Agricultural and Forest Meteorology最新文献

{"title":"Bedrock controls vegetation resilience: Dominant role of lithology in the 2022 southern China drought","authors":"Qian Li ,&nbsp;Yuemin Yue ,&nbsp;Lu Wang ,&nbsp;Xiangkun Qi ,&nbsp;Kelin Wang","doi":"10.1016/j.agrformet.2025.110991","DOIUrl":"10.1016/j.agrformet.2025.110991","url":null,"abstract":"<div><div>Although previous studies have shown that bedrock composition regulates vegetation drought vulnerability, the variability in the response and recovery mechanisms of vegetation under different lithologic contexts remain unclear. Based on the record-breaking extreme drought that occurred in Southwest China in 2022, this study integrated multi-source remote sensing data to systematically assess productivity loss, vegetation recovery time, and their main controlling factors across karst regions (dolomite and limestone) and non-karst regions (clastic rocks). The results showed that vegetation in dolomite areas experienced the most severe productivity loss, maximum GPP (Gross Primary Productivity) loss of shrubland reached 494 kg C/m², 2.57 times higher than that in clastic rock regions, and the average recovery time after drought reached 5.08 months, 1.60 times longer than in clastic regions. Importance analysis indicated that WUE (Water Use Efficiency) was the key factor affecting vegetation recovery in dolomite and limestone regions, with importance values of 0.76 and 0.35, respectively; whereas, temperature was the dominant factor in clastic rocks region (importance value = 0.85). Although vegetation in limestone areas recovered slightly faster than in dolomite, it was still limited by weak WUE. Coupled analysis of WUE and SSM (Surface Soil Moisture) revealed that WUE decreases with greater water availability in limestone and dolomite areas but increases in clastic regions, reflecting a higher water-use responsiveness of vegetation on clastic bedrock. This indicates that the limited soil water-holding capacity in karst regions restricts the potential for efficient water use under high-moisture conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110991"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying forest structural attributes and aboveground carbon dynamics with terrestrial laser scanning in a temperate deciduous forest","authors":"Shilin Chen ,&nbsp;Hans Verbeeck ,&nbsp;Louise Terryn ,&nbsp;Wout Cherlet ,&nbsp;Chang Liu ,&nbsp;Mathias Disney ,&nbsp;Yadvinder Malhi ,&nbsp;Niall Origo ,&nbsp;Joanne Nightingale ,&nbsp;Kim Calders","doi":"10.1016/j.agrformet.2025.110995","DOIUrl":"10.1016/j.agrformet.2025.110995","url":null,"abstract":"<div><div>Quantifying forest structure and aboveground biomass carbon (AGBC) dynamics over time is crucial for evaluating climate change impact on carbon stocks, and providing key insights into changes in the terrestrial carbon cycle. To date, the use of multi-temporal terrestrial laser scanning (TLS) to detect temporal dynamics of forest structure and AGBC remains largely unexplored. In this study, we demonstrate the use of bi-temporal TLS data to quantify fine-scale dynamics of forest structure and AGBC. A total of 831 live trees were extracted and manually aligned from two leaf-off datasets collected in a 1.4 ha area of temperate woodland (Wytham Woods, UK) in 2016 and 2022. Results indicated that, at the individual tree level, most trees exhibited positive growth in structural attributes between 2016 and 2022, including diameter at breast height (DBH, 60.2 % of trees), tree height (H, 75.8 %), crown projection area (CPA, 64.7 %), crown volume (CV, 60.5 %), and aboveground volume (V, 50.5 %). At the plot level, all structural attributes also increased, including basal area (1.8 m²/ha, 4.8 % growth), H (128.9 m/ha, 1.4 %), CPA (411.9 m²/ha, 3.0 %), DBH (1.5 m/ha, 1.1 %), CV (181.7 m³/ha, 0.3 %), and V (7.9 m³/ha, 1.0 %). The total AGBC of the study area saw a net carbon gain of 0.4 Mg C/ha/year over the six-year period. Notably, trees with DBH greater than 60 cm contributed over 40 % of the total AGBC. Moreover, our results reveal that branch dynamics play a crucial role in AGBC dynamics, underscoring the added value of TLS for tracking AGBC changes over time.