1,198
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Water quality spatial-temporal analysis of gravel pit ponds in the southeast regional park Madrid (Spain) from 1984 to 2009.

, , &
Pages 10636-10658 | Received 28 Oct 2021, Accepted 30 Jan 2022, Published online: 10 Feb 2022

References

  • Agencia Estatal de Meteorología de España. 2017. Informe de radiación solar. https://www.bing.com/search?q=Agencia+Estatal+de+Meteorolog%C3%ADa+de+Espa%C3%B1a.+(2017).+Informe+de+radiaci%C3%B3n+solar.+Madrid&cvid=60ab20a244d74436813cfd9e0d10aef7&aqs=edge.69i57.259j0j4&pglt=2083&FORM=ANAB01&PC=LGTS.
  • Álvarez-Cobelas M, Rubio A, Arauzo M, Alarcón P, Limnética VA. 1987. Morfometria y composición química de una laguna de gravera. Limnetica.Net. http://www.limnetica.net/documentos/limnetica/limnetica-3-1-p-91.pdf.
  • Álvarez-Cobelas M. 1991. Optical limnology of a hypertrophic gravel‐pit lake. Int Revue Ges Hydrobiol Hydrogr. 76(2):213–223. https://doi.org/10.1002/iroh.19910760206.
  • Álvarez-Cobelas M, Rojo C, Benavent-Corai J. 2019. Long-term phytoplankton dynamics in a complex temporal realm. Sci Rep. 9(1):15967. https://doi.org/10.1038/s41598-019-52333-z.
  • Álvarez-Cobelas M. 2000. Estudio fisico-químico de los ambientes estancados del Parque Regional del Sureste de la Comunidad de Madrid. Centro de Investigaciones Ambientales de la Comunidad de Madrid “Fernando González Bernáldez.”
  • Andrews J. 1990. Principles of restoration of gravel pits for wildlife. Br Wildlife. 2(2):80–88. https://doi.org/10.1016/0006-3207(92)91240-s.
  • Beltrán-Abaunza JM, Kratzer S, Höglander H. 2017. Using MERIS data to assess the spatial and temporal variability of phytoplankton in coastal areas. Int J Remote Sens. 38(7):2004–2028. https://doi.org/10.1080/01431161.2016.1249307.
  • Blanchet CC, Arzel C, Davranche A, Kahilainen KK, Secondi J, Taipale S, Lindberg H, Loehr J, Manninen-Johansen S, Sundell J, et al. 2022. Ecology and extent of freshwater browning – What we know and what should be studied next in the context of global change. Sci Total Environ. 812:152420. https://doi.org/10.1016/J.SCITOTENV.2021.152420.
  • Boucher J, Weathers KC, Norouzi H, Steele B. 2018. Assessing the effectiveness of Landsat 8 chlorophyll a retrieval algorithms for regional freshwater monitoring. Ecol Appl. 28(4):1044–1054. https://doi.org/10.1002/eap.1708
  • Bracher A, Xi H, Dinter T, Mangin A, Strass V, von Appen WJ, Wiegmann S. 2020. High resolution water column phytoplankton composition across the Atlantic ocean from ship-towed vertical undulating radiometry. Front Mar Sci. 7:235. https://doi.org/10.3389/fmars.2020.00235
  • Castagna SED, de Luca DA, Lasagna M. 2015. Eutrophication of piedmont quarry lakes (North-Western Italy): hydrogeological factors, evaluation of trophic levels and management strategies. J Environ Assess Pol Manag. 17(04):1550036. https://doi.org/10.1142/S1464333215500362
  • Chao Rodríguez Y, el Anjoumi A, Domínguez Gómez JA, Rodríguez Pérez D, Rico E. 2014. Using Landsat image time series to study a small water body in Northern Spain. Environ Monit Assess. 186(6): 3511–3522. https://doi.org/10.1007/s10661-014-3634-8
  • Chen Z, Zhang SR, Coster AJ, Fang G. 2015. EOF analysis and modeling of GPS TEC climatology over North America. J Geophys Res Space Phys. 120(4):3118–3129. https://doi.org/10.1002/2014JA020837
  • Chu HJ, Kong SJ, Chang CH. 2018. Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression. Int J Appl Earth Obs Geoinf. 65:1–11. https://doi.org/10.1016/J.JAG.2017.10.001
  • Comunidad de Madrid. 2020. Plan de Actuación sobre Humedales Catalogados de la Comunidad de Madrid. Madrid – Bing. https://www.bing.com/search?q=Plan+de+Actuaci%C3%B3n+sobre+Humedales+Catalogados+de+la+Comunidad+de+Madrid.+Madrid&qs=n&form=QBRE&msbsrank=0_0__0&sp=-1&pq=plan+de+actuaci%C3%B3n+sobre+humedales+catalogados +de+la+comunidad+de+madrid.+madrid&sc=0-79&sk=&cvid=1790048BAEA54D62B99D5E207A1741E4.
