Groundwater Modeling in Integrated Water Resources Management—Visions for 2020

Groundwater modeling is undergoing a change from traditional stand-alone studies toward being an integrated part of holistic water resources management procedures. This is illustrated by the development in Denmark, where comprehensive national databases for geologic borehole data, groundwater-related geophysical data, geologic models, as well as a national groundwater-surface water model have been established and integrated to support water management. This has enhanced the benefits of using groundwater models. Based on insight gained from this Danish experience, a scientifically realistic scenario for the use of groundwater modeling in 2020 has been developed, in which groundwater models will be a part of sophisticated databases and modeling systems. The databases and numerical models will be seamlessly integrated, and the tasks of monitoring and modeling will be merged. Numerical models for atmospheric, surface water, and groundwater processes will be coupled in one integrated modeling system that can operate at a wide range of spatial scales. Furthermore, the management systems will be constructed with a focus on building credibility of model and data use among all stakeholders and on facilitating a learning process whereby data and models, as well as stakeholders' understanding of the system, are updated to currently available information. The key scientific challenges for achieving this are (1) developing new methodologies for integration of statistical and qualitative uncertainty; (2) mapping geological heterogeneity and developing scaling methodologies; (3) developing coupled model codes; and (4) developing integrated information systems, including quality assurance and uncertainty information that facilitate active stakeholder involvement and learning.     

Influence of Fluctuating Groundwater Table on Volatile Organic Chemical Emission Flux at a Dissolved Chlorinated-Solvent Plume Site

Groundwater elevation fluctuation has been recognized as one mechanism causing temporal indoor air volatile organic chemical (VOC) impacts in vapor intrusion risk assessment guidance. For dissolved VOC sources, groundwater table fluctuation shortens/lengthens the transport pathway, and delivers dissolved contaminants to soils that are alternating between water saturated and variably saturated conditions, thereby enhancing volatilization potential. To date, this mechanism has not been assessed with field data, but enhanced VOC emission flux has been observed in lab-scale and modeling studies. This work evaluates the impact of groundwater elevation changes on VOC emission flux from a dissolved VOC plume into a house, supplemented with modeling results for cyclic groundwater elevation changes. Indoor air concentrations, air exchange rates, and depth to groundwater (DTW) were collected at the study house during an 86-d constant building underpressurization test. These data were used to calculate changes in trichloroethylene (TCE) emission flux to indoor air, during a period when DTW varied daily and seasonally from about 3.1 to 3.4 m below the building foundation (BF). Overall, TCE flux to indoor air varied by about 50% of the average, without any clear correlation to changes in DTW or its change rate. To complement the field study, TCE surface emission fluxes were simulated using a one-dimensional model (HYDRUS 1D) for conditions similar to the field site. Simulation results showed time-averaged surface TCE fluxes for cyclic water-table elevations were greater than for stationary water-table conditions at an equivalent time-averaged water-table position. The magnitudes of temporal TCE emission flux changes were generally less than 50% of the time-averaged flux, consistent with the field site observations. Simulation results also suggested that TCE emission flux changes due to groundwater fluctuation are likely to be significant at sites with shallow groundwater (e.g., < 0.5 m BF) and permeable soil types (e.g., sand).     

An Open,Object-Based Framework for Generating Anisotropy in Sedimentary Subsurface Models

The spatial distribution of hydraulic properties in the subsurface controls groundwater flow and solute transport. However, many approaches to modeling these distributions do not produce geologically realistic results and/or do not model the anisotropy of hydraulic conductivity caused by bedding structures in sedimentary deposits. We have developed a flexible object-based package for simulating hydraulic properties in the subsurface—the Hydrogeological Virtual Realities (HyVR) simulation package. This implements a hierarchical modeling framework that takes into account geological rules about stratigraphic bounding surfaces and the geometry of specific sedimentary structures to generate realistic aquifer models, including full hydraulic-conductivity tensors. The HyVR simulation package can create outputs suitable for standard groundwater modeling tools (e.g., MODFLOW), is written in Python, an open-source programming language, and is openly available at an online repository. This paper presents an overview of the underlying modeling principles and computational methods, as well as an example simulation based on the Macrodispersion Experiment site in Columbus, Mississippi. Our simulation package can currently simulate porous media that mimic geological conceptual models in fluvial depositional environments, and that include fine-scale heterogeneity in distributed hydraulic parameter fields. The simulation results allow qualitative geological conceptual models to be converted into digital subsurface models that can be used in quantitative numerical flow-and-transport simulations, with the aim of improving our understanding of the influence of geological realism on groundwater flow and solute transport.     

