Evapotranspiration estimation method and computer storage medium in karst basin based on distributed two-dimensional daily model

Abstract

The present invention discloses a karst basin evapotranspiration estimation method and a computer storage medium based on a distributed two-dimensional daily model, and belongs to the technical field of karst basin evapotranspiration estimation. The method includes: selecting a typical karst basin for continuous hydrological and meteorological observations; obtaining multi-source remote sensing data, conducting continuous observations of the basin underlying surface, and obtaining the change information of the underlying surface of the typical karst basin; measuring evapotranspiration in situ experiments, and analyzing the correlation between the evapotranspiration of different underlying surfaces and climate factors; using multivariate statistical analysis to calculate the degree-day factor matrix and establish a two-dimensional daily model of evapotranspiration; preliminarily calculating the distributed basin evapotranspiration based on the two-dimensional daily model of evapotranspiration, and evaluating the accuracy of the two-dimensional daily model of evapotranspiration in combination with hydrological and meteorological observations to obtain an accuracy evaluation result; correcting model parameters and improving the two-dimensional daily model of evapotranspiration; calculating the evapotranspiration of the target basin based on the two-dimensional daily model of evapotranspiration, and providing accurate parameters for hydrogeological research.

Description

Technical Field

[0001] The invention relates to the technical field of evapotranspiration estimation in a karst watershed, and more particularly to a karst watershed evapotranspiration estimation method based on a distributed two-dimensional daily model and a computer storage medium. Background Art

[0002] Evapotranspiration (ET) is the process by which water changes from liquid or solid to gas and enters the atmosphere. It consists of vegetation interception evaporation, vegetation transpiration, soil evaporation and water surface evaporation, involving multiple complex elements such as soil, water surface, vegetation and atmosphere. This process is not only an important carrier of energy transmission in the energy cycle, but also a key link connecting water, heat and carbon cycles. It is also an important component of the land surface water cycle and an important component of energy balance. How to calculate evapotranspiration at different scales has always been one of the focus issues in the research of hydrology, geography, meteorology, ecology, vegetation, soil science and other disciplines.

[0003] There are many existing evapotranspiration estimation / simulation methods. However, since evapotranspiration is continuous and variable in time and heterogeneous in space, and the underlying surface is variable in time and non-uniform in space, the current evapotranspiration estimation / simulation methods have the following three common problems:

[0004] First, the remote sensing evapotranspiration estimation model has obvious theoretical flaws. The mathematical basis of the model is the energy balance equation, which is a mechanistic model. Its biggest theoretical problem is that it does not consider horizontal energy transmission, which is obviously inconsistent with Darcy's law. The movement of groundwater is both vertical and horizontal, and the energy transmission in the horizontal direction is generally not less than that in the vertical direction.

[0005] Second, the observation method of the remote sensing evapotranspiration estimation model is flawed. The remote sensing observation method uses discrete sampling on a time scale, using instantaneous data from one point (the time point when the remote sensing data is obtained) to replace at least one day's data (using MODIS data to replace 16 days), ignoring the continuous variability of evapotranspiration in time.

[0006] Third, the mathematical accuracy of the remote sensing evapotranspiration estimation model cannot be calculated. The most sensitive parameter of the remote sensing evapotranspiration estimation model is the land surface temperature. At present, the highest accuracy of the land surface temperature inverted under ideal conditions (clear sky conditions with uniform surface and accurately known emissivity) using remote sensing technology (MODIS and AVHRR data) is 1°C. The reality is that the underlying surface is non-uniform, the weather is changeable, and ideal conditions are difficult to achieve. The accuracy of land surface temperature inversion under non-ideal conditions cannot be calculated at present, and the reliability of the model cannot be guaranteed.

[0007] In summary, the existing evapotranspiration estimation / simulation methods result in inaccurate final evapotranspiration estimates.

[0008] Therefore, how to provide a karst basin evapotranspiration estimation method and computer storage medium based on a distributed two-dimensional daily model that can solve the above problems is an issue that technical personnel in this field urgently need to solve. Summary of the invention

[0009] In view of this, the present invention provides a karst basin evapotranspiration estimation method based on a distributed two-dimensional daily model and a computer storage medium, which provides a solution for how to obtain high-precision evapotranspiration at the karst basin scale.

