[1] A method for designing groundwater monitoring networks to define the extent of agricultural contamination is proposed. The method is particularly well suited to reducing existing networks where data are missing from time series records. A simulated annealing optimization algorithm is used to minimize the variance of the estimation error obtained by kriging in combinatorial problems, created by selecting an optimal subset of stations from the original set. Optimization is performed for several measuring times, obtaining an equal number of optimized small-dimension networks; stations that repeat more often in these networks are selected to make part of the final network. A compliance groundwater nitrate monitoring network in the south of Portugal is used to illustrate the method. The original 89-station network was converted into 16 stations. Results show that considerable reductions in operating costs (about 80%) are compatible with a cost-effective network capable of detecting noncompliance with national and European norms.
This article focuses on the design of groundwater monitoring networks to detect contamination with nitrates from agricultural origin. This is a problem that has been in the minds of the general public, scientists, governmental agencies, and legislators for some time now. If one looks at European statistics, despite still incomplete data, in 13% of the regions the 50 mg/l European water quality standard for drinking water (Drinking Water Directive, 98/83/EC) is exceeded in more than 25% of the monitoring stations. A compliance groundwater nitrate‐monitoring network is developed for a case study in the south of Portugal (Gabbro of Beja aquifer system), using both variance‐reduction and space‐filling approaches. In the first the variance of the error of estimation obtained by ordinary kriging is used, after building a covariance model, and the objective is to minimize the average kriging variance. In the second approach a criterion for the quality of spatial coverage is used, usually based on a metric. The objective here is also usually to minimize a function of the metric (criterion). The search for a solution is made in an iterative manner, by replacing one station, analyzing the result, and deciding whether to keep the solution or not. Due to the enormous number of possible combinations even for small networks, a structured search method, the simulated annealing method, is used to obtain the final network.
Diffuse pollution is among the major environmental concerns in terms of prevention of further deterioration and restoration of water to a "good status" in terms of ecological and chemical parameters. A step forward should be made for finding better land use, crop irrigation and fertilization practices to avoid damaging water bodies. This paper presents a framework for obtaining the decisions to be implemented in order to define a sustainable agriculture land use and production practices. A multidisciplinary approach is proposed for building a decision model capable of representing all the issues involved in the scope of an integrated management of land and water resources. The framework proposed is the basis of a research project recently financed by the Portuguese research foundation (Fundação para a Ciência e a Tecnologia). The main objectives of the project can be summarized as follows: 1) Improve the scientific knowledge regarding the interrelation between the agriculture land use and the production practices and the groundwater and the surface water quality protection, towards a more sustainable agriculture; 2) Contribute to support future decisions in terms of more adequate policies regarding rural land use planning (type of crops and associated fertilizers and treatment techniques), taking into consideration the protection of the environment based on vulnerability and risk concepts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.