Skip to main content

Advertisement

SpringerLink
Log in

Impact of river flow modification on wetland hydrological and morphological characters

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

Abstract

A good number of researchers investigated the impact of flow modification on hydrological, ecological, and geomorphological conditions in a river. A few works also focused on hydrological modification on wetland with some parameters but as far the knowledge is concerned, linking river flow modification to wetland hydrological and morphological transformation following an integrated modeling approach is often lacking. The current study aimed to explore the degree of hydrological alteration in the river and its effect on downstream riparian wetlands by adopting advanced modeling approaches. After damming, maximally 67 to 95% hydrological alteration was recorded for maximum, minimum, and average discharges. Wavelet transformation analysis figured out a strong power spectrum after 2012 (damming year). Due to attenuation of flow, the active inundation area was reduced by 66.2%. After damming, 524.03 km2 (48.9% of total pre-dam wetland) was completely obliterated. Hydrological strength (HS) modeling also reported areas under high HS declined by 14% after post-dam condition. Wetland hydrological security state (WSS) and HS matrix, a new approach, are used to explore wetland characteristics of inundation connectivity and hydrological security state. WSS was defined based on lateral hydrological connectivity. HS under critical and stress WWS zones deteriorated in the post-dam period. The morphological transformation was also well recognized showing an increase in area under the patch, edge, and a decrease in the area under the large core area. All these findings established a clear linkage between river flow modification and wetland transformation, and they provided a good clue for managing wetlands.

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:

Similar content being viewed by others

References

  • Adel MM (2013) Upstream water piracy, the strongest weapon of cornering a downstream nation. Environ Ecol Res 1(3):85–128

    Article  Google Scholar 

  • Aghsaei H, Dinan NM, Moridi A, Asadolahi Z, Delavar M, Fohrer N, Wagner PD (2020) Effects of dynamic land use/land cover change on water resources and sediment yield in the Anzali wetland catchment, Gilan, Iran. Sci Total Environ 712:136449

    Article  CAS  Google Scholar 

  • Al-Abadi AM, Al-Najar NA (2020) Comparative assessment of bivariate, multivariate and machine learning models for mapping flood proneness. Natural Hazards 100(2):461–491

    Article  Google Scholar 

  • Alafifi AH, Rosenberg DE (2020) Systems modeling to improve river, riparian, and wetland habitat quality and area. Environ Modell Softw 126:104643

    Article  Google Scholar 

  • Ali R, Kuriqi A, Abubaker S, Kisi O (2019) Hydrologic alteration at the upper and middle part of the Yangtze river, China: towards sustainable water resource management under increasing water exploitation. Sustainability 11(19):5176

    Article  Google Scholar 

  • Amenuvor M, Gao W, Li D, Shao D (2020) Effects of dam regulation on the hydrological alteration and morphological evolution of the Volta river delta. Water 12(3):646

    Article  Google Scholar 

  • Arabameri A, Chandra Pal S, Rezaie F, Chakrabortty R, Saha A, Blaschke T, Di Napoli M, Ghorbanzadeh O, Thi Ngo PT (2021) Decision Tree based ensemble machine learning approaches for landslide susceptibility mapping. Geocarto International, pp1–28

  • Arabameri A, Santosh M, Saha S, Ghorbanzadeh O, Roy J, Tiefenbacher JP, Moayedi H, Costache R (2021) Spatial prediction of shallow landslide: application of novel rotational forest-based reduced error pruning tree. Geomatics, Natural Hazards and Risk 12(1):1343–1370

    Article  Google Scholar 

  • Arévalo-Mejía R, Leblois E, Salinas-Tapia H, Mastachi-Loza CA, Bâ KM, Díaz-Delgado C (2020) A baseline assessment of hydrologic alteration degree for the Mexican catchments at gauged rivers (2016). Sci Total Environ 729:139041

    Article  Google Scholar 

  • Araghi A, Baygi MM, Adamowski J, Malard J, Nalley D, Hasheminia SM (2015) Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data. Atmos Res 155:52–72

    Article  Google Scholar 

  • Barter RL, Yu B (2018) Superheat: An R package for creating beautiful and extendable heatmaps for visualizing complex data. J Comput Graph Stat 27(4):910–922

