Skip to main content

Advertisement

SpringerLink
Log in

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight–based multi-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively. According to model validation performances, entropy-MCDM models (RMSE < 2.48) are rationalized to the harmonic relationship of riverine system, whereas fuzzy and AHP-MCDM models (RMSE < 2.79) are signified to HSDs, and these results are closer to real problems. With the acceptability of AHP-MCDM models through the percentage change (73.89%) and intensity change (17.16) assessment, it points that over HSDs are crucial factors for river health degradation. Moreover, final outcome of the present research helps to find out the sick river health sites for ecological restoration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

References

  • Aazami J, Esmaili-Sari A, Abdoli A, Sohrabi H, Van den Brink PJ (2015) Monitoring and assessment of water health quality in the Tajan River, Iran using physicochemical, fish and macroinvertebrates indices. J Environ Health SCI 13(1):1–12

    CAS  Google Scholar 

  • Alemu T, Bahrndorff S, Pertoldi C, Hundera K, Alemayehu E, Ambelu A (2018) Development of a plant based riparian index of biotic integrity (RIBI) for assessing the ecological condition of highland streams in East Africa. Ecol Indic 87:77–85

    Article  Google Scholar 

  • Ameri AA, Pourghasemi HR, Cerda A (2018) Erodibility prioritization of subwatersheds using morphometric parameters analysis and its mapping: a comparison among TOPSIS, VIKOR, SAW, and CF multi-criteria decision making models. Sci Total Environ 613:1385–1400. https://doi.org/10.1016/j.scitotenv.2017.09.210

    Article  CAS  Google Scholar 

  • Badri SA (2003) Models of rural planning. Pamphlets Practical Lesson in Geography Rural Planning. Payame Noor University, p. 126

  • Bhattacharya R, Dolui G, Chatterjee ND (2019a) Effect of instream sand mining on hydraulic variables of bedload transport and channel planform: an alluvial stream in South Bengal basin. India Environ Earth SCI 78(10):1–24

    CAS  Google Scholar 

  • Bhattacharya RK, Chatterjee ND, Das K (2019b) Geomorphic response to riverine land cover dynamics in a quarried alluvial river Kangsabati, South Bengal India. Environ Earth SCI 78(22):1–18

    Article  CAS  Google Scholar 

  • Bhattacharya RK, Chatterjee ND, Dolui G (2019c) Consequences of sand mining on water quality and instream biota in alluvial stream: a case-specific study in South Bengal River India. Sustain Water Resour Manag 5(4):1815–1832

    Article  Google Scholar 

  • Bhattacharya RK, Chatterjee ND, Das K (2020a) Impact of instream sand mining on habitat destruction or transformation using coupling models of HSI and MLR. Spat Inf Res 28(1):67–85

    Article  Google Scholar 

  • Bhattacharya RK, Chatterjee ND, Das K (2020b) Sub-basin prioritization for assessment of soil erosion susceptibility in Kangsabati, a plateau basin: a comparison between MCDM and SWAT models. Sci Total Environ 734:139474

    Article  CAS  Google Scholar 

  • Bhattacharya RK, Chatterjee ND, Das K (2020c) An integrated GIS approach to analyze the impact of land use change and land cover alteration on ground water potential level: a study in Kangsabati Basin India. Groundw Sustain Dev 11:100399

    Article  Google Scholar 

  • Bhattacharya RK, Das Chatterjee N (2021) Sand mining consequences on habitat ecology, water quality and species diversity: implementing of HSI, MLR, WQI and ANN methods. In River sand mining modelling and sustainable practice (pp. 251–311). Springer, Cham. https://doi.org/10.1007/978-3-030-72296-8_7

  • Bhattacharya RK, Chatterjee ND, Das K (2021) Assessment of habitat quality in quarried reach of alluvial river B. C. Patra et al. (eds.), River Health and Ecology in South Asia. https://doi.org/10.1007/978-3-030-83553-8_11

  • Birk S, Bonne W, Borja A, Brucet S, Courrat A, Poikane S, Solimini A, Van De Bund W, Zampoukas N, Hering D (2012) Three hundred ways to assess Europe’s surface waters: an almost complete overview of biological methods to implement the Water Framework Directive. Ecol Indic 18:31–41

