IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v312y2025ics0378377425001660.html

Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity

Author

Listed:
  • Dai, Meng
  • Feng, Ping
  • Li, Jianzhu
  • Shi, Xiaogang
  • Wang, Hanye

Abstract

Precipitation deficit will directly affect soil water, and soil water deficit will directly influence crop growth and exert a definite influence on the hydrological cycle. At present, drought propagation is based mainly on the hypothesis of serial stationarity to analyze the propagation from meteorological drought (MD) to soil moisture drought (SMD), but with global climate change, the hypothesis of stationarity has been overturned. Research on drought propagation under nonstationarity is lacking. To this end, it is exceedingly meaningful to explore the propagation from MD to SMD under nonstationary conditions. Taking three regions of Luanhe River Basin (LRB) as the subject of study, the generalized additive models for location, scale and shape (GAMLSS) model was utilized to construct a nonstationary drought index. The drought propagation time (PTm) and propagation threshold (PTr) were calculated via conditional probability, and the dynamic change in drought propagation was analyzed via a moving window. Finally, the optimal parameters of the model were established on the basis of land use data from 1980 via the soil and water assessment tool (SWAT) model, and the land use data from 2000 and 2018 were replaced to investigate the comprehensive effects of land use/cover change (LUCC) and climate on drought propagation. The findings indicated that (1) the precipitation and soil moisture series were nonstationary during the growing season from 1962 to 2018; (2) the shortest static PTm was observed for Chengde in spring and autumn and Hanjiaying in summer, and the drought propagation process in Hanjiaying was accelerating during the whole growing season; (3) under the two drought scenarios (moderate and severe), the largest static PTr of drought occurred in the spring of Sandaohezi and the summer and autumn of Hanjiaying, and the MD of Sandaohezi was more likely to trigger SMD in autumn; and (4) the LUCC had little influence on the drought PTm and PTr in the basin by changing the land use data of different periods (2000 and 2018) based on the SWAT model with fixed parameters. These findings have important implications for early warning of agricultural drought and water resource management in watersheds.

Suggested Citation

  • Dai, Meng & Feng, Ping & Li, Jianzhu & Shi, Xiaogang & Wang, Hanye, 2025. "Effects of land use/cover change on propagation dynamics from meteorological to soil moisture drought considering nonstationarity," Agricultural Water Management, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:agiwat:v:312:y:2025:i:c:s0378377425001660
    DOI: 10.1016/j.agwat.2025.109452
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377425001660
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2025.109452?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Caixia Liu & Rui Xu & Kaiji Xu & Yiwen Lin & Yingui Cao, 2023. "Carbon Emission Effects of Land Use in Chaobai River Region of Beijing–Tianjin–Hebei, China," Land, MDPI, vol. 12(6), pages 1-23, June.
    2. Yanjun Wang & Shanshan Wen & Xiucang Li & Fischer Thomas & Buda Su & Run Wang & Tong Jiang, 2016. "Spatiotemporal distributions of influential tropical cyclones and associated economic losses in China in 1984–2015," 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. 84(3), pages 2009-2030, December.
    3. Qiaoqiao Gong & Piling Sun & Qingguo Liu & Junxiong Mo, 2022. "Topographical Gradient Characteristics of Land-Use Changes in the Agro-Pastoral Ecotone of Northern China," Land, MDPI, vol. 11(12), pages 1-19, December.
    4. Jing Zhuge & Jie Zeng & Wanxu Chen & Chi Zhang, 2023. "Impacts of Land-Use Change on Ecosystem Services Value in the South-to-North Water Diversion Project, China," IJERPH, MDPI, vol. 20(6), pages 1-20, March.
    5. Yixuan Wang & Jianzhu Li & Ping Feng & Fulong Chen, 2015. "Effects of large-scale climate patterns and human activities on hydrological drought: a case study 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. 76(3), pages 1687-1710, April.
    6. 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.
    7. Lingling Bin & Weichao Yang & Kui Xu, 2023. "Driving Force Exploration for Flash Flood Based on Mann–Kendall Test and Geographical Detector: A Case Study of Hainan Island, China," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    8. Donald Wilhite & Mark Svoboda & Michael Hayes, 2007. "Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 763-774, May.
    9. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    10. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    11. Li, Jiale & Li, Yu & Yin, Lei & Zhao, Quanhua, 2024. "A novel composite drought index combining precipitation, temperature and evapotranspiration used for drought monitoring in the Huang-Huai-Hai Plain," Agricultural Water Management, Elsevier, vol. 291(C).
    12. Fulong Chen & Jianzhu Li, 2016. "Quantifying drought and water scarcity: a case study in the Luanhe 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. 81(3), pages 1913-1927, April.
    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. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    2. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    3. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    4. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    5. Lucio Masserini & Matilde Bini & Monica Pratesi, 2017. "Effectiveness of non-selective evaluation test scores for predicting first-year performance in university career: a zero-inflated beta regression approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 693-708, March.
    6. Tong, Edward N.C. & Mues, Christophe & Thomas, Lyn, 2013. "A zero-adjusted gamma model for mortgage loan loss given default," International Journal of Forecasting, Elsevier, vol. 29(4), pages 548-562.
    7. Alexander Silbersdorff & Kai Sebastian Schneider, 2019. "Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    8. Tong, Edward N.C. & Mues, Christophe & Brown, Iain & Thomas, Lyn C., 2016. "Exposure at default models with and without the credit conversion factor," European Journal of Operational Research, Elsevier, vol. 252(3), pages 910-920.
    9. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    10. D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," 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. 117(3), pages 2617-2646, July.
    11. Shuhui Guo & Lihua Xiong & Jie Chen & Shenglian Guo & Jun Xia & Ling Zeng & Chong-Yu Xu, 2023. "Nonstationary Regional Flood Frequency Analysis Based on the Bayesian Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 659-681, January.
    12. Maike Hohberg & Katja Landau & Thomas Kneib & Stephan Klasen & Walter Zucchini, 2018. "Vulnerability to poverty revisited: Flexible modeling and better predictive performance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(3), pages 439-454, September.
    13. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    14. Epstein, Leonardo D. & Inostroza-Quezada, Ignacio E. & Goodstein, Ronald C. & Choi, S. Chan, 2021. "Dynamic effects of store promotions on purchase conversion: Expanding technology applications with innovative analytics," Journal of Business Research, Elsevier, vol. 128(C), pages 279-289.
    15. Serinaldi, Francesco, 2011. "Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape," Energy Economics, Elsevier, vol. 33(6), pages 1216-1226.
    16. Yolanda M. Gómez & Diego I. Gallardo & Marcelo Bourguignon & Eduardo Bertolli & Vinicius F. Calsavara, 2023. "A general class of promotion time cure rate models with a new biological interpretation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 66-86, January.
    17. Christophe Croux & Irène Gijbels & Ilaria Prosdocimi, 2012. "Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models," Biometrics, The International Biometric Society, vol. 68(1), pages 31-44, March.
    18. I. Gijbels & I. Prosdocimi & G. Claeskens, 2010. "Nonparametric estimation of mean and dispersion functions in extended generalized linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 580-608, November.
    19. repec:plo:pone00:0042309 is not listed on IDEAS
    20. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    21. Ana María Martínez-Rodríguez & Antonio Conde-Sánchez & María José Olmo-Jiménez, 2019. "A new approach to truncated regression for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 503-526, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:eee:agiwat:v:312:y:2025:i:c:s0378377425001660. 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.elsevier.com/locate/agwat .

    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.