A Review on Groundwater Recharge Estimation Using Wetspass Model

Transcription

1 A Review on Groundwater Recharge Estimation Using Wetspass Model Sophia S. Rwanga Abstract Most of the methods used to estimate groundwater recharge are point estimate. However groundwater quantification needs a method which is not only flexible but also reliable in order to accurately quantify its spatial and temporal variability. Groundwater models used for analyzing groundwater systems are often quasi - steady state and, therefore, need long-term average recharge. Thus WetSpass, a methodology for estimating spatially distributed long term average recharge under humid temporal conditions can be used. This model, integrates a water balance in a geographical information system (GIS) environment. This paper provides an overview of the use of WetSpass on the quantification of groundwater recharge. The previous applications are also presented. Keywords Groundwater, Modelling, Recharge, WetSpass I. INTRODUCTION ROUNDWATER is a precious resource of limited extent. GIn order to ensure its judicious use, proper evaluation is required. Groundwater has emerged to be one of the major sources of potable water for various purposes in both urban and rural areas. [4] reported that groundwater is often the only water resource, which is available around the year. This is because; groundwater has the advantage that it is frequently widely available in quantities sufficient to supply the needs of scattered communities. Evaluation of groundwater involves several factors of which, recharge is paramount. Quantification of the recharge rate is a prerequisite for efficient and sustainable management of groundwater [2]. Facing global environmental change including climate change, land use change and eventually adaptation processes, it is essential to assess the impact of all these changes on groundwater recharge and resources [18]. Thus determination of groundwater recharge has shifted from a basic problem to an urgent and fundamental issue in S.S Rwanga is a Lecturer in the Department of Civil Engineering, Vaal University of Technology, Andries Potgieter, private bag X 021, Vanderbijlpark, SE7, 1900 and a Doctoral student in Tshwane University of Technology. Corresponding author sophia.rwanga@yahoo.com, Telephone: hydrogeologic research for sustainable development of groundwater. This is because groundwater recharge estimation constitutes primary key for most approaches used to evaluate and sustainably manage groundwater resources. Most approaches for quantifying groundwater recharge measure it directly or indirectly over a limited area (point or small-basin scale) and for short periods of time [17] Over the past decade there has been a significant increase in the development of distributed hydrological models. Several of these models have been labeled "physically- based" having been parameterized in terms of quantities which, at least in theory, may be physically measurable [15]. [6] Has argued that such models are merely conceptual models as the physically-based quantities are, in fact, oversimplifications of reality and certainly not measurable with current point scale techniques. Despite this, the distributed nature of the current generation of hydrological models is able to exploit new data processing techniques that have the capability of handling detailed variability of catchment characteristics, if only for a subset of model parameters. Spatial variation in recharge due to distributed land-use, soil texture, topography, groundwater level, and hydro meteorological conditions are very important parameters which should be accounted for in recharge estimation. Specifically, a Geographical Information System (G1S) may provide the basic support for many distributed hydrological models. Most of groundwater models used for analyzing groundwater systems (infiltration discharge relations) are often quasi - steady state and, therefore, need long-term average recharge input. Thus WetSpass, which yields spatially varying groundwater recharge using spatially varying meteorological, land use and soil inputs, can be used in conjunction with the groundwater flow simulation model- MODFLOW for the purpose of understanding the characteristics of groundwater flow and the aquifer storage. The purpose of this paper is to provide an overview of the WetSpass model that is currently state-of-the-art for estimation groundwater flow. The focus is estimation of groundwater recharge due to distributed land-use, soil texture, topography, groundwater level, and hydro meteorological conditions. It is intended for readers to have a good understating on the WetSpass model and its applicability. Hence, this method is briefly described and references for further information are given. Further details on the model description, simulation procedures and model application are presented to illustrate the applicability of the model 156

