Abstract
A significant contributor to water pollution is increased nutrient concentration that results in eutrophication. Modeling approaches are crucial to understanding the dynamics of nutrients in river basins. This study integrates empirical models into Geographic Information Systems to quantify total nitrogen and phosphorus (TN and TP) load and concentration in watercourses of Brazil’s Lobo Stream Hydrographic Basin (LSHB). Land use, topographic, demographic, and hydrological data were used to simulate the load and concentration of nutrients generated by point and nonpoint pollution sources. The results indicate that the simulated TN and TP load is primarily generated by nonpoint sources, 81% and 76%, respectively. The Itaqueri River subbasin is the most critical, yielding more than half of the basin’s TN and TP load. About 90% of annual LSHB point pollution load is generated in the Itaqueri River subbasin, principally from the Água Branca Stream. The linear regression between simulated and observed concentration indicates significant relationships (TN, r2 = 0.73 (p < 0.05), TP, r2 = 0.78 (p < 0.05)). The method used was able to simulate TN and TP concentration in watercourses, but was inconsistent for point pollution, indicating it represents the dynamics of nutrients in rural basins more effectively than in urban ones. The study shows that its methodology, despite limitations, enables scientists and managers to understand and predict spatial distribution of nutrient concentration in LSHB watercourses.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The hydrological data used in this study are available in the National Water Agency (ANA) database (http://www.snirh.gov.br/hidroweb/apresentacao). Topographic maps are available in the Brazilian Institute of Statistical Geography (IBGE) database (https://www.ibge.gov.br/). SRTM-DEM images are available in the geomorphometric database of the National Institute for Space Research (INPE) (http://www.dsr.inpe.br/topodata/). The Sentinel-2 satellite images are available in the U.S Geological Survey (USGS) database (https://earthexplorer.usgs.gov/). The water quality data generated in this research are available from the corresponding author on reasonable request.
References
ANA (2009) Water Resources Conjuncture in Brazil. National Water Agency (ANA), Brasília, Brazil. http://www.snirh.gov.br/portal/snirh/centrais-de-conteudos/conjuntura-dos-recursos-hidricos
ANA (2012) Operative Manual of the Water Producer Program. National Water Agency (ANA), Brasília, Brazil. https://www.ana.gov.br/programas-e-projetos/programa-produtor-de-agua
ANA (2018) Sistema de Informações Hidrológicas (HidroWeb). National Water Agency (ANA), Brasília, Brazil. http://www.snirh.gov.br/hidroweb/
ANA (2019) Water Resources Conjuncture in Brazil. National Water Agency (ANA), Brasília, Brazil. http://www.snirh.gov.br/portal/snirh/centrais-de-conteudos/conjuntura-dos-recursos-hidricos
Anderson TA, Salice CJ, Erickson RA, McMurry ST, Cox SB, Smith LM (2013) Effects of land use and precipitation on pesticides and water quality in playa lakes of the southern high plains. Chemosphere 92(1):84–90. https://doi.org/10.1016/j.chemosphere.2013.02.054
Anjinho PS, Barbosa MAGA, Dos Santos AR, Mauad FF (2018) Espacialização do parâmetro Curve Number (CN) na bacia hidrográfica do ribeirão do Lobo para o período de 1985 e 2017. In: XVI Simpósio do Programa de Pós-Graduação em Ciências da Engenharia Ambiental, São Carlos: EESC-USP, p. 01-11 (in Portuguese)
