16 results about "Rainfall index" patented technology

The invention discloses a method for researching the cross-seasonal relation of rainfall abnormity in spring and summer in the middle and America, and the method comprises the steps: downloading a data set, and processing the data set to retain interannual signals; calculating Chinese American rainfall indexes in spring and summer by using the data; calculating a precipitation level phase transition index to obtain a transition type event and a persistent type event; further dividing the transition event and the persistent event into a positive event and a negative event; the physical mechanism of rainfall anomaly in the middle and American regions in spring and summer during the occurrence period of transformation and persistent events is studied; identifying and exploring the physical process of the sea temperature key area influencing rainfall anomaly in spring and summer; and exploring precursor factors influencing the cross-seasonal relationship of rainfall anomalies in spring and summer. The method solves the problem that in the prior art, cross-season continuous rainfall abnormity in the middle and American regions is not involved. According to the method, the precursor factors of the persistent events and the transformed events are identified, and the method has the potential to be applied to rainfall forecast in the middle and American regions, and provides reference for disaster prevention and reduction and agricultural production.

The invention belongs to the technical field of research on the relationship between snow drought and vegetation browning, and particularly discloses a quantification method and terminal equipment for the transfer relationship between snow drought and vegetation browning, and the method comprises the steps: obtaining a standard rainfall index, a nonparametric standardized snow water equivalent index and a normalized vegetation index in a preset time period of a research region; the snow drought grade of the research area is determined according to the non-parametric standardized snow water equivalent index, the snow drought type of the research area is determined according to the standard rainfall index and the non-parametric standardized snow water equivalent index, and the snow drought type comprises dry snow drought and warm snow drought; according to the normalized vegetation index, the standard rainfall index and the nonparametric standardized snow water equivalent index, determining the transmission time of vegetation browning caused by the corresponding type of snow drought; and according to the transmission time, determining the transmission probability of vegetation browning of different degrees caused by different grades and different types of snow and drought. According to the method, the transmission time and the transmission probability from snow drought to vegetation browning are quantified, and early drought monitoring and early warning can be improved.

The invention discloses a debris flow early warning judgment method and system, and belongs to the technical field of hydraulic engineering, and the method comprises the following steps: a, determining the gully bed longitudinal gradient and the area of a drainage basin formation region of potential gully-type debris flow through a topographic map; b, obtaining lithology types of gully-type debris flow, and classifying the lithology types of the gully-type debris flow; c, calculating topographic indexes of gully-type debris flow; d, calculating a rainfall index for inducing gully-type debris flow; e, calculating an early warning discrimination index of the gully-type debris flow; and f, according to the early warning discrimination indexes of the gully-type debris flow, dividing early warning levels of the gully-type debris flow with different lithology. According to the method, a quantitative comprehensive early warning judgment index is constructed, the scientificity and accuracy of judgment of the debris flow starting critical condition are remarkably improved, multi-stage dynamic early warning from extremely low risk to high risk is achieved, and a direct operable technical basis is provided for accurate implementation of graded emergency response and disaster prevention resource allocation.

The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to rainfall prediction technical field.The application discloses a kind of research area seasonal rainfall prediction method and system, it relates to

The present invention discloses a method for assessing the risk of construction project shutdowns based on rainfall indicators. By establishing a forecast model with actual precipitation and a 24-hour precipitation forecast as input conditions and the shutdown risk level as the output result, and matching corresponding response measures, a risk forecast text can be formed. When the actual precipitation and forecast precipitation data exceed the pre-set threshold indicators, the start-up conditions are met, and then the forecast model provides alarm information based on the actual situation and early warning information based on the forecast, so that project managers can make scientific decisions, improve the risk resistance of construction projects, and reduce losses caused by meteorological influences. The present invention solves the problem that project managers at existing construction sites rely on experience to deal with various types of weather, cannot make scientific decisions, and easily cause losses to the project.

The embodiment of the invention discloses a method and a system for identifying an asymmetric meteorological flood and drought sharp turn event. The method comprises the following steps: processing first rainfall data of a target area in a preset time on a time scale to obtain second rainfall data of a ten-day scale time sequence; according to the second rainfall data, generating a first standardized rainfall index of the target area in a single-ten-day-scale time sequence and a second standardized rainfall index of the target area in a multi-ten-day-scale time sequence, then, according to the first standardized rainfall index and the second standardized rainfall index, respectively determining a flood event and a drought event of the target area on the time sequence within the preset time, and finally, according to the flood event and the drought event of the target area on the time sequence within the preset time, determining the drought event. Therefore, the method can accurately recognize the flood and drought sudden turning event of the target area in the preset time, and has important theoretical significance and application value for risk assessment of extreme events and formulation of disaster prevention and reduction measures.

