Agricultural water conservation is crucial for sustainable development, particularly in water-scarce regions. This study examines the factors that influence water conservation behaviors among wheat farmers, comparing those in water-deficient areas to those in water-endowed regions. Utilizing a non-experimental causal-comparative approach, data were collected through a structured questionnaire administered to a sample of 132 randomly selected farmers. The validated instrument demonstrated reliability, with Cronbach’s alpha coefficients ranging from 0.61 to 0.87. Results indicated significant differences in economic, socio-cultural, attitudinal, demographic, and farm-related factors between the two groups. Three distinct profiles emerged: “Conservation Novices,” “Balanced Practitioners,” and “Conservation Champions,” each displaying varying levels of engagement and attitudes toward water conservation. The significant influence of utilitarian beliefs and environmental awareness underscores the necessity for tailored interventions. For water-deficient farmers, targeted education, financial incentives, and peer-to-peer networks could significantly enhance conservation efforts. Conversely, water-endowed farmers can benefit from experience-based workshops and personalized advisory services. Insights from this study provide valuable guidance for policymakers and stakeholders aiming to improve water management strategies in similarly water-scarce agricultural regions worldwide, emphasizing the need for adaptive approaches that consider the diverse characteristics of farming communities.
{"title":"Sustainable water management in wheat farming: Insights from diverse water environments","authors":"Maryam Sharifzadeh, Sanaz Golabvand, Maryam Afereydouni","doi":"10.1016/j.agwat.2024.109161","DOIUrl":"10.1016/j.agwat.2024.109161","url":null,"abstract":"<div><div>Agricultural water conservation is crucial for sustainable development, particularly in water-scarce regions. This study examines the factors that influence water conservation behaviors among wheat farmers, comparing those in water-deficient areas to those in water-endowed regions. Utilizing a non-experimental causal-comparative approach, data were collected through a structured questionnaire administered to a sample of 132 randomly selected farmers. The validated instrument demonstrated reliability, with Cronbach’s alpha coefficients ranging from 0.61 to 0.87. Results indicated significant differences in economic, socio-cultural, attitudinal, demographic, and farm-related factors between the two groups. Three distinct profiles emerged: “Conservation Novices,” “Balanced Practitioners,” and “Conservation Champions,” each displaying varying levels of engagement and attitudes toward water conservation. The significant influence of utilitarian beliefs and environmental awareness underscores the necessity for tailored interventions. For water-deficient farmers, targeted education, financial incentives, and peer-to-peer networks could significantly enhance conservation efforts. Conversely, water-endowed farmers can benefit from experience-based workshops and personalized advisory services. Insights from this study provide valuable guidance for policymakers and stakeholders aiming to improve water management strategies in similarly water-scarce agricultural regions worldwide, emphasizing the need for adaptive approaches that consider the diverse characteristics of farming communities.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109161"},"PeriodicalIF":5.9,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662046","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}
Pub Date : 2024-11-13DOI: 10.1016/j.agwat.2024.109167
Fırat Arslan , Francisco Alcon , Sinan Kartal , Kubilay Erdoğan , Demetrio Antonio Zema
This study explores the patterns of sustainable use and management of competing water sectors in the Alanya Water Users Association (WUA) in Southern Türkiye, over eight years (2013–2020) before the SARS-CoV-19 pandemic, focusing on the impacts of the recorded huge growth of tourism. Performance indicators of collective irrigation services are used to identify performance patterns and trends over time. The analysis has revealed a notable increase in water consumption for agricultural activities (+30 %), driven by the cultivation of tropical fruits, without a proportional rise in crop production. Concurrently, effective financial management is observed in the WUA, with a consistent reduction in unit Management, Operation and Maintenance costs (-40–70 %). Additionally, the total water demand has surged (+100 %) due to population growth and tourist flux. However, this increase has tensioned water delivery to crops, indicating higher pressures over water availability for all uses. The study has identified three distinct patterns in the technical, financial, and socio-economic performance of the WUA, particularly highlighting the last four years of increased water usage and the disruption caused by the SARS-CoV-19 pandemic in 2020. Despite the current adequacy of water resources, optimized strategies for water management are advocated to address anticipated demographic growth, the introduction of tropical crops and the environmental impacts of climate change.