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110995"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling spatial and temporal characteristics of cooling effects of rice paddy expansion in Northeast China","authors":"Tong Yang ,&nbsp;Jinwei Dong ,&nbsp;Jie Wang ,&nbsp;Chao Zhang ,&nbsp;Wenqi Liu ,&nbsp;Yuting Zhou ,&nbsp;Geli Zhang ,&nbsp;Guosong Zhao","doi":"10.1016/j.agrformet.2025.110967","DOIUrl":"10.1016/j.agrformet.2025.110967","url":null,"abstract":"<div><div>Rice paddy expansion in Northeast China can affect land surface temperature (LST) through biophysical mechanisms. However, the temporal and spatial heterogeneity of the LST effects, the variations associated with the area proportions of rice paddy, and the underlying biophysical mechanisms remain poorly understood. In this study, we analyze the differences in LST (dLST), albedo (dAlbedo), and evapotranspiration (dET) between rice paddies and adjacent rainfed croplands using a pair-wise comparison approach. Our results show that the expansion of rice paddies potentially reduces daytime LST (−2.02 ± 1.03 °C) and albedo (−1.02 ± 1.07 %) while increases nighttime LST (0.76 ± 0.41 °C) and ET (0.03 ± 1.20 mm/8 days) in Northeast China during the growing season (May to September). The effects are more pronounced in spring than in summer and autumn. Spatially, Sanjiang Plain exhibits a daytime cooling effect in later months and a nighttime warming effect in earlier months than other regions. For every ten percent increase in the area proportion of rice paddies, daytime dLST decreases by 1.60 °C, nighttime dLST increases by 0.64 °C, and dAlbedo decreases by 1.40 %. Using a decomposed temperature metric approach, we confirmed that non-radiative mechanisms dominate the cooling effects during the growing season. These findings emphasize the need to consider spatial heterogeneity and biophysical mechanisms of land cover changes in model simulations, crop planting plans, and regional climate mitigation strategies.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110967"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intra-annual density fluctuations in Pinus massoniana across subtropical forests in China: Occurrence patterns and triggering factors","authors":"Qin He ,&nbsp;Paolo Cherubini ,&nbsp;J. Julio Camarero ,&nbsp;Xiaochun Wang ,&nbsp;Yuan Zhang ,&nbsp;Danyang Yuan ,&nbsp;Shuguang Liu ,&nbsp;Liangjun Zhu","doi":"10.1016/j.agrformet.2025.110990","DOIUrl":"10.1016/j.agrformet.2025.110990","url":null,"abstract":"<div><div>Intra-annual density fluctuations (IADFs) are wood cells formed in response to abnormal climatic events during the growing season. They are crucial for evaluating the relationship between extreme climatic events and radial growth, as well as for understanding wood quality. However, most existing research has focused on seasonally dry Mediterranean and semi-arid conifer forests, with limited studies conducted in other regions—particularly subtropical forests, where frequent and severe droughts constrain forest productivity and growth. Here, we investigated the occurrence patterns and triggering factors of IADFs in <em>Pinus massoniana</em> plantations along a climate gradient in southern China. We found that latewood IADFs (IADF-L) are the predominant type formed by <em>P. massoniana</em>, whereas earlywood IADFs (IADF-E) are relatively rare. The frequency of IADFs showed a clear spatial pattern, gradually increasing as climate conditions became warmer and wetter. IADF-L frequency was negatively correlated with elevation but positively correlated with tree-ring width. High precipitation in late summer and early autumn, as well as hot and dry conditions during summer, triggered the formation of IADF-Ls, while spring (May) droughts induced IADF-E. The inferred climatic drivers of IADFs were further confirmed by climate-growth relationships based on seasonal wood data and the VS-Lite tree-ring growth model. Our findings provide a valuable foundation for developing management strategies for drought-prone subtropical pine forests. For example, artificial rainfall or supplemental irrigation during summer-autumn dry spells could stimulate the formation of IADF-Ls, thereby enhancing forest growth and carbon sequestration capacity.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110990"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APAR is a better predictor than LUE of the stem growth differences found between Loblolly pine grown in the United State and Brazil","authors":"Lorena Oliveira Barbosa ,&nbsp;Otávio Camargo Campoe ,&nbsp;José Roberto Soares Scolforo ,&nbsp;Henrique Ferraço Scolforo ,&nbsp;Timothy J. Albaugh ,&nbsp;Rachel Cook ,&nbsp;Rafael Rubilar ,&nbsp;Juscelina Arcanjo Santos","doi":"10.1016/j.agrformet.2025.110964","DOIUrl":"10.1016/j.agrformet.2025.110964","url":null,"abstract":"<div><div><em>Pinus taeda</em> is a species native to southeastern regions of the United State (USA), but plantations with the highest productivity are found in the southern region of Brazil (BRA). The objective of our study was to determine the higher (Light Use Efficiency) LUE and absorbed photosynthetically active radiation (APAR) of <em>P. taeda</em> genotypes with different spacings in order to evaluate potential strategies that could increase the productivity of intensively managed stands in Brazil and the United States. The experiment was designed as a