105 results about "Aboveground biomass" patented technology

A method for estimating the aboveground biomass of rice based on multi-spectral images of an unmanned aerial vehicle (UAV), including: normatively collecting UAV multi-spectral image data of rice canopy and ground measured biomass data; after collection, preprocessing images, extracting reflectivity and texture feature parameters, calculating a vegetation index, and constructing a new texture index; and by stepwise multiple regression analysis, integrating the vegetation index and the texture index to estimate rice biomass, and establishing a multivariate linear model for estimating biomass. A new estimation model is verified for accuracy by a cross-validation method. The method has high estimation accuracy and less requirements on input data, and is suitable for the whole growth period of rice. Estimating rice biomass by integrating UAV spectrum and texture information is proposed for the first time, and can be widely used for monitoring crop growth by UAV remote sensing.

The invention discloses a method for joint inversion of forest aboveground biomass by integrating high-resolution CCD data, hyperspectral image data and laser radar point cloud data. According to themethod, first, geometric correction and stitching preprocessing are performed on airborne high-resolution CCD images, geometric correction and atmospheric correction preprocessing are performed on hyperspectral images, filtering and interpolation are performed on the laser radar point cloud data to generate a digital terrain model, and the point cloud data is normalized; second, texture features,spectral features and point cloud structural features are extracted based on three data sources obtained after preprocessing respectively; and last, models are constructed respectively in combinationwith ground measured data and extracted feature variables to predict the forest aboveground biomass. Through the method, the forest aboveground biomass of a subtropical natural secondary forest is extracted; and compared with aboveground biomass estimation results obtained by using other approximate remote sensing methods, the relative root-mean-square error of the method is lowered by 10% or above.

The invention provides a forest aboveground biomass inversion method fused with spectrum and texture features and a forest aboveground biomass inversion system fused with the spectrum and texture features. The method comprises the following steps of calculating an aboveground biomass of a research region sample plot so as to obtain a sample plot biomass observation value; performing geometric correction and radiometric correction on high-resolution remote-sensing image panchromatic data and multispectral data; respectively performing statistical regression on the sample plot biomass observation value and a corresponding spectrum feature vegetation index, and selecting a spectrum feature inversion model; extracting various texture feature variables under different windows, respectively performing statistical regression on the sample plot biomass observation value and the corresponding texture feature variables, and selecting a texture feature inversion model; determining a weight through a sensitivity analysis of a spectrum key factor and a texture key factor, constructing a spectrum texture feature combination inversion model of the biomass, and realizing the forest aboveground biomass inversion. The method and the system provided by the invention have the advantages that the spectrum features and the texture features are fused, and the advantages of the spectrum features and the texture features for biomass inversion are fully exerted, so that the quantitative inversion precision of a forest aboveground biomass is effectively improved.

The invention provides a method for comprehensively regulating and controlling soil for cultivating blueberries, which is simple and easy, and can ensure that the pH value of the soil is stabilized within an appropriate internal of soil pH values for a long time, promote the growth of the blueberries, remarkably improve the yield of the blueberries, and promote the quality of fruits. Raw materials comprise sulfur powder with the sulfur content of 99.9 percent (325 meshes), decayed larch needles, pine barks, and an acid compound fertilizer K2SO4, wherein the total nutrient content is more than or equal to 45 percent (N-P2O5-K2O, 12-21-12). The method comprises the following steps of: determining the pH value of a soil sample by potentiometry, and applying the sulfur powder to adjust the soil if the pH value of the soil is greater than the pH value which is mostly suitable for the soil; and spreading the acid compound fertilizer K2SO4 which serves as a base fertilizer according to the application amount of 3kg / 100m2, and shallowly turning the soil in the depth of 5 to 10cm after fertilizer application. By the method, the pH value of the soil can be reduced to 4.5 and can be stabilized within the range for 3 years, so the soil is extremely suitable for planting the blueberries. When the blueberries are planted in improved areas, the aboveground biomass is increased by about 5 times, and the content of mineral nutrition and the content of trace elements in the soil are both greatly increased.

