Recharge Time Series Research Articles

Recharge Estimation Approach in a Data-Scarce Semi-Arid Region, Northern Ethiopian Rift Valley

Sustainable management of groundwater resources highly relies on the accurate estimation of recharge. However, accurate recharge estimation is a challenge, especially in data-scarce regions, as the existing models are data-intensive and require extensive parameterization. This study developed a process-based hydrologic model combining local and remotely sensed data for characterizing recharge in data-limited regions using a Basin Characterization Model (BCM). This study was conducted in Raya and Kobo Valleys, a semi-arid region in Northern Ethiopia, considering both the structural basin and the surrounding mountainous recharge areas. Climatic Research Unit monthly datasets for 1991 to 2020 and WaPOR actual evapotranspiration data were used. The model results show that the average annual recharge and surface runoff from 1991 to 2020 were 73 mm and 167 mm, respectively, with a substantial portion contributed along the front of the mountainous parts of the study area. The mountainous recharge occurred along and above the valleys as mountain-block and mountain-front recharge. The long-term estimates of the monthly recharge time series indicated that the water balance components follow the temporal pattern of rainfall amount. However, the relation of recharge to precipitation was nonlinearly related, showing the episodic nature of recharge in semi-arid regions. This study informed the spatial and temporal distribution of recharge and runoff hydrologic variables at fine spatial scales for each grid cell, allowing results to be summarized for various planning units, including farmlands. One third of the precipitation in the drainage basin becomes recharge and runoff, while the remaining is lost through evapotranspiration. The current study’s findings are vital for developing plans for sustainable management of water resources in semi-arid regions. Also, monthly groundwater withdrawals for agriculture should be regulated in relation to spatial and temporal recharge patterns. We conclude that combining scarce local data with global datasets and tools is a useful approach for estimating recharge to manage groundwater resources in data-scarce regions.

Advanced application of time series analysis in complex karst aquifers: A case study of the Unica springs (SW Slovenia)

Karst aquifers have very heterogeneous structure and complex hydrodynamics through conduits, fractures and matrix, therefore characteristics of groundwater flow and solute transport differ from those in intergranular and fissured aquifers. Appropriately adapted techniques of hydrogeological research are required for understanding of their functioning. This paper presents an advanced application of time series analysis in a binary karst aquifer known for its complex hydrodynamics and mixing of water from various sources of recharge. A classical approach with high temporal data resolution was extended to a spatial domain with simultaneous monitoring of precipitation, sinking streams, water flow in cave systems, and springs. The main objectives of this study were to define and compare the flow characteristics and storage capacity of selected springs and their catchments, and to determine the influence of different types of recharge (autogenic versus allogenic). The time series of recharge were analysed as input functions in the correlation and spectral analysis. The results undoubtedly show differences in water transfer through the system, storage capacity, and recharge characteristics. However, they also highlight the limitations of using cross-correlation functions to distinguish the influence of autogenic and allogenic recharge. Due to their interference, the interpretation of the results in complex karst systems can be ambiguous, therefore a method of partial cross-correlation analysis was additionally used. Although it has been used before in karst aquifers to spatially characterise groundwater circulation and autogenic recharge, in this study it was used for the first time to investigate the mutual influences of allogenic and autogenic recharge. The results confirmed that this approach provides additional insight into the functioning of binary karst aquifers.

Rainfall-Runoff Time Lags from Saltwater Interface Interactions in Atlantic Coastal Plain Basins

The dynamic behavior of the freshwater-saltwater interface (FSI) in coastal aquifers can introduce unexpected lags between recharge and stream discharge, especially when recharge is forced by long-term cyclical precipitation patterns. This work seeks to assess these FSI impacts at the watershed scale. Recharge-discharge time lags were evaluated in 68 watersheds overlying the Floridan Aquifer System in the coastal region of the southeastern United States (Florida, Georgia, and South Carolina). Utilizing the strength of the Atlantic multidecadal oscillation (AMO) signal in this region, 10–20 year averaged recharge and discharge time series were used for the selected watersheds. Lags of 10–25 years between recharge and discharge were found in 16% of the basins considered, possibly induced by a dynamic FSI which responded slowly to the AMO-scale recharge signal. Freshwater storage coefficients (S) were estimated from time series of change-in-storage and groundwater level, with 11 basins showing S>1.5 indicating water storage well above that expected for unconfined aquifers. These 11 basins with both multidecadal recharge-discharge time lags and high S values showed a positive linear relationship between time lag and FSI depth with slope 0.016 yr/m (R-squared = 0.30). These large time lags may be directly impacting the management of these basins as they obscure water and solute mass balances in the southeastern US.