{"title":"Sustainability of collective irrigation under water competition between agriculture and civil uses: The case study of Alanya Water Users Association (Türkiye)","authors":"Fırat Arslan , Francisco Alcon , Sinan Kartal , Kubilay Erdoğan , Demetrio Antonio Zema","doi":"10.1016/j.agwat.2024.109167","DOIUrl":"10.1016/j.agwat.2024.109167","url":null,"abstract":"<div><div>This study explores the patterns of sustainable use and management of competing water sectors in the Alanya Water Users Association (WUA) in Southern Türkiye, over eight years (2013–2020) before the SARS-CoV-19 pandemic, focusing on the impacts of the recorded huge growth of tourism. Performance indicators of collective irrigation services are used to identify performance patterns and trends over time. The analysis has revealed a notable increase in water consumption for agricultural activities (+30 %), driven by the cultivation of tropical fruits, without a proportional rise in crop production. Concurrently, effective financial management is observed in the WUA, with a consistent reduction in unit Management, Operation and Maintenance costs (-40–70 %). Additionally, the total water demand has surged (+100 %) due to population growth and tourist flux. However, this increase has tensioned water delivery to crops, indicating higher pressures over water availability for all uses. The study has identified three distinct patterns in the technical, financial, and socio-economic performance of the WUA, particularly highlighting the last four years of increased water usage and the disruption caused by the SARS-CoV-19 pandemic in 2020. Despite the current adequacy of water resources, optimized strategies for water management are advocated to address anticipated demographic growth, the introduction of tropical crops and the environmental impacts of climate change.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109167"},"PeriodicalIF":5.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662045","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}
Pub Date : 2024-11-12DOI: 10.1016/j.agwat.2024.109150
Sana Zeeshan Shirazi , Buchun Liu , Yuan Liu , Rui Han , Yongchang Zhu , Oumeng Qiao , Honglei Che , Yiming Zhang , Xurong Mei
Global warming is projected to increase future droughts that will have a significant impact on maize cultivation in China. Therefore, we studied the changing climate patters and its impact during the maize growth period (MGP) using the downscaled outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585) for the future period in three timelines (2020–2039; 2040–2069; and 2070–2099) relative to the baseline period (1981–2014). The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated on monthly, 3-monthly, and 6-monthly timescales to monitor the short and long-term future drought conditions during the MGP in the north of China. Our results show an increase of mean temperature by 0.63–1.90 °C, 0.85–2.13 °C, and 1.21–2.42 °C under SSP245 and 1.42–2.76 °C, 1.84–3.07 °C, and 2.01–3.57 °C under SSP585 in 2030 s, 2060 s, and 2090 s across the region during MGP. The precipitation during MGP is projected to increase from 22.71–97.14 mm and 29.92–98.40 mm from 2030 s to 2090 s under SSP245 and SSP585, respectively, relative to the base period. Our results also indicate regional variations in drought occurrences, with Northwestern Arid Region (NWAR), Inner Mongolia Region (IMR), and Northeast China (NEC) experiencing differing degrees of drought intensity. The duration of mild droughts is projected to increase by 5.6 %–8.5 % (SSP245) and 5.7 %–9.2 % (SSP585) and moderate droughts are expected to rise by 3.8 %–8.8 % (SSP245) and 4.2 %–9.9 % (SSP585). In the NWAR, mild droughts are projected to increase by 24.3 %–30.5 % (SSP245) and 27.2 %–33.3 % (SSP585) and moderate droughts increasing by 13.1 %–25.6 % (SSP245) and 18.9 %–31.5 % (SSP585) from the 2030 s to the 2090 s, respectively. Future projections also suggest a significant increase in the severity of mild, moderate, and severe droughts across the study area, with northwestern regions exhibiting the highest increase. The results of this study provide region specific valuable insights for efficient utilization of water resources, adaptive irrigation strategies, and need for drought-resistant crop varieties in the north of China.
{"title":"Understanding climate variability and its impact on drought occurrences in maize producing regions: Evidence from north of China","authors":"Sana Zeeshan Shirazi , Buchun Liu , Yuan Liu , Rui Han , Yongchang Zhu , Oumeng Qiao , Honglei Che , Yiming Zhang , Xurong Mei","doi":"10.1016/j.agwat.2024.109150","DOIUrl":"10.1016/j.agwat.2024.109150","url":null,"abstract":"<div><div>Global warming is projected to increase future droughts that will have a significant impact on maize cultivation in China. Therefore, we studied the changing climate patters and its impact during the maize growth period (MGP) using the downscaled outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585) for the future period in three timelines (2020–2039; 2040–2069; and 2070–2099) relative to the baseline period (1981–2014). The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated on monthly, 3-monthly, and 6-monthly timescales to monitor the short and long-term future drought conditions during the MGP in the north of China. Our results show an increase of mean temperature by 0.63–1.90 °C, 0.85–2.13 °C, and 1.21–2.42 °C under SSP245 and 1.42–2.76 °C, 1.84–3.07 °C, and 2.01–3.57 °C under SSP585 in 2030 s, 2060 s, and 2090 s across the region during MGP. The precipitation during MGP is projected to increase from 22.71–97.14 mm and 29.92–98.40 mm from 2030 s to 2090 s under SSP245 and SSP585, respectively, relative to the base period. Our results also indicate regional variations in drought occurrences, with Northwestern Arid Region (NWAR), Inner Mongolia Region (IMR), and Northeast China (NEC) experiencing differing degrees of drought intensity. The duration of mild droughts is projected to increase by 5.6 %–8.5 % (SSP245) and 5.7 %–9.2 % (SSP585) and moderate droughts are expected to rise by 3.8 %–8.8 % (SSP245) and 4.2 %–9.9 % (SSP585). In the NWAR, mild droughts are projected to increase by 24.3 %–30.5 % (SSP245) and 27.2 %–33.3 % (SSP585) and moderate droughts increasing by 13.1 %–25.6 % (SSP245) and 18.9 %–31.5 % (SSP585) from the 2030 s to the 2090 s, respectively. Future projections also suggest a significant increase in the severity of mild, moderate, and severe droughts across the study area, with northwestern regions exhibiting the highest increase. The results of this study provide region specific valuable insights for efficient utilization of water resources, adaptive irrigation strategies, and need for drought-resistant crop varieties in the north of China.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109150"},"PeriodicalIF":5.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662043","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}
