Agricultural Water Management最新文献

{"title":"Trade-offs among yield, water productivity, water footprint, and economic benefits for wheat production under conservation tillage: A long-term field experiment approach","authors":"Linlin Wang ,&nbsp;Lingling Li ,&nbsp;Junhong Xie ,&nbsp;Zhuzhu Luo ,&nbsp;Setor Kwami Fudjoe ,&nbsp;Jairo A. Palta ,&nbsp;Shiqing Li","doi":"10.1016/j.agwat.2025.109435","DOIUrl":"10.1016/j.agwat.2025.109435","url":null,"abstract":"<div><div>Water footprint (WF) is a water sustainable management indicator that quantifies the virtual water use in crop production. Water productivity (WP) and WF were examined under different tillage practices for wheat (<em>Triticumaestivum</em> L.) in the semiarid Loess Plateau of China. Wheat was grown in 2002 −2017 with six tillage practices: conventional tillage (T), no-till without straw cover (NT), conventional tillage with straw cover (TS), no-till with straw cover (NTS), conventional tillage with plastic mulching (TP), no-till with plastic mulching (NTP). Tillage practices did not significantly increase crop evapotranspiration, but NTS, TP, and NTP reduced soil evaporationwhile increasing transpiration, root growth and biomass accumulation. Additionally, NTS reduced the water consumption during the early stage but increased the water utilization from heading to harvest, while TP, and NTP exhibited the opposite pattern. Wheat yield under TS, NTS, TP, and NTP was higher by13, 28, 22, and 24 %, respectively, than under T, with corresponding improvements in water productivity of 15, 24, 26, and 24 %, respectively. The change in net economic return was 39, 21, 148, −49, and 18 % for NT, TS, NTS, TP, and NTP, respectively, compared to T; the sustainability yield index was 0.45, 0.41, 0.52, 0.55, 0.48 and 0.47, respectively. Total water consumption was significantly increased by 8.2 and 9.8 % under TS and NTS, respectively, compared to T. WF under NTS, TP and NTP was significantly decreased by 18.6, 18.5 and 22.3 % compared to T, respectively. These results suggests that NTS increased yield, economic benefits and WP with less WF through enhancing root growth and water utilization during the filling period. Therefore, NTS represented a sustainable a sustainable water management strategy for wheat in the semiarid Loess Plateau.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109435"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143666337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of crop water status using UAV-based images data with a model updating strategy","authors":"Ning Yang ,&nbsp;Zhitao Zhang ,&nbsp;Xiaofei Yang ,&nbsp;Ning Dong ,&nbsp;Qi Xu ,&nbsp;Junying Chen ,&nbsp;Shikun Sun ,&nbsp;Ningbo Cui ,&nbsp;Jifeng Ning","doi":"10.1016/j.agwat.2025.109445","DOIUrl":"10.1016/j.agwat.2025.109445","url":null,"abstract":"<div><div>This study aims to evaluate crop water status by fusing multiple features from the unmanned aerial vehicle (UAV)-based canopy images with model updating strategy. A UAV platform carrying multispectral and thermal infrared cameras was used to collect high spatial resolution images of winter wheat and summer maize under different water treatments over two years. The plant water content (PWC) and above-ground biomass (AGB), which represent crop water status, were collected simultaneously. The vegetation indices (VIs), texture features, and canopy thermal indicators were extracted from UAV-based images to estimate PWC and AGB based on CNN-LSTM-Attention (CLA) model. The results showed that combining spectral, textural, and thermal features with the CLA model significantly improved estimation accuracy. Specifically, multi-feature fusion achieved the best performance in winter wheat, with MAE of 1.80 % and 1.23 %, and RMSE of 2.13 % and 1.57 % for PWC in 2022 and 2023, respectively. For AGB, the corresponding MAE values were 1.12 t/hm² and 1.04 t/hm², and RMSE values were 1.41 t/hm² and 1.31 t/hm². In addition, the model updating strategy successfully verified the robustness of the estimation model for winter wheat across different years, and the application of the CLA model to summer maize demonstrated its effective transferability. In summary, this method can improve the estimation accuracy of PWC and AGB, thereby achieving efficient evaluation of crop water status.