Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to ac...Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.展开更多
Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations i...Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.展开更多
English writing is gaining high attention and emphasis in our college syllabus. It is a complicated process of written communication. In the process, the four basic skills—speaking, reading, listening and writing are...English writing is gaining high attention and emphasis in our college syllabus. It is a complicated process of written communication. In the process, the four basic skills—speaking, reading, listening and writing are organically integrated together. This paper is about the process-based approach in English writing class and its aim to emphasize the importance of process-based approach to writing. There are four parts in this paper. I start with a brief introduction to the importance of writing. Next, I will introduce my practice in English writing class. Then I will comment on the process approach and then make a little revision.展开更多
Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical...Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we展开更多
Generative AI severs the link between polished products and genuine learning,exposing the limits of outcome-only assessment.This paper advances a socio-technical framework for Al-enabled process-based assessment(PBA)t...Generative AI severs the link between polished products and genuine learning,exposing the limits of outcome-only assessment.This paper advances a socio-technical framework for Al-enabled process-based assessment(PBA)that reframes evaluation as continuous diagnosis embedded in learning.A five-stage pipeline-task→trace→model→feedback→validation-aligns pedagogical intent with instrumentation of interaction,dis-course,and multimodal evidence,and treats the human Al pair as the unit of analysis within a distributed cognition perspective.Methodologically,the framework maps trace types to appropriate model families(e.g.,sequential pattern mining,HMMs,NLP)while requiring explainability so insights are actionable.For practice,it specifies teacher AI orchestration roles that preserve human judgment and defines governance protocols for privacy,fairness,transparency,and cultural responsiveness.The result is a principled route to assess complex problem solving with integrity in the age of generative AI.展开更多
With technological advancements,weapon system development has become increasingly complex and costly.Using modeling and simulation(M&S)technology in the conceptual design stage is effective in reducing the develop...With technological advancements,weapon system development has become increasingly complex and costly.Using modeling and simulation(M&S)technology in the conceptual design stage is effective in reducing the development time and cost of weapons.One way to reduce the complexity and trial-and-error associated with weapon development using M&S technology is to develop combat scenarios to review the functions assigned to new weapons.Although the M&S technology is applicable,it is difficult to analyze how effectively the weapons are functioning,because of the dynamic features inherent in combat scenario modeling,which considers interrelations among different weapon entities.To support review of weapon functions including these characteristics,this study develops a process-based modeling(PBM)method to model the interactions between weapons in the combat scenario.This method includes the following three steps:(1)construct virtual models by converting the weapons and the weapon functions into their corresponding components;(2)generate the combat process from the combat scenario,which is derived from the interrelations among weapons under consideration using reasoning rules;(3)develop a process-based model that describes weapon functions by combining the combat process with virtual models.Then,a PBM system based on this method is implemented.The case study executed on this system shows that it is useful in deriving process-based models from various combat scenarios,analyzing weapon functions using the derived models,and reducing weapon development issues in the conceptual design stage.展开更多
The consequences of climate change continue to threaten European forests,particularly for species located at the edges of their latitudinal and altitudinal ranges.While extensively studied in Central Europe,European b...The consequences of climate change continue to threaten European forests,particularly for species located at the edges of their latitudinal and altitudinal ranges.While extensively studied in Central Europe,European beech forests require further investigation to understand how climate change will affect these ecosystems in Mediterranean areas.Proposed silvicultural options increasingly aim at sustainable management to reduce biotic and abiotic stresses and enhance these forest ecosystems'resistance and resilience mechanisms.Process-based models(PBMs)can help us to simulate such phenomena and capture early stress signals while considering the effect of different management approaches.In this study,we focus on estimating sensitivity of two state-of-the-art PBMs forest models by simulating carbon and water fluxes at the stand level to assess productivity changes and feedback resulting from different climatic forcings as well as different management regimes.We applied the 3D-CMCC-FEM and MEDFATE forest models for carbon(C)and water(H_(2)O)fluxes in two sites of the Italian peninsula,Cansiglio in the north and Mongiana in the south,under managed vs.unmanaged scenarios and under current climate and different climatic scenarios(RCP4.5 and RCP8.5).To ensure confidence in the models’results,we preliminary evaluated their performance in simulating C and H_(2)O flux in three additional beech forests of the FLUXNET network along a latitudinal gradient spanning from Denmark to central Italy.The 3D-CMCC-FEM model achieved R^(2)values of 0.83 and 0.86 with RMSEs of 2.53 and 2.05 for C and H_(2)O fluxes,respectively.MEDFATE showed R^(2)values of 0.76 and 0.69 with RMSEs of 2.54 and 3.01.At the Cansiglio site in northern Italy,both models simulated a general increase in C and H_(2)O fluxes under the RCP8.5 climate scenario compared to the current climate.Still,no benefit in managed plots compared to unmanaged ones,as the site does not have water availability limitations,and thus,competition for water is low.At the Mongiana site in southern Italy,both models predict a decrease in C and H_(2)O fluxes and sensitivity to the different climatic forcing compared to the current climate;and an increase in C and H_(2)O fluxes when considering specific management regimes compared to unmanaged scenarios.Conversely,under unmanaged scenarios plots are simulated to experience first signals of mortality prematurely due to water stress(MEDFATE)and carbon starvation(3D-CMCC-FEM)scenarios.In conclusion,while management interventions may be considered a viable solution for the conservation of beech forests under future climate conditions at moister sites like Cansiglio,in drier sites like Mongiana conservation may not lie in management interventions alone.展开更多
Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions am...Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them.This particularly applies to invasive species,which can greatly alter ecological processes in their invaded territories.Here we focus on the pine wood nematode(PWN,Bursaphelenchus xylophilus),an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe.It is expected to expand its range into continental Europe with heavy impacts possible.Given the unknown dynamics of PWN in continental Europe,we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine(BITE),a model designed to implement a variety of forest biotic agents,from fungi to large herbivores.To simulate dynamically changing host availability and conditions,BITE was coupled with the forest landscape model iLand.The potential impacts of introducing PWN were assessed in a Central European forest landscape(40,928ha),likely within PWN’s reach in future decades.A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal,colonization,and vegetation impact,whereas parameters related to population growth manifested a minor effect.Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave,eliminating 40%–95%of pine trees within 100 years post-introduction,with a maximum annual carbon loss between 1.3%and 4.2%.PWN-induced tree mortality reduced the Gross Primary Productivity,increased heterotrophic respiration,and generated a distinct legacy sink effect in the recovery period.This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.展开更多
College of Resources and Environment/Sino-Danish Center, Univers Beijing 100049, China nstitute of Geographic Sciences and ty of Chinese Academy of SciencesAbstract： Quantifying the contributions of climate change a...College of Resources and Environment/Sino-Danish Center, Univers Beijing 100049, China nstitute of Geographic Sciences and ty of Chinese Academy of SciencesAbstract： Quantifying the contributions of climate change and human activities to ecosystem evapotranspiration （ET） and gross primary productivity （GPP） changes is important for adaptation assessment and sustainable development. Spatiotemporal patterns of ET and GPP were estimated from 2000 to 2014 over North China Plain （NCP） with a physical and remote sensing-based model. The contributions of climate change and human activities to ET and GPP trends were separated and quantified by the first difference de-trending method and multivariate regression. Results showed that annual ET and GPP increased weakly, with climate change and human activities contributing 0.188 mm yr-2 and 0.466 mm yr-2 to ET trend of 0.654 mm yr-2, and -1.321 g C m-2 yr-2 and 7.542 g C m-2 yr-2 to GPP trend of 6.221 g C m-2 yr-2, respectively. In cropland, the increasing trends mainly occurred in wheat growing stage; the contributions of climate change to wheat and maize were both negative. Precipitation and sunshine duration were the major climatic factors regulating ET and GPP trends. It is concluded that human activities are the main drivers to the long term tendencies of water consumption and gross primary productivity in the NCP.展开更多
Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and ...Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.展开更多
Soil organic carbon(SOC)in croplands is a key property of soil quality for ensuring food security and agricultural sustainability,and also plays a central role in the global carbon(C)budget.When managed sustainably,so...Soil organic carbon(SOC)in croplands is a key property of soil quality for ensuring food security and agricultural sustainability,and also plays a central role in the global carbon(C)budget.When managed sustainably,soils may play a critical role in mitigating climate change by sequestering C and decreasing greenhouse gas emissions into the atmosphere.However,the magnitude and spatio-temporal patterns of global cropland SOC are far from well constrained due to high land surface heterogeneity,complicated mechanisms,and multiple influencing factors.Here,we use a process-based agroecosystem model(DLEM-Ag)in combination with diverse spatially-explicit gridded environmental data to quantify the long-term trend of SOC storage in global cropland area during 1901-2010 and identify the relative impacts of climate change,elevated CO2,nitrogen deposition,land cover change,and land management practices such as nitrogen fertilizer use and irrigation.Model results show that the total SOC and SOC density in the 2000s increased by 125%and 48.8%,respectively,compared to the early 20th century.This SOC increase was primarily attributed to cropland expansion and nitrogen fertilizer use.Factorial analysis suggests that climate change reduced approximately 3.2%(or 2,166 Tg C)of the total SOC over the past 110 years.Our results indicate that croplands have a large potential to sequester C through implementing better land use management practices,which may partially offset SOC loss caused by climate change.展开更多
Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental...Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental conditions.However,they offer little infor-mation on spatial variability effects on farm-scale yield.Remote Sensing(RS)is a useful tool to upscale yield estimates from farm scales to regional levels.Much research used RS with rice models for reliable yield estimation.As several countries start to operatio-nalize rice monitoring systems,it is needed to synthesize current literature to identify knowledge gaps,to improve estimation accuracies,and to optimize processing.This paper critically reviewed significant developments in using geospatial methods,imagery,and quantitative models to estimate rice yield.First,essential characteristics of rice were discussed as detected by optical and radar sensors,band selection,sensor configuration,spatial resolution,mapping methods,and biophysical variables of rice derivable from RS data.Second,various empirical,process-based,and semi-empirical models that used RS data for spatial estimation of yield were critically assessed-discussing how major types of models,RS platforms,data assimilation algorithms,canopy state variables,and RS variables can be integrated for yield estimation.Lastly,to overcome current constraints and to improve accuracies,several possibilities were suggested-adding new modeling modules,using alternative canopy variables,and adopting novel modeling approaches.As rice yields are expected to decrease due to global warming,geospatial rice yield estimation techniques are indispensable tools for climate change assessments.Future studies should focus on resolving the current limitations of estimation by precise delineation of rice cultivars,by incorporating dynamic harvesting indices based on climatic drivers,using innovative modeling approaches with machine learning.展开更多
