IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v487y2024ics0304380023002983.html
   My bibliography  Save this article

Assessing the contribution of hydrologic and climatic factors on vegetation condition changes in semi-arid wetlands: An analysis for the Narran Lakes

Author

Listed:
  • Liu, Moyang
  • Hamilton, Serena H.
  • Jakeman, Anthony J.
  • Lerat, Julien
  • Savage, Callum
  • Croke, Barry F.W.

Abstract

Vegetation in semi-arid wetlands often serve as a critical habitat and refuge for a wide range of species. In many wetlands, on-ground monitoring of vegetation is either not comprehensive or unavailable, which impedes our understanding of the system. However, basic data on climate and hydrological variables, as well as remote sensing data, can often be acquired. The Narran Lakes system in the Lower Balonne catchment in New South Wales, Australia, is a Ramsar-listed wetland and an exemplar in terms of possessing such basic data. For the Narran Lakes we conducted correlation analysis between the anomaly of the Normalized Difference Vegetation Index (NDVI) as response variable and various climatic and hydrological factors as explanatory variables taking into account different time-lag and accumulative time-averaged effects. The generalized additive model framework was used to identify the contribution of the individual variables to NDVI and examine the nonlinear interactions of the hydro-climatic, water availability factors (soil moisture, precipitation and inflow in the study) on NDVI change within the Narran Lakes. We also undertook various cross-validation exercises to appreciate uncertainties in the results. The results show that: (1) Soil moisture is the primary factor influencing NDVI; and (2) Water availability factors interact in a complex manner to affect NDVI and, more specifically, these factors have a positive impact on NDVI, although the degree of impact differs; (3) The impact of the hydrological and climatic factors is highly variable between wet and dry resource states, both for the whole floodplain vegetation and its lignum community. Overall, the analysis improved our understanding of how the driving factors affect vegetation growth, thus supporting the monitoring and management of vegetation communities in the Narran Lakes. The methods can be applied to other wetlands with similar data availability.