A warm-season lawn grass winter green-maintaining growth-promoting agent and a method for making the same relate to a plant green-maintaining growth-promoting agent, providing a warm-season lawn grass winter green-maintaining growth-promoting agent capable of increasing chlorophyll content and overground biomass, reinforcing cold resistance and prolonging green period and a method for making the same. The growth-promoting agent comprises an A component, a B component and a C component, wherein the A component is a paclobutrazol triacontanol aqueous solution containing a latent solvent; the B component is a chitosan acidic aqueous solution; and the C component is proteolysis product quick-acting fertilizer. The method is as follows: paclobutrazol powder is dissolved in the latent solvent, and triacontanol and water are added so as to obtain the A component; chitosan and water are added in an acidic latent solvent, thereby obtaining the B component; and proteolysis product is dissolved by water, and then urea, potash magnesium sulphate fertilizer and water are added so as to obtain the C component.

The invention discloses a forest-biomass remote sensing inversion method based on spectral curve characteristic differentiation. Landsat 8OLI and actually measured data serve as a data source, and a forest-biomass leaf biomass and above-ground biomass inversion model which takes Landsat 8OLI red-light band reflectivity R, near-infrared band reflectivity NIR, red-light band central wavelength CW<R> and near-infrared band central wavelength CW<NIR> as characterization parameters is constructed. The model is good in inversion effect and provides a new technical method and means for rapidly, accurately and comprehensively estimating above-ground biomass of different forest community types in large stretches of forests.

The invention relates to a method for defining the degradation degree of a high-cold steppe. The method comprises the following steps of: (1) selecting a defining range; (2) determining various indexes of the degradation level of the high-cold steppe; (3) randomly selecting dozens of communities from the high-cold steppe and determining plant community dominant species in the high-cold steppe; (4) determining the coverage of graminaceous plants in each plant community dominant specie and initially classifying according to the indexes in the step (2); (5) determining the aboveground biomass relative scale of the plant community dominant species in each community and the aboveground biomass relative scale of edible grass and classifying once again according to the indexes in the step (2); (6) measuring the organic matter content distribution range of a surface soil sample of each community; and (7) comparing and verifying the organic matter content distribution range obtained in the step (6) with the organic matter content distribution range in the step (2) and finishing defining when the accuracy is over 90 percent. The method disclosed by the invention is simple, quick and accurate and ensures that the rehabilitation and protection of a degraded high-cold steppe are specific and scientific.

The invention discloses a low-temperature resisting method for festuca arundinacea by using air-dried sludge inoculants, which is implemented by comprising components including pseudomonas stutzeri, trichoderma reesei and yellow streptomyces 100-times diluent or pseudomonas stutzeri, trichoderma reesei and yellow streptomyces 200-times diluent. Development results of the invention show that the application of the complex microbial inoculants of pseudomonas stutzeri, trichoderma reesei and streptomyces griseoflavus can significantly improve the height, the aboveground biomass and the chlorophyll content of festuca arundinacea plants, and improve the cold resistance thereof. The regreening time of festuca arundinacea to which the complex microbial inoculants are applied is about five days earlier than that in a blank, and the comprehensive index of lawn appearance of regreened festuca arundinacea is also significantly higher than that in the blank, which fully shows the application potential of the complex microbial inoculants in practice.

The invention discloses a system and a method for quickly obtaining forest above-ground biomass. A forest crown image is accurately obtained by using an unmanned aerial vehicle system with high resolution, the crown area of woods is obtained by analyzing the forest crown image, the diameter at breast height of the woods is measured in field, a diameter at breast height and crown area regression equation and an above-ground biomass and crown area regression equation are established, the diameter at breast height of woods in a forest to be predicted is obtained through the diameter at breast height and crown area regression equation, the above-ground biomass of woods in the forest to be predicted is obtained through the above-ground biomass and crown area regression equation, and then the overall above-ground biomass of the forest to be predicted is obtained. The method provided by the invention is quick, effective, accurate in result and relatively low in cost, and is beneficial for popularization and wide application of unmanned aerial vehicle technology in forestry investigation.