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109445"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143666336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of subsurface drainage and year-round irrigation on crop water-salt stress and yield in an arid region","authors":"Jiawei Liu ,&nbsp;Quanzhong Huang ,&nbsp;Zelin Hou ,&nbsp;Xiaojiang Zhu ,&nbsp;Fuping Xue ,&nbsp;Guanhua Huang","doi":"10.1016/j.agwat.2025.109406","DOIUrl":"10.1016/j.agwat.2025.109406","url":null,"abstract":"<div><div>Agricultural drainage mitigates soil salinization in farmland and enhances economic yield. As water resource challenges intensify, the need for effective and sustainable irrigation and drainage strategies increases. This study presents a 3-year experiment (2020–2022) on the effects of three irrigation quotas and subsurface drainage on soil water and salt dynamics, groundwater depth, and crop productivity in the Hetao Irrigation District. Drainage pipes were installed at a 1.5 m depth with a spacing of 45 m. The irrigation quotas for the subsurface drainage (SD) districts (SD1, SD2, and SD3) were 100, 140, and 180 mm during the preplanting period; 70, 100, and 130 mm during the sunflower growth period; and 160, 180, and 200 mm, during autumn, respectively. The control treatment (CK) followed the same quotas as SD3 without subsurface drainage. The annual SD volume was 75–99 mm. The groundwater depths in CK were 0.15–0.25 m shallower than SD areas. SD quickly regulated the groundwater depth, affecting soil water storage. During the irrigation–drainage period (May–November), the amount of salt discharged by the SD was 3.12–4.29 t ha⁻¹. The 33.96–46.02 % of soil salt storage changes in the 0–150 cm were drained away by subsurface pipes, whereas the remainder leached into deeper soil layers or groundwater. Preplanting irrigation combined with SD provided an optimal soil water and salinity environment for sunflower emergence. SD reduced salinity stress during the sunflower growth period and increased sunflower yields by 9.68–14.70 % over 3 years. Autumn irrigation and SD were crucial for soil salt leaching and soil moisture conservation. Considering the effects of SD, year-round precipitation and irrigation on sunflower yield and water productivity, a year-round water replenishment of 510 mm is optimal with SD in an arid region.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109406"},"PeriodicalIF":5.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel low-cost trunk load cell sensor for estimating canopy transpiration in the grapevine","authors":"Filippo Del Zozzo,&nbsp;Ginevra Canavera,&nbsp;Tommaso Frioni,&nbsp;Eugenio Magnanini,&nbsp;Stefano Poni","doi":"10.1016/j.agwat.2025.109432","DOIUrl":"10.1016/j.agwat.2025.109432","url":null,"abstract":"<div><div>Reliable, uninterrupted, and affordable measurements of vine water status continue to be a challenge within a global warming scenario. While recent work has concentrated on micro-tensiometers able to provide a continuous recording of trunk water potential, the current study provides the first calibration of a newly designed, low-cost load cell weight (LCW) transducer applied to the vine trunk, yielding an electric output in mV. The calibration run was conducted for 47 days (24 August–9 October 2022) on six mature field-grown and well-watered Cabernet Sauvignon vines enclosed in plastic chambers for uninterrupted monitoring of whole-vine transpiration (T_total). To broaden the range of T_total values, half of the vines were trimmed at flowering at eight main leaves. Correlations between the average daily T_total and maximum daily LCW difference for data pooled over the whole measuring period were considerably loose, with or without the inclusion of rainy or overcast days. Conversely, correlations between mean T_total and LCW the latter given as the diurnal maximum minus the instantaneous reading run from dawn to about 5 pm over 27 mostly clear days gave a very close fit (R² = 0.95–0.97) in both canopy treatments. Likewise, the same regressions run on data averaged over four mostly cloudy days maintained a similar accuracy (R² = 0.93–0.94) of the interpolated linear models. Once referred to data taken diurnally on either mostly clear or mostly cloudy days between sunrise and maximum T_total reached around 5 pm, the LCW sensor showed high accuracy. Moreover, the sensors were sensitive enough to detect differences induced by a variation in canopy size due to early shoot trimming. Its very low cost (around 12 euros), easy and fully non-invasive installment and negligible maintenance requirements encourage deeper evaluation in terms of sensitivity to phenology, cultivar and water supply levels.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109432"},"PeriodicalIF":5.