Suggested Citation

  • Liu, Moyang & Hamilton, Serena H. & Jakeman, Anthony J. & Lerat, Julien & Savage, Callum & Croke, Barry F.W., 2024. "Assessing the contribution of hydrologic and climatic factors on vegetation condition changes in semi-arid wetlands: An analysis for the Narran Lakes," Ecological Modelling, Elsevier, vol. 487(C).
    • Handle: RePEc:eee:ecomod:v:487:y:2024:i:c:s0304380023002983
    DOI: 10.1016/j.ecolmodel.2023.110568
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023002983
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110568?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Luobin Yan & Ruixiang He & Milica Kašanin-Grubin & Gusong Luo & Hua Peng & Jianxiu Qiu, 2017. "The Dynamic Change of Vegetation Cover and Associated Driving Forces in Nanxiong Basin, China," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    2. Siyuan Tian & Albert I. J. M. Van Dijk & Paul Tregoning & Luigi J. Renzullo, 2019. "Forecasting dryland vegetation condition months in advance through satellite data assimilation," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    3. Jean-François Pekel & Andrew Cottam & Noel Gorelick & Alan S. Belward, 2016. "High-resolution mapping of global surface water and its long-term changes," Nature, Nature, vol. 540(7633), pages 418-422, December.
    4. Marra, Giampiero & Wood, Simon N., 2011. "Practical variable selection for generalized additive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2372-2387, July.
    5. Paul Omute & Rob Corner & Joseph Awange, 2012. "The use of NDVI and its Derivatives for Monitoring Lake Victoria’s Water Level and Drought Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1591-1613, April.
    6. Wen, Li & Yang, Xihua & Saintilan, Neil, 2012. "Local climate determines the NDVI-based primary productivity and flooding creates heterogeneity in semi-arid floodplain ecosystem," Ecological Modelling, Elsevier, vol. 242(C), pages 116-126.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giacomo Falchetta & Nicolò Stevanato & Magda Moner-Girona & Davide Mazzoni & Emanuela Colombo & Manfred Hafner, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," Working Papers 2020.09, Fondazione Eni Enrico Mattei.
    2. Zak-Szatkowska, Malgorzata & Bogdan, Malgorzata, 2011. "Modified versions of the Bayesian Information Criterion for sparse Generalized Linear Models," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2908-2924, November.
    3. Christina Kassara & Christos Barboutis & Anastasios Bounas, 2025. "Favorable stopover sites and fuel load dynamics of spring bird migrants under a changing climate," Climatic Change, Springer, vol. 178(1), pages 1-19, January.
    4. Nicolás Ruiz, Néstor & Suárez Alonso, María Luisa & Vidal-Abarca, María Rosario, 2021. "Contributions of dry rivers to human well-being: A global review for future research," Ecosystem Services, Elsevier, vol. 50(C).
    5. Jinlong Li & Genxu Wang & Chunlin Song & Shouqin Sun & Jiapei Ma & Ying Wang & Linmao Guo & Dongfeng Li, 2024. "Recent intensified erosion and massive sediment deposition in Tibetan Plateau rivers," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    6. Marivoet, Wim & Ulimwengu, John M., 2024. "Spatial typology for food system analysis: Taking stock and setting a research agenda," World Development Perspectives, Elsevier, vol. 35(C).
    7. Mohammad Zeynoddin & Hossein Bonakdari & Silvio José Gumiere & Alain N. Rousseau, 2023. "Multi-Tempo Forecasting of Soil Temperature Data; Application over Quebec, Canada," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    8. Ogilvie, Andrew & Fall, Cheickh Sadibou & Bodian, Ansoumana & Martin, Didier & Bruckmann, Laurent & Dia, Djiby & Leye, Issa & Ndiaye, Papa Malick & Soro, Donissongou Dimitri & Danumah, Jean Homian & B, 2025. "Surface water and flood-based agricultural systems: Mapping and modelling long-term variability in the Senegal river floodplain," Agricultural Water Management, Elsevier, vol. 308(C).
    9. Vinícius B. P. Chagas & Pedro L. B. Chaffe & Günter Blöschl, 2022. "Climate and land management accelerate the Brazilian water cycle," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    10. Finlay, Jessica & Esposito, Michael & Langa, Kenneth M. & Judd, Suzanne & Clarke, Philippa, 2022. "Cognability: An Ecological Theory of neighborhoods and cognitive aging," Social Science & Medicine, Elsevier, vol. 309(C).
    11. Zhang, Yuliang & Wu, Zhiyong & Singh, Vijay P. & Lin, Qingxia & Ning, Shaowei & Zhou, Yuliang & Jin, Juliang & Zhou, Rongxing & Ma, Qiang, 2023. "Agricultural drought characteristics in a typical plain region considering irrigation, crop growth, and water demand impacts," Agricultural Water Management, Elsevier, vol. 282(C).
    12. Paulilo Brasil & Pedro Medeiros, 2020. "NeStRes – Model for Operation of Non-Strategic Reservoirs for Irrigation in Drylands: Model Description and Application to a Semiarid Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 195-210, January.
    13. Juan Armando Torres Munguía, 2018. "What is behind homicide gender gaps in Mexico? A spatial semiparametric approach," Ibero America Institute for Econ. Research (IAI) Discussion Papers 236, Ibero-America Institute for Economic Research.
    14. Donghui Xu & Gautam Bisht & Zeli Tan & Eva Sinha & Alan V. Vittorio & Tian Zhou & Valeriy Y. Ivanov & L. Ruby Leung, 2024. "Climate change will reduce North American inland wetland areas and disrupt their seasonal regimes," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    15. Qianhan Wu & Linghong Ke & Jida Wang & Tamlin M. Pavelsky & George H. Allen & Yongwei Sheng & Xuejun Duan & Yunqiang Zhu & Jin Wu & Lei Wang & Kai Liu & Tan Chen & Wensong Zhang & Chenyu Fan & Bin Yon, 2023. "Satellites reveal hotspots of global river extent change," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    16. Alexander Kreuzer & Luciana Dalla Valle & Claudia Czado, 2022. "A Bayesian non‐linear state space copula model for air pollution in Beijing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 613-638, June.
    17. Abbasi, H.N. & Zeeshan, Muhammad, 2023. "An integrated Geographic Information System and Analytical Hierarchy process based approach for site suitability analysis of on-grid hybrid concentrated solar-biomass powerplant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    18. Gressani, Oswaldo & Lambert, Philippe, 2021. "Laplace approximations for fast Bayesian inference in generalized additive models based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
    19. Yi Xi & Shushi Peng & Gang Liu & Agnès Ducharne & Philippe Ciais & Catherine Prigent & Xinyu Li & Xutao Tang, 2022. "Trade-off between tree planting and wetland conservation in China," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    20. Falchetta, Giacomo & Stevanato, Nicolò & Moner-Girona, Magda & Mazzoni, Davide & Colombo, Emanuela & Hafner, Manfred, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," FEP: Future Energy Program 305213, Fondazione Eni Enrico Mattei (FEEM) > FEP: Future Energy Program.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:487:y:2024:i:c:s0304380023002983. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.