References

  1. I. Zimoch, Operational safety of the water supply system under conditions of water quality variations in the waterpipe network, Ochrona Środowiska, Environ. Prot., 31 (2009) 51–55 (in Polish).
  2. I. Zimoch, J. Szymik-Gralewska, Risk assessment methods of a water supply system in terms of reliability and operation cost, WIT Trans. Built Environ., 139 (2014) 51–62.
  3. L.A. Al‑Maliki, S.K. Al‑Mamoori, I.A. Jasim, K. El‑Tawel, N. Al‑Ansari, F.G. Comair, Perception of climate change effects on water resources: Iraqi undergraduates as a case study, Arabian J. Geosci., 15 (2022) 503, doi: 10.1007/s12517-022-09695-y.
  4. N. Kumar, V. Poonia, B.B. Gupta, M.K. Goyal, A novel framework for risk assessment and resilience of critical infrastructure towards climate change, Technol. Forecasting Social Change, 165 (2021) 120532, doi: 10.1016/j.techfore.2020.120532.
  5. S. Salimi, S.A.A.A.N. Almuktar, M. Scholz, Impact of climate change on wetland ecosystems: a critical review of experimental wetlands, J. Environ. Manage., 286 (2021) 112160, doi: 10.1016/j.jenvman.2021.112160.
  6. I. Zimoch, J. Paciej, Spatial risk assessment of drinking water contamination by nitrates from agricultural areas in the Silesia province, Desal. Water Treat., 57 (2016) 1084–1097.
  7. G. Konapala, A.K. Mishra, Y. Wada, M.E. Mann, Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation, Nat. Commun., 11 (2020) 3044, doi: 10.1038/s41467-020-16757-w.
  8. European Environment Agency, Worst Seasonal Water Scarcity Conditions for European Countries in 2019, Measured by the Water Exploitation Index Plus (WEI+), Report 2023. Available at https://www.eea.europa.eu/data-and-maps/figures/worst-seasonal-water-scarcity-conditions
  9. World Meteorological Organization, State of the Climate in Europe 2022, World Meteorological Organization (WMO), WMO-No. 1320, Geneva, 2023.
  10. European Environment Agency, Drought Impact on Ecosystems in Europe - 8th EAP, 2023. Available at https://www.eea.europa.eu/en/analysis/indicators/drought-impact-on-ecosystemsin-europe
  11. European Environment Agency, Water Resources Across Europe — Confronting Water Stress: An Updated Assessment, EEA Report, 12/2021, European Environment Agency, Luxembourg, 2021.
  12. Eurostat, Renewable Freshwater Resources – Long Term Annual Averages, Data Browser (Accessed on 12/12/2023). https://ec.europa.eu/eurostat/databrowser/view/env_wat_ltaa/ default/table?lang=en
  13. A. Psomas, G. Bariamis, S. Roy, J. Rouillard, U. Stein, Study of the Impacts of Pressures on Groundwater in Europe: Comparative Study on Quantitative and Chemical Status of Groundwater Bodies: Service Contract No 3415/B2020/ EEA.58185, European Environment Agency, 2021.
  14. Institute of Meteorology and Water Management - National Research Institute, Statement from the IMWM-PIB Press Office, Hydrological Situation in Poland - DROUGHT, Warsaw 2022, (in Polish). Available at https://www.imgw.pl/sites/default/files/2022-05/imgw_0512-sytuacja-hydrologiczna-w-polscesusza.pdf
  15. Regulation of the Polish Minister of Infrastructure of 15 July 2021 Regarding the Adoption of the Plan for Counteracting the Effects of Drought, Journal of Laws 2021, Item 1615. Available at https://dziennikustaw.gov.pl/D2021000161501.pdf
  16. Polish Ministry of Infrastructure, Project: Investment Program for Improving the Quality and Reducing Losses of Drinking Water by People, Project No.: POIS.02.01.00-00-0001/2020, Report, Cracow 2021 (in Polish). https://www.gov.pl/web/ infrastruktura/przyjeto-program-inwestycyjny-w-zakresiepoprawy-jakosci-i-ograniczenia-strat-wody-przeznaczonejdo-spozycia-przez-ludzi
  17. 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, OJ L 435, 23.12.2020, 1–62.