    Article  Google Scholar 

  • Boulton AJ (1993) Stream ecology and surface-hyporheic hydrologic exchange: implications, techniques and limitations. Mar Freshw Res 44(4):553–564

    Article  Google Scholar 

  • Boulton AJ (2000) River ecosystem health down under: assessing ecological condition in riverine groundwater zones in Australia. Ecosyst Health 6(2):108–118

    Article  Google Scholar 

  • Cheng X, Chen LD, Sun RH, Kong PR (2018) Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China. Sci Total Environ S616–617:376–385. https://doi.org/10.1016/j.scitotenv.2017.10.316

    Article  CAS  Google Scholar 

  • Deng X, Xu Y, Han L, Yu Z, Yang M (2015) Assessment of river health based on an improved entropy-based fuzzy matter-element model in the Taihu Plain. China Ecol Indic 57:85–95. https://doi.org/10.1016/j.ecolind.2015.04.020

    Article  Google Scholar 

  • Deveci M, Canıtez F, Gökaşar I (2018) WASPAS and TOPSIS based interval type-2 fuzzy MCDM method for a selection of a car sharing station. Sustain Cities Soc 41:777–791

    Article  Google Scholar 

  • Ding Y, Shan B, Zhao Y (2015) Assessment of river habitat quality in the hai river basin, northern China. Int J Environ Res 12(9):11699–11717

    Google Scholar 

  • Dutta V, Sharma U, Kumar R (2017) Assessment of river ecosystems and environmental flows: Role of flow regimes and physical habitat variables. Clim Chang Environ Sustain 5(1):20–34

    Article  Google Scholar 

  • Feng B, Zhang M, Chen J, Xu J, Xiao B, Zhou M, Zhang M (2021) Reduction in the phytoplankton index of biotic integrity in riverine ecosystems driven by industrial activities, dam construction and mining: a case study in the Ganjiang River. China Ecol Indic 120:106907

    Article  CAS  Google Scholar 

  • Folk RL, Ward WC (1957) Brazos River bar: a study in the significance of grain size parameters. J Sediment Petrol 27(1):3–26. https://doi.org/10.1306/74D70646-2B21-11D7-8648000102C1865D

    Article  Google Scholar 

  • Friend PF, Sinha R (1993) Braiding and meandering parameters. Geol Soc Lond Spec Publ 75(1):105–111

    Article  Google Scholar 

  • Gain AK, Giupponi C (2015) A dynamic assessment of water scarcity risk in the Lower Brahmaputra River Basin: an integrated approach. Ecol Indic 48:120–131. https://doi.org/10.1016/j.ecolind.2014.07.034

    Article  Google Scholar 

  • Ghaleno MRD, Meshram SG, Alvandi E (2020) Pragmatic approach for prioritization of flood and sedimentation hazard potential of watersheds. Soft Comput 24:15701–15714

    Article  Google Scholar 

  • Gupta S, Gupta SK (2021) Development and evaluation of an innovative Enhanced River Pollution Index model for holistic monitoring and management of river water quality. Environ Sci Pollut Res 28(21):27033–27046

    Article  CAS  Google Scholar 

  • Hezer S, Gelmez E, Özceylan E (2021) Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID-19 Regional Safety Assessment. Infect Public Health 14(6):775–786

    Article  Google Scholar 

  • Julien IY (2002) River mechanics. Cambridge University Press, Cambridge.https://doi.org/10.1017/CBO9781139164016

  • Kadam AK, Wagh VM, Muley AA, Umrikar BN, Sankhua RN (2019) Prediction of water quality index using artificial neural network and multiple linear regression modelling approach in Shivganga River basin India. Model Earth Syst Environ 5(3):951–962

    Article  Google Scholar 

  • Kaganski S, Majak J, Karjust K (2018) Fuzzy AHP as a tool for prioritization of key performance indicators. In Procedia CIRP. https://doi.org/10.1016/j.procir.2018.03.097

    Article  Google Scholar 

  • Karr JR (1999) Defining and measuring river health. Freshw Biol 41:221–234

    Article  Google Scholar 

  • Karr JR (1981) Assessment of biotic integrity using fish communities. Fisheries 6(6):21–27

    Article  Google Scholar 

  • Kristensen EA, Baattrup-Pedersen A, Thodsen H (2011) An evaluation of restoration practises in lowland streams: Has the physical integrity been re-created? Ecol Eng 37(11):1654–1660