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variable's correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot‐North (TEAD‐N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF‐based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well‐calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging‐based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation.     

The New Potential for Understanding Groundwater Contaminant Transport

The groundwater remediation field has been changing constantly since it first emerged in the 1970s. The remediation field has evolved from a dissolved‐phase centric conceptual model to a DNAPL‐dominated one, which is now being questioned due to a renewed appreciation of matrix diffusion effects on remediation. Detailed observations about contaminant transport have emerged from the remediation field, and challenge the validity of one of the mainstays of the groundwater solute transport modeling world: the concept of mechanical dispersion (Payne et al. 2008). We review and discuss how a new conceptual model of contaminant transport based on diffusion (the usurper) may topple the well‐established position of mechanical dispersion (the status quo) that is commonly used in almost every groundwater contaminant transport model, and evaluate the status of existing models and modeling studies that were conducted using advection‐dispersion models.     

Identifying the flow pattern and natural recharge at a strategic groundwater resource in the Dornogobi Province,Mongolia

The strategic project of economic development in the Dornogobi Province in Mongolia is dependent on water supply. Thus a comprehensive hydrogeological characterization was focused on the Upper Cretaceous multi-aquifer system north of Sainshand city. A conceptual model was developed to discover the groundwater flow pattern essential to correct the setting of the numerical model of groundwater flow created using MODFLOW to assess the natural recharge of the aquifer. The conceptualization was based on geological and hydrogeological characterization. However, the evaluation of hydrochemistry proved to be the key factor revealing the principal feature of the groundwater flow pattern, which is the presence of preferential flow zones. These zones allow for intensive transfer of relatively fresh Na(Mg,Ca)?HCO₃-dominated groundwater into discharge areas, where it leaks into the Quaternary aquifer. The numerical model suggested an enormous natural recharge of 22 100 m³/d, originating in 64% of the preferential flow zones.     

Groundwater remediation: the next 30 years

Groundwater remediation technologies are designed, installed, and operated based on the conceptual models of contaminant hydrogeology that are accepted at that time. However, conceptual models of remediation can change as new research, new technologies, and new performance data become available. Over the past few years, results from multiple-site remediation performance studies have shown that achieving drinking water standards (i.e., Maximum Contaminant Levels, MCLs) at contaminated groundwater sites is very difficult. Recent groundwater research has shown that the process of matrix diffusion is one key constraint. New developments, such as mass discharge, orders of magnitude (OoMs), and SMART objectives are now being discussed more frequently by the groundwater remediation community. In this paper, the authors provide their perspectives on the existing "reach MCLs" approach that has historically guided groundwater remediation projects, and advocate a new approach built around the concepts of OoMs and mass discharge.     

Modeling surface water–groundwater interaction in New Zealand: Model development and application

Most rivers worldwide have a strong interaction with groundwater when they leave the mountains and flow over alluvial plains before flowing into the seas or disappearing in the deserts, and in New Zealand, typically, rivers lose water to the groundwater in the upper plains and generally gain water from the groundwater in the lower plains. Aiming at simulating surface water–groundwater interaction nationally in New Zealand, we developed a conceptual groundwater module for the national hydrologic model TopNet to simulate surface water–groundwater interaction, groundwater flow, and intercatchment groundwater flow. The developed model was applied to the Pareora catchment in South Island of New Zealand, where there are concurrent spot gauged flows. Results show that the model simulations not only fit quite well to flow measurement but also to concurrent spot gauged flows, and compared to the original TopNet, it has a significant improvement in the low flows. Sensitivity analysis shows river flow is sensitive to the river losing/gaining rate instead of groundwater characteristic, while groundwater storage is sensitive to both river losing/gaining rate and groundwater characteristic. This indicates our conceptual approach is promising for nationwide modeling without the large amount of geology and aquifer data typically required by physically‐based modeling approaches.     

