Average Annual Precipitation Research Articles

Determination of Climatic Changes in Düzce Province Using Three Different Climate Classification Methods

Aim of this study is to determine the climate characteristics of Düzce province referring to different climate classification systems. The study was carried out in Düzce province. Climate characteristics and climatic changes were analyzed by using De Martonne, Köppen, and Thornthwaite classification methods. The study utilized 60 years of precipitation and temperature data recorded by the General Directorate of Meteorology. Data analyses were conducted within five-year intervals. According to the results, the average annual temperature of Düzce province has been on the rise since 1994, and the average precipitation data for the last 10 years exceeded the 60-year average. In the simple linear regression analysis, it was determined that there was an increase in both average temperature and annual average total precipitation values. According to De Martonne climate classification, the province lies within the semi-humid climate class. Examining the data of the last 10 years, it was determined to be within the Cfak (Hot summer, cool winters, subtropical humid climate) climate class according to the Köppen-Trewartha climate classification and within the B1rB2'b4' (Humid, second-degree mesothermal region with almost no water deficit, and under the influence of oceanic climate) climate class according to the Thornthwaite climate classification. For Düzce province, both the change in climate types according to Köppen-Trewartha and Thorntwaite classifications and the changes in temperature and precipitation data in recent years may indicate climate change.

Landslide Susceptibility Assessment Based on Multisource Remote Sensing Considering Inventory Quality and Modeling

The completeness of landslide inventories and the selection of evaluation models significantly impact the accuracy of landslide susceptibility assessments. Conventional field geological survey methods and single remote-sensing technology struggle to reliably identify landslides under complex environmental conditions. Moreover, prevalent landslide susceptibility evaluation models are often plagued by issues such as subjectivity and overfitting. Therefore, we investigated the uncertainty in susceptibility modeling from the aspects of landslide inventory quality and model selection. The study focused on Luquan County in Yunnan Province, China. Leveraging multisource remote-sensing technologies, particularly emphasizing optical remote sensing and InSAR time-series deformation detection, the existing historical landslide inventory was refined and updated. This updated inventory was subsequently used to serve as samples. Nine evaluation indicators, encompassing factors such as distance to faults and tributaries, lithology, distance to roads, elevation, slope, terrain undulation, distance to the main streams, and average annual precipitation, were selected on the basis of the collation and organization of regional geological data. The information value and two coupled machine-learning models were formulated to evaluate landslide susceptibility. The evaluation results indicate that the two coupled models are more appropriate for susceptibility modeling than the single information value (IV) model, with the random forest model optimized by genetic algorithm in Group I2 exhibiting higher predictive accuracy (AUC = 0.796). Furthermore, comparative evaluation results reveal that, under equivalent model conditions, the incorporation of a remote-sensing landslide inventory significantly enhances the accuracy of landslide susceptibility assessment results. This study not only investigates the impact of landslide inventories and models on susceptibility outcomes but also validates the feasibility and scientific validity of employing multisource remote-sensing technologies in landslide susceptibility assessment.

Discrepancies in precipitation changes over the Southwest River Basin of China based on ISIMIP3b

Selecting appropriate global climate models (GCMs) is crucial for minimizing uncertainty in regional climate projections under future scenarios. Previous studies have predominantly assessed the modeling capability of GCMs for regional precipitation climatology and its long-term patterns based on annual and seasonal precipitation data. Building upon these, we primally evaluated the performance of five GCMs from phase 3b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) in simulating precipitation concentration and its variations in the Southwest River Basin (SWRB) of China using the precipitation concentration index (PCI). The results indicate that: (1) The 5 GCMs generally capture the spatial distribution of annual average precipitation in the SWRB but significantly overestimate its magnitude, with a maximum regional average deviation of 207.80 mm. Furthermore, all models tend to overestimate the overall drying trend in the SWRB and show limited capability in simulating interdecadal variations of annual precipitation. (2) While the 5 GCMs reasonably simulate the spatial distribution of annual average PCI in the SWRB, they tend to overestimate its values, with a maximum regional average deviation of 1.54. Additionally, their simulation performance in capturing PCI trends and interdecadal variations is also limited. (3) The 5 GCMs tend to overestimate seasonal precipitation in the SWRB, with the best simulation performance for the distribution of autumn precipitation, followed by spring and summer, and the poorest for winter. Significant differences exist in the simulation performance of the models for seasonal precipitation proportions, which result in discrepancies in the models’ representation of PCI. Moreover, the models’ poor simulation performance of PCI trends is partly due to their inadequate modeling of trends in seasonal precipitation proportions. The findings will contribute to laying the foundation for meteorological hydrological research and water resource management in the SWRB.