Anjinho PS, Dos Santos AR, Barbosa MAGA, Mauad FF (2019) Spatial-temporal analysis of the risk to water pollution against land use changes in Lobo Stream Drainage Basin, Itirapina-SP, Brazil. Electronic Journal of Management, Education and Environmental Technology 23(34):01–10
APHA (1992) Standard methods for examination of water and wastewater. American Public Health Association (APHA), Washington, USA
Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Kannan N (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508. https://doi.org/10.13031/2013.42256
Baattrup-Pedersen A, Göthe E, Larsen SE, O’Hare M, Birk S, Riis T, Friberg N (2015) Plant trait characteristics vary with size and eutrophication in E uropean lowland streams. J Appl Ecol 52(6):1617–1628. https://doi.org/10.1111/1365-2664.12509
Baker TJ, Miller SN (2013) Using the Soil and Water Assessment Tool (SWAT) to assess land use impact on water resources in an East African watershed. J Hydrol 486:100–111. https://doi.org/10.1016/j.jhydrol.2013.01.041
Balbinot R, De Oliveira NK, Vanzetto SC, Pedroso K, Valério ÁF (2008) The forest role in the hydrological cycle at hydrological basins. Ambiência 4(1):131–149
Beasley DB, Huggins LF, Monke A (1980) ANSWERS: A model for watershed planning. Transactions of the ASAE 23(4):938–944. https://doi.org/10.13031/2013.34692
Biswas JK, Bera B, Chanda R, Sarkar SK, Majumdar J, Majumder S, Hazra S (2018) Nutrient modeling of an urban lake using best subset method. Int J Environ Sci Te 15(9):1867–1878. https://doi.org/10.1007/s13762-017-1540-7
Brauman KA, Daily GC, Duarte TKE, Mooney HA (2007) The nature and value of ecosystem services: an overview highlighting hydrologic services. Annu Rev Environ Resour 32:67–98. https://doi.org/10.1146/annurev.energy.32.031306.102758
Brazil (2005) National Environmental Council Resolution (CONAMA) 357. Dispõe sobre a classificação dos corpos de água e diretrizes ambientais para o seu enquadramento, bem como estabelece as condições e parâmetros de lançamento de efluentes, e dá outras providências (in Portuguese). Union Official Diary, DF. http://www2.mma.gov.br/port/conama/legiabre.cfm?codlegi=459
Brazil (2012) Federal Law N° 12.651, may 25, 2012. Brazilian Forest Code, Brasília, DF. http://www.planalto.gov.br/ccivil_03/_Ato2011-2014/2012/Lei/L12651.htm
Brazil (2018) Diagnóstico dos Serviços de Água e Esgotos – 2016. Brazil Ministry of Cities, Brasília, Brazil (in Portuguese).
Cabral JP (2010) Water microbiology. Bacterial pathogens and water. Int J Environ Res Public Health 7(10):3657–3703. https://doi.org/10.3390/ijerph7103657
Campbell D, Arcy B, Frost A, Novotny V, Sansom A (2004) Diffuse pollution–an introduction to the problems and solutions. IWA, London
Campregher R, Martins RC (2017) O “Modelo Broa” e a produção de conhecimento científico sobre o meio ambiente. Desenvolvimento e Meio ambiente 40:329–344 (in Portuguese). https://doi.org/10.5380/dma.v40i0.49243
CEPAGRI (2017) Climate information. Centre for meteorological and climate research applied to agriculture (CEPAGRI). State University of Campinas (Unicamp). http://www.cepagri.unicamp.br/
Chaves HML, Rosa JWC, Vadas RG, Oliveira RV (2002) Regionalização de vazões mínimas em bacias através de interpolação em sistemas de informação geográfica. Brazilian Journal of Water Resources 7(3):43–51 (in Portuguese). https://doi.org/10.21168/rbrh.v7n3.p43-51
Christofoletti CA, Escher JP, Correia JE, Marinho JFU, Fontanetti CS (2013) Sugarcane vinasse: environmental implications of its use. Waste Manag 33(12):2752–2761. https://doi.org/10.1016/j.wasman.2013.09.005