[0010] In order to achieve the above object, the present invention provides the following technical solutions:

[0011] On the one hand, the present invention provides a method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model, comprising:

[0012] Select typical karst basins for continuous hydrological and meteorological observations;

[0013] Acquire multi-source remote sensing data, conduct continuous observation of the underlying surface of the watershed, and obtain information on changes in the underlying surface of typical karst watersheds;

[0014] In-situ experiments were conducted to measure evapotranspiration and analyze the correlation between evapotranspiration and climate factors on different underlying surfaces;

[0015] Based on the correlation between evapotranspiration of different underlying surfaces and climatic factors, multivariate statistical analysis was used to calculate the degree-day factor matrix and establish a two-dimensional daily model of evapotranspiration.

[0016] Based on the two-dimensional daily evapotranspiration model, the distributed basin evapotranspiration is preliminarily calculated, and the accuracy of the two-dimensional daily evapotranspiration model is evaluated in combination with hydrological and meteorological observations to obtain the accuracy evaluation results.

[0017] According to the results of the accuracy evaluation, the model parameters are corrected and the two-dimensional daily model of evapotranspiration is improved;

[0018] The evapotranspiration of the target basin is calculated based on the two-dimensional daily model of evapotranspiration.

[0019] Preferably, the selecting of typical karst basins for continuous hydrological and meteorological observations includes:

[0020] Selecting a typical hydrogeological unit as a karst basin for continuous hydrological observation to obtain water cycle characteristics of the karst basin;

[0021] A meteorological observation station is established to conduct continuous in-situ observation of meteorological elements related to evapotranspiration, obtain continuous meteorological data, and obtain the correlation between the water cycle and climate in the karst basin.

[0022] Preferably, the underlying surface includes the following two types:

[0023] Surface karst zone and ordinary underlying surface.

[0024] Preferably, the acquiring of multi-source remote sensing data, continuous observation of the underlying surface of the watershed, and acquisition of change information of the underlying surface of the karst watershed includes:

[0025] The GF-4 remote sensing data is used to observe the changes in vegetation coverage in the surface karst zone and ordinary underlying surface, and to obtain information on changes in the underlying surface of the karst basin.

[0026] Preferably, the in-situ experiment measures evapotranspiration and analyzes the correlation between evapotranspiration of different underlying surfaces and climate factors, including:

[0027] The evapotranspiration of the surface karst zone and vegetation area under different climatic conditions was measured in the field using photosynthesis meters and lysimeters, and the correlation between evapotranspiration of different underlying surfaces and climatic factors was analyzed.

[0028] Preferably, the correlation between the evapotranspiration of different underlying surfaces and climate factors is used to calculate the degree-day factor matrix using multivariate statistical analysis to establish a two-dimensional daily model of evapotranspiration, including:

[0029] Based on the correlation between evapotranspiration and climatic factors of different underlying surfaces, a degree-day model of evapotranspiration and meteorological factors was established.

[0030] The degree-day model is expanded into a two-dimensional model based on meteorological factors and underlying surface, resulting in a two-dimensional daily model of evapotranspiration.

[0031] Preferably, the degree-day model is expanded into a two-dimensional model based on meteorological factors and underlying surface, and a two-dimensional daily model of evapotranspiration is obtained, including:

[0032] Write the degree-day factor of each underlying surface in the form of a row matrix to obtain the degree-day factor matrix;

[0033] Write the meteorological factors in the form of a matrix to obtain the meteorological factor matrix;

[0034] The number of pixels of the underlying surface type constitutes the underlying surface matrix;

[0035] Based on the underlying surface matrix, the underlying surface degree-day factor matrix and the meteorological factor matrix, a two-dimensional daily model of evapotranspiration is obtained.