2 II. AN INTRODUCTION TO WETSPASS WetSpass stands for Water and Energy Transfer between Soil, Plants and Atmosphere under quasi-steady State [10]. It is a physically based model for the estimation of long-term average spatial patterns of groundwater recharge, surface runoff and evapotranspiration employing physical and empirical relationships. Regional groundwater models used for analyzing recharge-discharge relations are often quasi-steady and need long-term average recharge input that accounts for the spatial variability of the recharge. A. Model Description The total water balance for a raster cell (Figure. 1) is split into independent water balances for the vegetated, bare-soil, open-water and impervious parts of each cell. This allows one to account for the non-uniformity of the land-use per cell, which is dependent on the resolution of the raster cell. The processes in each part of a cell are set in a cascading way. This means that an order of occurrence of the processes, after the precipitation event, is assumed. Defining such an order is a prerequisite for the seasonal timescale with which the processes will be quantified. The quantity determined for each process is consequently limited by a number of constraints. Precipitation is taken as the starting point for the computation of the water balance of each of the above mentioned components of a raster cell, the rest of the processes (interception, runoff, evapotranspiration, and recharge) follow in an orderly manner. C. Vegetated area The water balance for a vegetated area depends on the average seasonal precipitation (P), interception fraction (I), surface runoff (Sv), actual transpiration (Tv), and groundwater recharge (Rv) all with the unit of [LT -1 ], with the relation given below P = I + S v + T V + R v (4) D. Surface runoff Surface runoff is calculated in relation to precipitation amount, precipitation intensity, interception and soil infiltration capacity. Initially the potential surface runoff (S v - pot) is calculated as S v pot = C sv (P I) (5) Where, C sv is a surface runoff coefficient for vegetated infiltration areas, and is a function of vegetation, soil type and slope. In the second step, actual surface runoff is calculated from the Sv-pot by considering the differences in precipitation intensities in relation to soil infiltration capacities. S v = C Hor S v pot (6) Where C Hor is a coefficient for parameterizing that forms part of a seasonal precipitation contributing to the Hortonian overland flow. C Hor for groundwater discharge areas is equal to 1.0 since all intensities of precipitation contribute to surface runoff. Only high intensity storms can generate surface runoff in infiltration areas. E. Evapotranspiration For the calculation of seasonal evapotranspiration, a reference value of transpiration is obtained from open-water evaporation and a vegetation coefficient: T rv = ce o (7) Fig.1 Schematic water balance of a hypothetical raster cell (10) B. WetSpass: Water balance calculation The water balance components of vegetated, bare-soil, openwater, and impervious surfaces are used to calculate the total water balance of a raster cell as follows:, ET raster = avet v + ase s + aoe o + aie i (1) S raster = avs v + ass s + aos o + ais i (2) R raster = avr v + asr s + aor o + air i (3) Where ET raster, S raster, R raster are the total evapotranspiration, surface runoff, and groundwater recharge of a raster cell respectively, each having a vegetated, bare-soil, open-water and impervious area component denoted by av, as, ao, and ai, respectively. T rv = the reference transpiration of a vegetated surface [LT - 1 ]; E o = potential evaporation of open water [LT -1 ] and c= vegetation coefficient [ ]. This vegetation coefficient can be calculated as the ratio of reference vegetation transpiration as given by the Penman- Monteith equation to the potential open-water evaporation, as given by the Penman equation: C = 1+ γ 1+ γ 1+r c ra (8) γ = psychrometric constant [ML -1 T -2 C -1 ]; Δ = slope of the first derivative of the saturated vapor pressure curve (slope of saturation vapor pressure at the prevailing air temperature) [ML -1 T -2 C -1 ]; r c = canopy resistance [TL -1 ] and r a = aerodynamic resistance [TL -1 ] given by; r a = 1 k 2 ua ln z a d z0 2 (9) 157

3 International Conference on Civil and Environmental Engineering (CEE'2013) Nov , 2013 Johannesburg (South Africa) k is the Von Karman constant (0.4) [ ]; u a is the wind speed [LT -1 ] at measurement level z a = 2m; d is the zero-plane displacement length [L] and z o is the roughness length for the vegetation or soil [L].For vegetated groundwater discharge areas, the actual transpiration (Tv) is equal to the reference transpiration as there is no soil or water availability limitation: T v = T rv if (G d h t ) R d (10) G d, is groundwater depth [L]; h t is the tension saturated height [L] and R d is the rooting depth [L]. For vegetated areas where the groundwater level is below the root zone the actual transpiration is given by: T v = f(θ)t rv if (G d h t ) > R d (11) f(θ) is a function of the water content and for a time variant situation it is defined as f(θ) = (1 a 1 ) w/trv (12) with w = P + (θ fc θ pwp )R d (13) a 1 is a calibrated parameter related to the sand content of a soil type [-]; w is the available water for transpiration [LT -1 ] and θ fc - θ pwp is the plant available water content [T -1 ] per time step, stated as the difference in water content at field capacity and at permanent wilting point. F. Recharge The last component, the groundwater recharge, is then calculated as a residual term of the water balance, i.e, R v = P S v ET v E s I (14) ET v is the actual evapotranspiration [LT -1 ] given as the sum of transpiration T v and E s (the evaporation from bare soil found in between the vegetation). The spatially distributed recharge is therefore estimated from the vegetation type, soil type, slope, groundwater depth, and climatic variables of precipitation, potential evapotranspiration, temperature, and wind-speed. WetSpass recharge outputs can be used as an input for the groundwater model like