Agricultural Water Management最新文献_第10页

A comparative life cycle assessment of drip and flood irrigation of in-shell pecan production in the Mesilla Valley, New Mexico, United States 美国新墨西哥州梅西拉山谷内壳山核桃生产滴灌和漫灌的生命周期比较评估

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-08 DOI: 10.1016/j.agwat.2025.109532

Raji Lukkoor , Colleen C. Naughton , Sara M. Torres , Richard Heerema , Rolando A. Flores Galarza , Joshua H. Viers , Alexander G. Fernald

{"title":"A comparative life cycle assessment of drip and flood irrigation of in-shell pecan production in the Mesilla Valley, New Mexico, United States","authors":"Raji Lukkoor , Colleen C. Naughton , Sara M. Torres , Richard Heerema , Rolando A. Flores Galarza , Joshua H. Viers , Alexander G. Fernald","doi":"10.1016/j.agwat.2025.109532","DOIUrl":"10.1016/j.agwat.2025.109532","url":null,"abstract":"<div><div>Quantifying the water use and environmental impacts of irrigated crops in arid regions is essential for sustainable agriculture. The arid southwestern state of New Mexico in the United States (US) is a major producer of pecans, a water-intensive crop. Climate change-induced surface water scarcity has increased reliance on pumped groundwater, resulting in higher emissions and causing aquifer depletion. This study uses a life cycle assessment (LCA) to quantify and compare the water use and environmental impacts of one kilogram of in-shell pecan production using drip and flood irrigation, making this the first LCA of pecan production. The cradle-to-farm gate system boundary includes the life cycle stages of pruning, irrigation, production, and harvest. Primary data sources include interviews with Mesilla Valley pecan producers, New Mexico State University extension publications and specialists, and state and County agriculture reports. Data analysis and modeling were conducted using the LCA software SimaPro 9.6.0.1. Four impact categories were assessed, including global warming potential, smog, ecotoxicity, and fossil fuel depletion. The production life cycle stage had the highest emissions (59–78 % across the four impact categories), driven by fertilizer production. Groundwater pumping accounted for 12–34 % of emissions in the four impact categories. Flood irrigation with groundwater reduced emissions by 63–87 % per kilogram of yield compared to drip irrigation with groundwater. A twofold system combining flood irrigation with surface water and drip irrigation with groundwater is recommended to balance aquifer recharge and emissions reductions. These findings can guide sustainable practices for pecans and other orchard crops in arid regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"315 ","pages":"Article 109532"},"PeriodicalIF":5.9,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rethinking the modernization of pressurized networks: Lessons from a case study in the Gharb (Morocco) 重新思考高压交通网络的现代化：以摩洛哥加尔布为例的经验教训

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-08 DOI: 10.1016/j.agwat.2025.109520

Abla Kettani , Ricardo Aliod , Marcel Kuper , Abdelilah Taky , Sami Bouarfa , Ali Hammani

{"title":"Rethinking the modernization of pressurized networks: Lessons from a case study in the Gharb (Morocco)","authors":"Abla Kettani , Ricardo Aliod , Marcel Kuper , Abdelilah Taky , Sami Bouarfa , Ali Hammani","doi":"10.1016/j.agwat.2025.109520","DOIUrl":"10.1016/j.agwat.2025.109520","url":null,"abstract":"<div><div>Irrigation modernization aims to improve water efficiency and reduce energy costs while ensuring the long-term sustainability of irrigation systems. However, restricted investments, and standardized management often create technical and economic constraints that limit farmers' ability to adapt irrigation methods to their needs. This study examines the 2012 collective drip irrigation project in the Gharb irrigation scheme (Morocco), adaptation of a previous existing network, which sought to replace sprinkler irrigation with drip irrigation to improve water and energy use. Despite initial adoption, 48 % of farmers reverted to sprinkler irrigation due to pressure deficiencies, soil constraints, and financial barriers. By means of an original methodology supported by hydraulic modeling and design tools (Gestar®) and field data collection, we evaluated alternative network operational conditions and infrastructure modifications to improve system reliability. The findings show that allowing farmers to combine drip and low-pressure sprinkler irrigation enhances flexibility while restraining water and energy use. Improving network performance requires resizing bottleneck pipes and adjusting head at pumping station, ensuring sufficient pressure at outlets for nominal conditions. These modifications must be economically viable, requiring cost-benefit analyses to balance infrastructure investments with long-term affordability. Beyond technical adjustments, the study highlights the importance of negotiation and participatory governance in irrigation modernization. While this case focuses on the Gharb region, the research approach, the challenges of infrastructure limits, adaptation strategies, and governance gaps are relevant to irrigation modernization worldwide. Ultimately, modernization should support farmer-centered irrigation systems, ensuring economic feasibility, resource efficiency, and adaptability to future challenges.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109520"},"PeriodicalIF":5.9,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating root zone soil moisture in farmland by integrating multi-source remote sensing data based on the water balance equation 基于水分平衡方程的多源遥感数据综合估算农田根区土壤水分

