IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16938-d1006342.html
   My bibliography  Save this article

Hydrological Response of Tropical Catchments to Climate Change as Modeled by the GR2M Model: A Case Study in Costa Rica

Author

Listed:
  • Maikel Mendez

    (Escuela de Ingeniería en Construcción, Instituto Tecnológico de Costa Rica, Cartago 30101, Costa Rica)

  • Luis-Alexander Calvo-Valverde

    (Escuela de Ingeniería en Computación, Instituto Tecnológico de Costa Rica, Cartago 30101, Costa Rica)

  • Pablo Imbach

    (Tropical Agricultural Research and Higher Education Center, Turrialba 30501, Costa Rica)

  • Ben Maathuis

    (Department of Water Resources, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7514 AE Enschede, The Netherlands)

  • David Hein-Grigg

    (Department of Geography, University of Exeter, Exeter EX4 4PS, UK)

  • Jorge-Andrés Hidalgo-Madriz

    (Gerencia Ambiental, Investigación y Desarrollo, Instituto Costarricense de Acueductos y Alcantarillados, San José 10109, Costa Rica)

  • Luis-Fernando Alvarado-Gamboa

    (Unidad de Climatología, Departamento de Desarrollo, Instituto Meteorológico Nacional (IMN), Ministerio del Ambiente y Energía (MINAE), San José 10109, Costa Rica)

Abstract

This study aimed to assess the impacts of climate change on streamflow characteristics of five tropical catchments located in Costa Rica. An ensemble of five General Circulation Models (GCMs), namely HadGEM2-ES, CanESM2, EC-EARTH, MIROC5, MPI-ESM-LR dynamically downscaled by two Regional Climate Models (RCMs), specifically HadRM3P and RCA4, was selected to provide an overview of the impacts of different climate change scenarios under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the 1961–1990 baseline period. The GR2M hydrological model was used to reproduce the historical monthly surface runoff patterns of each catchment. Following calibration and validation of the GRM2 model, the projected impact of climate change on streamflow was simulated for a near-future (2011–2040), mid-future (2041–2070) and far-future (2071–2100) for each catchment using the bias-corrected GCM-RCM multimodel ensemble-mean (MEM). Results anticipate wetter conditions for all catchments in the near-future and mid-future periods under RCPs 2.6 and 4.5, whereas dryer conditions are expected for the far-future period under RCP 8.5. Projected temperature trends indicate consistently warmer conditions with increasing radiative forcing and future periods. Streamflow changes across all catchments however are dominated by variations in projected precipitation. Wetter conditions for the near-future and mid-future horizons under RCPs 2.6 and 4.5 would result in higher runoff volumes, particularly during the late wet season (LWS). Conversely, dryer conditions for the far-future period under RCP8.5 would result in considerably lower runoff volumes during the early wet season (EWS) and the Mid-Summer Drought (MSD). In consequence, projected seasonal changes on streamflow across all catchments may result in more frequent flooding, droughts, and water supply shortage compared to historical hydrological regimes.