The invention discloses an optical microwave cooperative inversion method and system for an urban above-ground biomass. The method comprises the steps of obtaining an AGB observation value of a samplebiomass by use of a sample area single-plant parameter data set acquired by a ground surface observation test; performing pretreatment to obtain a canopy height value CHM, surface reflectance data and a backscattering coefficient; extracting various LiDAR variables based on the CHM data, and extracting multiple optical characteristic vegetation indices based on the optical surface reflectance data, and simultaneously extracting multiple microwave characteristic variables based on the microwave backscattering coefficient data; extracting a biomass estimation value of an LiDAR data coverage area; selecting a sample for subsequent modeling and verification by use of a stratified random sampling method with the biomass value of the LiDAR data coverage area as a training and verification sample set; screening out an optimal optical and microwave characteristic variable by use of a variable screening method; and constructing an AGB-inverted optical model, a microwave model and an optical and microwave cooperative model, and selecting an optimal model to realize biomass inversion.

The invention discloses a grassland above-ground biomass retrievalinversion method based on high-time resolution and high-spatial resolution multispectral remote sensing data. The method comprises thefollowing specific steps: 1) selecting multispectral remote sensing data covering the a grassland growing season, calculating thean NDVI (Normalized Difference Vegetation Index), and synthesizing toobtain the monthly maximum NDVI covering the a research area; 2) interpolating according to the monthly mean temperature, the monthly total precipitation and the monthly total solar radiation data ofa meteorological station, to generate the monthly mean temperature, the monthly total precipitation and the monthly total solar radiation data covering the research area; 3) calculating the NPP (Net Primary Productivity) of the grassland by using a CASA (Carnegie-Ames-Stanford Approach) model based on the LUE (Light Use Efficiency) theory; 4) calculating the above-ground biomass of the grassland according to the NPP and the ratio of the above-ground biomass to the underground biomass.

The invention discloses an aboveground biomass estimation and scale conversion method oriented to a mean regional spectral unit, which mainly comprises the following steps: expression of remote sensing geoscience cognitive knowledge; Feature mining and screening; Homogeneous regional spectral unit segmentation; Biomass estimates at various scales. The invention can solve the problem that the current multi-scale biomass estimation mostly depends on the multi-resolution remote sensing image and the sampling of the field sample points under the multi-scale, and the introduction of the multi-source data makes up for the limitation of using only the optical data, and improves the operability of the fast estimation and conversion of the biomass under the different scales.

The invention discloses application of soaking seeds in mixed liquor in improving salt resistance of lawn plants; wherein, the mixed liquor is formed by 1.0g / L ammonium nitrate and 5-20mmol / L malic acid or citric acid based on the volume ratio of 1:0.01-0.03; salt resistance is saline soil containing 0.1-0.4% of salt. In the invention, after being applied to the mixed liquor, the soaking seeds have good promoting actions on salt resistance in height, chlorophyll, aboveground biomass, root growth and the like of two lawn plants and can provide a theoretical basis for pre-sowing treatment of the lawn plants and wider application of the mixed liquor in the lawn plant field.

The invention relates to the field of ecological environment monitoring, and discloses an arbor biomass measuring and calculating method based on an unmanned aerial vehicle hyperspectrum and a machinelearning algorithm, which is used for better realizing biomass monitoring of arbor of a target area type. The method comprises the following steps: acquiring a hyperspectral image of terrestrial plants in a target area by using an unmanned aerial vehicle, modeling based on the hyperspectral image, and extracting elevation information of a digital surface model; extracting spectral information from the original image photos, and performing quantitative inversion model training by adopting a machine learning algorithm according to types of terrestrial plant ecological environment monitoring vegetation classifications in combination with high-level information, characteristic wave bands and vegetation indexes of various plants in the target area to obtain an inversion model; classifying thevegetation types of the target area by using an inversion model so as to extract arbor classification data; and finally, calculating to obtain the arbor biomass by utilizing the extracted arbor classification data and combining with an aboveground biomass formula. The invention is suitable for arbor biomass measurement and calculation.