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-objective synergistic optimization model considering the water-energy-food-carbon nexus and bioenergy","authors":"Gaiqiang Yang ,&nbsp;Yuxin Su ,&nbsp;Lijuan Huo ,&nbsp;Dongpeng Guo ,&nbsp;Yusi Wu","doi":"10.1016/j.agwat.2025.109431","DOIUrl":"10.1016/j.agwat.2025.109431","url":null,"abstract":"<div><div>As global climate change continues to pose significant challenges, it is increasingly essential to explore sustainable agricultural development strategies. This study aims to develop a multi-objective collaborative optimization model, using the Fen River Irrigation District as a case study. It examines strategies based on the water-energy-food-carbon nexus and seeks to maximize bioenergy production. The research methodology integrates multi-objective optimization theory with the ideal point method to obtain optimization solutions. This approach ensures the maximization of bioenergy output while minimizing carbon emissions and economic costs. The findings reveal that optimized bioenergy production in the study area can reach 1.17 × 10¹² J, with contributions of 29.50 % from agriculture and 70.50 % from animal husbandry. Notably, animal husbandry emerges as the primary source of bioenergy production, generating 8.27 × 10¹¹ J, predominantly from pigs, followed by sheep and cattle. The total optimized agricultural cultivation area is determined to be 6.76 × 10⁴ ha, with corn taking the largest share at 73.86 % of the total cultivated area, which improves the economic benefits of agriculture while increasing the production of bioenergy. Fruits and vegetables account for 8.69 %, wheat for 3.45 %, and legumes for 13.99 %. In terms of the economic and environmental implications of bioenergy production, agriculture contributes more significantly to the agricultural economy compared to animal husbandry. Carbon dioxide (CO₂) emissions are the major contributor to overall carbon emissions, followed by methane (CH₄). The optimized allocation of water resources results in a more reasonable ratio between surface water and groundwater supply, with 0.41 × 10⁸ m³ coming from groundwater and 1.93 × 10⁸ m³ from surface water, effectively alleviating the problem of regional water resources tension and guaranteeing the long-term stability of agricultural production. The optimization model focuses on generating solutions that conserve resources and reduce costs while simultaneously protecting the environment. This ultimately provides decision-makers with improved alternatives for managing agricultural resources.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109431"},"PeriodicalIF":5.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing the prediction of irrigation demand for open field vegetable crops in Germany through neural networks, transfer learning, and ensemble models","authors":"Samantha Rubo,&nbsp;Jana Zinkernagel","doi":"10.1016/j.agwat.2025.109402","DOIUrl":"10.1016/j.agwat.2025.109402","url":null,"abstract":"<div><div>Precise irrigation management in vegetable production is key for optimizing water use and ensuring crop productivity. This study develops two types of artificial neural networks (ANNs), multilayer perceptron (MLPs) and long short-term memory (LSTM) networks for the prediction of available water capacity (AWC in %) as target parameter for irrigation scheduling. These ANNs are trained with experimental data from three-year (2020–2023) open field trials with spinach on two sites in Germany, and for three soil layers (0–20 cm, 20–40 cm and 40–60 cm). This data encompassed soil texture, plant signals and plant developmental status derived from vegetation indices based on spectral reflectance along with meteorological variables including mean air temperature, humidity, wind speed, photothermal time, and their cumulative values. Two additional models are pretrained with freely accessible AWC data from 320 stations across Germany and subsequently fine-tuned with the same experimental data as before. An ANN ensemble model consolidates the knowledge from preceding models to enhance robustness and promote transferability to new climatic conditions and soil textures. Methods of explainable AI such as variable importance analysis and sensitivity analysis enhance the model explainability by identifying influential factors for each soil layer. Models trained with additional AWC data and fine-tuned with experimental performed best (R² &gt; 0.98, RMSE &lt;1.5 %) across all soil depths. The LSTM models perform slightly better than the MLP equivalent, emphasizing the importance of temporal dependencies in soil moisture prediction. The ensemble model minimized cumulative errors and provided stable results by averaging the outputs of all models. While ANNs provide highly accurate results, implementation requires expertise and resources of IT infrastructures such as the development of interfaces to weather stations and, if applicable, additional sensors. Consequently, deploying the ANN-based IS in practice requires a service provider with specialized knowledge in both IT and vegetable production for effective implementation and maintenance.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109402"},"PeriodicalIF":5.