Recent regional changes in nutrient fluxes of European surface waters.

We have quantified inputs and fate of nutrients in European fresh and marine waters from 1990 to 2018. We have used the conceptual model GREEN to assess the impact of efforts on curbing nutrient pollution in European regions. In the first two decades, i.e. in the 1990s and through the start of the new millennium, nutrient inputs to waters decreased significantly. Nutrient pollution in freshwaters and to the sea largely reduced in all regions, although at different pace. However, around 2008-2010 trends in nutrient inputs changed, marking an increase in the last decade, particularly from agricultural diffuse sources. In some regions, current nutrient inputs to waters are close to those estimated at the beginning of the 1990s. At the end of the study period, nutrient concentrations in freshwaters remain above thresholds congruent with good ecological status of water bodies in most downstream reaches. European policies tackling point sources are close to reach their maximum impact. In the face of this approaching ceiling, sustainable nutrient management on agricultural land becomes pivotal for effective nutrient control in river basins. The regional approach highlighted differences across Europe that may provide tailored opportunities to plan effective strategies for achieving environmental targets.

The number of people exposed to water stress in relation to how much water is reserved for the environment: a global modelling study.

BACKGROUND: Increasing human demand for water and changes in water availability due to climate change threatens water security worldwide. Additionally, exploitation of water resources induces stress on freshwater environments, leading to biodiversity loss and reduced ecosystem services. We aimed to conduct a spatially detailed assessment of global human water stress for low to high environmental flow (EF) protection. METHODS: In this modelling study, we used the LISFLOOD model to generate daily natural flows without anthropogenic water use for 1980-2018. On the basis of these flows, we selected three EF methods (EF with high ecological protection [EFPROT], EF with minimum flow requirements [EFMIN], and variable monthly flow [EFVMF]) to calculate monthly EFs. We assessed monthly consumptive water use for industry, agricultural crops, livestock, municipalities, and energy production for 2010. We then estimated the corresponding number of people under water stress per month on a global and national level using a spatially detailed population database for 2010. FINDINGS: We estimate that 3·2 billion (EFPROT), 2·4 billion (EFVMF), and 2·2 billion (EFMIN) people lived under water stress for at least 1 month per year, corresponding to 46%, 35%, and 32% of the world's population in 2010, respectively. Around 80% of people living under water stress lived in Asia; in particular, India, Pakistan, and northeast China. Compared with EFMIN, imposing EFPROT globally would have put between 710 million (March) to 1 billion (June) additional people under water stress on a monthly basis, whereas this would have been 72 million (August) to 218 million (April) additional people if EFVMF were imposed. INTERPRETATION: Ensuring high ecological protection would put nearly half of the world's population (3·2 billion people) under water stress for at least 1 month per year. Policy makers and water managers have to make an important trade-off when allocating limited water resources between direct human needs and the environment. A better understanding of local ecosystem needs is crucial to alleviating current and future human water stress, while sustaining healthy ecosystems. FUNDING: None.

Modelling nutrient fluxes into the Mediterranean Sea.

STUDY REGION: Mediterranean River Basins. STUDY FOCUS: Human activities and consequent pollution have put the freshwater and marine ecosystems of the Mediterranean region under pressure, with high risk of eutrophication phenomena. In this study, an extended version of the Geospatial Regression Equation for European Nutrient losses model (GREEN), originally developed for estimating nutrient loads from diffuse and point sources in Europe, was extended to include additional nutrient sources using a grid cell discretization. The spatial resolution is 5 arc minute and the model inputs consist of the latest and best available global data. NEW HYDROLOGICAL INSIGHTS FOR THE REGION: The results of this study show that during 2003-2007 (baseline), 1.87 Tg/y of total nitrogen (TN), 1.22 Tg/y of nitrates (N-NO3), 0.11 Tg/y of total phosphorus (TP) and 0.03 Tg/y of orthophosphate (P-PO4) were discharged in the Mediterranean Sea. The source apportionment analysis showed that the main contributor to total nitrogen and nitrate loads is agriculture followed by natural background, while for orthophosphate dominant sources include wastewater and scattered dwellings. Two scenarios were investigated to assess sustainable water and nutrient management options, showing that the reduction of 50% of nitrogen surplus leads to a significant reduction of nitrogen emission in regions characterized by high intensity agriculture, while the upgrading of wastewater treatment plants to tertiary level was more efficient for TP reduction.