MODFLOW. MODFLOW is an extremely versatile finite-difference groundwater model that simulates three-dimensional groundwater flow through a porous medium [9]. It was designed to have a modular structure that facilitates ease of understanding and ease of enhancing. S s = h t = x K xx h x + y K h xx y + z K h xx z W.. (15) Kxx, Kyy and Kzz hydraulic conductivity along the x, y and z coordinate axes, which are assumed to be parallel to the major axes of hydraulic conductivity [LT -1 ]; h: the potentiometric head [L]; W: volumetric flux per unit volume, representing sources and/or sinks of water [L 3 T -1 ]; Ss: the specific storage of the porous material [L -1 ]; t: time [T]. Solution of the equation is obtained by using a block centered finite-difference approximation. Equation (15) when combined with boundary and initial conditions describes transient flow in a heterogeneous and anisotropic medium provided that the principal axes of hydraulic conductivity are aligned with the coordinate directions. For steady state conditions the term on the right hand side of the equation reduces to zero. The flow regime is represented by blocks made of grids (plan view) and layers (side view). III. GIS IMPLEMENTATION ON WETSPASS MODEL WetSpass is integrated in the GIS ArcView as a raster model, coded in Avenue. Parameters, such as land-use and related soil type, are connected to the model as attribute tables of the land-use and soil raster maps. This allows an easy definition of new land-use or soil types, as well as changes to parameter values. For the land-use type a land cover maps are used, which should be based on a Landsat 5 classified image with 50 by 50 m resolution. WetSpass in a steady-state groundwater model improves the prediction of the simulated groundwater level, discharge and recharge areas. In the simulation process groundwater level are used as input to the WetSpass model. This leads to a stable solution for the groundwater level and discharge areas after a few iterations. WetSpass model computes and generates time series of flow hydrographs at selected stations in a recharge areas and maps of spatial outputs. For each map in GIS format are saved at specified time increment, and then used for graphical presentation to see the complete temporal and spatial variation of each variables during a model simulation. A. Input Data WetSpass Input files WetSpass requires a combination of ArcView/ArcInfo grid files and tables (dbf files) as input, which are listed below: TABLE I ARCVIEW/ ARCINFO GRID FILES FOR GIS IMPLEMENTATION ArcView/ ArcInfo Grid files Tables (dbf) Soil Soil parameter Topography Runoff coefficient Slope Land-use parameter (summer and winter) Land use (summer and winter) Temperature (summer and winter) Precipitation (summer and winter) PET*(summer and winter) Wind speed (summer and winter) Groundwater depth* (summer and winter) B. MODFLOW Input file The input files for MODFLOW may vary depending on the version of the model, on the model set up and the user s preference. Nevertheless the common files will include the following: 158

4 International Conference on Civil and Environmental Engineering (CEE'2013) Nov , 2013 Johannesburg (South Africa) TABLE II ASCII INPUT FILES FOR MODFLOW MODEL ASCII files for MODFLOW Recharge Initial head Boundary mask Transmissivity ( or hydraulic and layer thickness) Top layer Bottom layer River or drains Wells C. WetSpass-MODFLOW Simulation Procedures The WetSpass-MODFLOW model starts simulation with one of the two models. Suppose the simulation starts with the WetSpass model (Figure 2), in that case an initial estimate of the groundwater depth is used along with the other WetSpass input grids (landuse type, Soils, Precipitation, Evapotranspiration, and Wind-speed). The resulting spatially distributed groundwater recharge output from the WetSpass run is then used as an input for MODFLOW for a groundwater simulation. From this MODFLOW run a new groundwater depth will be produced, which is then compared with the estimated one and if the difference between them is smaller than a pre-set value by the user, the simulation procedure is stopped. If not, the newly simulated groundwater depth is used as a WetSpass input for the next iteration, and the iterations continue until convergence. Convergence is said to be reached when the changes in computed heads occurring from successive iterations is less than the value specified by the user. Therefore, the model checks for the largest groundwater head changes from all of the cells and compares it with the convergence criterion and determines whether the iteration should continue or not. If the convergence criterion is fulfilled then the groundwater head will be displayed as a theme in the View window of ArcView interface. If not, the dialog shown in Figure 2 is displayed and the user will be asked if he/she wants to run the model again or not. Fig. 2 Processes involved in running the WetSpass and MODFLOW models interactively [13]. IV. PREVIOUS APPLICATIONS ON WETSPASS The research was done at Hasa basin [1] aimed to estimate the water balance components including surface runoff, actual evapotranspiration and groundwater recharge by using Geographical information system (GIS), Remote sensing and land use information together with the WetSpass model in order to come up with the strategies which can be used for environment and socio- economic development. On this research, WetSpass model was used to estimate the long term average spatially varying water balance components. All