Growth and yield modeling has a long history in forestry. The methods of measuring the growth of stand basal area have evolved from those developed in the U.S.A. and Germany during the last century. Stand basal area m...Growth and yield modeling has a long history in forestry. The methods of measuring the growth of stand basal area have evolved from those developed in the U.S.A. and Germany during the last century. Stand basal area modeling has progressed rapidly since the first widely used model was published by the U.S. Forest Service. Over the years, a variety of models have been developed for predicting the growth and yield of uneven/even-aged stands using stand-level approaches. The modeling methodology has not only moved from an empirical approach to a more ecological process-based approach but also accommodated a variety of techniques such as： 1） simultaneous equation methods, 2） difference models, 3） artificial neural network techniques, 4） linear/nonlinear regression models, and 5） matrix models. Empirical models using statistical methods were developed to reproduce accurately and precisely field observations. In contrast, process models have a shorter history, developed originally as research and education tools with the aim of increasing the understanding of cause and effect relationships. Empirical and process models can be married into hybrid models in which the shortcomings of both component approaches can, to some extent, be overcome. Algebraic difference forms of stand basal area models which consist of stand age, stand density and site quality can fully describe stand growth dynamics. This paper reviews the current literature regarding stand basal area models, discusses the basic types of models and their merits and outlines recent progress in modeling growth and dynamics of stand basal area. Future trends involving algebraic difference forms, good fitting variables and model types into stand basal area modeling strategies are discussed.展开更多
A process-based 3D numerical model for surfzone hydrodynamics and beach evolution was established. Comparisons between the experimental data and model results proved that the model could effectively describe the hydro...A process-based 3D numerical model for surfzone hydrodynamics and beach evolution was established. Comparisons between the experimental data and model results proved that the model could effectively describe the hydrodynamics, sediment transport feature and sandbar migration process in the surfzone with satisfactory precision. A series of numerical simulations on the wave breaking and shoaling up to a barred beach were carried out based on the model system. Analyzed from the model results, the wave-induced current system in the surfzone consists of two major processes, which are the phase-averaged undertow caused by wave breaking and the net drift caused by both of the nonlinear wave motion and surface roller effect. When storm waves come to the barred beach, the strong offshore undertow along the beach suppresses the onshore net drift, making the initial sandbar migrate to the seaside. Under the condition of calm wave environment, both the undertow and net drift flow to the shoreline at the offshore side of the sandbar, and then push the initial sandbar to the shoreline. The consideration of surface roller has significant impact on the modeling results of the sandbar migration. As the roller transfer rate increases, the sandbar moves onshore especially under the storm wave condition.展开更多
The stability of estuarine channel-shoal systems is important for port utilization,navigation maintenance,habitat protection and ecosystem service functions.This paper uses the South Channel of the Changjiang(Yangtze ...The stability of estuarine channel-shoal systems is important for port utilization,navigation maintenance,habitat protection and ecosystem service functions.This paper uses the South Channel of the Changjiang(Yangtze River)Estuary as a typical example to investigate the channel-shoal adjustment mechanism and its future trend.The combined approaches of bathymetric data analysis and process-based modeling(Delft3D)are applied.Quantitative analysis of morphological changes indicates that the South Channel experienced remarkable channel-shoal adjustment during 1958–2018.Periodic evolution was identified,including shoal migration,incision and emergence under natural conditions before the mid-1980s.Since then,fluvial sediment decline and local human intervention have interrupted the periodic processes.After 1986,as river sediment discharge started to decline,the South Channel converted to net erosion,and both the mid-channel shoal at the bifurcation node and the tail of the Ruifeng Shoal showed significant scour.Process-based hydrodynamic simulations revealed that the northern rotation of the mainstream downstream of Wusong triggered the erosion of the Ruifeng Shoal,while unordered sand mining at the shoal tail in approximately 2002 enhanced shoal shrinkage.In addition,the self-adjustment of the transverse section shape resulted in abnormal accretion in 2002–2007.Afterward,the South Channel underwent overall erosion as sediment discharge decreased to a low level(<150 Mt/a).Five stages of channel-shoal pattern adjustment and accretion/erosion status during the past 60years were defined,i.e.,the accretion stage(1958–1965),remarkable channel-shoal adjustment stage(1978–1986),slow erosion stage(1986–1997),shoal scour and shrinkage stage(1997–2007)and overall channel-shoal erosion stage(2007–2018).Model prediction of the evolutionary trend indicates that overall erosion within the South Channel is most likely to continue in 2015–2050.Further adjustment of the South Channel under extremely low sediment discharge may threaten the riverbed stability and the sustainable development of this large-scale estuary.Future work on adaptive strategies for varying conditions is recommended.展开更多
Different leaf(evergreen vs.deciduous habit)and xylem(diffuse-vs.ring-porous wood)traits represent contrasting strategies to face seasonal changes in water availability and temperature.However,how contrasting leaf and...Different leaf(evergreen vs.deciduous habit)and xylem(diffuse-vs.ring-porous wood)traits represent contrasting strategies to face seasonal changes in water availability and temperature.However,how contrasting leaf and xylem habits of coexisting tree species affect stem wood formation and tree-ring development remains poorly understood.Here,we investigated the spatio-temporal patterns of wood formation in two deciduous oaks(Quercus faginea and Quercus petraea)and two evergreen oaks(Quercus ilex and Quercus suber)coexisting in seasonally dry Mediterranean forests along an aridity gradient in Spain.We hypothesized that growth responses to drought and intra-and inter-annual growth patterns would differ between functional groups.We simulated intra-and interannual growth using a modified version of the Vaganov-Shashkin(VS)process-based,growth model.The VS model simulations were used to estimate growth changes under a high emission scenario(RCP 8.5)for the current distribution of the study oak species and to forecast their future performance under warm(4.8℃)conditions in the Iberian Peninsula.Our simulations indicate that climate warming would induce a shortening of the ringgrowth season and a reduction of radial growth in evergreen and deciduous Mediterranean oaks,particularly in dry sites from southern and eastern Iberia currently occupied by Q.ilex and Q.faginea.Evergreen oaks may better recover after dry periods than deciduous oaks by resuming growth after the summer drought.Low soil water availability in spring would be more detrimental to growth of deciduous oaks.Process-based growth models should be refined and validated to better forecast changes in tree growth as a function of climate.展开更多
