IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i1p847-d1023538.html
   My bibliography  Save this article

The Impact of Climate Change on Evapotranspiration and Flow in a Major Basin in Northern Mexico

Author

Listed:
  • Aldo Rafael Martínez-Sifuentes

    (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, CENID-RASPA, Gómez Palacio C.P. 35150, Durango, Mexico)

  • Ramón Trucíos-Caciano

    (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, CENID-RASPA, Gómez Palacio C.P. 35150, Durango, Mexico)

  • Víctor Manuel Rodríguez-Moreno

    (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Campo Experimental Pabellón, Km 32.5, Carretera Aguascalientes—Zacatecas, Pabellón de Arteaga C.P. 20660, Aguascalientes, Mexico)

  • José Villanueva-Díaz

    (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, CENID-RASPA, Gómez Palacio C.P. 35150, Durango, Mexico)

  • Juan Estrada-Ávalos

    (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, CENID-RASPA, Gómez Palacio C.P. 35150, Durango, Mexico)

Abstract

Climate defines the hydrological cycle of each region and climate change will undoubtedly affect the recharge processes of the world’s water tables and the water resources currently available at the basin and microbasin scale. The objective of the present paper is to evaluate future changes in evapotranspiration and flows from the Sardinas River basin in North Durango, Mexico. The Rural Genius Model (GR2M) is an aggregated monthly hydrological model, which is used to reconstruct flows from precipitation and evapotranspiration by applying two functions: a production function and a transfer function. A transfer function has been used under four shared socioeconomic pathway scenarios (126, 245, 370, and 585). Pettitt and Mann–Kendall statistical tests were used to determine trends, which were identified by the breakpoint in the evapotranspiration and flow time series. Results showed that under climate change scenarios, evapotranspiration shows an increase over time. Under the climate scenario, SSP 126, and the application of the statistical test in the flow series show an increasing trend with a break in May for 2090, with a mean of 1658 mm before and 2238 mm after the break, with an excess of 34.98%. The flow under the SSP 245 climate scenario predicts a mean flow of 1703.11 mm and a break in May of the 2090 horizon, with a mean before and after the break of 1624 mm and 2168 mm, respectively, with an excess of 33.49%. Under the SSP 370 scenario, the mean is expected to be 1710.81 mm, with a break in May 2090, before and after means of 1633 mm and 2166 mm, respectively, with an excess of 32.63%. Under climate change scenario SSP 585, the mean expected will be 1701.43 mm and the break in the flow series will occur in May of the 2090 horizon, with a mean of 1628 mm before the break and 2132 mm after, with a flow excess of 30.95%. The results of this study can be a basis for decision-makers for better management and protection of water resources in northern Durango, Mexico.

