Assessment of sources and fate of nitrate in shallow groundwater of an agricultural area by using a multi-tracer approach

AbstractNitrate isotopic values are often used as a tool to understand sources of contamination in order to effectively manage groundwater quality. However, recent literature describes that biogeochemical reactions may modify these values. Therefore, data interpretation is difficult and often vague. We provide a discussion on this topic and complement the study using halides as comparative tracers assessing an aquifer underneath a sub-humid to humid region in NE Mexico. Hydrogeological information and stable water isotopes indicate that active groundwater recharge occurs in the 8000km2 study area under present-day climatic and hydrologic conditions. Nitrate isotopes and halide ratios indicate a diverse mix of nitrate sources and transformations. Nitrate sources include organic waste and wastewater, synthetic fertilizers and soil processes. Animal manure and sewage from septic tanks were the causes of groundwater nitrate pollution within orchards and vegetable agriculture. Dairy activities within a radius of 1000m from a sampling point significantly contributed to nitrate pollution. Leachates from septic tanks caused nitrate pollution in residential areas. Soil nitrogen and animal waste were the sources of nitrate in groundwater under shrubland and grassland. Partial denitrification processes helped to attenuate nitrate concentration underneath agricultural lands and grassland, especially during summer months

Evaluation of the performance of Euro-CORDEX Regional Climate Models for assessing hydrological climate change impacts in Great Britain: A comparison of different spatial resolutions and quantile mapping bias correction methods

Regional Climate Models (RCMs) are an essential tool for analysing regional climate change impacts, such as hydrological change, as they provide simulations with more small-scale details and expected smaller errors than global climate models. There has been much effort to increase the spatial resolution and simulation skill of RCMs (i.e. through bias correction), yet the extent to which this improves the projection of hydrological change is unclear. Here, we evaluate the skill of five reanalysis-driven Euro-CORDEX RCMs in simulating precipitation and temperature, and as drivers of a hydrological model to simulate river flow on four UK catchments covering different physical, climatic and hydrological characteristics. We use a comprehensive range of evaluation indices for aspects of the distribution such as means and extremes, as well as for the structure of time series. We test whether high-resolution RCMs provide added value, through analysis of two RCM resolutions, 0.44° (50 km) and 0.11° (12.5 km), which are also bias-corrected employing the parametric quantile-mapping (QM) method, using the normal distribution for temperature, and the Gamma (GQM) and Double Gamma (DGQM) distributions for precipitation. The performance of these is considered for a range of meteorological variables and for the skill in simulating hydrological impacts at the catchment scale. In a small catchment with complex topography, the 0.11° RCMs clearly outperform their 0.44° version for precipitation and temperature, but when used in combination with the hydrological model, fail to capture the observed river flow distribution. In the other (larger) catchments, only one high-resolution RCM consistently outperforms its low-resolution version, implying that in general there is no added value from using the high-resolution RCMs in those catchments. Both resolutions produce river flow simulations that cover the observed flow duration curve, but the ensemble spread is large and therefore the simulations are difficult to use in practice. GQM decreases most of the simulation biases, except for extreme precipitation and high flows, which are further decreased by DGQM, which also reduces the multi-model simulation spread. Bias correction does not improve the representation of daily temporal variability measured by the Nash-Sutcliffe Efficiency Index, but it does for monthly variability, in particular when applying DGQM, which reduces most of the simulation biases. Overall, an increase in RCM resolution does not imply a better simulation of hydrology and bias-correction represents an alternative to ease decision-making

Spatial and temporal patterns of flow intermittency in a Mediterranean basin using the SWAT+ model

International audienceNon-perennial rivers and streams are ubiquitous. Nonetheless, our understanding of their hydrological patterns is minimal. Hydrological models are powerful tools to study and characterize hydrological patterns, but few can simulate extremes such as non-flow events. We aimed to capture and accurately simulate the flow intermittency spatial and temporal patterns in a Mediterranean river basin with the restructured Soil and Water Assessment Tool (SWAT+). We calibrated the model using a multi-objective optimization algorithm and using data from two gauging stations in the mainstream for the period 2000–2020. Furthermore, we validated the flow intermittency simulations against stage data series at 14 stations. The results indicated that the model accurately simulates flow intermittency and low flows in the study period. We observed a significant variation in flow intermittency in both space and time with a remarkable inter-annual variability. We also observed an increase in flow intermittency over the study period

The effect of weighting hydrological projections based on the robustness of hydrological models under a changing climate

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Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies

International audienceVarious methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. In this study both climate and hydrological models are analysed, and the result of a research experiment is presented using model weighting with the participation of six climate model experts and six hydrological model experts. For the experiment, seven climate models are a priori selected from a larger EURO-CORDEX (Coordinated Regional Downscaling Experiment – European Domain) ensemble of climate models, and three different hydrological models are chosen for each of the three European river basins. The model weighting is based on qualitative evaluation by the experts for each of the selected models based on a training material that describes the overall model structure and literature about climate models and the performance of hydrological models for the present period. The expert elicitation process follows a three-stage approach, with two individual rounds of elicitation of probabilities and a final group consensus, where the experts are separated into two different community groups: a climate and a hydrological modeller group. The dialogue reveals that under the conditions of the study, most climate modellers prefer the equal weighting of ensemble members, whereas hydrological-impact modellers in general are more open for assigning weights to different models in a multi-model ensemble, based on model performance and model structure. Climate experts are more open to exclude models, if obviously flawed, than to put weights on selected models in a relatively small ensemble. The study shows that expert elicitation can be an efficient way to assign weights to different hydrological models and thereby reduce the uncertainty in climate impact. However, for the climate model ensemble, comprising seven models, the elicitation in the format of this study could only re-establish a uniform weight between climate models