Agricultural Water Management最新文献

{"title":"Productivity of water and heat resources and cotton yield response to cropping pattern and planting density in cotton fields in arid area","authors":"Zhenlin Dong, Sumei Wan, Yunzhen Ma, Jinbin Wang, Lu Feng, Yunlong Zhai, Tiantian Li, Zhengjun Cui, Jian Wang, Beifang Yang, Ze Yang, Zhan Zhao, Fei Yan, Shiwu Xiong, Yabing Li, Guodong Chen","doi":"10.1016/j.agwat.2024.109197","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109197","url":null,"abstract":"The individual effects of cropping patterns and planting densities on cotton yield formation and resource utilization have been extensively studied in the arid regions of western China, but research on their combined impacts remains limited. This study hypothesized that optimizing cropping patterns and planting densities would enhance hydrothermal resource productivity and cotton yield in the region. To test this, a two-year field experiment (2022–2023) employed a split-plot design with two main planting patterns (four rows per film and six rows per film) and three planting densities (low, medium, and high) as subplots. Using internet of sensor technology, soil temperature and moisture were monitored to assess their spatial and temporal distributions. The effects of planting pattern, density, and their interactions on cotton yield, yield components, biomass accumulation, and water and heat utilization were evaluated. The interaction between pattern and density significantly influenced cotton yield, harvest index, and water productivity, with planting density exerting a stronger effect on water productivity than planting pattern. In 2023, the four-row pattern at low and medium densities produced higher yields than the high-density treatment. Over the two-year period, the four-row, low-density treatment achieved 8.77 % and 13.40 % greater water productivity than the medium- and high-density treatments, respectively, while the six-row, medium-density treatment outperformed low and high densities, increasing water productivity by 3.64 % and 8.74 %. Seed cotton yield was also higher, with a 2.88 % and 6.15 % increase in the four-row, low-density treatment and an 8.51 % and 4.79 % increase in the six-row, medium-density treatment compared to higher-density treatments. The study further analyzed spatial and temporal variations in soil moisture and temperature and their link to resource productivity and cotton yield. Soil water content differences ranged from 0.10 to 0.90 mm in the four-row pattern and from 0.20 to 0.70 mm in the six-row pattern between low- and high-density treatments. Planting density significantly affected soil temperature during flowering and boll-setting stages. Lint and seed cotton yields showed positive correlations with soil heat production efficiency (PE<ce:inf loc=\"post\">soil</ce:inf>) and negative correlations with water production efficiency (WP<ce:inf loc=\"post\">c</ce:inf>), with optimal patterns observed in the four-row, low-density and six-row, medium-density treatments. These findings explain why these configurations led to a higher harvest index and enhanced hydrothermal resource productivity. This study provides valuable insights into the optimal configurations for maximizing cotton yield and resource efficiency in arid regions, supporting sustainable cotton production under resource-limited conditions.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"81 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805359","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":"Enhancing cotton irrigation with distributional actor–critic reinforcement learning","authors":"Yi Chen, Meiwei Lin, Zhuo Yu, Weihong Sun, Weiguo Fu, Liang He","doi":"10.1016/j.agwat.2024.109194","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109194","url":null,"abstract":"Accurate predictions of irrigation’s impact on crop yield are crucial for effective decision-making. However, current research predominantly focuses on the relationship between irrigation events and soil moisture, often neglecting the physiological state of the crops themselves. This study introduces a novel intelligent irrigation approach based on distributional reinforcement learning, ensuring that the algorithm simultaneously considers weather, soil, and crop conditions to make optimal irrigation decisions for long-term benefits. To achieve this, we collected climate data from 1980 to 2024 and conducted a two-year cotton planting experiment in 2023 and 2024. We used soil and plant state indicators from 5 experimental groups with varying irrigation treatments to calibrate and validate