The morphology of sheep wool applied as organic fertilizer biodegraded in the soil was examined. The investigations were conducted in natural conditions for unwashed waste wool, which was rejected during sorting and then chopped into short segments and wool pellets. Different types of wool were mixed with soil and buried in experimental plots. The wool samples were periodically taken and analyzed for one year using Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray Spectroscopy (EDS). During examinations, the changes in the fibers' morphology were observed. It was stated that cut wool and pellet are mechanically damaged, which significantly accelerates wool biodegradation and quickly destroys the whole fiber structure. On the contrary, for undamaged fibers biodegradation occurs slowly, layer by layer, in a predictable sequence. This finding has practical implications for the use of wool as an organic fertilizer, suggesting that the method of preparation can influence its biodegradation rate. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(SEM)(sic)(sic)(sic)(sic)(sic)X(sic)(sic)(sic)(sic)(EDS)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity (Vs) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to Vs data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and Vs respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and Vs correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

Soil compaction caused by heavy agricultural machinery poses a significant challenge to sustainable farming by degrading soil health, reducing crop productivity, and disrupting environmental dynamics. Field traffic optimization can help abate compaction, yet conventional algorithms have mostly focused on minimizing route length while overlooking soil compaction dynamics in their cost function. This study introduces Soil2Cover, an approach that combines controlled traffic farming principles with the SoilFlex model to minimize soil compaction by optimizing machinery paths. Soil2Cover prioritizes the frequency of machinery passes over specific areas, while integrating soil mechanical properties to quantify compaction impacts. Results from tests on 1000 fields demonstrate that our approach achieves a reduction in route length of up to 4-6% while reducing the soil compaction on headlands by up to 30% in both single-crop and intercropping scenarios. The optimized routes improve crop yields whilst reducing operational costs, lowering fuel consumption and decreasing the overall environmental footprint of agricultural production. The implementation code will be released with the third version of Fields2Cover, an open-source library for the coverage path planning problem in agricultural settings.

Forest growth in tropical regions is regulated in part by climatic factors, such as precipitation and temperature, and by soil factors, such as nutrient availability and water storage capacity. We examined a decade of growth data from Eucalyptus clonal plantations from over 113,000 forest inventory plots across a 10 million-ha portion of Mato Grosso do Sul in southwestern Brazil. From this full dataset, three subsets were screened: 71,000 plots to characterize growth and yield across water table depth classes, 17,000 plots to build generalized models, and 50,000 plots for clone-based analyses. Average precipitation varied little across the region (1150 to 1270 mm yr(-1)), but water table depth ranged from less than 10 m to over 100 m. Where the water table was within 10 m of the surface, about 20 % of the total water used by trees came from this saturated zone. Water tables deeper than 50 m contributed very little to tree water use. Sites with a water table within 10 m averaged 47 m(3) ha(-1) yr(-1) in stem growth (mean annual increment, MAI) across a full rotation, compared to less than 37 m(3) ha(-1) yr(-1) for sites with water tables deeper than 50 m. Drought-induced canopy damage rose from 7 % to 30 % along the water tables depth gradient, while tree mortality rose nearly fourfold. The optimal stocking level was about 1360 trees ha(-1) where water tables were accessible, declining to 1080 trees ha(-1) where they were not. Among the 15 most planted Eucalyptus clones, increases in MAI from the lowest to highest water table depths ranged from + 4.8 to + 16.8 m(3) ha(-1) yr(-1) , reflecting significant genotype-environment interactions. On average, MAI decreased by 0.8 m(3) ha(-1) yr(-1) (ranging from 0.4 to 1.4) for every 10 m increase in water table depth. Similarly, the Site Index at base age 7 years declined from 31 m to 27 m, with an average reduction of 0.25 m per 10 m increase in water table depth. Physiographic modeling of water table depths offers useful information for forest management practices like forest inventory and planning, clonal allocation, optimized planting densities, fertilization strategies, coppice techniques, and other landscape-specific strategies like tree breeding zones.

This paper aims to investigate the tunnelling stability of underwater slurry pressure balance (SPB) shields and the formation and evolution mechanisms of ground collapse following face instability. A laboratory SPB shield machine was employed to simulate the entire tunnelling process. Multi-faceted monitoring revealed the responses of soil pressure, pore water pressure, and surface subsidence during both stable and unstable phases. The morphological evolution characteristics of surface collapse pits were analyzed using three-dimensional scanning technology. The experimental results indicate that: (1) The key to stable tunnelling is balancing the pressure in the slurry chamber with the tunnelling speed, which ensures the formation of a filter cake in front of the cutterhead. (2) The torque of the cutterhead, soil pressure, and surface subsidence respond significantly and synchronously when the tunnel face becomes unstable, while the soil and water pressures are relatively less noticeable. (3) Excavation disturbance results in a gentler angle of repose and a wider range of collapse in the longitudinal direction of the collapsed pit. (4) A formula for predicting the duration of collapse is proposed, which effectively integrates the evolution patterns of the collapse pit and has been well-validated through comparison with the experimental results. This study provides a reference for the safe construction of tunnel engineering in saturated sand.

