225 results about "Arid zone" patented technology

The invention provides an intelligent ecological restoration system, method and device for a high and steep slope of a strip mine in an arid region. Comprising a data acquisition layer which realizes real-time acquisition of multi-dimensional environmental data through InSAR satellite remote sensing, a ground sensor network and unmanned aerial vehicle multispectral imaging; the transmission layer adopts LoRa and 5G hybrid networking; the platform layer is used for constructing a slope stability prediction and restoration scheme optimization platform based on a digital twinborn model and a deep learning algorithm; and the application layer is used for remotely controlling the repairing device through a mobile terminal and a Web terminal and monitoring the repairing progress in real time. The problems that a traditional restoration technology is poor in adaptability, low in vegetation survival rate, high in ecological restoration cost, insufficient in monitoring technology application, insufficient in monitoring feedback mechanism, insufficient in intelligence, long in ecological restoration period and the like are solved.

The invention discloses a construction method for governing and repairing desertification degraded grassland in an arid area, and relates to the technical field of sand governing. The method comprises the following steps: evaluating a native vegetation type, vegetation coverage, a soil degradation and desertification degree, a soil type and a water resource condition; performing classified measures according to natural conditions, and determining different types of dune (flowing, fixed or semi-fixed) treatment measures; construction preparation; grid sand barriers are laid on the windward sides of the moving dunes and the semi-fixed dunes, and sand stabilization operation is conducted in a mechanical and manual combined mode; digging pits to plant indigenous shrubs subjected to special treatment, and using rooting water retention bags to improve the survival rate; the granular organic fertilizer and the seeds are mixed and stirred according to a certain proportion and then sown into soil at a time, the operation frequency is reduced, and precise fertilization is achieved. Through effective sand prevention and control measures, the sand wind damage is reduced, the living environment of farmers and herdsmen is protected, and the living quality is improved.

The invention relates to the technical field of ecological protection, and discloses a method for evaluating the stability of an ecological system in an arid region, which comprises the following steps: S1, constructing an index system, S2, performing multi-source remote sensing fusion, S3, performing response modeling on the ecological system, and S4, constructing a stability evaluation matrix in a sensitivity dimension; the method comprises the following steps: S1, constructing four-quadrant stability classification to carry out index weighting, S5, intelligently collecting ground sample points, and then combining an ecological change hot area graph, S6, carrying out model dynamic feedback optimization, and S7, outputting a result and carrying out zoning application, namely dividing a key protection and restoration area and supporting regional ecological safety pattern construction and continuous management. Through fusion of remote sensing data and intelligent acquisition and analysis of ground samples, dynamic updating and real-time monitoring of stability evaluation of the ecological system in the arid region are realized, and the effects of accurately reflecting ecological changes and providing efficient and timely data support for decision makers are obtained.

The invention discloses a high and cold arid region slope soil stability safety risk evaluation system and method, and relates to the technical field of slope engineering. The state of each side slope under multi-dimensional indexes such as freeze-thaw cycle frequency, dry-wet alternation index, wind erosion strength, shear strength, water content, porosity and fracture density is quantified, the feature similarity between any two side slopes is calculated, and then a side slope feature similarity matrix is formed. Based on the matrix, an unsupervised clustering algorithm (such as spectral clustering, similarity propagation and the like) can be adopted to divide a plurality of side slopes into similar subsets with structural characteristics similar to environmental response, and category attribution of risks is achieved. On the basis, structural variation analysis, historical instability statistics and central risk difference extraction are performed on similar slope samples, so that the internal instability tendency of the slope can be identified, and a risk prediction model suitable for the type of slope can be constructed through feature training.

