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Spatial Persistence of Water Chemistry Patterns Across Flow Conditions in a Mesoscale Agricultural Catchment
Author(s) -
Gu S.,
Casquin A.,
Dupas R.,
Abbott B. W.,
Petitjean P.,
Durand P.,
Gruau G.
Publication year - 2021
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2020wr029053
Subject(s) - environmental science , water quality , hydrology (agriculture) , spatial variability , drainage basin , sink (geography) , pollutant , sampling (signal processing) , ecology , geography , geology , biology , statistics , geotechnical engineering , mathematics , cartography , filter (signal processing) , computer science , computer vision
Protecting water quality at catchment scales is complicated by the high spatiotemporal variability in water chemistry. Consequently, determining pollutant sources requires costly monitoring strategies to diagnose causes and guide management solutions. However, recent studies have shown that spatial patterns in water chemistry can be persistent at catchment scales, potentially allowing identification of pollution sources and sinks with just a few sampling campaigns. Here, we tested a new method to quantify spatial persistence (SP) of water chemistry patterns with data from synoptic samplings in 22 headwater subcatchments within a 375 km 2 catchment in western France (March 2018 to July 2019). This new method to quantify SP reduces dependence on long‐term metrics such as flow‐weighted concentrations, which are usually uncertain or unavailable. We applied the method to 16 ecologically relevant water quality parameters, including soluble reactive phosphorus, nitrate, and dissolved organic carbon. The results showed an average SP of 0.68 among parameters during the study period. For most parameters, SP was higher during the high‐flow winter period but lower and more variable during the low‐flow summer period. We found that the SP ultimately depended on the ratio between the temporal and spatial coefficients of variation (variance explained: 70%) rather than the temporal synchrony among subcatchments (variance explained: 4%). These results demonstrate that in these temperate catchments, synoptic sampling during the high‐flow winter period allows efficient identification of source and sink subcatchments, while more frequent samplings are needed to characterize ecological conditions at low flow.