Tangzhe Nie , Peng Zhang , Peng Chen , Haijun Liu , Lili Jiang , Zhongyi Sun , Shuai Yin , Tianyi Wang , Tiecheng Li , Zhongxue Zhang
{"title":"Impacts of climate change and water–fertilizer management on water balance dynamics in transplanting and direct–seeded paddy fields","authors":"Tangzhe Nie , Peng Zhang , Peng Chen , Haijun Liu , Lili Jiang , Zhongyi Sun , Shuai Yin , Tianyi Wang , Tiecheng Li , Zhongxue Zhang","doi":"10.1016/j.csag.2025.100070","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change and alterations in water and fertilizer management exert profound impact on water balance of paddy fields, posing uncertainty regarding the sustainability of rice production. This study investigates the interplay between climate change and water and fertilizer management on the water balance of paddy fields, aiming to ensure sustainable water use and agricultural production security. Utilizing a 24<strong>-</strong>year experimental dataset (1978<strong>–</strong>2001), the study examines the effects of climate variability and management strategies on water balance parameters. The independent variables included in this study were water surface evaporation, effective rainfall, wind speed, sunlight duration, relative humidity, average temperature, maximum daily temperature, minimum daily temperature, minimum relative humidity, average water vapour pressure, accumulated temperature, water depth, and nitrogen application. Advanced statistical techniques, including grey relational analysis, path analysis, and principal component analysis, were employed to assess the impacts of independent variables on water consumption, evapotranspiration, percolation, transpiration, and evaporation. This research focuses on two cropping modes: water direct<strong>–</strong>seeded mode (WDM) and transplanting mode (PM). The grey relational analysis demonstrated that climate change, and water<strong>–</strong>fertilizer management, had differing effects on various water balance parameters. Path analysis revealed that temperature and humidity had the greatest direct and indirect effects. Principal component analysis grouped the variables and found that the significant factors under WDM influencing PC1 included maximum daily temperature, minimum daily temperature, nitrogen application, average temperature, wind speed, and relative humidity, which collectively accounted for 39.6 %. The significant factors affecting PC1 under PM included relative humidity, minimum relative humidity, effective rainfall, sunlight duration, and average water vapour pressure, which together accounted for 30.1 % of the total variation. The findings of this study indicated that water surface evaporation, accumulated temperature, and water depth played a relatively minor role in influencing the water balance of paddy fields across both cropping modes. This research contributes to the advancement of climate<strong>–</strong>smart agriculture, emphasizing the conservation of water resources while striving for optimal yields.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"2 3","pages":"Article 100070"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate Smart Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950409025000310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Climate change and alterations in water and fertilizer management exert profound impact on water balance of paddy fields, posing uncertainty regarding the sustainability of rice production. This study investigates the interplay between climate change and water and fertilizer management on the water balance of paddy fields, aiming to ensure sustainable water use and agricultural production security. Utilizing a 24-year experimental dataset (1978–2001), the study examines the effects of climate variability and management strategies on water balance parameters. The independent variables included in this study were water surface evaporation, effective rainfall, wind speed, sunlight duration, relative humidity, average temperature, maximum daily temperature, minimum daily temperature, minimum relative humidity, average water vapour pressure, accumulated temperature, water depth, and nitrogen application. Advanced statistical techniques, including grey relational analysis, path analysis, and principal component analysis, were employed to assess the impacts of independent variables on water consumption, evapotranspiration, percolation, transpiration, and evaporation. This research focuses on two cropping modes: water direct–seeded mode (WDM) and transplanting mode (PM). The grey relational analysis demonstrated that climate change, and water–fertilizer management, had differing effects on various water balance parameters. Path analysis revealed that temperature and humidity had the greatest direct and indirect effects. Principal component analysis grouped the variables and found that the significant factors under WDM influencing PC1 included maximum daily temperature, minimum daily temperature, nitrogen application, average temperature, wind speed, and relative humidity, which collectively accounted for 39.6 %. The significant factors affecting PC1 under PM included relative humidity, minimum relative humidity, effective rainfall, sunlight duration, and average water vapour pressure, which together accounted for 30.1 % of the total variation. The findings of this study indicated that water surface evaporation, accumulated temperature, and water depth played a relatively minor role in influencing the water balance of paddy fields across both cropping modes. This research contributes to the advancement of climate–smart agriculture, emphasizing the conservation of water resources while striving for optimal yields.