The invention relates to the field of agricultural water resource management, in particular to a method, device and equipment for estimating irrigation water consumption and canal system water utilization efficiency, and the method comprises the steps: screening extreme meteorological and hydrological data meeting extreme rainfall scene conditions from historical meteorological data and hydrological data, calculating label data representing moisture storage and discharge capacity of an underground water change zone by combining net exchange flux at a deep soil boundary in an extreme rainfall scene, and constructing a space-time variable specific yield estimation model by combining a machine learning algorithm based on dynamic nonlinear influence and spatial heterogeneity of the extreme rainfall scene on soil moisture; training a specific yield estimation model by using the data set carrying the label data; and based on the dynamic similar characteristics of the soil moisture in the extreme rainfall scene and the irrigation scene, migrating the trained specific yield estimation model to the irrigation scene so as to estimate the irrigation water consumption and the canal system water utilization efficiency. Therefore, the problem of how to improve the parameter accuracy of the arid region is solved.

The invention provides an arid region saline-alkali soil treatment method which comprises the following steps: step 1, region division: dividing saline-alkali soil into a planting region and a saline-alkali water collection and treatment region; 2, a planting area is constructed, the planting area is composed of an original layer, a first water drainage and salt guide layer, an air permeation prevention layer, a second water drainage and salt guide layer and a planting layer from bottom to top, the air permeation prevention layer can prevent salt from ascending, and the water drainage and salt guide layer can drain saline-alkaline water in soil; and step 3, constructing a saline-alkaline water collection and treatment area, and performing filtration and electro-adsorption salt reduction on the collected saline-alkaline water to realize recycling of the saline-alkaline water. Layered improvement of the planting area is combined with an integrated structure of saline-alkali water collection, ion adsorption and storage, the salt content of soil is reduced, the nutrient content of the soil is increased, and all-round treatment and utilization of'blocking ', 'discharging', 'treating 'and'using' of the saline-alkali water are achieved.

The invention discloses a green three-dimensional planting system for promoting agricultural economic development in an arid region. The green three-dimensional planting system comprises a climate adaptation module; the weather prediction module is responsible for providing weather change prediction; the crop selection and crop rotation module is responsible for selecting suitable drought-enduring crops and implementing scientific crop rotation; the three-dimensional planting structure module is responsible for designing a reasonable three-dimensional planting framework according to the selected drought-enduring crops; the soil improvement module is responsible for adding an organic fertilizer and a modifier and improving the soil moisture retention capability; according to the invention, through weather prediction information provided by the climate adaptation module, the system can predictively adjust an irrigation strategy, and insufficient or excessive irrigation caused by sudden weather change is avoided. The intelligent irrigation module is combined with a neural network algorithm, the irrigation amount and time are accurately calculated and automatically adjusted according to the real-time meteorological data, the drought-enduring crop characteristics, the three-dimensional planting architecture and the soil improvement condition, accurate control over irrigation is achieved, and the utilization efficiency of water resources is remarkably improved.

The invention provides a method suitable for water retention of soil with different textures. In order to better perform size matching between the biochar and soil particles, particle size grading is performed on the biochar according to the size of soil aggregates, and three kinds of biochar with the particle size larger than 2.0 mm, the particle size ranging from 0.25 mm to 2.0 mm and the particle size smaller than 0.25 mm are obtained. The three kinds of biochar with different particle sizes are used in different types of soil respectively, and 5% of biochar with the particle size of 0.25-2.0 mm is selectively applied according to the water retention requirement of the arid area loam farmland; according to the drainage requirements of loam waterlogging areas with more rainfall, 5% of biochar with the particle size larger than 2.0 mm is selectively applied; and 5% of biochar with the particle size smaller than 0.25 mm is selectively applied for water and soil conservation of sandy soil in the arid region. By scientifically regulating and controlling the particle size and the application amount of the biochar, the biochar is matched with the specific properties of the soil, so that the water retention capacity of the soil is improved, and the soil efficiency is improved.

The invention discloses a drought disaster risk quantitative assessment method fusing an irrigation disaster reduction effect, and belongs to the field of disaster risk assessment, and the method comprises the steps: obtaining different meteorological data of a target region in a three-dimensional space grid scale, and calculating a drought index; a drought event is identified by using an ST-KMeans clustering method; drought events are screened and combined, the space overlapping degree of the clustered drought region and the historical disaster region is calculated, and risk loss data docking is carried out; generating a drought event characteristic dynamic data set, and measuring the drought event; and in combination with the land coverage and utilization data of the target area and the farmland irrigation area data, extracting irrigation response information serving as a drought adaptability measure, and carrying out irrigation disaster reduction capability quantification and risk assessment. According to the method, irrigation information can be integrated on the basis of drought event identification, the drought slow release effect of irrigation in different time and space scales is quantitatively evaluated, and a scientific basis is provided for drought disaster risk management and agricultural adaptability policies.