The application discloses a kind of mountain torrent disaster dynamic early warning index determination method based on multi-dimensional element coupling, comprising: collecting the real-time and historical risk hidden danger data of associated rainfall station, water level station, flow station, soil moisture station in dangerous area;Combining flood data to construct HEC-RAS two-dimensional grid rainfall model;Determine the flood inundation range by rainfall model simulation, and determine the flood control capacity of specified object, determine mountain torrent disaster early warning rainfall;Introduce river engineering facility hidden danger, early soil moisture content, regional geological data and the multi-dimensional mountain torrent influencing factor in current hydrological state of river channel and construct corresponding data model;Based on a group of dynamic early warning rainfall and coupling associated multi-dimensional mountain torrent influencing factor data model, used to correct initial early warning rainfall threshold, to form dynamic perception mountain torrent disaster early warning index.The application can form dynamic situation perception early warning rainfall index, realize the transition from static risk to dynamic risk.

The invention relates to the technical field of extreme rainfall indexes, and discloses a method for analyzing the contribution rate of a plateau extreme rainfall event driving factor based on an extreme rainfall index, and the method comprises the following steps: deploying a microwave transmitting end and a microwave receiving end at the col of the windward side of a plateau, and transmitting microwaves with specific attributes to the sky of the plateau through the microwave transmitting end; the feedback microwaves received by the microwave receiving end are subjected to characteristic comparison with the microwaves emitted by the microwave emitting end, and then rainfall event factors of the cloud layer above the plateau are obtained; the rainfall event factor specifically comprises a reflectivity factor and a velocity spectrum width of the feedback microwave. According to the plateau local heavy rainfall real-time detection method, the microwave receiving and transmitting device is arranged in the plateau windward side col, cloud layer rainfall event factors are directly obtained, the problem of monitoring blind areas caused by terrain shielding of a traditional meteorological radar is solved, specific-frequency microwaves penetrate through the cloud layer, feedback characteristics are analyzed, and the real-time detection capacity of plateau local heavy rainfall is remarkably improved.

The present invention discloses a method for quantitatively analyzing the driving factors of meteorological drought. By performing an inconsistency test on the standardized rainfall index (SPI) sequence and combining it with an analysis of the impact of human activities, the watershed type is identified. The entire study period is divided into a baseline period and a human activity period. The meteorological drought index of the two periods is analyzed and calculated to obtain the impact of human activities on meteorological drought and the impact of climate factors on meteorological drought, thereby quantitatively distinguishing the impact of the two factors on meteorological drought.

The present application relates to data processing, and provides a risk map generation method, device, equipment and storage medium. The method collects initial station rainfall data and pre-processes to obtain target station rainfall data, collects grid rainfall data and rainfall claim information, calculates index information of each preset rainfall index based on the grid rainfall data, selects a target index based on the index information and the rainfall claim information and extracts target information, corrects the target information based on the target station rainfall data to obtain correction data including intensity data and frequency data, updates the intensity data based on the frequency data to obtain a risk value, and identifies a preset map based on the risk value, thereby improving the accuracy and comprehensiveness of the rainfall risk map. In addition, the present application also relates to blockchain technology, and the rainfall risk map can be stored in the blockchain.

The invention relates to the technical field of drainage basin environment monitoring, and particularly discloses a drainage basin phosphorus loss hot spot area identification method based on hydrological connectivity, which comprises the following steps: firstly, determining a research area, extracting a drainage basin vector boundary, and acquiring soil total phosphorus content data by utilizing a GIS (Geographic Information System); then, data such as a digital elevation model and soil texture are obtained, the hydrological function connectivity index is obtained by calculating the relative smoothness, the sediment rainfall index and the surface runoff, and spatial distribution of the hydrological function connectivity index is defined; and finally, based on GIS (Geographic Information System) space overlay analysis, dividing regions by taking the 25th and 75th quantiles of the soil total phosphorus content and the hydrological function connectivity index as boundaries, and dividing the drainage basin phosphorus loss risk grades into high, medium and low classes, thereby identifying the drainage basin phosphorus loss hot spot regions. The method comprehensively considers hydrology and phosphorus content factors, is scientific and efficient, and provides a powerful basis for prevention and control of phosphorus pollution in the drainage basin.