    Article  Google Scholar 

  • Kuo Y, Yang T, Huang GW (2008) The use of grey relational analysis in solving multiple attribute decision-making problems. Comput Ind Eng 55:80–93. https://doi.org/10.1016/j.cie.2007.12.002

    Article  Google Scholar 

  • Liu W, Xu M, Zhao N, Zhou X, Pan B, Tian S, Lei F (2019) River health assessment of the Yellow River source region, Qinghai-Tibetan Plateau, China, based on tolerance values of macroinvertebrates. Environ Sci Pollut Res 26(10):10251–10262

    Article  Google Scholar 

  • Luo Z, Zuo Q, Shao Q (2018) A new framework for assessing river ecosystem health with consideration of human service demand. Sci Total Environ 640:442–453

    Article  Google Scholar 

  • Ma D, Luo W, Yang G, Lu J, Fan Y (2019) A study on a river health assessment method based on ecological flow. Ecol Modell 401:144–154

    Article  Google Scholar 

  • Maddock I (1999) The importance of physical habitat assessment for evaluating river health. Freshw Biol 41(2):373–391

    Article  Google Scholar 

  • Margalef RAMON (1958) Temporal sucession and spatial heterogeneity in Phytoplankton In; Perspective in marine biology. University of California press. USA. https://doi.org/10.1525/9780520350281-024

  • Mittal N, Mishra A, Singh R, Bhave AG, van der Valk M (2014) Flow regime alteration due to anthropogenic and climatic changes in the Kangsabati River, India. Ecohydrol Hydrobiol 14(3):182–191

    Article  Google Scholar 

  • Mupenzi C, Li L, Al LNE (2017) Spatial pattern assessment of lake kivu basin rivers water quality using national sanitation foundation water quality and rivers pollution indices. Desalin Water Treat 95:128–143

    Google Scholar 

  • Mura SNS, Gope A (2020) Anthropogenic impact on forms and processes of the Kangsabati River Basin. In Anthropogeomorphology of Bhagirathi-Hooghly River System in India (253–296). CRC Press. https://doi.org/10.1201/9781003032373

  • Nădăban S, Dzitac S, Dzitac I (2016) Fuzzy TOPSIS: a general view. Procedia Comput Sci 91:823–831

    Article  Google Scholar 

  • Navratil O, Albert MB (2010) Non-linearity of reach hydraulic geometry relations. J Hydrol 388:280–290

    Article  Google Scholar 

  • Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455. https://doi.org/10.1016/S0377-2217(03)00020-1

    Article  Google Scholar 

  • Petesse ML, Siqueira-Souza FK, de Carvalho FCE, Petrere M (2016) Selection of reference lakes and adaptation of a fish multimetric index of biotic integrity to six amazon floodplain lakes. Ecol Eng 97:535–544

    Article  Google Scholar 

  • Pielou EC (1966) The measurement of diversity in different types of biological collections. J Theor Biol 13:131–144

    Article  Google Scholar 

  • Poikane S, Kelly M, Cantonati M (2016) Benthic algal assessment of ecological status in European lakes and rivers: Challenges and opportunities. Sci Total Environ 568:603–613

    Article  CAS  Google Scholar 

  • Qiu Y (2011) Management decision entropy and its application. China Electric Power Press, Beijing (in Chinese)

  • Restrepo JD, Escobar R, Tosic M (2018) Fluvial fluxes from the Magdalena River into Cartagena Bay, Caribbean Colombia: trends, future scenarios, and connections with upstream human impacts. Geomorphology 302:92–105. https://doi.org/10.1016/j.geomorph.2016.11.007

    Article  Google Scholar 

  • Reynolds CS (2003) Planktic community assembly in flowing water and the ecosystem health of rivers. Ecol Modell 160(3):191–203

    Article  Google Scholar 

  • Sadat MA, Guan Y, Zhang D, Shao G, Cheng X, Yang Y (2020) The associations between river health and water resources management lead to the assessment of river state. Ecol Indic 109:105814

    Article  Google Scholar 

  • Sargaonkar A, Deshpande V (2003) Development of an overall index of pollution for surface water based on a general classification scheme in Indian context. Environ Monit Assess 89(1):43–67