Collier CA, De Almeida Neto MS, De Almeida GMA, Rosa Filho JS, Severi W, El-Deir ACA (2019) Effects of anthropic actions and forest areas on a neotropical aquatic ecosystem. Sci Total Environ 691:367–377. https://doi.org/10.1016/j.scitotenv.2019.07.122
Collischonn W, Tucci CEM (2001) Simulação hidrológica de grandes bacias. Thesis, Federal University of Rio Grande do Sul, Porto Alegre, Brazil (in Portuguese). http://hdl.handle.net/10183/2500
Couture RM, Moe SJ, Lin Y, Kaste Ø, Haande S, Solheim AL (2018) Simulating water quality and ecological status of Lake Vansjø, Norway, under land-use and climate change by linking process-oriented models with a Bayesian network. Sci Total Environ 621:713–724. https://doi.org/10.1016/j.scitotenv.2017.11.303
Delkash M, Al-Faraj FA, Scholz M (2014) Comparing the export coefficient approach with the soil and water assessment tool to predict phosphorous pollution: the Kan watershed case study. Water Air Soil Pollut 225(10):2122. https://doi.org/10.1007/s11270-014-2122-7
Dodds WK, Bouska WW, Eitzmann JL, Pilger TJ, Pitts KL, Riley AJ, Thornbrugh DJ (2009) Eutrophication of US freshwaters: analysis of potential economic damages. Environ Sci Technol 43(1):12–19. https://doi.org/10.1021/es801217q
Dunn SM, Brown I, Sample J, Post H (2012) Relationships between climate, water resources, land use and diffuse pollution and the significance of uncertainty in climate change. J Hydrol 434:19–35. https://doi.org/10.1016/j.jhydrol.2012.02.039
El-Khoury A, Seidou O, Lapen DR, Que Z, Mohammadian M, Sunohara M, Bahram D (2015) Combined impacts of future climate and land use changes on discharge, nitrogen and phosphorus loads for a Canadian river basin. J Environ Manag 151:76–86. https://doi.org/10.1016/j.jenvman.2014.12.012
Estigoni MV, Matos AJS, Mauad FF (2014) Assessment of the accuracy of different standard methods for determining reservoir capacity and sedimentation. J Soils Sediments 14(7):1224–1234. https://doi.org/10.1007/s11368-013-0816-x
Frascareli D, Cardoso-Silva S, Mizael JDOSS, Rosa AH, Pompêo MLM, López-Doval JC, Moschini-Carlos V (2018) Spatial distribution, bioavailability, and toxicity of metals in surface sediments of tropical reservoirs, Brazil. Environ Monit Assess 190(4):199. https://doi.org/10.1007/s10661-018-6515-8
Guignard MS, Leitch AR, Acquisti C, Eizaguirre C, Elser JJ, Hessen DO, Soltis DE (2017) Impacts of nitrogen and phosphorus: from genomes to natural ecosystems and agriculture. Front Ecol Evol 5:70. https://doi.org/10.3389/fevo.2017.00070
Her Y, Chaubey I, Frankenberger J, Jeong J (2017) Implications of spatial and temporal variations in effects of conservation practices on water management strategies. Agric Water Manag 180:252–266. https://doi.org/10.1016/j.agwat.2016.07.004
Huang J, Hong H (2010) Comparative study of two models to simulate diffuse nitrogen and phosphorus pollution in a medium-sized watershed, southeast China. Estuar Coast Shelf S 86(3):387–394. https://doi.org/10.1016/j.ecss.2009.04.003
Hutchinson MF (1989) A new procedure for gridding elevation and stream line data with automatic removal of spurious pits. J Hydrol 106(3-4):211–232. https://doi.org/10.1016/0022-1694(89)90073-5
IBGE (1969) Folha Topográfca de Itirapina (SF-23-M-1-3) em escala 1:50.000. Brazilian Institute of Geography and Statistics (IBGE), Brasília, Brazil
IBGE (1971) Folha Topográfca São Carlos (SF-23-Y-A-I-1) em escala 1:50.000. Brazilian Institute of Geography and Statistics (IBGE), Brasília, Brazil.