  • Cressie N, Wikle C. 2015. Statistics for spatio-temporal data. https://books.google.com/books?hl=es&lr=&id=4L_dCgAAQBAJ&oi=fnd&pg=PP1&ots=idWU3BNn0-&sig=itYykh_C0wyLAKxBD5PUlXtyuR8.
  • Delasalles E, Ziat A, Denoyer L, Gallinari P. 2019. Spatio-temporal neural networks for space-time data modeling and relation discovery. Knowl Inf Syst. 61(3):1241–1267. https://doi.org/10.1007/S10115-018-1291-X/TABLES/5
  • Devlin MJ, Petus C, da Silva E, Tracey D, Wolff NH, Waterhouse J, Brodie J. 2015. Water quality and river plume monitoring in the Great Barrier Reef: an overview of methods based on ocean colour satellite data. Remote Sens. 7(10):12909–12941. https://doi.org/10.3390/RS71012909
  • Díaz JMC, Araujo JM. 2017. Historic urbanization process in Spain (1746–2013): from the fall of the American empire to the real estate bubble. J Urban Hist. 43(1):33–52. https://doi.org/10.1177/0096144215583481
  • Domínguez Gómez JA, Chuvieco Salinero E, Sastre Merlín A. 2009. Monitoring transparency in inland water bodies using multispectral images. Int J Remote Sens. 30(6):1567–1586. https://doi.org/10.1080/01431160802513811
  • Domínguez Gómez JA, Peña R. 1999. Trophic state assessment in two gravel pits (El Campillo & El Porcal) using airborne imagery. Limnetica.16(1).
  • EC. 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. Off J Eur Parliam. :1–73.
  • Echavarría-Caballero C, Domínguez-Gómez JA, González-García C, García-García MJ. 2019. Assessment of Landsat 5 images atmospherically corrected with LEDAPS in water quality time series. Can J Remote Sens. 45(5):691–706. https://doi.org/10.1080/07038992.2019.1674136
  • el Serafy GYH, Schaeffer BA, Neely MB, Spinosa A, Odermatt D, Weathers KC, Baracchini T, Bouffard D, Carvalho L, Conmy RN, et al. 2021. Integrating inland and coastal water quality data for actionable knowledge. Remote Sens. 13(15):2899. https://doi.org/10.3390/RS13152899
  • Giardino C, Pepe M, Brivio PA, Ghezzi P, Zilioli E. 2001. Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imagery. Sci Total Environ. 268(1–3):19–29. https://doi.org/10.1016/S0048-9697(00)00692-6
  • Godah W, Szelachowska M, Krynski J. 2018. Application of the PCA/EOF method for the analysis and modelling of temporal variations of geoid heights over Poland. Acta Geod Geophys. 53(1):93–105. https://doi.org/10.1007/s40328-017-0206-8
  • Hannachi A, Jolliffe IT, Stephenson DB. 2007. Empirical orthogonal functions and related techniques in atmospheric science: a review. Int J Climatol. 27(9):1119–1152. https://doi.org/10.1002/joc.1499
  • Hestir EL, Brando VE, Bresciani M, Giardino C, Matta E, Villa P, Dekker AG. 2015. Measuring freshwater aquatic ecosystems: the need for a hyperspectral global mapping satellite mission. Remote Sens Environ. 167:181–195. https://doi.org/10.1016/j.rse.2015.05.023
  • Hicks BJ, Stichbury GA, Brabyn LK, Allan MG, Ashraf S. 2013. Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region. New Zealand Environ Monit Assess. 185(9):7245–7261. https://doi.org/10.1007/s10661-013-3098-2
  • Kim SE, Seo IW, Choi SY. 2017. Assessment of water quality variation of a monitoring network using exploratory factor analysis and empirical orthogonal function. Environ Modell Software. 94:21–35. https://doi.org/10.1016/j.envsoft.2017.03.035
  • Kim SH, Yang CS, Ouchi K. 2015. Spatio-temporal patterns of Secchi depth in the waters around the Korean Peninsula using MODIS data. Estuarine Coastal Shelf Sci. 164:172–182. https://doi.org/10.1016/j.ecss.2015.07.003
  • Li X, Yang C, Zhang H, Wang P, Tang J, Tian Y, Zhang Q. 2021. Identification of abandoned Jujube fields using multi-temporal high-resolution imagery and machine learning. Remote Sens. 13(4):801. https://doi.org/10.3390/rs13040801
  • Liew SC, Chia AS, Kwoh LK. 2010. Spatio-temporal variability of precipitation in Southeast Asia analyzed using the empirical orthogonal function (EOF) technique. International Geoscience and Remote Sensing Symposium (IGARSS), 4701–4704.