    Article  CAS  Google Scholar 

  • Sargaonkar AP, Rathi B, Baile A (2011) Identifying potential sites for artificial groundwater recharge in sub-watershed of river Kanhan. India Environ Earth Sci 62(5):1099–1108. https://doi.org/10.1007/s12665-010-0598-z

    Article  Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281

    Article  Google Scholar 

  • Shan C, Dong Z, Lu D, Xu C, Wang H, Ling Z, Liu Q (2021) Study on river health assessment based on a fuzzy matter-element extension model. Ecol Indic 127:107742

    Article  Google Scholar 

  • Shannon CE (1949) The mathematical theory of communication. CE Shannon and Warren Weaver, Urbana. https://pure.mpg.de/rest/items/item_2383164/component/file_2383163/content

  • Sharma P, Meher PK, Kumar A, Gautam YP, Mishra KP (2014) Changes in water quality index of Ganges river at different locations in Allahabad. Sustain Water Qual Ecol 3:67–76

    Article  Google Scholar 

  • Shi X, Liu J, You X, Bao K, Meng B, Chen B (2017) Evaluation of river habitat integrity based on benthic macroinvertebrate-based multi-metric model. Ecol Model 353:63–76

    Article  Google Scholar 

  • Shukla RK, Garg D, Agarwal A (2014) An integrated approach of Fuzzy AHP and Fuzzy TOPSIS in modeling supply chain coordination. Prod Manuf Res 2(1):415–437. https://doi.org/10.1080/21693277.2014.919886

    Article  Google Scholar 

  • Si T, Wang C, Liu R, Guo Y, Yue S, Ren Y (2020) Multi-criteria comprehensive energy efficiency assessment based on fuzzy-AHP method: a case study of post-treatment technologies for coal-fired units. Energy 200:117533. https://doi.org/10.1016/j.energy.2020.117533

    Article  CAS  Google Scholar 

  • Singh PK, Saxena S (2018) Towards developing a river health index. Ecol Indic 85:999–1011. https://doi.org/10.1016/j.ecolind.2017.11.059

    Article  Google Scholar 

  • Solangi YA, Shah SAA, Zameer H, Ikram M, Saracoglu BO (2019) Assessing the solar PV power project site selection in Pakistan: based on AHP-fuzzy VIKOR approach. Environ Sci Pollut Res 26(29):30286–30302

    Article  Google Scholar 

  • Smith MJ, Kay WR, Edward DHD, Papas PJ, Richardson KSJ, Simpson JC, Pinder AM, Cale DJ, Horwitz PH, Davis JA, Yung FH (1999) AusRivAS: using macroinvertebrates to assess ecological condition of rivers in Western Australia. Freshw Biol 41(2):269–282

    Article  Google Scholar 

  • Stewardson M (2005) Hydraulic geometry of stream reaches. J Hydrol 36:97–111

    Article  Google Scholar 

  • Su Y, Li W, Liu L, Hu W, Li J, Sun X, Li Y (2021) Health assessment of small-to-medium sized rivers: Comparison between comprehensive indicator method and biological monitoring method. Ecol Indic 126:107686

    Article  Google Scholar 

  • Ustaoğlu F, Tepe Y, Taş B (2020) Assessment of stream quality and health risk in a subtropical Turkey river system: A combined approach using statistical analysis and water quality index. Ecol Indic 113:105815

    Article  Google Scholar 

  • Von Schiller D, Acuña V, Aristi I, Arroita M, Basaguren A, Bellin A, Boyero L, Butturini A, Ginebreda A, Kalogianni E, Larrañaga A (2017) River ecosystem processes: A synthesis of approaches, criteria of use and sensitivity to environmental stressors. Sci Total Environ 596:465–480

    Article  Google Scholar 

  • Wang Y, Xu L, Solangi YA (2020) Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustain Cities Soc 52:101861

    Article  Google Scholar 

  • Wu C, Chen W (2020) Indicator system construction and health assessment of wetland ecosystem—taking Hongze Lake Wetland China as an Example. Ecol Indic 112:106164

    Article  Google Scholar 

  • Xue C, Shao C, Chen S (2020) SDGs-based river health assessment for small-and medium-sized watersheds. Sustainability 12(5):1846

  • Yang T, Liu JL, Chen QY (2013) Assessment of plain river ecosystem function based on improved gray system model and analytic hierarchy process for the Fuyang River, Haihe River Basin. Ecol Model 268:37–47