Suggested Citation

  • Maikel Mendez & Luis-Alexander Calvo-Valverde & Pablo Imbach & Ben Maathuis & David Hein-Grigg & Jorge-Andrés Hidalgo-Madriz & Luis-Fernando Alvarado-Gamboa, 2022. "Hydrological Response of Tropical Catchments to Climate Change as Modeled by the GR2M Model: A Case Study in Costa Rica," Sustainability, MDPI, vol. 14(24), pages 1-31, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16938-:d:1006342
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16938/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/24/16938/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Renate Wilcke & Thomas Mendlik & Andreas Gobiet, 2013. "Multi-variable error correction of regional climate models," Climatic Change, Springer, vol. 120(4), pages 871-887, October.
    2. Matthias Themeßl & Andreas Gobiet & Georg Heinrich, 2012. "Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal," Climatic Change, Springer, vol. 112(2), pages 449-468, May.
    3. Julio Pérez-Sánchez & Javier Senent-Aparicio & Francisco Segura-Méndez & David Pulido-Velazquez & Raghavan Srinivasan, 2019. "Evaluating Hydrological Models for Deriving Water Resources in Peninsular Spain," Sustainability, MDPI, vol. 11(10), pages 1-36, May.
    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. Philippe Roudier & Jafet C. M. Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    2. Markus Stoffel & Thomas Mendlik & Michelle Schneuwly-Bollschweiler & Andreas Gobiet, 2014. "Possible impacts of climate change on debris-flow activity in the Swiss Alps," Climatic Change, Springer, vol. 122(1), pages 141-155, January.
    3. A. Casanueva & J. Bedia & S. Herrera & J. Fernández & J. M. Gutiérrez, 2018. "Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool," Climatic Change, Springer, vol. 147(3), pages 411-425, April.
    4. Philippe Roudier & Jafet Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    5. Xu Chen & Ruiguang Han & Ping Feng & Yongjie Wang, 2022. "Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1305-1337, January.
    6. Salem, Golam Saleh Ahmed & Kazama, So & Shahid, Shamsuddin & Dey, Nepal C., 2018. "Impacts of climate change on groundwater level and irrigation cost in a groundwater dependent irrigated region," Agricultural Water Management, Elsevier, vol. 208(C), pages 33-42.
    7. Pascalle Smith & Georg Heinrich & Martin Suklitsch & Andreas Gobiet & Markus Stoffel & Jürg Fuhrer, 2014. "Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change," Climatic Change, Springer, vol. 127(3), pages 521-534, December.
    8. Schönhart, Martin & Mitter, Hermine & Schmid, Erwin & Heinrich, Georg & Gobiet, Andreas, 2014. "Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(3).
    9. Yi Yang & Jianping Tang, 2023. "Downscaling and uncertainty analysis of future concurrent long-duration dry and hot events in China," Climatic Change, Springer, vol. 176(2), pages 1-25, February.
    10. Polo, Jesús & Ballestrín, Jesús & Carra, Elena, 2020. "Assessment and improvement of modeling the atmospheric attenuation based on aerosol optical depth information with applicability to solar tower plants," Energy, Elsevier, vol. 208(C).
    11. Zafar Iqbal & Shamsuddin Shahid & Tarmizi Ismail & Zulfaqar Sa’adi & Aitazaz Farooque & Zaher Mundher Yaseen, 2022. "Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    12. Leibin Wang & Robert V. Rohli & Qigen Lin & Shaofei Jin & Xiaodong Yan, 2022. "Impact of Extreme Heatwaves on Population Exposure in China Due to Additional Warming," Sustainability, MDPI, vol. 14(18), pages 1-13, September.
    13. Jie Chen & Xunchang John Zhang, 2021. "Challenges and potential solutions in statistical downscaling of precipitation," Climatic Change, Springer, vol. 165(3), pages 1-19, April.
    14. Mohamed Salem Nashwan & Shamsuddin Shahid & Eun-Sung Chung, 2020. "High-Resolution Climate Projections for a Densely Populated Mediterranean Region," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    15. Victoria M. Garibay & Margaret W. Gitau & Nicholas Kiggundu & Daniel Moriasi & Fulgence Mishili, 2021. "Evaluation of Reanalysis Precipitation Data and Potential Bias Correction Methods for Use in Data-Scarce Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1587-1602, March.
    16. He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
    17. Lorenzo Sangelantoni & Eleonora Gioia & Fausto Marincioni, 2018. "Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 849-884, September.
    18. Thi Lan Anh Dinh & Filipe Aires, 2023. "Revisiting the bias correction of climate models for impact studies," Climatic Change, Springer, vol. 176(10), pages 1-30, October.
    19. Roland Kaitna & Andreas Gobiet & Franz Sinabell & Markus Stoffel, 2014. "DEUCALION – Determining and Visualising Impacts of Greenhouse Climate Rainfall in Alpine Watersheds on Torrential Disasters," WIFO Studies, WIFO, number 59816, April.
    20. Xumin Zhang & Simin Qu & Jijie Shen & Yingbing Chen & Xiaoqiang Yang & Peng Jiang & Peng Shi, 2023. "Effect of Distinct Evaluation Objectives on Different Precipitation Downscaling Methods and the Corresponding Potential Impacts on Catchment Runoff Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1913-1930, March.

    More about this item

    Keywords

    bias-correction; climate-change; GCM; GR2M; RCM; RCP; streamflow; precipitation;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    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:gam:jsusta:v:14:y:2022:i:24:p:16938-:d:1006342. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.