Volume 19 Issue 2
May  2026
Turn off MathJax
Article Contents
Anabela Rebelo, Ana Mariano, Samuel Fernandes, Andreia Franco, Felisbina Quadrado. 2026: A novel semi-quantitative model for environmental risk assessment in Portuguese surface water catchments: Supporting compliance with the European Drinking Water Directive. Water Science and Engineering, 19(2): 172-182. doi: 10.1016/j.wse.2026.01.003
Citation: Anabela Rebelo, Ana Mariano, Samuel Fernandes, Andreia Franco, Felisbina Quadrado. 2026: A novel semi-quantitative model for environmental risk assessment in Portuguese surface water catchments: Supporting compliance with the European Drinking Water Directive. Water Science and Engineering, 19(2): 172-182. doi: 10.1016/j.wse.2026.01.003

A novel semi-quantitative model for environmental risk assessment in Portuguese surface water catchments: Supporting compliance with the European Drinking Water Directive

doi: 10.1016/j.wse.2026.01.003
  • Received Date: 2025-08-20
  • Accepted Date: 2026-01-05
  • This study developed a novel semi-quantitative model for environmental risk assessment in surface water (SW) catchment areas (CAs) in Portugal, designed to assist authorities in complying with the European Drinking Water Directive (DWD). The model integrates a four-phase risk assessment framework with multicriteria decision analysis (MCDA), supported by a geographic information system (GIS) for mapping and analyzing spatial data on pollution hazards and water resources characteristics. GIS facilitates direct data access and incorporates elements from relevant river basin management plans (RBMPs), ensuring the use of updated and validated information. The model evaluates risks from both point and diffuse pollution sources, demonstrating its versatility and effectiveness through successful applications in two case studies: the Lever Montante and Odelouca CAs in Portugal. The assessment yielded a moderate risk classification for the Lever Montante CA and a very low risk for the Odelouca CA. These results provide clear and actionable insights for risk management and demonstrate the capacity of the model to differentiate risk levels between CAs. The findings of this study are consistent with SW monitoring data from the basin, adhering to critical data parameters without overstatement or misrepresentation of significant values, thereby enabling a reliable and balanced risk representation. This tool offers Portuguese authorities a systematic and repeatable method for conducting periodic risk assessments and optimizing monitoring programs, ensuring ongoing compliance with the DWD while effectively safeguarding water resources.

     

  • loading
  • [1]
    Abdullah, M.F., Siraj, S., Hodgett, R.E., 2021. An overview of multi-criteria decision analysis (MCDA) application in managing water-related disaster events: Analyzing 20 years of literature for flood and drought events. Water 13(10), 1358. https://doi.org/10.3390/w13101358.
    [2]
    Andries, D.M., Garrido, A., De Stefano, L., 2025. Addressing drivers and data gaps in Spain's non-compliance of drinking water quality standards. Science of The Total Environment 963, 178412. https://doi.org/10.1016/j.scitotenv.2025.178412.
    [3]
    Portuguese Environment Agency (APA), 2024. River Basin Management Plans. APA, Amadora (in Portuguese). https://apambiente.pt/agua/planos-de-gestao-de-regiao-hidrografica.
    [4]
    Cantoni, B., Penserini, L., Vries, D., Dingemans, M.M.L., Bokkers, B.G.H., Turolla, A., Smeets, P.W.M.H., Antonelli, M., 2021. Development of a quantitative chemical risk assessment (QCRA) procedure for contaminants of emerging concern in drinking water supply. Water Research 194, 116911. https://doi.org/10.1016/j.watres.2021.116911.
    [5]
    Chernysh, Y., Stejskalova, L., Soldan, P., Lai, F.Y., Khan, U.A., Lundborg, C.S., Giamberini, L., Minguez, L., Monte, M.C., Blanco, A., et al., 2025. Risk assessment as a tool to improve water resource management. Water Resources Management 39(1), 47-63. https://doi.org/10.1007/s11269-024-03982-x.