[0036] Preferably, the distributed basin evapotranspiration is preliminarily calculated based on the two-dimensional daily model of evapotranspiration, and the accuracy of the two-dimensional daily model of evapotranspiration is evaluated using mathematical accuracy and actual accuracy in combination with hydrological and meteorological observations, and the accuracy evaluation results obtained include:

[0037] Based on the two-dimensional daily model of evapotranspiration, the distributed observation values, cumulative observation values, annual evapotranspiration of each pixel and annual evapotranspiration of the karst basin are calculated;

[0038] Calculate the error of the two-dimensional daily model of evapotranspiration according to the error propagation law, and output the mathematical accuracy of the two-dimensional daily model of evapotranspiration;

[0039] The basin evapotranspiration is calculated based on the basin water balance equation, and the actual accuracy of the evapotranspiration two-dimensional daily model is output.

[0040] First, a two-dimensional daily model of evapotranspiration was preliminarily established. A result was calculated using this model, and then the settlement result was compared with the actual observation result, which is the actual accuracy. The model itself has mathematical accuracy. The actual accuracy and mathematical accuracy are used to evaluate the accuracy (reliability) of the model. The parameters were modified according to the evaluation results to improve the model. This is the step of accuracy evaluation.

[0041] On the other hand, the present invention provides a computer storage medium, characterized in that a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, a karst basin evapotranspiration estimation method based on a distributed two-dimensional daily model is executed.

[0042] Through the above technical scheme, it can be known that compared with the prior art, the present invention discloses a karst basin evapotranspiration estimation method and a computer storage medium based on a distributed two-dimensional daily model. First, a technical means combining ground survey and remote sensing monitoring is used to obtain basic data such as hydrology, meteorology, and underlying surface; then an in-situ experiment is carried out to measure the evapotranspiration under different meteorological conditions and calculate the degree-day factor matrix; according to the two-dimensional daily model, the evapotranspiration of the basin scale is preliminarily calculated; the mathematical accuracy and actual accuracy of the model are evaluated, and the model parameters are corrected; finally, the evapotranspiration of the karst basin scale is calculated according to the corrected two-dimensional daily model of evapotranspiration. A two-dimensional daily model of evapotranspiration is established by fitting the measured data to calculate the evapotranspiration of the basin scale. The two-dimensional daily model of evapotranspiration adopts a method combining in-situ measurement with model calculation, ground survey with remote sensing monitoring, and the observation means are continuous and accumulative in time and distributed in space; the underlying surface is changing in time and heterogeneous in space; the calculation results are cumulative in time and distributed in space, which conforms to the characteristics of evapotranspiration. The present invention can provide accurate parameters for hydrogeological research and data support for human time activities such as the rational allocation of water resources, and has important scientific and practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0044] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0045] Figure 2 This is a diagram of the observation points for the evapotranspiration in-situ experiment provided in Example 2. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1

[0048] On the one hand, Embodiment 1 of the present invention discloses a method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model, comprising:

[0049] Select typical karst basins for continuous hydrological and meteorological observations;

[0050] Acquire multi-source remote sensing data, conduct continuous observation of the underlying surface of the watershed, and obtain information on changes in the underlying surface of typical karst watersheds;

[0051] In-situ experiments were conducted to measure evapotranspiration and analyze the correlation between evapotranspiration and climate factors on different underlying surfaces;

[0052] Based on the correlation between evapotranspiration of different underlying surfaces and climatic factors, multivariate statistical analysis was used to calculate the degree-day factor matrix and establish a two-dimensional daily model of evapotranspiration.

[0053] Based on the two-dimensional daily evapotranspiration model, the distributed basin evapotranspiration is preliminarily calculated, and the accuracy of the two-dimensional daily evapotranspiration model is evaluated in combination with hydrological and meteorological observations to obtain the accuracy evaluation results.

[0054] According to the results of the accuracy evaluation, the model parameters are corrected and the two-dimensional daily model of evapotranspiration is improved;

[0055] The evapotranspiration of the target basin is calculated based on the two-dimensional daily model of evapotranspiration.

