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Temporal Variations in Chemical Proprieties of Waterbodies within Coastal Polders: Forecast Modeling for Optimizing Water Management Decisions

Author

Listed:
  • Davor Romić

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

  • Marko Reljić

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

  • Marija Romić

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

  • Marina Bagić Babac

    (Department of Applied Computing, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

  • Željka Brkić

    (Department of Hydrogeology and Engineering Geology, Croatian Geological Survey, Milana Sachsa 2, 10000 Zagreb, Croatia)

  • Gabrijel Ondrašek

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

  • Marina Bubalo Kovačić

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

  • Monika Zovko

    (Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia)

Abstract

In polder-type land, water dynamics are heavily influenced by the artificial maintenance of water levels. Polders are low-lying areas of land that have been reclaimed from the sea or from freshwater bodies and are protected from flooding by dikes or other types of flood-protection structures. The water regime in polders is typically managed using a system of canals, pumps, and sluices to control the flow of water in and out of the area. In this study, the temporal changes in water salinity in the polder-type agricultural floodplain within the Neretva River Delta (NRD), Croatia, were analyzed by applying multivariate statistics and forecast modelling. The main aim of the study was to test the model that can be used in practice to forecast, primarily, water suitability for irrigation in a coastal low-lying agricultural catchment. The specific aim of this study was to use hydrochemistry data series to explain processes in water salinity dynamics and to test the model which may provide accurate salinity prediction, or finally select the conditions in which the model can be applied. We considered the accuracy of the model, and it was validated using independent data sets. To describe different patterns of chemical changes in different water classes due to their complex hydrological connectivity, multivariate statistics (PCA) were coupled with time-series analysis and Vector Autoregression (VAR) model forecasting. The multivariate statistics applied here did not indicate a clear connection between water salinity of the surface-water bodies and groundwater. The lack of correlation lies in the complex hydrological dynamics and interconnectivity of the water bodies highly affected by the artificial maintenance of the groundwater level within the polder area, as well as interventions in the temporal release of freshwater into the drainage canal network. Not all individual water classes contributed equally to the dominant patterns of ionic species identified by PCA. Apparently, land use and agricultural management practices in the different polders lead to uneven water chemistry and the predominant contributions of specific ions, especially nutrients. After applying the Granger causality test to reveal the causal information and explain hidden relationships among the variables, only two surface-water and two groundwater monitoring locations displayed a strong causal relationship between water electrical conductivity (EC w ) as an effect and sea level as a possible cause. The developed models can be used to evaluate and emphasize the unique characteristics and phenomena of low-lying land and to communicate their importance and influence to management authorities and agricultural producers in managing and planning irrigation management in the wider Mediterranean area.

Suggested Citation

  • Davor Romić & Marko Reljić & Marija Romić & Marina Bagić Babac & Željka Brkić & Gabrijel Ondrašek & Marina Bubalo Kovačić & Monika Zovko, 2023. "Temporal Variations in Chemical Proprieties of Waterbodies within Coastal Polders: Forecast Modeling for Optimizing Water Management Decisions," Agriculture, MDPI, vol. 13(6), pages 1-27, May.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1162-:d:1159923
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    References listed on IDEAS

    as
    1. Rivas-Tabares, David & Tarquis, Ana M. & Willaarts, Bárbara & De Miguel, Ángel, 2019. "An accurate evaluation of water availability in sub-arid Mediterranean watersheds through SWAT: Cega-Eresma-Adaja," Agricultural Water Management, Elsevier, vol. 212(C), pages 211-225.
    2. Liwei Tang & Ke Li & Pinrong Jia, 2020. "Impact of Environmental Regulations on Environmental Quality and Public Health in China: Empirical Analysis with Panel Data Approach," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    3. N. Colombani & A. Osti & G. Volta & M. Mastrocicco, 2016. "Impact of Climate Change on Salinization of Coastal Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2483-2496, May.
    4. Lê, Sébastien & Josse, Julie & Husson, François, 2008. "FactoMineR: An R Package for Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i01).
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    6. Wang, Yong & Zhao, Yong & Yan, Long & Deng, Wei & Zhai, Jiaqi & Chen, Minjian & Zhou, Fei, 2022. "Groundwater regulation for coordinated mitigation of salinization and desertification in arid areas," Agricultural Water Management, Elsevier, vol. 271(C).
    7. Marko Reljić & Marija Romić & Davor Romić & Gordon Gilja & Vedran Mornar & Gabrijel Ondrasek & Marina Bubalo Kovačić & Monika Zovko, 2023. "Advanced Continuous Monitoring System—Tools for Water Resource Management and Decision Support System in Salt Affected Delta," Agriculture, MDPI, vol. 13(2), pages 1-19, February.
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    Cited by:

    1. Gerard Arbat & Daniele Masseroni, 2024. "The Use and Management of Agricultural Irrigation Systems and Technologies," Agriculture, MDPI, vol. 14(2), pages 1-5, January.

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