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-06 DOI: 10.1016/j.agwat.2025.109544

Xuqian Bai , Shuailong Fan , Ruiqi Li , Tianjin Dai , Wangye Li , Sumeng Ye , Long Qian , Lu Liu , Zhitao Zhang , Haorui Chen , Haiying Chen , Youzhen Xiang , Junying Chen , Shikun Sun

{"title":"Estimating root zone soil moisture in farmland by integrating multi-source remote sensing data based on the water balance equation","authors":"Xuqian Bai , Shuailong Fan , Ruiqi Li , Tianjin Dai , Wangye Li , Sumeng Ye , Long Qian , Lu Liu , Zhitao Zhang , Haorui Chen , Haiying Chen , Youzhen Xiang , Junying Chen , Shikun Sun","doi":"10.1016/j.agwat.2025.109544","DOIUrl":"10.1016/j.agwat.2025.109544","url":null,"abstract":"<div><div>Existing remote sensing approaches for estimating root zone soil moisture are limited by their dependence on initial conditions, sensitivity to model parameters, and high computational costs. This study proposes a lightweight model for predicting root zone soil moisture at the irrigation district scale. The model is developed based on the soil water balance equation and incorporates multi-source remote sensing data. A random forest algorithm is employed as the core predictive framework. The model is validated in the Jiefangzha Irrigation District. Results show: (1) The model achieves satisfactory accuracy, with site-level R values of 0.43–0.72 and RMSE of 0.007–0.01; for scattered locations, R values range from 0.53 to 0.66 and RMSE from 0.005 to 0.01; (2) Downscaling methods effectively resolve spatial scale mismatches, allowing substitution of water balance equation features and high-resolution simulations. Downscaling errors range from 12.56 %–16.60 % for RH, 3.18–3.61 mm for PET, 0.03–0.05 for kNDVI, 1.76–4.74 °C for LST, and 0.08–0.11 m³ /m³ for SSM; (3) Annual average AWF in 2018 and 2019 remains stable at ∼0.12, with daily variations mainly from late July to early September; (4) Initial soil moisture has minor impact on long-term simulations, with convergence after ∼40 days; (5) The relative importance of influencing factors is: AWFt-1, SMAPt-1, RH, kNDVI, SMAPt, precipitation, and PET. The proposed model reduces sensitivity and computational burden, enabling accurate root zone soil moisture prediction at the irrigation district scale.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109544"},"PeriodicalIF":5.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Carbon incentives and farm economics: A study of peatland drainage optimization 碳激励与农业经济：泥炭地排水优化研究

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-06 DOI: 10.1016/j.agwat.2025.109512

Janne Rämö , Domna Tzemi , Antti Miettinen , Henrik Wejberg , Heikki Lehtonen

{"title":"Carbon incentives and farm economics: A study of peatland drainage optimization","authors":"Janne Rämö , Domna Tzemi , Antti Miettinen , Henrik Wejberg , Heikki Lehtonen","doi":"10.1016/j.agwat.2025.109512","DOIUrl":"10.1016/j.agwat.2025.109512","url":null,"abstract":"<div><div>Natural, waterlogged peatlands are recognized as the most efficient carbon storage ecosystems, playing a critical role in climate regulation. However, in Europe, agriculture on drained peat soils — although comprising only 2.5 % of the agricultural area — contributes disproportionately, generating approximately 25 % of the EU’s total agricultural greenhouse gas emissions. This study examines the potential of drainage optimization and rewetting as strategies to reduce emissions from peatlands while balancing agricultural productivity. We quantitatively analyse the production, land use, and economic implications for farmers in two different farm scenarios using economic modelling and dynamic optimization. Our analysis evaluates the impact of carbon subsidy pricing on crop diversity and farmer income. Results indicate that while carbon subsidy prices have minimal influence on crop rotation diversity, they significantly affect farmers' income. With a subsidy price of 30€ per ton of CO<sub>2</sub> equivalent, or 80€ per ton in the case of high-value crops, farmers transition into \"carbon farmers\", obtaining higher share of total net present value from carbon subsidies rather than traditional agricultural income. Furthermore, the majority of climate benefits, including GHG reduction, are realized already at the 30€/tCO<sub>2</sub>e subsidy threshold. The findings suggest that carbon subsidies could offer a viable financial incentive for farmers to adopt peatland rewetting practices, which could reduce GHG emissions substantially. However, subsidy designs need careful calibration to ensure they do not distort agricultural practices or reduce crop diversity, while still delivering significant climate benefits.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109512"},"PeriodicalIF":5.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing crop water deficiency for regional adaptation to climate change 评估作物缺水状况以促进区域适应气候变化