[0056] In a specific embodiment, a typical hydrogeological unit is selected to carry out continuous hydrological and meteorological observations, including:

[0057] Select typical hydrogeological units to carry out continuous hydrological observations and study the water cycle characteristics of the basin; establish meteorological observation stations to carry out continuous in-situ observations of meteorological elements related to evapotranspiration, obtain continuous meteorological data, and study the correlation between the water cycle and climate in the basin. Provide basic parameters and accuracy evaluation basis for the two-dimensional daily model of evapotranspiration.

[0058] In a specific embodiment, multi-source remote sensing data is used to conduct continuous observation of the underlying surface of the watershed and study the changing characteristics of the underlying surface of the watershed, including:

[0059] The underlying surface can be generalized into four categories: artificial building areas (houses, squares, roads, etc.), water surfaces, surface karst zones, and ordinary underlying surfaces. The properties of the first two types of underlying surfaces do not change on a time scale. The biggest feature of the surface karst zone is that the soil distribution is discontinuous and the soil layer is thin. There is no soil evaporation and groundwater evaporation, only vegetation transpiration and a small amount of intercepted evaporation. The underlying surface properties change with the vegetation coverage on a time scale. Ordinary underlying surfaces are all types except the first three types, characterized by continuously distributed soil. Evaporation includes soil evaporation, groundwater evaporation, vegetation transpiration and vegetation intercepted evaporation. The underlying surface properties change with the vegetation coverage on a time scale.

[0060] The change of vegetation coverage is the core of the influence of underlying surface elements on evapotranspiration. The main content of the continuous observation of the basin underlying surface is to use the GF-4 remote sensing data to observe the changes in vegetation coverage of the surface karst zone and the ordinary underlying surface, study the changing characteristics of the basin underlying surface, and provide basic parameters for the two-dimensional daily model of evapotranspiration.

[0061] In a specific embodiment, in-situ experiments are performed to measure evapotranspiration and study the correlation between evapotranspiration of different underlying surfaces and climate factors, including:

[0062] Photosynthesizers and lysimeters were used to measure the evapotranspiration of the surface karst zone and vegetation area under different climatic conditions in the field, the correlation between evapotranspiration of different underlying surfaces and climatic factors was studied, and the mathematical basis of the two-dimensional daily model of evapotranspiration was established.

[0063] In a specific embodiment, a two-dimensional daily model of evapotranspiration is established using multivariate statistical analysis to preliminarily calculate the evapotranspiration of a watershed, including:

[0064] Based on the correlation between evapotranspiration of different underlying surfaces and climatic factors, a two-dimensional daily model was established using multivariate statistical analysis methods to preliminarily calculate the distributed basin evapotranspiration.

[0065] In a specific embodiment, evaluating the accuracy of the model and improving the model include:

[0066] The mathematical accuracy of the two-dimensional daily model is evaluated according to the error propagation law. The actual accuracy of the two-dimensional daily model is evaluated according to the basin water balance equation. The model parameters are corrected according to the accuracy evaluation to improve the evapotranspiration model.

[0067] In a specific embodiment, according to the established distributed two-dimensional daily model based on meteorological factors and underlying surface types, evapotranspiration at the karst basin scale is calculated to provide accurate parameters for hydrogeological research.

[0068] Specifically, according to the physical basis of the evapotranspiration model, evapotranspiration is significantly positively correlated with the temperature, wind force, and saturated water vapor pressure difference among the meteorological factors, and the contribution of meteorological factors is linearly added. Similar to the glacier meltwater measurement day model, evapotranspiration has a critical point of saturated water vapor pressure difference. When the saturated water vapor pressure difference is greater than the zero point V0, there is no evapotranspiration; different from the glacier meltwater measurement day model, evapotranspiration does not have a zero point of temperature and wind force.