文章以喀拉喀什河为例，解析1956—2023年天然径流及降水序列的演变特征，揭示径流突变与降水周期性规律。运用累计距平分析法、Mann-Kendall突变检验法和Morlet小波，对相关序列数据开展研究。研究结果表明：径流量呈现阶段性变化，2008年前后发生突变，Morlet小波分析降水序列在1988年前后存在4-6年显著周期；降水丰枯交替明显，但90年代后呈现整体偏湿趋势，1993年后丰水期频次增加。揭示了干旱区内陆河流域径流对气候变暖的响应机制，明确了降水周期的作用。通过多尺度方法集成与长序列数据挖掘，深化了对干旱区内陆河流域水文过程复杂性的认识，为同类区域水资源可持续管理提供了可推广的技术路径与决策依据。

文章以喀拉喀什河为例，解析1956—2023年天然径流及降水序列的演变特征，揭示径流突变与降水周期性规律。运用累计距平分析法、Mann-Kendall突变检验法和Morlet小波，对相关序列数据开展研究。研究结果表明：径流量呈现阶段性变化，2008年前后发生突变，Morlet小波分析降水序列在1988年前后存在4-6年显著周期；降水丰枯交替明显，但90年代后呈现整体偏湿趋势，1993年后丰水期频次增加。揭示了干旱区内陆河流域径流对气候变暖的响应机制，明确了降水周期的作用。通过多尺度方法集成与长序列数据挖掘，深化了对干旱区内陆河流域水文过程复杂性的认识，为同类区域水资源可持续管理提供了可推广的技术路径与决策依据。

文章以喀拉喀什河为例，解析1956—2023年天然径流及降水序列的演变特征，揭示径流突变与降水周期性规律。运用累计距平分析法、Mann-Kendall突变检验法和Morlet小波，对相关序列数据开展研究。研究结果表明：径流量呈现阶段性变化，2008年前后发生突变，Morlet小波分析降水序列在1988年前后存在4-6年显著周期；降水丰枯交替明显，但90年代后呈现整体偏湿趋势，1993年后丰水期频次增加。揭示了干旱区内陆河流域径流对气候变暖的响应机制，明确了降水周期的作用。通过多尺度方法集成与长序列数据挖掘，深化了对干旱区内陆河流域水文过程复杂性的认识，为同类区域水资源可持续管理提供了可推广的技术路径与决策依据。

The wheat powdery mildew (WPM) is one of the most severe crop diseases worldwide, affecting wheat growth and causing yield losses. The WPM was a bottom-up disease that caused the loss of cell integrity, leaf wilting, and canopy structure damage with these symptoms altering the crop's functional traits (CFT) and canopy spectra. The unmanned aerial vehicle (UAV)-based hyperspectral analysis became a mainstream method for WPM detection. However, the CFT changes experienced by infected wheats, the relationship between CFT and canopy spectra, and their role in WPM detection remained unclear, which might blur the understanding for the WPM infection. Therefore, this study aimed to propose a new method that considered the role of CFT for detecting WPM and estimating disease severity. The UAV hyperspectral data used in this study were collected from the Plant Protection Institute's research demonstration base, Xinxiang city, China, covering a broad range of WPM severity (0-85 %) from 2022 to 2024. The potential of eight CFT [leaf structure parameter (N), leaf area index (LAI), chlorophyll a + b content (Cab), carotenoids (Car), Car/Cab, anthocyanins (Ant), canopy chlorophyll content (CCC) and average leaf angle (Deg)] obtained from a hybrid method combining a radiative transfer model and random forest (RF) and fifty-five narrow-band hyperspectral indices (NHI) was explored in WPM detection. Results indicated that N, Cab, Ant, Car, LAI, and CCC showed a decreasing trend with increasing disease severity, while Deg and Car/Cab exhibited the opposite pattern. There were marked differences between healthy samples and the two higher infection levels (moderate and severe infection) for Cab, Car, LAI, Deg, CCC, and Car/Cab. N and Ant only showed significant differences between the healthy samples and the highest infection level (severe infection). As Cab, Car, and Ant decreased, the spectral reflectance in the visible light region increased. The decrease in N and LAI was accompanied by a reduction in reflectance across the entire spectral range and the near-infrared area, which was exactly the opposite of Deg. The introduction of CFT greatly improved the accuracy of the WPM severity estimation model with R2 of 0.92. Features related to photosynthesis, pigment content, and canopy structure played a decisive role in estimating WPM severity. Also, results found that the feature importance showed a remarkable interchange as increasing disease levels. Using features that described canopy structure changes, such as optimized soil adjusted vegetation index, LAI, visible atmospherically resistant indices, and CCC, the mild infection stage of this disease was most easily distinguished from healthy samples. In contrast, most severe impacts of WPM were best characterized by features related to photosynthesis (e.g., photochemical reflectance index 515) and pigment content (e.g., normalized phaeophytinization index). This study help deepen the understanding of symptoms and spectral responses caused by WPM infection.