The invention discloses a combined soil additive composed of biological carbon and a nitrification inhibitor and a preparation method of the combined soil additive, wherein the combined soil additive are subjected to combined application under certain conditions to achieve the purposes of: 1) promoting the increase of aboveground biomass and yield of wheat, wherein the pot experiment shows that the wheat yield subjected to the combined application is respectively 80%, 65% and 103% higher than the wheat yield subjected to the single application of biological carbon, the single application of nitrification inhibitor and the application of no additive in the control treatment; 2) promoting the absorption and utilization of wheat to nitrogen, improving the nitrogen fertilizer use efficiency, wherein the pot experiment shows that the nitrogen harvest index compared with the control treatment without applying the additive is increased by 22%; 3) reducing the TN concentration in a runoff liquid and a leakage liquid as well as the TP concentration in the runoff liquid, so as to reduce the loss of nitrogen and phosphorus, avoid environmental pollution to the greatest extent; the combined soil additive has good economic and social benefits, and provides a useful reference for guiding the agricultural production.

The invention discloses a method for calculating the aboveground biomass based on UAV remote sensing images, and belongs to the field of UAV remote sensing application. The method includes the steps of obtains remote sensing images of a research area through a UAV and performing splicing, performing interpretation and analysis of the spliced remote sensing images, obtaining main information of trees in the research area, measuring diameter at breast height (DBH) information of the trees in a small area on the site, combining with crown breadth information of the obtained tree species, substituting into a DBH-crown breadth model: D=aCb, determining values of a and b in the model, and obtaining DBH-crown breadth model information of each tree species in the research area; substituting the DBH-crown breadth model information into a pre-established northeast China forest DBH-biomass empirical equation, and obtaining a crown breadth-biomass equation of each tree species in the research area; and through the obtained tree crown breadth information and a crown breadth-biomass model, calculating the aboveground biomass in the research area. The method can quickly obtain the biomass in theresearch area.

The invention discloses a foliar fertilizer promoting alfalfa seedling growth in acidic soil. The foliar fertilizer is composed by mixing a root growth solution, a mineral nutrient solution, an organic nutrient solution and clear water. Each liter of the foliar fertilizer contains 1-2ml of the root growth solution, 1-2ml of a plant nutrient solution, 3-5ml of the organic nutrient solution, and the balance clear water. The foliar fertilizer of the invention can effectively promote the growth and development of alfalfa seedling roots in strongly acidic soil, protect root activity and cell structures, relieve alfalfa seedling poisoning, and promote alfalfa growth. In a soil environment with pH of 4.5, the foliar fertilizer of the invention is adopted to treat alfalfa which has an average plant height of 5cm. The foliar fertilizer is sprayed once every 10 days and 2 times in total. 1-2L / m<2> of the fertilizer is sprayed every time. After 30 days of treatment, the alfalfa root biomass is increased by 1.5-1.8 times compared with a control one (only spraying water), and the aboveground biomass is increased by 1.0-1.4 times compared with the control one.

The invention discloses a method for improving winter resistance of turf by adopting household garbage compost offscourings. The ryegrass seedlings cultivated by compost and cold-hardened in cold environment with gradually decreased temperature have no obvious difference from the seedlings in the control group in indexes such as protective enzyme, proline and conductivity, but are slightly shorter. The aboveground biomass of the cold-hardened ryegrass seedlings cultivated by compost offscourings is reduced by 26.74% compared with that of the seedlings in the control group and is reduced by 23.21% compared with that of the seedlings with relatively poorer matix nutrition in the filter paper group. The final technical effect shows that the cold-hardened turf can fully resist winter in the winter environment of not less than 10 DEG C below zero in the outdoor balcony without being provided with a heating facility, and the aim of storing the turf in winter and producing all year around is achieved.