    [6]
    Chhipi-Shrestha, G., Hewage, K., Sadiq, R., 2017. Microbial quality of reclaimed water for urban reuses: Probabilistic risk-based investigation and recommendations. Science of The Total Environment 576, 738-751. https://doi.org/10.1016/j.scitotenv.2016.10.105.
    [7]
    Choo, M., Yoon, D.K., 2024. A meta-analysis of the relationship between disaster vulnerability and disaster damage. International Journal of Disaster Risk Reduction 102, 104302. https://doi.org/10.1016/j.ijdrr.2024.104302.
    [8]
    Das, A., 2025. An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment 3(1), 117. https://doi.org/10.1007/s44274-025-00327-2.
    [9]
    Dettori, M., Arghittu, A., Deiana, G., Castiglia, P., Azara, A., 2022. The revised European Directive 2020/2184 on the quality of water intended for human consumption. A step forward in risk assessment, consumer safety and informative communication. Environmental Research 209, 112773. https://doi.org/10.1016/j.envres.2022.112773.
    [10]
    Dise, N.B., Wright, R.F., 1995. Nitrogen leaching from European forests in relation to nitrogen deposition. Forest Ecology and Management 71(1), 153-161. https://doi.org/10.1016/0378-1127(94)06092-W.
    [11]
    European Union (EU), 2020. Directive (EU) 2020/2184 of the European Parliament and of the Council of 16 December 2020 on the quality of water intended for human consumption (recast). Offical Journal of the European Union L 435.
    [12]
    European Union (EU), 2024. Directive (EU) 2024/3019 of the European Parliament and of the Council of 27 November 2024 concerning urban wastewater treatment (recast). Offical Journal of the European Union L 2024/3019.
    [13]
    Fadina, T., Liu, Y., Wang, R., 2024. A framework for measures of risk under uncertainty. Finance and Stochastics 28(2), 363-390. https://doi.org/10.1007/s00780-024-00528-2.
    [14]
    Farokhi, S., Najarchi, M., Mazaheri, H., Shabanlou, S., 2025. Dynamic coupling of qualitative-quantitative models for operation of water resources based on environmental criteria. Applied Water Science 15(2), 21. https://doi.org/10.1007/s13201-024-02356-3.
    [15]
    Geng, G., Wardlaw, R., 2013. Application of multi-criterion decision making analysis to integrated water resources management. Water Resources Management 27(8), 3191-3207. https://doi.org/10.1007/s11269-013-0343-y.
    [16]
    Goodwin, D., Raffin, M., Jeffrey, P., Smith, H.M., 2015. Applying the water safety plan to water reuse: Towards a conceptual risk management framework. Environmental Science: Water Research & Technology 1, 709-722. https://doi.org/10.1039/c5ew00070j.
    [17]
    Guan, W., Liu, Q., Dong, C., 2022. Risk assessment method for industrial accident consequences and human vulnerability in urban areas. Journal of Loss Prevention in the Process Industries 76, 104745. https://doi.org/10.1016/j.jlp.2022.104745.
    [18]
    Guo, G., Duan, R., 2022. A new method to determine the scale range of environmental damage caused by water pollution accidents. Water Supply 22(4), 3968-3979. https://doi.org/10.2166/ws.2022.027.
    [19]
    International Organization for Standardization (ISO), 2020. Guidelines for Treated Wastewater Use for Irrigation Projects - Part 1: The Basis of a Reuse Project for Irrigation. ISO, Geneve.
    [20]
    Jensen, R.C., Hansen, H., 2020. Selecting appropriate words for naming the rows and columns of risk assessment matrices. International Journal of Environmental Research and Public Health 17(15), 5521. https://doi.org/10.3390/ijerph17155521.