Pub Date : 2024-11-12DOI: 10.1016/j.agwat.2024.109158
Zhongrui Zhu , Jiusheng Li , Delan Zhu
To fully understand the sprinkler irrigation-crop-soil continuum, prevent sprinkler erosion, and ensure good development of sprinkler technology, it is essential to characterize the spatiotemporal variability of physical parameters and the splash erosion potential of sprinkler water droplets. The influences of maize canopy and sprinkler characteristics on the spatiotemporal distribution patterns of throughfall, droplet physical parameters, and splash erosion potential were investigated using a 2D-Video-Distrometer. The results showed that MC negatively affected throughfall generation. Irrigation characteristics could not fundamentally reverse the influence of MC on the sprinkler water distribution evenness. Compared to the early stages, the large throughfall at the later stages occurred near the stem base. MC reduced the KEV and SER of sprinkler water droplets. Dripping drops generated on maize leaves caused splash erosion. The SDP laws of KEV and SER of throughfall droplets were basically the same. Contrary to others, the DD of throughfall increased concomitant with the application of sprinkler droplets of 1.48 mm. MC positively influenced the CV of the DD of sprinkler water. Changes in the volume proportions of dripping drops and inadequately breaking droplets resulted in the SDP of the DD of throughfall. The percentages of the Veq of throughfall droplets at different growth stages were 86.81 %, 77.06 %, 55.08 %, and 51.48 %, respectively. Only treatments of 1.48 mm increased the Veq of throughfall droplets. MC and DD affected the distribution heterogeneity of the Veq of throughfall droplets. Differences in the Veqs of large droplets were responsible for the SDP of the velocities of throughfall droplets. Only treatments with small droplets significantly reduced the number of throughfall droplets. And the number of throughfall droplets characterized a SDP with greater values the farther from the stem, whereas others were opposite. The results will provide theoretical and applied implications for diversifying the sprinkler-crop-soil continuum and elucidate the involvement of sprinkler irrigation in the hydrogeochemical cycle of agricultural land.
{"title":"Exploring the effects of maize canopy on the spatiotemporal distribution heterogeneity of the determinants of sprinkler irrigation droplet splash erosivity","authors":"Zhongrui Zhu , Jiusheng Li , Delan Zhu","doi":"10.1016/j.agwat.2024.109158","DOIUrl":"10.1016/j.agwat.2024.109158","url":null,"abstract":"<div><div>To fully understand the sprinkler irrigation-crop-soil continuum, prevent sprinkler erosion, and ensure good development of sprinkler technology, it is essential to characterize the spatiotemporal variability of physical parameters and the splash erosion potential of sprinkler water droplets. The influences of maize canopy and sprinkler characteristics on the spatiotemporal distribution patterns of throughfall, droplet physical parameters, and splash erosion potential were investigated using a 2D-Video-Distrometer. The results showed that MC negatively affected throughfall generation. Irrigation characteristics could not fundamentally reverse the influence of MC on the sprinkler water distribution evenness. Compared to the early stages, the large throughfall at the later stages occurred near the stem base. MC reduced the KE<sub>V</sub> and SER of sprinkler water droplets. Dripping drops generated on maize leaves caused splash erosion. The SDP laws of KE<sub>V</sub> and SER of throughfall droplets were basically the same. Contrary to others, the DD of throughfall increased concomitant with the application of sprinkler droplets of 1.48 mm. MC positively influenced the CV of the DD of sprinkler water. Changes in the volume proportions of dripping drops and inadequately breaking droplets resulted in the SDP of the DD of throughfall. The percentages of the V<sub>eq</sub> of throughfall droplets at different growth stages were 86.81 %, 77.06 %, 55.08 %, and 51.48 %, respectively. Only treatments of 1.48 mm increased the V<sub>eq</sub> of throughfall droplets. MC and DD affected the distribution heterogeneity of the V<sub>eq</sub> of throughfall droplets. Differences in the V<sub>eq</sub>s of large droplets were responsible for the SDP of the velocities of throughfall droplets. Only treatments with small droplets significantly reduced the number of throughfall droplets. And the number of throughfall droplets characterized a SDP with greater values the farther from the stem, whereas others were opposite. The results will provide theoretical and applied implications for diversifying the sprinkler-crop-soil continuum and elucidate the involvement of sprinkler irrigation in the hydrogeochemical cycle of agricultural land.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109158"},"PeriodicalIF":5.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662042","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}
Pub Date : 2024-11-12DOI: 10.1016/j.agwat.2024.109149
Lijie Luo , He Xiaojuan , Yifeng Qin , Yaoze Liu , Yizhao Wu , Mingsheng Chen , Yiying Liao , Liang Zhang , Xudong Li
The removal of nitrogen from farmland drainage is challenging due to the typically low carbon-to-nitrogen (C/N) ratio. In this study, an algal-bacterial symbiosis system was developed to treat low C/N farmland drainage. The investigation focused on the nutrient removal rates, microbial growth characteristics, extracellular polymeric substances (EPS) content, and microbial community species composition under varied disturbance frequencies and light conditions (intensity and duration). Results demonstrated that the optimal operating conditions were three disturbances per 24 h, a light intensity of 20,000 lux, and a 16-hour lighting duration. Under these conditions, the average removal rates of soluble chemical oxygen demand, total nitrogen, total phosphorus, nitrate nitrogen, and ammonia nitrogen reached 45.1 %, 73.3 %, 98.1 %, 63.1 %, and 97.3 %, respectively. Compared to continuous disturbance, intermittent disturbance reduced energy consumption by over 90 % and promoted higher biomass accumulation, with an average dry weight of 508.7 mg L−1 and chlorophyll-a concentration of 521.0 μg L−1. Meanwhile, a robust microbial community and a balanced bacterial-to-algal gene copy ratio (exceeding 25:1) were critical for nutrient removal. The optimized system facilitated symbiote secretion of bound polysaccharides (45.2 μg L−1, double that of other reactors), promoting the formation of robust biofilms and enhancing nutrient removal. This work provides a technical reference for improving nutrient removal in low C/N wastewater treatment processes.