Upscaling Hillslope‐Scale Subsurface Flow to Inform Catchment‐Scale Recession Behavior

AbstractThe subsurface flow contribution to a basin hydrograph is often conceptualized as a single lumped reservoir parameterized by a power law function fit through the observed recession behavior of the basin. However, basins may be better represented as multiple independent subsurface hillslope reservoirs characterized with variable, transient recession behavior as a function of the time history of recharge. In this work, we unify the latter, more complex understanding of the subsurface with the large‐scale power law recession behavior convenient in hydrologic modeling applications. This unification is achieved by deriving upscaling relationships capable of converting simple metrics of basin hillslope topography into a signature basin response characterizing the subsurface‐flow‐induced recession from a single recharge event. Event superposition may then be used to simulate the application of a time series of recharge and a simple scaling relationship may be used to handle basins with homogeneous conductivity. The signature response is informed by numerical simulations of the hillslope‐storage Boussinesq equation for unconfined saturated flow through sloping hillslopes applied to 30 basins in the CAMELS database. The efficacy of the upscaled signature response in replicating numerical simulations in 50 CAMELS basins is demonstrated, as is the practical efficacy of the upscaling relationships for predicting transient recession in 17 of these basins. The upscaled signature response method thus provides a tool for hydrologic modelers to estimate transient recession parameters using the insights of subsurface flow modeling, although the predictions made by this method are unable to capture the full variability of observed recession behavior.

Recharge variability in Australia's southeast alpine region derived from cave monitoring and modern stalagmite δ18O records

Oxygen isotopic (δ18O) variations in stalagmite records have the potential to provide new insights about past climates beyond the instrumental record. This paper presents the first high-resolution oxygen isotope time series of three coeval stalagmite records from the alpine region of south-eastern Australia covering the period 1922–2006 CE. We use extended surface and cave monitoring datasets, petrographic investigation, modelled recharge time series and farmed calcite precipitates to assess the controls on speleothem δ18O and investigate the coherence between three records from Harrie Wood Cave. The drip water response to recent interannual rainfall variability shows that cave drip water Cl−, δ18O and drip rate display a clear response to an increase in rainfall recharge. It is demonstrated that stalagmites from the same drip sites also record variability in interannual recharge, where an increase in δ18O values is observed with lower recharge, while a decrease in δ18O values correspond to higher recharge amounts. The three stalagmite δ18O records are in broad agreement, showing common responses to relatively higher recharge between 1945 and 1995 CE and the low recharge periods between 1937 and 1945 CE (World War II drought) and late 1996 to 2006 CE (beginning of the Millennium Drought). However, differences in the magnitude of the relative response of each stalagmite δ18O record varies. Based on evidence from our cave monitoring study and farmed calcites, we conclude that the differences between the three stalagmite records is attributed to variability in the contribution of preferential flows during recharge events and the store reservoir volume supplying the drip site. When the δ18O decreases in response to enhanced recharge, the speleothem δ13C also decreases, and this is interpreted to reflect a soil respiration response to changes in soil moisture availability due to recharge. Hence, stalagmite δ18O from the Australian alpine region can be applied to reconstruct periods of relatively higher and lower rainfall recharge and thus extend our knowledge of the timing and relative magnitude of droughts as well as past periods of higher recharge in this region.

Daily time series of groundwater recharge derived from temporal variation of water level

Daily time series of groundwater recharge derived from temporal variation of water level

Use of an Efficient Proxy Solution for the Hillslope‐Storage Boussinesq Problem in Upscaling of Subsurface Stormflow