    Article  Google Scholar 

  • Behnia P, Blais-Stevens A (2018) Landslide susceptibility modelling using the quantitative random forest method along the northern portion of the Yukon Alaska Highway Corridor, Canada. Nat Hazards 90(3):1407–1426

    Article  Google Scholar 

  • Bouramtane T, Kacimi I, Bouramtane K, Aziz M, Abraham S, Omari K, Valles V, Leblanc M, Kassou N, El Beqqali O, Bahaj T (2021) Multivariate analysis and machine learning approach for mapping the variability and vulnerability of urban flooding: The Case of Tangier City, Morocco. Hydrology 8(4):182

    Article  Google Scholar 

  • Bregoli F, Crosato A, Paron P, McClain ME (2019) Humans reshape wetlands: Unveiling the last 100 years of morphological changes of the Mara Wetland, Tanzania. Sci Total Environ 691:896–907

    Article  CAS  Google Scholar 

  • Breiman L (2001) Random forests. Mach Learn 45(1):5–32

    Article  Google Scholar 

  • Bunn SE, Arthington AH (2002) Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manage 30(4):492–507

    Article  Google Scholar 

  • Camargo FF, Sano EE, Almeida CM, Mura JC, Almeida T (2019) A comparative assessment of machine-learning techniques for land use and land cover classification of the Brazilian tropical savanna using ALOS-2/PALSAR-2 polarimetric images. Remote Sens 11(13):1600

  • Chakraborty R, Talukdar S, Basu T, Pal S (2018) Habitat identity crisis caused by the riparian wetland squeeze in Tangon river basin, Barind Region, India. Spat Inf Res 26(5):507–516

    Article  Google Scholar 

  • Chen W, Hong H, Li S, Shahabi H, Wang Y, Wang X, Ahmad BB (2019) Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles. J Hydrol 575:864–873

    Article  Google Scholar 

  • Chen L, Wu Y, Xu YJ, Zhang G (2021) Alteration of flood pulses by damming the Nenjiang River, China–implication for the need to identify a hydrograph-based inundation threshold for protecting floodplain wetlands. Ecol Ind 124:107406

    Article  Google Scholar 

  • Chen T, Zhu L, Niu RQ, Trinder CJ, Peng L, Lei T (2020) Mapping landslide susceptibility at the Three Gorges Reservoir, China, using gradient boosting decision tree, random forest and information value models. J Mt Sci 17(3)

  • Cheng J, Xu L, Wang X, Jiang J, You H (2018) Assessment of hydrologic alteration induced by the Three Gorges Dam in Dongting Lake, China. River Res Appl 34(7):686–696

    Article  Google Scholar 

  • Chicco D, Jurman G (2020) The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC genomics 21(1):1–13

    Article  Google Scholar 

  • Choi C, Kim J, Han H, Han D, Kim HS (2020) Development of water level prediction models using machine learning in wetlands: A case study of Upo wetland in South Korea. Water 12(1):93

  • Costache R, Bui DT (2020) Identification of areas prone to flash-flood phenomena using multiple-criteria decision-making, bivariate statistics, machine learning and their ensembles. Sci Total Environ 712:136492

    Article  CAS  Google Scholar 

  • Cui G, Liu Y, Tong S (2021) Analysis of the causes of wetland landscape patterns and hydrological connectivity changes in Momoge National Nature Reserve based on the Google Earth Engine Platform. Arab J Geosci 14(3):1–16

    Article  CAS  Google Scholar 

  • Das RT, Pal S (2018) Investigation of the principal vectors of wetland loss in Barind tract of West Bengal. GeoJournal 83(5):1115–1131

    Article  Google Scholar 

  • Das S, Adhikary PP, Shit PK, Bera B (2021) Urban wetland fragmentation and ecosystem service assessment using integrated machine learning algorithm and spatial landscape analysis. Geocarto International:1–19

  • Deforet T, Marmonier P, Rieffel D, Crini N, Giraudoux P, Gilbert D (2009) Do parafluvial zones have an impact in regulating river pollution? Spatial and temporal dynamics of nutrients, carbon, and bacteria in a large gravel bar of the Doubs River (France). Hydrobiologia. 623(1):235–250

    Article  CAS  Google Scholar 

  • Du J, Wu X, Wang Z, Li J, Chen X (2020) Reservoir-induced hydrological alterations using ecologically related hydrologic metrics: case study in the Beijiang river, China. Water 12(7):2008