  • Liu D, Yu SJ, Xiao QT, Qi TC, Duan HT. 2021. Satellite estimation of dissolved organic carbon in eutrophic Lake Taihu, China. REMOTE Sens Environ. 264:112572. https://doi.org/10.1016/j.rse.2021.112572
  • Lobo F, de L, Nagel GW, Maciel DA, de Carvalho LAS, Martins VS, Barbosa CCF, de Moraes Novo EML. 2021. Algaemap: algae bloom monitoring application for inland waters in Latin America. Remote Sens. 13(15):2874. https://doi.org/10.3390/RS13152874
  • López-Andreu FJ, Erena M, Dominguez-Gómez JA, López-Morales JA. 2021. Sentinel-2 images and machine learning as tool for monitoring of the common agricultural policy: Calasparra rice as a case study. Agronomy. 11(4):621. https://doi.org/10.3390/AGRONOMY11040621
  • Maeda EE, Lisboa F, Kaikkonen L, Kallio K, Koponen S, Brotas V, Kuikka S. 2019. Temporal patterns of phytoplankton phenology across high latitude lakes unveiled by long-term time series of satellite data. Remote Sens Environ. 221:609–620. https://doi.org/10.1016/j.rse.2018.12.006
  • Mollema P, Antonellini M, Gabbianelli G, Laghi M, Marconi V, Minchio A. 2012. Climate and water budget change of a Mediterranean coastal watershed, Ravenna, Italy. Environ Earth Sci. 65(1):257–276. https://doi.org/10.1007/s12665-011-1088-7
  • Mollema P, Antonellini M. 2016. Water and (bio)chemical cycling in gravel pit lakes: a review and outlook. Earth-Sci Rev. 159:247–270. https://doi.org/10.1016/j.earscirev.2016.05.006
  • Mollema P, Stuyfzand P, Juhász-Holterman MHA, van Diepenbeek PMJA, Antonellini M. 2015. Metal accumulation in an artificially recharged gravel pit lake used for drinking water supply. J Geochem Explor. 150:35–51. https://doi.org/10.1016/j.gexplo.2014.12.004
  • Moreno N, García-Avilés J. 1997. Valoración ambiental y caracterización de los ecosistemas acuáticos leníticos del Parque Regional en torno a los ejes de los cursos bajos de los ríos. https://www.researchgate.net/profile/Javier-Garcia-Aviles/publication/297387060_Valoracion_ambiental_y_caracterizacion_de_los_ecosistemas_acuaticos_leniticos_del_Parque_Regional_en_torno_a_los_ejes_de_los_cursos_bajos_de_los_rios_Manzanares_y_Jarama/links/56deb0c408ae46f1e9a0e3eb/Valoracion-ambiental-y-caracterizacion-de-los-ecosistemas-acuaticos-leniticos-del-Parque-Regional-en-torno-a-los-ejes-de-los-cursos-bajos-de-los-rios-Manzanares-y-Jarama.pdf.
  • Mostaza-Colado D, Carreño-Conde F, Rasines-Ladero R, Iepure S. 2018. Hydrogeochemical characterization of a shallow alluvial aquifer: 1 baseline for groundwater quality assessment and resource management. Sci Total Environ. 639:1110–1125. https://doi.org/10.1016/j.scitotenv.2018.05.236
  • Mukadi PM, González-García C. 2021. Time series analysis of climatic variables in peninsular spain. trends and forecasting models for data between 20th and 21st centuries. Climate 2021. 9(7):119. https://doi.org/10.3390/CLI9070119
  • Nas B, Ekercin S, Karabörk H, Berktay A, Mulla DJ. 2010. An application of landsat-5TM image data for water quality mapping in Lake Beysehir, Turkey. Water Air Soil Pollut. 212(1–4):183–197. https://doi.org/10.1007/s11270-010-0331-2
  • Naumenko MA. 2008. Seasonality and trends in the Secchi disk transparency of Lake Ladoga. Hydrobiologia. 599(1):59–65. https://doi.org/10.1007/s10750-007-9198-7
  • OCDE. 1982. OECD: eutrophication of waters. monitoring, assessment and control. 154pp Paris: organisation for economic co-operation and development 1982. Int Revue Der Gesamten Hydrobiol Und Hydrograph. 69(2):200.