A hybrid framework for improving recharge and discharge estimation for a three-dimensional groundwater flow model

We employed the ArcGIS plug-in package PRO-GRADE (Lin et al. 2009), developed for zonation of recharge/discharge (R/D) for modeling two-dimensional aquifer systems, to develop alternative R/D zonations for an existing three-dimensional groundwater flow model of a complex hydrogeologic setting. Our process began by intersecting PRO-GRADE output with the existing model's 4-zone R/D representation to develop a model having 12 R/D zones (R12) and then calibrating the resulting model using PEST. We then revised the R12 zonation using supplementary GIS data to develop a 51-zone R/D zonation (R51). From R51, we developed a series of daughter models having 40, 30, 28, and 18 R/D zones by removing zones from R51 if calibration resulted in little change in the zone's starting R/D rate and/or if the model was insensitive to the zone's R/D rate. For these models (R40N, R30N, R28N, and R18N), we used the ArcGIS Nibble tool to rapidly and consistently reassign model cells within eliminated zones of R51 to the zone of the nearest model cell in a retained zone having the same starting value. R12, R51, R40N, R30N, R28N, and R18N are all more accurate than the original model (R4), although improvements relative to stream discharge targets exceeded improvements relative to head targets. The models also executed with better numerical stability and less mass balance discrepancy than R4. These improvements demonstrate that R/D estimation in a complex shallow three-dimensional steady-state model can be improved with PRO-GRADE estimates of R/D when guided by calibration statistics and supplemental geographic data.     

Complexity vs. Simplicity: Groundwater Model Ranking Using Information Criteria

A groundwater model characterized by a lack of field data about hydraulic model parameters and boundary conditions combined with many observation data sets for calibration purpose was investigated concerning model uncertainty. Seven different conceptual models with a stepwise increase from 0 to 30 adjustable parameters were calibrated using PEST. Residuals, sensitivities, the Akaike information criterion (AIC and AICc), Bayesian information criterion (BIC), and Kashyap's information criterion (KIC) were calculated for a set of seven inverse calibrated models with increasing complexity. Finally, the likelihood of each model was computed. Comparing only residuals of the different conceptual models leads to an overparameterization and certainty loss in the conceptual model approach. The model employing only uncalibrated hydraulic parameters, estimated from sedimentological information, obtained the worst AIC, BIC, and KIC values. Using only sedimentological data to derive hydraulic parameters introduces a systematic error into the simulation results and cannot be recommended for generating a valuable model. For numerical investigations with high numbers of calibration data the BIC and KIC select as optimal a simpler model than the AIC. The model with 15 adjusted parameters was evaluated by AIC as the best option and obtained a likelihood of 98%. The AIC disregards the potential model structure error and the selection of the KIC is, therefore, more appropriate. Sensitivities to piezometric heads were highest for the model with only five adjustable parameters and sensitivity coefficients were directly influenced by the changes in extracted groundwater volumes.     

A Tracer Test to Characterize Treatment of TCE in a Permeable Reactive Barrier

A tracer test was conducted to characterize the flow of groundwater across a permeable reactive barrier constructed with plant mulch (a biowall) at the OU‐1 site on Altus Air Force Base, Oklahoma. This biowall is intended to intercept and treat groundwater contaminated by trichloroethylene (TCE) in a shallow aquifer. The biowall is 139‐m long, 7.3‐m deep, and 0.5‐m wide. Bromide was injected from an upgradient well into the groundwater as a conservative tracer, and was subsequently observed breaking through in monitoring wells within and downgradient of the biowall. The bromide breakthrough data demonstrate that groundwater entering the biowall migrated across it, following the slope of the local groundwater surface. The average seepage velocity of groundwater was approximately 0.06 m/d. On the basis of the Darcy velocity of groundwater and geometry of the biowall, the average residence time of groundwater in the biowall was estimated at 10 d. Assuming all TCE removal occurred in the biowall, the reduction in TCE concentrations in groundwater across the biowall corresponds to a first‐order attenuation rate constant in the range of 0.38 to 0.15 per d. As an independent estimate of the degradation rate constant, STANMOD software was used to fit curves through data on the breakthrough of bromide and TCE in selected wells downgradient of the injection wells. Best fits to the data required a first‐order degradation rate constant for TCE removal in the range of 0.13 to 0.17 per d. The approach used in this study provides an objective evaluation of the remedial performance of the biowall that can provide a basis for design of other biowalls that are intended to remediate TCE‐contaminated groundwater.     