    Article  Google Scholar 

  • Duc NA, Nguyen LT, Thai TH, Khan A, Rautenstrauch K, Schmidt C (2020) Assessing cumulative impacts of the proposed Lower Mekong Basin hydropower cascade on the Mekong river floodplains and Delta–overview of integrated modeling methods and results. J Hydrol 581:122511

    Article  Google Scholar 

  • Elfeky MG, Aref WG, Elmagarmid AK (2005) Periodicity detection in time series databases. IEEE Trans Knowl Data Eng 17(7):875–887

    Article  Google Scholar 

  • Epting SM, Hosen JD, Alexander LC, Lang MW, Armstrong AW, Palmer MA (2018) Landscape metrics as predictors of hydrologic connectivity between coastal plain forested wetlands and streams. Hydrol Process 32(4):516–532

    Article  Google Scholar 

  • Finlayson CM (2013) Climate change and wise use of wetlands: informations from Australian wet lands. Hydrobiologia 708(1):145–152

    Article  CAS  Google Scholar 

  • Fleischmann A, Collischonn W, Paiva R, Tucci CE (2019) Modeling the role of reservoirs versus floodplains on large-scale river hydrodynamics. Natural Hazards 99(2):1075–1104

    Article  Google Scholar 

  • Fritz KM, Schofield KA, Alexander LC, McManus MG, Golden HE, Lane CR, Kepner WG, LeDuc SD, DeMeester JE, Pollard AI (2018) Physical and chemical connectivity of streams and riparian wetlands to downstream waters: a synthesis. JAWRA J Am Water Resour Assoc 54(2):323–345

    Article  CAS  Google Scholar 

  • Gain AK, Giupponi C (2015) A dynamic assessment of water scarcity risk in the Lower Brahmaputra River Basin: An integrated approach. Ecol Ind 48:120–131

    Article  Google Scholar 

  • Galib SM, Lucas MC, Chaki N, Fahad FH, Mohsin ABM (2018) Is current floodplain management a cause for concern for fish and bird conservation in Bangladesh's largest wetland? Aqua Conserv Marine Freshw Ecosyst 28(1):98–114

    Article  Google Scholar 

  • Gao BC (1996) NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58(3):257–266

    Article  Google Scholar 

  • Gao Y, Chen L, Zhang W, Li X, Xu Q (2021) Spatiotemporal variations in characteristic discharge in the Yangtze River downstream of the Three Gorges Dam. Sci Total Environ 785:147343

    Article  CAS  Google Scholar 

  • Ge J, Peng W, Huang W, Qu X, Singh SK (2018) Quantitative assessment of flow regime alteration using a revised range of variability methods. Water 10(5):597

    Article  Google Scholar 

  • Ghasemain B, Asl DT, Pham BT, Avand M, Nguyen HD, Janizadeh SJVJOES (2020) Shallow landslide susceptibility mapping: A comparison between classification and regression tree and reduced error pruning tree algorithms. Vietnam J Earth Sci 42(3):208–227

    Google Scholar 

  • Goupillaud P, Grossmann A, Morlet J (1984) Cycle-octave and related transforms in seismic signal analysis. Geoexploration 23(1):85–102

    Article  Google Scholar 

  • Greet J, Fischer S, Russell K (2020) Longer duration flooding reduces the growth and sexual reproductive efforts of a keystone wetland tree species. Wetlands Ecol Manag 28(4):655–666

    Article  CAS  Google Scholar 

  • Han J, Kim J, Park S, Son S, Ryu M (2020) Seismic vulnerability assessment and mapping of Gyeongju, South Korea using frequency ratio, decision tree, and random forest. Sustainability 12(18):7787

    Article  Google Scholar 

  • Huang F, Zhang N, Guo LD, Xia ZQ (2016) August. Assessing the hydrologic alteration of the Yangtze River using the histogram matching approach. In IOP Conference Series: Earth and Environmental Science (Vol. 39, No. 1, p. 012002). IOP Publishing

  • Huang F, Li F, Zhang N, Chen Q, Qian B, Guo L, Xia Z (2017) A histogram comparison approach for assessing hydrologic regime alteration. River Res Appl 33(5):809–822