[0069] Based on the above description, the degree-day model formula of evapotranspiration and meteorological factors is obtained as follows:

[0070]

[0071] In the formula, ET m is the evapotranspiration based on meteorological factors (mm·Δt -1 ), DDF1 is the degree-day factor based on temperature (mm·℃ -1 ·Δt -1 ), T is the temperature (℃), DDF2 is the degree-day factor based on wind speed (mm·s·m -1 ·Δt -1 ), W is wind speed (m·s -1 ), DDF3 is the degree-day factor based on the saturated water vapor pressure difference (mm·hPa -1 ·Δt -1 ), V is the saturated vapor pressure difference (hPa), V0 is the critical saturated vapor pressure difference (hPa) for evapotranspiration; evapotranspiration is expressed as the sum over a period of time (Δt), and the step size of Δt is determined by the observation frequency of the observation instrument, which is detailed in the technical route section; the degree-day factor of wind speed (mm·s·m -1 ·Δt -1 ), mm represents the vertical height of evapotranspiration, and m represents the horizontal distance of wind. The directions of the two length units are different. ET1 is ET m ET2 is a matrix that adds the underlying surface elements to ET1, and is the key to transforming the degree-day model from one dimension to two dimensions.

[0072] Compared with the single underlying surface properties of glaciers, the underlying surface types in karst basins are diverse and changeable. It is necessary to add the underlying surface elements to the degree-day model based on meteorological factors and expand the degree-day model into a two-dimensional model based on meteorological factors and underlying surface.

[0073] In a specific embodiment, the distributed observation value of evapotranspiration at the karst basin scale is calculated based on the two-dimensional daily model of evapotranspiration, including:

[0074] Assuming there are i types below, the degree-day factor of each underlying surface can be written in the form of a row matrix, denoted as matrix D.

[0075] D=[ddf i1 ddf i2 ddf i3 ]Matrix (1-1)

[0076] ddf in matrix (1-1) i1 is the temperature degree-day factor of the i-th type underlying surface (mm·℃ -1 ·Δt -1 ), ddf i2 is the wind speed daily factor of the ith underlying surface (mm·s·m -1 ·Δt -1 ), ddf i3 is the saturated vapor pressure difference degree-day factor of the i-th type underlying surface (mm·hPa -1 ·Δt -1 ).

[0077] For the convenience of calculation, the meteorological factors are also written in the form of a matrix, denoted as matrix M.

[0078] M = [TWV] matrix (1-2)

[0079] In the matrix (1-2), T is the temperature (℃), W is the wind speed (m·s -1 ), V is the saturated water vapor pressure difference (hPa).

[0080] The two-dimensional daily model of evapotranspiration can be written in the form of a matrix except for the discriminant conditions:

[0081] ET1=MD T Formula (1-4)

[0082] According to the matrix operation rules, the calculation result ET1 of formula (1-4) is a 1×1 matrix, whose value is the evapotranspiration of each pixel (this study intends to use GF-4 data with a pixel scale of 50m×50m) in the Δt time period, realizing the distributed observation of evapotranspiration at the karst basin scale.

[0083] In a specific embodiment, calculating the cumulative observation value of evapotranspiration at the karst basin scale based on the two-dimensional daily model of evapotranspiration includes:

[0084] Multiply formula (1-4) by the following surface matrix, which is expressed as formula (1-5).

[0085] ET2=MD T L Formula (1-5)

[0086] Where, matrix L is the 1×i underlying surface matrix (1-3), l i is the number of pixels of the i-th underlying surface type. According to the matrix operation rules, the calculation result ET2 of formula (1-5) is a 1×i row matrix. The sum of all elements of the row matrix is ​​the total evapotranspiration of the karst basin in the Δt time period, realizing the cumulative observation of evapotranspiration at the karst basin scale.

[0087] L=[l1 l2…l i ]Matrix (1-3)

[0088] The ET1 values ​​of each Δt time period throughout the year are accumulated pixel by pixel, which is the annual evapotranspiration of each pixel; the sum of the ET2 elements of each Δt time period throughout the year is accumulated to obtain the annual evapotranspiration of the karst basin.

[0089] Specifically, according to the degree-day model of evapotranspiration and meteorological factors described above, it is necessary to obtain meteorological elements and underlying surface elements. This embodiment 1 intends to adopt a field continuous observation method to obtain meteorological data, and generalize from point to area through spatial difference to achieve distributed continuous observation; adopt a remote sensing high-frequency monitoring method to obtain continuous underlying surface data. The data obtained by the remote sensing method is distributed in space, reflecting the spatial heterogeneity of the underlying surface; adopt an in-situ measurement method to measure the evapotranspiration and meteorological factors of different underlying surface types, and calculate the degree-day factors of different underlying surface types. It is especially important to select a suitable evapotranspiration measurement method according to local conditions; and through the evaluation of mathematical accuracy and actual accuracy, correct the model parameters and improve the reliability of the model.

