A lumped conceptual model to simulate groundwater level time-series

Lumped, conceptual groundwater models can be used to simulate groundwater level time-series quickly and efficiently without the need for comprehensive modelling expertise. A new model of this type, AquiMod, is presented for simulating groundwater level time-series in unconfined aquifers. Its modular design enables users to implement different model structures to gain understanding about controls on aquifer storage and discharge. Five model structures are evaluated for four contrasting aquifers in the United Kingdom. The ability of different model structures and parameterisations to replicate the observed hydrographs is examined. AquiMod simulates the quasi-sinusoidal hydrographs of the relatively uniform Chalk and Sandstone aquifers most efficiently. It is least efficient at capturing the flashy hydrograph of a heterogeneous, fractured Limestone aquifer. The majority of model parameters demonstrate sensitivity and can be related to available field data. The model structure experiments demonstrate the need to represent vertical aquifer heterogeneity to capture the storage-discharge dynamics efficiently

Investigating the impacts of low permeability layers in the Chalk on groundwater levels and river flows using multiple modelling methods : lessons from the Ver catchment

In northwest Hertfordshire, the Chalk stratigraphy comprises of the New Pit Formation with numerous marl bands. At the base of the underlying Hollywell Nodular is the Melbourn Rock and the Plenus Marls Member. These marl bands are characterized as low hydraulic conductivity horizons and can “split" the aquifer and control its response to perturbations such as recharge and abstraction. In this study we apply numerical modelling to site data of the Chalk aquifer near the River Ver to explore how these various low permeability marl layers might affect Chalk stream baseflow in response to changes in groundwater abstraction. Groundwater in southeast England supports a large proportion of public water supply and sensitive ecosystems. A significant proportion of this groundwater comes from the Chalk aquifer. The Government’s 25-Year Environment Plan highlights the importance of restoring flow to ecologically important chalk streams. Here we demonstrate the importance of multi layer settings of hydrogeological models to improve the management of water resources and protect England’s rare chalk streams

Constraining recharge and groundwater models with HydEOmex soil moisture observations

Estimation of groundwater recharge has underpinned a wide variety of groundwater resource and quality assessments within the UK at a range of scales. For example, there are many studies that have quantified time‑varying recharge rates in order to model the transport of diffuse and point-source pollutants from the land surface, through groundwater systems to receptors such as rivers and abstraction boreholes (e.g. Stuart et al., 2006; Wilby et al., 2006; Jackson et al., 2007; Cuthbert et al., 2013; Ascott et al., 2016; Wang et al., 2016). Groundwater recharge estimation is, of course, central to groundwater resource evaluation and catchment management (Environment Agency, 2011), including the estimation of sustainable groundwater abstraction licences (Environment Agency, 2013), predominantly undertaken by the UK’s environmental regulators. At the scale of a UK regional aquifer (approximately 100-2500km2) estimates of recharge have generally been evaluated by constructing catchment water balances, but also by assessing the performance of regional groundwater models driven with simulated recharge time-series (Quinn et al., 2012). Catchment boundaries used to construct water balances have not always coincided with those of groundwater systems, therefore the use of regional groundwater flow models to constrain estimates of groundwater recharge has become popular within the UK (Shepley et al., 2012). Because recharge can only be measured directly at the point scale, and even then with difficulty, regional groundwater flow models have often been used as the only means to evaluate recharge estimates. However, it is not uncommon for both the parameters of recharge and groundwater flow models to be adjusted at the same time during model calibration to obtain a good “fit” to the state variables that can be measured: principally groundwater levels and river flows. Recharge models typically simulate soil drainage, or potential recharge, by conceptualising the surface infiltration, evaporation, runoff, and drainage processes of the soil store. Many different types of recharge model, of varying degrees of complexity, have been applied (e.g. Finch, 1998; Heathcote et al., 2004; Sorensen et al., 2014), most of which include a variable that describes the saturation of the soil; often expressed as a soil moisture deficit (SMD) with respect to a field capacity (FC), or as a volumetric water content. Examples in which soil water contents simulated by recharge models used to drive regional groundwater models have been compared to observations of soil moisture are difficult to identify in the literature. Studies which consider aspects of this problem include Crow et al. (2005), Brunner et al. (2007), Montzka et al. (2012), and Albergel et al. (2012), but the specific task of assimilating soil moisture observations, whether derived from instruments installed in the soil (e.g. tensiometers or neutron probes) or remotely sensed, into distributed recharge and groundwater models does not appear to have been considered. Recently new spatial datasets have become available due to the development and application of remote sensing methods to monitor soil moisture. Many of these datasets are derived from satellite remote sensing (at a resolution of ~1km), but in-catchment instruments are now also generating time-series of soil moisture at the field-scale (approximately 100m). These new datasets provide the opportunity to evaluate recharge models used to drive regional groundwater flow models, and to constrain their parameter values and outputs. In this study we investigate the use of new remote-sensed soil moisture data products to do this, and consider their value to the groundwater modelling community. We do this using very simple recharge and groundwater models calibrated and evaluated against observed soil moisture content and groundwater level data