Assessment of urbanization‐related groundwater flooding process via Visual MODFLOW modeling: A case study for the northern part of Almaty city, Kazakhstan

AbstractGroundwater flooding might be triggered by disregarding hydrogeological processes during urban area development. Such flooding might result in public disruption, engineering infrastructure destruction, and general damage to natural and human environments, as in the northern part of Almaty city. A MODFLOW groundwater flow model was used to simulate and quantitatively assess the changes in hydrogeological conditions affecting the groundwater flooding process. A field study of the Akbulak micro‐district research site showed that groundwater flooding occurred in its center owing to a water table hillock with a total area of 0.07 km2 and groundwater levels ranging from 1.2 to 0.25 m below the ground surface. The MODFLOW simulation suggested that this water table hillock developed from runoff, which, owing to a decrease in natural infiltration across an urbanized area, accumulated in low‐elevation areas and infiltrated. This runoff accumulation effect may be up to eight times the annual average precipitation amount. Once in local sub‐basins, larger runoff volume infiltrates into an underlying aquifer water table that is already high, might cause groundwater flooding in populated areas. The Almaty scenario simulation confirmed the field observations, suggesting that the clogging of the Karasu‐type stream has concentrated runoff to low‐elevation areas and is the leading cause of flooding.

Long-term potato response to different irrigation scheduling methods using saline water in an arid environment

Crops’ water requirement is generally higher than the annual average precipitation in arid environments characterized by scarce freshwater resources. While using saline water for irrigation can help sustain agriculture in water-stressed regions, several challenges arises concerning productivity and soil salinization. However, adoption of efficient irrigation techniques such as drip irrigation, irrigation scheduling, and deficit irrigation can help optimize water productivity and mitigate salinity problems in irrigated agriculture. In southern Tunisia, potato is considered among the main cultivated horticultural crops due to its high economic value while it is considered as a crop sensitive to salinity. This crop (cv. Spunta) was the subject of long-term studies (2002–2020) conducted during the fall period in the arid region of Médenine. The crop response to full and deficit irrigation with saline water was assessed for several seasons under contrasting climatic conditions. Scheduling using the soil water balance (SWB) method consisted of the total and/or partial replacement of accumulated crop evapotranspiration (ETc), as derived from climatic data and crop coefficients. The impact of decreasing amounts of irrigation waters on crop yield and soil salinity with waters having a salinity ranging between 3 and 7 dS m−1 was evaluated. Results showed improvements in yield (30% to 37%) obtained with the SWB strategy under actual farming conditions, supporting the use of this strategy for irrigation. Appropriate scheduling also seems to be a key element in saving water (15%–22%) and in reducing risks of soil salinization. In the dry environment of southern Tunisia, optimum supply seems to correspond to a replacement of 100% to approximately 70%–80% of ETc. Applying such irrigation levels resulted in a lower salinity buildup in the root zone and higher crop water productivity. Natural salt leaching seems to be more effective under a more humid soil profile. Yield decreases and soil salinity increases almost linearly (r2 = 0.60) with decreasing irrigation water amounts. Future work should focus on the integration of management practices when using saline water. Investigating the relationship and interaction between irrigation amounts, cultivar, fertilizer supply, and salt leaching will help in resolving productivity and environmental issues.

