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

Uncertainties in river basin data at various support scales ? Example from Odense Pilot River Basin

International audienceIn environmental modelling studies field data usually have a spatial and temporal scale of support that is different from the one at which models operate. This calls for a methodology for rescaling data uncertainty from one support scale to another. In this paper data uncertainty is assessed for various environmental data types collected for monitoring purposes from the Odense river basin in Denmark by use of literature information, expert judgement and simple data analyses. It is demonstrated how such methodologies can be applied to data that vary in space or time such as precipitation, climate variables, discharge, surface water quality, soil parameters, groundwater abstraction, heads and groundwater quality variables. Data uncertainty is categorised and assessed in terms of probability density functions and temporal or spatial autocorrelation functions. The autocorrelation length scales are crucial when support scale is changing and it is demonstrated how the assumption used when estimating the autocorrelation parameters may limit the applicability of these autocorrelation functions

Current Results of the EC-sponsored Catchment Modelling (CatchMod) Cluster

To support the Water Framework Directive implementation, much research has been commissioned at both national and European levels. CatchMod is a cluster of these projects, which is focusing on the development of computational catchment models and related tools. This paper presents an overview of the results of the CatchMod cluster to dat

Integrated hydrological modeling of the North China Plain and implications for sustainable water management

Groundwater overdraft has caused fast water level decline in the North China Plain (NCP) since the 1980s. Although many hydrological models have been developed for the NCP in the past few decades, most of them deal only with the groundwater component or only at local scales. In the present study, a coupled surface water–groundwater model using the MIKE SHE code has been developed for the entire alluvial plain of the NCP. All the major processes in the land phase of the hydrological cycle are considered in the integrated modeling approach. The most important parameters of the model are first identified by a sensitivity analysis process and then calibrated for the period 2000–2005. The calibrated model is validated for the period 2006–2008 against daily observations of groundwater heads. The simulation results compare well with the observations where acceptable values of root mean square error (RMSE) (most values lie below 4 m) and correlation coefficient (<i>R</i>) (0.36–0.97) are obtained. The simulated evapotranspiration (ET) is then compared with the remote sensing (RS)-based ET data to further validate the model simulation. The comparison result with a <i>R</i>² value of 0.93 between the monthly averaged values of simulated actual evapotranspiration (AET) and RS AET for the entire NCP shows a good performance of the model. The water balance results indicate that more than 70% of water leaving the flow system is attributed to the ET component, of which about 0.25% is taken from the saturated zone (SZ); about 29% comes from pumping, including irrigation pumping and non-irrigation pumping (net pumping). Sustainable water management analysis of the NCP is conducted using the simulation results obtained from the integrated model. An effective approach to improve water use efficiency in the NCP is by reducing the actual ET, e.g. by introducing water-saving technologies and changes in cropping

An automated method to build groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs

Abstract. Large-scale integrated hydrological models are important decision support tools in water resources management. The largest source of uncertainty in such models is the hydrostratigraphic model. Geometry and configuration of hydrogeological units are often poorly determined from hydrogeological data alone. Due to sparse sampling in space, lithological borehole logs may overlook structures that are important for groundwater flow at larger scales. Good spatial coverage along with high spatial resolution makes airborne time-domain electromagnetic (AEM) data valuable for the structural input to large-scale groundwater models. We present a novel method to automatically integrate large AEM data-sets and lithological information into large-scale hydrological models. Clay-fraction maps are produced by translating geophysical resistivity into clay-fraction values using lithological borehole information. Voxel models of electrical resistivity and clay fraction are classified into hydrostratigraphic zones using k-means clustering. Hydraulic conductivity values of the zones are estimated by hydrological calibration using hydraulic head and stream discharge observations. The method is applied to a Danish case study. Benchmarking hydrological performance by comparison of simulated hydrological state variables, the cluster model performed competitively. Calibrations of 11 hydrostratigraphic cluster models with 1–11 hydraulic conductivity zones showed improved hydrological performance with increasing number of clusters. Beyond the 5-cluster model hydrological performance did not improve. Due to reproducibility and possibility of method standardization and automation, we believe that hydrostratigraphic model generation with the proposed method has important prospects for groundwater models used in water resources management.</jats:p

On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark

This study analyzes the quality of the raw and post-processed seasonal forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) System 4. The focus is given to Denmark, located in a region where seasonal forecasting is of special difficulty. The extent to which there are improvements after post-processing is investigated. We make use of two techniques, namely linear scaling or delta change (LS) and quantile mapping (QM), to daily bias correct seasonal ensemble predictions of hydrologically relevant variables such as precipitation, temperature and reference evapotranspiration (ET0). Qualities of importance in this study are the reduction of bias and the improvement in accuracy and sharpness over ensemble climatology. Statistical consistency and its improvement is also examined. Raw forecasts exhibit biases in the mean that have a spatiotemporal variability more pronounced for precipitation and temperature. This variability is more stable for ET0 with a consistent positive bias. Accuracy is higher than ensemble climatology for some months at the first month lead time only and, in general, ECMWF System 4 forecasts tend to be sharper. ET0 also exhibits an underdispersion issue, i.e., forecasts are narrower than their true uncertainty level. After correction, reductions in the mean are seen. This, however, is not enough to ensure an overall higher level of skill in terms of accuracy, although modest improvements are seen for temperature and ET0, mainly at the first month lead time. QM is better suited to improve statistical consistency of forecasts that exhibit dispersion issues, i.e., when forecasts are consistently overconfident. Furthermore, it also enhances the accuracy of the monthly number of dry days to a higher extent than LS. Caution is advised when applying a multiplicative factor to bias correct variables such as precipitation. It may overestimate the ability that LS has in improving sharpness when a positive bias in the mean exists.</p

Modeling subsurface hydrology in floodplains

Evans would also like to acknowledge the generous funding provided by the Natural Environment Research Council (NERC) and the University of St Andrews 600 Fund, without which this work would not have been possible. Singer was supported by funding from NSF EAR #700555. The data output files are hosted online by the NERC Environmental Information Data Centre [Evans et al., 2018].Soil-moisture patterns in floodplains are highly dynamic, owing to the complex relationships between soil properties, climatic conditions at the surface, and the position of the water table. Given this complexity, along with climate change scenarios in many regions, there is a need for a model to investigate the implications of different conditions on water availability to riparian vegetation. We present a model, HaughFlow, which is able to predict coupled water movement in the vadose and phreatic zones of hydraulically connected floodplains. Model output was calibrated and evaluated at 6 sites in Australia to identify key patterns in subsurface hydrology. This study identifies the importance of the capillary fringe in vadose zone hydrology due to its water storage capacity and creation of conductive pathways. Following peaks in water table elevation, water can be stored in the capillary fringe for up to months (depending on the soil properties). This water can provide a critical resource for vegetation that is unable to access the water table. When water table peaks coincide with heavy rainfall events, the capillary fringe can support saturation of the entire soil profile. HaughFlow is used to investigate the water availability to riparian vegetation, producing daily output of water content in the soil over decadal time periods within different depth ranges. These outputs can be summarised to support scientific investigations of plant-water relations, as well as in management applications.Publisher PDFPeer reviewe