AbstractThe hillslope‐storage Boussinesq (hsB) equation is a modification of the one‐dimensional Boussinesq representation of saturated subsurface flow that accommodates the impact of converging and diverging flows resulting from a hillslope with nonconstant width. Here, a surrogate model, the hsB Proxy, is developed which closely emulates the results of high‐quality numerical solutions of the hsB to reproduce the drainage response of a wide range of wedge‐shaped hillslopes in response to a recharge time series at a fraction of the computational cost of a numerical solution and with minimal loss of fidelity. The efficacy of the Proxy in emulating the hsB response of a single hillslope and the aggregate response of a network of hillslopes is demonstrated. The Proxy applies to wedge‐shaped hillslopes with homogenous hydraulic conductivity under uniform recharge, with the expectation that these hillslopes may inform future investigations into the upscaling behavior that results in the known power‐law relationship between subsurface storage and outflow in a basin. The utility of the hsB as a tool for evaluating upscaling problems is demonstrated in two applications. First, the Proxy response is compared to the known basin‐scale recession behavior in the Panola Mountain Research Watershed, under both transient and steady‐state conditions. Second, the Proxy is applied to derive the single best effective hillslope in a basin. The Proxy is expected to be a useful tool for rapid simulation of subsurface flow from hillslopes for use in hydrological models and land surface schemes.

Vadose Zone Lag Time Effect on Groundwater Drought in a Temperate Climate

An essential factor in the propagation of drought, from meteorological drought to groundwater drought, is the delay between a precipitation event and the groundwater recharge reaching the groundwater table. This delay, which mainly occurs in the vadose zone of the hydrological cycle, is often poorly studied. Therefore, this paper proposes a method for estimating the spatially distributed delay in the vadose zone using the kinematic wave approximation of Richards’ equation combined with the van Genuchten–Burdine and Brooks–Corey parametric model. The modeling was approached (1) using a detailed parametrization of soil and geological layers and (2) using lumped hydraulic and physical properties of geological layers. The results of both approaches were compared against the physically based flow model Hydrus-1D. This analysis shows that using a detailed parametrization of soil and geological layers results in good comparison, with a Nash–Sutcliffe efficiency of 0.89 for Brooks–Corey and 0.80 for van Genuchten–Burdine. The delay result of the Brooks–Corey model was incorporated into the groundwater recharge time series from 1980 to 2013 to analyze the effect of this delay on groundwater drought. The results show that the delay in the vadose zone influences groundwater drought characterization features such as the number, duration, and intensity of drought events.

Quantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach – first application on the Amazon

Abstract. The knowledge of water storage volumes in catchments and in river networks leading to river discharge is essential for the description of river ecology, the prediction of floods and specifically for a sustainable management of water resources in the context of climate change. Measurements of mass variations by the GRACE gravity satellite or by ground-based observations of river or groundwater level variations do not permit the determination of the respective storage volumes, which could be considerably bigger than the mass variations themselves. For fully humid tropical conditions like the Amazon the relationship between GRACE and river discharge is linear with a phase shift. This permits the hydraulic time constant to be determined and thus the total drainable storage directly from observed runoff can be quantified, if the phase shift can be interpreted as the river time lag. As a time lag can be described by a storage cascade, a lumped conceptual model with cascaded storages for the catchment and river network is set up here with individual hydraulic time constants and mathematically solved by piecewise analytical solutions. Tests of the scheme with synthetic recharge time series show that a parameter optimization either versus mass anomalies or runoff reproduces the time constants for both the catchment and the river network τC and τR in a unique way, and this then permits an individual quantification of the respective storage volumes. The application to the full Amazon basin leads to a very good fitting performance for total mass, river runoff and their phasing (Nash–Sutcliffe for signals 0.96, for monthly residuals 0.72). The calculated river network mass highly correlates (0.96 for signals, 0.76 for monthly residuals) with the observed flood area from GIEMS and corresponds to observed flood volumes. The fitting performance versus GRACE permits river runoff and drainable storage volumes to be determined from recharge and GRACE exclusively, i.e. even for ungauged catchments. An adjustment of the hydraulic time constants (τC, τR) on a training period facilitates a simple determination of drainable storage volumes for other times directly from measured river discharge and/or GRACE and thus a closure of data gaps without the necessity of further model runs.

