Agricultural Water Management最新文献

{"title":"Root zone soil moisture mapping at very high spatial resolution using radar-derived surface soil moisture product","authors":"Nadia Ouaadi ,&nbsp;Abdelghani Chehbouni ,&nbsp;Emna Ayari ,&nbsp;Bouchra Ait Hssaine ,&nbsp;Jamal ElFarkh ,&nbsp;Michel Le Page ,&nbsp;Salah Er-Raki ,&nbsp;Aaron Boone","doi":"10.1016/j.agwat.2025.109507","DOIUrl":"10.1016/j.agwat.2025.109507","url":null,"abstract":"<div><div>Root zone soil moisture (RZSM) is a key variable controlling the soil-vegetation-atmosphere exchanges. Its estimation is vital for monitoring hydrological, meteorological and agricultural processes. A number of large-scale products exist but with a coarse resolution (&gt;1 km), which is not suitable for plot-scale studies. The aim of this work is to map RZSM, for the first time, at very high spatial resolution using a very high spatial resolution surface soil moisture (SSM) product and a recursive exponential filter. SSM is estimated from Sentinel-1 data using the water cloud model at a resolution of approximately 50 m. The approach was evaluated on a database consisting of 12 fields, including 7 winter wheat and 5 summer maize fields, irrigated using different techniques. The results show that the approach performs reasonably well using Sentinel-1 SSM product with correlation coefficient (R) between 0.3 and 0.82, root-mean-square error (RMSE) between 0.05 and 0.12 m³/m³ and a bias in the range −0.1–0.07 m³/m³, at 15–20 cm depth. This is equivalent to R = 0.6, RMSE = 0.12 m³/m³ and bias = 0.07 m³/m³ using the entire database, which is quite low compared to the use of in situ SSM measurements (R = 0.81, RMSE = 0.07 m³/m³ and bias = 0.03 m³/m³). This is related to inaccuracies in the SSM product, where fields with good SSM estimation also resulted in good RZSM estimation and conversely. In addition to SSM, the approach is also sensitive to its time constant T. Analysis of RZSM sensitivity to T shows that the optimum T value depends on soil texture, climate and measurement depth. In particular, low optimum T values (1 day) are obtained for loamy and sandy loam soils, while higher values (5–10 days) are optimal for soils with a high clay fraction, at 15–20 cm depth. These values increase with soil depth and are influenced by seasonal atmospheric demand. Combined to reasonable statistical metrics, the spatial variability depicted by the RZSM maps opens up prospects for high-resolution RZSM mapping from Sentinel-1 SSM data using a simple approach over annual crops. This is of prime relevance for agricultural applications requiring very high-resolution estimation at plot scale, such as crop yield, irrigation and fertilizer management, as well as for the assessment of inter-plot variability.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109507"},"PeriodicalIF":5.9,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882847","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}

{"title":"Mild water deficit during maturity reduces cracking rate of greenhouse muskmelon while improving fruit quality","authors":"Qimin Xue ,&nbsp;Hao Li ,&nbsp;Taisheng Du","doi":"10.1016/j.agwat.2025.109465","DOIUrl":"10.1016/j.agwat.2025.109465","url":null,"abstract":"<div><div>Fruit cracking is frequent in fleshy fruits and is closely related to unreasonable irrigation, affecting fruit yield and quality at harvest and therefore sales. However, it remains to be demonstrated whether there are reasonable deficit irrigation (DI) practices that could reduce fruit cracking while ensuring that yield is not reduced and fruit quality is improved. Three-season (spring 2021, spring 2022 and summer 2022) deficit irrigation experiments were conducted to investigated the responses of greenhouse muskmelons (<em>Cucumis melo</em> var. chinensis) in terms of plants water status, yield, irrigation water productivity (IWP), fruit cracking rate, output value and fruit quality. Results showed that cracked fruit rate was significantly positive with irrigation amount at fruit maturity stage (stage M). Furthermore, it was related with stem water potential at midday and transpiration just at stage M, not flowering-swelling stage (stage F). Although yield and IWP were not significantly affected under mild DI applied at stage M, cracked fruit rate was significantly decreased by 73 %, resulting in the highest output value. The application of DI during both stage F and M had a negative impact on fruit size, fresh weight and dry matter weight, but had a remarkable positive effect on the accumulation of soluble solids such as sugars. The comprehensive quality score based on principal component analysis and membership function method revealed that severe DI applied at entire reproductive period had optimal comprehensive quality score. Entropy-TOPSIS result indicated that mild deficit irrigation applied at stage M was a reasonable strategy for greenhouse substrate cultivation of muskmelon. This study provides a reasonable irrigation regime, which not only helps to improve fruit quality and ensure yield at harvest, but also reduces economic losses due to lower fruit cracking and opens up new prospects for horticultural production.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109465"},"PeriodicalIF":5.9,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878951","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}

