Matches in SemOpenAlex for { <https://semopenalex.org/work/W2145245193> ?p ?o ?g. }
- W2145245193 abstract "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." @default.
- W2145245193 created "2016-06-24" @default.
- W2145245193 creator A5000016441 @default.
- W2145245193 creator A5009666468 @default.
- W2145245193 creator A5049069725 @default.
- W2145245193 creator A5086676401 @default.
- W2145245193 date "2004-02-01" @default.
- W2145245193 modified "2023-10-17" @default.
- W2145245193 title "Groundwater nitrate monitoring network optimization with missing data" @default.
- W2145245193 cites W118650051 @default.
- W2145245193 cites W1485120282 @default.
- W2145245193 cites W1536637415 @default.
- W2145245193 cites W166947370 @default.
- W2145245193 cites W1966903467 @default.
- W2145245193 cites W1968703561 @default.
- W2145245193 cites W1970871380 @default.
- W2145245193 cites W1970952643 @default.
- W2145245193 cites W1971123239 @default.
- W2145245193 cites W1990564186 @default.
- W2145245193 cites W1994574262 @default.
- W2145245193 cites W2005228957 @default.
- W2145245193 cites W2013740555 @default.
- W2145245193 cites W2015248263 @default.
- W2145245193 cites W2015724533 @default.
- W2145245193 cites W2019432230 @default.
- W2145245193 cites W2020999234 @default.
- W2145245193 cites W2024060531 @default.
- W2145245193 cites W2026574367 @default.
- W2145245193 cites W2028042973 @default.
- W2145245193 cites W2029421725 @default.
- W2145245193 cites W2031646560 @default.
- W2145245193 cites W2032776595 @default.
- W2145245193 cites W2033152133 @default.
- W2145245193 cites W2050773676 @default.
- W2145245193 cites W2056760934 @default.
- W2145245193 cites W2063230513 @default.
- W2145245193 cites W2066434298 @default.
- W2145245193 cites W2068216323 @default.
- W2145245193 cites W2069144035 @default.
- W2145245193 cites W2069172951 @default.
- W2145245193 cites W2071038433 @default.
- W2145245193 cites W2076315829 @default.
- W2145245193 cites W2089681428 @default.
- W2145245193 cites W2091396986 @default.
- W2145245193 cites W2107941094 @default.
- W2145245193 cites W2112345210 @default.
- W2145245193 cites W2125420983 @default.
- W2145245193 cites W2145674968 @default.
- W2145245193 cites W2158323410 @default.
- W2145245193 cites W2158340476 @default.
- W2145245193 cites W2169260525 @default.
- W2145245193 cites W2171787603 @default.
- W2145245193 cites W2217952474 @default.
- W2145245193 cites W2613782353 @default.
- W2145245193 cites W4230330640 @default.
- W2145245193 cites W81980361 @default.
- W2145245193 cites W2156471863 @default.
- W2145245193 doi "https://doi.org/10.1029/2003wr002469" @default.
- W2145245193 hasPublicationYear "2004" @default.
- W2145245193 type Work @default.
- W2145245193 sameAs 2145245193 @default.
- W2145245193 citedByCount "33" @default.
- W2145245193 countsByYear W21452451932013 @default.
- W2145245193 countsByYear W21452451932015 @default.
- W2145245193 countsByYear W21452451932016 @default.
- W2145245193 countsByYear W21452451932017 @default.
- W2145245193 countsByYear W21452451932018 @default.
- W2145245193 countsByYear W21452451932019 @default.
- W2145245193 countsByYear W21452451932021 @default.
- W2145245193 countsByYear W21452451932022 @default.
- W2145245193 countsByYear W21452451932023 @default.
- W2145245193 crossrefType "journal-article" @default.
- W2145245193 hasAuthorship W2145245193A5000016441 @default.
- W2145245193 hasAuthorship W2145245193A5009666468 @default.
- W2145245193 hasAuthorship W2145245193A5049069725 @default.
- W2145245193 hasAuthorship W2145245193A5086676401 @default.
- W2145245193 hasBestOaLocation W21452451931 @default.
- W2145245193 hasConcept C11413529 @default.
- W2145245193 hasConcept C119857082 @default.
- W2145245193 hasConcept C124101348 @default.
- W2145245193 hasConcept C126255220 @default.
- W2145245193 hasConcept C126980161 @default.
- W2145245193 hasConcept C127413603 @default.
- W2145245193 hasConcept C177264268 @default.
- W2145245193 hasConcept C187320778 @default.
- W2145245193 hasConcept C199360897 @default.
- W2145245193 hasConcept C33923547 @default.
- W2145245193 hasConcept C39432304 @default.
- W2145245193 hasConcept C41008148 @default.
- W2145245193 hasConcept C76177295 @default.
- W2145245193 hasConcept C81692654 @default.
- W2145245193 hasConcept C9357733 @default.
- W2145245193 hasConceptScore W2145245193C11413529 @default.
- W2145245193 hasConceptScore W2145245193C119857082 @default.
- W2145245193 hasConceptScore W2145245193C124101348 @default.
- W2145245193 hasConceptScore W2145245193C126255220 @default.
- W2145245193 hasConceptScore W2145245193C126980161 @default.
- W2145245193 hasConceptScore W2145245193C127413603 @default.
- W2145245193 hasConceptScore W2145245193C177264268 @default.
- W2145245193 hasConceptScore W2145245193C187320778 @default.