The invention discloses an arid region groundwater reserve estimation method and system based on multi-source remote sensing data, and relates to the technical field of groundwater monitoring, and the method comprises the steps: collecting land water reserve data and remote sensing image data of a target arid region, obtaining a land water reserve change sequence according to the land water reserve data, carrying out the region weighting of the target arid region, and obtaining a target arid region groundwater reserve change sequence; obtaining a land water reserve change sequence of the target arid region; based on the remote sensing image data of the target arid region, using a digital elevation model to obtain a surface water reserve change sequence of the target arid region, using a land surface process model to obtain a soil water reserve change sequence of the target arid region, and establishing an underground water reserve model of the target arid region; and performing error analysis on an output result of the groundwater reserve model by using a Monte Carlo simulation method. According to the method, through collaborative inversion of multi-source remote sensing data and integration of the groundwater reserve models, accurate quantification of spatial-temporal dynamic of the groundwater reserves in the arid region is realized.

The invention discloses an ecological restoration method for salinized land in a semi-arid region based on a natural solution. The ecological restoration method comprises the following steps: S1, defining a plurality of ecological restoration regions; s2, planting plants; in each ecological restoration area, high-layer plants are planted on a circle of the edge of the ecological restoration area, and a circle of middle-layer plants and a circle of low-layer plants are sequentially planted into the ecological restoration area; s3, arranging an ecological restoration area; according to the invention, an ecological restoration area with multi-layer plant distribution can be formed, the restoration and improvement of biodiversity are facilitated, and through the arrangement of the first groove, the sand barrier and the spacing between the first groove and the sand barrier, the purpose that seeds of plants in each layer stay in or near the first groove along with wind to achieve sowing and growth can be achieved in the subsequent year; multiple layers of plants along the first grooves are formed, the ecological restoration effect is enhanced, subsequent sowing through wind power is facilitated, and manual close planting is not needed any more.

The invention belongs to the technical field of strip mine dumping design and ecological restoration, and discloses a design method for a soil layer structure of an open pit coal mine dumping site in a western arid and semi-arid region. The invention aims to solve the problem of poor permeability of the viscous surface soil layer of the dumping site at present by optimizing the design of the soil layer structure of the open pit coal mine dumping site in the western arid and semi-arid region from bottom to top by taking low-cost industrial solid wastes as raw materials and designing a geologic structure of'water-resisting layer-water-bearing layer-surface soil layer '. And the later ecological reclamation of the waste dump is facilitated.

The utility model discloses an artificial breeding nest structure for breeding crayfishes in sandy soil in northwest arid regions, which is suitable for sandy soil water environment in northwest arid regions, and uses PVC (polyvinyl chloride) pipes as breeding pipes of the crayfishes, so that durability and corrosion resistance of a breeding device are guaranteed, and the breeding pipes have good light resistance and heat preservation. Circulating holes are further formed in the breeding pipes and used for helping water in the pipes to normally circulate, circulation of water bodies is ensured, water in the breeding pipes continuously flows, dissolved oxygen in the pipes is increased, a more suitable growth environment is created for the crayfishes, meanwhile, during breeding of the crayfishes, separated crayfish eggs can be collected through the breeding net, and the breeding efficiency is improved. The crayfish can be prevented from escaping all around, so that the economic loss is avoided; the product effectively solves the problems of a traditional nest in a sandy soil water body, improves the breeding efficiency and survival rate of the crayfish, and improves the production economic benefits of crayfish farmers in the northwest arid region to a certain extent.