    Article  Google Scholar 

  • Huang X, Suwal N, Fan J, Pandey KP, Jia Y (2019) Hydrological Alteration Assessment by Histogram Comparison Approach: A Case Study of Erdu River Basin, China. J Coast Res 93(SI):139–145

    Article  Google Scholar 

  • Jeziorska J (2019) UAS for wetland mapping and hydrological modeling. Remote Sensing 11(17):1997

    Article  Google Scholar 

  • Karim F, Marvanek S, Merrin LE, Nielsen D, Hughes J, Stratford D, Pollino C (2020) Modelling flood-induced wetland connectivity and impacts of climate change and dam. Water 12(5):1278

    Article  Google Scholar 

  • Khatun R, Talukdar S, Pal S, Kundu S (2021) Measuring dam induced alteration in water richness and eco-hydrological deficit in flood plain wetland. J Environ Manage 285:112157

    Article  Google Scholar 

  • Kundu S, Pal S, Talukdar S, Mandal I (2021) Impact of wetland fragmentation due to damming on the linkages between water richness and ecosystem services. Environ Sci Pollut Res, pp.1-20

  • Lee S, McCarty GW, Moglen GE, Lang MW, Jones CN, Palmer M, Yeo IY, Anderson M, Sadeghi AM, Rabenhorst MC (2020) Seasonal drivers of geographically isolated wetland hydrology in a low-gradient, coastal plain landscape. J Hydrol 583:124608

    Article  Google Scholar 

  • Li D, Long D, Zhao J, Lu H, Hong Y (2017) Observed changes in flow regimes in the Mekong river basin. J Hydrol 551:217–232

    Article  Google Scholar 

  • Li B, Yang Z, Cai Y, Li B (2021) The frontier evolution and emerging trends of hydrological connectivity in river systems: a scientometric review. Front Earth Sci 15(1):81–93

    Article  CAS  Google Scholar 

  • Liu N, Gao J, Jiang X, Zhang Z, Wang Q (2016) Seismic time-frequency analysis via STFT-based concentration of frequency and time. IEEE Geosci Remote Sens Lett 14(1):127–131

    Article  Google Scholar 

  • Liu Z, Zhao L, Xu T, Bu F, Liu X, Zhou D (2018) Quantification of potential flood inundation areas in the marsh wetland of Honghe National Natural Reserve, Northeast China. Ecohydrol Hydrobiol 18(4):355–364

    Article  Google Scholar 

  • Lu C, Ren C, Wang Z, Zhang B, Man W, Yu H, Gao Y, Liu M (2019) Monitoring and assessment of wetland loss and fragmentation in the cross-boundary protected area: a case study of Wusuli River Basin. Remote Sens 11(21):2581

    Article  Google Scholar 

  • Maurya PK, Malik DS, Yadav KK, Kumar A, Kumar S, Kamyab H (2019) Bioaccumulation and potential sources of heavy metal contamination in fish species in River Ganga basin: possible human health risks evaluation. Toxicol Rep 6:472–481

    Article  CAS  Google Scholar 

  • McFeeters SK (1996) The use of the normalized difference water index (NDWI) in the delineation of open water features. Intl J Remote Sens 17(7):1425–1432

    Article  Google Scholar 

  • Meng B, Liu JL, Bao K, Sun B (2020) Methodologies and management framework for restoration of wetland hydrologic connectivity: a synthesis. Integr Environ Assess Manage 16(4):438–451

    Article  Google Scholar 

  • Milani M, Marzo A, Toscano A, Consoli S, Cirelli GL, Ventura D, Barbagallo S (2019) Evapotranspiration from horizontal subsurface flow constructed wetlands planted with different perennial plant species. Water 11(10):2159

    Article  CAS  Google Scholar 

  • Mitsch WJ, Gosselink JG (2015) Wetlands. John Wiley & Sons

  • Mohamed WNHW, Salleh MNM, Omar AH (2012) A comparative study of reduced error pruning method in decision tree algorithms. In: 2012 IEEE International conference on control system, computing and engineering. IEEE, pp 392–397

  • Mondal D, Pal S (2018) Monitoring dual-season hydrological dynamics of seasonally flooded wetlands in the lower reach of Mayurakshi river, Eastern India. Geocarto Intl 33(3):225–239