Study on the Factors Affecting the Humus Horizon Thickness in the Black Soil Region of Liaoning Province, China

Understanding the spatial variability and driving mechanisms of humus horizon thickness (HHT) degradation is crucial for effective soil degradation prevention in black soil regions. The study compared ordinary kriging interpolation (OK), inverse distance weighted interpolation (IDW), and regression kriging interpolation (RK) using mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and relative RMSE to select the most accurate model. Environmental variables were then integrated to predict HHT characteristics. Results indicate that: (1) RK was superior to OK and IDW in characterizing HHT with the smallest ME (11.45), RMSE (14.98), MAE (11.45), and RRMSE (0.44). (2) The average annual temperature (0.29), precipitation (0.27), and digital elevation model (DEM) (0.21) were the primary factors influencing the spatial variability of HHT. (3) The HHT exhibited notable variability, with an increasing trend from the southeast towards the central and northern directions, being the thinnest in the southeast. It was thicker in the northeast and southwest regions, thicker but less dense along the southern Bohai coast, thicker yet sporadically distributed in the northwest (especially Chaoyang and Fuxin), and thick with aggregated distribution over a smaller area in the northeastern direction (e.g., Tieling). These findings provide a scientific basis for accurate soil management in Liaoning Province.

СТРУКТУРЫ ИСПОЛЬЗОВАНИЯ ПАХОТНЫХ ЗЕМЕЛЬ В ЛЕСОСТЕПНОЙ ЗОНЕ БАШКИРСКОГО ЗАУРАЛЬЯ СО ВТОРОЙ ПОЛОВИНЫ 20 ВЕКА

We analyzed modern use of arable lands of 1985 in forest-steppe zone of Post-Ural of the Republic of Bashkortostan. Climate is temperate continental. An average annual temperature is 1.6℃ and an average annual precipitation of 427.9 mm. The hottest month is July with an average temperature of 17.5 and the coldest month is January with an average temperature of -14.8℃. Modern agricultural lands usually are used as a hay (43%). Use can be caused with local cattle breeding as traditional horse breeding. Overgrowth captures by 25% of Pinus silvestris. Scot’s pine is growing better on dry lands because it captures more area of overgrowth.

Quantifying recharge mechanisms in low-hilly areas of a loess region: Implications for the quantity and quality of groundwater

Groundwater plays a crucial role in sustaining water supply and irrigation in arid regions with thick vadose zones; however, the recharge mechanisms and their impact on water quality remain contentious. For flood-irrigated areas, irrigation water amount is not well known to evaluate the effect of irrigation on the recharge. In this study, we employed multiple tracers to investigate recharge mechanisms in a low-hilly region with some flood-irrigated areas, where irrigation water recharge was estimated by the chloride mass balance method combined with the tritium peak method. Deep soil samples from irrigated lands in vadose zone and groundwater from unconfined aquifers were collected to determine the contents of the water isotopes (2H, 18O, and 3H), chlorides (Cl-), and nitrates (NO3−). The findings revealed unique tritium peaks preserved in the loess vadose zone, where the recharge rate under the non-irrigated site was estimated to be only 8.6 mm yr−1, 2.4 % of the average annual precipitation. According to the estimated irrigated recharge rates, irrigation water dominates the potential diffuse recharge in vadose zone. For the aquifer recharge, we then quantified diffuse recharge (62.2 ± 4.7 %, piston flow) and focused recharge (37.8 ± 4.7 %, preferential flow) via the line-conditioned excess (lc-excess) balance method. Focused recharge occurred in low depressions, where surface runoff carrying sediments with high solutes converged in large rainfall events during wet season. Subsequently, focused mode rapidly recharges groundwater with NO3− and Cl- elevated, deteriorating water quality of phreatic aquifer. Finally, we concluded focused recharge does not dominate aquifer recharge, but significantly affects groundwater quality. These findings underscore the implications for the sustainability of agricultural water and soil resources management, emphasizing the potential impacts of soil conservation on groundwater quality in low-hilly regions.