The invention discloses a machine learning and multi-source variable-based high-precision prediction method for soil organic carbon in an arid region, and solves the problems of high spatial heterogeneity of soil organic carbon in the arid region and high traditional detection cost. The method comprises the following steps: collecting a soil sample by adopting layered random sampling, and integrating seven types of environmental variables such as climate, vegetation, terrain and remote sensing to construct a feature set; a Boruta algorithm is adopted for screening, an optimized feature set is obtained, and redundant data are eliminated; the method comprises the following steps: dividing a training set and a test set through Kolmogorov-Smirnov test; the method comprises the following steps of: generating 100 base models by using parameter optimized random forest and extreme gradient lifting double-model collaborative prediction and combining a Bootstrap integration strategy; inputting the target area optimization feature set to obtain an organic carbon prediction result; according to the method, the monitoring cost is effectively reduced, spatial-temporal dynamic inversion of soil organic carbon based on historical environment variables is supported, and a reliable technical scheme is provided for dynamic monitoring and ecological management of soil carbon.

The invention relates to the technical field of artificial intelligence, and discloses a gobi desert surface temperature prediction method based on deep learning. According to the method, a system architecture in which an acquisition end, a remote sensing end, an edge computing terminal and a central server cooperatively operate is constructed, and fusion and real-time transmission of multi-source observation data are realized. By designing a space-time neural network model fused with physical constraints, combining an angle-guided convolutional neural network and a gated cycle unit structure, and introducing surface energy balance and Stefan-Boltzmann radiation consistency constraints, high-precision prediction and physical consistency modeling of surface temperature are realized. And a cross-scale reconstruction and missing detection complementation mechanism is adopted, so that the spatial continuity and resolution of a prediction result are improved. According to the method, high-precision, stable and self-adaptive prediction of the surface temperature of the gobi desert area is realized, and intelligent support is provided for meteorological monitoring, ecological evaluation and early warning decision making of the arid area.

The provided is a modeling method of tropospheric delay for arid-areas including sandy, gobi and desert regions based on GNSS. The modeling method incudes: obtaining a troposphere zenith hydrostatic delay ZHD and a troposphere zenith wet delay ZWD by utilizing a GPT-3 model, and summing to obtain a troposphere zenith total delay ZTD; inversely calculating the ZTD by utilizing a ground-based GNSS, obtaining a high-precision ZWD inversed by the GNSS by calculating a difference between the ZTD and the troposphere zenith hydrostatic delay ZHD obtained by a Saastamonien model, inversely calculating an atmospheric weighted average temperature T′m by utilizing an ERA5 data set, performing linear correction to obtain a corrected temperature Tmr, and calculating a priori value ZWD0 of the high-precision ZWD; and correcting the ZWD0, and adding the corrected ZWD0 with the ZHD to obtain a corrected value of the high-precision ZTD.

Provided is a method for determining a proper plant spacing for vegetation ecological restoration in an arid region. The method includes the following steps: step 1, acquiring soil parameters and soil water parameters in a survey region; step 2, determining vegetation parameters for the survey region; step 3, collecting hydrological data of the survey region; step 4, determining a transpiration of a dominant plant species in a vegetation community of the survey region; step 5, calculating a thickness of a shallow groundwater action layer in the survey region; step 6, determining a thickness of an available water absorption layer; step 7, determining a water content within the thickness of the available water absorption layer; and step 8, determining the proper plant spacing for a vegetation. The method can effectively solve the problem of desertification of oases in arid regions.

The invention discloses an arid region identification method based on a GRACE satellite, and the method comprises the steps: obtaining satellite remote sensing original data, carrying out the median filtering of the satellite remote sensing original data, and obtaining noise reduction data; complementing missing data for the noise reduction data to obtain complemented data; calculating a normalized vegetation index and a temperature vegetation drought index according to the complementation data to obtain a drought index; time sequence features are extracted according to the drought indexes, principal component analysis is carried out on the time sequence features, and comprehensive indexes are obtained; spatial clustering analysis is carried out on the comprehensive indexes, and target areas with similar drought characteristics are divided; calculating a topographic relief degree and a land utilization type proportion based on the target area in combination with the land utilization data and the topographic data; selecting a target area of which the topographic relief degree is greater than a preset threshold value, and performing topographic correction on the drought index of the selected target area to obtain a corrected drought index; and judging the drought grade of the target area according to the corrected drought index and the land utilization type ratio.

