Predicting drought and flood disaster-prone alternating zones and enhancing cropland disaster resilience are critical for agricultural water management, mitigating meteorological disaster risks, and ensuring food security. However, the spatial prediction of climate disaster vulnerability at the local scale faces challenges such as data gaps and insufficient resolution, which results in a lack of relevant research. This study uses a coupled model of particle swarm optimization (PSO), long short-term memory (LSTM), and graph attention network (GAT) integrating historical data to predict drought- and flood-prone areas in 2035 in Heshun County, Shanxi Province, a typical small-scale inland mountainous region of China. Additionally, the study assesses cropland resilience using the TOPSIS method, and based on the spatial distribution of drought and flood disasters, proposes a Flood- Drought-Resilience Analysis (FDRA) framework, further formulating a site selection strategy for future High Standard Farmland (HSF) projects. The overall findings indicate that: (1) Precipitation (Pr) and the Standardized Precipitation-Evapotranspiration Index (SPEI) have increased in recent years, with Pr expected to continue rising until 2035. (2) The integration of historical data with the predictions from the PSO-LSTM-GAT model reveals significant spatial overlap between historical and future disaster-prone areas and intensive cropland, especially in the central region. (3) Compared to single models, the PSO-LSTM-GAT model demonstrates significantly improved performance and precision in predicting drought- and flood-prone areas. (4) Through the FDRA integrated adjustment mechanism, 6.6668 km2 of unsuitable land was identified, and 6.7349 km2 of high-quality land was selected as the proposed site for the next round of HSF projects. In the final part of the study, management zoning plans were designed for other areas vulnerable to drought and flood disasters, and specific recommendations for enhancing cropland resilience were provided. This study provides a theoretical basis for enhancing agricultural disaster resilience and sustainable development in localized areas, offering scientific decision-making support for policymakers to address future climate change and disaster risks.

Sewage sludge (SS) poses significant environmental and socio-economic challenges due to its high moisture content and limited disposal options. Hydrothermal carbonization (HTC) has been identified as an effective pretreatment method to enhance the stability and reactivity of hydrochar (HC) for energy applications. This study investigates the co-gasification behavior of pyrolyzed HC derived from SS and coal char in CO2 environments, with a focus on the influence of temperature (850 degrees C, 900 degrees C, and 950 degrees C) and particle size (35 mu m, 110 mu m, 250 mu m, and 430 mu m) on gasification reactivity and carbon conversion. Experimental results show that smaller particles (35 mu m) exhibited the highest reactivity due to their larger surface area-to-volume ratio, achieving a gasification rate of 0.010945 s-1 at 950 degrees C. Increasing the temperature significantly enhanced carbon conversion, with conversion rates accelerating particularly at 950 degrees C during the initial phases. Coal char demonstrated rapid thermal degradation, while HC displayed superior thermal stability and reduced reactivity at higher temperatures due to its more condensed carbon structure. Notably, HC concentrations (15 %) improved overall reactivity compared to lower concentrations (5 %), emphasizing the synergistic effects of co-gasification. This study highlights the critical role of temperature and particle size in optimizing waste-to-energy conversion processes, offering actionable insights for enhancing efficiency and sustainability in waste management systems.

In the context of climate change, exploring and predicting the spatio-temporal distribution of flood disasters is crucial for developing effective flood risk management and disaster reduction strategies. This study tackles the shortcomings of traditional methods used to measure the risk of regional flood disasters, which often lack precision. A series of machine learning models enhanced by Particle Swarm Optimization - Machine learning (PSO-ML) models were developed and integrated with General Circulation Model (GCM) data to analyze the temporal and spatial characteristics of flood disasters under different scenarios in Shanxi Province, China. Results indicate that the frequency of days with precipitation exceeding 50 mm in the study area increased from 23 in 1981 to 71 in 2021. The northernmost city, DT, experienced 18 extreme precipitation days, while the southernmost city, YC, recorded 71 such days. A gradual increasing trend in extreme precipitation days was observed from north to south and from distant to near areas. The PSO-ML models demonstrated notably improved performance compared to traditional models across all indices. PSO-XGBoost, PSO-RF, and PSO-KNN exhibited higher prediction accuracy than conventional single models, with AUC values of 0.98, 0.95, and 0.94, respectively. Land use change, elevation, and slope emerged as the most influential factors, with weights of 10.37%, 10.01%, and 8.76%, respectively. Across four scenarios (SSP126, SSP245, SSP370, and SSP585), flood-prone areas were projected to shift southward, with varying degrees of increase in risk areas. The SSP370 scenario showed gradual growth, projecting 7660.116 km² of at-risk area by 2100. The SSP585 scenario exhibited the most rapid growth, with a projected peak of 13,933.69 km² by 2070. This research proposes a novel approach to flood disaster risk assessment and offers insights for effectively mitigating regional flood risks.

