62 results about "Future climate" patented technology

A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

The invention discloses a method drawing up a multi-goal reservoir optimization scheduling graph capable of being self-adaptive to climate change. The method for drawing up the multi-goal reservoir optimization scheduling graph comprises the steps of: step 1. establishing a coupling model of a global climate model (GCM) and a variable infiltration capacity (VIC) hydrological model so as to forecast a run-off process under a future climate change scene; step two. establishing a multi-goal reservoir optimization scheduling graph model; and step 3. taking the forecast run-off process data under the future climate change scene as the input of the optimization scheduling graph model, and drawing up the multi-goal optimization scheduling graph model by adapting a self-adaptive genetic algorithm. The method for drawing up the multi-goal reservoir optimization scheduling graph has the advantages of balancing the social economy goal and ecological goal of reservoir scheduling, improving the comprehensive benefits of reservoir scheduling to the maximum degree on the condition of ensuring the flood control safety of a reservoir and being capable of being self-adaptive to future climate change and being widely applied to the production practice of multi-goal reservoir optimization scheduling.

The present invention discloses a crop irrigation water requirement calculation method on future climatic conditions. The method comprises the steps of collecting the future climatic mode data, and correcting the future climatic mode data based on the historical actually measured meteorological data to enable the future climatic mode data to be suitable for the climatic change influence evaluation of a region or station scale; according to the growth period data of a crop field test and an accumulated temperature formula, constructing a response model of the crop planting date and the crop growth period length to the temperature; utilizing a penman formula to combine a single crop coefficient method and a soil moisture stress coefficient to calculate the crop daily water requirement; based on a crop irrigation system and a water balance principle to calculate the crop daily irrigation water requirement. Aiming at the influence of the climatic change on the agricultural water resource security, the method of the present invention considers the change of the crop planting date and the growth period caused by the global warming, so that a water resource planning management department can forecast the regional future agricultural water resource utilization amount more accurately, and accordingly, a water resource planning scheme is proposed more reasonably.

The invention discloses a water resource optimal allocation method based on an artificial intelligence algorithm. The method comprises the following steps that collected hydrometeorology, land utilization types, DEM and hydrogeology are used as input data of a surface water and underground water simulation model, actual measurement data are used for calibrating and verifying related parameters, related model parameters are determined, and a surface water-underground water coupling simulation model is constructed; according to the invention, future climate scene data is combined to predict thewater resource supply and demand of the future area, the water resource supply and demand serves as an input value of the multi-objective planning model, the built multi-objective optimization model is solved through NSGA-II, a reasonable water resource optimal configuration scheme under the future climate change scene is finally obtained, and the method has very important practical significance and practicability.

The invention discloses a response analysis method for surface water quality to a climate change. The method is characterized by comprising the following steps of: 1, prediction of a future climate change factor change trend, 2, building and calibration of an SWAT model, 3, calculation of total nitrogen and total phosphorus, and 4, a response of the surface water quality to the climate change. Compared with the prior art, the method based on future climate prediction, the SWAT hydrological model and statistical analysis simulates influences on the surface water quality change by climate change factors such as temperature and rainfall through setting different temperature change scenes and rainfall change scenes, simulation study on the water quality influences by the climate change is developed with the SWAT hydrological model as a basis, a response relation between the climate change and the water quality change is built, and response analysis of the surface water quality to the climate change can be carried out. The method of the invention can be widely applied to response study on the surface water quality to the climate change, particularly response analysis of the surface water quality in Hetao areas to the climate change.

The invention discloses an irrigation requirement computation system and an irrigation requirement computation method under a climatic variation background. A historical data input module inputs collected climate parameters and crop information into a data forecasting module; the data forecasting module forecasts future climate parameters and crop information according to historical climate parameters and crop information; a sensor state control module selects a wireless sensor needing to be awakened and wireless sensor awakening time according to the forecasted future climate parameters and crop information, and collects the corresponding climate parameters and crop information in real time while the wireless sensor is awakened; and an irrigation strategy generation and execution module generates an irrigation strategy, and irrigates crops in time. The irrigation requirement computation system provided by the invention, irrigation water of the crops can be effectively managed while the wireless sensor has minimal network energy consumption; the computation method not only depends on the climate parameters and crop parameters, but also comprehensively considers economic efficiency of the crops and economy bearing capacity of farmers, so that utilization efficiency of water resources can be improved, and climatic variations can be effectively tackled; and meanwhile, consumption of network resources is greatly reduced by a dormant state of the wireless sensor, and a device life is improved.