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of SIMDualKc model for irrigation scheduling of winter wheat in the Haouz plain, Morocco","authors":"Zaineb Bouswir ,&nbsp;Salah Er-Raki ,&nbsp;Saïd Khabba ,&nbsp;Jamal Ezzahar ,&nbsp;Hiba Ait Ben ahmed ,&nbsp;Zoubair Rafi ,&nbsp;Abdelghani Chehbouni","doi":"10.1016/j.agwat.2025.109430","DOIUrl":"10.1016/j.agwat.2025.109430","url":null,"abstract":"<div><div>Agricultural water management in arid and semi-arid regions faces significant challenges, exacerbated by climate change and rising food demand. To address this, the study proposes a strategy for tailoring the irrigation requirements of winter wheat according to its specific water needs at different development stages and under varying environmental conditions. For this purpose, the SIMDualKc model was used for irrigation scheduling to avoid water stress and percolation losses, thereby optimizing crop water use and supporting sustainable management practices.</div><div>The model was first calibrated and validated using various in situ data, including actual evapotranspiration <span><math><mrow><msub><mrow><mi>ET</mi></mrow><mrow><mi>c act</mi></mrow></msub><mspace></mspace></mrow></math></span>, available soil water in root zone (<em>ASW</em>), and vegetation cover fraction (<span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>), as well as the climatic forcing data. These data were collected over two winter wheat fields in the Chichaoua province (Center of Morocco) during two growing seasons (2016/2017 and 2017/2018). The comparison between simulation and measurement data shows promising results, with average values of RMSE (R²) being 0.56 mm/day (0.94), 0.08 (0.97) and 11.7 mm (0.94) for<span><math><mrow><mspace></mspace><msub><mrow><mi>ET</mi></mrow><mrow><mi>c act</mi></mrow></msub><mspace></mspace></mrow></math></span>, <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span> and <em>ASW</em>, respectively.</div><div>Additionally, the evaluation of the soil water balance, considering the irrigation amount supplied by the farmer, revealed substantial water losses through deep percolation for both fields during the two wheat seasons: 203 mm and 120 mm during the first season, and 435 mm and 307 mm during the second season, highlighting the necessity of optimized irrigation management practices. Using the SIMDualKc model, an optimized irrigation scheduling is proposed, achieving an important reduction of required irrigation amount by about 69 % of the amount supplied by the farmer without inducing water stress or percolation losses. This underscores the SIMDualKc’s potential for optimizing irrigation management of winter wheat cultivation in the Haouz region of Morocco.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109430"},"PeriodicalIF":5.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-mulching under no-tillage promotes maize root growth and improves yield by optimizing soil hydrothermal conditions in semi-arid regions","authors":"Jia Wang ,&nbsp;Jun Fan ,&nbsp;Huan Wang ,&nbsp;Xi Wang ,&nbsp;Yuzhu Xing ,&nbsp;Yongquan Gao ,&nbsp;Mingde Hao","doi":"10.1016/j.agwat.2025.109428","DOIUrl":"10.1016/j.agwat.2025.109428","url":null,"abstract":"<div><div>In dryland agricultural ecosystems, particularly in semi-arid regions, achieving sustainable crop production is crucial. Although no-tillage and mulching are common practices for conserving water and increasing yields, the combined effects of dual-mulching (straw and plastic film) under no-tillage on soil hydrothermal properties, root growth, and yield remain unclear. Based on the long-term field experiment established in the Loess Plateau of China in 2004, this study investigated the effects of conventional tillage (CT), no-tillage (NT), no-tillage with plastic film mulching (NTP), no-tillage with straw mulching (NTS), and no-tillage with dual mulching of straw and plastic film (NTSP) on soil water, temperature, root growth, and maize yield during the 2022–2023 growing season. The results revealed that NTSP significantly increased soil temperature at the 0–15 cm depth during the VE stage, while reducing the average soil temperature at the 0–30 cm depth during the V6-R3 stage (P &lt; 0.05). Compared to CT, NTSP significantly increased soil water content (SWC) and soil water storage (SWS) at various growth stages, thereby promoting increased root density during critical growth stages (P &lt; 0.05). Moreover, NTSP significantly improved grain yield and its components, biomass yield, water use efficiency (WUE), and rainfall use efficiency (RUE). The grain yield of NTSP increased by 17 % and 40 % compared to NTP and NTS (P &lt; 0.05). Correlation analysis indicated a significant negative correlation between soil temperature during the VT-R3 stage and root growth, while SWC at different stages showed a positive correlation with root growth (P &lt; 0.05). SWS had a greater impact on yield than soil temperature, with pre-sowing SWS having the greatest effect on yield. Overall, NTSP improves soil hydrothermal conditions, boosts root growth, and increases yields. It enhances water use efficiency, supports sustainable farming in semi-arid regions, and offers a solution for soil water conservation in dryland agriculture.