    [21]
    Jirka, G.H., Bleninger, T., Burrows, R., Larsen, T., 2004. Management of point source discharges into rivers: Where do environmental quality standards in the new EC-water framework directive apply? International Journal of River Basin Management 2(3), 225-233. https://doi.org/10.1080/15715124.2004.9635234.
    [22]
    Josefsson, H., 2018. The Environmental Liability Directive, the Water Framework Directive and the definition of ‘water damage’. Environmental Law Review 20(3), 151-162. https://doi.org/10.1177/1461452918789814.
    [23]
    Kombo Mpindou, G.O.M., Escuder Bueno, I., Chorda Ramon, E., 2022. Risk analysis methods of water supply systems: Comprehensive review from source to tap. Applied Water Science 12(4), 56. https://doi.org/10.1007/s13201-022-01586-7.
    [24]
    Kundu, D., Dutta, D., Joseph, A., Jana, A., Samanta, P., Bhakta, J.N., Alreshidi, M.A., 2024. Safeguarding drinking water: A brief insight on characteristics, treatments and risk assessment of contamination. Environmental Monitoring and Assessment 196(2), 180. https://doi.org/10.1007/s10661-024-12311-z.
    [25]
    Li, L., Dong, Y., Chen, Y., Jiao, J., Zou, X., 2022. A new method for environmental risk assessment of pollutants based on multi-dimensional risk factors. Toxics 10(11), 659. https://doi.org/10.3390/toxics10110659.
    [26]
    Luo, X., Kou, C., Wang, Q., 2022. Optimal fertilizer application reduced nitrogen leaching and maintained high yield in wheat-maize cropping system in North China. Plants 11(15), 1963. https://doi.org/10.3390/plants11151963.
    [27]
    Lyu, H.-M., Yin, Z.-Y., 2023. An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong. Sustainable Cities and Society 91, 104427. https://doi.org/10.1016/j.scs.2023.104427.
    [28]
    Markiewicz, A., Bjorklund, K., Eriksson, E., Kalmykova, Y., Stromvall, A.-M., Siopi, A., 2017. Emissions of organic pollutants from traffic and roads: Priority pollutants selection and substance flow analysis. Science of The Total Environment 580, 1162-1174. https://doi.org/10.1016/j.scitotenv.2016.12.074.
    [29]
    Marshall, R., Fischer, T.B., 2005. Best practice use of SEA - Industry, energy and sustainable development. In: Schmidt, M., Joao, E., Albrecht, E. (Eds.), Implementing Strategic Environmental Assessment. Springer, Berlin, Heidelberg.
    [30]
    Mazziotta, M., Pareto, A., 2021. Everything you always wanted to know about normalization (but were afraid to ask). Rivista Italiana di Economia Demografia e Statistica 75 (1), 41-52.
    [31]
    Megharaj, M., Dillon, P., Naidu, R., Kookana, R., Correll, R., Wenzel, W.W., 2020. Pollution: Point source. In: Wang, Y. (Ed.), Landscape and Land Capacity (2nd Edition). CRC Press, Boca Raton.
    [32]
    Osman, S.A., Das, J., 2023. GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia. SN Applied Sciences 5(5), 134. https://doi.org/10.1007/s42452-023-05360-5.
    [33]
    Pallavi, S., Yashas, S.R., Anilkumar, K.M., Shahmoradi, B., Shivaraju, H.P., 2021. Comprehensive understanding of urban water supply management: Towards sustainable water-socio-economic-health-environment nexus. Water Resources Management 35(1), 315-336. https://doi.org/10.1007/s11269-020-02734-x.
    [34]
    Rebelo, A., Ferra, I., Goncalves, I., Marques, A.M., 2014. A risk assessment model for water resources: Releases of dangerous and hazardous substances. Journal of Environmental Management 140, 51-59. https://doi.org/10.1016/j.jenvman.2014.02.025.