{"title":"Assessment of saline water irrigation on biomass and quality of alfalfa: A sustainable agriculture perspective","authors":"Boyuan Lou ,&nbsp;Yanzhe Hu ,&nbsp;Teng Li ,&nbsp;Qingsong Liu ,&nbsp;Jintao Wang ,&nbsp;Xinliang Dong ,&nbsp;Liu Tian ,&nbsp;Xuejia Zhang ,&nbsp;Wenxin Bian ,&nbsp;Tong Liu ,&nbsp;Menghao Zhao ,&nbsp;Hongyong Sun","doi":"10.1016/j.agwat.2025.109504","DOIUrl":"10.1016/j.agwat.2025.109504","url":null,"abstract":"<div><div>The lack of freshwater resources is a critical limiting factor for the crop production in the arid and semi-arid regions. Saline water irrigation presents a viable solution for addressing freshwater scarcity, particularly in North China Plain, by leveraging saline water resources to sustain crop production while minimizing soil salinity accumulation through seasonal rainfall leaching. This study assessed the effects of saline water irrigation (5.0 and 7.6 dS/m) on alfalfa biomass and quality across five irrigation amounts (20–100 mm) in 2022–2023. Results showed that reasonable saline water irrigation significantly enhanced alfalfa biomass and quality. Biomass increased markedly in the first two harvests (H1, H2) due to the irrigation but not in the latter two (H3, H4). The maximum biomass achieved at 60 mm (5.0 dS/m, 15.99 t/ha) and 76 mm (7.6 dS/m, 14.71 t/ha), representing 40.3 % and 24.3 % increases over rainfed controls. Early-season harvests (H1-H2) exhibited 10–67 % biomass enhancements primarily through stem growth (35–80 % contribution). CP was significantly increased at the H1 with irrigation of 60 mm (5.0 dS/m), whereas elevated salinity (7.6 dS/m) increased ADF and NDF content. Saline water irrigation elevated soil EC, while summer rainfall effectively leached salts, maintaining 0–40 cm soil salinity below alfalfa tolerance thresholds. Structural equation modeling quantified critical interactions: irrigation amount directly enhanced biomass while elevating soil EC, and water salinity indirectly reduced yield via EC accumulation. The optimal irrigation amounts were determined to be 51.0–72.3 mm for 5.0dS/m saline water and 58.3–76.0 mm for 7.6dS/m water, which balanced 20–40 % yield gains with stable interannual soil EC.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109504"},"PeriodicalIF":5.9,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878518","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}

{"title":"Field-scale evaluation of low-elevation and mobile drip irrigation systems","authors":"Masoumeh Hashemi,&nbsp;Matt Yost,&nbsp;Jonathan Holt","doi":"10.1016/j.agwat.2025.109502","DOIUrl":"10.1016/j.agwat.2025.109502","url":null,"abstract":"<div><div>Available water in arid watersheds is scarce and is projected to decline in the future. Therefore, optimizing water use in all sectors, especially the agricultural sector with the highest consumptive use, is critical. One common option for optimizing water use is improving irrigation system efficiency. In this on-farm study, three irrigation technologies for center pivots at different irrigation levels were investigated over space and time. Satellite imagery was used to examine the performance of each treatment at a field scale for different crops during 2016–2020. Relative yield change among various crops was calculated to compare treatments spatially and temporally. Finally, relative yield changes were simulated using the most accurate machine learning models for each irrigation technology. The sensitivity of feature importance was evaluated using sensitivity analysis and SHAP (SHapley Additive exPlanations), an interpretable machine learning method based on game theory. The results showed that the performance of irrigation systems was influenced by climate conditions such as temperature and precipitation, as well as field features. For example, in drought years, soil electrical conductivity (EC) had the highest influence for some irrigation technologies, while in years with more normal precipitation, elevation had the greatest impact. The method proposed in this paper can be applied in other fields to evaluate irrigation technologies and support better decision-making aimed at enhancing agricultural productivity.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"314 ","pages":"Article 109502"},"PeriodicalIF":5.9,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882846","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}