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-06 DOI: 10.1016/j.agwat.2025.109525

Séverin Yvoz , Martin Lechenet , Philippe Amiotte-Suchet , Thierry Castel , Elisa Betting , Marjorie Ubertosi

{"title":"Assessing crop water deficiency for regional adaptation to climate change","authors":"Séverin Yvoz , Martin Lechenet , Philippe Amiotte-Suchet , Thierry Castel , Elisa Betting , Marjorie Ubertosi","doi":"10.1016/j.agwat.2025.109525","DOIUrl":"10.1016/j.agwat.2025.109525","url":null,"abstract":"<div><div>The increase in crop water stress is one of the most critical effects of climate change and threatens farm production and food security both locally and globally. The adaptation process of the entire food system must be grounded in a local quantitative assessment of future water requirements and the consequences for production losses if those requirements are not met. Thus, we developed a high-resolution crop water requirement model which integrates climate, soil and crop characteristics at a daily timestep. Our prospective study for 2100 (using the RCP8.5 climate scenario) at the regional scale (Bourgogne–Franche–Comté, BFC, in Eastern France) reveals a projected 8 % decrease in average grain production and a 14 % reduction in forage production. However, crop response to climate change vary both spatially and temporally. Summer crops are expected to bear a more marked impact from water stress, with an increase in variability over the years, amplifying the risk for human and animal food security. Other aspects of climate change, such as heat stress, late-spring frost, or an increase in pest pressure, could further impact yields. We emphasize the necessity of addressing climate change adaptation at the regional system level through multi-actor collaboration. Our reproducible approach serves as a rational starting point for designing new strategies based on a combination of adaptive responses at different scales, spanning from the field to the regional scale.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109525"},"PeriodicalIF":5.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of irrigation on cropland yield potential and scenario-based optimization in Northeast China 东北灌溉对农田产量潜力的影响及情景优化

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-06 DOI: 10.1016/j.agwat.2025.109522

Jiahui Li , Xinliang Xu , Luo Liu , Xiaojuan Deng , Shihao Wang

{"title":"Impact of irrigation on cropland yield potential and scenario-based optimization in Northeast China","authors":"Jiahui Li , Xinliang Xu , Luo Liu , Xiaojuan Deng , Shihao Wang","doi":"10.1016/j.agwat.2025.109522","DOIUrl":"10.1016/j.agwat.2025.109522","url":null,"abstract":"<div><div>As a key region for national food security, Northeast China (NEC) is under growing pressure to balance agricultural productivity and water availability amid global climate change and rising food demand. These challenges underscore the need for efficient, spatially targeted irrigation strategies to optimize water use and sustain crop production. In this study, we apply the Global Agro-Ecological Zones (GAEZ) model to assess the impacts of climate change and irrigation on yield potential dynamics across NEC from 2000 to 2020. We further conduct multi-scenario analysis to explore the outcomes of increasing irrigated area proportion by 10 %, 30 %, and 50 %, evaluating their effects on yield gap closure and climate change mitigation. Our results show an average annual increase in yield potential of 56.36 kg·ha<sup>−1</sup>·a<sup>−1</sup> across the region. Climate change caused a 1.23 % loss in multi-year total yield potential, with 68.28 % of these losses occurring in rainfed areas, while 80.54 % of yield gains were observed in irrigated areas. Except for rice, which experienced moderate gains (49.31 kg·ha⁻¹ annually), other major crops—particularly maize and soybeans—were negatively affected by climate trends. Irrigation offset nearly 4.81 times the total climate-induced yield losses, although its positive impact has declined over time. Among the scenarios, a 30 % increase in irrigated area proportion demonstrated the greatest potential, particularly for maize. Under this scenario, yield gaps could be closed and climate-induced losses fully compensated in 16.32 % and 17.82 % of NEC croplands, respectively, primarily in the southern Songnen Plain, Liao River Plain and Greater Khingan Mountains Region. These findings provide a scientific basis for optimizing irrigation strategies to ensure food security and promote sustainable water resource management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109522"},"PeriodicalIF":5.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An optimization framework for multi-year planning of land and water allocation 水土配置多年规划优化框架