The invention discloses a drainage basin sediment production forecasting method and system considering a rainfall accumulation effect and a medium. The method comprises the steps of data acquisition and collection; the early-stage influence rainfall is calculated, and the index attenuation type early-stage rainfall index APIt is calculated; constructing a threshold set, determining a short-window rainfall high threshold P3, high and low threshold P3, low, and determining a long-window rainfall high threshold PL, high and low threshold PL, low; representing a sand supply state; an event type judgment rule; event type judgment; sand reduction and recovery of continuous events; performing cold start treatment; calibrating parameters; according to the method, a multi-scale early-stage influence rainfall index, sand supply state characterization and a continuous event sand reduction factor are introduced, a'sand supply-sand transport capacity 'mismatch mechanism is systematically described, and the prediction stability and interpretability under different hydrological years and multi-event sequence conditions are improved.

The present application belongs to the technical field of disaster prevention and mitigation and hydrological information intelligent processing, and particularly relates to a method and system for mountain flood warning of a lack of data basin based on few-shot learning. The method comprises: collecting rainfall events of a source basin and a target basin respectively, and constructing a corresponding event scale rainfall sequence for each rainfall event; then extracting event level rainfall features from the sequence, and combining the event level rainfall features with a previous rainfall index to form an event level feature vector; subsequently, taking the historical mountain flood event labels of the source basin as the basis, the feature vector and the corresponding label of the source basin form a support set, and the feature vector of the target basin forms a query set; under the premise that the mountain flood warning model is not trained and parameter adjusted by using the target basin samples, the support set and the query set are jointly input into the model according to a preset rule, and the prediction results of each rainfall event of the target basin are output; when the prediction result is determined as a mountain flood event, mountain flood warning information is issued. The present application realizes cross-basin migration of mountain flood identification without retraining the model.

The invention provides an extreme rainfall external forced attribution method based on season-region decoupling. The method comprises the following steps: S1, acquiring multi-source data; s2, carrying out standardization treatment on the extreme rainfall index; s3, data space consistency processing; s4, risk area modeling; s5, seasonal characteristic quantity calculation; s6, performing time sequence noise reduction processing; s7, carrying out model verification and mutation detection; s8, multi-force signal decoupling is carried out; and S9, performing significance test and attribution quantification. Through fine analysis of the season scale, the limitation of traditional annual scale analysis is broken through, and the difference influence of external forces in different seasons is revealed; the multiple regression model and the three-signal decoupling framework provided by the invention realize independent contribution separation of man-made forcing and natural forcing, and solve the problem that multiple external forcing signals are mixed in the prior art; the method provides attribution results of regional differentiation, supports policy making, such as coping strategies of high-risk and low-risk regions and estimation under future emission scenes, and provides a basis for disaster prevention and reduction.

The invention discloses a research area seasonal rainfall prediction method and system, and relates to the technical field of rainfall prediction. Comprising the following steps: taking monthly average reanalysis data of historical ERA5 data of a research area as a historical forecasting factor set; dividing the research area according to longitude lines and latitude lines, determining a seasonal rainfall index according to the rainfall sum of each radial grid point and each latitudinal grid point at the historical moment, and decomposing the seasonal rainfall index into a plurality of physical components; determining a causal relationship between the plurality of physical components and a historical forecast factor set, and determining a key influence area of each historical forecast factor influencing each physical component; constructing a historical rainfall forecast sample set according to the key influence region, and training the wavelet neural network to obtain a regional seasonal rainfall forecast model; and inputting the real-time forecasting factor data into the regional seasonal rainfall forecasting model to obtain the seasonal rainfall forecasting intensity of the research region. The method can effectively improve the prediction accuracy of seasonal rainfall.

The invention relates to the technical field of rainfall prediction, and particularly discloses a method for predicting abnormal rainfall in the main flood season of Beijing, Tianjin and Hebei in summer, which comprises the following steps: constructing rainfall circulation indexes of the main flood season from the next half of July to the first half of August in the Beijing, Tianjin and Hebei region; calculating to obtain a rainfall circulation index value of a prediction period based on latitudinal wind field prediction data output by a mainstream numerical mode at home and abroad, and performing rainfall quantitative prediction through the rainfall circulation index value of the prediction period; the method comprises the following steps: establishing a unary linear regression relationship with global sea surface temperatures in March to June of each year on the basis of main flood season rainfall indexes from the next half of July to the first half of August in the Beijing-Tianjin-Hebei region constructed on the basis of historical related rainfall data from the next half of July to the first half of August in the Beijing-Tianjin-Hebei region, and obtaining key sea areas associated with main flood season rainfall index abnormity in the current year; and performing rainfall qualitative prediction by taking the sea surface temperature of the key sea area as a key index.