{"title":"Collaborative solutions for agricultural water pollution in smallholder economies: Farmers and local governments unite","authors":"Yong Sun ,&nbsp;Xiaomin Huang ,&nbsp;Buhailiqimu Paerhati ,&nbsp;Kan Zhou","doi":"10.1016/j.agwat.2025.109499","DOIUrl":"10.1016/j.agwat.2025.109499","url":null,"abstract":"<div><div>Agricultural water pollution has become a major source of surface water pollution, particularly in smallholder economies where limited resources, decentralized operations, and varying technological levels exacerbate the challenge. Existing research often overlooks the unique challenges confronted by these smallholder economies, particularly the intricate interactions between local governments and farmers, which are pivotal to the success of pollution control measures. This study addresses the complex issue of managing agricultural water pollution by exploring the synergistic role of farmers and local governments. Using dynamic evolutionary game theory, we developed a model to analyze their interactions, identifying four equilibrium points that demonstrate local asymptotic stability under specific conditions. Our findings reveal that enhanced environmental benefits, increased green preferences, and heightened social pressure directly incentivize farmers to adopt environmentally friendly behaviors. Conversely, high participation costs and the expectation of high economic gains from non-participation can deter farmers from reducing pollution. Government efforts in publicity, regulatory intensity, penalties, and subsidies significantly influence farmers' behaviors and the evolution of the game system. This study provides important insights for optimizing control strategies and promoting the harmonious coexistence of smallholder economies and environmental protection, offering a novel framework for addressing the challenges of agricultural water pollution management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109499"},"PeriodicalIF":5.9,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876505","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}

{"title":"Evaluation of the LI-710 evapotranspiration sensor in comparison to full eddy covariance for monitoring energy fluxes in perennial and annual crops","authors":"Srinivasa Rao Peddinti ,&nbsp;Isaya Kisekka","doi":"10.1016/j.agwat.2025.109501","DOIUrl":"10.1016/j.agwat.2025.109501","url":null,"abstract":"<div><div>Reliable and low-cost sensors for measuring evapotranspiration (ET) and associated energy fluxes are crucial for hydrologic monitoring and water management; however, conventional methods such as eddy covariance (EC) can be prohibitively expensive and complex. This study evaluates the performance of the LI-710 sensor across perennial (citrus, almond, pistachio) and annual crops (processing tomatoes) by comparing daily ET, sensible heat flux (H), and latent heat flux (LE) measurements with those from full EC systems under California’s Central Valley climatic conditions. Measurements from the LI-710 were corrected for unclosed energy balance using an energy-balance-residual (EBR) method that incorporates independent net radiation and soil heat flux data. Uncorrected LI-710 fluxes exhibited a consistent underestimation, as reflected in low or negative Nash–Sutcliffe efficiency (NSE) values. For ET, processing tomato NSE increased from 0.35 to 0.94 with EBR correction, citrus from 0.32 to 0.73, almond from −2.09 to 0.79, and pistachio from 0.72 to 0.95. H improved similarly (processing tomato: 0.86–0.97; citrus: 0.13–0.67; almond: −0.35 to 0.75; pistachio: 0.20–0.85), while LE accuracy rose from 0.44 to 0.95 in processing tomatoes, −0.10 to 0.77 in citrus, −1.51 to 0.76 in almonds, and 0.71–0.93 in pistachios. Corresponding reductions in root mean square error (RMSE) confirmed that EBR-corrected LI-710 measurements closely aligned with EC observations, effectively capturing seasonal peaks and phenological transitions. These results highlight the LI-710 sensor’s potential as a lower-cost, user-friendly alternative to full EC systems for routine flux monitoring, provided that energy-balance adjustments are implemented. Such an approach can support precision irrigation and sustainable water management, particularly in regions facing increasing pressures on freshwater resources.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109501"},"PeriodicalIF":5.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874546","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}