The invention discloses a multifunctional climate data model and an application thereof. The multifunctional climate data model takes methods, such as an air temperature elevation regulation equation, a bilinear distance weighting interpolation, harmonic fitting and the like, as a basis to realize the generation of climate variables at any scale. According to data, by combining a species distribution model, tree species suitability distribution under a future climate condition can be predicted, and the basis is provided for tree species selection during the afforestation or reafforestation of a forestry department so as to improve forestry productivity. The climate data generated by the multifunctional climate data model also can provide long-term climate data support for a forest ecosystem growth model so as to improve the prediction precision of the growth model. According to a downscaling method provided by the invention, a plurality of atmospheric general circulation model prediction results of the Intergovernmental Panel on Climate Change can be converted at any scale so as to provide the data support for relevant researches under multiple models and multiple scenes.

The invention discloses a staging design flood derivation method in an integrated climate mode. The staging design flood derivation method comprises the steps: establishing a coupling model of a GCM and a VIC so as to predict the reservoir runoff process under the future climate change scene; through an arithmetic average method, obtaining an average state runoff process under a climate change scene; analyzing the runoff process by adopting a probability variable point method to divide a main flood period and a non-main flood period; constructing a reservoir design flood peak quantity most possible combination method calculation model through a Copula function; and taking reservoir prediction runoff data under a future climate change scene as input of a designed flood peak quantity combination method calculation model, and meanwhile, calculating the united design values of the reservoir under different recurrence period levels by considering multivariate same-frequency combination and most possible combination. The staging design flood derivation method has a strong statistical basis, and provides a new way for staged design flood calculation under a climate change scene.

The invention discloses a hydrological drought assessment method in a climatic change scene, which comprises the following steps: firstly, collecting meteorological, hydrological and topographic dataof a research area, and constructing an SWAT hydrological model database; obtaining a future meteorological sequence through a multivariable deviation correction method based on M global climate modes, and inputting the future meteorological sequence into an SWAT model to obtain M groups of future runoff sequences; calculating M groups of standardized runoff indexes, and extracting drought characteristic values through a run-length theory; calculating a key index PI influencing the regional drought, taking the key index PI as a covariable, and constructing a two-variable hydrological drought joint probability distribution function under a non-consistency condition; based on the most probable combined scene, separately solving drought duration and intensity of M groups of historical reference time periods and future time periods in different joint recurrence periods; and based on the medians of the M groups of most probable scenes, quantizing the change of the drought characteristic values, and evaluating the influence of climate change on the future hydrological drought situation of the drainage basin. The method is good in evaluation reliability, and provides a practical value fordealing with future climate disasters.

The invention discloses a drought and flood sudden turning risk assessment method. The method is based on hydrometeorological variables. The metod comprises the steps of: calculating an average time sequence Pt of continuous N time periods; extracting a time sequence Pt-1 lagging behind an N time period from the time sequence Pt-1; then, according to the time sequence Pt and Pt-1, determining drought and flood thresholds by using a threshold level method; and constructing a joint probability distribution function between Pt and Pt-1 based on a copula joint distribution function, and further constructing a condition distribution function model of drought-to-waterlogging and waterlogging-to-drought between Pt and Pt-1 to realize risk probability evaluation of drought-to-waterlogging and waterlogging-to-drought. After the model is established through the mode, the drought and flood sudden turning risk assessment method can effectively assess the possibility of drought and flood disastersin a certain period of a certain region, and can also predict the possibility of such risks in the region in a future climate scene according to meteorological data simulated and predicted in the future, thereby providing an accurate and reliable basis for resisting the drought and flood disasters and risk management decisions.

