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 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 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 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 reservoir adaptive scheduling method based on the D-S evidence theory, which is characterized by including the following steps: S1, predicting the temperature and precipitation within a future research time through GCMs (Global Cycle Model) and a downscaling technology, taking the prediction result as the input predicted runoff of a hydrological model, and taking the runoff prediction results output by GCMs as multiple future climate change scenarios; S2, constituting a recognition framework with each potential climate change scenario as a focal element Theta in the D-S evidence theory; S3, defining corresponding basic probability assignment functions m1, m2 and m3; S4, synthesizing three evidences based on a modified D-S synthesis rule, and calculating the synthesis probability m123 of the scenarios; S5, letting the weight Alpha of each scenario be equal to a trust function; and S6, constructing a reservoir optimal scheduling model with the maximum weighted average of the average benefits over the years as an optimization objective, setting a linear scheduling function, and optimizing the parameters of the scheduling function through a simulated optimization approach to get an adaptive scheduling scheme.

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 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 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 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.

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.