split-split-plot, and evaluations included 81 trees in BRA and 63 trees in the USA, two genotypes (clone C3 vs. open pollination (OP)) and two spacings (BRA – 2.4 × 6.8 m, 613 trees/ha; USA – 3.66 × 4.42 m, 618 trees/ha) and narrow spacing (BRA – 2.4 × 2.2 m, 1894 trees/ha; USA – 3.66 × 1.47 m, 1853 trees/ha). Individual tree calculations of LUE were made at both locations for each tree by dividing its current annual stem increment (WNPPi) by APAR estimated from MAESTRA, a process-based model. The parameterization of this model included the use of forest inventory data, meteorological data, crown characteristics (average crown radius, height, diameter, and leaf area), leaf area density distribution, leaf transmittance, and leaf and soil reflectance. Results showed that trees growing in Brazil had greater leaf area (32%) and stem biomass growth (5%) and absorbed more light (49%) than trees in the USA. The genotype C3 was more efficient than OP in light use at both locations. Narrow spacing resulted in higher LUE values (0,8 g MJ^-1). APAR explain 80% and 65% of WNPP in BRA and USA, respective. Our results suggest that LUE explained the growth differences between sites, genotypes, and spacings, while APAR provided a better differentiation of WNPP between the sites.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110964"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved gap-filling of eddy covariance CO2 fluxes using remote sensing and environmental variables via XGBoost","authors":"Simon De Cannière ,&nbsp;Sebastian Wieneke ,&nbsp;Thomas Servotte ,&nbsp;Adrià Descals ,&nbsp;Tim Verdonck ,&nbsp;Ivan Janssens","doi":"10.1016/j.agrformet.2025.110987","DOIUrl":"10.1016/j.agrformet.2025.110987","url":null,"abstract":"<div><div>Gap-filling of eddy covariance (EC) CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> flux data is critical for quantifying ecosystem carbon balances, yet traditional methods like Marginal Distribution Sampling (MDS) do not adequately represent sub-daily carbon fluxes and it fails to leverage vegetation dynamics, which is especially problematic for filling in gaps longer than one week. This study evaluates the potential of eXtreme Gradient Boosting (XGBoost), a machine learning approach, to improve gap-filling of net ecosystem exchange (NEE) and gross primary production (GPP) by integrating remote sensing (RS) data and environmental data, both from in-situ measurements and from the ERA5 reanalysis model over a temperate pine forest (ICOS site BE-Bra). We compare three XGBoost models: (1) in-situ (meteorological, soil moisture, and tower-based sun-induced chlorophyll fluorescence (SIF)), (2) large-scale (ERA5 and Sentinel-2-derived vegetation indices), and (3) hybrid (combining ERA5 and Sentinel-2-derived vegetation indices with in-situ radiation). The results show XGBoost outperforms MDS for NEE gap-filling in all of its scenarios, with minimal performance degradation for gaps up to 56 days. Soil moisture and SIF improved predictions during warm periods (Air Temperature <span><math><mo>&gt;</mo></math></span> 25° C), when these data were taken from in-situ sources. SHAP analysis revealed light-related drivers as dominant controls. During heatwaves, typically co-occurring with high-light conditions, soil water content became an important driver. Overall, the hybrid model achieved comparable model performance as the models with in-situ data, demonstrating the viability of satellite RS and reanalysis for operational gap-filling. However, in-situ irradiation turned out notably more useful compared to irradiation from a reanalysis. Our findings advocate for XGBoost as a robust tool to integrate multi-source data, advancing carbon flux quantification beyond traditional methods, espescially when it comes to modeling the sub-daily carbon fluxes, which is important when using EC data for evaluating remote sensing based carbon flux estimations.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110987"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climatic control on soil microbial methane uptake across forest biomes","authors":"Yongping Kou ,&nbsp;Manuel Delgado-Baquerizo ,&nbsp;Wenqiang Zhao ,&nbsp;Xiangzhen Li ,&nbsp;Yanhong Wu ,&nbsp;Xiaohu Wang ,&nbsp;Jiangtao Xiao ,&nbsp;Haijian Bing ,&nbsp;Qing Liu","doi":"10.1016/j.agrformet.2025.110942","DOIUrl":"10.1016/j.agrformet.2025.110942","url":null,"abstract":"<div><div>Soil microbial methane (CH₄) uptake is critical for mitigating global warming and is sensitive to climate change. However, how climatic changes regulate the capacity of forest soils to uptake CH₄ across environmental gradients remains largely unclear. Here, we investigated the distribution and key drivers of the CH₄ oxidation potential (MOP) across 26 forests along a latitudinal gradient of 4000 km with structural