Characteristics and Indicative Significance of Groundwater Stable Isotopes in the Loess Plateau at the Regional Scale

Regional groundwater recharge is a critical scientific issue for sustainable groundwater resource development and management. However, spatial variations in groundwater recharge in the Loess Plateau （LP） remain poorly understood. To fill this knowledge gap, a systematic sampling campaign and stable isotope analysis were carried out for groundwater （shallow aquifer） in 13 major catchments during July 2019. The main objectives of this study were： ① to understandthe spatial distribution and influencing factors of stable isotopes in groundwater and ② to reveal the groundwater recharge sources and pathways and their spatial variations, combined with the precipitation stable isotope datasets. Stable isotopes in groundwater had poor spatial variations at the regional scale； however, they became isotopically depleted with the increase in annual average precipitation on the catchment scale （r = -0.87）. Compared with the stable isotope of precipitation, stable isotopes of groundwater were generally depleted and were similar to the precipitation of the rainy season （July-September）. These together indicated that there was pronounced seasonality of groundwater recharge, and the main recharge period was the rainy season. In particular, the recharge seasonality index （δP/G） was closely related to the catchment's average annual precipitation （r = -0.77） and leaf area index （r = -0.63）. In addition, groundwater lc-excess was generally negative, with the catchment-mean value ranging from -4.3‰ to -0.7‰. Hydrologically, this indicated that groundwater recharge pathways （ratio of matrix flow vs. preferential flow） were different among these catchments, which should be quantitatively determined by combining the saturated zone （groundwater） and the unsaturated zone （soil） in future work. Our findings can improve the understanding of groundwater recharge in LP and provide a scientific basis for sustainable management of groundwater resources at the regional scale.

Application of coupled WetSpass-M and MODFLOW models to estimate spatial–temporal water balance components in the Chemoga watershed, Ethiopia

ABSTRACT The groundwater level in the Chemoga watershed has been declining due to an increase in water demand, anthropogenic activities, and climate change effects. This paper uses the WetSpass-MODFLOW coupling to evaluate the groundwater recharge in the Chemoga watershed. The MODFLOW groundwater flow simulation model is then used to simulate the hydraulic head distribution based on these findings. The input data of WetSpass models are soil, land cover, topography, slope, and groundwater depth, as well as monthly meteorological characteristics (such as temperature, wind speed, and rainfall). The long-term spatial and temporal average annual precipitation of 1,453 mm is distributed as 169 mm (11.63%) groundwater recharge and 879 mm (60.5%) surface runoff, while 405 mm (27.87%) is lost through evapotranspiration. In such seasonal variations, the groundwater head due to the wet/summer stress period varied from 4 to 41 m. While in the dry/winter stress period groundwater head varied from 3.5 to 39.8 m, and also the groundwater head due to the annual stress period varied from 3.7 to 40 m. The findings are extensive and can be applied to water resource management and groundwater resource development in a sustainable manner by safeguarding high groundwater recharge locations, and reevaluating allowable groundwater abstraction rates.

Spatio-Temporal Distribution of Water Availability in Marshyangdi Basin: Hydrological Model Development

This Study has developed a hydrological model for the Marshyangdi river basin in Western Nepal, showing considerable potential for developing water resources and overall national prosperity. The model is also used to characterise hydrology and assess the availability of water resources across different spatial and temporal dimensions, hence improving our comprehension of water availability and its possible applications. The newly developed hydrological model in the Soil and Water Assessment Tool (SWAT) replicates the mean flows, hydrological pattern, and flow duration curve at the basin and 54 sub-basin outputs. Additionally, the model undergoes calibration and validation, employing Sufi-2 to fine-tune hydrological parameters. Based on the data generated by the model, the annual average precipitation (P) in the Marshyangdi basin is projected to be 1843 mm. Approximately 17.88% of the average yearly rainfall is lost via evapotranspiration; however, this varies significantly across different locations and time periods. Contrasting the two, the mountains have a higher moisture level than the Himalayan regions. The predicted average annual flow volume at the basin outflow is 9467.423 million cubic metres (MCM). Examining water shortages, finding regions with excess water, and developing solutions to address the competing needs of agriculture, industry, urban areas, and ecosystems are advantageous. Therefore, this method may improve the effectiveness of strategic planning and the long-term management of water resources.