[0090] On the other hand, embodiment 1 of the present invention discloses a computer storage medium, characterized in that a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the karst basin evapotranspiration estimation method based on the distributed two-dimensional daily model as described above is executed.

[0091] Example 2

[0092] The detailed process of the evapotranspiration estimation method for a karst basin based on a distributed two-dimensional daily model provided in the specific application example 1 is as follows:

[0093] See also Figure 1The method flow of the present invention includes the steps of acquiring data, in-situ experiments, establishing models, verifying models, improving ladders and drawing conclusions, and specifically includes: according to the two-dimensional daily model of evapotranspiration proposed in Example 1 of the present invention, firstly, basic data such as hydrology, meteorology, and underlying surface are acquired by combining ground surveys with remote sensing monitoring; then, in-situ experiments are carried out to measure evapotranspiration under different meteorological conditions and calculate the degree-day factor matrix; according to the two-dimensional daily model, the evapotranspiration at the basin scale is preliminarily calculated; the mathematical accuracy and actual accuracy of the model are evaluated, and the model parameters are corrected; finally, the evapotranspiration at the karst basin scale is calculated according to the corrected two-dimensional daily model of evapotranspiration.

[0094] Specifically, the Haiyang-Zhaidi karst basin in the east of Guilin was selected as the research area. The Haiyang-Zhaidi karst basin is a hydrogeological field observation base of the Ministry of Natural Resources. It is a karst basin with complete recharge-runoff-discharge conditions and has complete groundwater dynamic observation equipment.

[0095] Specifically, hydrogeological observations include:

[0096] According to the principles of hydrogeology, the water balance equation of the basin is as follows:

[0097] P+R gI =E+R sO +R gO +q+ΔW formula (3-1)

[0098] Where P is the rainfall in the basin during the time period; R gI is the amount of water flowing into the basin from underground during the time period; E is the evapotranspiration during the time period; R sO R is the amount of water flowing out of the basin from the surface during the time period; gO is the amount of water flowing out of the basin from the ground during the time period; q is the water consumption during the time period; ΔW is the change in water storage capacity in the basin during the time period.

[0099] The Haiyang-Zhaidi base is a completely closed karst basin with no groundwater inflow or outflow (except for the total outlet of the basin). There is no R in the basin water balance equation. gI and R sO Item. Existing research results show that there is no industrial water in the basin, only domestic water and agricultural water. Most of the domestic water returns to the basin in various forms, and the amount of domestic water consumed is very small and can be ignored; most of the agricultural water infiltrates through the soil to form groundwater, and a small part enters the atmosphere through evaporation and transpiration, which is included in evaporation. Only a small amount of vegetation physiological water is used, and q can be ignored. The water balance equation of the Haiyang-Zhaidi karst basin is:

[0100] P=E+R gO +ΔW formula (3-2)

[0101] The meaning of each term in the formula is consistent with formula (3-1). Using the existing groundwater dynamic observation equipment at the Haiyang-Zhaidi base, the groundwater flow R is recorded every 10 minutes. gO ; A small meteorological observation station is used to record rainfall P every 10 minutes. There are only two surface water bodies in the basin (larger than the pixel scale of the GF-4 image (50m×50m)). The water depth and water surface area are measured once a month to measure the change in water storage capacity ΔW. From this, the water balance equation can be used to calculate the total evapotranspiration of the basin, which is used as a comparison value for the model calculation to evaluate the reliability of the model.

[0102] Specifically, meteorological observations include:

[0103] Four meteorological stations are evenly distributed in the basin. Meteorological factors (temperature, relative humidity, wind speed) in a hydrological year are observed every 10 minutes. The saturated water vapor pressure difference is calculated according to formula (3-3) using temperature and relative humidity as parameters.

