Search Results (167)

Given that the Sunkoshi River watershed (located in the southern foot of the Himalayas) is sensitive to climate change and its mountain ecosystem provides important services, we aim to evaluate its spatial and temporal variation patterns of vegetation, represented by the Normalized Difference Vegetation Index (NDVI), during 2000–2021 and identify the dominant driving factors of vegetation change. Based on the NDVI dataset (MOD13A1), we used the simple linear trend model, seasonal and trend decomposition using loess (STL) method, and Mann–Kendall test to investigate the spatiotemporal variation features of NDVI during 2000–2021 on multiple scales (annual, seasonal, monthly). We used the partial correlation coefficient (PCC) to quantify the response of the NDVI to land surface temperature (LST), precipitation, humidity, and soil moisture. The results indicate that the annual NDVI in 52.6% of the study area (with elevation of 1–3 km) increased significantly, while 0.9% of the study area (due to urbanization) degraded significantly during 2000–2021. Daytime LST dominates NDVI changes on spring, summer, and winter scales, while precipitation, soil moisture, and nighttime LST are the primary impact factors on annual NDVI changes. After removing the influence of soil moisture, the contributions of climate factors to NDVI change are enhanced. Precipitation shows a 3-month lag effect and a 5-month cumulative effect on the NDVI; both daytime LST and soil moisture have a 4-month lag effect on the NDVI; and humidity exhibits a 2-month cumulative effect on the NDVI. Overall, the study area turned green during 2000–2021. The dominant driving factors of NDVI change may vary on different time scales. The findings will be beneficial for climate change impact assessment on the regional eco-environment, and for integrated watershed management. Full article

The DNDC-Rice model effectively simulates yield and greenhouse gas emissions within a paddy system, while its performance under upland conditions remains unclear. Using data from a long-term cover crop experiment (fallow [FA] vs. rye [RY]) in a soybean field, this study validated the DNDC-Rice model’s performance in simulating soil dynamics, crop growth, and C-N cycling processes in upland systems through various indicators, including soil temperature, water-filled pore space (WFPS), soybean biomass and yield, CO₂ and N₂O fluxes, and soil organic carbon (SOC). Based on simulated results, the underestimation of cumulative N₂O flux (25.6% in FA and 5.1% in RY) was attributed to both underestimated WFPS and the algorithm’s limitations in simulating N₂O emission pulses. Overestimated soybean growth increased respiration, leading to the overestimation of CO₂ flux. Although the model captured trends in SOC stock, the simulated annual values differed from observations (−9.9% to +10.1%), potentially due to sampling errors. These findings indicate that the DNDC-Rice model requires improvements in its N cycling algorithm and crop growth sub-models to improve predictions for upland systems. This study provides validation evidence for applying DNDC-Rice to upland systems and offers direction for improving model simulation in paddy-upland rotation systems, thereby enhancing its applicability in such contexts. Full article

To address thermal imbalance and ground temperature degradation in shallow geothermal heat pump (GSHP) systems in severely cold climates, this study analyzes a typical logistics building using an hourly dynamic load model. Multiyear simulations were conducted to investigate the coupling between building load variation and soil thermal response. The results indicate that with a cumulative heating load of 14.681 million kWh and cooling load of 6.3948 million kWh, annual heat extraction significantly exceeds heat rejection, causing ground temperature to decline by about 1 °C per year. Over five and ten years, the cumulative drops reached 2.65 °C and 4.71 °C, respectively, leading to a noticeable reduction in borehole heat exchanger performance and system COP. The study quantitatively evaluates ground temperature and heat exchange degradation, highlighting the key role of load imbalance. To mitigate long-term thermal deterioration, strategies such as load optimization, summer heat reinjection, and operational adjustments are proposed. The findings offer guidance for the design and sustainable operation of GSHP systems in cold regions. Full article

