Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution.

The HydroATLAS database provides a standardized compendium of descriptive hydro-environmental information for all watersheds and rivers of the world at high spatial resolution. Version 1.0 of HydroATLAS offers data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. HydroATLAS derives the hydro-environmental characteristics by aggregating and reformatting original data from well-established global digital maps, and by accumulating them along the drainage network from headwaters to ocean outlets. The attributes are linked to hierarchically nested sub-basins at multiple scales, as well as to individual river reaches, both extracted from the global HydroSHEDS database at 15 arc-second (~500 m) resolution. The sub-basin and river reach information is offered in two companion datasets: BasinATLAS and RiverATLAS. The standardized format of HydroATLAS ensures easy applicability while the inherent topological information supports basic network functionality such as identifying up- and downstream connections. HydroATLAS is fully compatible with other products of the overarching HydroSHEDS project enabling versatile hydro-ecological assessments for a broad user community.

Estimating the eco-toxicological risk of estrogens in China's rivers using a high-resolution contaminant fate model.

The contamination of freshwater systems arises in many river basins due to industrialization and population growth, posing risks to ecosystems and human health. Despite these concerns, the fate and potential impact of many emerging pollutants are currently unknown, especially when the compounds are released into surface waters from populations distributed across large spatial scales. In order to address this shortcoming, a spatially-explicit contaminant fate model was developed as an extension of the global, vector-based river routing model HydroROUT. HydroROUT operates at very high spatial resolution (∼500 m), simulates river and stream chemical transport with in-stream removal, and contains links to a set of lakes and reservoirs, which act as a partial sink during the transport. The chemical fate model was applied to China and includes a consumption and release module based on county-level population demographics, considers point-source contributions from 2547 wastewater treatment plants, and accumulates contributions of rural and urban populations not connected to sewage treatment plants. As a case study, the sources and fates of the estrogens estrone (E1), 17ß-estradiol (E2), estriol (E3), as well as the synthetic estrogenic steroid hormone 17α-ethinylestradiol (EE2) were modelled in Chinese surface water bodies. Preliminary validation of the results showed predictions to be within the ranges of concentrations reported in literature, with exception of EE2. The total estrogenic mass in the entire river and lake system amounted to 370 tonnes of estrogens, with about 1.3 tonnes per year discharged to the ocean, neighboring countries or to inland sinks. Under a selected baseline scenario, eco-toxicological risk-i.e., contaminant concentrations in excess of the predicted no effect concentration (PNEC)-is found in 23.6% of all analyzed rivers of China with an average flow > 0.1 m3/s. Out of these, about 4% of rivers showed a high level of risk of 10 times or more above PNEC. Medium-to-large rivers are disproportionally affected; for example, 23.6%, 37.3%, 29.0% and 21.6% of river length are at risk in rivers of 1-10, 10-100, 100-1,000, and 1,000-10,000 m3/s of discharge, respectively, whereas no risk was predicted in the largest rivers (i.e., >10,000 m3/s) of China. Wastewater treatment plants process 22.5% of the total hormone load and thus play an important role in water quality control by reducing the risk in substantial portions of the river network, which would otherwise show elevated risk. Releases from untreated population dominate by far the overall contribution to risk.

Risk assessment of down-the-drain chemicals at large spatial scales: Model development and application to contaminants originating from urban areas in the Saint Lawrence River Basin.

Chemicals released into freshwater systems threaten ecological functioning and may put aquatic life and the health of humans at risk. We developed a new contaminant fate model (CFM) that follows simple, well-established methodologies and is unique in its cross-border, seamless hydrological and geospatial framework, including lake routing, a critical component in northern environments. We validated the model using the pharmaceutical Carbamazepine and predicted eco-toxicological risk for 15 pharmaceuticals in the Saint-Lawrence River Basin, Canada. The results indicated negligible to low environmental risk for the majority of tested chemicals, while two pharmaceuticals showed elevated risk in up to 13% of rivers affected by municipal effluents. As an integrated model, our CFM is designed for application at very large scales with the primary goal of detecting high risk zones. In regulatory frameworks, it can help screen existing or new chemicals entering the market regarding their potential impact on human and environmental health. Due to its high geospatial resolution, our CFM can also facilitate the prioritization of actions, such as identifying regions where reducing contamination sources or upgrading treatment plants is most pertinent to achieve targeted pollutant removal or to protect drinking water resources.

Estimating the volume and age of water stored in global lakes using a geo-statistical approach.

Lakes are key components of biogeochemical and ecological processes, thus knowledge about their distribution, volume and residence time is crucial in understanding their properties and interactions within the Earth system. However, global information is scarce and inconsistent across spatial scales and regions. Here we develop a geo-statistical model to estimate the volume of global lakes with a surface area of at least 10 ha based on the surrounding terrain information. Our spatially resolved database shows 1.42 million individual polygons of natural lakes with a total surface area of 2.67 × 106 km2 (1.8% of global land area), a total shoreline length of 7.2 × 106 km (about four times longer than the world's ocean coastline) and a total volume of 181.9 × 103 km3 (0.8% of total global non-frozen terrestrial water stocks). We also compute mean and median hydraulic residence times for all lakes to be 1,834 days and 456 days, respectively.