Long‐term trends in mountain groundwater levels across Canada and the United States

AbstractMountains have a critical role in freshwater supply for downstream populations. As the climate changes, groundwater stored in mountains may help buffer the impacts to declining water resources caused by decreased snowpack and glacier recession. However, given the scarcity of groundwater observation wells in mountain regions, it remains unclear how mountain groundwater is being impacted by climate change across ecoregions. This study quantifies temporal trends in mountain groundwater levels and explores how various climatic, physiographic and anthropogenic factors affect these trends. We compiled data from 171 public groundwater observation wells within mountain regions across Canada and the United States, for which at least 20 years of monthly data is available. The Mann‐Kendall test for monotonic trend revealed that 54% of these wells have statistically significant temporal trends (p < 0.05) over the period of record, of which 69% were negative and therefore indicating overall declining groundwater storage. Wells in the western mountain ranges showed stronger trends (both positive and negative) than the eastern mountain ranges, and higher elevation wells showed fewer negative trends than the low elevation (<400 m asl) wells (p < 0.05). Correlation, Kruskal‐Wallis tests, stepwise multiple linear regression and random forest regression were used to identify factors controlling groundwater trends. Statistical analysis revealed that lower‐elevation mountain regions with higher average annual temperatures and lower average annual precipitation have the greatest declines in groundwater storage under climate change. Trends in temperature and precipitation, and ecoregion were also important predictors on groundwater level trends, highlighting geographic differences in how mountain wells are responding to climate change. Furthermore, sedimentary bedrock aquifers showed markedly more negative trends than crystalline bedrock aquifers. The findings demonstrate that the impact of climate change on mountain water resources extends to the subsurface, with important implications for global water resources.

Influence of Neltuma flexuosa and rainfall event on the germination of Leptochloa crinita and Pappophorum caespitosum in two different locations along a stress gradient in the central Monte desert

AbstractIn drylands, grass germination occurs after a large rainfall event. However, trees influence the water requirements for germination either by decreasing the rate of evaporation from soil surface or by interception rainfall with their canopy. The aim of this work was to evaluate the role of Neltuma flexuosa tree on the germination of Leptochloa crinita and Pappophorum caespitosum grasses in response to precipitation events of different sizes. The experiment was conducted in two locations within the Monte desert, Argentina: a semi‐arid location with an average annual precipitation of 345 mm and an arid location with an average annual precipitation of 156 mm. Six microsites were established under N. flexuosa canopies and six microsites in open areas at both locations. Within each microsite, 35 seeds of each grass species were exposed to precipitation events of varying sizes. This procedure was repeated 14 times across two growing seasons. Germinated seeds were counted in the laboratory. Generalized linear mixed models were then applied to evaluate the effects of accumulated precipitation and the microsite on the grass germination in both locations. Results showed that N. flexuosa did not influence the germination of either grass species in the arid location. However, in the semi‐arid location, N. flexuosa facilitated the germination of P. caespitosum only. Large precipitation events would act as an environmental signal for these perennial grasses, allowing them to germinate in favorable years regardless of the microsite or the location.

The Fremont Frontier: Living at the Margins of Maize Farming

Abstract The Fremont provide an important case study to examine the resilience of ancient farmers to climatic downturns, because they lived at the far northern margin of intensive maize agriculture in the American West, where the constraints on maize production are made abundantly clear. Using a tree-ring and simulation-based reconstruction of average annual precipitation and maize growing degree days, along with cost-distance to perennial streams, we model spatial variability in Fremont site density in the eastern Great Basin. The results of our analysis have implications for defining the ecological envelope in which farming is a viable strategy across this arid region and can be used to predict where and why maize farming strategies might evolve and eventually collapse as climate changes over time.