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109428"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification of phosphorus-uptake effect on table grape (Vitis vinifera L.) cvs. Early Sweet and Crimson physiology, growth, and productivity using a lysimeter system","authors":"Patrick Mdemba ,&nbsp;Noemi Tel-Zur ,&nbsp;Gastone Tanga ,&nbsp;Uri Yermiyahu ,&nbsp;Noam Reshef ,&nbsp;Amnon Lichter ,&nbsp;Yonatan Ron ,&nbsp;Arnon Dag","doi":"10.1016/j.agwat.2025.109433","DOIUrl":"10.1016/j.agwat.2025.109433","url":null,"abstract":"<div><div>Evaluation of phosphorus (P) level is vital for vineyard management; however, our current understanding of how P supply affects table grapes, particularly growth, productivity, and quality parameters, is limited. We investigated the influence of various P-application levels on two table grape cultivars: the early-bearing white 'Early Sweet' and the late-bearing red 'Crimson'. During two consecutive seasons, grapevines were grown in 500-L lysimeters with perlite as the growth medium and subjected to three P-fertigation treatments (1, 5 and 15 mg L⁻¹ P). High P-utilization efficiency (&gt;90 %) was achieved for 1 and 5 mg L⁻¹ P. Levels of P application were reflected in the P levels of diagnostic leaves, with blade analysis providing more consistent results than petiole analysis. Increased P supply reduced sugar accumulation in developing fruit. Primary cluster number was reduced with increased P supply for 'Crimson' vines in 2022. Low P caused a reduction in SPAD in leaves toward the end of the summer, indicating the importance of P for chlorophyll stability. In addition, low levels of P led to reduced vegetative growth, as reflected in evapotranspiration and leaf area index in 'Early Sweet' and in the dry pruning weight of both cultivars. Precise P management in 'Early Sweet' and 'Crimson' may increase growth, yield, and fruit quality, and will enable better P-utilization efficiency, thereby reducing costs and environmental contamination.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109433"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated deep vertical rotary tillage and subsurface pipe drainage techniques for sustainable soil salinization management and cotton production in arid regions","authors":"Zhijie Li ,&nbsp;Qiang Meng ,&nbsp;Ling Li ,&nbsp;Zhentao Bai ,&nbsp;Yanjie Li ,&nbsp;Hongguang Liu ,&nbsp;Pengfei Li ,&nbsp;Tangang Wang","doi":"10.1016/j.agwat.2025.109429","DOIUrl":"10.1016/j.agwat.2025.109429","url":null,"abstract":"<div><div>Soil salinization impacts over 6 % of the world’s arable land, presenting an even greater challenge to agriculture in arid regions. This study assessed various subsurface pipe arrangements (B1: 1.0 m depth, 20 m spacing; B2: 0.8 m depth, 16 m spacing), deep vertical rotary tillage (DVRT) depths (DT40: 40 cm, DT60: 60 cm), and conventional tillage (CT) over the period from 2021 to 2023 to evaluate their long-term effects on soil properties, drainage characteristics, and crop production. The results indicated that the combination of DVRT and SPD significantly reduced the levels of salt and ions (Na⁺, K⁺, Mg²⁺, Ca²⁺, Cl⁻, and SO₄²⁻). Increasing tillage depth and reducing pipe spacing and depth significantly improved soil desalination and drainage but reduced soil water storage. Meanwhile, the total nitrogen (TN), phosphorus (TP), and potassium (TK) contents in the 0–20 cm soil layer were significantly reduced by 3–8 %, 3–6 %, and 9–19 %, respectively, compared to the CT treatment. Specifically, the DT60-B1 treatment exhibited the greatest soil desalination and drainage but also had the highest concentrations of TN, TP, and TK in the drainage. Although these changes initially caused a 5 % and 8 % decrease in average dry mass and yield, respectively, cotton’s uptake of Na⁺ and Cl⁻ decreased over time, while the uptake of Ca²⁺, as well as the accumulation of C, N, P, and K, along with yield, gradually increased. Random forest analysis showed that soil salinity and water storage significantly impacted yield, with electrical conductivity identified as the primary limiting factor. In 2023, the DT60–B1 treatment yielded significantly more than the CT treatment, and its comprehensive evaluation index increased from 0.44 to 0.67, indicating a shift from inhibition to promotion of crop growth over time. Long-term application requires optimizing pipeline layout and farming practices to improve productivity and sustain saline soil use.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"312 ","pages":"Article 109429"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}