The invention discloses a design flood derivation method and system based on equal reliability in a climatic change scene. The invention belongs to the field of reservoir flood control safety design.A future climate change scene is obtained based on global climate mode output and a two-stage deviation correction method considering meteorological variable correlation; a VIC distributed hydrological model is driven to obtain a runoff situation considering the influence of climate change; a principal component analysis method is adopted to preferably select an extreme rainfall index influencingflood characteristics as a covariable; a time-varying hydrological frequency analysis model is constructed by considering inconsistency of a flood sequence, a flood design value combination under a climatic change scene is deduced based on an equal reliability method, a most possible value is adopted as a final design value, and a 95% confidence interval is selected to estimate uncertainty of thefinal design value. According to the method, the influence of climate change on flood characteristics can be fully considered, and an important reference basis with high operability can be provided for deducing adaptive design flood in a climate change scene.

The invention provides a runoff calculation and prediction method based on a watershed hydrological model. The method comprises the steps: building a watershed hydrological model, and constructing a feature region basic watershed database; dividing hydrological response units according to different characteristic area basic drainage basin data; inputting localized model data, and carrying out related data simulation; determining model parameters of the watershed hydrological model; verifying the correctness of the watershed hydrological model; and inputting meteorological data in the watershed in a future climate scene into the watershed hydrological model, and predicting the river runoff in the hydrological response unit. According to the rainfall runoff and rainfall runoff prediction method, the whole runoff production and confluence process in the drainage basin is considered, the water flow movement process of the whole drainage basin is simulated by inputting climate data, drainage basin data and land utilization data of the drainage basin, and the rainfall runoff and rainfall runoff prediction method can be well applied to simulation of river runoff of the drainage basin and is fast in rainfall runoff calculation and program response.

The invention relates to the technical field of reservoir scheduling, and provides a failure early warning analysis method of a reservoir scheduling rule under the influence of climate change, comprising the following steps: generating a plurality of groups of simulation runoff sequences according to air temperature and rainfall prediction information, a hydrological model and a stochastic simulation method under future climate change conditions; obtaining a plurality of groups of corresponding annual benefit samples based on a current reservoir scheduling rule; classifying the reservoir dispatching annual benefits by using the hydrological annual types to obtain classified reservoir dispatching annual benefits; through parameter estimation and goodness-of-fit test, screening an optimal probability distribution function suitable for the classified reservoir dispatching annual benefit out; based on the optimal probability distribution function and the acceptable risk level, determining a classified risk early warning threshold through inverse cumulative distribution calculation; by means of a probability change point analysis method, identifying the failure early warning time of the current reservoir scheduling rule under the future climate change condition. Through the steps, the time point when the reservoir regulation rule is changed can be prompted.

The invention discloses a method for predicting the suitable habitat of a ginkgo fruit forest based on climate and soil factors, and belongs to the technical field of species distribution prediction. The method comprises the steps of firstly, establishing a climate ecological niche model and a soil ecological niche model; predicting the habitat types of the ginkgo fruit forest by using the climate ecological niche model and the soil ecological niche model, and classifying the habitat types of the ginkgo fruit forest; carrying out verification test on the model and a prediction result through a seed field test; filtering the climate-suitable habitat by using the soil-suitable habitat; and predicting the change of the suitable habitat of the ginkgo fruit forest under the future climate scene. The two models are combined, the current and future under different climate change scenes can be predicted, the reliability of model output is verified through experimental data, the prediction process is more efficient, the result is more accurate, prediction of the habitat suitability classification model conforms to the knowledge of phytophysiology and economics, and the habitat suitability classification model has good application prospects. The method has important significance for guiding the production practice of the ginkgo fruit forest.