Antibiotic resistance is emerging as a critical issue in chicken farms due to the excessive use of antibiotics. However, the current understanding of the richness (abundance), diversity, and spatial distribution of airborne antibiotic resistance genes remains limited. According to the findings, bioaerosol is one of the major pathways for the transmission of antibiotic resistance genes (ARGs) in chicken farms. The research focused on the analysis of bacterial communities, mobile genetic elements (MGEs), and ARGs in samples of both feces and air, comparing summer and winter conditions. The average concentration of airborne ARGs and MGEs during winter is higher than that during summer when using the ventilation system. The tetC gene has been detected as the main airborne ARGs, with an abundance of tetC was 4.9 +/- 0.3 lg copies/m3. Lactobacillus and Acinetobacter, along with various opportunistic pathogens, have been identified as predominant bacteria in both air and fecal samples. Diverse bacterial populations tend to proliferate at high temperatures, while relative humidity (RH) has adverse effects. Wind velocity plays a crucial role in dispersing ARGs through the air. Network interaction analysis indicates that fecal matter contributes to 19.9% of airborne bacterial levels in summer and 59.4% in winter. Additionally, horizontal gene transfer (HGT) significantly contributes to the dissemination of airborne ARGs during winter, with a probability of 77.8%, compared to a minimal probability of 12.0% in summer. These findings may deliver a comprehensive knowledge of the transmission and dissemination characteristics of airborne ARGs and serve as a guideline for evaluating potential threats associated with chicken farms. There is a need for increased endeavors to mitigate and control the potential health risks arising from airborne ARGs.

Rice is an important cereal crop rich in starch and carbohydrates grown around the globe. Despite its significance, rice exhibits substantial genetic variation, particularly under environmental stresses such as salinity. This study investigates the genetic diversity of F3 segregating populations of rice under normal and salt stress. Various segregating genotypes were evaluated, demonstrating statistically significant differences (p<0.01 and p<0.05, ANOVA) in morphological and physiological parameters. The genotypes Kharagnjia and L-12 performed well in normal soils, while Shua-92 and L-20 showed better performance in tiller plant-1 and panicle length. The cluster analysis grouped rice genotypes into four major clusters based on genetic similarity. Principal Component Analysis (PCA) identified tillers per plant, panicle length, grain yield per plant, and leaf area as key contributors to genetic variation. The highest variability was observed in PC-XII (100%) and PC-XI (98.3%). These findings provide valuable insights for breeding programs aimed at enhancing salt tolerance in rice.

Analysing the patterns and impacts of land-use changes in the production–living–ecological space (PLES) of the Fenhe River Basin (FRB 39,721 km2), China, is necessary to support sustainable development. Based on remote sensing images from 1990 to 2020, we aimed to analyse the PLES land-use changes. Industrial production and living spaces continuously encroached on the agricultural production and ecological spaces between 1990 and 2022 owing to industrialisation and urbanisation, and the ecological land area decreased by 699.21 km2, while the industrial production land area increased by 521.32 km2. We used the soil and water assessment tool (SWAT) model to quantitatively analyse the impact of PLES changes on runoff in the FRB. With the continuous expansion of production and living spaces, the extensive use of concrete in cities has led to ground hardening, making it difficult for precipitation to infiltrate, with surface runoff increasing by 0.3 mm annually. The reduction in ecological space has led to a reduction in forests and grasslands, weakening the water-holding capacity of the watershed and affecting groundwater storage. This study provides a scientific basis for watershed management and the integrated development of PLES.

This study reports the optimum hydrogen (H2) production from municipal solid waste (MSW) via waste eggshell derived-CaO catalyst through gasification technology. The response surface model was applied to design the experiments and the data validation. Results showed that CaO catalyst had a better performance that enhanced 15 mol% more H2 production than non-catalytic gasification by mainly involving reaction temperature and catalyst loading as the critical parameters. Tar content was efficiently declined from 11.34 wt. % to 4.7 , wt. %, which ultimately elevated the H2 and syngas from 33.95 mol% to 51.27 mol% and 74.05 to 83.4674.05–83.46 wt. %, respectively. The model showed a strong interaction among the statistical parameters verified through the regression values; R2 = 0.990, P-value = 0.000005, respectively. Scanning electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller techniques investigated the catalyst's structure hence; presented comparable results. From tar analysis, the aromatics were found as the dominant family followed by polycyclic aromatic, phenyls, aliphatic, aromatic heterocyclic, polycyclic, and aromatic ketones. Optimum H2 production of 51.27 mol% (with H2/CO ratio 2.82, LHV 9.47 MJ/Nm3, and H2 yield 22.74 mol kg-MSW−1) was produced which can be a better alternative to depleting fossil fuels and utilized for liquid fuel manufacturing and power generation.