{"title":"Optimizing nutrient removal of algal-bacterial symbiosis system for treating low C/N farmland drainage","authors":"Lijie Luo , He Xiaojuan , Yifeng Qin , Yaoze Liu , Yizhao Wu , Mingsheng Chen , Yiying Liao , Liang Zhang , Xudong Li","doi":"10.1016/j.agwat.2024.109149","DOIUrl":"10.1016/j.agwat.2024.109149","url":null,"abstract":"<div><div>The removal of nitrogen from farmland drainage is challenging due to the typically low carbon-to-nitrogen (C/N) ratio. In this study, an algal-bacterial symbiosis system was developed to treat low C/N farmland drainage. The investigation focused on the nutrient removal rates, microbial growth characteristics, extracellular polymeric substances (EPS) content, and microbial community species composition under varied disturbance frequencies and light conditions (intensity and duration). Results demonstrated that the optimal operating conditions were three disturbances per 24 h, a light intensity of 20,000 lux, and a 16-hour lighting duration. Under these conditions, the average removal rates of soluble chemical oxygen demand, total nitrogen, total phosphorus, nitrate nitrogen, and ammonia nitrogen reached 45.1 %, 73.3 %, 98.1 %, 63.1 %, and 97.3 %, respectively. Compared to continuous disturbance, intermittent disturbance reduced energy consumption by over 90 % and promoted higher biomass accumulation, with an average dry weight of 508.7 mg L<sup>−1</sup> and chlorophyll-a concentration of 521.0 μg L<sup>−1</sup>. Meanwhile, a robust microbial community and a balanced bacterial-to-algal gene copy ratio (exceeding 25:1) were critical for nutrient removal. The optimized system facilitated symbiote secretion of bound polysaccharides (45.2 μg L<sup>−1</sup>, double that of other reactors), promoting the formation of robust biofilms and enhancing nutrient removal. This work provides a technical reference for improving nutrient removal in low C/N wastewater treatment processes.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109149"},"PeriodicalIF":5.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662044","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}
Agricultural non-point source (ANPS) pollution increasingly threatens China’s aquatic ecosystems. Intercropping grain crops (GC) and cash crops (CC) increases landscape fragmentation, making pollution control harder. As producers of ANPS pollution and beneficiaries of its governance, farmers’ participation is crucial for improving water environments. However, the impact of social networks, closely related to farmers’ economic behavior in rural China, on different cropping types of farmers’ ANPS pollution governance behavior remains unclear. Based on survey data from 305 farmers in a typical village in the Lijiang River Basin, social networks of GC and CC farmers were constructed. By introducing network embedding theory, we examined how social networks influence governance resource allocation and collective action among farmers. Combining social network theory with technology acceptance model (TAM), an extended TAM was proposed to discuss the influence of farmers’ social network structural position (SNSP) on their willingness to participate in governance (WP), considering the role of cognition. Results showed that GC farmers’ social network have small-world characteristics (Small-world quotient=2.153) with a network density of only 0.016, lacking bridging ties and showing low trust among actors. CC farmers’ network had a density of 0.029, a clearer core-periphery structure (Core-periphery index=0.267), key farmers showed stronger bridging capabilities with average betweenness centrality of 4.234 %. CC farmers’ networks had diverse ties and higher trust among actors. CC farmers’ network structure improved information diffusion and is more effective in acquiring resources and collaborative governance. Structural equation modeling showed that SNSP positively affect WP for GC and CC farmers, with path coefficients of 0.245 and 0.294. Mediating analysis showed that GC farmers’ perceived usefulness and CC farmers’ perceived ease of use had the largest mediating effects between SNSP and WP, at 20.9 % and 26.8 %, highlighting cognition’s different roles. Social networks variably impact governance behavior among different farmers, and strategies considering these differences can enhance governance efficiency.