  18. U. Jüttner, H. Peck, M. Christopher, Supply chain risk management: outlining an agenda for future research, Int. J. Logist. Res. Appl., 6 (2003) 197–210.
  19. P.K. Marhavilas, D. Koulouriotis, V. Gemeni, Risk analysis and assessment methodologies in the work sites: on a review, classification and comparative study of the scientific literature of the period 2000–2009, J. Loss Prev. Process Ind., 24 (2011) 477–523.
  20. I. Mohammadfam, S. Mahmoudi, A. Kianfar, Comparative safety assessment of chlorination unit in Tehran treatment plants with HAZOP & ETBA techniques, Procedia Eng., 45 (2012) 27–30.
  21. S. Sikandar, S. Ishtiaque, N. Soomro, Hazard and operability (HAZOP) study of wastewater treatment unit producing biohydrogen, Sindh. Univ. Res. J-SURJ (Sci. Ser.), 48 (2016) 131–136.
  22. T. Kletz, Hazop and Hazan Identifying and Assessing Process Industry Hazards, 4th ed., CRC Press, Boca Raton, 2018.
  23. S.O. Hansson, T. Aven, Is risk analysis scientific?, Risk Anal., 34 (2014) 1173–1183.
  24. U. Hauptmanns, M. Marx, T. Knetsch, GAP - a fault-tree based methodology for analyzing occupational hazards, J. Loss Prev. Process Ind., 18 (2005) 107–113.
  25. B. Tchórzewska-Cieślak, K. Pietrucha-Urbanik, D. Papciak, An approach to estimating water quality changes in water distribution systems using fault tree analysis, Resources, 8 (2019) 1–162.
  26. K. Boryczko, D. Szpak, J. Żywiec, B. Tchórzewska-Cieślak, The use of a fault tree analysis (FTA) in the operator reliability assessment of the critical infrastructure on the example of water supply system, Energies, 15 (2022) 4416, doi: 10.3390/en15124416.
  27. A Lindhe, L. Rosén, T. Norberg, O. Bergstedt, Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems, Water Res., 43 (2009) 1641–1653.
  28. S. Abedzadeh, A. Roozbahani, A. Heidari, Risk assessment of water resources development plans using fuzzy fault tree analysis, Water Res. Manage., 34 (2020) 2549–2569.
  29. G.K. Beim, B.F. Hobbs, Event tree analysis of lock closure risks, J. Water Res. Plann. Manage., 123 (1997) 169–178.
  30. Y. Yang, Y. Hu, J. Zheng, A decision tree approach to the risk evaluation of urban water distribution network pipes, Safety, 6 (2020) 1–9.
  31. I. Zimoch, E. Szymura, K. Moraczewska-Majkut, I.-Y. Richard Yeh, The Event Tree Using in Identification of THMs’ Formation in Water Supply System, Z. Dymaczewski, J. Jeż- Walkowiak, M. Nowak, Eds., Water Supply and Water Quality, Preceding PZITS, Poznań, 2014, pp. 545–558.
  32. J.R. Santos, S.T. Pagsuyoin, L.C. Herrera, R.R. Tan, K.D. Yu, Analysis of drought risk management strategies using dynamic inoperability input–output modeling and event tree analysis, Environ. Syst., 34 (2014) 492–506.
  33. T. Rosqvist, R. Molarius, H. Virta, A. Perrels, Event tree analysis for flood protection - an exploratory study in Finland, Reliab. Eng. Syst., 112 (2013) 1–7.
  34. B.C. Ezell, J.V. Farr, I. Wiese, Infrastructure risk analysis of municipal water distribution system, J. Infrastruct. Syst., 6 (2000) 118, doi: 10.1061/(ASCE)1076-0342(2000)6:3(118).