Based on ascending and descending orbit SAR data from 2017–2025, this study analyzes the long time-series deformation monitoring and slip pattern of an active-layer detachment thaw slump, a typical active-layer detachment thaw slump in the permafrost zone of the Qinghai-Tibetan Plateau, by using the small baseline subset InSAR (SBAS-InSAR) technique. In addition, a three-dimensional displacement deformation field was constructed with the help of ascending and descending orbit data fusion technology to reveal the transportation characteristics of the thaw slump. The results show that the thaw slump shows an overall trend of “south to north” movement, and that the cumulative surface deformation is mainly characterized by subsidence, with deformation ranging from −199.5 mm to 55.9 mm. The deformation shows significant spatial heterogeneity, with its magnitudes generally decreasing from the headwall area (southern part) towards the depositional toe (northern part). In addition, the multifactorial driving mechanism of the thaw slump was further explored by combining geological investigation and geotechnical tests. The analysis reveals that the thaw slump’s evolution is primarily driven by temperature, with precipitation acting as a conditional co-factor, its influence being modulated by the slump’s developmental stage and local soil properties. The active layer thickness constitutes the basic geological condition of instability, and its spatial heterogeneity contributes to differential settlement patterns. Freeze–thaw cycles affect the shear strength of soils in the permafrost zone through multiple pathways, and thus trigger the occurrence of thaw slumps. Unlike single sudden landslides in non-permafrost zones, thaw slump is a continuous development process that occurs until the ice content is obviously reduced or disappears in the lower part. This study systematically elucidates the spatiotemporal deformation patterns and driving mechanisms of an active-layer detachment thaw slump by integrating multi-temporal InSAR remote sensing with geological and geotechnical data, offering valuable insights for understanding and monitoring thaw-induced hazards in permafrost regions. Full article

Angelica biserrata (Shan et Yuan) Yuan et Shan (A. biserrata) roots, a widely distributed medicinal crop with intraspecific diversity, exhibits significant variability in coumarin content across habitats. This study integrated metabolomics and transcriptomics to dissect the spatial heterogeneity in metabolite profiles and gene expression, revealing the mechanisms driving coumarin biosynthesis divergence. By synthesizing climate-related big data with machine learning and Bayesian-optimized deep learning models, we identified key environmental drivers and predicted optimal cultivation conditions. The key findings were as follows: (1) differential regions most strongly influenced coumarin; (2) upstream genes (such as PAL-1, PAL-2, BGLU44, etc.) modulated downstream coumarin metabolites; (3) elevation (Elev) and warmest quarter temperature (Bio10) dominated coumarin variation, whereas May solar radiation (Srad5) and precipitation seasonality (Bio15) controlled transcriptomic reprogramming; (4) the optimized environment for bioactive compounds included mean annual temperature (Bio1) = 9.99 °C, annual precipitation (Bio12) = 1493 mm, Elev = 1728 m, cumulative solar radiation = 152,643 kJ·m⁻²·day⁻¹, and soil organic carbon = 11,883 g·kg⁻¹. This study aimed to clarify the biological characteristics and differential regulatory mechanisms of A. biserrata roots in different habitats, establish a theoretical framework for understanding the molecular mechanisms controlling metabolic changes under various habitats, and contribute to elucidating the formation of active constituents while facilitating their effective utilization. Full article

This study combines field experiments and numerical analysis using the HYDRUS model to investigate the impact of water table depths on evaporation processes in semi-arid regions with shallow groundwater. Two lysimeters with different water table depths were set up in the Ordos Basin, Northwest China, and instrumented with multi-depth soil moisture and temperature sensors. The experimental data were used to calibrate and validate numerical models that simulated both non-isothermal and isothermal flows. The results reveal that groundwater levels significantly influence the evaporation rate, dictating the position of the evaporation front and zero-flux plane. Isothermal models underestimated cumulative evaporation by 14.7% and 44.2% for the shallow and deep-water table lysimeters, respectively, while non-isothermal models produced more accurate results with 0.95% overestimation and 5.2% underestimation. The study demonstrates that incorporating both water and heat transport into numerical models enhances the accuracy of evaporation estimates under varying groundwater conditions. Furthermore, the findings show that when the evaporation front occurs near the surface, liquid water flux dominates, whereas water vapor flux plays a crucial role when the evaporation front is located below the surface. These results offer valuable insights for refining water management strategies and models in agricultural and ecological systems of semi-arid areas, underscoring the critical role of considering soil moisture and temperature dynamics, along with groundwater levels, in accurately quantifying evaporation for improved resource management. Full article