The invention relates to a method for quantitatively solving a basin water reserve change elasticity coefficient of the runoff, which decomposes the effective rainfall in the basis of a water balanceequation considering basin water reserve change into a difference between rainfall and basin water reserve change, and finds out the water reserve change elasticity coefficient of the runoff through further derivation on the basis. By adopting the technical scheme, when the rainfall, potential evapotranspiration, basin water reserve change and evaporation observed in a historical period exist, thesensitivity (namely the water reserve elasticity coefficient of the runoff) of the runoff to the basin water reserve change can be quantitatively solved. The sensitivity of the runoff is a relativelystable characteristic, so that the runoff change rate caused by the water reserve change under the human activity conditions of future climate change or underground water exploitation and the like can be estimated through the water reserve elasticity coefficient of the runoff obtained in the historical period, and a technical guarantee is provided for comprehensively evaluating the response of the water resource quantity under the change environment.

The invention provides a climate change risk analysis and evaluation method, which comprises the steps of determining climate variables and social and economic variables based on historical climate data, historical social and economic data and quantifiable climate policy indexes; respectively constructing a regional economic loss model, a meta-analysis loss model, an extreme disaster loss model and a department climatic loss model from top to bottom according to the climatic variable and the social economic variable; and determining comprehensive climatic change economic loss according to theregional economic loss model, the meta-analysis loss model, the extreme disaster loss model and the department climatic loss model. An economic model and a physical model are coupled, modeling is carried out based on historical data, social and economic risks caused by climate change are evaluated based on future climate change data, the influence of climate change on a social and economic systemis quantified, and probabilistic loss and income caused by climate change are obtained.

The invention discloses a drainage basin ecological space layout evaluation method, which comprises the following steps: collecting drainage basin ecological space data, calculating multi-index evaluation parameter characteristics in different time periods according to the drainage basin ecological space data, and constructing a drainage basin ecological space multi-parameter evaluation model according to the calculated multi-index evaluation parameter characteristics. The multi-parameter evaluation model adopts an entropy weight method to normalize indexes in parameter characteristics and determine entropy weight, and comprehensive evaluation of the ecological space layout of the drainage basin in different time periods is completed; according to the method, the ecological drainage basin is analyzed by adopting multi-sample data, fragmentation of the ecological layout of the drainage basin is analyzed and improved from multiple angles, a multi-parameter evaluation model is constructed, objective parameter weights are determined by adopting an entropy weight method, the problem of high subjectivity of weight determination is solved, and the evaluation method with high universality is obtained; and the evaluation result is used for reasonably planning the ecological space of the drainage basin, and reference and basis can be provided for next ecological planning locally in combination with future climate scene analysis, so that the method has remarkable practical significance.

The invention provides a future climate building multi-target energy-saving optimization method and system, and the method comprises the steps: generating future hourly climate data according to the obtained historical meteorological data and predicted monthly scale data; determining an optimization target and a decision variable; inputting the decision variable into the building model; importing the building model and future hourly climate data into energy consumption simulation software to obtain building energy consumption and thermal discomfort time; according to the building model, carbon emission in the whole life cycle is obtained through calculation; inputting the building energy consumption, the thermal discomfort time and the full-life-cycle carbon emission into a neural network, and fitting and outputting a target function; inputting the target function into a genetic algorithm to obtain a group of Pareto optimal solutions; and a linear weighted sum method is utilized to set weight coefficients according to requirements, and a final optimization scheme is obtained. Based on the method, the invention further provides an optimization system. According to the method, the influence of future climate change on the building performance is considered, so that the calculation result of the optimization target is more practical.

The invention discloses a passive residential building energy consumption prediction method based on future climate change, and belongs to the technical field of passive residential building energy consumption simulation prediction, and the method comprises the steps: 1, carrying out the downscaling of typical meteorological data, and generating a future climate meteorological file; 2, constructing a passive residential building three-dimensional model according to peripheral structure parameters and indoor thermal disturbance parameters of a specific building; and 3, importing the generated future climate and weather file and the created three-dimensional model of the passive residential building into Openstudio, and simulating and predicting the energy consumption condition of the passive residential building under the future climate change. According to the method, the energy consumption condition of the passive residential building under the future climate change can be estimated, whether the energy consumption change condition of the passive residential building meets the relevant design standard or not under the future climate condition can be predicted, and therefore relevant influence factor parameters are correspondingly improved.