  35. E. Doménech, S. Martorell, G.O.M. Kombo-Mpindou, J. Macián-Cervera, I. Escuder-Bueno, Risk assessment of Cryptosporidium intake in drinking water treatment plant by a combination of predictive models and event-tree and fault-tree techniques, Sci. Total Environ., 838 (2022) 1–9.
  36. M. Gheibi, M. Karrabi, M. Eftekhari, Designing a smart risk analysis method for gas chlorination units of water treatment plants with combination of failure mode effects analysis, Shannon entropy, and petri net modeling, Ecotoxicol. Environ. Saf., 171 (2019) 600–608.
  37. H. Hwang, K. Lansey, D.R. Quintanar, Resilience-based failure mode effects and criticality analysis for regional water supply system, J. Hydroinf., 17 (2014) 193–210.
  38. G. Doyle, M. Grabinsky, Applying GIS to a water main corrosion study, J. AWWA, 95 (2003) 90–104.
  39. R. Booth, J. Rogers, Using GIS technology to manage infrastructure capital assets, J. AWWA, 93 (2001) 62–68.
  40. I. Zimoch, J. Paciej, Spatial risk assessment of drinking water contamination by nitrates from agricultural areas in the Silesia province, Desal. Water Treat., 57 (2016) 1084–1097.
  41. I. Zimoch, J. Paciej, Use of water turbidity as an identifier of microbiological contamination in the risk assessment of water consumer health, Desal. Water Treat., 199 (2020) 499–511.
  42. I. Zimoch, Hazardous event analysis of microbiological contamination in risk management of large water supply systems, Desal. Water Treat., 247 (2022) 72–81.
  43. G.O.M.K. Mpindou, I.E. Bueno, E.Ch. Ramón, Risk analysis methods of water supply systems: comprehensive review from source to tap, Appl. Water Sci., 56 (2022) 1–20.
  44. D. Fu, Y. Li, G. Huang, A fuzzy-Markov-chain-based analysis method for reservoir operation, Stoch. Environ. Res. Risk Assess., 26 (2012) 375–391.
  45. T.Ch. Chiam, Y. Yih, C.A. Mitchell, Control policies for a watertreatment system using the Markov decision process. Part 2: simulation and analysis, Habitation, 12 (2009) 27–32.
  46. H. Shi, X. Wang, H. Guo, H. Hao, Risk assessment models to investigate the impact of emergency on a water supply system, Water Supply, 20 (2020) 3542–3556.
  47. J.I. Sempewo, L. Kyokaali, Prediction of the future condition of a water distribution network using a Markov based approach: a case study of Kampala water, Procedia Eng., 154 (2016) 374–383.
  48. Z. Li, H. Feng, Y. Liang, N. Xu, S. Nie, H. Zhang, A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo, Int. J. Crit. Infrastruct., 27 (2019) 1–9.
  49. J. Zhang, X. Shi, J. Li, Stochastic simulation of natural water supply and demand in irrigation district and risk evaluation, J. Hydrol. Eng., 24 (2019) 1–12.
  50. E. Goharian, Z. Zahmatkesh, S. Sandoval-Solis, Uncertainty propagation of hydrologic modeling in water supply system performance: application of Markov chain Monte Carlo method, J. Hydrol. Eng., 23 (2018) 1–9.
  51. M. Tabesh, A. Roozbahani, F. Hadigol, E. Ghaemi, Risk assessment of water treatment plants using fuzzy fault tree analysis and Monte Carlo simulation, Iran. J. Sci. Technol.- Trans. Civ. Eng., 46 (2022) 643–658.
  52. B. Barbeau, P. Payment, J. Coallier, B. Clément, M. Prévost, Evaluating the risk of infection from the presence of giardia and cryptosporidium in drinking water, Quant. Microbiol., 2 (2000) 37–54.