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-05 DOI: 10.1016/j.agwat.2025.109505

Raphael Linker , Isaya Kisekka

{"title":"An optimization framework for multi-year planning of land and water allocation","authors":"Raphael Linker , Isaya Kisekka","doi":"10.1016/j.agwat.2025.109505","DOIUrl":"10.1016/j.agwat.2025.109505","url":null,"abstract":"<div><div>Multi-year planning of allocation of agricultural land and irrigation water remains a major challenge, which is exacerbated by decreasing arable land and increasing water scarcity in many regions. This paper presents a model-based framework to address this challenge. One of the key elements of the proposed framework is that it takes into account explicitly the need to rotate crops according to some agronomically-based sequences. The framework consists of three nested optimizations: Innermost: Optimize water allocation assuming pre-divided fields and pre-determined crop rotations. Middle: Optimize crop rotation sequences within each field. Outermost: Optimize fields geometry to maximize net income. These computations leverage crop- and soil-specific 'Yield value vs. Irrigation' functions derived from an auxiliary multi-objective optimization problem, namely maximizing yield and minimizing water use. In this manner, all the planning is based on the knowledge contained in complex crop growth models (rather than simplistic models), without having to actually run these models a prohibitively high number of times. The procedure is illustrated on two 67 ha areas near Davis, CA, that altogether contained seven types of soil. Planning was performed for a 10-year planning horizon, assuming seven crops (&fallowing) and six crop rotation patterns were available to choose from. Several scenarios that differed in terms of water availability are presented. The results demonstrate the strong impact that crop rotation requirements have on the overall performance.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109505"},"PeriodicalIF":5.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Inversion of citrus SPAD value and leaf water content by combining feature selection and ensemble learning algorithm using UAV remote sensing images 结合特征选择和集成学习算法反演柑橘SPAD值和叶片含水量

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-05 DOI: 10.1016/j.agwat.2025.109524

Quanshan Liu , Fei Chen , Ningbo Cui , Zongjun Wu , Xiuliang Jin , Shidan Zhu , Shouzheng Jiang , Daozhi Gong , Shunsheng Zheng , Lu Zhao , Zhihui Wang

{"title":"Inversion of citrus SPAD value and leaf water content by combining feature selection and ensemble learning algorithm using UAV remote sensing images","authors":"Quanshan Liu , Fei Chen , Ningbo Cui , Zongjun Wu , Xiuliang Jin , Shidan Zhu , Shouzheng Jiang , Daozhi Gong , Shunsheng Zheng , Lu Zhao , Zhihui Wang","doi":"10.1016/j.agwat.2025.109524","DOIUrl":"10.1016/j.agwat.2025.109524","url":null,"abstract":"<div><div>Soil and Plant Analyzer Development (SPAD) value and leaf water content (LWC) are critical physiological parameters for agricultural irrigation and growth monitoring in late-maturing citrus. Accurate monitoring of citrus SPAD value and LWC is of great significance for guiding precision irrigation, improving water use efficiency, and enhancing yield. To rapidly and efficiently obtain the SPAD value and LWC of citrus orchards, this study extracted vegetation index (VI) and texture feature (TF) of late-maturing citrus at different growth stages based on UAV multi-spectral images. Feature variable selection methods (decision tree (DT) and least absolute shrinkage and selection operator (Lasso)) were combined with Support vector machine regression (SVR), AdaBoost (Ada), SVR-AdaBoost (SVR-Ada) and WOA-SVR-Ada. Models for estimating SPAD value and LWC in citrus orchards were constructed using VI, TF, and VI+TF as inputs. The results showed that the DT algorithm demonstrated superior capability in identifying feature variables compared to the Lasso. The integration of VI and TF can enhance the inversion accuracy of citrus SPAD value and LWC models. Compared to the SVR, Ada and SVR-Ada, the WOA-SVR-Ada model, constructed by combining the DT algorithm with VI+TF as inputs (WOA-SVR-Ada<sub>D3</sub>), exhibited the highest estimation accuracy for both SPAD value and LWC. Therefore, combining feature variable selection methods with ensemble learning algorithms, along with the fusion of multi-feature information from UAV multispectral, holds promise for providing precise and robust estimations of SPAD value and LWC for late-maturing citrus in the seasonal drought regions of Southwest China.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109524"},"PeriodicalIF":5.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-term mulched drip irrigation enhances cotton yield by improving soil quality, microbial community structure, and N conversion 长期膜下滴灌通过改善土壤质量、微生物群落结构和氮转化来提高棉花产量