Suggested Citation

  • Aldo Rafael Martínez-Sifuentes & Ramón Trucíos-Caciano & Víctor Manuel Rodríguez-Moreno & José Villanueva-Díaz & Juan Estrada-Ávalos, 2023. "The Impact of Climate Change on Evapotranspiration and Flow in a Major Basin in Northern Mexico," Sustainability, MDPI, vol. 15(1), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:1:p:847-:d:1023538
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/847/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/1/847/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martin Jung & Markus Reichstein & Philippe Ciais & Sonia I. Seneviratne & Justin Sheffield & Michael L. Goulden & Gordon Bonan & Alessandro Cescatti & Jiquan Chen & Richard de Jeu & A. Johannes Dolman, 2010. "Recent decline in the global land evapotranspiration trend due to limited moisture supply," Nature, Nature, vol. 467(7318), pages 951-954, October.
    2. A. N. Pettitt, 1979. "A Non‐Parametric Approach to the Change‐Point Problem," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(2), pages 126-135, June.
    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. Stephen J. Déry & Marco A. Hernández-Henríquez & Tricia A. Stadnyk & Tara J. Troy, 2021. "Vanishing weekly hydropeaking cycles in American and Canadian rivers," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    2. Tao, Hai & Diop, Lamine & Bodian, Ansoumana & Djaman, Koffi & Ndiaye, Papa Malick & Yaseen, Zaher Mundher, 2018. "Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso," Agricultural Water Management, Elsevier, vol. 208(C), pages 140-151.
    3. Kazi Ali Tamaddun & Ajay Kalra & Sajjad Ahmad, 2019. "Spatiotemporal Variation in the Continental US Streamflow in Association with Large-Scale Climate Signals Across Multiple Spectral Bands," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 1947-1968, April.
    4. Jie Yang & Yimin Wang & Jun Yao & Jianxia Chang & Guoxin Xu & Xin Wang & Hui Hu, 2020. "Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin," 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. 103(2), pages 1711-1726, September.
    5. Alina Bărbulescu & Cristian Ștefan Dumitriu, 2021. "On the Connection between the GEP Performances and the Time Series Properties," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
    6. Alfredas Račkauskas & Martin Wendler, 2020. "Convergence of U-processes in Hölder spaces with application to robust detection of a changed segment," Statistical Papers, Springer, vol. 61(4), pages 1409-1435, August.
    7. Hsin-Yu Chen & Yu-Hsiang Hsu & Chia-Chi Huang & Hsin-Fu Yeh, 2023. "Baseflow Variation in Southern Taiwan Basin," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    8. Catherine Araujo Bonjean & Alioune N’diaye & Olivier Santoni, 2019. "Who benefits from the return of the rains? The case of the Ferlo breeders in Senegal [A qui profite le retour des pluies ? Le cas des éleveurs du Ferlo]," CERDI Working papers halshs-02419601, HAL.
    9. Feng, Jiaojiao & Wang, Weizhen & Xu, Feinan & Wang, Shengtang, 2024. "Evaluating the ability of deep learning on actual daily evapotranspiration estimation over the heterogeneous surfaces," Agricultural Water Management, Elsevier, vol. 291(C).
    10. Songbai Hong & Jinzhi Ding & Fei Kan & Hao Xu & Shaoyuan Chen & Yitong Yao & Shilong Piao, 2023. "Asymmetry of carbon sequestrations by plant and soil after forestation regulated by soil nitrogen," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    11. Roquia Salam & Abu Reza Md. Towfiqul Islam & Shakibul Islam, 2020. "Spatiotemporal distribution and prediction of groundwater level linked to ENSO teleconnection indices in the northwestern region of Bangladesh," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4509-4535, June.
    12. Zhang, Yixiao & He, Tao & Liang, Shunlin & Zhao, Zhongguo, 2023. "A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches," Agricultural Water Management, Elsevier, vol. 289(C).
    13. Jing Xu & Ping Zhao & Johnny C. L. Chan & Mingyuan Shi & Chi Yang & Siyu Zhao & Ying Xu & Junming Chen & Ling Du & Jie Wu & Jiaxin Ye & Rui Xing & Huimei Wang & Lu Liu, 2024. "Increasing tropical cyclone intensity in the western North Pacific partly driven by warming Tibetan Plateau," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    14. Song, Lisheng & Bateni, Sayed M. & Xu, Yanhao & Xu, Tongren & He, Xinlei & Ki, Seo Jin & Liu, Shaomin & Ma, Minguo & Yang, Yang, 2021. "Reconstruction of remotely sensed daily evapotranspiration data in cloudy-sky conditions," Agricultural Water Management, Elsevier, vol. 255(C).
    15. Yuanfang Chai & Yao Yue & Louise J. Slater & Jiabo Yin & Alistair G. L. Borthwick & Tiexi Chen & Guojie Wang, 2022. "Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    16. Sanghyuk Yoo & Sangyong Jeon & Seunghwan Jeong & Heesoo Lee & Hosun Ryou & Taehyun Park & Yeonji Choi & Kyongjoo Oh, 2021. "Prediction of the Change Points in Stock Markets Using DAE-LSTM," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    17. Uilson Ricardo Venâncio Aires & Demetrius David Silva & Michel Castro Moreira & Carlos Antônio Alvares Soares Ribeiro & Celso Bandeira de Melo Ribeiro, 2020. "The Use of the Normalized Difference Vegetation Index to Analyze the Influence of Vegetation Cover Changes on the Streamflow in the Manhuaçu River Basin, Brazil," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 1933-1949, April.
    18. Joseph Ngatchou-Wandji & Echarif Elharfaoui & Michel Harel, 2022. "On change-points tests based on two-samples U-Statistics for weakly dependent observations," Statistical Papers, Springer, vol. 63(1), pages 287-316, February.
    19. Hsin-Yu Chen & Chia-Chi Huang & Hsin-Fu Yeh, 2021. "Quantifying the Relative Contribution of the Climate Change and Human Activity on Runoff in the Choshui River Alluvial Fan, Taiwan," Land, MDPI, vol. 10(8), pages 1-14, August.
    20. Xue Zhong & Xiaohui Jiang & Leilei Li & Jing Xu & Huanyu Xu, 2020. "The Impact of Socio-Economic Factors on Sediment Load: A Case Study of the Yanhe River Watershed," Sustainability, MDPI, vol. 12(6), pages 1-18, March.

    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:15:y:2023:i:1:p:847-:d:1023538. 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.