Wenxin Xie , Hui Ran , Anni Deng , Kunhao Jiang , Han Ru , Ning Yao , Jianqiang He , Tehseen Javed , Xiaotao Hu
{"title":"气候变化促进渭河流域夏玉米产量和水分生产力的变化——基于分布式作物模型的区划研究","authors":"Wenxin Xie , Hui Ran , Anni Deng , Kunhao Jiang , Han Ru , Ning Yao , Jianqiang He , Tehseen Javed , Xiaotao Hu","doi":"10.1016/j.agwat.2025.109500","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change represents a significant threat to global food security, underscoring the critical need to predict its impacts on crop yield and water productivity (WP). This study employed a two-stage evaluation process to select four global climate models (GCMs) from a pool of 13 GCMs, based on four shared socio-economic pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). A comparative analysis of the average weighted fusion method and the least squares weighted fusion method revealed that the latter was more suitable for future solar radiation data fusion. The distributed DSSAT-CERES-Maize model was employed to simulate summer maize yield and WP in the Weihe River Basin from 1982 to 2099, incorporating crop cultivation and irrigation areas. Machine learning quantified the relative importance of key meteorological factors influencing spatial variations in yield and WP. The prediction indicates that future temperature and rainfall increases will become more widespread across the basin. By 2099, the maximum temperature is expected to rise by an average of 2.5°C, the minimum temperature by 2.6°C, and rainfall by 71 mm. In contrast, solar radiation is projected to decrease in more areas. In the future, escalating mitigation challenges over time will drive a spatial shift in high-yield areas (≥7500 kg ha⁻¹) and areas with increased yield and WP (historically 1.5 times higher), migrating from the southeastern to the northwestern parts of the Weihe River Basin—transitioning from historically wetter to drier areas. Simultaneously, the southeastern region is expected to experience yield and WP reductions of up to 40 %. Under rainfed conditions, WP is projected to benefit more than under irrigation as mitigation challenges intensify. Rising temperatures emerge as the dominant factor influencing yield and WP changes across 82 % of the basin on average, serving as the primary driver of the spatial shift in yield- and WP-increasing zones. This study provides theoretical support for farmers and policymakers in specifying appropriate management measures for the Weihe River Basin to adapt to climate change, aiming to ensure sustainable agricultural development and enhance summer maize productivity.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109500"},"PeriodicalIF":5.9000,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Climate change promotes shifts of summer maize yield and water productivity in the Weihe River Basin: A regionalization study based on a distributed crop model\",\"authors\":\"Wenxin Xie , Hui Ran , Anni Deng , Kunhao Jiang , Han Ru , Ning Yao , Jianqiang He , Tehseen Javed , Xiaotao Hu\",\"doi\":\"10.1016/j.agwat.2025.109500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Climate change represents a significant threat to global food security, underscoring the critical need to predict its impacts on crop yield and water productivity (WP). This study employed a two-stage evaluation process to select four global climate models (GCMs) from a pool of 13 GCMs, based on four shared socio-economic pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). A comparative analysis of the average weighted fusion method and the least squares weighted fusion method revealed that the latter was more suitable for future solar radiation data fusion. The distributed DSSAT-CERES-Maize model was employed to simulate summer maize yield and WP in the Weihe River Basin from 1982 to 2099, incorporating crop cultivation and irrigation areas. Machine learning quantified the relative importance of key meteorological factors influencing spatial variations in yield and WP. The prediction indicates that future temperature and rainfall increases will become more widespread across the basin. By 2099, the maximum temperature is expected to rise by an average of 2.5°C, the minimum temperature by 2.6°C, and rainfall by 71 mm. In contrast, solar radiation is projected to decrease in more areas. In the future, escalating mitigation challenges over time will drive a spatial shift in high-yield areas (≥7500 kg ha⁻¹) and areas with increased yield and WP (historically 1.5 times higher), migrating from the southeastern to the northwestern parts of the Weihe River Basin—transitioning from historically wetter to drier areas. Simultaneously, the southeastern region is expected to experience yield and WP reductions of up to 40 %. Under rainfed conditions, WP is projected to benefit more than under irrigation as mitigation challenges intensify. Rising temperatures emerge as the dominant factor influencing yield and WP changes across 82 % of the basin on average, serving as the primary driver of the spatial shift in yield- and WP-increasing zones. This study provides theoretical support for farmers and policymakers in specifying appropriate management measures for the Weihe River Basin to adapt to climate change, aiming to ensure sustainable agricultural development and enhance summer maize productivity.</div></div>\",\"PeriodicalId\":7634,\"journal\":{\"name\":\"Agricultural Water Management\",\"volume\":\"314 \",\"pages\":\"Article 109500\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2025-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural Water Management\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378377425002148\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Water Management","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378377425002148","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
Climate change promotes shifts of summer maize yield and water productivity in the Weihe River Basin: A regionalization study based on a distributed crop model
Climate change represents a significant threat to global food security, underscoring the critical need to predict its impacts on crop yield and water productivity (WP). This study employed a two-stage evaluation process to select four global climate models (GCMs) from a pool of 13 GCMs, based on four shared socio-economic pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). A comparative analysis of the average weighted fusion method and the least squares weighted fusion method revealed that the latter was more suitable for future solar radiation data fusion. The distributed DSSAT-CERES-Maize model was employed to simulate summer maize yield and WP in the Weihe River Basin from 1982 to 2099, incorporating crop cultivation and irrigation areas. Machine learning quantified the relative importance of key meteorological factors influencing spatial variations in yield and WP. The prediction indicates that future temperature and rainfall increases will become more widespread across the basin. By 2099, the maximum temperature is expected to rise by an average of 2.5°C, the minimum temperature by 2.6°C, and rainfall by 71 mm. In contrast, solar radiation is projected to decrease in more areas. In the future, escalating mitigation challenges over time will drive a spatial shift in high-yield areas (≥7500 kg ha⁻¹) and areas with increased yield and WP (historically 1.5 times higher), migrating from the southeastern to the northwestern parts of the Weihe River Basin—transitioning from historically wetter to drier areas. Simultaneously, the southeastern region is expected to experience yield and WP reductions of up to 40 %. Under rainfed conditions, WP is projected to benefit more than under irrigation as mitigation challenges intensify. Rising temperatures emerge as the dominant factor influencing yield and WP changes across 82 % of the basin on average, serving as the primary driver of the spatial shift in yield- and WP-increasing zones. This study provides theoretical support for farmers and policymakers in specifying appropriate management measures for the Weihe River Basin to adapt to climate change, aiming to ensure sustainable agricultural development and enhance summer maize productivity.
期刊介绍:
Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.