A newly emerging design pattern, named as adaptable design （AD）, which aims at developing products that are adaptable from design to post-life cycle, is discussed. AD consists of four main phases： product modeling,...A newly emerging design pattern, named as adaptable design （AD）, which aims at developing products that are adaptable from design to post-life cycle, is discussed. AD consists of four main phases： product modeling, design platform, specific design and product redesign. A new process-based design data model （PDDM） is presented which is organized according to the principles of convenient knowledge extraction, data representation, layout, sharing and reuse. Based on the PDDM, a universal design platform for product family development is established, which has characters of modularity, parameter-driven, variant design, etc. The framework of the platform is also proposed as a conceptual structure and overall logical organization for generating a family of products. AD methodology is successfully applied to develop a family of tunnel boring machine （TBM） for different engineering projects, with the efficiency of our developing team being greatly increased.展开更多
In order to improve the accuracy of prediction when using the empirical orthogonal function （EOF） method, this paper describes a novel approach for two-dimensional （2D） EOF analysis based on extrapolating both the...In order to improve the accuracy of prediction when using the empirical orthogonal function （EOF） method, this paper describes a novel approach for two-dimensional （2D） EOF analysis based on extrapolating both the spatial and temporal EOF components for long-term prediction of coastal morphological changes. The approach was investigated with data obtained from a process-based numerical model, COAST2D, which was applied to an idealized study site with a group of shore-parallel breakwaters. The progressive behavior of the spatial and temporal EOF components, related to bathymetric changes over a training period, was demonstrated, and EOF components were extrapolated with combined linear and exponential functions for long-term prediction. The extrapolated EOF components were then used to reconstruct bathymetric changes. The comparison of the reconstructed bathymetric changes with the modeled results from the COAST2D model illustrates that the presented approach can be effective for long-term prediction of coastal morphological changes, and extrapolating both the spatial and temporal EOF components yields better results than extrapolating only the temporal EOF component.展开更多
There has been increased interest in quantifying the manure production of livestock, primarily driven by public authorities, who aim to evaluate the environmental impact of livestock production, but also at the farm l...There has been increased interest in quantifying the manure production of livestock, primarily driven by public authorities, who aim to evaluate the environmental impact of livestock production, but also at the farm level, to manage manure storage and availability of fertilizer for crop production. Moreover, current manure production estimates from intensively reared beef calves are higher than actual production due to changes in farming systems, advances in animal genetics and feed efficiency. This study aims to redefine and update manure production estimates in intensively reared beef calves to predict manure production as a policy and planning tool, as there are no current models available. A trial was conducted to collect data on manure production during the growing-finishing period (243 d) of 54 Limousine calves (from 346.7 to 674.0 kg live weight, LW). Such data were used to develop two models to predict manure excretion: (1) a complex mechanistic model (CompM), and (2) a simplified empirical model (SimpM). Both models were evaluated against an independent dataset including a total of 4,692 animals on 31 farms and 5 breeds. Results from CompM require interpretation because the model does not output a single value but a range of manure production (minimum, medium and maximum), and would therefore be more suitable for professional use. The SimpM could be considered simple, reliable, and versatile for predicting manure excretion at farm level. SimpM could be refined and improved by including data from other studies on beef cattle with distinct characteristics and management.展开更多
The greenhouse gas budget on the Tibetan Plateau remains unknown and the potential for methane(CH_(4))and nitrous oxide(N_(2)O)emissions from an intensifying livestock system and expanding surface water in offsetting ...The greenhouse gas budget on the Tibetan Plateau remains unknown and the potential for methane(CH_(4))and nitrous oxide(N_(2)O)emissions from an intensifying livestock system and expanding surface water in offsetting terrestrial carbon dioxide(CO_(2))sinks are both of great concerns and uncertainties,which compromise an accurate assessment of Tibetan Plateau contribution to China’s ambitious climate goals by 2060s.Here we integrated greenhouse gas flux measurements at∼500 sites in empirical modeling approaches,emissions from the livestock sector with process-based biogeochemistry modeling to estimate CH_(4)and N_(2)O fluxes across terrestrial ecosystems and inland waters in 2000s and 2010s.We found that emissions from livestock and inland waters,predominantly contributed by CH_(4),compensated∼21%and∼13%of carbon sinks provided by forests and grasslands after adjusting carbon burial in sediments and riverine carbon export,respectively.The Tibetan Plateau then acted as an appreciable greenhouse gas sink that almost compensated for its contemporary anthropogenic emissions,making it nearly climate-neutral.The enhancement of terrestrial CO_(2)sinks in the 2060s under medium warming scenario would be counterbalanced by livestock CH_(4)emissions when the current overgrazing status continues.By transitioning to a livestock-forage balance and implementing mitigation initiatives to reduce livestock emission intensity,the greenhouse gas sink is projected to increase by more than 1.5 times.We suggested that a transition towards sustainable pastoralism illuminates the path to minimizing ecosystem greenhouse gas emissions and amplifying the role of the Tibetan Plateau in fulfilling China’s climate ambition.展开更多
基金supported by the National Natural Science Foundation of China(42101382 and 41901342)the Shandong Provincial Natural Science Foundation(ZR2020QD016)the National Key Research and Development Program of China(2016YFD0300101).
文摘Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.
基金supported by the National Key Research and Development Program of China(2016YFD0300101,and 2016YFD0300110)the National Natural Science Foundation of China(41871253 and 31671585)+1 种基金the“Taishan Scholar”Project of Shandong Province,Chinathe Key Basic Research Project of Shandong Natural Science Foundation,China(ZR2017ZB0422)。
文摘Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.
文摘English writing is gaining high attention and emphasis in our college syllabus. It is a complicated process of written communication. In the process, the four basic skills—speaking, reading, listening and writing are organically integrated together. This paper is about the process-based approach in English writing class and its aim to emphasize the importance of process-based approach to writing. There are four parts in this paper. I start with a brief introduction to the importance of writing. Next, I will introduce my practice in English writing class. Then I will comment on the process approach and then make a little revision.