Urban green spaces are important components of city spaces that are vulnerable to degradation in soil–water–climate processes. This vulnerability is exacerbated by current climate change and park usage density. This study examines the dynamics of soil water repellency in the topsoils of selected urban parks in Berlin, aiming to assess the relationships between weather conditions, soil water content, and soil water repellency. This study is based on monthly sampled soils from spots originating from three selected parks—Fischtal Park, Stadtpark Steglitz, and Rudolph-Wilde Park—between September 2022 and October 2023; two of the parks are exclusively rainwater fed, and one is irrigated during summer months. For each sample soil, water repellency persistence and severity were analyzed. Time series analysis was conducted including soil water content. In addition, the total organic carbon content (TOC) and sample texture were analyzed. The results show that the rainfall amount, number of dry days, and maximum temperature during different time intervals prior to the sampling date predominantly control the variation in the soil water repellency via the soil water content. Soil water repellency variations observed appear more event-related than monthly or seasonal, as rainfall is evenly distributed through the years without a distinct dry or wet season in Berlin. The non-repellency of the soil samples was usually observed when the associated water content was increased, which is linked to high cumulative rainfall and short dry periods. Low rainfall amounts and long dry periods in summer result in the re-establishment of the soil water repellency, possibly affecting increased runoff generation and soil erosion risk. Spatially, the repellency properties were observed at locations under healthy vegetation cover, while soils located on the upper slope locations and on the pathways lacked repellency characteristics. Full article

Drip irrigation with plastic mulch is widely used to save water and improve fertilizer efficiency in arid regions in Xinjiang. However, farmers freely use irrigation water in pursuit of a high cotton yield, and the impact of different irrigation amounts on nitrous oxide (N₂O) emissions is still unclear. A field experiment was conducted in 2023 in Xinjiang, China, with drip-irrigated cotton (Gossypium hirsutum L.) to determine N₂O emissions with different irrigation intensities. The different irrigation treatments were designed as follows: irrigation was performed to maintain soil moisture at (1) an 80% field capacity (Q80); (2) 90% field capacity (Q90); and (3) 100% field capacity (Q100). The results showed that the yield of cotton decreased with the increase in irrigation intensity. A 100% field capacity is beneficial for ammonium and nitrate transformation. The N₂O emissions remained at a relatively low level during the non-irrigated fertilization period. In every irrigation and fertilization cycle, the N₂O emissions were mainly concentrated during the process from wet to dry. The peak occurred during days 1–3 of irrigation. Throughout the growth period, the cumulative N₂O emissions were 1.15, 1.48, and 2.63 kg N ha⁻¹ under the Q80, Q90, and Q100 treatments, respectively. As the irrigation intensity increased, the dominant species of soil bacteria and fungi showed substitution, while the dominant species of soil actinomycetes were not replaced. Fungi, actinomycetes, the available potassium, and the carbon to nitrogen ratio were positively correlated with nitrous oxide emissions, and the soil temperature was negatively correlated with nitrous oxide emissions. These results demonstrate that increased irrigation could increase the risk of greenhouse gas emissions when using plastic mulch with drip irrigation. Full article