A hybrid artificial neural network-numerical model for ground water problems

Numerical models constitute the most advanced physical-based methods for modeling complex ground water systems. Spatial and/or temporal variability of aquifer parameters, boundary conditions, and initial conditions (for transient simulations) can be assigned across the numerical model domain. While this constitutes a powerful modeling advantage, it also presents the formidable challenge of overcoming parameter uncertainty, which, to date, has not been satisfactorily resolved, inevitably producing model prediction errors. In previous research, artificial neural networks (ANNs), developed with more accessible field data, have achieved excellent predictive accuracy over discrete stress periods at site-specific field locations in complex ground water systems. In an effort to combine the relative advantages of numerical models and ANNs, a new modeling paradigm is presented. The ANN models generate accurate predictions for a limited number of field locations. Appending them to a numerical model produces an overdetermined system of equations, which can be solved using a variety of mathematical techniques, potentially yielding more accurate numerical predictions. Mathematical theory and a simple two-dimensional example are presented to overview relevant mathematical and modeling issues. Two of the three methods for solving the overdetermined system achieved an overall improvement in numerical model accuracy for various levels of synthetic ANN errors using relatively few constrained head values (i.e., cells), which, while demonstrating promise, requires further research. This hybrid approach is not limited to ANN technology; it can be used with other approaches for improving numerical model predictions, such as regression or support vector machines (SVMs).     

Predicting Aquifer Response Time for Application in Catchment Modeling

It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land‐use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land‐use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site‐specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data‐scarce catchments.     

Bioremediation in Fractured Rock: 1. Modeling to Inform Design,Monitoring, and Expectations

Field characterization of a trichloroethene (TCE) source area in fractured mudstones produced a detailed understanding of the geology, contaminant distribution in fractures and the rock matrix, and hydraulic and transport properties. Groundwater flow and chemical transport modeling that synthesized the field characterization information proved critical for designing bioremediation of the source area. The planned bioremediation involved injecting emulsified vegetable oil and bacteria to enhance the naturally occurring biodegradation of TCE. The flow and transport modeling showed that injection will spread amendments widely over a zone of lower‐permeability fractures, with long residence times expected because of small velocities after injection and sorption of emulsified vegetable oil onto solids. Amendments transported out of this zone will be diluted by groundwater flux from other areas, limiting bioremediation effectiveness downgradient. At nearby pumping wells, further dilution is expected to make bioremediation effects undetectable in the pumped water. The results emphasize that in fracture‐dominated flow regimes, the extent of injected amendments cannot be conceptualized using simple homogeneous models of groundwater flow commonly adopted to design injections in unconsolidated porous media (e.g., radial diverging or dipole flow regimes). Instead, it is important to synthesize site characterization information using a groundwater flow model that includes discrete features representing high‐ and low‐permeability fractures. This type of model accounts for the highly heterogeneous hydraulic conductivity and groundwater fluxes in fractured‐rock aquifers, and facilitates designing injection strategies that target specific volumes of the aquifer and maximize the distribution of amendments over these volumes.     

Parameter Estimation for Groundwater Models under Uncertain Irrigation Data

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression‐based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least‐squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least‐squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least‐squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.     

A Borehole Test for Chlorinated Solvent Diffusion and Degradation Rates in Sedimentary Rock

We present a new field measurement and numerical interpretation method (combined termed “test”) to parameterize the diffusion of trichloroethene (TCE) and its biodegradation products (DPs) from the matrix of sedimentary rock. The method uses a dual-packer system to interrogate a low-permeability section of the rock matrix adjacent to a previously contaminated borehole and uses the borehole monitoring history to establish the pretest condition. TCE and its DPs are removed from the groundwater between the packers at the onset of the testing. The parameters estimated by fitting a radial diffusion model to the concentration history and borehole concentration data, also termed back diffusion, are the tortuosity factor and sorption coefficients of TCE and DPs in the rock matrix and the TCE and DP biodegradation rate coefficients in the borehole. We demonstrate the equipment design and the interpretive method using a borehole accessing the gray mudstone at a TCE contaminated site in the Newark Basin. In this test, both nonreactive (bromide) and reactive (trichlorofluoroethene) tracers are used to constrain the estimated parameters; however, the bromide tracer was not needed to estimate the parameters in this test. The parameters estimated from the field test are consistent with values measured independently in laboratory experiments using field samples of similar lithology. From the interpretation, we compute the TCE and DP concentration distributions in the rock matrix prior to the test to illustrate how the results can be used to enhance understanding of contaminant distribution in the rock matrix.     

Numerically quantifying the relative importance of topography and buoyancy in driving groundwater flow

Both topography and buoyancy can drive groundwater flow;however,the interactions between them are still poorly understood.In this paper,the authors conduct numerical simulations of variable-density fluid flow and heat transport to quantify their relative importance.The finite element modeling experiments on a 2-D conceptual model reveal that the pattern of groundwater flow depends largely upon the relative magnitude of the flow rate due to topography alone and the flow rate due to buoyancy alone.When fluid ...     