{"title":"Social network shapes farmers’ non-point source pollution governance behavior – A case study in the Lijiang River Basin, China","authors":"Zhanbo Qin , Qinxue Xu , Changping Zhang , Lanlan Zuo , Lingling Chen , Rongjie Fang","doi":"10.1016/j.agwat.2024.109162","DOIUrl":"10.1016/j.agwat.2024.109162","url":null,"abstract":"<div><div>Agricultural non-point source (ANPS) pollution increasingly threatens China’s aquatic ecosystems. Intercropping grain crops (GC) and cash crops (CC) increases landscape fragmentation, making pollution control harder. As producers of ANPS pollution and beneficiaries of its governance, farmers’ participation is crucial for improving water environments. However, the impact of social networks, closely related to farmers’ economic behavior in rural China, on different cropping types of farmers’ ANPS pollution governance behavior remains unclear. Based on survey data from 305 farmers in a typical village in the Lijiang River Basin, social networks of GC and CC farmers were constructed. By introducing network embedding theory, we examined how social networks influence governance resource allocation and collective action among farmers. Combining social network theory with technology acceptance model (TAM), an extended TAM was proposed to discuss the influence of farmers’ social network structural position (SNSP) on their willingness to participate in governance (WP), considering the role of cognition. Results showed that GC farmers’ social network have small-world characteristics (Small-world quotient=2.153) with a network density of only 0.016, lacking bridging ties and showing low trust among actors. CC farmers’ network had a density of 0.029, a clearer core-periphery structure (Core-periphery index=0.267), key farmers showed stronger bridging capabilities with average betweenness centrality of 4.234 %. CC farmers’ networks had diverse ties and higher trust among actors. CC farmers’ network structure improved information diffusion and is more effective in acquiring resources and collaborative governance. Structural equation modeling showed that SNSP positively affect WP for GC and CC farmers, with path coefficients of 0.245 and 0.294. Mediating analysis showed that GC farmers’ perceived usefulness and CC farmers’ perceived ease of use had the largest mediating effects between SNSP and WP, at 20.9 % and 26.8 %, highlighting cognition’s different roles. Social networks variably impact governance behavior among different farmers, and strategies considering these differences can enhance governance efficiency.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109162"},"PeriodicalIF":5.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661737","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}
Pub Date : 2024-11-09DOI: 10.1016/j.agwat.2024.109152
Ziwu Guo , Qin Li , Jing Wu , Liting Yang , Lili Fan , Le Zhang , Minghui Qin , Shuanglin Chen
Generally spoken that light and soil water conditions within patches often negatively correlate, significantly affecting the growth of clonal plants. But the role of clonal integration in modulating carbohydrate metabolism of paired ramets under heterogeneous environments remains unclear. Hence the initial research is performed focusing on water and carbohydrate sharing among ramets under heterogeneous environments and its impact on non-structural carbohydrate (NSC) accumulation and conversion of whole clonal system. Connected and disconnected clonal fragments of dwarf bamboo were planted in four heterogeneous environments differing in patch contrast with negatively correlated light and soil water. Photosynthetic capacity, NSC content, and its metabolic characteristics were measured, and the effects of water and NSC sharing on the performance of paired bamboo ramets were also analyzed. Leaf photosynthetic rate (Pn) and NSC content of shade ramets ranged from 7.06 to 8.56μmol·m−2·s−1, 140.85–176.12 mg.g−1, and those for unshaded ramets were 3.98 ∼6.97μmol·m−2·s−1 and 129.58–170.81 mg.g−1, respectively. Rhizome connection significantly decreased leaf Pn, NSC, chlorophyll, and RuBisCo in shaded ramets but increased these parameters in unshaded ramets. High water contrast led to higher leaf Pn, NSC, chlorophyll, and RuBisCo activity in both ramets with rhizome connection. Moderately shaded treatments (50 % shading) increased leaf Pn, NSC, and chlorophyll content in both shaded and unshaded ramets with rhizome connection. Rhizome connection significantly decreased the activities of sucrose synthase (SS), sucrose phosphate synthase (SPS), and amylase in shaded ramets, but increased SS, SPS, amylase, and invertase (INV) in unshaded ramets. Water sharing promoted both leaf NSC and Pn in ramets growing under high light but low soil water conditions when connected to ramets growing under shading but higher soil water conditions. The mutual conversion of starch into sugar between paired ramets enhanced the fitness of the entire clonal system. Obviously the findings provide new insights into the adaptive strategies of dwarf bamboo to drought and shading stress through physiological integration (water and NSC sharing) and NSC conversion, which could help predict the impact of climate change on bamboo growth and productivity.