Groundwater Recharge Prediction Using Linear Regression, Multi-Layer Perception Network, and Deep Learning

As the largest freshwater storage in the world, groundwater plays an important role in maintaining ecosystems and helping humans adapt to climate change. However, groundwater dynamics, such as groundwater recharge, cannot be measured directly and is influenced by spatially and temporally complex processes, models are therefore required to capture the dynamics and provide scientific advice for decision-making. This paper developed, estimated and compared the performance of linear regression, multi-layer perception (MLP) and Long Short-Term Memory (LSTM) models in predicting groundwater recharge. The experimental dataset consists of time series of annual recharge from the year 1970 to 2012, based on water table fluctuation estimates from 465 bores in the states of South Australia and Victoria, Australia. We identified the factors that influenced groundwater recharge and found that the correlation between rainfall and groundwater recharge was strongest. The linear regression model had the poorest fitting performance, with the root mean squared error (RMSE) being greater than 0.19 when various proportions of training data were considered. The MLP model outperformed the linear regression in the prediction capability, achieving RMSE = 0.11 when 80% of training data was considered. The LSTM model was found to have the best performance, whose root mean squared errors were less than 0.12 when various proportions of training data were applied. The relative importance of influential predictors was evaluated using the above three models.

Spatial and temporal variability of groundwater recharge in a sandstone aquifer in a semiarid region

Abstract. With the aim to understand the spatial and temporal variability of groundwater recharge, a high-resolution, spatially distributed numerical model (MIKE SHE) representing surface water and groundwater was used to simulate responses to precipitation in a 2.16 km2 upland catchment on fractured sandstone near Los Angeles, California. Exceptionally high temporal and spatial resolution was used for this catchment modeling: hourly climate data, a 20 m×20 m grid in the horizontal plane, and 240 numerical layers distributed vertically within the thick vadose zone and in the upper part of the groundwater zone. The finest practical spatial and temporal resolutions were selected to accommodate the large degree of surface and subsurface variability of catchment features. Physical property values for the different lithologies were assigned based on previous on-site investigations, whereas the parameters controlling streamflow and evapotranspiration were derived from calibration to continuous streamflow at the outfall and to average hydraulic heads from 17 wells. Confidence in the calibrated model was enhanced by validation through (i) comparison of simulated average recharge to estimates based on the applications of the chloride mass-balance method to data from the groundwater and vadose zones within and beyond the catchment, (ii) comparison of the water isotope signature (18O and 2H) in shallow groundwater to the variability of isotope signatures for precipitation events over an annual cycle, and (iii) comparison of simulated recharge time series and observed fluctuation of water levels. The average simulated recharge across the catchment for the period 1995–2014 is 16 mm yr−1 (4 % of the average annual precipitation), which is consistent with previous estimates obtained by using the chloride mass balance method (4.2 % of the average precipitation). However, one of the most unexpected results was that local recharge was simulated to vary from 0 to >1000 mm yr−1 due to episodic precipitation and overland runoff effects. This recharge occurs episodically with the major flux events at the bottom of the evapotranspiration zone, as simulated by MIKE SHE and confirmed by the isotope signatures, occurring only at the end of the rainy season. This is the first study that combines MIKE SHE simulations with the analysis of water isotopes in groundwater and rainfall to determine the timing of recharge in a sedimentary bedrock aquifer in a semiarid region. The study advances the understanding of recharge and unsaturated flow processes and enhances our ability to predict the effects of surface and subsurface features on recharge rates. This is crucial in highly heterogeneous contaminated sites because different contaminant source areas have widely varying recharge and, hence, groundwater fluxes impacting their mobility.

Contribution of isotopic research techniques to characterize high-mountain-Mediterranean karst aquifers: The Port del Comte (Eastern Pyrenees) aquifer

Water resources in high mountain karst aquifers are usually characterized by high rainfall, recharge and discharge that lead to the sustainability of the downstream ecosystems. Nevertheless, these hydrological systems are vulnerable to the global change impact. The mean transit time (MTT) is a key parameter to describe the behavior of these hydrologic systems and also to assess their vulnerability. This work is focused on estimating MTT by using environmental tracers in the framework of high-mountain karst systems with a very thick unsaturated zone (USZ). To this end, it is adapted to alpine zones a methodology that combines a semi-distributed rainfall-runoff model to estimate recharge time series, and a lumped-parameter model to obtain ΜΤΤ. The methodology has been applied to the Port del Comte Massif (PCM) hydrological system (Southeastern Pyrenees, NE Spain), a karst aquifer system with an overlying 1000 m thick USZ. Six catchment areas corresponding to most important springs of the system are considered. The obtained results show that hydrologically the behavior of the system can be described by an exponential flow model (EM), with MTT ranging between 1.9 and 2.9 years. These ΜΤΤ values are shorter than those obtained by considering a constant recharge rate along time, which is the easiest and most applied aquifer recharge hypothesis when estimating ΜΤΤ through lumped-parameter models.