inputs maps for the model were prepared by aid of ArcView GIS. The model was then simulated on two seasons; summer and winter giving put spatial variations of recharge and runoff as a function of land use and soil type. It was found that, the WetSpass model depends on the soil type and land use classes; hence lack of relevant land use map may lead to the wrong output which could lead to wrong decisions. However the model proven to provide good results provided that an accurate and up to date data are used. Another recent research was done by [8] at Jafr basin in Jordan to estimate groundwater recharge by using GIS based spatial model; WetSpass. In this research both spatially and temporarily variation of recharge was taken into consideration. GIS and remote sensing were the key tools used on this research to accomplish modelling process by WetSpass model. Moreover, results obtained from the WetSpass model were compared with the estimated recharge to groundwater carried out by [3] and [5]. The results demonstrated that the estimation of groundwater recharge using WetSpass is in good agreement with those obtained by other studies. WetSpass was used for the analysis of the effect of landuse changes on the groundwater discharge areas for Grote Nete basin, Belgium [14], [13], [15], [11]. WetSpass recharge outputs for the Dijle, Demer and Nete river basins were used as an input for the groundwater model. Total discharge and surface runoff and base-flow, were used for the calibration of the WetSpass water balance components. The associated groundwater model was also calibrated along with the WetSpass calibration. Again, the resulting groundwater discharge areas were verified by mapped phreatophytes. WetSpass was also used in the analysis of the hydrological characteristics of the Kikbeek sub-basin of the Border Meuse River, Belgium [16]. In the study, fast and slow discharge coefficients were calculated from WetSpass output data as these discharge coefficients were related to the total surface runoff and groundwater recharge respectively. By using the WetSpass model of the actual hydrological situation in the Kikbeek sub-basin as a starting point, the sensitivity of the discharge coefficients of the Kikbeek sub-basin towards climate and landuse changes was analyzed. Numerous climate and landuse scenarios were used and the geographical input data of the present situation was adjusted for their simulations by WetSpass. Moreover WetSpa model was applied to analyzing the effects of topography, soil type, and land use cover on the runoff characteristics for upper Biebrza catchment [7]. The derivation of parameter maps and analysis of the daily runoff as reaction of the catchment on rainfall was performed. The values for the catchment justified the assessment of the model 159

5 quality measurements as very good. The factors most affecting the process of river outflow formation were determined using the analysis of model sensitivity to relative changes in parameter values. It was found that the evaluation of the model quality depended largely on the quality of meteorological data and proper parameterization of the soil cover. V. CONCLUSION Spatial distribution of recharge is seldom taken into account in groundwater simulations, although poorly parameterized recharge can increase significantly the uncertainty in modeling results and calibration, especially the estimation of the hydraulic conductivity. The developed GIS-based WetSpass methodology is therefore a tool that, in conjunction with a groundwater model, MODFLOW can simulate accurately the spatial distribution of long-term average recharge. The development of the model and the parameter estimation is not the result of an a priori upward physical approach, but rather a downward process, starting from a simple water balance approach, which subsequently evolved by introducing relevant concepts and input data step by step. The model can be used to estimate spatially distributed and long-term average recharge. The estimated distributed recharge through WetSpass can, therefore, be used in regional steady-state groundwater models and, hence, decrease the uncertainty estimation of groundwater recharge. The model gives various hydrological outputs on yearly and seasonal (summer and winter) basis. Even though the model is originally developed mainly to compute the long-term average spatially distributed recharge. It also simulates runoff, evapotranspiration, interception, transpiration, and soil evaporation. The results from the model can be analysed in various ways. The analysis can include; summer and winter output difference, analysis of spatial variations of recharge runoff as a function of land use ad soil type and analysis of evapotranspiration and recharge. Also, Integrating WetSpass and MODFLOW can be used to understand the groundwater flow characteristics that can be used as a decision support system (DSS) for water resource management. The model has successful applied to different parties of the world to account for groundwater recharge estimates. Previous applications showed that, the model can be used to quantify both groundwater recharge and discharge. There is a need to entail the use of WetSpass in semi arid areas where groundwater is vital. [4] H.Wang, L. kgotlhang and W. Kinzelbach, Using remote sensing data to model groundwater recharge potential in Kanye region, Botswana. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008 Vol. 37. Part B8. 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