The invention belongs to the technical field of photovoltaic solar power station park rainfall irrigation, and discloses an arid area grassland photovoltaic system under-panel irrigation monitoring method, system and device. According to the method, a monitoring device is used for monitoring the soil humidity under a current arid area photovoltaic park (grassland photovoltaic system) panel in real time, and when the soil humidity is lower than a threshold value set by a user, the monitoring device starts a water suction pump to work through an internal processor; meanwhile, the monitoring device controls the opening degree and the opening and closing time of an intelligent switch electromagnetic valve additionally arranged on a tee joint or a four-way joint in the transverse pipe and longitudinal pipe connecting device; and the remote arid area grassland soil monitoring end performs comprehensive treatment according to the current soil humidity to obtain an optimal soil humidity and soil salinity and alkalinity combined value. The soil humidity around the drip irrigation opening of the underground drip irrigation pipeline can be monitored, the water suction pump is turned on and turned off through the monitoring center device, and the water utilization efficiency of vegetation of a grassland photovoltaic system in an arid region is improved.

The invention provides a remote sensing estimation method for high spatial-temporal resolution crop evapotranspiration in an arid and semi-arid region, which comprises the following steps of: acquiring cloudless or less-cloudless high spatial resolution optical remote sensing data of a crop growing season in a research region, and calculating or inverting remote sensing earth surface parameters required by high spatial resolution evapotranspiration; comprising a vegetation index NDVI, a leaf area index LAI, a vegetation coverage FVC, a surface water index LSWI and a surface albedo; the method comprises the following steps: acquiring meteorological reanalysis data of daily scales ERA5-Land and GLADAS of a research area, wherein the meteorological reanalysis data comprises relative humidity RH, average temperature Ta, air pressure Pa, solar short-wave radiation # imgabs0 #, downward long-wave radiation # imgabs1 # and upward long-wave radiation # imgabs2 #; according to the technical scheme, multi-source remote sensing data, an evapotranspiration physical model and a space-time fusion technology based on evapotranspiration characteristics are utilized, and estimation of high space-time resolution evapotranspiration of the arid and semi-arid agricultural areas is achieved.

The invention discloses a risk dynamic analysis method for a vegetation phenological period in an arid region, and the method comprises the steps: constructing a spring phenological model and an autumn phenological model in different partitions according to the partitions of different growth season initial periods SOS and growth season final periods EOS of plants in the arid region; respectively calculating vegetation growth risk coefficients of different growth season initial stage SOS partitions and growth season final stage EOS partitions; carrying out weight fusion on the vegetation growth risk coefficients to obtain a long-period vegetation growth risk comprehensive coefficient F in the arid region; calculating an ecological groundwater drought risk coefficient; calculating a vegetation risk dynamic coefficient of the arid region; and evaluating the growth risk of the vegetation in the arid region in the phenological period. According to the method, the drought risk influence coefficient is comprehensively calculated by utilizing representative feature data corresponding to different subareas and phenological areas, and comprehensive analysis of vegetation risk assessment in the arid area is realized by combining the ecological underground water drought risk coefficient on the annual scale.

The invention belongs to the field of remote sensing technology application, mainly aims at three typical grassland ecological system types of desert, grassland and meadow in an arid region, and discloses a grassland ecological health four-dimensional quantitative evaluation method based on multi-source remote sensing data. Comprising the following steps: S1, data fusion and long-time-sequence base construction: aiming at three typical grassland ecosystems of desert, grassland and meadow in an arid region, integrating long-time-sequence multi-source remote sensing images and auxiliary environment observation data, and reconstructing a model through a space-time fusion algorithm and missing data; and constructing a long-time-sequence multi-dimensional raster data set which is consistent in spatial resolution and covers non-biological background conditions. According to the system, accurate evaluation of long-time-sequence comprehensive conditions of different typical grassland types in the arid region is realized, the input information dimension and quality of the evaluation model are remarkably improved, and the ecological health problem is innovatively and accurately diagnosed from the deficiency of system bases, functional vitality, structural tissues or stress resistance recovery capability on the spatio-temporal scale.