IBGE (2010) Demographic Census of 2010. Brazilian Institute of Geography and Statistics (IBGE), Brasília, Brazil. https://ww2.ibge.gov.br/home/estatistica/populacao/censo2010/default.shtm
IEA (2018) Valor da produção agropecuária do estado de São Paulo: resultado preliminar de 2018. Institute of Agricultural Economics (IEA), São Paulo, Brazil (In Portuguese). http://www.iea.sp.gov.br/out/TerTexto.php?codTexto=14543
IF (2005) Plano de Manejo Integrado das Estações Ecológica e Experimetnal de Itirapina/SP. Forestry Institute of São Paulo (IF), São Paulo, Brazil (In Portuguese)
Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogramm Eng Rem S 54(11):1593–1600
Júnior CB, De Souza FAO, Mauad FF (2015) GIS automation for spatialization of water availability. Anu Inst Geocienc 38(2):47–55
Le Moal M, Gascuel-Odoux C, Ménesguen A, Souchon Y, Étrillard C, Levain A, Pinay G (2019) Eutrophication: a new wine in an old bottle? Sci Total Environ 651:1–11. https://doi.org/10.1016/j.scitotenv.2018.09.139
Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res Atmos 99(7):14415–14428. https://doi.org/10.1029/94JD00483
Libos MIPC, Rotunno Filho OC, Zeilhofer P (2003) Modelagem da poluição não pontual na bacia do rio Cuiabá baseada em Geoprocessamento. Brazilian J Water Res 8(4):115–135. https://doi.org/10.21168/rbrh.v8n4.p115-135
Lima RN, De Melo Ribeiro CB, Barbosa CCF, Filho OCR (2016) Study of point and diffuse pollution in the Funil reservoir hydropower plant contribution basin using spatially distributed Geographic Information System modeling. Eng Sanit Ambient 21(1):139–150. https://doi.org/10.1590/S1413-41520201600100127676
Liu A, Li D, Liu L, Guan Y (2014) Understanding the role of urban road surface characteristics in influencing stormwater quality. Water Resour Manag 28(14):5217–5229. https://doi.org/10.1007/s11269-014-0788-7
Lucas M, Wendland E (2016) Recharge estimates for various land uses in the Guarani Aquifer System outcrop area. Hydrol Sci J 61(7):1253–1262. https://doi.org/10.1080/02626667.2015.1031760
Martinelli LA, Filoso S (2008) Expansion of sugarcane ethanol production in Brazil: environmental and social challenges. Ecol Appl 18(4):885–898. https://doi.org/10.1890/07-1813.1
Martini DZ, Sanches IDA, Galdos MV, Da Silva CRU, Dalla-Nora EL (2018) Land availability for sugarcane derived jet-biofuels in São Paulo—Brazil. Land Use Policy 70:256–262. https://doi.org/10.1016/j.landusepol.2017.10.035
McDonnell JJ, Sivapalan M, Vaché K, Dunn S, Grant G, Haggerty R, Selker J (2007) Moving beyond heterogeneity and process complexity: a new vision for watershed hydrology. Water Resour Res 43(7). https://doi.org/10.1029/2006WR005467
Meyer JL, Strayer DL, Wallace JB, Eggert SL, Helfman GS, Leonard NE (2007) The contribution of headwater streams to biodiversity in river networks. J Am Water Resour Assoc 43(1):86–103. https://doi.org/10.1111/j.1752-1688.2007.00008.x
Michette, JF (2015) Modelos de previsão de erosão pluvial utilizando SIG: estudo na bacia hidrográfica da Represa do Lobo (Broa), SP. Dissertation, University of Sao Paulo, Brazil. https://teses.usp.br/teses/disponiveis/18/18149/tde-28072015-131559/pt-br.php
Mizael JDOSS, Cardoso-Silva S, Frascareli D, Pompêo MLM, Moschini-Carlos V (2020) Ecosystem history of a tropical reservoir revealed by metals, nutrients and photosynthetic pigments preserved in sediments. CATENA 184:104242. https://doi.org/10.1016/j.catena.2019.104242
Molina-Navarro E, Andersen HE, Nielsen A, Thodsen H, Trolle D (2018) Quantifying the combined effects of land use and climate changes on stream flow and nutrient loads: a modelling approach in the Odense Fjord catchment (Denmark). Sci Total Environ 621:253–264. https://doi.org/10.1016/j.scitotenv.2017.11.251
Moreira MC, Pruski FF, Da Silva DD, Da Silva JMA (2010) Comparação dos valores da Q7, 10 estimados por diferentes métodos de regionalização de vazões. Revista engenharia na agricultura 18(6): 522-528 (In Portuguese). https://doi.org/10.13083/reveng.v18i6.204.