The invention belongs to the field of vegetation restoration, in particular to a method for restoring bald spots in alpine lakeside saline-alkali wetlands. It consists of the following steps: 1. Ridges on the surface of the bald spot treatment area; 2. Add 5-10 cm foreign soil to the bald spot treatment area; 3. Supplement grass in the bald spot treatment area; 4. Bald spot treatment The area is covered with film for insulation. The invention solves the problem that the high salinity and alkalinity of the bald spots in the grasslands in the alpine lakeside area hinders the germination of forage seeds and the high cold and low temperature in the early stage of forage growth, so that the temperature of the bald spot repair area is increased by 1-3°C; the number of seedlings can reach more than 7,000 plants / m2 , which is similar to the germination rate of pasture planted in farmland soil, the coverage is increased by 3 to 5 times, reaching 50%; the salinity is reduced by 20%, the water conservation rate is increased by 10%; the biomass on the ground is increased by 10 times, and the annual pasture output reaches 38.5kg / mu, and finally achieve the purpose of restoring bald spots in alpine lakeside wetlands.

The invention discloses a wettable powder composition based on trichoderma harzianum M-17 chlamydospore as well as a preparation method and application of the wettable powder composition. The wettable powder composition comprises chlamydospore powder, a carrier, a wetting agent, a dispersing agent and an ultraviolet protective agent, and the chlamydospore powder is obtained by performing amplification culture on trichoderma harzianum M-17 strains; the fungus type of the Trichoderma harzianum M-17 strain is Trichoderma harzianum, the preservation number of the Trichoderma harzianum M-17 is CCTCC NO: 2018538, the Trichoderma harzianum M-17 is provided by the Institute of Plant Protection, Academy of Agriculture and forestry Sciences in Ningxia, the M-17 contained in the wettable powder composition has an inhibition effect on pathogenic bacteria of soil-borne diseases of potatoes, reduces harmful fungi in soil and can promote the development of root systems, the soil nutrition absorption capability is enhanced, the stress resistance of the potatoes is improved, the growth promoting effect is achieved, the overground biomass accumulation is increased, and the yield is obviously increased.

The invention provides a method for purifying domestic wastewater by using willows through super deep flow, which comprises the following steps: restoring eutrophic surface water through a super deep flow method by selecting red willows with excellent flooding tolerance; taking twigs of annual robust willows, and cutting into cutting slips with a length of 10-15cm; by taking a phenolic foam board as a carrier, planting the willow slips, and pre-culturing to accelerate rootage; transferring the willow seedlings into a tank containing domestic wastewater, wherein the contact area of the rhizospheres with the water body is enlarged through the deep and developed root systems of the red willows in combination with a super deep flow manner; and enabling a nutrient solution to circularly flow through a pump, thus increasing the oxygen supply to the rhizospheres. According to the red willow-based super deep flow method, nitrogen and phosphorus in a water body are effectively absorbed and purified, the wastewater treatment amount is increased, and the purification efficiency is improved. No secondary pollution is produced; and the aboveground biomass can be periodically harvested for wattling use, thus having high economic benefits and landscape effect.

The invention provides a method, device and system for evaluating the community stability of an open pit coal mine dump. The evaluation method comprises the following steps of: establishing an evaluation hierarchy of the community stability of the open pit coal mine dump, wherein the evaluation hierarchy comprises: a target layer, a factor layer and an index layer, the target layer takes communitystability as an evaluation target, the factor layer comprises a community structure, community functions and a community environment, and indexes of the index layer comprise community diversity indexes, coverage, height, species number, overground biomass, underground biomass, soil moisture content, soil total nitrogen, soil available phosphorus and soil available potassium; Calculating the weight of each index in the index layer by using an analytic hierarchy process, and constructing a community stability evaluation system; And normalizing the indexes in the index layer, calculating a community stability index through an evaluation system and determining a community stability level. The technical problem that the ecological stability evaluation method in the prior art cannot accuratelyreflect the structural characteristics and the functional characteristics of the community is solved.