Investigating the variation in and key factors influencing the yield of super hybrid rice cultivated at different altitudes but within the same latitude provides valuable insights for further improvements in super hybrid rice grain yields. Field and pot experiments were conducted using four rice varieties at the following two altitudinal locations in Sichuan Province, China: Hanyuan (high, 1000 m) and Luxian (low, 300 m). The results indicated that Hanyuan achieved an average grain yield of 13.89 t ha⁻¹ in paddy fields, with yields being from 63.6% to 94.2% higher than those at Luxian in the field experiments and from 10.8% to 68.0% higher in the pot experiments. The grain yield was consistently higher in the soil from Hanyuan compared to that from Luxian at the same sites. In the field experiments, the grain yield was influenced by location (L), plant density (P), and variety (V), but there were no significant interactions between these factors. In the pot experiments, the grain yield was significantly impacted by L, soil (S), and the interaction between L and S. Climatic factors, which varied with the altitude of the planting site, played a crucial role in achieving optimal yields of the super hybrid rice. Hanyuan exhibited more cumulative solar radiation with a longer growth duration and lower temperatures and higher soil fertility compared to Luxian. The higher grain yield observed at Hanyuan was linked to increases in panicle numbers, spikelets per panicle, grain filling, pre- and post-heading biomass production, and the harvest index. The variations in biomass production between Hanyuan and Luxian were largely due to differences in pre- and post-heading crop growth rates (CGRs) and pre-heading radiation use efficiency (RUE), which were influenced by differences in the maximum and minimum temperatures and cumulative solar radiation. This study indicated that the differences in the grain yield of super hybrid rice across various ecological sites are primarily influenced by altitude and soil fertility, and further enhancement of the grain yield can be achieved by concurrently increasing biomass production before and after heading through improvements in pre- and post-heading CGR. Full article

Droughts are a major driver of global environmental degradation, threatening lives and causing significant economic losses, with approximately 80% of these losses linked to agricultural drought, characterized by soil moisture deficits. Remote sensing technology offers high spatiotemporal resolution data for continuous monitoring of soil moisture and drought severity. However, the effectiveness of remote sensing drought indices across different soil depths remains unclear. This study assessed the performance of eight widely used drought indices—Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), Normalized Vegetation Supply Water Index (NVSWI), Temperature–Vegetation Dryness Index (TVDI), and Standardized Precipitation–Evapotranspiration Index (SPEI) at multiple timescales—in monitoring soil moisture at five depths (0–50 cm, at 10 cm intervals) across nine agricultural regions of China from 2001 to 2020. Results reveal that the monitoring performance of drought indices varies significantly across regions and soil depths, with a general decline in performance as soil depth increases. For soil depths between 10–40 cm, VCI and NVSWI exhibited the highest accuracy, while PDI, MPDI, and VHI performed optimally in the Northeast China Plain. At 50 cm depth, however, optical remote sensing indices struggled to accurately capture soil moisture conditions. Additionally, TCI and TVDI showed notable lag effects, with 4-month and 5-month delays, respectively, while SPEI exhibited cumulative effects over 3–6 months. These findings provide critical insights to guide the selection of appropriate drought indices for soil moisture monitoring, aiding agricultural drought management and decision-making. Full article

Understanding the dynamics of soil respiration (Rs) in response to freeze–thaw cycles is crucial due to permafrost degradation on the Qinghai–Tibet Plateau (QTP). We conducted continuous in situ observations of Rs using an Li-8150 automated soil CO₂ flux system, categorizing the freeze–thaw cycle into four stages: completely thawed (CT), autumn freeze–thaw (AFT), completely frozen (CF), and spring freeze–thaw (SFT). Our results revealed distinct differences in Rs magnitudes, diurnal patterns, and controlling factors across these stages, attributed to varying thermal regimes. The mean Rs values were as follows: 2.51 (1.10) μmol·m⁻²·s⁻¹ (CT), 0.37 (0.04) μmol·m⁻²·s⁻¹ (AFT), 0.19 (0.06) μmol·m⁻²·s⁻¹ (CF), and 0.68 (0.19) μmol·m⁻²·s⁻¹ (SFT). Cumulatively, the Rs contributions to annual totals were 89.32% (CT), 0.79% (AFT), 5.01% (CF), and 4.88% (SFT). Notably, the temperature sensitivity (Q10) value during SFT was 2.79 times greater than that in CT (4.63), underscoring the significance of CO₂ emissions during spring warming. Soil temperature was the primary driver of Rs in the CT stage, while soil moisture at 5 cm depth and solar radiation significantly influenced Rs during SFT. Our findings suggest that global warming will alter seasonal Rs patterns as freeze–thaw phases evolve, emphasizing the need to monitor CO₂ emissions from alpine meadow ecosystems during spring. Full article