Chemotaxonomic variation of volatile components in Zanthoxylum Bungeanum peel and effects of climate on volatile components

BackgroundZanthoxylum bungeanum Maxim. is widely distributed across China, and the aroma of its peel is primarily determined by its volatile components. In this study, we analyzed the characteristics of volatile components in Z. bungeanum peels from different regions and investigated their correlation with climatic factors.ResultsThe results identified 126 compounds in Z. bungeanum, with 27 compounds exhibiting distinct odor characteristics. Linalool was the most abundant, with an average relative content of 21.664%. The volatile oil of Z. bungeanum predominantly features spicy, floral, citrus, and mint aromas. The classification results indicated a significant difference in elevation at the ZB10 collection points in Shaanxi Province compared to other groups. Temperature, average annual precipitation, and wind speed were crucial factors influencing the accumulation of volatile components.ConclusionsThis study is beneficial for enhancing the quality of Z. bungeanum, expanding the understanding of how climatic factors influence the accumulation of volatile substances, and promoting agricultural practices in regions with similar climatic conditions.

Integrating niche and occupancy models to infer the distribution of an endemic fossorial snake (Atractus lasallei).

Understanding species distribution and habitat preferences is crucial for effective conservation strategies. However, the lack of information about population responses to environmental change at different scales hinders effective conservation measures. In this study, we estimate the potential and realized distribution of Atractus lasallei, a semi-fossorial snake endemic to the northwestern region of Colombia. We modelled the potential distribution of A. lasallei based on ecological niche theory (using maxent), and habitat use was characterized while accounting for imperfect detection using a single-season occupancy model. Our results suggest that A. lasallei selects areas characterized by slopes below 10°, with high average annual precipitation (>2500mm/year) and herbaceous and shrubby vegetation. Its potential distribution encompasses the northern Central Cordillera and two smaller centers along the Western Cordillera, but its habitat is heavily fragmented within this potential distribution. When the two models are combined, the species' realized distribution sums up to 935 km2, highlighting its vulnerability. We recommend approaches that focus on variability at different spatio-temporal scales to better comprehend the variables that affect species' ranges and identify threats to vulnerable species. Prompt actions are needed to protect herbaceous and shrub vegetation in this region, highly demanded for agriculture and cattle grazing.

Effect of Water Tank Size and Supply on Greenhouse-Grown Kidney Beans Irrigated by Rainwater in Cold and Arid Regions of North China

In response to water scarcity in the Bashang area of northwest Hebei Province, a cold and arid region in north China, and to address the diminishing groundwater levels caused by pumping irrigation, this study investigated the impact of rainwater tank size and water supply on kidney beans production in greenhouses under various precipitation scenarios to determine the production potential and development strategies for regional precipitation resources. Under the background of average annual precipitation, kidney bean yield increased with increasing reservoir volume and shorter irrigation cycles. Under a 4-day irrigation cycle, the water demand satisfaction rate of kidney beans reached 100% water demand when the rainwater tank size was 15.7 m3. Against the wide variation in multi-year regional precipitation from 1992 to 2023, the annual effect of rainwater harvest was simulated using precipitation data collected 20 years with an 80% precipitation guarantee rate. The average minimum yield reduction rate obtained was 9.4%, and the corresponding minimum rainwater tank size was 29.5 m3. By superimposing the rainwater harvested in the shed and nonshed areas, the volume of the reservoir without yield reduction could be reduced to 20.0 m3. The sum of discharged and inventory water was much greater than the water scarcity in each water supply situation. Simulating and analyzing the effect of the relationship between rainwater tank size and water supply on rainwater harvesting in regional farmland by year provides important data affecting the construction of regional rainwater storage facilities and water supply efficiency. To achieve a high, stable yield of kidney beans grown in a greenhouse with shed film and shed area rainwater harvesting in north China, 2.6 m3 supplementary groundwater irrigation is still needed during the annual growing season.