分析欠发达地区土地流转行为的影响因素,揭示其影响机理,可为加快欠发达地区土地流转,完善流转政策提供有益参考.文章基于技术接受模型理论,利用山西省欠发达地区5307份农户样本,应用结构方程模型揭示农户土地流转行为的影响机理.结果表明:1)感知有用性和感知易用性对农户土地流转行为产生正向影响,感知有用性的作用效应强于感知易用性,其中经济感知有用性的作用效应最强.2)家庭环境、社会环境及土地环境通过影响农户土地流转感知而间接影响其土地流转行为.3)农户土地流转行为的决策路径为:外部环境因素→感知有用性→ 土地流转行为;外部环境因素→ 感知易用性→土地流转行为;外部环境→感知易用性→感知有用性→土地流转行为.由此可见,基于特定环境所形成的感知有用性和感知易用性会对土地流转行为产生显著影响.因此推动土地流转,应当立足当地实际,重点提增土地流转的经济效益,提升流转交易的便捷度.

以山西省107个县域为研究单元,基于全排列多边形综合图示法计算土地多功能利用水平值,采用空间解析几何模型测度土地多功能耦合度、协调性、综合发展程度,并以轨迹分析法进行分区,探究2005-2020年土地多功能综合发展程度及区域协调发展情况,厘清县域土地多功能利用水平综合情况.结果表明:(1)山西省土地多功能利用水平时空演化阶段特征明显,2005-2020年生产功能优势区由点状分布逐步扩散、联结,呈现集聚态势,且随着能矿经济衰退和经济转型,导致2020年集聚度较2010年明显降低;生活功能与生产功能空间格局基本一致,呈现分区集聚、南强于北的特征;生态功能相对稳定,与生产、生活功能鲜明互补.(2)土地多功能空间协调偏离度与耦合度空间分布有异但格局特征趋同;而综合发展程度与耦合度空间分异均呈阶段性变化.(3)生产与生活功能的耦合度、综合发展程度总体提升,但提升幅度小,整体水平低;生态功能微弱恢复,整体水平趋于中等;协调偏离度整体较优,但存在低水平协调.

"国土空间规划概论"课程是研究人地系统问题的综合性课程,是土地资源管理专业重要的专业基础课.文章基于新文科发展要求,将PBL教学模式引入"国土空间规划概论"课程教学实践,系统阐述了 PBL教学在该课程中的显著优势,设计基于PBL教学模式的课程组织过程和教学环节,构建一种符合应用型文科发展需要的国土空间规划课程PBL教学模式,为土地资源管理专业在新文科建设中实现优化升级提供了一种新的路径.

The general land use planning is to arrange all kinds of land use behaviors in an orderly manner, and its own disorder will inevitably affect the scientific and authoritative nature of the general land use planning, which makes the effect of land management unsatisfactory. The reason is that there are differences in the spatial scale of general land use planning, which makes the analysis of land information not comprehensive enough. Therefore, this paper puts forward the dynamic planning of sustainable land use based on GIS and symmetry algorithm. The collected land information is preprocessed by ArcGIS, and the land remote sensing images are classified by decision tree combined with ENVI (Visual Image Environment), using local sparse coding to extract land use features, with enhancement and reconstruction of remote sensing images using symmetric algorithm. On this basis, the factors that limit the spatial expansion of land are analyzed, and the land planning is completed by substituting them into Arc Map software. Experiments show that the average accuracy rate of this method for land planning reaches 91.22%, which can effectively complete land planning.

厘清黄河流域生态现状,分析生态系统服务时空演化特征及与经济协调发展情况,对提升区域经济协调发展具有重要意义.基于黄河流域9省区2000—?2020年土地利用数据及国民经济发展数据,测算生态系统服务价值及经济与生态环境协调指数,揭示黄河流域生态系统服务价值时空演化特征及与经济协调发展关系,结果表明:(1)2000—?2020年黄河流域全域生态服务价值(ESV)持续增长,由2000年的7020.74亿元增长到2020年的25598.24亿元;(2)研究期内,黄河流域经济与生态协调发展存在显著空间相关性,且人类活动及土地利用方式对生态系统服务价值影响较大,高度冲突区逐渐集中于上游青海、四川、甘肃等省区内经济欠发达地区和下游河南、山东等省区内人类干扰密度较高的地区;(3)研究区经济与生态环境协调发展空间分布不均衡,2000—?2020年空间集聚态势逐步加大,且冲突区面积远大于协调区,中下游及下游区域两极分化现象明显;(4)研究区内不同区域资源禀赋与生态环境差异较大,要因地制宜,找出不同区域适合自身发展的路径,综合推动黄河流域经济发展与生态环境保护的耦合协调发展.