{"title":"Adaptation strategies for deficit irrigation management under extreme climate conditions","authors":"Kelechi Igwe,&nbsp;Ikenna Onyekwelu,&nbsp;Vaishali Sharda","doi":"10.1016/j.agwat.2025.109506","DOIUrl":"10.1016/j.agwat.2025.109506","url":null,"abstract":"<div><div>Crop production in arid and semi-arid regions faces increasing threats from severe weather conditions during the growing season. Irrigation, while critical for mitigating the negative impacts of these conditions, requires data-driven scheduling approaches to optimize productivity and curb excessive withdrawal of limited groundwater resources. This study utilizes the Decision Support System for Agrotechnology Transfer (DSSAT) - Crop Environment Resource Synthesis (CERES) Maize model to evaluate maize yield, water savings, and irrigation water productivity under two irrigation scheduling methods: a conventional soil-moisture-based method and a crop evapotranspiration-based (ET_c-based) method in Finney County, Southwestern Kansas, United States. Heat and water stress scenarios were induced by increasing the growing season maximum temperatures by 1 °C, 2 °C, and 4 °C, and extending the duration of dry periods by one day during critical growth stages. Twelve ET_c-based treatments, comprising of varying ET_c requirement thresholds needed to trigger irrigation (15 mm, 20 mm, 25 mm, and 30 mm), and ET_c replacement levels (50 %, 75 %, and 100 %), were simulated over 30 years (1991–2020). The ET_c-based treatments were compared to a soil moisture-based strategy which automatically applied a fixed irrigation amount whenever the plant available water in the soil dropped to 50 %. Results indicate that applying 75 % of the required ET_c at a 30 mm threshold is the most effective strategy. This approach limited yield losses to 10 %, enhanced water savings by 25 %, and irrigation water productivity by 12 % (mean growing season ET_c = 736 mm) when compared to the conventional soil-moisture-based method (mean-growing season ET_c = 838 mm) under normal and extreme weather conditions. These findings highlight the potential of ET_c-based irrigation to conserve water resources, ensuring more sustainable, climate-resilient agriculture.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109506"},"PeriodicalIF":5.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876506","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}

{"title":"Water and heat resource utilization influence cotton yield through sowing date optimization under varied climate","authors":"Hamad Khan ,&nbsp;Nangial Khan ,&nbsp;Zeeshan Khan ,&nbsp;Han Yingchun ,&nbsp;Yang Beifang ,&nbsp;Lei Yaping ,&nbsp;Zhi Xiaoyu ,&nbsp;Xiong Shiwu ,&nbsp;Shang Shilong ,&nbsp;Ma Yunzhen ,&nbsp;Jiao Yahui ,&nbsp;Lin Tao ,&nbsp;Yabing Li","doi":"10.1016/j.agwat.2025.109491","DOIUrl":"10.1016/j.agwat.2025.109491","url":null,"abstract":"<div><div>Drought threatens to destroy almost 70 % of the world's cotton supply. Optimizing sowing dates is an agricultural strategy that may help synchronize ecology and productivity. Field data on the coupling impact of various environmental resources on cotton and its response to climate change under sowing date control is still lacking, though. This study examined how resource use efficiencies like water use efficiency (WUE), water consumption, water productivity and heat production efficiency (PEsoil) changed during six sowing dates (S1-S6) over two years (2023 and 2024), characterized by distinct temperature and rainfall. Results revealed that in 2023, optimal climatic conditions and well-timed rainfall events led to a maximum seed cotton yield under S4 (+178 % increase), whereas late sowing (S6) led to a −10 % decrease compared to S1. However, in 2024, delayed sowing had a more adverse impact, with yield declined up to −39 %, likely due to irregular rainfall and suboptimal temperature distribution during critical reproductive stages. The highest water use amounted to the flowering and boll development stages, exceeding 700 mm in late sowing treatments. However, WUE and WPc in delayed sowing were substantially lower than in early sowing, indicating inefficient resource conversion. Furthermore, statistical analysis of year-to-year specific positive correlations with resource use metrics were found to be significant with seed cotton yield. In 2023, WUE (R² = 0.8350), WPc (R² = 0.7189), and PEsoil (R² = 0.8586) were correlated (strongly) with early sowing dates (S1 and S2) due to optimal timing of growth stages with respect to temperature and rainfall regimes. Though the overall R² values were slightly reduced with changed rainfall pattern and cooler peak temperatures, early sowing still had a positive correlation with WUE (R² = 0.81), WPc (R² = 0.69), and PEsoil (R² = 0.78) during 2024, implying stable performance under variable climatic conditions. Similarly, these early sowing treatments also had more stable aboveground biomass, had higher LAI and demonstrated the ability to synchronize phenological state with hydrothermal availability. Principal component analysis (PCA) also confirmed that early sowing increased resource use coupling and yield resilience under the two climatic years. This study introduces a novel integration of temporal sowing optimization, multi-sensor environmental monitoring, and resource coupling analysis. Future studies should focus on integrating climate forecasting models with sowing date recommendations to enable dynamic, site-specific cotton management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109491"},"PeriodicalIF":5.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874545","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}

