IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v312y2025ics0378377425001660.html
   My bibliography  Save this article

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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    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. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrand, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," Econometrics and Statistics, Elsevier, vol. 5(C), pages 20-44.
    3. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    4. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    5. 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.
    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. 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.
    8. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    9. 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.
    10. repec:plo:pone00:0042309 is not listed on IDEAS
    11. Groll, Andreas & Hambuckers, Julien & Kneib, Thomas & Umlauf, Nikolaus, 2019. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 140(C), pages 59-73.
    12. Westgate, Bradford S. & Woodard, Dawn B. & Matteson, David S. & Henderson, Shane G., 2016. "Large-network travel time distribution estimation for ambulances," European Journal of Operational Research, Elsevier, vol. 252(1), pages 322-333.
    13. Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
    14. Komlos, John & Brabec, Marek, 2011. "The trend of BMI values of US adults by deciles, birth cohorts 1882-1986 stratified by gender and ethnicity," Economics & Human Biology, Elsevier, vol. 9(3), pages 234-250, July.
    15. Luis Vanegas & Gilberto Paula, 2015. "A semiparametric approach for joint modeling of median and skewness," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 110-135, March.
    16. Jianzhu Li & Yuming Lei & Senming Tan & Colin D. Bell & Bernard A. Engel & Yixuan Wang, 2018. "Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4239-4252, October.
    17. Uddameri, Venkatesh & Ghaseminejad, Ali & Hernandez, E. Annette, 2020. "A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels," Agricultural Water Management, Elsevier, vol. 238(C).
    18. Lei Zou & Jun Xia & Dunxian She, 2018. "Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1421-1438, March.
    19. Zhao, Weihua & Lian, Heng & Song, Xinyuan, 2017. "Composite quantile regression for correlated data," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 15-33.
    20. Alexander Sohn & Nadja Klein & Thomas Kneib, 2014. "A New Semiparametric Approach to Analysing Conditional Income Distributions," SOEPpapers on Multidisciplinary Panel Data Research 676, DIW Berlin, The German Socio-Economic Panel (SOEP).
    21. Peth, Denise & Mußhoff, Oliver & Funke, Katja & Hirschauer, Norbert, 2018. "Nudging Farmers to Comply With Water Protection Rules – Experimental Evidence From Germany," Ecological Economics, Elsevier, vol. 152(C), pages 310-321.

    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.