The invention provides a method for planting spring corn in a dry sloping field, and belongs to the technical field of agriculture. According to the technical system, through a three-level combination scheme of structural water storage, process regulation and control and systematic rotation, the transformation of dry-farming corn production from passive drought resistance to active water transfer is realized. Compared with a traditional mode, ineffective rainfall is converted into water available for root systems through deep scarification water storage and furrow rainwater collection; the resource waste is reduced by dynamic supplementary irrigation and slow-release fertilization, and a'small-amount and multiple-time 'supply rule of the semi-arid region is met; the crop rotation system remarkably improves the system stability through leguminous crop nitrogen fixation and corn high-light-effect complementation. According to the embodiment of the invention, the technical system provided by the invention realizes the breakthrough of 689.36 kg / mu of spring corn yield and 2.38 kg / m < 3 > of water utilization efficiency in the loess plateau semi-arid region, and provides a reproducible technical normal form for the arid region with annual rainfall of 400-500mm.

The invention discloses a method for manufacturing a simulated earthen ruins rammed earth test wall based on original diseases, and relates to the field of earthen ruins protection and restoration. The method comprises the following steps: step 1, determining earthen archaeological site diseases to be researched and preparing materials; 2, mold assembling and disease marking are carried out; 3, layered ramming is conducted; step 4, crack disease processing; step 5, performing undercutting disease processing; 6, weathering disease processing; step 7, processing rain erosion diseases; and step 8, northwest environment simulation. The earthen archaeological site rammed earth wall is manufactured by integrating multiple disease collaborative simulation technologies of fissure, undermining, weathering and rain erosion, meanwhile, adaptability design of a strong wind erosion area, a strong sunshine area and a strong salinization area is made for northwest arid areas, and the method has the core advantages of disease reproduction authenticity, standardized grading, environment adaptability and the like; a scientific and reasonable technical means is provided for earthen archaeological site protection engineering, and a reliable test piece is provided for research and development of a protection technology.

The invention relates to the technical field of environmental protection and monitoring, and discloses an arid region oasis water environment ecological safety early warning method, which comprises the following steps: step 1, constructing a sky-air-land-water three-dimensional monitoring network, the monitoring network comprises a satellite remote sensing monitoring subsystem, an unmanned aerial vehicle remote sensing monitoring subsystem, a ground sensor monitoring subsystem and an underwater monitoring subsystem, and the monitoring network is used for acquiring multi-scale and multi-element water environment ecological data; step 2, establishing an ecological safety evaluation index system of the oasis water environment in the arid region, the evaluation system including four first-level indexes of hydrology and water resource dimension, water environment quality dimension, ecological health dimension and social economy dimension, and setting a plurality of quantifiable second-level indexes under each first-level index. A combined prediction model in which a Markov chain and a long-short-term memory neural network are coupled is adopted, and a system dynamics scene simulation method is combined, so that the perspectiveness and scene adaptability of the early warning method are effectively enhanced.

The invention discloses an arid and semi-arid region water consumption threshold determination method and device based on water balance, and the method comprises the steps: determining the change of land water reserves, and constructing a first function relation between the change of land water reserves and water consumption redundancy; the water consumption redundancy represents the rainfall surplus degree when the water amount balance is maintained; the land water reserve change is the difference between the land water reserve at the ith moment and the land water reserve at the (i-1) th moment; calculating the water consumption redundancy and the evapotranspiration total water consumption threshold value based on the first function relation when the water amount is balanced; establishing a second function relationship between the land water reserve change and the main water consumption redundancy, and calculating a main water consumption threshold value when the water amount is balanced; and establishing a relationship between the main water consumption factor and the main water consumption threshold value to determine the water consumption threshold value of the arid and semi-arid region. The method provided by the invention can provide reliable reference for quantifying the water consumption threshold value of the arid and semi-arid regions, and has important practical significance for reasonable allocation of water resources and promotion of agricultural and ecological sustainable development.