the DSSAT model. Subsequently, we innovatively integrated a distributional reinforcement learning method—an effective machine learning technique for continuous control problems. Our algorithm focuses on 17 indicators, including crop leaf area, stem leaf count, and soil evapotranspiration, among others. Through a well-designed network structure and cumulative rewards, our approach effectively captures the relationships between irrigation events and these states. Additionally, we validated the robustness and generalizability of the model using three years of extreme weather data and two consecutive years of cross-site observations. This method surpasses previous irrigation strategies managed by standard reinforcement learning techniques (e.g., DQN). Empirical results indicate that our approach significantly outperforms traditional agronomic decision-making, enhancing cotton yield by 13.6% and improving water use efficiency per kilogram of crop by 6.7%. In 2024, our method was validated in actual field experiments, achieving the highest yield among all approaches, with a 12.9% increase compared to traditional practices. Our research provides a robust framework for intelligent cotton irrigation in the region and offers promising new directions for implementing smart agricultural decision systems across diverse areas.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"24 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805361","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–saving irrigation combined with N–loaded clinoptilolite enhances nutrient yield, and water productivity by improving rice root characteristics: A combined PCA–SEM analysis","authors":"Yang Sun, Qi Wu, Daocai Chi, Hongyang Chen, Suyun Zhu, Qingliang Liu","doi":"10.1016/j.agwat.2024.109203","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109203","url":null,"abstract":"Nitrogen (N) –loaded clinoptilolite is renowned for its high–water retention and nutrient supplementation properties, which benefit crop growth. However, its combined effects with water–saving irrigation regime on N mineralization, root system characteristics, and nutrient yield, particularly their regulatory pathways, remain underexplored. This two–year split–plot experiment evaluated the impact of two irrigation regimes (I<ce:inf loc=\"post\">CF</ce:inf>: continuous flooding irrigation; I<ce:inf loc=\"post\">AWD</ce:inf>: alternate wet–dry irrigation) and two rates of N–loaded clinoptilolite (NZ<ce:inf loc=\"post\">0</ce:inf>: no N–loaded clinoptilolite; NZ<ce:inf loc=\"post\">10</ce:inf>: 10 t·ha<ce:sup loc=\"post\">–1</ce:sup>) on root characteristics, mineralized N, nutrient yield, and water productivity. We employed principal component analysis (PCA) and structural equation modeling (SEM) to analyze the interactions among the factors. The I<ce:inf loc=\"post\">AWD</ce:inf>NZ<ce:inf loc=\"post\">10</ce:inf> treatment showed the greatest water–saving potential, increasing the irrigated area by 0.29–fold compared to I<ce:inf loc=\"post\">CF</ce:inf>NZ<ce:inf loc=\"post\">0</ce:inf>. N–loaded clinoptilolite under I<ce:inf loc=\"post\">AWD</ce:inf> increased root surface area by 12.6 %, average root diameter by 14.2 %, and root volume by 13.8 %. Additionally, I<ce:inf loc=\"post\">AWD</ce:inf> increased mineralized N by 22.4 %, while N–loaded clinoptilolite further boosted it by 34.7 %. Root characteristics (r = 0.78) were crucial mediators in the effect of N–loaded clinoptilolite on protein (r = 0.64) and amylose nutritional yield (r = 0.68). Water usage influenced protein (r = -0.93) and amylose nutritional water productivity (r =-0.67) indirectly via chalky rice rate (r =0.90). In summary, integrating N–loaded clinoptilolite with the I<ce:inf loc=\"post\">AWD</ce:inf> regime not only enhanced rice root characteristics and mineralized N but also led to substantial increases in nutrient yield and water productivity. These findings underscore the potential for N–loaded clinoptilolite to be adopted as a key component in sustainable agricultural practices, offering a pathway to optimize resource use, reduce environmental impact, and improve crop productivity in water–limited regions.