文摘Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we
文摘Generative AI severs the link between polished products and genuine learning,exposing the limits of outcome-only assessment.This paper advances a socio-technical framework for Al-enabled process-based assessment(PBA)that reframes evaluation as continuous diagnosis embedded in learning.A five-stage pipeline-task→trace→model→feedback→validation-aligns pedagogical intent with instrumentation of interaction,dis-course,and multimodal evidence,and treats the human Al pair as the unit of analysis within a distributed cognition perspective.Methodologically,the framework maps trace types to appropriate model families(e.g.,sequential pattern mining,HMMs,NLP)while requiring explainability so insights are actionable.For practice,it specifies teacher AI orchestration roles that preserve human judgment and defines governance protocols for privacy,fairness,transparency,and cultural responsiveness.The result is a principled route to assess complex problem solving with integrity in the age of generative AI.
基金Project supported by the Defense Acquisition Program Administration and Agency for Defense Development of the Republic of Korea(Nos.UD110006MD and UD140022PD)。
文摘With technological advancements,weapon system development has become increasingly complex and costly.Using modeling and simulation(M&S)technology in the conceptual design stage is effective in reducing the development time and cost of weapons.One way to reduce the complexity and trial-and-error associated with weapon development using M&S technology is to develop combat scenarios to review the functions assigned to new weapons.Although the M&S technology is applicable,it is difficult to analyze how effectively the weapons are functioning,because of the dynamic features inherent in combat scenario modeling,which considers interrelations among different weapon entities.To support review of weapon functions including these characteristics,this study develops a process-based modeling(PBM)method to model the interactions between weapons in the combat scenario.This method includes the following three steps:(1)construct virtual models by converting the weapons and the weapon functions into their corresponding components;(2)generate the combat process from the combat scenario,which is derived from the interrelations among weapons under consideration using reasoning rules;(3)develop a process-based model that describes weapon functions by combining the combat process with virtual models.Then,a PBM system based on this method is implemented.The case study executed on this system shows that it is useful in deriving process-based models from various combat scenarios,analyzing weapon functions using the derived models,and reducing weapon development issues in the conceptual design stage.
基金the Institute Research Centre for Ecological and Forestry Applications (CREAF) of Barcelona that supported the research by the Spanish “Ministerio de Ciencia e Innovacio'n”(MCIN/AEI/ 10.13039/501100011033) (grant agreement No. PID 2021-126679OBI00)partially supported by MIUR Project (PRIN 2020) between WATER and carbon cycles during droug“Unraveling interactionsht and their impact on water resources and forest and grassland ecosySTEMs in the Mediterranean climate (WATERSTEM)”(Project number: 20202WF53Z),“WAFER”at CNR (Consiglio Nazionale delle Ricerche)+3 种基金Priwitzer et al. (2014) (cod. 2020E52THS)-Research Projects of National Relevance funded by the Italian Ministry of University and Research entitled: “Multi-scale observations to predict Forest response to pollution and climate change”(MULTIFOR, project number: 2020E52THS)funding by the project OptForEU Horizon Europe research and innovation programme under grant agreement No. 101060554the project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4-Call for tender No. 3138 of December 16, 2021, rectified by Decree n.3175 of December 18, 2021 of Italian Ministry of UniversityResearch funded by the European UnionationEU under award Number: Project code CN_00000033–Next Gener, Concession Decree No. 1034 of June 17, 2022 adopted by the Italian Ministry of University and Research, CUP B83C22002930006, Project title“National Biodiversity Future Centre-NBFC”
文摘The consequences of climate change continue to threaten European forests,particularly for species located at the edges of their latitudinal and altitudinal ranges.While extensively studied in Central Europe,European beech forests require further investigation to understand how climate change will affect these ecosystems in Mediterranean areas.Proposed silvicultural options increasingly aim at sustainable management to reduce biotic and abiotic stresses and enhance these forest ecosystems'resistance and resilience mechanisms.Process-based models(PBMs)can help us to simulate such phenomena and capture early stress signals while considering the effect of different management approaches.In this study,we focus on estimating sensitivity of two state-of-the-art PBMs forest models by simulating carbon and water fluxes at the stand level to assess productivity changes and feedback resulting from different climatic forcings as well as different management regimes.We applied the 3D-CMCC-FEM and MEDFATE forest models for carbon(C)and water(H_(2)O)fluxes in two sites of the Italian peninsula,Cansiglio in the north and Mongiana in the south,under managed vs.unmanaged scenarios and under current climate and different climatic scenarios(RCP4.5 and RCP8.5).To ensure confidence in the models’results,we preliminary evaluated their performance in simulating C and H_(2)O flux in three additional beech forests of the FLUXNET network along a latitudinal gradient spanning from Denmark to central Italy.The 3D-CMCC-FEM model achieved R^(2)values of 0.83 and 0.86 with RMSEs of 2.53 and 2.05 for C and H_(2)O fluxes,respectively.MEDFATE showed R^(2)values of 0.76 and 0.69 with RMSEs of 2.54 and 3.01.At the Cansiglio site in northern Italy,both models simulated a general increase in C and H_(2)O fluxes under the RCP8.5 climate scenario compared to the current climate.Still,no benefit in managed plots compared to unmanaged ones,as the site does not have water availability limitations,and thus,competition for water is low.At the Mongiana site in southern Italy,both models predict a decrease in C and H_(2)O fluxes and sensitivity to the different climatic forcing compared to the current climate;and an increase in C and H_(2)O fluxes when considering specific management regimes compared to unmanaged scenarios.Conversely,under unmanaged scenarios plots are simulated to experience first signals of mortality prematurely due to water stress(MEDFATE)and carbon starvation(3D-CMCC-FEM)scenarios.In conclusion,while management interventions may be considered a viable solution for the conservation of beech forests under future climate conditions at moister sites like Cansiglio,in drier sites like Mongiana conservation may not lie in management interventions alone.
基金supported by the project“EVA4.0”,No.CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE of the Czech Republicthe H2020 project RESONATE under grant agreement No.101000574.