{"title":"Clonal integration alters metabolic non-structural carbohydrate processes of a dwarf bamboo under negatively correlated light and soil water conditions","authors":"Ziwu Guo , Qin Li , Jing Wu , Liting Yang , Lili Fan , Le Zhang , Minghui Qin , Shuanglin Chen","doi":"10.1016/j.agwat.2024.109152","DOIUrl":"10.1016/j.agwat.2024.109152","url":null,"abstract":"<div><div>Generally spoken that light and soil water conditions within patches often negatively correlate, significantly affecting the growth of clonal plants. But the role of clonal integration in modulating carbohydrate metabolism of paired ramets under heterogeneous environments remains unclear. Hence the initial research is performed focusing on water and carbohydrate sharing among ramets under heterogeneous environments and its impact on non-structural carbohydrate (NSC) accumulation and conversion of whole clonal system. Connected and disconnected clonal fragments of dwarf bamboo were planted in four heterogeneous environments differing in patch contrast with negatively correlated light and soil water. Photosynthetic capacity, NSC content, and its metabolic characteristics were measured, and the effects of water and NSC sharing on the performance of paired bamboo ramets were also analyzed. Leaf photosynthetic rate (<em>P</em><sub><em>n</em></sub>) and NSC content of shade ramets ranged from 7.06 to 8.56μmol·m<sup>−2</sup>·s<sup>−1</sup>, 140.85–176.12 mg.g<sup>−1</sup>, and those for unshaded ramets were 3.98 ∼6.97μmol·m<sup>−2</sup>·s<sup>−1</sup> and 129.58–170.81 mg.g<sup>−1</sup>, respectively. Rhizome connection significantly decreased leaf <em>P</em><sub><em>n</em></sub>, NSC, chlorophyll, and RuBisCo in shaded ramets but increased these parameters in unshaded ramets. High water contrast led to higher leaf <em>P</em><sub><em>n</em></sub>, NSC, chlorophyll, and RuBisCo activity in both ramets with rhizome connection. Moderately shaded treatments (50 % shading) increased leaf <em>P</em><sub><em>n</em></sub>, NSC, and chlorophyll content in both shaded and unshaded ramets with rhizome connection. Rhizome connection significantly decreased the activities of sucrose synthase (SS), sucrose phosphate synthase (SPS), and amylase in shaded ramets, but increased SS, SPS, amylase, and invertase (INV) in unshaded ramets. Water sharing promoted both leaf NSC and <em>P</em><sub><em>n</em></sub> in ramets growing under high light but low soil water conditions when connected to ramets growing under shading but higher soil water conditions. The mutual conversion of starch into sugar between paired ramets enhanced the fitness of the entire clonal system. Obviously the findings provide new insights into the adaptive strategies of dwarf bamboo to drought and shading stress through physiological integration (water and NSC sharing) and NSC conversion, which could help predict the impact of climate change on bamboo growth and productivity.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109152"},"PeriodicalIF":5.9,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661735","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}
Pub Date : 2024-11-09DOI: 10.1016/j.agwat.2024.109160
Tingrui Yang , Jinghua Zhao , Ming Hong , Mingjie Ma
To improve nitrogen uptake and grain quality in maize, this study explores the dynamic processes of nitrogen accumulation, distribution, and translocation under varying water and nitrogen supplies, aiming to optimize water-nitrogen management practices. Field trials were conducted in Karamay, Xinjiang, in 2022 and 2023, with different irrigation levels (75 % ETc, 100 % ETc, 125 % ETc) and nitrogen application rates (0, 93, 186, 279 kg Nhm−2). The effects of water and nitrogen supply on nitrogen accumulation and distribution in aboveground maize organs were analyzed, and the dynamic characteristics of maize nitrogen accumulation were examined using the characteristic parameters of the Richards nitrogen accumulation equation. The results showed that beyond the W2N2 treatment (irrigation at 100 % ETc and nitrogen application of 186 kg N hm−2), increases in irrigation and nitrogen did not significantly enhance nitrogen accumulation per plant. Under W2N2, high levels of nitrogen were accumulated in maize leaf, stem, bract, cob, and grain. The nitrogen transfer among different organs and their contribution to grain nitrogen showed the following hierarchy: leaf > stem > cob > bract, with the contribution rates to grain nitrogen ranging from 26.16 % to 56.23 % over the two years. The Richards model accurately quantified the dynamic relationship between water-nitrogen supply and crop nitrogen accumulation, with the coefficient of determination (R²) ranging from 0.9864 to 0.9999 and the normalized root mean square error (NRMSE) from 0.70 % to 6.51 %. Optimal water-nitrogen supply significantly reduced the accumulated temperature required for maize to enter the rapid nitrogen accumulation phase and achieve maximum growth rates, while extending the duration of the rapid growth phase and increasing both the maximum growth rate and the average growth rate during this period. Grain nitrogen accumulation was positively correlated with nitrogen accumulation rates, as well as nitrogen accumulation and translocation in various organs. Under suitable irrigation and nitrogen application, the interactive effects of water and nitrogen (W × N) significantly increased both nitrogen accumulation and nitrogen accumulation rates, laying a foundation for nitrogen translocation to grains in the late growth stages and enhancing grain nitrogen accumulation. Thus, appropriate water and nitrogen supply can significantly influence nitrogen accumulation, distribution, and translocation processes in maize, regulating grain nitrogen accumulation. This study provides valuable information for nitrogen accumulation regulation and grain quality improvement in maize in Xinjiang and other regions with similar climatic conditions.