  53. G. Medema, J.F. Loret, T.-A. Stenstrom, N. Ashbolt, MICRORISK-Microbiological Risk Assessment: A Scientific Basis for Managing Drinking Water Safety From Source to Tap, Final Report, Quantitative Microbial Risk Assessment in the Water Safety Plan, Project Co-funded by the European Commission Under the 5-th Framework Programme, Theme 4: Energy, Environment and Sustainable Development, 2006 (Contract EVK1-CT-2002–00123).
  54. J. Schijven, J. Derx, A.M. de Roda Husman, A.P. Blaschke, A.H. Farnleitner, QMRAcatch: microbial quality simulation of water resources including infection risk assessment, J. Environ. Qual., 44 (2015) 1491–1502.
  55. J. Kenza, B. Barbeau, A. Carrière, R. Desjardins, M. Prévost, Including operational data in QMRA model: development and impact of model inputs, J. Water Health, 7 (2009) 77–95.
  56. S.R. Petterson, Application of a QMRA framework to inform selection of drinking water interventions in the developing context, Risk Anal., 36 (2016) 203–214.
  57. K. Lane, S.E. Hrudey, A critical review of risk matrices used in water safety planning: improving risk matrix construction, J. Water Health, 21 (2023) 1795–1811.
  58. R. Nunes, E. Arraut, M. Pimentel, Risk assessment model for the renewal of water distribution networks: a practical approach, Water, 15 (2023) 1509, doi: 10.3390/w15081509.
  59. J.R. Rak, B. Tchórzewska-Cieślak, K. Pietrucha-Urbanik, A hazard assessment method for waterworks systems operating in self-government units, Int. J. Environ. Res. Public Health, 16 (2019) 1–12.
  60. Budiyono, P. Ginandjar, L.D. Saraswati, D.R. Pangestuti, Martini, S.P. Jati, Z. Rahfiludin, Risk assessment of drinking water supply system in the Tidal Inundation Area of Semarang – Indonesia, Procedia Environ. Sci., 23 (2015) 93–98.
  61. I. Zimoch, J. Paciej, Spatial risk assessment of health hazards from Legionella spp. presence in hot water systems in Silesia Province, Ochrona Środowiska, Environ. Prot., 36 (2014) 23–28 (in Polish).
  62. I. Zimoch, J. Paciej, Health risk assessment of swimming pool users from the effects of Legionella spp. contamination of water, J. Ecol. Eng., 21 (2020) 178–189.
  63. J. Rucka, T. Suchanek, Risk analysis of the drinking water supply system of the small village, MM Sci. J., (2016) 1497–1501.
  64. J. Rak, K. Boryczko, Two-Parameter Method for Assessing the Water Resources Diversification of Collective Water Supply Systems Using Shannon-Weaver Indicator, Z. Dymaczewski, J. Jeż-Walkowiak, A. Urbaniak, Eds., Water Supply and Water Quality, Polish Association of Sanitary Engineers and Technicians, Greater Poland Branch, Poznań, 2016, pp. 345–369 (in Polish).
  65. K. Boryczko, J. Rak, Assessment of the diversification of water supply in selected cities using the two-parameter method using the Pielou index, INSTAL, 6 (2016) 60–63 (in Polish).
  66. J. Rak, K. Boryczko, Assessment of Water Supply Diversification Using the Pielou Index, M. Pawlowska, L. Pawlowski, Eds., Environmental Engineering V, CRC Press, London, 2017, pp. 53–58.
  67. E.C. Pielou, Population and Community Ecology: Principles and Methods, Gordon and Breach, New York, 1974.
  68. Y. Peng, M. Fan, J. Song, T. Cui, R. Li, Assessment of Plant Species Diversity Based on Hyperspectral Indices at a Fine Scale, Scientific Reports, 2018.
  69. C. Palaghianu, A tool for computing diversity and consideration on differences between diversity indices, J. Environ. Eng. Landscape Manage., 5 (2014) 78–82.
  70. G. Türkmen, N. Kazanci, Applications of various biodiversity indices to benthic macroinvertebrate assemblages in streams of a national park in Turkey, Int. Rev. Hydrobiol., 3 (2010) 111–125.
