Determination of capture zones of wells by Monte Carlo simulation

Capture zones of wells play an important role in groundwater protection especially with respect to persistent chemicals and nitrate introduced by agriculture. While wellhead protection zones based on the 50-day isochrone are relevant for protection against bacterial pollution the whole capture zone must be included in the protection zone if persistent chemicals are considered. Generally, the shape and size of a catchment zone cannot be determined exactly due to inherent uncertainty of aquifer and recharge parameters. therefore a stochastic method is used. 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 which 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 modelling. 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. By reducing the size of the zones of equal parameter values it is seen that the aquifer can be replaced by a homogeneous one if zones become small against the typical dimensions of the capture zone. The need for identification of large scale features is stressed.