Performance of landscape composition metrics for predicting water quality in headwater catchments
Status PubMed-not-MEDLINE Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
31594979
PubMed Central
PMC6783472
DOI
10.1038/s41598-019-50895-6
PII: 10.1038/s41598-019-50895-6
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Land use is a predominant threat to the ecological integrity of streams and rivers. Understanding land use-water quality interactions is essential for the development and prioritization of management strategies and, thus, the improvement of water quality. Weighting schemes for land use have recently been employed as methods to advance the predictive power of empirical models, however, their performance has seldom been explored for various water quality parameters. In this work, multiple landscape composition metrics were applied within headwater catchments of Central Europe to investigate how weighting land use with certain combinations of spatial and topographic variables, while implementing alternate distance measures and functions, can influence predictions of water quality. The predictive ability of metrics was evaluated for eleven water quality parameters using linear regression. Results indicate that stream proximity, measured with Euclidean distance, in combination with slope or log-transformed flow accumulation were dominant factors affecting the concentrations of pH, total phosphorus, nitrite and orthophosphate phosphorus, whereas the unweighted land use composition was the most effective predictor of calcium, electrical conductivity, nitrates and total suspended solids. Therefore, both metrics are recommended when examining land use-water quality relationships in small, submontane catchments and should be applied according to individual water quality parameter.
Zobrazit více v PubMed
Hynes H. The stream and its valley. Verhandlungen Int. Vereinigung Theor. und Angew. Limnol. 1975;19:1–15.
Allan JD. Landscapes and Riverscapes: The Influence of Land Use on Stream Ecosystems. Annu. Rev. 2004;35:257–284.
Gergel SE. Spatial and non-spatial factors: When do they affect landscape indicators of watershed loading? Landsc. Ecol. 2005;20:177–189.
Ripl W. Water: The bloodstream of the biosphere. Philos. Trans. R. Soc. B Biol. Sci. 2003;358:1921–1934. doi: 10.1098/rstb.2003.1378. PubMed DOI PMC
Grill G, et al. Mapping the world’s free-flowing rivers. Nature. 2019;569:215–221. doi: 10.1038/s41586-019-1111-9. PubMed DOI
Basnyat P, Teeter LD, Flynn KM, Lockaby BG. Relationships between landscape characteristics and nonpoint source pollution inputs to coastal estuaries. Environ. Manage. 1999;23:539–549. doi: 10.1007/s002679900208. PubMed DOI
Ahearn DS, et al. Land use and land cover influence on water quality in the last free-flowing river draining the western Sierra Nevada. California. 2005;313:234–247.
Giri S, Qiu Z. Understanding the relationship of land uses and water quality in Twenty First Century: A review. J. Environ. Manage. 2016;173:41–48. doi: 10.1016/j.jenvman.2016.02.029. PubMed DOI
Sun Y, Guo Q, Liu J, Wang R. Scale effects on spatially varying relationships between urban landscape patterns and water quality. Environ. Manage. 2014;54:272–287. doi: 10.1007/s00267-014-0287-x. PubMed DOI
King R. Spatial Considerations for Linking Watershed Land Cover To Ecological Indicators in Streams Galley a-105. Ecol. Appl. 2004;15:104–120.
