Book contents
- Frontmatter
- Contents
- List of Contributors
- 1 Introduction
- 2 Integrated regional risk assessment and safety management: Challenge from Agenda 21
- 3 Risk analysis: The unbearable cleverness of bluffing
- 4 Aspects of uncertainty, reliability, and risk in flood forecasting systems incorporating weather radar
- 5 Probabilistic hydrometeorological forecasting
- 6 Flood risk management: Risk cartography for objective negotiations
- 7 Responses to the variability and increasing uncertainty of climate in Australia
- 8 Developing an indicator of a community's disaster risk awareness
- 9 Determination of capture zones of wells by Monte Carlo simulation
- 10 Controlling three levels of uncertainties for ecological risk models
- 11 Stochastic precipitation-runoff modeling for water yield from a semi-arid forested watershed
- 12 Regional assessment of the impact of climate change on the yield of water supply systems
- 13 Hydrological risk under nonstationary conditions changing hydroclimatological input
- 14 Fuzzy compromise approach to water resources systems planning under uncertainty
- 15 System and component uncertainties in water resources
- 16 Managing water quality under uncertainty: Application of a new stochastic branch and bound method
- 17 Uncertainty in risk analysis of water resources systems under climate change
- 18 Risk and reliability in water resources management: Theory and practice
- 19 Quantifying system sustainability using multiple risk criteria
- 20 Irreversibility and sustainability in water resources systems
- 21 Future of reservoirs and their management criteria
- 22 Performance criteria for multiunit reservoir operation and water allocation problems
- 23 Risk management for hydraulic systems under hydrological loads
9 - Determination of capture zones of wells by Monte Carlo simulation
Published online by Cambridge University Press: 18 January 2010
- Frontmatter
- Contents
- List of Contributors
- 1 Introduction
- 2 Integrated regional risk assessment and safety management: Challenge from Agenda 21
- 3 Risk analysis: The unbearable cleverness of bluffing
- 4 Aspects of uncertainty, reliability, and risk in flood forecasting systems incorporating weather radar
- 5 Probabilistic hydrometeorological forecasting
- 6 Flood risk management: Risk cartography for objective negotiations
- 7 Responses to the variability and increasing uncertainty of climate in Australia
- 8 Developing an indicator of a community's disaster risk awareness
- 9 Determination of capture zones of wells by Monte Carlo simulation
- 10 Controlling three levels of uncertainties for ecological risk models
- 11 Stochastic precipitation-runoff modeling for water yield from a semi-arid forested watershed
- 12 Regional assessment of the impact of climate change on the yield of water supply systems
- 13 Hydrological risk under nonstationary conditions changing hydroclimatological input
- 14 Fuzzy compromise approach to water resources systems planning under uncertainty
- 15 System and component uncertainties in water resources
- 16 Managing water quality under uncertainty: Application of a new stochastic branch and bound method
- 17 Uncertainty in risk analysis of water resources systems under climate change
- 18 Risk and reliability in water resources management: Theory and practice
- 19 Quantifying system sustainability using multiple risk criteria
- 20 Irreversibility and sustainability in water resources systems
- 21 Future of reservoirs and their management criteria
- 22 Performance criteria for multiunit reservoir operation and water allocation problems
- 23 Risk management for hydraulic systems under hydrological loads
Summary
ABSTRACT
Effective protection of a drinking water well against pollution by persistent compounds requires the knowledge of the well's capture zone. This zone can be computed by means of groundwater flow models. However, because the accuracy and uniqueness of such models is very limited, the outcome of a deterministic modeling exercise may be unreliable. In this case stochastic modeling may present an alternative to delimit the possible extension of the capture zone. In a simplified example two methods are compared: the unconditional and the conditional Monte Carlo simulation. In each case realizations of an aquifer characterized by a recharge rate and a transmissivity value are produced. By superposition of capture zones from each realization, a probability distribution can be constructed which indicates for each point on the ground surface the probability to belong to the capture zone. The conditioning with measured heads may both shift the mean and narrow the width of this distribution. The method is applied to the more complex example of a zoned aquifer. Starting from an unconditional simulation with recharge rates and transmissivities randomly sampled from given intervals, observation data of heads are successively added. The transmissivities in zones that do not contain head data are generated stochastically within boundaries typical for the zone, while the remaining zonal transmissivities are now determined in each realization through inverse modeling. With a growing number of conditioning data the probability distribution of the capture zones is shown to narrow. The approach also allows the quantification of the value of data. Data are the more valuable the larger the decrease of uncertainty they lead to.
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- Publisher: Cambridge University PressPrint publication year: 2002