文摘Forests worldwide are experiencing increasingly intense biotic disturbances;however,assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them.This particularly applies to invasive species,which can greatly alter ecological processes in their invaded territories.Here we focus on the pine wood nematode(PWN,Bursaphelenchus xylophilus),an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe.It is expected to expand its range into continental Europe with heavy impacts possible.Given the unknown dynamics of PWN in continental Europe,we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine(BITE),a model designed to implement a variety of forest biotic agents,from fungi to large herbivores.To simulate dynamically changing host availability and conditions,BITE was coupled with the forest landscape model iLand.The potential impacts of introducing PWN were assessed in a Central European forest landscape(40,928ha),likely within PWN’s reach in future decades.A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal,colonization,and vegetation impact,whereas parameters related to population growth manifested a minor effect.Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave,eliminating 40%–95%of pine trees within 100 years post-introduction,with a maximum annual carbon loss between 1.3%and 4.2%.PWN-induced tree mortality reduced the Gross Primary Productivity,increased heterotrophic respiration,and generated a distinct legacy sink effect in the recovery period.This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.
基金National Natural Science Foundation of China, No.41471026 National Key Research and Development Program of China, No.2016YFC0401402Acknowledgment We thank to all the data providers. We also appreciate editors and reviewers for their constructive comments and suggestions. Finally, the first author is grateful to the invaluable support received from doctoral student ZOU Yi.
文摘College of Resources and Environment/Sino-Danish Center, Univers Beijing 100049, China nstitute of Geographic Sciences and ty of Chinese Academy of SciencesAbstract： Quantifying the contributions of climate change and human activities to ecosystem evapotranspiration （ET） and gross primary productivity （GPP） changes is important for adaptation assessment and sustainable development. Spatiotemporal patterns of ET and GPP were estimated from 2000 to 2014 over North China Plain （NCP） with a physical and remote sensing-based model. The contributions of climate change and human activities to ET and GPP trends were separated and quantified by the first difference de-trending method and multivariate regression. Results showed that annual ET and GPP increased weakly, with climate change and human activities contributing 0.188 mm yr-2 and 0.466 mm yr-2 to ET trend of 0.654 mm yr-2, and -1.321 g C m-2 yr-2 and 7.542 g C m-2 yr-2 to GPP trend of 6.221 g C m-2 yr-2, respectively. In cropland, the increasing trends mainly occurred in wheat growing stage; the contributions of climate change to wheat and maize were both negative. Precipitation and sunshine duration were the major climatic factors regulating ET and GPP trends. It is concluded that human activities are the main drivers to the long term tendencies of water consumption and gross primary productivity in the NCP.
基金supported by the International Science & Technology Cooperation Program of China (2010DFA92720-10)the "Hundred Talents Program" of the Chinese Academy of Sciences (Y174131001)supported by the National Basic Research Program of China (2009CB825105)
文摘Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.
基金supported by NASA Kentucky NNX15AR69H,NSF grant nos.1940696,1903722,and 1243232Andrew Carnegie Fellowship Award no.G-F-19-56910.
文摘Soil organic carbon(SOC)in croplands is a key property of soil quality for ensuring food security and agricultural sustainability,and also plays a central role in the global carbon(C)budget.When managed sustainably,soils may play a critical role in mitigating climate change by sequestering C and decreasing greenhouse gas emissions into the atmosphere.However,the magnitude and spatio-temporal patterns of global cropland SOC are far from well constrained due to high land surface heterogeneity,complicated mechanisms,and multiple influencing factors.Here,we use a process-based agroecosystem model(DLEM-Ag)in combination with diverse spatially-explicit gridded environmental data to quantify the long-term trend of SOC storage in global cropland area during 1901-2010 and identify the relative impacts of climate change,elevated CO2,nitrogen deposition,land cover change,and land management practices such as nitrogen fertilizer use and irrigation.Model results show that the total SOC and SOC density in the 2000s increased by 125%and 48.8%,respectively,compared to the early 20th century.This SOC increase was primarily attributed to cropland expansion and nitrogen fertilizer use.Factorial analysis suggests that climate change reduced approximately 3.2%(or 2,166 Tg C)of the total SOC over the past 110 years.Our results indicate that croplands have a large potential to sequester C through implementing better land use management practices,which may partially offset SOC loss caused by climate change.
基金This work is supported by New Zealand Ministry of Foreign Affairs and Trade PhD Scholarship and the University of Auckland’s Postgraduate Research Student SupportMinistry of Foreign Affairs and Trade,New Zealand,University of Auckland.
文摘Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental conditions.However,they offer little infor-mation on spatial variability effects on farm-scale yield.Remote Sensing(RS)is a useful tool to upscale yield estimates from farm scales to regional levels.Much research used RS with rice models for reliable yield estimation.As several countries start to operatio-nalize rice monitoring systems,it is needed to synthesize current literature to identify knowledge gaps,to improve estimation accuracies,and to optimize processing.This paper critically reviewed significant developments in using geospatial methods,imagery,and quantitative models to estimate rice yield.First,essential characteristics of rice were discussed as detected by optical and radar sensors,band selection,sensor configuration,spatial resolution,mapping methods,and biophysical variables of rice derivable from RS data.Second,various empirical,process-based,and semi-empirical models that used RS data for spatial estimation of yield were critically assessed-discussing how major types of models,RS platforms,data assimilation algorithms,canopy state variables,and RS variables can be integrated for yield estimation.Lastly,to overcome current constraints and to improve accuracies,several possibilities were suggested-adding new modeling modules,using alternative canopy variables,and adopting novel modeling approaches.As rice yields are expected to decrease due to global warming,geospatial rice yield estimation techniques are indispensable tools for climate change assessments.Future studies should focus on resolving the current limitations of estimation by precise delineation of rice cultivars,by incorporating dynamic harvesting indices based on climatic drivers,using innovative modeling approaches with machine learning.