  71. M.A.S. Jewel, M.A. Haque, R. Khatun, M.S. Rahman, A comparative study of fish assemblage and diversity indices in two different aquatic habitats in Bangladesh: Lakhandaha Wetland and Atari River, Jordan J. Biol. Sci., 11 (2018) 427–434.
  72. C. Ricotta, M.L. Carranza, G. Avena C. Blasi, Quantitative comparison of the diversity of landscapes with actual vs. potential natural vegetation, Appl. Veg. Sci., 3 (2000) 157–162.
  73. M. Smale, E.C.H. Meng, J.P. Brennan, R. Hu, Using Ecological Indices and Economics to Explain Diversity in a Wheat Crop: Examples From Australia and China, 2000 Conference (44th), January 23–25, 2000, Australian Agricultural and Resource Economics Society, Sydney, Australia 123732.
  74. S. Harnphattananusorn, T. Puttitanun, Generation gap and its impact on economic growth, Heliyon, 7 (2021) e07160, doi: 10.1016/j.heliyon.2021.e07160.
  75. L.V. Bystrykh, M.E. Belderbos, Measures of clonal hematopoiesis: are we missing something?, Front. Med., 9 (2022) 1–9.
  76. B. Heidrich, M. Vital, I. Plumeier, N. Döscher, S. Kahl, J. Kirschner, S. Ziegert, P. Solbach, H. Lenzen, A. Potthoff, M.P. Manns, H. Wedemeyer, D.H. Pieper, Intestinal microbiota in patients with chronic hepatitis C with and without cirrhosis compared with healthy controls, Liver Int., 38 (2018) 50–58.
  77. B. Heidrich, M. Vital, I. Plumeier, N. Döscher, S. Kahl, J. Kirschner, S. Ziegert, P. Solbach, H. Lenzen, A. Potthoff, M.P. Manns, H. Wedemeyer, D.H. Pieper, Intestinal microbiota in patients with chronic hepatitis C with and without cirrhosis compared with healthy controls, Liver Int., 38 (2018) 50–58.
  78. F.B. Garcez, J.C. Garcia de Alencar, S.S.M. Fernandez, V.I. Avelino-Silva, E.C. Sabino, R.C.R. Martins, L.A.M. Franco, S.M.L. Ribeiro, H.P. de Souza, T.J. Avelino-Silva, Association between gut microbiota and delirium in acutely ill older adults, J. Gerontol. A Biol. Sci. Med. Sci., 78 (2023) 1320–1327.
  79. J.R. Rak, Proposal for assessing the diversification of water volume in network water reservoirs, JCEEA, 32 (2015) 339–349 (in Polish).
  80. J.R. Rak, K. Boyczko, Use of Pielou indicator to the three parameters water supply diversification assessment, INSTAL, 7/8 (2017) 67–70 (in Polish).
  81. K. Boryczko, J.R. Rak, Method for assessment of water supply diversification, Resources, 9 (2020) 87, doi: 10.3390/resources9070087.
  82. C.L. Amorim, M. Alves, P.M.L. Castro, I. Henriques, Bacterial community dynamics within an aerobic granular sludge reactor treating wastewater loaded with pharmaceuticals, Ecotoxicol. Environ. Saf., 147 (2018) 905–912.
  83. D. Gebler, D. Kayzer, K. Szoszkiewicz, A. Budka, Artificial neural network modelling of macrophyte indices based on physico-chemical characteristics of water, Hydrobiologia, 737 (2014) 215–224.
  84. D. Szpak, B. Tchórzewska-Cieślak, Assessment of the failure rate of water supply system in terms of safety of critical infrastructure, Chemik, 68 (2014) 862–864 (in Polish).
  85. J.R. Rak, K. Boryczko, Use of Pielou Indicator to Three-Parameters Water Supply Diversification Assessment, I. Zimoch, Ed., Current Issue in Water Treatment and Water Distribution, Silesian University Press, Gliwice, 2017, pp. 369–380 (in Polish).