equation modeling and multiple regression. We found that climate was a fundamental driver of MOP, with soil MOP peaking in the subtropical zone and being the lowest in the temperate zone. Structural equation modeling provided evidence that soil MOP was directly driven by changes in the aridity index and indirectly by regulating plant biomass, followed by soil properties. We also found that the environmental context influenced MOP within particular biomes and vegetation types. For example, the cold temperate zone exhibited a significant positive correlation between soil copper content and MOP, suggesting copper as a key factor explaining the variation in soil MOP in this region, as the particulate methane monooxygenase that catalyzes the oxidation of CH₄ is a copper-bound membrane metalloenzyme. Within coniferous broad-leaved forests, soil manganese emerged as a significant predictor of soil MOP, because CH₄ oxidation could be coupled to the reduction of manganese oxides, highlighting its biome-specific role in ecosystem functioning. In addition, methanotrophic richness was most important for explaining soil MOP in coniferous forests due to the lower alpha diversity of methanotrophs observed here. Our study provides solid evidence that climate and local environmental conditions regulate CH₄ sinks in forest ecosystems, with implications for predicting terrestrial carbon cycling under global climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110942"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond surface fluxes: Observational and computational needs of multilayer canopy models – A walnut orchard test case","authors":"Gordon B. Bonan ,&nbsp;Sean P. Burns ,&nbsp;Edward G. Patton","doi":"10.1016/j.agrformet.2025.110960","DOIUrl":"10.1016/j.agrformet.2025.110960","url":null,"abstract":"<div><div>Land surface models simulate fluxes exchanged between the land and atmosphere in weather and climate models. The prevailing modeling paradigm uses a big-leaf canopy parameterization that is not vertically-resolved. Multilayer canopy models have received interest over the past several years as a means to improve surface fluxes and enable new science. We present results from a comparison of the Community Land Model (CLM) multilayer canopy model (CLM-ml v2) and observations of air temperature, specific humidity, wind speed, and fluxes (net radiation, sensible heat, latent heat, momentum) at multiple heights in and above a walnut orchard during the Canopy Horizontal Array Turbulence Study (CHATS). The dataset provides a benchmark with which to test multilayer models. Above-canopy sensible heat, latent heat, and momentum fluxes are well simulated under a range of atmospheric regimes spanning strongly unstable, weakly unstable, near-neutral, weakly stable, and strongly stable, as are vertical profiles of fluxes within the canopy. Vertical profiles of wind speed closely match the observations under all stability regimes. Vertical profiles of air temperature and specific humidity are well simulated except for strongly stable conditions, when the first-order turbulence closure cannot represent within-canopy non-local vertical mixing that would otherwise transport the cool air produced by radiative cooling of the upper canopy downward to the lower canopy. Our model–data comparison highlights the potential of multilayer models to simulate the surface air space. The multilayer canopy model is simpler and more consistent with theory than is the CLM big-leaf canopy model, and it modernizes the canopy physics for theoretical and computational advances compared with CLM’s outdated ad-hoc parameterizations. Nonetheless, our analysis points to further modeling needs and identifies observations central to model testing. Measurements of within-canopy micrometeorology and leaf gas exchange are needed in addition to above-canopy fluxes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110960"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of nonlinear surface energy partitioning on potential evapotranspiration: A machine learning study based on FLUXNET data","authors":"Weiqi Liu ,&nbsp;Shaoxiu Ma ,&nbsp;Haiyang Xi ,&nbsp;Linhao Liang ,&nbsp;Kun Feng ,&nbsp;Atsushi Tsunekawa","doi":"10.1016/j.agrformet.2025.111005","DOIUrl":"10.1016/j.agrformet.2025.111005","url":null,"abstract":"<div><div>Potential evapotranspiration (PET) is a key variable in drought occurrence and modeling. The no-water-limited Bowen ratio (β_NWL) is widely used to construct energy balance-based PET models by assuming that β_NWL does not vary with climate and vegetation conditions. However, we found that β_NWL varies significantly with climate as well as vegetation conditions based on global-wide observational flux data. Therefore, this study aims to investigate the dominant influence factors of