Peterson EE, Pearse AR. IDW-Plus: An ArcGIS Toolset for Calculating Spatially Explicit Watershed Attributes for Survey Sites. J. Am. Water Resour. Assoc. 2017;53:1241–1249. doi: 10.1111/1752-1688.12558. DOI
Huang J, Huang Y, Pontius RG, Zhang Z. Geographically weighted regression to measure spatial variations in correlations between water pollution versus land use in a coastal watershed. Ocean Coast. Manag. 2015;103:14–24. doi: 10.1016/j.ocecoaman.2014.10.007. DOI
Allan JD, Erickson DL, Fay J. The influence of catchment and use on stream integrity across multiple spatial scales. Freshw. Biol. 1997;37:149–161. doi: 10.1046/j.1365-2427.1997.d01-546.x. DOI
Strayer DL, et al. Effects of land cover on stream ecosystems: Roles of empirical models and scaling issues. Ecosystems. 2003;6:407–423. doi: 10.1007/PL00021506. DOI
Kändler M, et al. Impact of land use on water quality in the upper Nisa catchment in the Czech Republic and in Germany. Sci. Total Environ. 2017;586:1316–1325. doi: 10.1016/j.scitotenv.2016.10.221. PubMed DOI
Sheldon F, et al. Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score. Ecol. Appl. 2012;22:2188–2203. doi: 10.1890/11-1792.1. PubMed DOI
Van Sickle J, Burch Johnson C. Parametric distance weighting of landscape influence on streams. Landsc. Ecol. 2008;23:427–438. doi: 10.1007/s10980-008-9200-4. DOI
Walsh CJ, Webb JA. Spatial weighting of land use and temporal weighting of antecedent discharge improves prediction of stream condition. Landsc. Ecol. 2014;29:1171–1185. doi: 10.1007/s10980-014-0050-y. DOI
Peterson EE, Sheldon F, Darnell R, Bunn SE, Harch BD. A comparison of spatially explicit landscape representation methods and their relationship to stream condition. Freshw. Biol. 2011;56:590–610. doi: 10.1111/j.1365-2427.2010.02507.x. DOI
Helin J, Hyytiäinen K, Korpela EL, Kuussaari M. Model for quantifying the synergies between farmland biodiversity conservation and water protection at catchment scale. J. Environ. Manage. 2013;131:307–317. doi: 10.1016/j.jenvman.2013.09.029. PubMed DOI
Thompson J, Pelc CE, Brogan WR, Jordan TE. The multiscale effects of stream restoration on water quality. Ecol. Eng. 2018;124:7–18. doi: 10.1016/j.ecoleng.2018.09.016. DOI
Mattson KM, Angermeier PL. Integrating human impacts and ecological integrity into a risk-based protocol for conservation planning. Environ. Manage. 2007;39:125–138. doi: 10.1007/s00267-005-0238-7. PubMed DOI
Bierschenk AM, Savage C, Townsend CR, Matthaei CD. Intensity of Land Use in the Catchment Influences Ecosystem Functioning Along a Freshwater-Marine Continuum. Ecosystems. 2012;15:637–651. doi: 10.1007/s10021-012-9536-0. DOI
Soldán T, et al. Aquatic insects of the Bohemian Forest glacial lakes: Diversity, long-term changes, and influence of acidification. Silva Gabreta. 2012;18:123–283.
Finn DS, Blouin MS, Lytle DA. Population genetic structure reveals terrestrial affinities for a headwater stream insect. Freshw. Biol. 2007;52:1881–1897. doi: 10.1111/j.1365-2427.2007.01813.x. DOI
Hubalová, P.; Janíček, T.; Pokorný, D.; Fousová, E.; Prošek, V. Report on the state of water management in the Czech Republic. (2018).
Čada, V. & Svoboda, M. Structure and origin of mountain Norway spruce in the Bohemian Forest Structure and origin of mountain Norway spruce in the Bohemian Forest. For. Sci. (2011).
Simon OP, et al. The status of freshwater pearl mussel in the Czech Republic: Several successfully rejuvenated populations but the absence of natural reproduction. Limnologica. 2015;50:11–20. doi: 10.1016/j.limno.2014.11.004. DOI
Vacek S, Podrazsky, Vladimir V. Forest ecosystems of the Šumava Mts. and their management S. J. For. Sci. 2003;49:291–301. doi: 10.17221/4703-JFS. DOI
McConnell DA, Ferris CP, Doody DG, Elliott CT, Matthews DI. Phosphorus Losses from Low-Emission Slurry Spreading Techniques. J. Environ. Qual. 2013;42:446. doi: 10.2134/jeq2012.0024. PubMed DOI
Žlábek P, Bystřický V, Ondr P, Kvítek T, Lechner P. Long-term progress in water quality after grassing and fertilization reduction in spring areas of the Šumava Mountains. Soil Water Res. 2008;3:121–128. doi: 10.17221/3/2008-SWR. DOI
Kroupova V, Klimes F, Kral M. Models of cattle breeding in Sumava National Park. Silbva Gabreta. 1996;1:249–255.
Kopáček J, et al. Chemical composition of atmospheric deposition in the catchments of Plešné and Čertovo lakes in 1998–2012. Silva Gabreta. 2013;19:1–23.
Kvítek T, et al. Changes of nitrate concentrations in surface waters influenced by land use in the crystalline complex of the Czech Republic. Phys. Chem. Earth. 2009;34:541–551. doi: 10.1016/j.pce.2008.07.003. DOI
ÚNMZ. Czech Office for Standards, Metrology and Testing (2018). Available at, http://www.unmz.cz/office/en (Accessed: 18th July 2018).