    [35]
    Rebelo, A., Bento Amaro, A., Quadrado, F., 2022. Water reuse: A risk assessment model for water resources. KnE Materials Science 7(1), 193-203. https://doi.org/10.18502/kms.v7i1.11623.
    [36]
    Rebelo, A., Franco, A., Quadrado, F., Reis, V., Batista, S., Garcia, A. I., Ferreira, R., Quintas, A., Marques, A.M., 2024. Substantial damage to surface water in the context of environmental crimes. Environmental Science: Advances 3(3), 422-435. https://doi.org/10.1039/D3VA00381G.
    [37]
    Rebelo, A., Farabegoli, G., 2025. Water circularity index: A novel approach for authorities and operators. Chemosphere 377, 144366. https://doi.org/10.1016/j.chemosphere.2025.144366.
    [38]
    Ren, K., Huang, S., Huang, Q., Wang, H., Leng, G., Fang, W., Li, P., 2020. Assessing the reliability, resilience and vulnerability of water supply system under multiple uncertain sources. Journal of Cleaner Production 252, 119806. https://doi.org/10.1016/j.jclepro.2019.119806.
    [39]
    Rihab, R., Gannouni, S., Rebai, N., 2024. A comparative study of different methods of multi-criteria decision analysis (MCDA) with spatial reference to select suitable sites for treated wastewater of irrigated perimeters. Sustainable Water Resources Management 10(4), 147. https://doi.org/10.1007/s40899-024-01120-4.
    [40]
    Saaty, T., 1980. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York.
    [41]
    Saaty, T., Sodenkamp, M., 2008. Making decisions in hierarchic and network systems. International Journal of Applied Decision Science 1(1), 24-79. https://doi.org/10.1504/IJADS.2008.017952.
    [42]
    Tiemeyer, B., Kahle, P., 2014. Nitrogen and dissolved organic carbon (DOC) losses from an artificially drained grassland on organic soils. Biogeosciences 11(15), 4123-4137. https://doi.org/10.5194/bg-11-4123-2014.
    [43]
    Vilao, R., Venancio, C., Lopes, M.A., Albergaria, T., 2024. REA: State of The Environment Report 2024 - Highlights. Portuguese Environment Agency, Amadora.
    [44]
    Wang, Q., Su, M., Zeng, L., Chen, H., 2022. A new method to assist decision-making of water environmental emergency in expressway region. International Journal of Environmental Research and Public Health 19(16), 10043. https://doi.org/10.3390/ijerph191610043.
    [45]
    Wiering, M., Kirschke, S., Akif, N.U., 2023. Addressing diffuse water pollution from agriculture: Do governance structures matter for the nature of measures taken? Journal of Environmental Management 332, 117329. https://doi.org/10.1016/j.jenvman.2023.117329.
    [46]
    Wolfram, J., Stehle, S., Bub, S., Petschick, L.L., Schulz, R., 2021. Water quality and ecological risks in European surface waters - Monitoring improves while water quality decreases. Environment International 152, 106479. https://doi.org/10.1016/j.envint.2021.106479.
    [47]
    Yang, M., Shi, L., Liu, B., 2022. Risks assessment and driving forces of urban environmental accident. Journal of Cleaner Production 340, 130710. https://doi.org/10.1016/j.jclepro.2022.130710.
    [48]
    Zhao, Z., Gil, P., Loureiro, J., Petrella, L., Henriques, J., 2024. Reliability assessment of models for risk stratification: A knowledge-based approach. In: Proceedings of the 2024 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, Abu Dhabi, pp. 564-571. https://doi.org/10.1109/ICDMW65004.2024.00078.
    [49]
    Zheng, Y., Wang, Q., Zhang, X., Yu, J., Li, C., Chen, L., Liu, Y., 2022. Nitrogen and phosphorus retention risk assessment in a drinking water source area under anthropogenic activities. Remote Sensing 14(9), 2070. https://doi.org/10.3390/rs14092070.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)

    Article Metrics

    Article views (693) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return