β_NWL and to simulate the nonlinear relationship between β_NWL with environmental factors by leveraging flux observation globally and machine learning models. We then applied the nonlinear β_NWL to develop a PET model (<span><math><mrow><mi>P</mi><mi>E</mi><msub><mi>T</mi><msub><mi>β</mi><mrow><mi>N</mi><mi>W</mi><mi>L</mi><mo>−</mo><mi>R</mi><mi>F</mi></mrow></msub></msub></mrow></math></span>) and evaluated its performance under various conditions, comparing it against commonly used PET models. Our results showed that the gross primary productivity (GPP) had the most significant effect on β_NWL, with a relative importance of 31%. The <span><math><mrow><mi>P</mi><mi>E</mi><msub><mi>T</mi><msub><mi>β</mi><mrow><mi>N</mi><mi>W</mi><mi>L</mi><mo>−</mo><mi>R</mi><mi>F</mi></mrow></msub></msub></mrow></math></span> model significantly improved the accuracy of daily PET estimation (R² ≥ 0.93, TSS ≥ 0.96, RMSE ≤ 0.48 mm/day, -0.04 mm/day ≤ MB ≤ 0.06 mm/day) against observation. Moreover, we also found that the <span><math><mrow><mi>P</mi><mi>E</mi><msub><mi>T</mi><msub><mi>β</mi><mrow><mi>N</mi><mi>W</mi><mi>L</mi><mo>−</mo><mi>R</mi><mi>F</mi></mrow></msub></msub></mrow></math></span> model can effectively reduce the uncertainty (overestimation or underestimation) of PET estimation by commonly used PET models especially under drought conditions and hence significantly enhance the reliability of drought monitoring. This study reveals the influence of nonlinear relationships of surface energy partitioning on PET, which would be insightful for PET estimation as well as drought monitoring.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 111005"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rainfall partitioning and interception simulation for typical species in the Taihang Mountains, China","authors":"Bo Guo ,&nbsp;Hui Yang ,&nbsp;Chunyu Zhu ,&nbsp;Zhibang Yan ,&nbsp;Jiansheng Cao ,&nbsp;Yanjun Shen","doi":"10.1016/j.agrformet.2025.111004","DOIUrl":"10.1016/j.agrformet.2025.111004","url":null,"abstract":"<div><div>Rainfall partitioning plays a key role in the ecosystem water cycle and watershed water balance, and understanding its processes in the Taihang Mountains is essential for optimizing afforestation strategies and improving water resource management. Various afforestation species have been introduced since the implementation of ecological restoration projects, yet their effects on rainfall partitioning remain unclear. In this study, we used field observations and the Revised Gash model to investigate rainfall partitioning and its influencing factors among typical species in the Taihang Mountains. The results showed that the interception percentage, throughfall percentage, and stemflow percentage of different species at the study site ranged from 8.1% to 28.7%, 69.6% to 90.9%, and 0.9% to 10.5% of total rainfall, respectively. Rainfall amount was the most significant factor affecting rainfall partitioning, while rainfall duration and rainfall intensity had less impact on rainfall partitioning. The Revised Gash model was effectively parameterized for this region, with the relative error of the validation model for simulating typical vegetation interception ranging from -11.9% to 10.2%. The calculation method for the average evaporation rate of the canopy in the Revised Gash model affected the accuracy of interception simulations, with the Penman-Monteith method (<span><math><msub><mover><mrow><mi>E</mi></mrow><mo>‾</mo></mover><mi>PM</mi></msub></math></span>) providing better interception loss simulations for <em>P. bungeana</em>, while the mean method (<span><math><msub><mover><mrow><mi>E</mi></mrow><mo>‾</mo></mover><mi>TF</mi></msub></math></span>) was recommended for other species. Under extreme heavy rainfall events, interception loss ranged from 6.5% to 27.0% among different species. The Revised Gash model parameterized using the mean method (<span><math><msub><mover><mrow><mi>E</mi></mrow><mo>‾</mo></mover><mi>TF</mi></msub></math></span>) achieved relative errors ranging from -26.9% to 7.2% in simulating interception loss under extreme heavy rainfall events across different species. For all species, interception loss during and after rainfall accounted for the largest proportion, comprising 92.83% to 98.40% of interception loss. Compared to native species, economic species exhibited higher interception capacities, suggesting their more significant potential to influence rainfall partitioning and hydrological processes in the Taihang Mountains. In summary, evaluating the rainfall partitioning of typical species in this region has scientific significance for assessing hydrological processes and selecting afforestation species.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 111004"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}