农地流转是实现规模化经营和促进农民收入的重要手段,深入探讨农地流转相关问题对于农村发展及巩固脱贫具有重要意义.基于计划行为理论,利用山西省陵川县的实地调研数据,通过中介效应模型检验农地流转意愿是否对农户认知与农地流转产生中介效应,并进一步采用二元Logistic回归模型分析农户流转意愿与流转行为产生偏差的影响因素.研究结果表明,农户流转意愿对于农户认知与农地流转行为间的中介效应显著;农地流转中有意愿并参与流转的农户有73户,占到总比的47.4％,有意愿但未流转的农户也有81户,达到总比例的52.6％,二者间存在较大偏差;农户流转意愿与行为产生偏差的主要影响因素包括农户性别、农户职业、家庭人口数量、家庭耕地数量、家庭收入、耕地撂荒情况和农户认知7个因素,各因素均呈现不同的正负作用.在此研究基础上,对当前研究区域内存在的农地流转问题提出相关建议.

为探究生产—生活—生态（"三生"）功能协调情况,基于综合评价模型和力学平衡模型,选用2005年、2010年和2018年土地利用类型和统计数据,测度山西省"三生"功能时空演变及协同/权衡关系特征。结果表明:（1）2005—2018年"三生"功能时空分异特征明显,生产功能为下降态势,呈现出"平原高,山区低"的分布格局;生活功能持续上升,空间分布与生产功能相似;生态功能呈上升状态,但需注意恶化倾向,空间格局稳定。（2）研究期间,"三生"功能协同性显著提升且趋势合理,空间分布与生产、生活功能趋同。（3）依据"三生"功能协调度偏离情况,划分功能主导区和提升区,明确各县域功能特征。研究结果可为国土空间规划提供依据。

探究生产-生活-生态("三生")功能耦合协调关系可为国土空间规划和区域协调发展提供依据,本研究利用耦合协调度模型、空间相关性分析和Tobit模型,选用2005、2010、2018年土地利用类型和统计数据分析山西省县域"三生"功能耦合协调度时空演化特征及相关影响因素.结果表明:(1)2005—2018年山西省县域耦合协调度水平显著提升,耦合协调变化由不合理转向合理.(2)2005—2018年山西省县域"三生"功能耦合协调度水平地域分异特征明显,整体呈现出"东西低,中部高;平原高,山地低"的空间分布格局.(3)山西省县域"三生"功能耦合协调度存在显著的空间相关性,高水平县域在平原区小规模集聚,低水平县域在山地区大范围集中.(4)山西省县域"三生"功能耦合协调度时空分异是国家宏观管制、社会经济因素、自然资源禀赋和自然地理条件综合作用的结果.

为了探究不同退耕还林地的土壤养分保持特征,以黄土高原丘陵沟壑区岔口流域不同退耕还林地为研究对象,对实施退耕还林后的生态林地(刺槐、柏树)、经济林地(核桃林地)土壤样品进行采集,并以坡耕地土壤样本为对照,采用单因素方差分析(one-way ANOVA)的方法进行不同样地0～ 20和20 ～ 40 cm土层养分含量的多重比较,以皮尔逊相关系数进行土壤养分间的相关分析性,并以修正的内梅罗公式对不同退耕还林样地土壤养分进行评价.结果 表明:1)岔口流域退耕还林土壤养分含量多属于中等变异,表层(0 ～20 cm)土壤的各养分含量均高于20 ～ 40 cm土层;2)不同样地土壤养分含量总体上表现为生态林＞经济林＞坡耕地;3)退耕还林样地土壤的有机质与全氮、速效氮及速效钾含量呈显著相关;4)流域生态林土壤养分综合评价为“中”,经济林为“差”.该研究显示,岔口流域退耕还林地土壤养分保持效益总体上优于坡耕地,但不同退耕还林地土壤的各养分保持特征呈现出一定的差异性,对于生态林地与经济林地的土壤养分进行综合研究,可为不同模式退耕还林地土壤生态修复提供依据.

