Export contour lines, modified the grid export routine, in order to have real-world X,Y,Z. The statistics report may be saved to a text (.TXT) or Excel (.XLS) file, copied to the clipboard, or printed as is. Drawdown estimation - Drawdowns from pumping can be differentiated from natural water-level fluctuations with water-level modeling in SeriesSEE, a Microsoft ® Excel add-in with utilities for viewing, cleaning, manipulating, and analyzing time-series data. Hantush-Bierschenk (1964): step drawdown test, analysis of well losses.Slug testing - Estimate hydraulic conductivity from slug tests with Bouwer and Rice ( 1976) or KGS models ( Butler and Garnett, 2000).Jacob-Lohman - Estimate transmissivity from declining discharge of a flowing well. Abstract A summary with real data analysis, particularly for the ordinary situation, especially looking for the effect of iron bacteria, clogging and failure.Distance-drawdown - Estimate transmissivity from multi-well aquifer test under confined or unconfined conditions.for flowing wells in a confined aquifer, and the step-drawdown test. Step drawdown - Estimate transmissivity and well-loss coefficients from step drawdown data. These spreadsheets were written in Microsoft Excel 9.0 (use of trade names does not.Cooper-Jacob pumping and recovery - Simultaneously analyze drawdown and residual drawdowns to estimate transmissivity from a single-well aquifer test.Hydrology functions -A collection of basic math functions in Excel VBA that were developed by Bruce Hunt ( Hunt, 2005).PLISM - Pit Lake Iterative Simulation Model simulates pit lake formation.Distance-drawdown - Theis solution for estimating drawdown at distances from a pumping well.Analytical-Engine INTERFACE - A macro for automatically processing data in an Excel application.Tools exist for all listed items but explanatory text has not been written. Tool and explanation exists where tool name is highlighted and hyperlinked to explanatory page. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANNPSO model is capable of identifying the optimal location of wells efficiently.Excel workbooks and FORTRAN based tools for hydrologic analysis that I have developed over the years are available from this page. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The discharge and location of the pumpingwells were taken as the decision variable and theANN-PSOmodel was applied to find out the optimal location of the wells. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. It can be concluded that GA is a helpful tool for automatic calibration of variable density fluid systems such as seawater intrusion cases. Results show a good match for observed and simulated data. Step-Test Computer Program Bierschenks Multiple Step-Drawdown Test: Example One Bierschenks Multiple Step-Drawdown Test: Example Two Jacob-Walton 3-Step Drawdown Option Kasenows Step-Drawdown Test Option Comparing Bierschenk And Kasenow Solutions Step-Test Example Data. Firstly, flow and transport parameters (hydraulic conductivity, porosity, specific storage coefficient and longitudinal dispersivity) were estimated simultaneously in steady-state and, secondly, in the developed code, these results were used as initial values of the parameters in transient-state. In the last two decades, the overexploitation of groundwater has caused a major water level drawdown and, consequently, salt-water intrusion. The methodology was applied to a coastal aquifer with heterogeneous formations in a semi-arid area near salty Tashk Lake (electrical conductivity 61,420 µS/cm), Fars province, Iran. A simple GA was used to minimize the RMSE criterion. The auto-calibration objective function was defined with the root mean square errors (RMSE) between the observed and the simulated values. Firstly, the SEAWAT code was used for the forward solution part and then a program was written in MATLAB for coupling the forward and inverse processes. Flow and mass transport parameter estimation was done by creating an inverse model of a seawater intrusion system using a genetic algorithm (GA) method as the optimization procedure.
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