Investigating the effect of complexity on groundwater flow modeling uncertainty

Considering complexity in groundwater modeling can aid in selecting an optimal model, and can avoid over parameterization, model uncertainty, and misleading conclusions. This study was designed to determine the uncertainty arising from model complexity, and to identify how complexity affects model uncertainty. The Ajabshir aquifer, located in East Azerbaijan, Iran, was used for comprehensive hydrogeological studies and modeling. Six unique conceptual models with four different degrees of complexity measured by the number of calibrated model parameters (6, 10, 10, 13, 13 and 15 parameters) were compared and characterized with alternative geological interpretations, recharge estimates and boundary conditions. The models were developed with Model Muse and calibrated using UCODE with the same set of observed data of hydraulic head. Different methods were used to calculate model probability and model weight to explore model complexity, including Bayesian model averaging, model selection criteria, and multicriteria decision-making (MCDM). With the model selection criteria of AIC, AICc and BIC, the simplest model received the highest model probability. The model selection criterion, KIC, and the MCDM method, in addition to considering the quality of model fit between observed and simulated data and the number of calibrated parameters, also consider uncertainty in parameter estimates with a Fisher information matrix. KIC and MCDM selected a model with moderate complexity (10 parameters) and the best parameter estimation (model 3) as the best models, over another model with the same degree of complexity (model 2). The results of these comparisons show that in choosing between models, priority should be given to quality of the data and parameter estimation rather than degree of complexity.     

Consequences of Groundwater-Model Vertical Discretization in Risk-Based Decision-Making

One of the first and most important decisions facing practitioners when constructing a numerical groundwater model is vertical discretization. Several factors will influence this decision, such as the conceptual model of the system and hydrostratigraphy, data availability, resulting computational burden, and the purpose of the modeling analysis. Using a coarse vertical discretization is an attractive option for practitioners because it reduces data requirements and model construction efforts, can increase model stability, and can reduce computational demand. However, using a coarse vertical discretization as a form of model simplification is not without consequence; this may give rise to unwanted side-effects such as biases in decision-relevant simulated outputs. Given its foundational role in the modeled representation of the aquifer system, herein we investigate how vertical discretization may affect decision-relevant simulated outputs using a paired complex-simple model analysis. A Bayesian framework and decision analysis approach are adopted. Two case studies are considered, one of a synthetic, linked unsaturated-zone/surface-water/groundwater hydrologic model and one of a real-world linked surface-water/groundwater hydrologic-nitrate transport model. With these models, we analyze decisions related to abstraction-induced changes in ecologically important streamflow characteristics and differences in groundwater and surface-water nitrate concentrations and mass loads following potential land-use change. We show that for some decision-relevant simulated outputs, coarse vertical discretization induces bias in important simulated outputs, and can lead to incorrect resource management action. For others, a coarse vertical discretization has little or no consequence for resource management decision-making.     

Modelling of the groundwater flow and of tracer movement in the porous and fissured media: Chalk Aquifer (Northern part of Paris Basin,France)

A groundwater flow model has been developed in order to study the chalk aquifer of Paris Basin, based on most of the geological and hydrological available data. The numerical processes are intended to modelling the groundwater flow in the Senonian (Late Cretaceous) formations and to visualize the tracer movement in groundwater resources in the experimental site of LaSalle Beauvais (northern part Paris Basin). Both objectives were achieved as follows: (i) the comprehension of the spatial distribution of the hydraulic conductivity in the chalk aquifer taking into account the characteristics of the hydrogeological system and (ii) the use of the analytical solution for describing one‐dimensional to two‐dimensional solute transport in a unidirectional steady‐state flow tracer with scale‐dependent dispersion. Advection and diffusion mechanisms are taken into account. Comparison between the breakthrough curves of the analytical and the numerical solutions provided an excellent agreement for various ranges of scale‐related transport parameters of interest. The developed power series solution facilitates fast prediction of the breakthrough curves at each observation point. Thus, the derived new solutions are widely applicable and are very useful for the validation of numerical transport. The numerical approach is carried out by MT3DMS, a Modular 3‐D Multi‐Species Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems, and based on total variation‐diminishing method using the ULTIMATE algorithm. The estimation of the infected surface could constitute an approach in water management and allows to prevent the risks of pollution and to manage the groundwater resource from a durable development perspective. Copyright © 2016 John Wiley & Sons, Ltd.