The invention relates to a comprehensive assessment technology for influences and risks of future climate changes on biodiversity and belongs to the technical field of ecological environment protection and climate change. Based on the comprehensive investigation of the characteristics of biodiversity in China, the technology, by using climate change scenario pre-estimation technology, a Monte Carlo method, computer simulation, GIS and risk assessment technology, discipline theories and practices such as climatology and probability theory, establishes an influence and risk assessment index of climate change on biodiversity, a species distribution loss rule, a randomized climate scenario, and a combination of niche models and climate scenarios, simulates a climate change influence, and assesses the influences and risks of future climate changes on biodiversity. The technology is a technical measure for establishing biodiversity protection acclimatization change, protects the biodiversity, and has important social, economical and environmental benefits. The technology is good in operability, low in cost, low in maintenance cost, wide in application range, and especially suitable for the assessment of influences and risks of the climate changes on biodiversity in China.

The invention discloses a water resources stochastic planning method for adapting to climate change belonging to the technical field of water resources management, which comprises the following steps:A, coupling statistical downscaling method and hydrological model to predict the available water resources amount in a basin on the basis of future climate change data; B, coupling statistical downscaling method and hydrological model. B, take that maximization of water resource utilization benefit as the goal, taking the available water resource quantity, the water resource demand quantity, theecological water use protection, the technical requirement and so on as the constraint condition, constructs the optimized allocation model of water resources. C, that optimization model is disassemble into an upper linear sub-model and a lower linear sub-model by adopt an interval interactive algorithm, and the optimization solution of the model is carried out. The invention can comprehensively consider the social economic objective and the ecological protection, predict the water resources evolution trend under the climate change background, provide more scientific and reliable data input for the sustainable water resources regulation and control, and provide more robust decision support for the water resources manager.

The invention discloses a water resource planning method based on simulation and considering climate change used for supporting regional water resource management among different water departments under complex and uncertain conditions. According to the method, a plurality of prediction models is coupled to reasonably predict the surface water resource quantity in a research area and the water demand of each large water consumption department in the area, and compared with a single prediction model, the coupled prediction model can improve the prediction precision to a certain extent; and different climate change scenes are constructed to drive the coupling prediction model, so that the limitation of influence of future climate change on water resource allocation is effectively solved. Onthis basis, a double-layer multi-objective planning model considering multiple uncertainty is established, the constructed optimization model is effectively solved through a hybrid algorithm, and finally a reasonable water resource optimal configuration scheme for selection under consideration of climate change and scene analysis is obtained.

The invention discloses a grassland vegetation coverage estimation and prediction method based on remote sensing, and relates to a method for estimating and predicting grassland vegetation coverage by using remote sensing and meteorological data. The problems that an existing grassland vegetation coverage observation method is long in period and high in cost, and the future grassland vegetation coverage cannot be accurately predicted are solved. The method comprises the steps of obtaining and preprocessing a remote sensing and meteorological data set; performing spatial interpolation processing on the historical observation meteorological data set; extracting unchanged grassland vegetation distribution as a research area; calculating grassland vegetation coverage per pixel by using a pixel bipartite model; extracting grassland vegetation coverage and meteorological element values of pixel-by-pixel in the research area; constructing a grassland vegetation coverage estimation model under the influence of climate change by using multiple stepwise regression; and predicting the future grassland vegetation coverage in combination with the meteorological data under the future climate change scene. The characteristics that remote sensing data are easy to obtain and large in spatial scale are utilized, and a new method is provided for grassland vegetation coverage estimation and prediction.