    Article  Google Scholar 

  • Mukherjee K, Pal S, Mukhopadhyay M (2018) Impact of flood and seasonality on wetland changing trends in the Diara region of West Bengal, India. Spat Inf Res 26(4):357–367

    Article  Google Scholar 

  • Mukherjee K, Pal S (2021) Hydrological and landscape dynamics of floodplain wetlands of the Diara region, Eastern India. Ecol Ind 121:106961

    Article  Google Scholar 

  • Nguyen H, Drebenstedt C, Bui XN, Bui DT (2020) Prediction of blast-induced ground vibration in an open-pit mine by a novel hybrid model based on clustering and artificial neural network. Nat Resour Res 29(2):691–709

    Article  Google Scholar 

  • Nhu VH, Shirzadi A, Shahabi H, Singh SK, Al-Ansari N, Clague JJ, Jaafari A, Chen W, Miraki S, Dou J, Luu C (2020) Shallow landslide susceptibility mapping: a comparison between logistic model tree, logistic regression, naïve Bayes tree, artificial neural network, and support vector machine algorithms. Intl J Environ Res Pub Health 17(8):2749

    Article  Google Scholar 

  • Onyango DO, Opiyo SB (2021) Detection of historical landscape changes in Lake Victoria Basin, Kenya, using remote sensing multi-spectral indices. Watershed Ecology and the Environment

  • Orimoloye IR, Kalumba AM, Mazinyo SP, Nel W (2020) Geospatial analysis of wetland dynamics: wetland depletion and biodiversity conservation of Isimangaliso Wetland, South Africa. J King Saud Univ Sci 32(1):90–96

    Article  Google Scholar 

  • Özelkan E (2020) Water body detection analysis using NDWI indices derived from landsat-8 OLI. Pol J Environ Stud 29(2):1759–1769

    Article  Google Scholar 

  • Pal S (2016a) Impact of Massanjore dam on hydro-geomorphological modification of Mayurakshi river, Eastern India. Environ Dev Sustain 18(3):921–944

    Article  Google Scholar 

  • Pal S (2016b) Impact of water diversion on hydrological regime of the Atreyee river of Indo-Bangladesh. Intl J River Basin Manage 14(4):459–475

    Article  Google Scholar 

  • Pal S, Saha TK (2018) Identifying dam-induced wetland changes using an inundation frequency approach: the case of the Atreyee river basin of Indo-Bangladesh. Ecohydrol Hydrobiol 18(1):66–81

    Article  Google Scholar 

  • Pal S, Talukdar S (2019) Impact of missing flow on active inundation areas and transformation of parafluvial wetlands in Punarbhaba–Tangon river basin of Indo-Bangladesh. Geocarto Intl 34(10):1055–1074

    Article  Google Scholar 

  • Pal S, Saha A, Das T (2019) Analysis of flow modifications and stress in the Tangon river basin of the Barind tract. Intl J River Basin Manage 17(3):301–321

    Article  Google Scholar 

  • Pal S, Paul S (2020) Assessing wetland habitat vulnerability in moribund Ganges delta using bivariate models and machine learning algorithms. Ecol Ind 119:106866

    Article  Google Scholar 

  • Pal S, Sarda R (2020) Damming effects on the degree of hydrological alteration and stability of wetland in lower Atreyee river basin. Ecol Ind 116:106542

    Article  Google Scholar 

  • Pal S, Talukdar S (2020) Modelling seasonal flow regime and environmental flow in Punarbhaba river of India and Bangladesh. J Clean Prod 252:119724

    Article  Google Scholar 

  • Pal S, Talukdar S, Ghosh R (2020) Damming effect on habitat quality of riparian corridor. Ecol Ind 114:106300

    Article  Google Scholar 

  • Pal S, Sarda R (2021a) Measuring the degree of hydrological variability of riparian wetland using hydrological attributes integration (HAI) histogram comparison approach (HCA) and range of variability approach (RVA). Ecol Ind 120:106966

    Article  Google Scholar 

  • Pal S, Sarda R (2021b) Modelling water richness in riparian flood plain wetland using bivariate statistics and machine learning algorithms and figuring out the role of damming. Geocarto Intl, pp.1-24

  • Pal S, Sarkar R, Saha TK (2022) Exploring the forms of wetland modifications and investigating the causes in lower Atreyee river floodplain area. Ecol Inf 67:101494