Oddělení GIS - O projektu & VÚV T.G.Masaryka. DIBAVOD. Available at, http://www.dibavod.cz/ (Accessed: 22nd July 2018).
Zhang H, et al. An integrated algorithm to evaluate flow direction and flow accumulation in flat regions of hydrologically corrected DEMs. CATENA. 2017;151:174–181. doi: 10.1016/j.catena.2016.12.009. DOI
Yu S, Xu Z, Wu W, Zuo D. Effect of land use on the seasonal variation of streamwater quality in the Wei River basin, China. Proc. Int. Assoc. Hydrol. Sci. 2015;368:454–459.
Ding J, et al. Influences of the land use pattern on water quality in low-order streams of the Dongjiang River basin, China: A multi-scale analysis. Sci. Total Environ. 2016;551–552:205–216. doi: 10.1016/j.scitotenv.2016.01.162. PubMed DOI
Ai L, Shi ZH, Yin W, Huang X. Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics. J. Hydrol. 2015;523:398–408. doi: 10.1016/j.jhydrol.2015.01.082. DOI
Pratt B, Chang H. Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales. J. Hazard. Mater. 2012;209–210:48–58. doi: 10.1016/j.jhazmat.2011.12.068. PubMed DOI
Varanka S, Hjort J, Luoto M. Geomorphological factors predict water quality in boreal rivers. Earth Surf. Process. Landforms. 2015;40:1989–1999. doi: 10.1002/esp.3601. DOI
Fučík P, Novák P, Žížala D. A combined statistical approach for evaluation of the effects of land use, agricultural and urban activities on stream water chemistry in small tile-drained catchments of south Bohemia, Czech Republic. Environ. Earth Sci. 2014;72:2195–2216. doi: 10.1007/s12665-014-3131-y. DOI
Wetzel, R. Limnology: Lake and River Ecosystems. (Academic Press, 2001).
Dodds WK. Misuse of inorganic N and soluble reactive P concentrations to indicate nutrient status of surface waters. J. North Am. Benthol. Soc. 2003;22:171–181. doi: 10.2307/1467990. DOI
Neal C, Heathwaite AL. Nutrient mobility within river basins: A European perspective. J. Hydrol. 2005;304:477–490. doi: 10.1016/j.jhydrol.2004.07.045. DOI
Bu H, Meng W, Zhang Y, Wan J. Relationships between land use patterns and water quality in the Taizi River basin, China. Ecol. Indic. 2014;41:187–197. doi: 10.1016/j.ecolind.2014.02.003. DOI
Duarte GT, Santos PM, Cornelissen TG, Ribeiro MC, Paglia AP. The effects of landscape patterns on ecosystem services: meta-analyses of landscape services. Landsc. Ecol. 2018;33:1247–1257. doi: 10.1007/s10980-018-0673-5. DOI
Gao H, et al. Landscape heterogeneity and hydrological processes: a review of landscape-based hydrological models. Landsc. Ecol. 2018;33:1597–1616. doi: 10.1007/s10980-018-0690-4. DOI
Kosmowska A, Żelazny M, Małek S, Siwek JP. & Jelonkiewicz, Ł. Effect of deforestation on stream water chemistry in the Skrzyczne massif (the Beskid Śląski Mountains in southern Poland) Sci. Total Environ. 2016;568:1044–1053. doi: 10.1016/j.scitotenv.2016.06.123. PubMed DOI
Wan R, et al. Inferring land use and land cover impact on stream water quality using a Bayesian hierarchical modeling approach in the Xitiaoxi River Watershed, China. J. Environ. Manage. 2014;133:1–11. doi: 10.1016/j.jenvman.2013.11.035. PubMed DOI
Silva DML, et al. Influence of land use changes on water chemistry in streams in the State of São Paulo, southeast Brazil. An. Acad. Bras. Cienc. 2012;84:919–30. doi: 10.1590/S0001-37652012000400007. PubMed DOI
Wu Y, Liu S. Modeling of land use and reservoir effects on nonpoint source pollution in a. J. Environ. Monit. 2012;14(9):2350–2361. doi: 10.1039/c2em30278k. PubMed DOI
Wu Y, Chen J. Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China. Ecol. Indic. 2013;32:294–304. doi: 10.1016/j.ecolind.2013.04.002. DOI
Sun, P. et al. Can the Grain-for-Green Program Really Ensure a Low Sediment Load on the Chinese Loess Plateau? Engineering, 10.1016/j.eng.2019.07.014 (in press).