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"230 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805363","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":"Remote sensing estimation of winter wheat residue cover with dry and wet soil background","authors":"Yuwei Yao, Hongrui Ren, Yujie Liu","doi":"10.1016/j.agwat.2024.109227","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109227","url":null,"abstract":"Estimation of crop residue cover is important for energy balance in agroecosystem and sustainable development of agriculture. We evaluated the dimidiate pixel model, widely used for estimating photosynthetic vegetation cover, for non-photosynthetic vegetation (such as winter wheat residue) cover estimation. In this study, based on spectral and cover data of winter wheat residue in dry and wet soil backgrounds, the spectral curves of winter wheat residue and soil were identified, the applicability of non-photosynthetic vegetation indices in dimidiate pixel model was analyzed, and the potential of dimidiate pixel model to estimate winter wheat residue cover was explored. In dry soil background, a lignocellulose absorption trough near 2100 nm in the spectral curve of residue-soil mixed scene was observed, and the absorption trough became deeper with increasing residue cover. The normalized difference tillage index (NDTI) had the best correlation with the measured cover of winter wheat residue, and the dimidiate pixel model constructed on the basis of this index was able to accurately estimate the winter wheat residue cover (R<ce:sup loc=\"post\">2</ce:sup>=0.64, RMSE=0.16, RE=26.32 %). In wet soil background, the ability of non-photosynthetic vegetation index to distinguish between winter wheat residue and soil was reduced by soil moisture. The results of this study provide effective insights into the estimation of winter wheat residue cover under different soil moisture conditions, and provide a useful reference for the study of remote sensing estimation of crop residue cover in a large region. The dimidiate pixel model using NDTI can also be used to estimate non-photosynthetic vegetation cover of natural vegetation.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"9 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805360","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":"Micro-nano bubble water subsurface drip irrigation affects strawberry yield and quality by modulation of microbial communities","authors":"Zhen Zheng, Yuming He, Yingli He, Jing Zhan, Chunyan Shi, Yujie Xu, Xiaowen Wang, Jian Wang, Chao Zhang","doi":"10.1016/j.agwat.2024.109228","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109228","url":null,"abstract":"Aerated irrigation can enhance soil conditions such as soil oxygen, soil temperature, and soil moisture content and alter the structure of soil microbial communities. However, there is a dearth of research on the specific mechanisms and their mutual influence. Rhizosphere soil microbes are sensitive to changes in the soil environment, and the delivery of air or oxygenated water to rhizosphere soil significantly impacts the structure of the soil microbial community. In this study, a greenhouse strawberry subsurface drip irrigation experiment with micro-nano bubble water (MNBW) was conducted, with seven different aeration treatments and one control treatment (CK). The results showed that compared to CK, the aeration treatments improved the soil conditions to varying degrees and changed the structure of the strawberry rhizosphere soil microbial community. Furthermore, the yield, vitamin C, soil oxygen content, soil temperature and soil moisture increased by an average of 108 %, 3 %, 12 %, 10 % and 4 %, respectively. The results indicated that MNBW irrigation increased the abundance of specific bacterial communities, thereby affecting strawberry yield and quality. Correlation analysis results revealed the specific mechanisms of mutual influence between soil environment and soil microbes. Therefore, A<ce:inf loc=\"post\">FE</ce:inf> (aeration during the fruit expansion stage) and A<ce:inf loc=\"post\">B+F</ce:inf> (aeration during both the budding stage and flowering stage) can significantly activate the microbes in the strawberry rhizosphere soil and are considered the optimal times for enhancing strawberry yield and quality through MNBW irrigation.