    Article  Google Scholar 

  • Paola JD, Schowengerdt RA (1995) A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. IEEE Trans Geosci Remote Sens 33(4):981–996

    Article  Google Scholar 

  • Pham BT, Prakash I, Singh SK, Shirzadi A, Shahabi H, Bui DT (2019) Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches. Catena 175:203–218

    Article  Google Scholar 

  • Quinlan JR (1987) Decision trees as probabilistic classifiers. In: Proceedings of the Fourth International Workshop on Machine Learning. Morgan Kaufmann, pp 31–37

  • Quintela FM, Lima GP, Silveira ML, Costa PG, Bianchini A, Loebmann D, Martins SE (2019) High arsenic and low lead concentrations in fish and reptiles from Taim wetlands, a Ramsar site in southern Brazil. Sci Total Environ 660:1004–1014

    Article  CAS  Google Scholar 

  • Rahmati O, Falah F, Dayal KS, Deo RC, Mohammadi F, Biggs T, Moghaddam DD, Naghibi SA, Bui DT (2020) Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia. Sci Total Environ 699:134230

    Article  CAS  Google Scholar 

  • Richter BD, Baumgartner JV, Braun DP, Powell J (1998) A spatial assessment of hydrologic alteration within a river network. Regulated Rivers: Research & Management: An International Journal Devoted to River Research and Management 14(4):329–340

    Google Scholar 

  • Rolls RJ, Leigh C, Sheldon F (2012) Mechanistic effects of low-flow hydrology on riverine ecosystems: ecological principles and consequences of alteration. Freshw Sci 31(4):1163–1186

    Article  Google Scholar 

  • Saha TK, Pal S (2019a) Emerging conflict between agriculture extension and physical existence of wetland in post-dam period in Atreyee river basin of Indo-Bangladesh. Environ Dev Sustain 21(3):1485–1505

    Article  Google Scholar 

  • Saha TK, Pal S (2019b) Exploring physical wetland vulnerability of Atreyee river basin in India and Bangladesh using logistic regression and fuzzy logic approaches. Ecol Ind 98:251–265

    Article  Google Scholar 

  • Saha TK, Pal S, Sarkar R (2021) Prediction of wetland area and depth using linear regression model and artificial neural network based cellular automata. Ecol Inf 62:101272

    Article  Google Scholar 

  • Sahour H, Kemink KM, O’Connell J (2022) Integrating SAR and optical remote sensing for conservation-targeted wetlands mapping. Remote Sensing 14(1):159

    Article  Google Scholar 

  • Santos CAG, Kisi O, da Silva RM, Zounemat-Kermani M (2018) Wavelet-based variability on streamflow at 40-year timescale in the Black Sea region of Turkey. Arab J Geosci 11(8):1–11

    Article  Google Scholar 

  • Sarkar UK, Mishal P, Borah S, Karnatak G, Chandra G, Kumari S, Meena DK, Debnath D, Yengkokpam S, Das P, DebRoy P (2020) Status, potential, prospects, and issues of floodplain wetland fisheries in India: synthesis and review for sustainable management. Rev Fish Sci Aquacult 29(1):1–32

    Google Scholar 

  • Sarda R, Das P (2018) Monitoring changing trends of water presence state in the major manmade reservoirs of Mayurakshi river basin, eastern India. Spat Inf Res 26(4):437–447

    Article  Google Scholar 

  • Shaikhina T, Lowe D, Daga S, Briggs D, Higgins R, Khovanova N (2019) Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation. Biomed Signal Process Control 52:456–462

    Article  Google Scholar 

  • Shen G, Yang X, Jin Y, Xu B, Zhou Q (2019) Remote sensing and evaluation of the wetland ecological degradation process of the Zoige Plateau Wetland in China. Ecol Ind 104:48–58

    Article  Google Scholar 

  • Shiau JT, Wu FC (2008) A histogram matching approach for assessment of flow regime alteration: application to environmental flow optimization. River Res Appl 24(7):914–928

    Article  Google Scholar 

  • Singha P, Das P, Talukdar S, Pal S (2020) Modeling livelihood vulnerability in erosion and flooding induced river island in Ganges riparian corridor, India. Ecol Ind 119:106825