{"title":"Coordination of abscisic acid and hydraulic signals in stomatal closure and yield of soybean genotypes with varying isohydry under different water conditions","authors":"Sanwei Yang ,&nbsp;Haixia Zhang ,&nbsp;Yi Jin ,&nbsp;Neil C. Turner ,&nbsp;Jiayin Pang ,&nbsp;Yinglong Chen ,&nbsp;Jin He","doi":"10.1016/j.agwat.2025.109495","DOIUrl":"10.1016/j.agwat.2025.109495","url":null,"abstract":"<div><div>Understanding soybean responses to drought stress is critical for breeding drought-tolerant varieties. The extent of stomatal regulation of leaf water potential during drought stress can be characterized by the degree of isohydry. We hypothesize that abscisic acid (ABA) and hydraulic signals, two key factors influencing stomatal regulation, coordinate differently to regulate stomatal closure and impact yield performance under varying drought intensities in soybeans with different isohydric behaviors. To test this, we selected four landraces and four modern cultivars exhibiting diverse isohydric behaviors and conducted a progressive drought experiment. The experiment measured stomatal conductance, photosynthetic rate (P_n), and leaf hydraulic conductance (K_leaf) as soil moisture progressively declined. Additionally, a water control experiment assessed foliar ABA content, osmotic adjustment (OA), and yield components under moderate (50 % pot capacity) and severe stress (30 % pot capacity) drought stress were compared relative to well-watered conditions. Results showed that modern cultivars, characterized by more isohydric behavior, produced higher ABA levels, triggering earlier stomatal closure at higher soil water content, which was subsequently modulated by hydraulic signals during prolonged drought. Isohydric genotypes also displayed enhanced OA, enabling them to maintain high P_n under severe drought stress. Under moderate drought stress, the isohydric cultivars experienced greater yield lose (21 % and 25 % for two isohydric cultivars vs. −8 % and 1 % for two landraces) and increased less water use efficiency for grain (WUEg). However, under severe drought stress, isohydric genotypes suffered less yield reduction (70 % and 72 % for isohydric cultivars vs. 79 % and 77 % for two anisohydric landraces) and increased more WUEg compared to anisohydric genotypes. Overall, isohydric genotypes, which exhibit a more conservative water-use strategy, are better suited for regions prone to severe drought stress. In contrast, anisohydric genotypes may perform better in regions with more reliable water availability.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109495"},"PeriodicalIF":5.9,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868853","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}

{"title":"Accounting for biomass water equivalent variations in soil moisture retrievals from cosmic ray neutron sensor","authors":"Samer K. Al-Mashharawi ,&nbsp;Susan C. Steele-Dunne ,&nbsp;Marcel M. El Hajj ,&nbsp;Martin Schrön ,&nbsp;Claude Doussan ,&nbsp;Dominique Courault ,&nbsp;Trenton E. Franz ,&nbsp;Matthew F. McCabe","doi":"10.1016/j.agwat.2025.109493","DOIUrl":"10.1016/j.agwat.2025.109493","url":null,"abstract":"<div><div>Cosmic ray neutron sensor (CRNS) has gained popularity in the last decade for its suitability in estimating area-averaged soil moisture (SM). The presence of fresh biomass influences the CRNS signal due to its water content, introducing bias to soil moisture estimation. Calibration and correction methods have been developed to account for this bias, but they usually require laborious sampling. Here, a novel approach is tested to assess the impact of biomass water equivalent (BWE) on CRNS soil moisture estimation. It was conducted in two contrasting environments from 15/11/21–1/02/23 for an olive orchard in Saudi Arabia, and from 15/02/22–30/03/23 for a cherry orchard in France. Water-uptake rates were monitored using sap flow sensors, as well as actual evapotranspiration (AET) and in-situ SM within the CRNS footprint. Concurrent environmental variables were also measured with a research-grade weather stations. It was found that when vapor pressure deficit (VPD) &gt; 1.8kPa, CRNS-derived SM (CRNS-SM) closely matched in-situ SM measurements, which indicates minimal influence from BWE. Conversely, when VPD is lower than 1.8kPa, CRNS-SM overestimates the in-situ moisture. An optimization approach was used to find a temporally-varying value of N₀ parameter that minimizes the difference between soil moisture estimated with CRNS and in-situ sensors. Furthermore, the results showed that the relative change in the optimized value of N₀ (N_0,opt) was well correlated with VPD in both orchards (R² = 0.66 for olive and R² = 0.74 for cherry orchards), indicating a strong correlation between these variables. These findings suggest that integrating VPD and CRNS observations, and using the VPD-N_0,opt correlation approach could be a promising way to account for the bias due to biomass dynamics on the estimation of area-averaged SM.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"313 ","pages":"Article 109493"},"PeriodicalIF":5.9,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868852","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}