Assessing the impact of human interventions on floods and low flows in the Wei River Basin in China using the LISFLOOD model.

Floods are extreme hydroclimatic events that threaten societies and ecosystems. The effects of these events are greatly influenced by the changes that humans have imposed on the environment. The LISFLOOD model is a physically based rainfall-runoff model that simulates the hydrological processes in a catchment. Using globally available land cover, soil, and vegetation as well as meteorological and geographical datasets as input, the LISFLOOD model has the potential to be applied worldwide, even for regions where data are lacking. This study first calibrated and validated the LISFLOOD model in the Wei River Basin in China (432,000 km2) for the years between 2000 and 2010 at 0.05° resolution with a monthly Nash-Sutcliffe model efficiency coefficient of 0.79 at the Huaxian station located at the catchment outlet. The outlets of 17 tributaries draining into the main river were then identified in order to assess the contribution of each tributary to the total runoff occurring as a result of flooding. Four categories of scenarios focusing on human interventions in the basin were created and evaluated: 1) Business as usual, 2) Additional reservoirs constructed in different catchments, 3) Land use as in 1980, and 4) Water diversion plan with a pipeline injection of a fixed daily inflow from an adjacent catchment. The results of the scenarios are presented for three strategically important cities located on the floodplain. In general, the construction of the reservoirs could have an effect on reducing peak flows and decreasing the flood return periods while increasing the low flows. The water diversion plan scenarios increased the low flow by 41 times averaged for the three cities. In conclusion, the LISFLOOD model is a sophisticated model for land and water management planning on the catchment scale for reducing the effects of flood and drought.

Uncertainty of modelled flow regime for flow-ecological assessment in Southern Europe.

Sustainable water basin management requires characterization of flow regime in river networks impacted by anthropogenic pressures. Flow regime in ungauged catchments under current, future, or natural conditions can be assessed with hydrological models. Developing hydrological models is, however, resource demanding such that decision makers might revert to models that have been developed for other purposes and are made available to them ('off-the-shelf' models). In this study, the impact of epistemic uncertainty of flow regime indicators on flow-ecological assessment was assessed at selected stations with drainage areas ranging from about 400 to almost 90,000km2 in four South European basins (Adige, Ebro, Evrotas and Sava). For each basin, at least two models were employed. Models differed in structure, data input, spatio-temporal resolution, and calibration strategy, reflecting the variety of conditions and purposes for which they were initially developed. The uncertainty of modelled flow regime was assessed by comparing the modelled hydrologic indicators of magnitude, timing, duration, frequency and rate of change to those obtained from observed flow. The results showed that modelled flow magnitude indicators at medium and high flows were generally reliable, whereas indicators for flow timing, duration, and rate of change were affected by large uncertainties, with correlation coefficients mostly below 0.50. These findings mirror uncertainty in flow regime indicators assessed with other methods, including from measured streamflow. The large indicator uncertainty may significantly affect assessment of ecological status in freshwater systems, particularly in ungauged catchments. Finally, flow-ecological assessments proved very sensitive to reference flow regime (i.e., without anthropogenic pressures). Model simulations could not adequately capture flow regime in the reference sites comprised in this study. The lack of reliable reference conditions may seriously hamper flow-ecological assessments. This study shows the pressing need for improving assessment of natural flow regime at pan-European scale.

Integrating remotely sensed surface water extent into continental scale hydrology.

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.