The invention discloses a camptotheca acuminate distribution prediction method based on MaxEnt and ArcGIS. The camptotheca acuminate distribution prediction method comprises the steps of screening outimportant ecological factors from climate variables and soil variables; utilizing a MaxEnt model to predict potential distribution of the camptotheca acuminate only under the climate simulation condition and only under the soil simulation condition under the current and future climate scenes, and obtaining a climate and soil dual-adaptive region through layer superposition; and finally, predicting and quantifying changes of the camptotheca acuminate in a climate and soil double-height suitable habitat range under different climate change scenes. The construction is performed for the climate and soil environment of the camptotheca acuminate, and high-correlation variables are moved again, so that the influence of colinearity on the model precision is reduced. And layers of the two models are superposed, so that the influence of colinearity of climate and soil ecological factor variables on potential distribution of the camptotheca acuminate is avoided. Therefore, the limiting effect ofthe soil factor and the climate factor can be expressed more accurately.

A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

The invention relates to a statistical downscaling method based on non-stationary time series decomposition. The method comprises the specific steps of S1, downscaling data preparation; S2, decomposing a non-stationary time sequence; S3, selecting an optimal time sequence decomposition result; S4, training a random forest model; S5, synthesizing decomposition components of the time sequence aftertraining; S6, performing model evaluation; and S7, downscaling a future scene. According to the method, a statistical relationship is searched among steady-state components; therefore, the problem ofrelated statistical relationship consistency hypothesis in statistical downscaling is solved, the problem of scale mismatching always existing between a climate model and a hydrological model is solved, and a more reliable way is provided for basin response in a series of researches such as future climate change by utilizing the hydrological model.

The invention relates to a reservoir flood control risk estimation method suitable for climate change. The method comprises the steps of utilizing historical and future data provided by an ASD downscaling model and a global climate model (GCM) to calculate annual precipitation under each GCM historical and future scene; analyzing uncertainty of future rainfall by adopting a Bayesian model weightedaverage (BMA) method and a Monte Carlo sampling method; based on a GAMLSS model, analyzing a covariant relationship between annual precipitation of the reference period and P-III distribution parameters; substituting the precipitation of the future year into the covariant relationship, and analyzing the uncertainty of the design flood caused by the uncertainty of the precipitation of the year; and finally, obtaining a design flood hydrograph group by adopting a same-frequency or same-multiple-ratio amplification method, obtaining the highest flood regulation water level through reservoir flood regulation calculation, calculating the probability that the water level exceeds the design flood level, and obtaining corresponding flood control risk rates in different periods of a future scene.

The invention discloses a larch distribution change and productivity collaborative estimation method under climatic change conditions. The method comprises the following steps: determining larch artificial forest tree species parameters of a forest farm level 3PG model and forest farm level climatic data; and inputting tree species parameters and climate data of the artificial larch forest. According to the larch distribution change and productivity collaborative estimation method under the climatic change condition, distribution and productivity change of a forest farm larch man-made forest can be predicted at the same time, and the influence of climatic change on the larch man-made forest can be evaluated; according to the method, main climate limiting factors of growth of the larch under current and future climate change conditions and changes of distribution and productivity of the larch can be evaluated in detail, the changes influence one another under a unified framework, the method has biological interpretation significance, productivity main variables interested by forest managers are provided, and the forest managers can learn about the growth of the larch. And the distribution and growth potential of the future larch man-made forest can be cooperatively evaluated in space and time.

The invention discloses a method drawing up a multi-goal reservoir optimization scheduling graph capable of being self-adaptive to climate change. The method for drawing up the multi-goal reservoir optimization scheduling graph comprises the steps of: step 1. establishing a coupling model of a global climate model (GCM) and a variable infiltration capacity (VIC) hydrological model so as to forecast a run-off process under a future climate change scene; step two. establishing a multi-goal reservoir optimization scheduling graph model; and step 3. taking the forecast run-off process data under the future climate change scene as the input of the optimization scheduling graph model, and drawing up the multi-goal optimization scheduling graph model by adapting a self-adaptive genetic algorithm. The method for drawing up the multi-goal reservoir optimization scheduling graph has the advantages of balancing the social economy goal and ecological goal of reservoir scheduling, improving the comprehensive benefits of reservoir scheduling to the maximum degree on the condition of ensuring the flood control safety of a reservoir and being capable of being self-adaptive to future climate change and being widely applied to the production practice of multi-goal reservoir optimization scheduling.