The invention discloses a method for determining the number of reasonable samples in forest aboveground biomass remote sensing estimation. The method comprises steps of taking two tree species, i.e.,pinus alpine and fir yunnanensis, as research objects, combining a Landsat 8 image and ground survey sample plot data, taking a k-NN remote sensing estimation model as a case and taking a root-mean-square error as an evaluation index based on a geostatistics semi-variance function theory; and calculating to obtain the number of samples when the precision of the pinus alpine and fir clovershanensismodels is optimal, and determining a reasonable sample number range. In order to discuss uncertainty of the number of samples in quantitative remote sensing inversion, the uncertainty influence of the number of samples in forest aboveground biomass estimation is analyzed based on a geostatistics semi-variation function theory and a k-NN model, and a reference basis is provided for a problem thatthe number of samples in traditional quantitative remote sensing inversion is difficult to determine.

The invention discloses a transcription factor derived from corn and new use of a coding gene thereof. The new use provided by the invention is a method using a coding nucleic acid molecule of ZmNLP1;1 to cultivate a transgenic plant. The method is a method for cultivating the transgenic plant with at least one characters of the following 1)-4): 1) aboveground biomass is higher than that of a receptor plant; 2) after induction of a nitrate, the nitrate transport protein gene expression is higher than that of the receptor plant; 3) after induction of the nitrate, nitrate reductase gene expression is higher than that of the receptor plant; and 4) after induction of the nitrate, nitrite reductase gene expression is higher than that of the receptor plant; and the method comprises a step for introducing a ZmNLP1;1 gene into the receptor plant; and the ZmNLP1;1 gene codes a protein shown in SEQ ID No.2. Experiments show that, in the condition of using nitric nitrogen (NO<3->) as a sole nitrogen source, the aboveground biomass and the total biomass of arabidopsis transgenic with the ZmNLP1;1 gene are increased significantly compared with that of receptor arabidopsis.

The invention discloses a method and a system for predicting the aboveground biomass of woody plants. The method firstly obtains input vectors (stem length, leaf number and root number of woody plants) and output vectors (fresh weight of stem and leaf and dry weight of stem and leaf of woody plants) of the BP neural network; constructing a BP neural network model for predicting aboveground biomassaccording to the input vector and the output vector; then the BP neural network model is trained in cycles according to several training samples, and the trained BP neural network model is generated,which can be directly used to predict the aboveground biomass of woody plants (fresh weight and dry weight of stem and leaf). The trained BP neural network model selects the phenotypic characteristics of woody plants (stem length, leaf number and root number) as independent variables, thus reducing the complexity and acquisition time of sample data acquisition, and eliminating the need of consuming a large amount of manpower and material resources; because of the close relationship between phenotypic characteristics and aboveground biomass, the prediction results have high accuracy.

The invention relates to a method for monitoring petroleum pollution in soil by utilizing community aboveground biomass indexes, belonging to the field of environmental pollution monitoring. The invention is realized by the following technical scheme: (1) establishing a plant / vegetation characteristic parameter forecasting model of total petroleum hydrocarbon content in the soil, which comprises the following steps: selecting a sampling point, measuring the plant / vegetation characteristic parameters of the sampling point, sampling the soil and measuring the total petroleum hydrocarbon content, and determining an optimal forecasting model of the total petroleum hydrocarbon content in the soil; and (2) computing the total petroleum hydrocarbon content in the soil of the monitoring point by utilizing the optimal forecasting model TPH=806.514-134.763ln(TBio), wherein TPH is the total petroleum hydrocarbon content in the soil, and the TBio is the total community aboveground biomass in the quadrat of which the area is 1m*1m. Compared with the traditional chemical analysis method of soil and plants, the invention has the advantages of simple and easy realization and low cost, can save a large amount of labor, financial resources and time and can realize the purpose of quickly monitoring the petroleum pollution in a large area.

