Cost-effective network design for groundwater flow monitoring

The extensive use of groundwater resources has increased the need for developing cost-effective monitoring networks to provide an indication of the degree to which the subsurface environment has been affected by human activities. This study presents a cost-effective approach to the design of groundwater flow monitoring networks. The groundwater network design is formulated with two problem formats: maximizing the statistical monitoring power for specified budget constraint and minimizing monitoring cost for statistical power requirement. The statistical monitoring power constraint is introduced with an information reliability threshold value. A branch and bound technique is employed to select the optimal solution from a discrete set of possible network alternatives. The method is tested to the design of groundwater flow monitoring problem in the Pomona County, California.

[1]  Dennis P. Lettenmaier Dimensionality problems in water quality network design , 1979 .

[2]  Nien-Sheng Hsu,et al.  Optimum experimental design for parameter identification in groundwater hydrology , 1989 .

[3]  Groundwater Monitoring Network: Analysis And Design , 1989 .

[4]  R. Ababou,et al.  Three-dimensional flow in random porous media , 1988 .

[5]  M. Mariño,et al.  The inverse problem for confined aquifer flow: Identification and estimation with extensions , 1987 .

[6]  R. Willis,et al.  Groundwater Systems Planning and Management , 1987 .

[7]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[8]  F. C. van Geer,et al.  Applications of Kalman filtering in the analysis and design of groundwater monitoring networks , 1987 .

[9]  Marshall E. Moss,et al.  Cost effective stream-gaging strategies for the Lower Colorado River basin; the Blythe field office operations , 1980 .

[10]  Chao-Lin Chiu,et al.  Applications of Kalman filter to hydrology, hydraulics, and water resources : proceedings of AGU Chapman Conference, held at University of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A., May 22-24, 1978 , 1978 .

[11]  E. D. Brill,et al.  A method for locating wells in a groundwater monitoring network under conditions of uncertainty , 1988 .

[12]  F. Szidarovszky,et al.  A method for optimal observation network design for groundwater management , 1984 .

[13]  L. Townley,et al.  Computationally Efficient Algorithms for Parameter Estimation and Uncertainty Propagation in Numerical Models of Groundwater Flow , 1985 .

[14]  E. Sudicky A natural gradient experiment on solute transport in a sand aquifer: Spatial variability of hydraulic conductivity and its role in the dispersion process , 1986 .

[15]  H. Loáiciga An optimization approach for groundwater quality monitoring network design , 1989 .

[16]  S. Rouhani Variance Reduction Analysis , 1985 .

[17]  Richard N. Palmer,et al.  Optimization of Water Quality Monitoring Networks , 1985 .

[18]  Marshall E. Moss,et al.  Space, time, and the third dimension (model error) , 1979 .

[19]  Ferenc Szidarovszky,et al.  Multiobjective observation network design for regionalized variables , 1983 .

[20]  R. Fletcher Practical Methods of Optimization , 1988 .

[21]  Joel Massmann,et al.  Groundwater contamination from waste management sites: The interaction between risk‐based engineering design and regulatory policy: 1. Methodology , 1987 .

[22]  Peter K. Kitanidis,et al.  Analysis of the Spatial Structure of Properties of Selected Aquifers , 1985 .