High-intensity coal mining significantly impacts the surrounding soil moisture (SM) through water seepage, artificial watering for dust suppression, and geomorphological changes, which will lead to ecological degradation. This study explores the impact of open-pit mines on surface SM in an arid–semiarid open-pit mine area of China over the period from 2000 to 2021. Using the temperature vegetation dryness index (TVDI), derived from the Land Surface Temperature–Normalized Difference Vegetation Index (LST-NDVI) feature space, this paper proposes a method—the TVDI of climate factor separation (TVDI-CFS)—to disentangle the influence of climate factors. The approach employs the Geographically and Temporally Weighted Regression (GTWR) model to isolate the influence of temperature and precipitation, allowing for a precise quantification of mining-induced disturbances. Additional techniques, such as buffer analysis and the Dynamic Time Warping (DTW) algorithm, are used to examine spatiotemporal variations and identify disturbance years. The results indicate that mining impacts on surface SM vary spatially, with disturbance distances of 420–660 m and strong distance decay patterns. Mining expansion has increased disturbance ranges and intensified cumulative effects. Inter-annual TVDI trends from 2015 to 2021 reveal clustered disturbances in alignment with mining directions, with the largest affected area in 2016. These findings provide a systematic valuable insights for ecological restoration and sustainable environmental management in mining-affected areas. Full article

Nitrous oxide (N₂O) is a major greenhouse gas (GHG) responsible for global warming. Improper fertilization in agricultural fields, particularly excessive nitrogen (N) application, accelerates soil N₂O emissions. Though partial substitution with organic fertilizer has been implemented to mitigate these emissions, the effect on perennial systems, such as tea plantations, remains largely unexplored. Therefore, the present study monitored soil N₂O emissions for a year in a tea plantation in South China under the following treatments: no N fertilizer (control, CK), chemical fertilizer alone (CF), replacing 40% of chemical fertilizer with organic fertilizer (CF + OF), and organic fertilizer alone (OF). Our results showed that the annual cumulative N₂O emissions from the plantation soil ranged from 1.03 to 3.43 kg N₂O-N ha⁻¹. The cumulative N₂O emissions, the yield-scaled N₂O emissions (YSNE), and the N₂O-N emission factor (EF) from the soil were the highest under the CF + OF treatment but the lowest under the OF treatment. Further analysis revealed that fertilization, mainly chemical fertilization, increased the soil ammonium (NH₄⁺-N) and nitrate (NO₃⁻-N) levels by 182–387% and 195–258%, respectively, and tea yields by 120–170%. However, tea yield decreased gradually with increasing organic substitution. These results prove that complete organic substitution reduces soil N₂O emissions and tea yield and suggest adopting an appropriate substitution rate for optimal effect. Further random forest (RF) modeling identified water-filled pore space (WFPS; 20.27% of total variation), soil temperature (Tsoil; 19.29%), and NH₄⁺-N (18.27%) as the key factors significantly contributing to the changes in soil N₂O flux. These findings provide a theoretical foundation for optimizing fertilization regimes for sustainable tea production and soil N₂O mitigation. Full article