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"74 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805364","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":"Lifecycle environmental benefits of integrated rational fertilization, biochar, and constructed wetland in mitigating nutrient loading","authors":"Yu-Ning Chen, Chihhao Fan, Michal Šereš, Markéta Šerešová, Jan Vymazal, Shu-Yuan Pan","doi":"10.1016/j.agwat.2024.109202","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109202","url":null,"abstract":"Agricultural activities due to fertilization contribute significantly to nutrient loadings and other environmental burdens, posing a severe threat to ecosystems. Although a portfolio of green agricultural practices is recommended, few studies address the environmental benefits from a life-cycle perspective. This study comprehensively evaluates the cradle-to-gate environmental benefits of integrating rational fertilization, biochar, and constructed wetlands (CWs) exemplified by plum cultivation. Four assessment scenarios were designed: (S1) conventional cultivation, (S2) rational fertilization with biochar amendment, (S3) conventional cultivation with a simulated CWs system, and (S4) rational fertilization with biochar amendment and a simulated CWs system. In the assessment, rational fertilization used half the fertilizer compared to conventional practices, biochar was applied at 0.1 ton/ha, and horizontal subsurface flow CWs were filled with washed gravel and planted with <ce:italic>Phragmites australis</ce:italic>. The findings show that rational fertilization combined with biochar (S2) or CWs (S3) alone show about half the eutrophication impacts of conventional cultivation (S1). Combining rational fertilization, biochar and CWs (S4) further reduces freshwater and marine eutrophication potentials by ∼73.5 % and ∼69.8 %, respectively. Similarly, these green agricultural practices (either S2 or S4) effectively reduce the overall endpoint impacts by about 47 %, with synergistic improvements, particularly in endpoint freshwater ecotoxicity and freshwater eutrophication, observed for S4 (a significant reduction of 76 %) compared to S1. Regarding the carbon footprint, the production of plums using conventional agriculture emits ∼300 kg CO<ce:inf loc=\"post\">2</ce:inf>-eq per ton-plum, whereas using green agricultural practices results in only ∼138 kg CO<ce:inf loc=\"post\">2</ce:inf>-eq per ton-plum, representing a reduction of 45.8 % in greenhouse gas emissions. This study highlights the potential of green agricultural practices to mitigate NPS nutrient loadings to aquifers and achieve sustainable agricultural management through reduced global warming and other environmental impacts.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"19 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805398","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":"The hydraulic performance and clogging characteristics of a subsurface drip irrigation system operating for five years in the North China plain","authors":"Li Zaiyu, Mo Yan, Gao Hao, Gong Shihong, Zhang Yanqun, Li Guangyong, Wu Feng","doi":"10.1016/j.agwat.2024.109217","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109217","url":null,"abstract":"Emitter clogging is one of the most significant obstacles to the widespread adoption of subsurface drip irrigation (SDI). This research focused on a five-year-old corn SDI system operating in the North China Plain, where the flow rates and internal clogging material content of 3384 non-pressure compensation emitters (accounting for 51.2 % of the total number of emitters) were measured through excavation. This research explored the response patterns of the emitter relative discharge (&lt;ce:italic&gt;Dra&lt;/ce:italic&gt;), Christiansen uniformity coefficient (&lt;ce:italic&gt;Cu&lt;/ce:italic&gt;), flow index (&lt;ce:italic&gt;x&lt;/ce:italic&gt;), and clogging substance content in various parts of the emitters to different levels of irrigation, nitrogen application, and aeration. The results revealed that &lt;ce:italic&gt;Dra&lt;/ce:italic&gt; and &lt;ce:italic&gt;Cu&lt;/ce:italic&gt; significantly decreased (p &lt; 0.05) with increasing nitrogen application, whereas the changes in irrigation and aeration were not statistically significant. The average &lt;ce:italic&gt;Dra&lt;/ce:italic&gt; and &lt;ce:italic&gt;Cu&lt;/ce:italic&gt; for the entire system were 88.3 % and 91.2 %, respectively, indicating good uniformity of the water distribution in the SDI system. The average &lt;ce:italic&gt;x&lt;/ce:italic&gt; of the emitters increased from 0.47 before installation to 0.53, suggesting a transition from turbulent flow to a partially turbulent flow state, which increased the risk of emitter clogging. Both &lt;ce:italic&gt;Dra&lt;/ce:italic&gt; and &lt;ce:italic&gt;Cu&lt;/ce:italic&gt; decreased linearly with increasing &lt;ce:italic&gt;x&lt;/ce:italic&gt; (R&lt;ce:sup loc=\"post\"&gt;2&lt;/ce:sup&gt;=0.64–0.78). The proportions of clogging substances in the emitter flow channels (&lt;ce:italic&gt;m&lt;/ce:italic&gt;&lt;ce:inf loc=\"post\"&gt;&lt;ce:italic&gt;c&lt;/ce:italic&gt;&lt;/ce:inf&gt;), outlet (&lt;ce:italic&gt;m&lt;/ce:italic&gt;&lt;ce:inf loc=\"post\"&gt;&lt;ce:italic&gt;o&lt;/ce:italic&gt;&lt;/ce:inf&gt;), and