{"title":"Appropriate water and nitrogen supply regulates the dynamics of nitrogen translocation and thereby enhancing the accumulation of nitrogen in maize grains","authors":"Tingrui Yang , Jinghua Zhao , Ming Hong , Mingjie Ma","doi":"10.1016/j.agwat.2024.109160","DOIUrl":"10.1016/j.agwat.2024.109160","url":null,"abstract":"<div><div>To improve nitrogen uptake and grain quality in maize, this study explores the dynamic processes of nitrogen accumulation, distribution, and translocation under varying water and nitrogen supplies, aiming to optimize water-nitrogen management practices. Field trials were conducted in Karamay, Xinjiang, in 2022 and 2023, with different irrigation levels (75 % ET<sub>c</sub>, 100 % ET<sub>c</sub>, 125 % ET<sub>c</sub>) and nitrogen application rates (0, 93, 186, 279 kg Nhm<sup>−2</sup>). The effects of water and nitrogen supply on nitrogen accumulation and distribution in aboveground maize organs were analyzed, and the dynamic characteristics of maize nitrogen accumulation were examined using the characteristic parameters of the Richards nitrogen accumulation equation. The results showed that beyond the W2N2 treatment (irrigation at 100 % ET<sub>c</sub> and nitrogen application of 186 kg N hm<sup>−2</sup>), increases in irrigation and nitrogen did not significantly enhance nitrogen accumulation per plant. Under W2N2, high levels of nitrogen were accumulated in maize leaf, stem, bract, cob, and grain. The nitrogen transfer among different organs and their contribution to grain nitrogen showed the following hierarchy: leaf > stem > cob > bract, with the contribution rates to grain nitrogen ranging from 26.16 % to 56.23 % over the two years. The Richards model accurately quantified the dynamic relationship between water-nitrogen supply and crop nitrogen accumulation, with the coefficient of determination (<em>R</em>²) ranging from 0.9864 to 0.9999 and the normalized root mean square error (<em>NRMSE</em>) from 0.70 % to 6.51 %. Optimal water-nitrogen supply significantly reduced the accumulated temperature required for maize to enter the rapid nitrogen accumulation phase and achieve maximum growth rates, while extending the duration of the rapid growth phase and increasing both the maximum growth rate and the average growth rate during this period. Grain nitrogen accumulation was positively correlated with nitrogen accumulation rates, as well as nitrogen accumulation and translocation in various organs. Under suitable irrigation and nitrogen application, the interactive effects of water and nitrogen (W × N) significantly increased both nitrogen accumulation and nitrogen accumulation rates, laying a foundation for nitrogen translocation to grains in the late growth stages and enhancing grain nitrogen accumulation. Thus, appropriate water and nitrogen supply can significantly influence nitrogen accumulation, distribution, and translocation processes in maize, regulating grain nitrogen accumulation. This study provides valuable information for nitrogen accumulation regulation and grain quality improvement in maize in Xinjiang and other regions with similar climatic conditions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109160"},"PeriodicalIF":5.9,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661736","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}
Monitoring soil salinity is essential for understanding the behavior of coastal wetland ecosystems and implementing effective management strategies. Despite the advantages of the Multi-Spectral Instrument (MSI) data for large-scale, high-frequency soil salinity monitoring, challenges remain in data preprocessing and model construction. We combined fractional-order derivative (FOD) technology with stacked machine learning models to monitor and map soil salinity using Sentinel-2 MSI data. The base models included Elastic Net Regression, Support Vector Regression, Artificial Neural Network, Extreme Gradient Boosting, and Random Forest, with Non-Negative Least Squares as the meta-learner. The results showed that low-order FOD enhanced image gradients and maintained a high peak signal-to-noise ratio, thereby improving the correlation with soil salinity. Notably, the 0.25-order FOD showed the best performance, increasing the correlation coefficient with soil salinity by up to 13 %. The stacked machine learning models effectively combined the strengths of different base models, enhancing prediction accuracy by more than 8 % compared to single models. Furthermore, combining stacked models with FOD further improved prediction accuracy, with an increase in R² of up to 9 %. The combination of 0.25-order FOD and the stacked machine learning model achieved the best performance (R² = 0.82, RMSE = 10.19 ppt, RPD = 2.38, RPIQ = 4.69). This approach provides a reference for rapid and effective large-scale digital mapping of soil salinity in coastal wetlands.
监测土壤盐度对于了解沿岸湿地生态系统的行为和实施有效的管理策略至关重要。尽管多光谱仪器（MSI）数据在大规模、高频率土壤盐度监测方面具有优势，但在数据预处理和模型构建方面仍存在挑战。我们将分数阶导数（FOD）技术与堆叠式机器学习模型相结合，利用哨兵-2 MSI 数据监测和绘制土壤盐度图。基础模型包括弹性网回归、支持向量回归、人工神经网络、极梯度提升和随机森林，元学习器为非负最小二乘法。结果表明，低阶 FOD 增强了图像梯度，并保持了较高的峰值信噪比，从而提高了与土壤盐度的相关性。值得注意的是，0.25阶 FOD 表现最佳，与土壤盐度的相关系数提高了 13%。堆叠机器学习模型有效地结合了不同基础模型的优势，与单一模型相比，预测精度提高了 8% 以上。此外，将堆叠模型与 FOD 相结合还进一步提高了预测精度，R² 提高了 9%。0.25 阶 FOD 与堆叠机器学习模型的组合取得了最佳性能（R² = 0.82、RMSE = 10.19 ppt、RPD = 2.38、RPIQ = 4.69）。该方法为快速有效地绘制沿海湿地土壤盐度大尺度数字地图提供了参考。