Differences in growth and survival of two varieties of Ochroma pyramidale in rustic plantations in southern Mexico

Ochroma pyramidale (Cav. Ex Lam.) is a rapidly growing pioneer tree native to the Americas. This species is important for rehabilitating degraded areas as well as commercially due to the wood`s low density and high resistance, making it useful for producing structural cores and lightweight plywood, as well as in the wind energy industry. For at least 50 years, two varieties of this species have been recognized by botanists as well as the Lacandon people of Chiapas, Mexico. This study provides comparative data regarding three years of growth of the white and red varieties of Ochroma pyramidale, indicating ideal soil and climatic conditions for commercial plantations. The white variety had a greater rate of growth and thrives with a high average annual precipitation (2330–3236 mm) and Luvisol or Leptosol with a neutral pH and a high P content. The red variety appears to be the most widely used in other regions of the world, while the white variety is rarely used commercially.

Changes in Soil Organic Carbon Density and Its Response to Climate Change and Human Activities Before and After the Grain for Green Project on the Loess Plateau

Accurately assessing the changes in soil organic carbon storage （SOCS） before and after the Grain for Green Project （GFG） in the Loess Plateau （LP） and exploring the relationship between its spatial and temporal distribution and the influencing factors were important references for the development of regional recycling as well as the formulation of ecological protection policies. Based on the data of climate, human activities, and SOCD in the surface （0-20 cm） and deep （0-100 cm） soil before and after GFG in the LP from 2001 to 2020, we investigated the changes in SOCD at different spatial and temporal scales by using the methods of trend analysis, the kriging method, and variance partitioning analysis. The results showed that： ① Before and after the GFG, the surface SOCS of the whole region increased by 8 338.7×104 t； the deep SOCS increased by 1 160.02×104 t. ② In each bioclimatic subregion, the whole-region average SOCD of Ⅰ （Semi-Humid Forest Region）, Ⅱ （Semi-Humid Semi-Arid Forest and Grassland Region）, and Ⅲ （Semi-Arid Typical Grassland Region） showed a significant increasing trend, with a decreasing trend in Ⅳ （arid semi-arid desert grassland area） and Ⅴ （arid desert area）. ③ The average surface SOCS increase in different ecosystems was ranked as follows： cropland > grassland > woodland > shrubs > bare land and sparse vegetation. The deep soil increase was ranked as follows： grassland > cropland > woodland > shrubs > bare land and sparse vegetation. ④ Climate factors were the most important driving factors for changes in SOCD； the annual average temperature and precipitation were significantly positively correlated with changes in SOCD. The results of the study could provide data support for regional ecological management and land use policy formulation to promote high quality development of the ecological environment in the LP.

Using eddy covariance observations to determine the carbon sequestration characteristics of subalpine forests in the Qinghai–Tibet Plateau

Abstract. Subalpine forests are a crucial component of the carbon cycling system in the Qinghai–Tibet Plateau (QTP). However, there are currently significant data gaps in the QTP, and it is essential to enhance continuous monitoring of forest carbon absorption processes in the future. This study investigates 2 years' carbon exchange dynamics of a subalpine forest on the QTP using an eddy covariance method. We first characterized the seasonal carbon dynamics of the subalpine forest, revealing the higher carbon dioxide (CO2) exchange rates in summer and autumn and lower rates in winter and spring, and found that autumn is the peak period for carbon sequestration in this subalpine forest, with the maximum measured value of CO2 absorption reaching 10.70 µmol m−2 s−1. Subsequently, we examined the environmental factors influencing the carbon sequestration function. Principal component analysis (PCA) shows that photosynthetically active radiation (PAR) was the major environmental factor driving the net ecosystem exchange (NEE) of CO2, significantly influencing forest carbon absorption, and the increase in relative humidity decreases the rate of carbon fixation. In addition, we explored NEE and its influencing factors at the regional scale and found that air temperature promotes carbon dioxide absorption (negative NEE values), while the average annual precipitation shows a minor effect on NEE. At the annual scale, the subalpine forest functions as a strong carbon sink, with an average NEE of −332 to −351 g C m−2 (from November 2020 to October 2022). Despite the challenges of climate change, forests remain robust carbon sinks with the highest carbon sequestration capacity in the QTP, with an average annual CO2 absorption rate of 368 g C m−2. This study provides valuable insights into the carbon cycling mechanism in subalpine ecosystems and the global carbon balance.