intrusion root (&lt;ce:italic&gt;m&lt;/ce:italic&gt;&lt;ce:inf loc=\"post\"&gt;&lt;ce:italic&gt;r&lt;/ce:italic&gt;&lt;/ce:inf&gt;) dry weight were 28.9 %, 69.3 %, and 1.8 % of the total clogging substance dry weight (&lt;ce:italic&gt;M&lt;/ce:italic&gt;), respectively. The particle size distributions of the clogging substances at the outlets were similar to those of the surrounding soil, which was caused mainly by negative pressure suction. Root intrusions were mostly concentrated at the outlets, with a small portion entering the flow channels, accounting for 4.3–20.1 % of the total flow channel length. Owing to the well-designed pressure regulation and air exhaust system used in this SDI research, along with higher soil moisture in the crop root zone, the negative linear relationship between &lt;ce:italic&gt;Dra&lt;/ce:italic&gt; and &lt;ce:italic&gt;mc&lt;/ce:italic&gt; was most significant (p &lt; 0.01). Based on time projection, this SDI system could operate normally for 8–11 years (&lt;ce:italic&gt;Dra&lt;/ce:italic&gt;, &lt;ce:italic&gt;Cu&lt;/ce:italic&gt; ≥ 80 %). To achieve a life of more than 20 years, additional acid/chlorine treatments, which supplement the existing system components and the current practice of flushing twice annual","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"9 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805367","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":"Long-term Cd remediation mechanisms and potential risks in soil with biochar application under dry-wet cycling at different soil moisture levels","authors":"Shuang Huang, Zhuowen Meng, Jingwei Wu, Lei Xin, Qin Zhao","doi":"10.1016/j.agwat.2024.109212","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109212","url":null,"abstract":"Dry-wet cycling and soil moisture are key factors affecting cadmium (Cd) remediation in soils by biochar; however, their long-term effects on the transport of Cd between soil and biochar, Cd fraction distribution, and Cd potential risks are still unclear. To reveal the long-term Cd remediation mechanisms and potential risks in soil under biochar treatment, 180 days of artificial dry-wet cycling was conducted at four soil moisture levels (40 % θ<ce:inf loc=\"post\">s</ce:inf>, 60 % θ<ce:inf loc=\"post\">s</ce:inf>, 80 % θ<ce:inf loc=\"post\">s</ce:inf>, and 100 % θ<ce:inf loc=\"post\">s</ce:inf>; θ<ce:inf loc=\"post\">s</ce:inf>, saturated water content, W/W) based on local meteorological data to simulate 30 years of natural dry-wet processes. The results showed that Cd adsorbed by biochar in soils during long-term ageing first underwent rapid adsorption (over 0–5 years of simulated ageing), then equilibrium stabilization (over 5–20 years of simulated ageing), and finally slight re-released (over 20–30 years of simulated ageing). Compared with the total Cd adsorbed by biochar in the 20th year of simulated ageing, Cd adsorption by biochar accounted for 85.28 %, 14.72 %, and −3.22 % during 0–5, 5–20, and 20–30 years of simulated ageing, respectively, in the soil at 100 % θ<ce:inf loc=\"post\">s</ce:inf>. Similarly, the available Cd slightly increased in 20–30 years of simulated ageing. The greater the soil moisture was, the more effective the adsorption and immobilization of Cd by biochar. At the 20th year of simulated ageing, the Cd adsorption by biochar at 100 % θ<ce:inf loc=\"post\">s</ce:inf> was 1.51 times that at 40 % θ<ce:inf loc=\"post\">s</ce:inf>; the available Cd in the soil with biochar at 100 % θ<ce:inf loc=\"post\">s</ce:inf> was 0.91 times that at 40 % θ<ce:inf loc=\"post\">s</ce:inf>. The contribution of nonmineral components in biochar to Cd adsorption was greater in 0–1 years of the simulation, but the contribution of mineral components dominated and slightly decreased during 1–30 years of the simulation. This study highlighted that biochar was fairly effective in the long-term remediation of Cd in contaminated soils, but there was some risk of Cd activation in the later stages due to the ageing of biochar. Agricultural irrigation management has a significant effect on the long-term effectiveness of biochar remediation of Cd pollution. To prevent Cd reactivation, a high field moisture level is recommended, and excessive dry-wet cycling should be avoided through water management practices such as frequent irrigation with small amounts of water.