Optimal design of a groundwater monitoring network in Daqing, China

Abstract

In the Daqing region of China there are 34 groundwater well fields with a groundwater withdrawal of 81.9×104 m3/d. Due to over-abstraction of the groundwater resources from the 1960s to present, a cone of depression up to 4,000 km2 has formed in the area. To monitor the change in the groundwater environment, it is necessary to design an effective groundwater-monitoring network. The sites for monitoring groundwater level were selected by applying the finite-element method coupled with Kalman filtering to the area in which the groundwater resources have been extensively exploited. The criterion is a threshold value of the standard deviation of estimation error. This threshold value is determined by the tradeoff between maximum information and minimum cost, in which the maximum information is characterized by the standard deviation and the minimum cost is equivalent to the number of observation wells. The groundwater flow model was calibrated by an optimal algorithm coupled the finite-element method with Kalman filtering by using the data from 16 observation wells from 1986 to 1993. A simulation algorithm coupled with the finite-element method with Kalman filtering analyzed the location data obtained from the existing 38 observation wells in the same region. The spatial distribution of standard deviation of estimation error is computed and the locations that have the maximum standard deviation are selected as additional sites for augmenting the existing observational well network at a given threshold value of the standard deviation surface. Based on the proposed method for selecting a groundwater level monitoring network, an optimal monitoring network with 88 observation wells with the measurement frequency of 12 times per year is selected in the Daqing region of China.