    Article  Google Scholar 

  • Smith LC, Turcotte DL, Isacks BL (1998) Stream flow characterization and feature detection using a discrete wavelet transform. Hydrol Process 12(2):233–249

    Article  Google Scholar 

  • Smith A, Tetzlaff D, Gelbrecht J, Kleine L, Soulsby C (2020) Riparian wetland rehabilitation and beaver re-colonization impacts on hydrological processes and water quality in a lowland agricultural catchment. Sci Total Environ 699:134302

    Article  CAS  Google Scholar 

  • Talukdar S, Pal S (2019) Effects of damming on the hydrological regime of Punarbhaba river basin wetlands. Ecol Eng 135:61–74

    Article  Google Scholar 

  • Talukdar S, Pal S (2020) Modeling flood plain wetland transformation in consequences of flow alteration in Punarbhaba river in India and Bangladesh. J Clean Prod 261:120767

    Article  Google Scholar 

  • Teng J, Xia S, Liu Y, Yu X, Duan H, Xiao H, Zhao C (2021) Assessing habitat suitability for wintering geese by using normalized difference water index (NDWI) in a large floodplain wetland, China. Ecol Ind 122:107260

    Article  Google Scholar 

  • Tian X, Zhao G, Mu X, Zhang P, Tian P, Gao P, Sun W (2019b) Hydrologic alteration and possible underlying causes in the Wuding River, China. Sci Total Environ 693:133556

    Article  CAS  Google Scholar 

  • Tian Y, Xu C, Hong H, Zhou Q, Wang D (2019a) Mapping earthquake-triggered landslide susceptibility by use of artificial neural network (ANN) models: an example of the 2013 Minxian (China) Mw 5.9 event. Geomatics, Natural Hazards and Risk 10(1):1–25

    Article  Google Scholar 

  • Tonkin JD, Merritt DM, Olden JD, Reynolds LV, Lytle DA (2018) Flow regime alteration degrades ecological networks in riparian ecosystems. Nature Ecol Evol 2(1):86–93

    Article  Google Scholar 

  • Tootchi A, Jost A, Ducharne A (2019) Multi-source global wetland maps combining surface water imagery and groundwater constraints. Earth Syst Sci Data 11(1):189–220

    Article  Google Scholar 

  • Urzică A, Mihu-Pintilie A, Stoleriu CC, Cîmpianu CI, Huţanu E, Pricop CI, Grozavu A (2021) Using 2D HEC-RAS modeling and embankment dam break scenario for assessing the flood control capacity of a multi-reservoir system (NE Romania). Water 13(1):57

    Article  Google Scholar 

  • van Oorschot M, Kleinhans M, Buijse T, Geerling G, Middelkoop H (2018) Combined effects of climate change and dam construction on riverine ecosystems. Ecol Eng 120:329–344

    Article  Google Scholar 

  • Vidon PG, Welsh MK, Hassanzadeh YT (2019) Twenty years of riparian zone research (1997–2017): where to next? J Environ Qual 48(2):248–260

    Article  CAS  Google Scholar 

  • Wang Y, Zhang N, Wang D, Wu J, Zhang X (2018) Investigating the impacts of cascade hydropower development on the natural flow regime in the Yangtze River, China. Sci Total Environ 624:1187–1194

    Article  CAS  Google Scholar 

  • Wang D, Zhang S, Wang G, Han Q, Huang G, Wang H, Liu Y, Zhang Y (2019) Quantitative assessment of the influences of Three Gorges Dam on the water level of Poyang Lake, China. Water 11(7):1519

    Article  Google Scholar 

  • Wang Y, Zhang N, Wang D, Wu J (2020) Impacts of cascade reservoirs on Yangtze River water temperature: assessment and ecological implications. J Hydrol 590:125240

    Article  Google Scholar 

  • Wantzen, K.M., Yule, C.M., Tockner, K. and Junk, W.J., 2008. Riparian wetlands of tropical streams. In Tropical stream ecology (pp. 199-217). Academic Press.