Moruzzi RB, Da Conceição FT, Sardinha D, Honda FP, Navarro GRB (2012) Avaliação de cargas difusas e simulação de autodepuração no córrego da Água Branca, Itirapina (SP). Geosciences 31(3):447–458
Motsinger J, Kalita P, Bhattarai R (2016) Analysis of best management practices implementation on water quality using the soil and water assessment tool. Water 8(4):145. https://doi.org/10.3390/w8040145
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—a discussion of principles. J Hydrol 10(3):282–290. https://doi.org/10.1016/0022-1694(70)90255-6
Novaes LF, Pruski FF, Pereira SB, Queiroz DO, Rodriguez RDG (2009) Gestão de recursos hídricos: uma nova metodologia para a estimativa das vazões mínimas. Revista Engenharia na Agricultura 17(1). https://doi.org/10.13083/reveng.v17i1.93
Omwoma S, Lalah JO, Ongeri DM, Schramm KW (2014) The impact of agronomic inputs on selected physicochemical features and their relationships with heavy metals levels in surface sediment and water in sugarcane farms in Nzoia, Kenya. Environ Earth Sci 71(10):4297–4308. https://doi.org/10.1007/s12665-013-2824-y
Pereira RDS (2005) Identificação e caracterização das fontes de poluição em sistemas hídricos. Revista Eletrônica de Recursos Hídricos 1(1):20–36
Quenzer AM, Maidment DR (1998) Constituent loads and water quality in the Corpus Christi Bay system. In Water Resources Engineering, ASCE, USA
Refsgaard JC, Storm B (1995) “MIKE SHE”, in computer models of watershed hydrology, Ed. por Singh, V.P., Water Resources Publications, Colorado, USA
Rodrigues-Filho JL, Degani RM, Soares FS, Periotto NA, Blanco FP, Abe DS, Tundisi JG (2015) Alterations in land uses based on amendments to the Brazilian Forest Law and their influences on water quality of a watershed. Braz J Biol Sci 75(1):125–134. https://doi.org/10.1590/1519-6984.08813
Rudorff BFT, Aguiar DA, Silva WF, Sugawara LM, Adami M, Moreira MA (2010) Studies on the rapid expansion of sugarcane for ethanol production in São Paulo State (Brazil) using Landsat data. Remote Sens 2(4):1057–1076. https://doi.org/10.3390/rs2041057
Ruggiero PG, Metzger JP, Tambosi LR, Nichols E (2019) Payment for ecosystem services programs in the Brazilian Atlantic Forest: Effective but not enough. Land Use Policy 82:283–291. https://doi.org/10.1016/j.landusepol.2018.11.054
Sadri S, Burn DH (2011) A Fuzzy C-Means approach for regionalization using a bivariate homogeneity and discordancy approach. J Hydrol 401(3-4):231–239. https://doi.org/10.1016/j.jhydrol.2011.02.027
Saunders WK, Maidment DR (1996) A GIS assessment of nonpoint source pollution in the San Antonio-Nueces coastal basin. Center for Research in Water Resources, University of Texas at Austin