  • Pal S, Chakraborty K. 2014. Importance of some physical and chemical characteristics of water bodies in relation to the incidence of zooplanktons: a review. Indian Journal of Social and Natural Sciences. 3:102–116.
  • Paltsev A, Creed IF. 2021. Are northern lakes in relatively intact temperate forests showing signs of increasing phytoplankton biomass? Ecosystems. https://doi.org/10.1007/s10021-021-00684-y
  • Peckenham JM, Thornton T, Whalen B. 2009. Sand and gravel mining: effects on ground water resources in Hancock county, Maine, USA. Environ Geol. 56(6):1103–1114.
  • Persson A. 2017. The story of the Hovmöller diagram: an (almost) eyewitness account. Bull Am Meteorol Soc. 98(5):949–957.
  • Rodrigo M, Rojo C, Segura M, Alonso-Guillén J, Martín M, Vera P. 2015. The role of charophytes in a Mediterranean pond created for restoration purposes. Elsevier. https://www.sciencedirect.com/science/article/pii/S0304377014000692.
  • Seelen LMS, Teurlincx S, Bruinsma J, Huijsmans TMF, van Donk E, Lürling M, de Senerpont Domis LN. 2021. The value of novel ecosystems: disclosing the ecological quality of quarry lakes. Sci Total Environ. 769:144294.
  • Seers BM, Shears NT. 2015. Spatio-temporal patterns in coastal turbidity – long-term trends and drivers of variation across an estuarine-open coast gradient. Estuarine Coastal Shelf Sci. 154:137–151. https://doi.org/10.1016/j.ecss.2014.12.018
  • Shevenell L, Connors KA, Henry CD. 1999. Controls on pit lake water quality at sixteen open-pit mines in Nevada. Appl Geochem. 14(5):669–687. https://doi.org/10.1016/S0883-2927(98)00091-2
  • Søndergaard M, Lauridsen TL, Johansson LS, Jeppesen E. 2018. Gravel pit lakes in Denmark: chemical and biological state. Sci Total Environ. 612:9–17. https://doi.org/10.1016/j.scitotenv.2017.08.163
  • U.S. Geological Survey. 2015. Mineral commodity summaries 2015 mineral commodity summaries 2015. US Geological Survey. http://www.usgs.gov/pubprod%0Ahttps://minerals.usgs.gov/minerals/pubs/commodity/phosphate_rock/mcs-2015-phosp.pdf.
  • van Buuren S, Groothuis-Oudshoorn K. 2011. mice: multivariate imputation by chained equations in R. J Stat Soft. 45(3):1–67. https://doi.org/10.18637/jss.v045.i03
  • Vucic JM, Cohen RS, Gray DK, Murdoch AD, Shuvo A, Sharma S. 2019. Young gravel-pit lakes along Canada’s Dempster highway: how do they compare with natural lakes? Arctic Antarctic Alpine Res. 51(1):25–39. https://doi.org/10.1080/15230430.2019.1565854
  • Wang R, Yan X, Niu Z, Chen W. 2021. Long-term changes in inland water surface temperature across china based on remote sensing data. J Hydrometeorol. 22(2):523–532. https://doi.org/10.1175/JHM-D-20-0104.1
  • Weeks S, Werdell PJ, Schaffelke B, Canto M, Lee Z, Wilding JG, Feldman GC. 2012. Satellite-derived photic depth on the Great Barrier Reef: spatio-temporal patterns of water clarity. Remote Sensing. 4(12):3781–3795. https://doi.org/10.3390/rs4123781
  • Yoder JA, Schollaert SE, O'Reilly JE. 2002. Climatological phytoplankton chlorophyll and sea surface temperature patterns in continental shelf and slope waters off the northeast U.S. coast. Limnol Oceanogr. 47(3):672–682. https://doi.org/10.4319/lo.2002.47.3.0672
  • Ziauddin G, Chakraborty SK, Jaiswar AK, Bhaumik U. 2013. Productivity study in relation to temperature and transparency in the euphotic zone of selected tropical freshwater floodplain wetlands of West Bengal. N Save Nature to Survive (Vol. 7, Issue 4). https://www.researchgate.net/publication/280832042.