Optimization for Early-Warning Monitoring Networks in Well Catchments Should Be Multi-objective, Risk-Prioritized and Robust Against Uncertainty

Abstract

Groundwater abstraction wells are commonly protected by zones of restricted land use. Such well protection areas typically cannot cover the entire well catchment, and numerous risk sources remain. Each risk source could release contaminants at any time, affect the well earlier or later, and thus put the quality of supplied water at risk. In this context, it seems fortunate that most well catchments are equipped with monitoring networks. Such networks, however, often grew historically while following diverse purposes that changed with time. Thus, they are often inadequate (or at least suboptimal) as reliable risk control mechanism. We propose to optimize existing or new monitoring networks in a multi-objective setting. The different objectives are minimal costs, maximal reliability in detecting recent or future contaminant spills, and early detection. In a synthetic application scenario, we show that (1) these goals are in fact competing, and a multi-objective analysis is suitable, (2) the optimization should be made robust against predictive uncertainty through scenariobased or Monte Carlo uncertainty analysis, (3) classifying the risk sources (e.g., as severe, medium, almost tolerable) is useful to prioritize the monitoring needs and thus to obtain better compromise solutions under budgetary constraints, and (4) one can defend the well against risk sources at unknown locations through an adequate model for the residual risk. Overall, the concept brings insight into the costs of reliability, the costs of early warning, the costs of uncertainty, and into the trade-off between covering only severe risks versus the luxury situation of controlling almost tolerable risks as well.

Multimedia Digital Signal Processing of Infrared Chemical Remote Sensing Based on Piecewise Linear Discriminant Algorithm

“…We published a variation model of deformation and constraint [5]. Under this premise, in this article, the restoration of infrared chemical remote sensing multimedia digital signals is proposed based on the boundary variation model, and at the same time, this model is equivalently segmented for calculation and judgment, and the original signal is appropriately restored [6].…”

Systematic Review of Methods to Determine the Cost‐Effectiveness of Monitoring Plans for Chemical and Biological Hazards in the Life Sciences

“…Multi‐objective optimization models were encountered a few times. Bode, Nowak, and Loschko () estimated Pareto‐optimal solutions for their multi‐objective optimization model to optimize groundwater monitoring. The 1st objective was to detect with maximum probability all possible future contaminations.…”

Editorial

“…Bode et al (2015) propose to optimize existing or new monitoring networks in well catchment areas in a multiobjective setting. Their concept brings insight into the costs of B Bernd Flemisch bernd@iws.uni-stuttgart.de Jan M. Nordbotten jan.nordbotten@uib.no Wolfgang Nowak wolfgang.nowak@iws.uni-stuttgart.de Amir Raoof a.raoof@uu.nl reliability, early warning and uncertainty, as well as into the trade-off between covering only severe risks versus the luxury situation of controlling almost tolerable risks as well.…”