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-05 DOI: 10.1016/j.agwat.2025.109527

Wenhao Li , Shuanglong Gao , Wenying Qu , Junfeng Li , Tehseen Javed , Shih-Hsin Ho , Zhenhua Wang

{"title":"Long-term mulched drip irrigation enhances cotton yield by improving soil quality, microbial community structure, and N conversion","authors":"Wenhao Li , Shuanglong Gao , Wenying Qu , Junfeng Li , Tehseen Javed , Shih-Hsin Ho , Zhenhua Wang","doi":"10.1016/j.agwat.2025.109527","DOIUrl":"10.1016/j.agwat.2025.109527","url":null,"abstract":"<div><div>Long-term mulched drip irrigation can improve cotton yield, but its effectiveness depends on how long the land has been cultivated, and the mechanisms behind this relationship are not yet fully understood. In this study, the uncultivated wasteland was used as a control to systematically assess how varying lengths of cotton cultivation influence soil physicochemical properties, microbial community dynamics, and nitrogen (N) transformation pathways. The results revealed that: (1) converting wasteland into cotton fields significantly improved soil quality, with survival rate and yield increasing by 10.04 % and 13.60 %, respectively, in fields cultivated for 22 years compared to those cultivated for 8 years; (2) long-term cultivation markedly enhanced microbial diversity and the relative abundance of beneficial taxa associated with crop growth; (3) genes related to fungal glutamate synthesis and ammonification, as well as bacterial nitrogen fixation and nitrification, were significantly upregulated, while those involved in bacterial glutamate synthesis, nitrite reduction, denitrification, and ammonification were downregulated; (4) core microbial taxa exhibited significant positive correlations with nitrogen cycle–related functional genes; (5) fungal diversity showed a strong positive correlation with cotton yield, whereas bacterial diversity did not. In summary, long-term cultivation can regulate microbial community structure by improving soil quality, thereby enhancing cotton yield by promoting fungal-driven nitrogen cycling and suppressing bacterial denitrification.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109527"},"PeriodicalIF":5.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-destructive method using UAVs for high-throughput water productivity assessment for winter wheat cultivars 基于无人机的冬小麦品种高通量水分生产力无损评价方法

IF 5.9 1区农林科学

Agricultural Water Management Pub Date : 2025-05-05 DOI: 10.1016/j.agwat.2025.109526

Na Liu , Qingshan Liu , Zimeng Liu , Yang Lu , Zongzheng Yan , Liwei Shao

{"title":"Non-destructive method using UAVs for high-throughput water productivity assessment for winter wheat cultivars","authors":"Na Liu , Qingshan Liu , Zimeng Liu , Yang Lu , Zongzheng Yan , Liwei Shao","doi":"10.1016/j.agwat.2025.109526","DOIUrl":"10.1016/j.agwat.2025.109526","url":null,"abstract":"<div><div>Grain yield or biomass production per unit water consumption is defined as crop water productivity (WP). Using cultivars with high WP is important for reducing the negative influences of water shortages on agricultural production. Common methods for obtaining the WP of different cultivars are time-consuming and required considerable labor input. Developing nondestructive and high-throughput methods is essential for phenotyping cultivars with high WP. Unmanned aerial vehicles (UAVs) capture high spatiotemporal resolution remote sensing data, offering an opportunity to accurately estimate evapotranspiration (ET) and biomass during crop growing seasons to assess WP. In this study, the WP at the main growing stages of 10 winter wheat cultivars was assessed under three irrigation levels based on UAV-derived ET and biomass. Continuous daily ET was estimated by a new method combining the SEBAL (Surface Energy Balance Algorithm for Land) model, crop coefficient (K<sub>c</sub>) and soil water balance equation. Biomass was estimated from multispectral data, and five machine learning algorithms were compared, with random forest selected as the best performer. Using the ET and biomass estimates from the UAV flights, the WP for different growing periods of various winter wheat cultivars was obtained. The WP at the biomass level around the flowering stage was significantly correlated with the WP at the grain yield level for all the cultivars under the three irrigation conditions. Therefore, the WP monitored using UAVs during this period was used to assess the final WP of different cultivars, as biomass accumulation during this stage was critical for final grain production, and the daily ET also peaked at this time. The results from this study showed that UAVs based on non-destructive and high-throughput methods was feasible for assessing the WP of multiple cultivars to save labor and time.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109526"},"PeriodicalIF":5.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0