Modeling impacts of climate change and human activities on groundwater resources using MODFLOW

Abstract This paper analyzes the impacts of climate change and human pressures on Yazd-Ardakan aquifer using the Hadley Centre Coupled Model, version 3 (HADCM3) circulation Model and A2 emission scenario. Water levels in the study aquifer were simulated using three-dimensional finite-difference groundwater model (MODFLOW 2000) with GMS 8.3 as pre- and postprocessing software. Input for groundwater recharge time series under the climate change scenarios were derived using a regression equation based on the cumulative deviation from mean rainfall using MATLAB. Human pressures on the aquifer were modeled through climate change impacts on water requirements of cultivated areas. Three scenarios were simulated to represent the effects of climate change and human pressures on aquifer storage and hydraulic head. Climate change and human pressures (scenario 1) will reduce aquifer storage and result in decreasing hydraulic head by −0.56 m year−1. Reduction in pumping water under scenario 2 (irrigation system modification) and scenario 3 (irrigation system modification and cropping patterns) will result in groundwater level fluctuation of about −0.32 and 0.08 m year−1, respectively. Scenario 3 is capable of restoring and protecting the groundwater resources in Yazd-Ardakan aquifer. The results of this study are useful to obtain sustainable groundwater management in Yazd-Ardakan aquifer.

Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands

Abstract. Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.

Numerical simulation of transient groundwater age distributions assisting land and water management in the Middle Wairarapa Valley, New Zealand

AbstractThis study used numerical models to simulate transient groundwater age distributions using a time‐marching Laplace transform Galerkin (TMLTG) technique. First, the TMLTG technique was applied to simple box models configured to match idealized lumped parameter models (LPMs). Even for simple box models, time‐varying recharge can generate groundwater age distributions with highly irregular shapes that vary over time in response to individual recharge events. Notably, the transient numerical simulations showed that the breakthrough and mean ages are younger than in the steady flow case, and that this difference is greater for sporadic recharge time series than for more regular recharge time series. Second, the TMLTG technique was applied to a transient numerical model of the 270 km2 Middle Wairarapa Valley, New Zealand. To our knowledge this study is the first application of the TMLTG technique to a real‐world example, made possible by the data set of tritium measurements that exists for the Wairarapa Valley. Results from a transient mean age simulation shows variation from a few days to over a decade in either temporal or spatial dimensions. Temporal variations of mean age are dependent on seasonal climate and groundwater abstraction. Results also demonstrated important differences between the transient age distributions derived from the TMLTG technique compared to the much simpler steady‐state LPMs that are frequently applied to interpret age tracer data. Finally, results had direct application to land and water management, for example for identification of land areas where age distributions vary seasonally, affecting the security of groundwater supplies used for drinking water.

Effect of heterogeneity on spatiotemporal variations of groundwater level in a bounded unconfined aquifer

Spatiotemporal variations of groundwater level due to a white noise recharge time series and a random transmissivity field in a bounded unconfined aquifer was studied. The analytical solutions for the variance and covariance of groundwater level were derived with non-stationary spectral analyses and superposition principle. It was found that the fluctuations of groundwater level are spatially non-stationary due to a fixed head boundary condition and temporal non-stationary at early time but gradually became stationary as time progresses due to effect of the initial condition. The variation in groundwater level is mainly caused by the random source/sink in the case of temporally random recharge and spatially random transmissivity. The effect of heterogeneity is to increase the variation of groundwater level and the maximum effect occurs close to the constant head boundary because of the linear mean hydraulic gradient. The heterogeneity also enhances the correlation of groundwater level, especially at large time intervals and small spatial distances.