    Article  Google Scholar 

  • Yang T, Liu J, Li X, Zhao X (2017) Plain river habitat assessment of Haihe River basin. Environ Sci Technol (china) 40(3):190–197

    Google Scholar 

  • Yang W, You Q, Fang N, Xu L, Zhou Y, Wu N, Ni CY, Liu Y, Liu GH, Yang T, Wang Y (2018) Assessment of wetland health status of Poyang Lake using vegetation-based indices of biotic integrity. Ecol Indic 90:79–89

    Article  Google Scholar 

  • Zavadskas EK, Kaklauskas A, Vilutiene T (2009) Multicriteria evaluation of apartment blocks maintenance contractors: Lithuanian case study. Int J Strateg Prop Manag 13(4):319–338. https://doi.org/10.3846/1648-715X.2009.13.319-338

    Article  Google Scholar 

  • Zavadskas EK, Turskis Z, Antucheviciene J, Zakarevicius A (2012) Optimization of weighted aggregated sum product assessment. Electron Electr Eng 6(122):3–6

    Google Scholar 

  • Zheng BH, Zhang Y, Li YB (2007) Study on indicators and methods for river habitat assessment of Liao River Basin. J Environ Sci 27:928–936 (in Chinese)

    CAS  Google Scholar 

  • Zeng P, Sun F, Liu Y, Che Y (2020) Future river basin health assessment through reliability-resilience-vulnerability: thresholds of multiple dryness conditions. Sci Total Environ 741:140395. https://doi.org/10.1016/j.scitotenv.2020.140395

    Article  CAS  Google Scholar 

  • Zhao YW, Zhou LQ, Dong BQ, Dai C (2019) Health assessment for urban rivers based on the pressure, state and response framework—a case study of the Shiwuli River. Ecol Indic 99:324–331

    Article  Google Scholar 

  • Zhu W, Liu Y, Wang S et al (2019) Development of microbial community–based index of biotic integrity to evaluate the wetland ecosystem health in Suzhou China. Environ Monit Assess 191:377. https://doi.org/10.1007/s10661-019-7512-2

    Article  Google Scholar 

  • Zhu Y, Tian D, Yan F (2020) Effectiveness of entropy weight method in decision-making. Math Probl Eng. https://doi.org/10.1155/2020/3564835

    Article  Google Scholar 

  • Zou Z, Yun Y, Sun J (2006) Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J Environ Sci (China) 18:1020–1023. https://doi.org/10.1016/S1001-0742(06)60032-6

    Article  CAS  Google Scholar 

  • Zuo QT, Luo ZL, Ding XY (2016) Harmonious development between socio-economy and river-lake water system in Xiangyang City. China Water 8(11):1–19

    Google Scholar 

Download references

Acknowledgements

The authors are thankful to Irrigation Office of Paschim Medinipur and Bankura, District Land and Land Reforms officer of the Paschim Midnapore and Bankura districts, WB in India, for providing the long-term and short-term sand mining of the Kangsabati River. We are also grateful to University Science Instrumentation Centre (USIC), Vidyasagar University, for providing the instrument facility (water analyzer) and Herbarium sheet.

Author information

Authors and Affiliations

  1. Department of Geography, Vidyasagar University Midnapore, Midnapore, West Bengal, 721102, India

    Raj Kumar Bhattacharya, Nilanjana Das Chatterjee & Kousik Das

Authors
  1. Raj Kumar Bhattacharya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nilanjana Das Chatterjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kousik Das
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Raj Kumar Bhattacharya: conceptualization, methodology, software, data curation, writing — original draft. Nilanjana Das Chatterjee: supervision, writing — review and editing. Kousik Das: software, visualization, investigation.

Corresponding author

Correspondence to Raj Kumar Bhattacharya.

Ethics declarations

Ethics approval

Not applicable.

Consent for publication

Not applicable for that specific section.

Consent to participate

All authors are approved and confirmed for submission to this journal.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Marcus Schulz

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 57 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bhattacharya, R.K., Das Chatterjee, N. & Das, K. Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models. Environ Sci Pollut Res 29, 84137–84165 (2022). https://doi.org/10.1007/s11356-022-21040-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-022-21040-0

Keywords

Search

Navigation