基金This study was supported by the National Natural Science Foundation of China （Grant No. 30471389）
文摘Growth and yield modeling has a long history in forestry. The methods of measuring the growth of stand basal area have evolved from those developed in the U.S.A. and Germany during the last century. Stand basal area modeling has progressed rapidly since the first widely used model was published by the U.S. Forest Service. Over the years, a variety of models have been developed for predicting the growth and yield of uneven/even-aged stands using stand-level approaches. The modeling methodology has not only moved from an empirical approach to a more ecological process-based approach but also accommodated a variety of techniques such as： 1） simultaneous equation methods, 2） difference models, 3） artificial neural network techniques, 4） linear/nonlinear regression models, and 5） matrix models. Empirical models using statistical methods were developed to reproduce accurately and precisely field observations. In contrast, process models have a shorter history, developed originally as research and education tools with the aim of increasing the understanding of cause and effect relationships. Empirical and process models can be married into hybrid models in which the shortcomings of both component approaches can, to some extent, be overcome. Algebraic difference forms of stand basal area models which consist of stand age, stand density and site quality can fully describe stand growth dynamics. This paper reviews the current literature regarding stand basal area models, discusses the basic types of models and their merits and outlines recent progress in modeling growth and dynamics of stand basal area. Future trends involving algebraic difference forms, good fitting variables and model types into stand basal area modeling strategies are discussed.
基金financially supported by the National Key Research and Development Program of China(Grant No.2016YFC0402603)the National Natural Science Foundation of China(Grant Nos.51779112,51509119,and 51609029)+2 种基金the Project of Tianjin Natural Science Foundation(Grant No.16JCQNJC06900)the Open Project of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(Grant No.2014492211)the Fundamental Research Funds for the Central Public Welfare Research Institutes(Grant Nos.TKS170101and TKS170202)
文摘A process-based 3D numerical model for surfzone hydrodynamics and beach evolution was established. Comparisons between the experimental data and model results proved that the model could effectively describe the hydrodynamics, sediment transport feature and sandbar migration process in the surfzone with satisfactory precision. A series of numerical simulations on the wave breaking and shoaling up to a barred beach were carried out based on the model system. Analyzed from the model results, the wave-induced current system in the surfzone consists of two major processes, which are the phase-averaged undertow caused by wave breaking and the net drift caused by both of the nonlinear wave motion and surface roller effect. When storm waves come to the barred beach, the strong offshore undertow along the beach suppresses the onshore net drift, making the initial sandbar migrate to the seaside. Under the condition of calm wave environment, both the undertow and net drift flow to the shoreline at the offshore side of the sandbar, and then push the initial sandbar to the shoreline. The consideration of surface roller has significant impact on the modeling results of the sandbar migration. As the roller transfer rate increases, the sandbar moves onshore especially under the storm wave condition.
基金Natural Science Foundation of China-Ministry of Water Resources-China Three Gorges Corporation Joint Fund for Changjiang Water Science Research,No.U2040202National Natural Science Foundation of China,No.42006156,No.52009008+1 种基金Fundamental Research Funds for Central Public Welfare Research Institutes,No.CKSF2021530/HLResearch Project on Major Scientific and Technological Issues in Watershed Water Management,No.CKSC2020791/HL。
文摘The stability of estuarine channel-shoal systems is important for port utilization,navigation maintenance,habitat protection and ecosystem service functions.This paper uses the South Channel of the Changjiang(Yangtze River)Estuary as a typical example to investigate the channel-shoal adjustment mechanism and its future trend.The combined approaches of bathymetric data analysis and process-based modeling(Delft3D)are applied.Quantitative analysis of morphological changes indicates that the South Channel experienced remarkable channel-shoal adjustment during 1958–2018.Periodic evolution was identified,including shoal migration,incision and emergence under natural conditions before the mid-1980s.Since then,fluvial sediment decline and local human intervention have interrupted the periodic processes.After 1986,as river sediment discharge started to decline,the South Channel converted to net erosion,and both the mid-channel shoal at the bifurcation node and the tail of the Ruifeng Shoal showed significant scour.Process-based hydrodynamic simulations revealed that the northern rotation of the mainstream downstream of Wusong triggered the erosion of the Ruifeng Shoal,while unordered sand mining at the shoal tail in approximately 2002 enhanced shoal shrinkage.In addition,the self-adjustment of the transverse section shape resulted in abnormal accretion in 2002–2007.Afterward,the South Channel underwent overall erosion as sediment discharge decreased to a low level(<150 Mt/a).Five stages of channel-shoal pattern adjustment and accretion/erosion status during the past 60years were defined,i.e.,the accretion stage(1958–1965),remarkable channel-shoal adjustment stage(1978–1986),slow erosion stage(1986–1997),shoal scour and shrinkage stage(1997–2007)and overall channel-shoal erosion stage(2007–2018).Model prediction of the evolutionary trend indicates that overall erosion within the South Channel is most likely to continue in 2015–2050.Further adjustment of the South Channel under extremely low sediment discharge may threaten the riverbed stability and the sustainable development of this large-scale estuary.Future work on adaptive strategies for varying conditions is recommended.
基金This study was funded by projects“Vulnerabilidad y resiliencia de bosques maduros de Quercus mediterraneos en espacios protegidos bajo diferentes escenarios climaticos y de gestion(QuMature)”(Ref.PRCV00594,Fundacion Biodiversidad)TED 2021-129770 B-C21(Spanish Ministry of Science and Innovation)FC was supported by the Portuguese R&D unit CFE(FCT/UIDB/04004/2020).