The invention relates to the field of ecological hydrology, and discloses an arid and semi-arid region plant ecological water consumption calculation method, which comprises the following steps: acquiring meteorological, soil and vegetation phenological data; constructing a root system depth dynamic evolution model, and updating the maximum depth of the root system day by day; determining the depth weight of the effective moisture extraction layer based on the dynamic root system distribution; calculating the weighted average effective soil water content; and outputting daily-scale ecological water consumption in combination with the corrected transpiration scale model. By coupling meteorological driving, soil moisture stress and a dynamic regulation and control mechanism of a plant growth stage on a root system, the water consumption inversion precision is remarkably improved, the root-mean-square error is reduced by more than 25% through actual measurement verification, and a high-precision quantification tool is provided for ecological water demand evaluation and water resource management.

The invention relates to the technical field of arid region ecological evaluation, and discloses an arid region ecological sensitivity evaluation method, which comprises the following steps: S1, multivariate data acquisition: acquiring land and land data by utilizing a satellite remote sensing image, acquiring topographic data by utilizing a DEM (Digital Elevation Model), acquiring a spectrum at a mineral sensitive wave band by utilizing a hyperspectral sensor, and acquiring a mineral sensitive wave band; a low-altitude unmanned aerial vehicle is used for carrying a multispectral camera to obtain vegetation disease and pest data, and the data are preprocessed and fused; s2, factor selection: selecting a landform factor, a vegetation factor, a soil factor, a water resource factor, a climate factor, a human activity factor, an ecological system service function value factor and a landscape connectivity factor; and S3, multi-factor grading evaluation: dividing the factor original data into five grades. Through multivariate data acquisition, hyperspectral remote sensing is used for acquiring mineral spectrums, and the unmanned aerial vehicle is used for acquiring fine vegetation disease and insect pest data, so that the problem of unreliable evaluation results caused by single source of existing ecological sensitivity evaluation data is solved.

The invention provides an arid region salt marsh grassland wetland water supplement regulation and control method and a related device, and the method comprises the steps: determining the ecological water demand and deficiency corresponding to a target region according to the wetland vegetation evapotranspiration, precipitation and underground water-soil water exchange flux of the target region in a target time period, the target area is any area in the salt marsh grassland wetland in the arid area; determining a water quantity adaptive gap corresponding to the target area according to the earth surface water supplementing quantity and the ecological water demand deficit quantity of the target area in the target time period; and performing water supplementing regulation and control on the target area according to the water quantity adaptive gap. According to the accurate evaluation result of the water volume adaptation gap, a refined drip irrigation technology is adopted to carry out ecological water supplementation on the salt marsh grassland wetland, the requirements of plants for water in all stages of the whole life cycle are ensured, and the stability and adaptability of a wetland ecological system are improved; and multi-target collaborative development of hydrological communication, biodiversity improvement, habitat optimization and the like of the wetland ecosystem is realized.

The invention discloses a method for repairing a karst mountain land in an extremely arid area under the condition of no soil collapse, belongs to the field of mine repairing, and aims to solve the problems that a certain strip mine belongs to a desert gobi area, the main type of soil is gypsum ash brown desert soil, the precipitation amount is small, the evaporation amount is large, and phytoremediation is difficult. The remediation object is the desert gobi area mine soil, the soil is mud left after mineral products are removed and the mineral products are deeply excavated by hundreds of meters, and the mud comes from hundreds of meters underground and hardly contains microorganisms; meanwhile, the saline-alkali content of the soil is very high. Different from the prior art, the remediation method provided by the invention adopts a manner of not killing soil, adopts the suaeda salsa as a remediation plant, and adopts a drip irrigation manner to ensure the water supply of the suaeda salsa, so that the remediation of the mine soil is realized. According to statistics, the total irrigation quota of the whole growth period of the suaeda salsa is 80-100 m < 3 > / mu, and the water consumption is obviously lower than the water consumption required by an existing remediation scheme.