Methods and models to quantify climate-driven changes in groundwater resources

Understanding climate-driven changes in groundwater resources is essential for future water resources management. In this paper, we review methods and models developed to quantify past, present and future climate-driven changes in groundwater resources, and provide an outlook for future research and practice. The Standardised Groundwater level Index (SGI) has been an effective methodology for quantifying historic groundwater resource status across different sites using observed historical data. However, the paucity of groundwater level data means that modelling groundwater levels may also be required. Lumped parameter models such as AquiMod have been shown to be effective at reconstructing groundwater levels at observation boreholes beyond historic records. These models have also been used for seasonal forecasting of groundwater levels and quantifying impacts of climate change. Major challenges remain in linking indicators of groundwater resource status (i.e. levels) with downstream impacts at both the high and low end of the hydrograph. An example of this is provided by estimating impacts of climate change on yields at abstraction boreholes during drought. As well as linking groundwater levels to impacts, future research should explore the full range of the SGI and apply the latest climate model data to AquiMod models. Access to both live groundwater level observations and high performance computing facilities would allow the methods reviewed here to be applied automatically, providing real-time hydrogeological data services

Reconstruction of multi-decadal groundwater level time-series using a lumped conceptual model

Multi-decadal groundwater level records, which provide information about long-term variability and trends, are relatively rare. Whilst a number of studies have sought to reconstruct river flow records, there have been few attempts to reconstruct groundwater level time-series over a number of decades. Using long rainfall and temperature records, we developed and applied a methodology to do this using a lumped conceptual model. We applied the model to six sites in the UK, in four different aquifers: Chalk, limestone, sandstone and Greensand. Acceptable models of observed monthly groundwater levels were generated at four of the sites, with maximum Nash–Sutcliffe Efficiency scores of between 0.84 and 0.93 over the calibration and evaluation periods, respectively. These four models were then used to reconstruct the monthly groundwater level time-series over approximately 60 years back to 1910. Uncertainty in the simulated levels associated with model parameters was assessed using the Generalized Likelihood Uncertainty Estimation method. Known historical droughts and wet period in the UK are clearly identifiable in the reconstructed levels, which were compared using the Standardized Groundwater Level Index. Such reconstructed records provide additional information with which to improve estimates of the frequency, severity and duration of groundwater level extremes and their spatial coherence, which for example is important for the assessment of the yield of boreholes during drought period

Data-Driven Estimation of Groundwater Level Time-Series at Unmonitored Sites Using Comparative Regional Analysis

A new method is presented to efficiently estimate daily groundwater level time series at unmonitored sites by linking groundwater dynamics to local hydrogeological system controls. The proposed approach is based on the concept of comparative regional analysis, an approach widely used in surface water hydrology, but uncommon in hydrogeology. Using physiographic and climatic site descriptors, the method utilizes regression analysis to estimate cumulative frequency distributions of groundwater levels (groundwater head duration curves, HDC) at unmonitored locations. The HDC is then used to construct a groundwater hydrograph using time series from distance-weighted neighboring monitored (donor) locations. For estimating times series at unmonitored sites, in essence, spatio-temporal interpolation, stepwise multiple linear regression (MLR), extreme gradient boosting (XGB), and nearest neighbors are compared. The methods were applied to 10-year daily groundwater level time series at 157 sites in unconfined alluvial aquifers in Southern Germany. Models of HDCs were physically plausible and showed that physiographic and climatic controls on groundwater level fluctuations are nonlinear and dynamic, varying in significance from “wet” to “dry” aquifer conditions. XGB yielded a significantly higher predictive skill than nearest neighbor and MLR. However, donor site selection is of key importance. The study presents a novel approach for regionalization and infilling of groundwater level time series that also aids conceptual understanding of controls on groundwater dynamics, both central tasks for water resources managers

Isolating the impacts of anthropogenic water use within the hydrological regime of north India