The invention discloses a marsh wetland reed aboveground biomass estimation method, and relates to a marsh wetland vegetation aboveground biomass estimation method. In order to solve the technical problems that existing marsh wetland reed aboveground biomass field measurement is large in workload, long in period and high in cost, and biomass cannot be rapidly and accurately estimated and predicted, the method comprises the steps of obtaining normalized vegetation index data, earth surface observation meteorological data and actually-measured marsh wetland reed aboveground biomass data and preprocessing same; interpolating the surface observation meteorological data to obtain a numerical spatial distribution data set of each meteorological element; resampling the numerical spatial distribution data set of each meteorological element, and unifying projection coordinates; obtaining an annual vegetation index maximum value data set by using a maximum value synthesis method; extracting annual vegetation index maximum values and meteorological element values corresponding to the biomass sampling points; and establishing a biomass simulation and prediction model. The method can accuratelyestimate and predict the aboveground biomass of the marsh wetland reed, and is small in workload, short in period and low in cost.

The invention discloses a precipitation condition evaluation method, specifically comprising the steps: acquiring and preprocessing precipitation data of a meteorological station; generating precipitation grid maps of different years according to the obtained preprocessed precipitation data; calculating a precipitation average value from the initial year to the target year according to the precipitation grid map, and generating an annual precipitation average value grid map; and calculating a difference value between a target period year and the annual precipitation mean value to obtain a difference value grid map. The abundance, smoothness and insufficiency of the rainfall condition of the generation area are directly displayed in the difference grid map, and automatic updating can be achieved according to year updating, and the water demand in agriculture and animal husbandry production is further guided; and based on a geographic information system, the precipitation condition evaluation method is seamlessly linked with other ecological index data such as vegetation indexes, vegetation coverage, net primary productivity and aboveground biomass during correlation analysis.

The invention discloses a calculation method for litter layer rainfall interception. After the method puts forward a theoretical calculating formula, the coefficients of parameters required by the calculating formula are determined through an experiment, and finally, a reasonable and feasible calculation method is obtained. The method relates to parameters related to the rainfall interception, wherein the parameters comprise vegetation coverage, above-ground biomass, duration of rainfall, raininess and the thickness of a litter layer. A soil box device for simulating the litter layer environment is manufactured, and a control experiment is set to determine the coefficients of parameters in the calculating formula. Finally, the calculating formula is verified through experiment data, and the accuracy of the formula is improved. The method is high in rationality and accuracy, meanwhile, a relationship between the earth surface litter layer and rainfall is established to identify the regulation ability of the litter layer for the rainfall, and therefore, a scientific basis is provided for researching the hydrology mechanism of the litter layer.

The invention relates to a detection method for enhancing the quality of soils with different textures by adopting a waste rubber granule medium, comprising the following steps of: respectively adding rubber granules with the grain diameters of 0.05-0.1 mm, 0.1-0.2 mm, 0.2-0.3 mm and 0.3-0.4 mm to the soils, sandy soils and clays by taking ryegrass with better trampling resistance as experimental materials; and respectively measuring a germination number, stem length, chlorophylls, aboveground biomass and underground biomass in the growing process to be used as foundations for evaluating a turf medium. Comprehensive evaluation expresses that a soil group is optimally mixed by adding matrixes of 0.1-0.2 mm and 0.2-0.3 mm rubber granule processing groups, a sandy soil group is optimally mixed by adding the matrix of the 0.2-0.3 mm rubber granule processing group, and a clay group is optimally mixed by adding the matrix of a 0.05-0.1 mm rubber granule processing group. The invention can improve the quality characteristics of the soils by mixing four waste rubber granules with different grain diameters with three matrixes.