文摘Different leaf(evergreen vs.deciduous habit)and xylem(diffuse-vs.ring-porous wood)traits represent contrasting strategies to face seasonal changes in water availability and temperature.However,how contrasting leaf and xylem habits of coexisting tree species affect stem wood formation and tree-ring development remains poorly understood.Here,we investigated the spatio-temporal patterns of wood formation in two deciduous oaks(Quercus faginea and Quercus petraea)and two evergreen oaks(Quercus ilex and Quercus suber)coexisting in seasonally dry Mediterranean forests along an aridity gradient in Spain.We hypothesized that growth responses to drought and intra-and inter-annual growth patterns would differ between functional groups.We simulated intra-and interannual growth using a modified version of the Vaganov-Shashkin(VS)process-based,growth model.The VS model simulations were used to estimate growth changes under a high emission scenario(RCP 8.5)for the current distribution of the study oak species and to forecast their future performance under warm(4.8℃)conditions in the Iberian Peninsula.Our simulations indicate that climate warming would induce a shortening of the ringgrowth season and a reduction of radial growth in evergreen and deciduous Mediterranean oaks,particularly in dry sites from southern and eastern Iberia currently occupied by Q.ilex and Q.faginea.Evergreen oaks may better recover after dry periods than deciduous oaks by resuming growth after the summer drought.Low soil water availability in spring would be more detrimental to growth of deciduous oaks.Process-based growth models should be refined and validated to better forecast changes in tree growth as a function of climate.
文摘A newly emerging design pattern, named as adaptable design （AD）, which aims at developing products that are adaptable from design to post-life cycle, is discussed. AD consists of four main phases： product modeling, design platform, specific design and product redesign. A new process-based design data model （PDDM） is presented which is organized according to the principles of convenient knowledge extraction, data representation, layout, sharing and reuse. Based on the PDDM, a universal design platform for product family development is established, which has characters of modularity, parameter-driven, variant design, etc. The framework of the platform is also proposed as a conceptual structure and overall logical organization for generating a family of products. AD methodology is successfully applied to develop a family of tunnel boring machine （TBM） for different engineering projects, with the efficiency of our developing team being greatly increased.
基金the School of Engineering at Cardiff University for providing the financial support of a Ph D studentship to accomplish the research
文摘In order to improve the accuracy of prediction when using the empirical orthogonal function （EOF） method, this paper describes a novel approach for two-dimensional （2D） EOF analysis based on extrapolating both the spatial and temporal EOF components for long-term prediction of coastal morphological changes. The approach was investigated with data obtained from a process-based numerical model, COAST2D, which was applied to an idealized study site with a group of shore-parallel breakwaters. The progressive behavior of the spatial and temporal EOF components, related to bathymetric changes over a training period, was demonstrated, and EOF components were extrapolated with combined linear and exponential functions for long-term prediction. The extrapolated EOF components were then used to reconstruct bathymetric changes. The comparison of the reconstructed bathymetric changes with the modeled results from the COAST2D model illustrates that the presented approach can be effective for long-term prediction of coastal morphological changes, and extrapolating both the spatial and temporal EOF components yields better results than extrapolating only the temporal EOF component.
文摘There has been increased interest in quantifying the manure production of livestock, primarily driven by public authorities, who aim to evaluate the environmental impact of livestock production, but also at the farm level, to manage manure storage and availability of fertilizer for crop production. Moreover, current manure production estimates from intensively reared beef calves are higher than actual production due to changes in farming systems, advances in animal genetics and feed efficiency. This study aims to redefine and update manure production estimates in intensively reared beef calves to predict manure production as a policy and planning tool, as there are no current models available. A trial was conducted to collect data on manure production during the growing-finishing period (243 d) of 54 Limousine calves (from 346.7 to 674.0 kg live weight, LW). Such data were used to develop two models to predict manure excretion: (1) a complex mechanistic model (CompM), and (2) a simplified empirical model (SimpM). Both models were evaluated against an independent dataset including a total of 4,692 animals on 31 farms and 5 breeds. Results from CompM require interpretation because the model does not output a single value but a range of manure production (minimum, medium and maximum), and would therefore be more suitable for professional use. The SimpM could be considered simple, reliable, and versatile for predicting manure excretion at farm level. SimpM could be refined and improved by including data from other studies on beef cattle with distinct characteristics and management.
基金supported by grants from the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(2024QZKK0301)the National Key Research and Development Program of China(2024YFF0809104)the National Natural Science Foundation of China(42425106).
文摘The greenhouse gas budget on the Tibetan Plateau remains unknown and the potential for methane(CH_(4))and nitrous oxide(N_(2)O)emissions from an intensifying livestock system and expanding surface water in offsetting terrestrial carbon dioxide(CO_(2))sinks are both of great concerns and uncertainties,which compromise an accurate assessment of Tibetan Plateau contribution to China’s ambitious climate goals by 2060s.Here we integrated greenhouse gas flux measurements at∼500 sites in empirical modeling approaches,emissions from the livestock sector with process-based biogeochemistry modeling to estimate CH_(4)and N_(2)O fluxes across terrestrial ecosystems and inland waters in 2000s and 2010s.We found that emissions from livestock and inland waters,predominantly contributed by CH_(4),compensated∼21%and∼13%of carbon sinks provided by forests and grasslands after adjusting carbon burial in sediments and riverine carbon export,respectively.The Tibetan Plateau then acted as an appreciable greenhouse gas sink that almost compensated for its contemporary anthropogenic emissions,making it nearly climate-neutral.The enhancement of terrestrial CO_(2)sinks in the 2060s under medium warming scenario would be counterbalanced by livestock CH_(4)emissions when the current overgrazing status continues.By transitioning to a livestock-forage balance and implementing mitigation initiatives to reduce livestock emission intensity,the greenhouse gas sink is projected to increase by more than 1.5 times.We suggested that a transition towards sustainable pastoralism illuminates the path to minimizing ecosystem greenhouse gas emissions and amplifying the role of the Tibetan Plateau in fulfilling China’s climate ambition.