[目的]探究山西省不同县域"三生"功能时空动态演化特征并分析其影响因素,为国土空间规划提供依据.[方法]基于山西省107个县2005,2010,2018年土地利用类型和统计数据,采用综合指数模型、动态度和空间计量模型分析其"三生"功能时空演化过程及影响因素.[结果]①2005-2018年山西省"三生"功能空间分异明显,生产、生活功能格局特征趋同,呈现出"平原高,山区低"的分布格局;生态功能分布特征与生产生活相反,空间格局稳定;"三生"综合功能提升明显,表现为"南高北低,中部高东西低"的局面.②2005-2018年生产和生态功能水平缓慢变化,呈现出先上升后下降波动变化趋势;生活功能处于快速提升阶段,提升明显;"三生"综合功能持续提高,但提升缓慢."三生"功能协调性提高,但功能单一化程度较高.③"三生"功能时空分异是自然地理环境、自然资源禀赋及社会经济因素综合作用的结果,"三生"功能受制于自然地理条件,自然资源禀赋是"三生"功能的基础和保障,社会经济因素则是"三生"功能的主要驱动力.[结论]山西省各县域需要在自然地理条件约束和经济社会转型发展背景下,促进"三生"功能各自提升与彼此协调,需要在明确各自主体功能定位的基础上,因地制宜,合理发展,依托自身区域优势与资源禀赋,构建起利益联结机制,推动山西省整体协调可持续发展.

如何以最小的城市土地资源投入获得最大的社会经济生态效益是区域可持续利用和高质量发展关注的重点之一.以黄河流域资源型城市为研究对象,构建土地绿色利用效率测算指标体系,利用SSBM(Super Slack Based Measure,SSBM)模型测度2009-2018年黄河流域资源型城市土地绿色利用效率,选取空间自相关模型分析土地绿色利用效率的时空演变特征,借助时空地理加权回归(Geographically and Temporally Weighted Regression,GTWR)模型揭示影响土地绿色利用效率因素.研究结果表明:1)从时序变化来看,2009-2018年,黄河流域资源型城市土地绿色利用效率整体变化趋势不明显.2)从空间差异来看,黄河流域资源型城市整体空间关联性不强,集聚态势不显著,局部表现出"小集聚大分散"的空间分布特征.3)土地绿色利用效率影响因素具有空间异质性特征,经济和产业结构始终是影响区域土地绿色利用效率的核心因素,科技作用逐渐凸显,同时不同类型资源型城市主导因素存在明显差异.研究结果对于促进土地绿色利用效率驱动机制的深入研究具有指导意义,也可为黄河流域资源型城市土地高效可持续利用提供科学参考.

针对不同因素影响,山区微小水体提取效果不佳的问题,选用2016年9月1日GF-1号卫星遥感影像,运用NDWI、SWI决策树、SVM分类3种不同方法对位于黄土高原沟壑区的山西省岔口流域的微小水体进行了提取,并对提取效果进行视觉对比与精度验证.结果表明,相比中低分辨率遥感影像,高分辨率遥感影像对于山区微小水体的提取结果更好,精度更高,可运用GF-1号影像进行流域水体的监测、提取;影响流域水体提取的主要因素是亮色地物(主要为建筑物)和阴影;NDWI、SWI决策树、SVM分类3种方法中,NDWI方式提取的水体信息较弱,SWI决策树与SVM分类法精度较高,但SWI决策树法消除了建筑物、亮色地物的影响,并较明显地区分了阴影与水体,因此更适用于流域微小水体的提取.

为分析比较全球公顷和国家公顷核算水资源生态足迹的异同,基于水资源生态足迹理论与方法,构建出"全球公顷"和"国家公顷"的山西省水资源生态足迹计算模型,对其2007—2018年水资源生态足迹进行了测算与比较分析.结果表明:(1)2种不同算法得出12年间山西省人均水资源生态足迹、人均水资源承载力、人均水资源生态赤字变化趋势相似,整体均呈上升趋势,但用国家公顷法得出的结果均大于用全球公顷法得出的同1年份的结果.(2)2种不同算法得出山西省2007—2018年万元GDP水资源生态足迹均呈下降趋势,说明12年间其水资源利用率在提高.(3)2种不同算法得出这12年间山西省水资源生态压力指数远>1,说明其水资源开发利用处于不安全状态.研究认为:(1)2种算法产生差异的主要原因在于采用的水资源均衡因子、水资源产量因子及区域水资源平均生产能力存在差异.国家公顷法比全球公顷法能更好地反映国家级以下空间尺度水资源开发利用态势.(2)需根据不同的研究目的,构建相应的计算模型进行水资源生态足迹的核算与分析,既有助于真实反映不同空间尺度上区域水资源开发利用态势,也有利于同级空间区域尺度上水资源生态足迹的比较.