Uncertainty in geological and hydrogeological data

Uncertainty in conceptual model structure and in environmental data is of essential interest when dealing with uncertainty in water resources management. To make quantification of uncertainty possible is it necessary to identify and characterise the uncertainty in geological and hydrogeological data. This paper discusses a range of available techniques to describe the uncertainty related to geological model structure and scale of support. Literature examples on uncertainty in hydrogeological variables such as saturated hydraulic conductivity, specific yield, specific storage, effective porosity and dispersivity are given. Field data usually have a spatial and temporal scale of support that is different from the one on which numerical models for water resources management operate. Uncertainty in hydrogeological data variables is characterised and assessed within the methodological framework of the HarmoniRiB classification

A nitrogen budget for Denmark; developments between 1990 and 2010, and prospects for the future

A nitrogen (N) budget for Denmark has been developed for the years 1990 to 2010, describing the inputs and outputs at the national scale and the internal flows between relevant sectors of the economy. Satisfactorily closing the N budgets for some sectors of the economy was not possible, due to missing or contradictory information. The budgets were nevertheless considered sufficiently reliable to quantify the major flows. Agriculture was responsible for the majority of inputs, though fisheries and energy generation also made significant contributions. Agriculture was the main source of N input to the aquatic environment, whereas agriculture, energy generation and transport all contributed to emissions of reactive N gases to the atmosphere. Significant reductions in inputs of reactive N have been achieved during the 20 years, mainly by restricting the use of N for crop production and improving livestock feeding. This reduction has helped reduce nitrate leaching by about half. Measures to limit ammonia emissions from agriculture and mono-nitrogen oxides (NO _x ) emissions from energy generation and transport, has reduced gaseous emissions of reactive N. Much N flows through the food and feed processing industries and there is a cascade of N through the consumer to solid and liquid waste management systems. The budget was used to frame a discussion of the potential for further reductions in losses of reactive N to the environment. These will include increasing the recycling of N between economic sectors, increasing the need for the assessment of knock-on effects of interventions within the context of the national N cycle

Evaluating recharge estimates based on groundwater head from different lumped models in Europe

Study region: The study uses 78 groundwater head time series across 10 European countries with various geological and hydrological settings. Study focus: The estimation of groundwater recharge using time series analysis and lumped modelling based on groundwater head time series is a low-cost and practical method. However, lumped recharge estimation models based on groundwater level variations are uncertain, and successful applications are known to depend on both climate and hydrogeological setting. Here, we assess the suitability of three different models to estimate recharge (Metran - Transfer Function-Noise model, AquiMod - groundwater level driven hydrological model, and GARDÉNIA - lumped catchment model). New hydrological insights: Results showed that while all three models generally did well during the modelling of groundwater heads, the resulting recharge estimations from the models were different. The analysis showed that the transfer-noise modelling of groundwater heads with recharge and evapotranspiration in Metran is not generally applicable for recharge estimation. The addition of physical information in AquiMod improved the recharge estimations, but the reliability was still limited without control of the water balance due to non-uniqueness. By adding discharge information to the modelling, GARDÉNIA can provide more reliable recharge values. Thus, recharge estimation from groundwater head time series without water balance information must be considered uncertain with low precision, but applicability can be improved when including knowledge of the local system