{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:16:01Z","timestamp":1792782961778,"version":"4.5.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universidade Do Estado Do Rio De Janeiro","id":[{"id":"https:\/\/ror.org\/0198v2949","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Environ Monit Assess"],"abstract":"Abstract<\/jats:title>\n \n Evaluating the performance of long-term water quality monitoring networks against international reference systems requires analytical tools capable of comparing entire empirical distributions \u2014 not merely summary statistics \u2014 yet distributional benchmarking methods have rarely been applied at the cross-continental scale. This study develops and applies a four-method analytical framework \u2014 combining Wasserstein-1 distributional distance (earth mover\u2019s distance), Shannon-entropy-weighted TOPSIS, linear programming (LP) convergence planning, and principal component analysis with hierarchical cluster analysis (PCA\/HCA) \u2014 to compare ten S\u00e3o Paulo river basins (Brazil) against 23 European countries monitored under the Water Framework Directive (WFD), using a harmonised dataset of 646,356 CETESB records and 998,410 GRQA\u00a0v1.4 records covering seven common physicochemical parameters over a shared window of 2016\u20132022. The Wasserstein-1 analysis reveals that the distributional gap is non-uniform: Afluentes do Para\u00edba do Sul (composite\n \n \n $$W_1 = 0.245$$<\/jats:tex-math>\n \n \n \n W<\/mml:mi>\n 1<\/mml:mn>\n <\/mml:msub>\n =<\/mml:mo>\n 0.245<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ) and the Cantareira system (\n \n \n $$W_1 = 0.333$$<\/jats:tex-math>\n \n \n \n W<\/mml:mi>\n 1<\/mml:mn>\n <\/mml:msub>\n =<\/mml:mo>\n 0.333<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ) are already within the distributional range of lower-ranking European countries, while the Alto\u00a0Tiet\u00ea (\n \n \n $$W_1 = 2.060$$<\/jats:tex-math>\n \n \n \n W<\/mml:mi>\n 1<\/mml:mn>\n <\/mml:msub>\n =<\/mml:mo>\n 2.060<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ) and M\u00e9dio\u00a0Tiet\u00ea (\n \n \n $$W_1 = 1.392$$<\/jats:tex-math>\n \n \n \n W<\/mml:mi>\n 1<\/mml:mn>\n <\/mml:msub>\n =<\/mml:mo>\n 1.392<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ) are distributional outliers. Shannon-entropy-weighted TOPSIS ranking of the 20 entities with complete parameter coverage (all ten Brazilian basins and the ten European countries with complete five-parameter medians) places Afluentes-PSB seventh overall (score = 0.901), above Portugal, Poland, Germany, and Belgium, while the Alto\u00a0Tiet\u00ea (0.246) and M\u00e9dio\u00a0Tiet\u00ea (0.194) rank last. Mann\u2013Whitney\u00a0U tests confirm statistically significant distributional differences for six of seven parameters, with large Cliff\u2019s\u00a0\n \n \n $$\\delta $$<\/jats:tex-math>\n \n \u03b4<\/mml:mi>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n for temperature (\n \n \n $$\\delta = +0.858$$<\/jats:tex-math>\n \n \n \u03b4<\/mml:mi>\n =<\/mml:mo>\n +<\/mml:mo>\n 0.858<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ), dissolved oxygen (\n \n \n $$\\delta = -0.768$$<\/jats:tex-math>\n \n \n \u03b4<\/mml:mi>\n =<\/mml:mo>\n -<\/mml:mo>\n 0.768<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ), and biochemical oxygen demand (\n \n \n $$\\delta = +0.571$$<\/jats:tex-math>\n \n \n \u03b4<\/mml:mi>\n =<\/mml:mo>\n +<\/mml:mo>\n 0.571<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ); nitrate is the sole parameter with no significant difference (\n \n \n $$p = 0.354$$<\/jats:tex-math>\n \n \n p<\/mml:mi>\n =<\/mml:mo>\n 0.354<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ;\n \n \n $$\\delta = -0.010$$<\/jats:tex-math>\n \n \n \u03b4<\/mml:mi>\n =<\/mml:mo>\n -<\/mml:mo>\n 0.010<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n , negligible). The LP convergence model, constrained by historically observed maximum improvement rates in the CETESB dataset, identifies dissolved oxygen as the binding convergence constraint for seven of ten basins, with critical-path convergence times ranging from 4.4 years (Afluentes-PSB) to 14.8 years (Alto\u00a0Tiet\u00ea) under the 90th-percentile feasibility assumption, lengthening to 5.5 and 28.7 years respectively under a more conservative 75th-percentile assumption; total phosphorus carries the highest LP cost weight (\n \n \n $$w = 0.669$$<\/jats:tex-math>\n \n \n w<\/mml:mi>\n =<\/mml:mo>\n 0.669<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ) but is the rate-limiting parameter for only one basin (Tiet\u00ea-M\u00e9dio). Rankings are robust to the weighting scheme (Kendall\u2019s\n \n \n $$\\tau \\ge 0.86$$<\/jats:tex-math>\n \n \n \u03c4<\/mml:mi>\n \u2265<\/mml:mo>\n 0.86<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n against equal-weight and CRITIC alternatives). Applied externally to 33 Polish and 26 Italian sub-basins under a leave-one-country-out design, basin scores correlate negatively with an independent measure of anthropogenic pressure in both countries (\n \n \n $$\\rho = -0.44$$<\/jats:tex-math>\n \n \n \u03c1<\/mml:mi>\n =<\/mml:mo>\n -<\/mml:mo>\n 0.44<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n and\n \n \n $$-0.42$$<\/jats:tex-math>\n \n \n -<\/mml:mo>\n 0.42<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n ), indicating that the benchmarking and ranking components transfer to monitoring systems on which the framework was not developed. PCA\/HCA distinguishes four typological clusters: the Tiet\u00ea\u00a0metropolitan\u00a0arc\u00a0(Cluster\u00a02), a predominantly\u00a0European mainstream (Cluster\u00a01), a clean-reference group (Cluster\u00a03) comprising four Brazilian basins together with Portugal, and an intermediate-impaired group (Cluster\u00a04). These findings demonstrate that S\u00e3o Paulo\u2019s monitoring network is not uniformly distant from the European reference; the proposed framework provides a replicable, distribution-sensitive KPI for monitoring network performance assessment applicable to any national network linked to an international reference archive.\n <\/jats:p>","DOI":"10.1007\/s10661-026-15914-w","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T08:12:31Z","timestamp":1789546351000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Wasserstein distributional distance and linear programming convergence planning as monitoring network benchmarking tools: cross-continental surface water quality assessment across Brazilian and European river basins"],"prefix":"10.1007","volume":"198","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8137-9054","authenticated-orcid":false,"given":"Hugo","family":"Pimentel Tavares","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nilo Ant\u00f4nio","family":"de Souza Sampaio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,16]]},"reference":[{"key":"15914_CR1","first-page":"1","volume":"L 327","author":"European Parliament and Council","year":"2000","unstructured":"European Parliament and Council. 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