Schindler DW (2012) The dilemma of controlling cultural eutrophication of lakes. P Roy Soc B-Biol Sci 279(1746):4322–4333. https://doi.org/10.1098/rspb.2012.1032
Sharp R, Tallis HT, Ricketts T, Guerry AD, Wood SA, Chaplin-Kramer R, Nelson E, Ennaanay D, Wolny S, Olwero N, Vigerstol K, Pennington D, Mendoza G, Aukema J, Foster J, Forrest J, Cameron D, Arkema K, Lonsdorf E, Kennedy C, Verutes G (2018). InVEST 3.7.0. user’s guide. The Natural Capital Project, Stanford University, University of Minnesota, The Nature Conservancy, and World Wildlife Fund
Shen Z, Liao Q, Hong Q, Gong Y (2012) An overview of research on agricultural non-point source pollution modelling in China. Sep Purif Technol 84:104–111. https://doi.org/10.1016/j.seppur.2011.01.018
Shrestha MK, Recknagel F, Frizenschaf J, Meyer W (2017) Future climate and land uses effects on flow and nutrient loads of a Mediterranean catchment in South Australia. Sci Total Environ 590:186–193. https://doi.org/10.1016/j.scitotenv.2017.02.197
Silva Lelis LC, Nascimento JG, Duarte SN, Pacheco AB, Bosquilia RWD, Wolff W (2020) Assessment of hydrological regionalization methodologies for the upper Jaguari River basin. J S Am Earth Sci 97:102402. https://doi.org/10.1016/j.jsames.2019.102402
Sith R, Watanabe A, Nakamura T, Yamamoto T, Nadaoka K (2019) Assessment of water quality and evaluation of best management practices in a small agricultural watershed adjacent to Coral Reef area in Japan. Agric Water Manag 213:659–673. https://doi.org/10.1016/j.agwat.2018.11.014
SMA (2010) Elaboração do Plano de Desenvolvimento e Proteção Ambiental da Bacia Hidrográfica do Reservatório Billings. Secretariat for the Environment of the State of São Paulo (SMA), São Paulo, Brazil (In Portuguese)
Smith VH, Schindler DW (2009) Eutrophication science: where do we go from here? Trends Ecol Evol 24(4):201–207. https://doi.org/10.1016/j.tree.2008.11.009
Smith VH, Tilman GD, Nekola JC (1999) Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ Pollut 100(1-3):179–196. https://doi.org/10.1016/S0269-7491(99)00091-3
Tucci CE (2002) Regionalização de vazões. Federal University of Rio Grande do Sul. Porto Alegre, Brazil
Tundisi JG, Matsumura-Tundisi T (2014) The ecology of UHE Carlos Botelho (Lobo-Broa Reservoir) and its watershed, São Paulo, Brazil. Fr Rev 6(2):75–91. https://doi.org/10.1608/FRJ-6.2.727
Tundisi JG, Matsumura-Tundisi T (2016) Integrating ecohydrology, water management, and watershed economy: Case studies from Brazil. Ecohydrol Hydrobiol 16(2):83–91. https://doi.org/10.1016/j.ecohyd.2016.03.006
Tundisi JG, Matsumura-Tundisi T, Rodrigues S (2003) Gerenciamento e Recuperação das Bacias Hidrográficas dos Rios Itaqueri e do Lobo e da UHE Carlos Botelho (Lobo-Broa) -Municípios de Itirapina e de Brotas. Rima Artes e Textos, São Carlos, Brazil.