{"title":"Monitoring soil salinity in coastal wetlands with Sentinel-2 MSI data: Combining fractional-order derivatives and stacked machine learning models","authors":"Congcong Lao , Xiayang Yu , Lucheng Zhan , Pei Xin","doi":"10.1016/j.agwat.2024.109147","DOIUrl":"10.1016/j.agwat.2024.109147","url":null,"abstract":"<div><div>Monitoring soil salinity is essential for understanding the behavior of coastal wetland ecosystems and implementing effective management strategies. Despite the advantages of the Multi-Spectral Instrument (MSI) data for large-scale, high-frequency soil salinity monitoring, challenges remain in data preprocessing and model construction. We combined fractional-order derivative (FOD) technology with stacked machine learning models to monitor and map soil salinity using Sentinel-2 MSI data. The base models included Elastic Net Regression, Support Vector Regression, Artificial Neural Network, Extreme Gradient Boosting, and Random Forest, with Non-Negative Least Squares as the meta-learner. The results showed that low-order FOD enhanced image gradients and maintained a high peak signal-to-noise ratio, thereby improving the correlation with soil salinity. Notably, the 0.25-order FOD showed the best performance, increasing the correlation coefficient with soil salinity by up to 13 %. The stacked machine learning models effectively combined the strengths of different base models, enhancing prediction accuracy by more than 8 % compared to single models. Furthermore, combining stacked models with FOD further improved prediction accuracy, with an increase in R² of up to 9 %. The combination of 0.25-order FOD and the stacked machine learning model achieved the best performance (R² = 0.82, RMSE = 10.19 ppt, RPD = 2.38, RPIQ = 4.69). This approach provides a reference for rapid and effective large-scale digital mapping of soil salinity in coastal wetlands.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109147"},"PeriodicalIF":5.9,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661733","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}
Pub Date : 2024-11-08DOI: 10.1016/j.agwat.2024.109157
Zhonghui Guo, Chang Feng, Liu Yang, Qing Liu
Blue water (BW) and green water (GW) are crucial components of the hydrological cycle, but their accurate simulation and interpretation remain challenging in data-scarce basins. We propose the SWAT-ELM-SHAP model, coupling the Soil and Water Assessment Tool (SWAT), Ensemble Learning Model (ELM), and Shapley Additive Explanations (SHAP) method. This novel approach bridges the gap between a physically-based hydrological model, a data-driven machine learning (ML) model, and a holistically-interpreted SHAP method, offering accurate blue-green water simulation and holistic result interpretation for improved water resources management in data-scarce basins. We took the transfer simulation of blue-green water from the Xiangjiang River Basin (source basin) to the Zishui River Basin (target basin) as a case study to test and evaluate the feasibility of the coupled model during 1991–2022. The model performance results indicate that the simulation accuracy of our new coupled model is improved in data-scarce basins. In combination with hydrological response features generated by SWAT and meteorological features as the ELM input, our model enhances the daily blue-green water simulation. The Nash-Sutcliffe Efficiency coefficient (NSE) for BW, Green water flow (GWF), and Green water storage (GWS) consistently exceeds 0.77 during the calibration period (1991–2010) and exceeds 0.8 during the testing period (2011–2022). The interpretation results of coupled model demonstrate that SHAP holistic interpretation provides good interpretability for blue-green water simulation results in data-scarce basins. In general, the SWAT-ELM-SHAP offers a referenced approach that can reliably and efficiently simulate blue-green water in data-scarce basins, but more importantly, can further our understanding of the potential causal relationships, influence mechanisms, and variation mechanisms of blue-green water under changing environmental conditions.
{"title":"Bridging the gap: An interpretable coupled model (SWAT-ELM-SHAP) for blue-green water simulation in data-scarce basins","authors":"Zhonghui Guo, Chang Feng, Liu Yang, Qing Liu","doi":"10.1016/j.agwat.2024.109157","DOIUrl":"10.1016/j.agwat.2024.109157","url":null,"abstract":"<div><div>Blue water (BW) and green water (GW) are crucial components of the hydrological cycle, but their accurate simulation and interpretation remain challenging in data-scarce basins. We propose the SWAT-ELM-SHAP model, coupling the Soil and Water Assessment Tool (SWAT), Ensemble Learning Model (ELM), and Shapley Additive Explanations (SHAP) method. This novel approach bridges the gap between a physically-based hydrological model, a data-driven machine learning (ML) model, and a holistically-interpreted SHAP method, offering accurate blue-green water simulation and holistic result interpretation for improved water resources management in data-scarce basins. We took the transfer simulation of blue-green water from the Xiangjiang River Basin (source basin) to the Zishui River Basin (target basin) as a case study to test and evaluate the feasibility of the coupled model during 1991–2022. The model performance results indicate that the simulation accuracy of our new coupled model is improved in data-scarce basins. In combination with hydrological response features generated by SWAT and meteorological features as the ELM input, our model enhances the daily blue-green water simulation. The Nash-Sutcliffe Efficiency coefficient (NSE) for BW, Green water flow (GWF), and Green water storage (GWS) consistently exceeds 0.77 during the calibration period (1991–2010) and exceeds 0.8 during the testing period (2011–2022). The interpretation results of coupled model demonstrate that SHAP holistic interpretation provides good interpretability for blue-green water simulation results in data-scarce basins. In general, the SWAT-ELM-SHAP offers a referenced approach that can reliably and efficiently simulate blue-green water in data-scarce basins, but more importantly, can further our understanding of the potential causal relationships, influence mechanisms, and variation mechanisms of blue-green water under changing environmental conditions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"306 ","pages":"Article 109157"},"PeriodicalIF":5.9,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661734","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}
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