The effects of anthropogenic water use play a significant role in determining the hydrological cycle of north India. This paper explores anthropogenic impacts within the region's hydrological regime by explicitly including observed human water use behaviour, irrigation infrastructure and the natural environment in the CHANSE (Coupled Human And Natural Systems Environment) socio‐hydrological modelling framework. The model is constrained by observed qualitative and quantitative information collected in the study area, along with climate and socio‐economic variables from additional sources. Four separate scenarios, including business as usual (BAU, representing observed irrigation practices), groundwater irrigation only (where the influence of the canal network is removed), canal irrigation only (where all irrigation water is supplied by diverted surface water) and rainfed only (where all human interventions are removed) are used. Under BAU conditions the modelling framework closely matched observed groundwater levels. Following the removal of the canal network, which forces farmers to rely completely on groundwater for irrigation, water levels decrease, while under a canal‐only scenario flooding occurs. Under the rainfed‐only scenario, groundwater levels similar to current business‐as‐usual conditions are observed, despite much larger volumes of recharge and discharge entering and leaving the system under BAU practices. While groundwater abstraction alone may lead to aquifer depletion, the conjunctive use of surface and groundwater resources, which includes unintended contributions of canal leakage, create conditions similar to those where no human interventions are present. Here, the importance of suitable water management practices, in maintaining sustainable water resources, is shown. This may include augmenting groundwater resources through managed aquifer recharge and reducing the impacts on aquifer resources through occasional canal water use where possible. The importance of optimal water management practices that highlight trade‐offs between environmental impact and human wellbeing are shown, providing useful information for policy makers, water managers and user

Time of emergence of impacts of climate change on groundwater levels in sub-Saharan Africa

The impacts of climate change on groundwater are poorly constrained, particularly in regions such as sub-Saharan Africa where global circulation models (GCMs) project different directions of precipitation change. Moreover, the timing of when climate change impacts on groundwater can be differentiated from natural variability has not been quantified. Here, for the first time, we estimate the time of emergence (ToE) of climate change impacts on groundwater levels, using time series from eight sites across Burkina Faso, West Africa. We apply output data from historical and RCP8.5 runs of CMIP5 GCMs to lumped groundwater models for each site, and estimate ToE by calculating signal to noise ratios for each site and CMIP5 model. We show that in addition to inconsistent direction of climate change impacts across different GCMs, there is inconsistency in the ToE of climate change signals in future groundwater levels, particularly in drying GCMs. Across the eight sites, between 5 (4) and 13 (13) CMIP5 GCMs of a possible 23 show a ToE associated with decreases (increases) in groundwater levels. ToE from CMIP5 GCMs producing decreases in groundwater levels (i.e. drying) is highly variable between sites and GCMs (across all sites, median ToE = 2049, interquartile range = 48 years). For CMIP5 GCMs producing increases in groundwater levels (i.e. wetting), ToE appears to occur earlier and with less variability (across all sites median ToE = 2011, interquartile range = 11 years). These results underline the need for development of no-regrets adaptation measures in parallel with reductions in GCM uncertainty

Localizing hydrological drought early warning using in situ groundwater sensors

Drought early warning systems (DEWSs) aim to spatially monitor and forecast risk of water shortage to inform early, risk-mitigating interventions. However, due to the scarcity of in situ monitoring in groundwater-dependent arid zones, spatial drought exposure is inferred using maps of satellite-based indicators such as rainfall anomalies, soil moisture, and vegetation indices. On the local scale, these coarse-resolution proxy indicators provide a poor inference of groundwater availability. The improving affordability and technical capability of modern sensors significantly increases the feasibility of taking direct groundwater level measurements in data-scarce, arid regions on a larger scale. Here, we assess the potential of in situ monitoring to provide a localized index of hydrological drought in Somaliland. We find that calibrating a lumped groundwater model with a short time series of groundwater level observations substantially improves the quantification of local water availability when compared to satellite-based indices. By varying the calibration length, we find that a 5-week period capturing both wet and dry season conditions provides most of the calibration capacity. This suggests that short monitoring campaigns are suitable for improving estimations of local water availabilities during drought. Short calibration periods have practical advantages, as the relocation of sensors enables rapid characterization of a large number of wells. These well simulations can supplement continuous in situ monitoring of strategic point sources to setup large-scale monitoring systems with contextualized and localized information on water availability. This information can be used as early warning evidence for the financing and targeting of early actions to mitigate impacts of hydrological drought