Turunen J, Markkula J, Rajakallio M, Aroviita J (2019) Riparian forests mitigate harmful ecological effects of agricultural diffuse pollution in medium-sized streams. Sci Total Environ 649:495–503. https://doi.org/10.1016/j.scitotenv.2018.08.427
USGS (2018) SENTINEL-2. United States Geological Survey (USGS) http://earthexplorer.usgs.gov/
Valeriano M, De Fátima Rossetti D, De Albuquerque PCG (2009) TOPODA: desenvolvimento da primeira versão do banco de dados geomorfométricos locais em cobertura nacional. In: XIV Brazilian Symposium on Remote Sensing. National Institute for Space Research (INPE), São José dos Campos, Brazil
Vigerstol KL, Aukema JE (2011) A comparison of tools for modeling freshwater ecosystem services. J Environ Manag 92(10):2403–2409. https://doi.org/10.1016/j.jenvman.2011.06.040
Vigiak O, Malagó A, Bouraoui F, Pastori M, Borrelli P, Pistocchi A (2016) Impact of current riparian land on sediment retention in the Danube River Basin. Sustainability of Sustainability of Water Quality and Ecology 8:30–49. https://doi.org/10.1016/j.swaqe.2016.08.001
Von Sperling M (2005) Introdução à qualidade das águas e ao tratamento de esgotos. Federal University of Minas Gerais. Minas Gerais, Brazil
Willmott CJ, Ackleson SG, Davis RE, Feddema JJ, Klink KM, Legates DR, Rowe CM (1985) Statistics for the evaluation and comparison of models. J Geophys Res Oceans 90(5):8995–9005. https://doi.org/10.1029/JC090iC05p08995
Wolff W, Duarte SN, Mingoti R (2014) Nova metodologia de regionalização de vazões, estudo de caso para o Estado de São Paulo. Brazilian Journal of Water Resources 19(4):21–33. https://doi.org/10.21168/rbrh.v19n4.p21-33
Yan Y, Guan Q, Wang M, Su X, Wu G, Chiang P, Cao W (2018) Assessment of nitrogen reduction by constructed wetland based on InVEST: a case study of the Jiulong River Watershed, China. Mar Pollut Bull 133:349–356. https://doi.org/10.1016/j.marpolbul.2018.05.050
Young RA, Onstad CA, Bosch DD, Anderson WP (1989) AGNPS: a nonpoint-source pollution model for evaluating agricultural watersheds. J Soil Water Conserv 44(2):168–173
Zeilhofer P, De Lima RMN (2005) REGIO: uma aplicação sig para subsidiar a regionalização de vazões. Caminhos de Geografia 7(17)
Zhang X, Zhang M (2011) Modeling effectiveness of agricultural BMPs to reduce sediment load and organophosphate pesticides in surface runoff. Sci Total Environ 409(10):1949–1958. https://doi.org/10.1016/j.scitotenv.2011.02.012
Zhao H, Jiang Q, Ma Y, Xie W, Li X, Yin C (2018) Influence of urban surface roughness on build-up and wash-off dynamics of road-deposited sediment. Environ Pollut 243:1226–1234. https://doi.org/10.1016/j.envpol.2018.09.105
Acknowledgments
We would like to thank the National Council of Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personne (CAPES) for granting scholarships to the authors, and the Center of Water Resources and Environmental Studies (CRHEA), University of São Paulo, for the structure offered.
Funding
Research grants from funding the National Council of Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personne (CAPES) agencies were awarded to the authors of this article.
Author information
Authors and Affiliations
Contributions
Phelipe da Silva Anjinho: conceptualization, methodology, formal analysis, investigation, writing - original draft, writing - review and editing, funding acquisition. Mariana Abibi Guimarães Araujo Barbosa: conceptualization, methodology, formal analysis, investigation, writing - review and editing, funding acquisition. Gabriela Leite Neves: investigation, writing - review and editing, funding acquisition. Allita Rezende dos Santos: investigation, writing - review and editing, funding acquisition. Frederico Fábio Mauad: resources, project administration, supervision. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Additional information
Responsible Editor: Thomas Hein
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
da Silva Anjinho, P., Barbosa, M.A.G.A., Neves, G.L. et al. Integrated empirical models to assess nutrient concentration in water resources: case study of a small basin in southeastern Brazil. Environ Sci Pollut Res 28, 23349–23367 (2021). https://doi.org/10.1007/s11356-020-12125-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-020-12125-9