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"1 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805401","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":"Multimodal sequential cross-modal transformer for predicting plant available water capacity (PAWC) from time series of weather and crop biological data","authors":"Dung Nguyen, Peter de Voil, Andries Potgieter, Yash P. Dang, Thomas G. Orton, Duc Thanh Nguyen, Thanh Thi Nguyen, Scott C. Chapman","doi":"10.1016/j.agwat.2024.109124","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109124","url":null,"abstract":"Deep learning (DL) and machine learning (ML) have been applied widely to satellite data of vegetation indices to infer indirect features associated with soil characteristics that affect crop performance in rain-fed environments. In this paper, we propose a DL model for prediction of plant available water capacity (PAWC) of the soil from sequential multi-modal data including time series of biomass, leaf area index (LAI), normalised difference vegetation index (NDVI), and cumulative weather variables. By initiating large numbers of simulations with different soil PAWC, weather and management parameters, we explore combinations of the simulation outputs and the weather to estimate the PAWC and to determine the factors that impede the accuracy of the prediction model. Experimental results demonstrate the significant potential of our method compared with traditional ML methods. Specifically, our method increases the prediction accuracy in situations where each PAWC profile is grouped into two or five classes of PAWC. For more classes (10 classes), the model achieves more than 60% for the overall accuracy and performs well on the lowest five PAWC classes. The utilisation of sequential multi-modal data to predict soil water level provides a direction for future work to translate onto empirical datasets and also to explore the boundaries of the prediction ability of DL models.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"38 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805403","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":"Physiological changes induced by green fodder expansion into grasslands and croplands enhance water-use efficiency in the Northeastern Tibetan Plateau","authors":"Xu Wang, Jilin Yang, Jie Wang, Tong Yang, Chuchen Chang, Yanbo Zhao, Xiaocui Wu, Geli Zhang, Xiangming Xiao","doi":"10.1016/j.agwat.2024.109218","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109218","url":null,"abstract":"The rapid green fodder expansion in native grassland and cropland in the northeastern Tibetan Plateau (a rain-fed region), driven by the increasing forage demand, has altered vegetation patterns and potentially affected carbon and water cycles. To clarify the elusive effects of green fodder expansion on the carbon sequestration and water consumption in this region, we examined its impacts on productivity, evapotranspiration, and water-use efficiency using a pairwise comparison approach at seasonal and annual scales in 2019. We also conducted an attribution analysis to undercover the mechanisms through which green fodder expansion influences water-use efficiency. Our results revealed that during the growing season, gross primary productivity in green fodder lands was 12.25 % and 4.14 % higher than the adjacent grasslands and croplands, respectively. Evapotranspiration was 2.89 % and 3.33 % lower in comparison. Ecosystem-level water-use efficiency was respectively 15.14 % and 6.92 % higher, while plant-level water-use efficiency increased by 4.76 % and 1.5 %, respectively. Green fodder expansion enhanced ecosystem-level water-use efficiency by increasing gross primary productivity and reducing evapotranspiration, while improvements in plant-level water-use efficiency were mainly driven by gross primary productivity increases. The changes in plant physiology and canopy structure induced by green fodder cultivation enhanced the CO<ce:inf loc=\"post\">2</ce:inf> assimilation capacity, reduced soil evaporation, and allocated more water toward transpiration, emerging as the dominant factors driving the observed changes in gross primary productivity and evapotranspiration. However, we found that green fodder planting also led to increased soil evaporation over the non-growing season, which partially offset its positive effect on water-use efficiency during the growing season. This study suggests that green fodder cultivation could be a potential solution to increasing forage supply in the northeastern Tibetan Plateau, while highlighting the necessity of reducing soil evaporation during the non-growing season to maximize the benefits of green fodder expansion.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"2 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805400","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}