture regional hydroclimatology.

Estimating evapotranspiration using an observation based terrestrial water budget

ABSTRACTEvapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500 m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground‐based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation‐based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. We demonstrate that while uncertainty in the water budget‐based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget‐based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite‐based ET retrieval optimization. Copyright © 2011 John Wiley & Sons, Ltd.

Parameterization of Blowing-Snow Sublimation in a Macroscale Hydrology Model

Abstract An algorithm that parameterizes the topographically induced subgrid variability in wind speed, snow transport, and blowing-snow sublimation was designed for use within macroscale hydrology models and other large-scale land surface schemes (LSSs). The algorithm is intended to provide consistent estimates of the relative influence of sublimation from blowing snow for continental-scale river basins, while balancing the land surface water and energy budgets. In addition to the standard LSS inputs, the model requires specification of the standard deviation of terrain slope, the mean fetch, and the lag-1 autocorrelation of terrain gradients. Sublimation fluxes are solved for each vegetation class, for each model grid cell. Model results are compared to observed snow water equivalent (SWE) and simulated estimates of sublimation from blowing snow for two small tundra watersheds: Imnavait Creek, Alaska, and Trail Valley Creek, Northwest Territories, Canada, produced by two different small-scale distribute...

Streamflow simulations for continental-scale river basins in a global atmospheric general circulation model

Streamflow simulations for 23 major river basins from the third-generation general circulation model (GCM) of the Canadian Centre for Climate Modelling and Analysis are assessed. Precipitation and runoff data are used from the AMIP II simulation in which the GCM is integrated for a 17-yr period with specific sea surface temperatures and sea-ice concentrations. Compared to the observations, the components of the global hydrological cycle and, the globally averaged precipitation and runoff over land, are well simulated. There remain, however, discrepancies in the simulation of regional precipitation and consequently runoff amounts, which lead to differences in basin-wide averaged quantities. Mean annual model precipitation is within 20% of the observed estimates for 13 out of 23 river basins considered. Model mean annual runoff is within 20% of the observed estimates for only 4 out of these 13 river basins. Analysis of basin-wide averaged monthly precipitation and streamflow data, and the errors associated with the mean, and amplitude and phase of the annual cycles, indicate that model streamflow simulations improve with improvement in GCM precipitation.

Development of a synthetic runoff routing model and its application

In continental and global scale modelling of land surface processes, stream flow, lateral movement of channel water within a channel network is an important component. It is an indispensable component in a fully coupled atmosphere-ocean-land general circulation models (GCMs). The aim of this study is to develop a synthetic runoff routing model for continental-scale river basins. Considering the resolution of typical GCMs, the model resolution is set to 1.0°. This model is designed to accept runoff generated in grid cells within a river basin, and route them to assigned points through a channel network. In this routing model, three routing schemes, Miller's scheme, kinematic wave model and multi-step multi-reachMuskingum-Cunge scheme are implemented. By applying this routing model to theChangjiang and Mississippi river basin, intercomparison of these three routing schemes is carried out.

HYDROLOGICAL MODELING OF CONTINENTAL-SCALE BASINS

▪ Abstract Recent increased interest in the role of the land surface in weather and climate, including impacts due to climate change, has resulted in land surface hydrologic models that incorporate processes which describe the exchange of water and energy at the Earth's surface. The development of a grid-based hydrological model with a full soil-vegetation-atmospheric-transfer (SVAT) land surface parameterization is summarized. The model is suitable both for simulating continental-scale river basins at high temporal and spatial resolutions and as the land surface parameterization in atmospheric general circulation models (AGCMs). Results for the Missouri River basin show the model can successfully simulate hydrological fluxes (e.g. streamflows and evaporation) for large catchments.