An Innovative Approach to Determination of Double-Porosity Fractured Aquifers Hydraulic Parameters Using Artificial Neural Network

Accurate determination of hydraulic parameter values is the first step to the sustainable development of an aquifer. Since Theis (1935), type curve matching technique (TCMT) has been used to estimate the aquifer parameters from pumping test data. The TCMT is subjected to graphical error. To eliminate the error an Artificial Neural Network (ANN) is developed as an alternative to the conventional TCMT by modeling the Bourdet-Gringaten’s well function for the determination of the fractured double porosity aquifer parameters. The neural network model is developed in a six-step protocol based on multi-layer perceptron (MLP) networks architecture and is trained for the well function of double porosity aquifers by the back propagation method and the Levenberg-Marquardt optimization algorithm. By applying the principal component analysis on the training input data and through a trial-and-error procedure the optimum structure of the network is fixed with the topology of [3×6×3]. The replicative, predictive and structural validity of the developed network are evaluated with synthetic and real field data. The developed network provides an automatic and fast procedure for the double porosity aquifer parameter determination that eliminates graphical errors inherent in the conventional TCMT. The network receives pumping test data and provides the user with the aquifer parameter values.

Approximation of Subsurface Seepage using 2- Dimensional Boussineq Equation

Groundwater is the main source of fresh water available for human beings. The surface water groundwater interaction affects the quantity and quality of groundwater. Hence the study of surfacewater-groundwater interaction is the emerging topic in this new era. In this paper, the analytical approximation of water table fluctuation in the aquifer is presented. The aquifer is subjected to the recharge and withdrawal activity through multiple basins and wells in the domain. The time dependent multiple recharge is considered. The flow is approximated by a non linear partial differential equation called Boussineq equation. The solution of Boussineq equation is developed using Finite Fourier cosine transform. Response of the solution to using numerical examples has been tested. Effect of aquifer parameters on the fluctuation of water table formation mainly water mound and cone of depression due to recharge and withdrawal are presented. The effect of permeability of aquifer base on the water table is also discussed.

Numerical Modeling of Water Table Fluctuation in Unconfined Sloping Aquifer in Response to Multiple Localized Recharge

Numerical modeling for the variations of water table fluctuation in response to subsurface seepage and downwards recharge is an important aspect in the estimation of surface-groundwater interaction. In this work, a numerical model is developed for the approximation of water table variation in an unconfined sloping aquifer subjected to the multiple localized recharge and seepage from the adjacent water body. The Boussinesq equation characterizing the flow of groundwater in unconfined sloping porous media is solved numerically using Du Fort Frankel finite difference method. The application of the result is demonstrated with illustrative examples using varying aquifer parameters. The results indicated that the water table form groundwater mound beneath recharge basins due to continuous recharge.

Analysis of Pressure Response at an Observation Well against Pressure Build-Up by Early Stage of CO2 Geological Storage Project

To ensure a safe and stable CO2 storage, pressure responses at an observation well is expected to be an important and useful field monitoring items to estimate the CO2 storage behaviors and the aquifer parameters during and after injecting CO2, because it can detect whether the injected CO2 leaks to the ground surface or the bottom of the sea. In this study, pressure responses were simulated to present design factors such as well location and pressure transmitter of the observation well. Numerical simulations on the pressure response and the time-delay from pressure build-up after CO2 injection were conducted by considering aquifer parameters and distance from the CO2 injection well to an observation well. The measurement resolution of a pressure transmitter installed in the observation well was presented based on numerical simulation results of the pressure response against pressure build-up at the injection well and CO2 plume front propagations. Furthermore, the pressure response at an observation well was estimated by comparing the numerical simulation results with the curve of CO2 saturation and relative permeability. It was also suggested that the analytical solution can be used for the analysis of the pressure response tendency using pressure build-up and dimensionless parameters of hydraulic diffusivity. Thus, a criterion was established for selecting a pressure transducer installed at an observation well to monitor the pressure responses with sufficient accuracy and resolution, considering the distance from the injection well and the pressure build-up at the injection well, for future CCS projects.

Estimating cumulative catchment streamflow depletion from abstractions

<p>Abstraction from surface and groundwater bodies alters river flow regimes. The economic and social benefits of abstraction need to be balanced against their consequences for hydrology dependent ecological functions, ecosystem services, cultural values and recreation. However, impacts of an abstraction on flow regimes are often assessed in isolation and so cumulative impacts of many spatially distributed abstractions on the catchment are not understood. While spatially distributed, high-resolution model(s) (e.g. MODFLOW) can be developed to understand the cumulative impacts of abstractions, this is cost prohibitive and the demand for data is high (e.g., system properties, hydroclimatic) to develop such a model at regional scales and, further, such site specific models cannot be transferred to other spatial locations. We have developed a model to estimate cumulative streamflow depletion at given locations of a stream network resulting from both surface and groundwater abstractions. The surface water abstractions directly deplete the nearest river segment with which the abstraction is associated. However, depletion owing to each groundwater take, response times of which can extend to weeks, months or even years following the abstractions, was associated with all river segments which were within a 2 km radius of the groundwater take. The proportion of depletion from each river segment owing to a groundwater take is dependent on distance between well and segment, flow (based on the naturalised 7-day mean annual low flow) and length of the segment within 2 km radius of the well. Two aquifer parameters (transmissivity and storativity) are used for calculating the streamflow depletion. Field tests can be used to measure these parameters but observations are not available for all necessary locations. We used Random Forest statistical techniques to estimate the aquifer parameters at unmeasured locations. Results of the streamflow depletion model are displayed using an interactive application (app). The model can be used to obtain timeseries of cumulative stream depletion at any location in the river network from many spatially distributed abstractions.</p>