컨벌루션 기법을 이용한 제주도 지하수 함양량의 시공간적 변화 분석

Temporal variation of groundwater levels in Jeju Island reveals time-delaying and dispersive process of recharge, mainly caused by the hydrogeological feature that thickness of the unsaturated zone is highly variable. Most groundwater flow models have limitations on delineating temporal variation of recharge, although it is a major component of the groundwater flow system. A new mathematical model was developed to generate time series of recharge from precipitation data. The model uses a convolution technique to simulate the time-delaying and dispersive process of recharge. The vertical velocity and the dispersivity are two parameters determining the time series of recharge for a given thickness of the unsaturated zone. The model determines two parameters by correlating the generated recharge time series with measured groundwater levels. The model was applied to observation wells of Jeju Island, and revealed distinctive variations of recharge depending on location of wells. The suggested model demonstrated capability of the convolution method in dealing with recharge undergoing the time-delaying and dispersive process. Therefore, it can be used in many groundwater flow models for generating a time series of recharge.

Analysis of groundwater drought building on the standardised precipitation index approach

Abstract. A new index for standardising groundwater level time series and characterising groundwater droughts, the Standardised Groundwater level Index (SGI), is described. The SGI builds on the Standardised Precipitation Index (SPI) to account for differences in the form and characteristics of groundwater level and precipitation time series. The SGI is estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. These monthly estimates are then merged to form a continuous index. The SGI has been calculated for 14 relatively long, up to 103 yr, groundwater level hydrographs from a variety of aquifers and compared with SPI for the same sites. The relationship between SGI and SPI is site specific and the SPI accumulation period which leads to the strongest correlation between SGI and SPI, qmax, varies between sites. However, there is a consistent positive linear correlation between a measure of the range of significant autocorrelation in the SGI series, mmax, and qmax across all sites. Given this correlation between SGI mmax and SPI qmax, and given that periods of low values of SGI can be shown to coincide with previously independently documented droughts, SGI is taken to be a robust and meaningful index of groundwater drought. The maximum length of groundwater droughts defined by SGI is an increasing function of mmax, meaning that relatively long groundwater droughts are generally more prevalent at sites where SGI has a relatively long autocorrelation range. Based on correlations between mmax, average unsaturated zone thickness and aquifer hydraulic diffusivity, the source of autocorrelation in SGI is inferred to be dependent on dominant aquifer flow and storage characteristics. For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI is inferred to be primarily related to autocorrelation in the recharge time series, while in granular aquifers, such as the Permo–Triassic sandstones, autocorrelation in SGI is inferred to be primarily a function of intrinsic saturated flow and storage properties of aquifer. These results highlight the need to take into account the hydrogeological context of groundwater monitoring sites when designing and interpreting data from groundwater drought monitoring networks.

Temporal scaling of groundwater discharge in dual and multicontinuum catchment models

This paper presents a multicontinuum approach to model fractal temporal scaling of catchment response in hydrological systems. The temporal scaling of discharge is quantified in frequency domain by the transfer function HðxÞ, which is defined as the ratio between the spectra of catchment response and recharge time series. The transfer function may scale with frequency x as HðxÞ x2b. While the classical linear and Dupuit models predict exponents of b52 and b51, observations indicate scalings with noninteger exponents b. Such behaviors have been described by multifractal models, which, however, often lack a relation to the medium characteristics. We revisit and extend the classical linear Dupuit aquifer models and discuss their physical meanings in the light of the resulting aquifer dynamics. On the basis of these classical models, we derive a multicontinuum approach that provides physical recharge models which are able to explain fractal behaviors with exponents 1=2 < b < 2. Furthermore, this approach allows to link the fractal dynamics of the discharge process to the physical aquifer characteristics as reflected in the distribution of storage time scales. We systematically analyze the catchment responses in the proposed multicontinuum models, and identify and quantify the time scales which characterize the dynamics of the catchment response to recharge.

A new approach to model the spatial and temporal variability of recharge to karst aquifers

Abstract. In karst systems, near-surface dissolution of carbonate rock results in a high spatial and temporal variability of groundwater recharge. To adequately represent the dominating recharge processes in hydrological models is still a challenge, especially in data scarce regions. In this study, we developed a recharge model that is based on a conceptual model of the epikarst. It represents epikarst heterogeneity as a set of system property distributions to produce not only a single recharge time series, but a variety of time series representing the spatial recharge variability. We tested the new model with a unique set of spatially distributed flow and tracer observations in a karstic cave at Mt. Carmel, Israel. We transformed the spatial variability into statistical variables and apply an iterative calibration strategy in which more and more data was added to the calibration. Thereby, we could show that the model is only able to produce realistic results when the information about the spatial variability of the observations was included into the model calibration. We could also show that tracer information improves the model performance if data about the spatial variability is not included.