  • Ward JV, Stanford JA (1989) The four-dimensional nature of lotic ecosystems. J N Am Benthol Soc 8:2–8

    Article  Google Scholar 

  • Warrens MJ, Pratiwi BC (2016) Kappa coefficients for circular classifications. J Classif 33(3):507–522

    Article  Google Scholar 

  • Weigend A, Gershenfeld N (1994) time series prediction: forecasting the future and understanding the past. Reading, Mass.: Addison- Wesley, Reading

  • Wondie A (2018) Ecological conditions and ecosystem services of wetlands in the Lake Tana Area, Ethiopia. Ecohydrol Hydrobiol 18(2):231–244

    Article  Google Scholar 

  • Xiong J, Li J, Cheng W, Wang N, Guo L (2019) A GIS-based support vector machine model for flash flood vulnerability assessment and mapping in China. ISPRS Intl J Geo-Inform 8(7):297

    Article  Google Scholar 

  • Xue L, Zhang H, Yang C, Zhang L, Sun C (2017) Quantitative assessment of hydrological alteration caused by irrigation projects in the Tarim river basin China. Sci Rep 7(1):1–13

    Google Scholar 

  • Yabusaki SB, Myers-Pigg AN, Ward ND, Waichler SR, Sengupta A, Hou Z, Chen X, Fang Y, Duan Z, Serkowski JA, Indivero J (2020) Floodplain inundation and salinization from a recently restored first-order tidal stream. Water Resour Res 56(7):e2019WR026850

    Article  Google Scholar 

  • Yan Y, Yang Z, Liu Q, Sun T (2010) Assessing effects of dam operation on flow regimes in the lower Yellow river. Proc Environ Sci 2:507–516

    Article  Google Scholar 

  • Yang T, Zhang Q, Chen YD, Tao X, Xu CY, Chen X (2008) A spatial assessment of hydrologic alteration caused by dam construction in the middle and lower Yellow River, China. Hydrol Process Intl J 22(18):3829–3843

    Article  Google Scholar 

  • Yang Z, Zhou M (2015) Weighted kappa statistic for clustered matched-pair ordinal data. Computational Statistics & Data Analysis 82:1–18

    Article  Google Scholar 

  • Zhang Y, Arthington AH, Bunn SE, Mackay S, Xia J, Kennard M (2012) Classification of flow regimes for environmental flow assessment in regulated rivers: the Huai River Basin, China. River Res Appl 28(7):989–1005

    Article  Google Scholar 

  • Zhao Z, Lou Y, Chen Y, Lin H, Li R, Yu G (2019) Prediction of interfacial interactions related with membrane fouling in a membrane bioreactor based on radial basis function artificial neural network (ANN). Bioresour Technol 282:262–268

    Article  CAS  Google Scholar 

  • Zheng Y, Zhang G, Wu Y, Xu YJ, Dai C (2019) Dam effects on downstream riparian wetlands: the Nenjiang River, Northeast China. Water 11(10):2038

    Article  Google Scholar 

Download references

Acknowledgements

The corresponding author of this article (Rajesh Sarda) would like to acknowledge University Grants Commission (UGC Ref. No.: 3430/(NET-DEC 2018)), New Delhi, India, for providing financial support as a Junior Research fellowship to conduct the research work presented in this paper. We would like to extend my gratitude to USGS for providing Landsat imageries.

Data availability

The datasets used and/or analyzed during the research work are available from the corresponding author on reasonable request.

Funding

The corresponding author of the article (Rajesh Sarda) would receive a Junior Research fellowship to conduct the research work.

Author information

Authors and Affiliations

  1. Department of Geography, University of Gour Banga, Malda, West Bengal, 732103, India

    Tamal Kanti Saha, Swades Pal & Rajesh Sarda

Authors
  1. Tamal Kanti Saha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Swades Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajesh Sarda
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study’s conception and design. Conceptualization, methodology designing, writing — review and editing — were performed by Dr. Swades Pal. Data curation, investigation, software, validation, and writing — original draft — were performed by Rajesh Sarda and Dr. Tamal Kanti Saha. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Rajesh Sarda.

Ethics declarations

Ethics approval

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Alexandros Stefanakis

Publisher’s note

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

Supplementary information

ESM 1

(DOCX 11 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saha, T.K., Pal, S. & Sarda, R. Impact of river flow modification on wetland hydrological and morphological characters. Environ Sci Pollut Res 29, 75769–75789 (2022). https://doi.org/10.1007/s11356-022-21072-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-022-21072-6

Keywords

Search

Navigation