Despite the continuous development of greenhouse cultivation technology, the influence mechanism of covering conditions on the root distribution of greenhouse crops remains unclear, which is emerging as a significant research topic at present. The interaction between mulching and irrigation plays a key role in the root growth of greenhouse tomatoes, but its specific impact awaits in-depth exploration. To explore the response patterns of greenhouse crop root distribution to the drip irrigation water amount under mulching conditions, the tomato was chosen as the research object. Three experimental treatments were set up: mulched high water (Y0.9), non-mulched high water (N0.9), and mulched low water (Y0.5) (where 0.9 and 0.5 represent the cumulative evaporation from a 20 cm standard evaporation pan). We analyzed the water and thermal zone of tomato roots as well as the root distribution. Based on this, a root distribution model was constructed by introducing a mulching factor (f_m) and a water stress factor (K_s). After carrying out two years of experimental research, the following results were drawn: (1) The average soil water content in the 0–60 cm soil layer was Y0.9 > N0.9 > Y0.5, and the average soil temperature in the 0–30 cm soil layer was Y0.5 > Y0.9 > N0.9. (2) The interaction between mulching and irrigation had a significant impact on the distribution of tomato roots. In the absence of mulch, the root surface area, average root diameter, root volume, and root length density initially increased and then decreased with depth, with the maximum root distribution concentrated around the 20 cm soil layer. Under mulched conditions, roots were predominantly located in the top layer (0–20 cm). Under the film mulching condition, the distribution range of root length density of low water (Y0.5) was wider than that of high water (Y0.9). (3) Root length density exhibited a significant cubic polynomial relationship with both the soil water content and soil temperature. In the N0.9 treatment, root length density had a bivariate cubic polynomial relationship with soil water and temperature, with a coefficient of determination (R²) of 0.97 and a normalized root mean square error (NRMSE) of 20%. (4) When introducing the film mulching factor (f_m) and water stress factor (K_s) into the root distribution model to simulate the root length density distribution of Y0.9 and Y0.5, it was found that the NRMSE was 22% and R² was 0.90 under the Y0.9 treatment, and the NRMSE was 24% and R² was 0.98 under the Y0.5 treatment. This study provides theoretical support for the formulation of scientifically sound irrigation and mulching management plans for greenhouse tomatoes. Full article

Scarce water resources, high temperatures, limited rainfall, elevated soil salinity, and poor soil quality (98% sand) challenge crop production in the desert regions of the Middle East. Proso millet’s resilience under these stresses presents a potential solution for enhancing food security in arid environments. This field study evaluated 24 proso millet genotypes under three environments (100% freshwater, 50% freshwater, and 10 dS/m salinity) in the UAE during normal and summer seasons, aiming to identify genotypes resilient to water, heat, and salinity stresses and to assess genotype-by-environment (G × E) interactions and key traits associated with grain yield. ANOVA indicated significant G × E interactions. Genotypes G9 and G24 displayed high yield and stability across environments during the normal season. In the summer, genotypes G7 and G10 exhibited resilience with high yields under high-temperature stress alone, while combined stresses led to yield reductions across all genotypes, with greater susceptibility under cumulative stress. GGE biplot analysis identified G9 as ideal in the normal season, while G15 and G23 demonstrated stability under combined stresses in the summer season. High chaffy grain yield (CGY) observed under summer stress conditions suggests a shift in resource allocation away from productive grain formation. The reproductive phase was highly vulnerable to heat stress, with 88% of this period experiencing daytime temperatures exceeding 40 °C, with a peak reaching up to 49 °C. These extreme conditions, coinciding with the crop’s critical growth stages, triggered a significant increase in chaffy grain production, substantially reducing overall grain yield. Despite these challenges, genotypes G7, G10, and G12 exhibited notable resilience, maintaining yields above 0.75 t ha⁻¹. Correlation analysis suggested that selecting for increased plant height, forage yield, and 1000-grain weight (TGW) could enhance grain yield under the normal and summer conditions. This study highlights the potential of proso millet genotypes as climate-resilient options for arid regions, providing a basis for developing stress-tolerant varieties and promoting sustainable agriculture in desert climates. Full article