[0104]

[0105] Where VPD is the saturated water vapor pressure difference, Ta is the air temperature (℃), and RH is the relative humidity.

[0106] Specifically, the underlying surface remote sensing observation includes:

[0107] The spatial and temporal changes of the underlying surface are monitored using the GF-4 geosynchronous orbit remote sensing data. First, the existing underlying surface types are classified to detect whether there are changes between major types of underlying surfaces, especially new artificial building areas and water bodies (there will be no mutual changes between the surface karst zone and the ordinary underlying surface).

[0108] The focus of the remote sensing observation of the underlying surface is to monitor the changes in vegetation coverage of the surface karst zone and the ordinary underlying surface on a time scale, which is monitored every 15 days. The data of the Gaofen-4 geosynchronous orbit satellite is available free of charge. The staring camera has ultra-high temporal resolution and rich infrared band information, which enables it to observe the surface vegetation at a high frequency and for a long period of time. The normalized vegetation index (NDVI) is calculated by the ratio of the red light band to the infrared band, and the fractional vegetation coverage (FVC) is calculated using the NDVI value as a parameter. The calculation formula of NDVI is:

[0109] NDVI=(NIR-R) / (NIR+R) Formula (3-4)

[0110] Where: NDVI is the normalized vegetation index, NIR is the reflectance value of the near-infrared band of remote sensing data, and R is the reflectance value of the red band of remote sensing data.

[0111] The calculation formula of vegetation coverage (FVC) is:

[0112] FVC=(NDVI i -NDVI s ) / (NDVI m +NDVI s ) Formula (3-5)

[0113] Where: FVC is vegetation coverage, NDVI is i is the NDVI value for each pixel, NDVI s is the NDVI value of completely bare land, NDVI m It is the maximum NDVI value of the pixel in the fully covered area.

[0114] NDVI s Theoretically, it should not change with time. For most bare land, its value should be approximately zero. However, due to changes in atmospheric influences, surface humidity, and seasonal conditions, NDVI s will change over time; in addition, due to differences in surface humidity, surface roughness, soil type, soil color and other conditions in different regions, NDVI s It also changes with different spatial locations. m Due to the influence of various factors such as different vegetation types and seasonal changes, its value will also change over time and space. m and NDVI s According to previous research experience, this embodiment 2 selects 5% of the accumulation percentage as the confidence level, that is, the accumulation percentage greater than 95% is full vegetation coverage, and less than 5% is approximately pure soil coverage. The corresponding NDVI values ​​are marked as NDVI m and NDVI s .

[0115] To facilitate model calculations, the vegetation coverage of the surface karst zone and ordinary underlying surface is divided into four levels on average, namely 0-25%, 25%-50%, 50%-75%, and 75%-100%.

[0116] Specifically, the evapotranspiration in situ experiment includes:

[0117] See also Figure 2 As shown in the figure, the distribution map of evapotranspiration in-situ experimental observation points. The basis for establishing a two-dimensional daily model is the measured evapotranspiration data. The measurement method must be selected according to the characteristics of the underlying surface and the evapotranspiration measurement is carried out under different climatic conditions on all types of underlying surfaces (once a month).

[0118] Specifically, evaporation observations in artificial building areas include:

[0119] The surface of the artificial construction area is hardened, and the atmospheric rainfall does not infiltrate. Without considering the lateral flow, its evapotranspiration is the evaporation of atmospheric rainfall. In the tropical and subtropical climate of the working area, its value is equal to the rainfall. According to meteorological data, the evapotranspiration of the artificial construction area is equal to the rainfall in the same period of time.

[0120] Specifically, water surface evaporation observations include:

[0121] According to the "Water Surface Evaporation Observation Specifications" (SL630-2013) issued by the Ministry of Water Resources, we chose to establish observation stations, install observation equipment, observe and record evaporation values, and observe meteorological elements such as temperature, humidity, and wind speed.

[0122] Specifically, common surface evapotranspiration observations include:

[0123] The evapotranspiration of ordinary underlying surface includes soil evaporation, groundwater evaporation, vegetation transpiration and vegetation interception evaporation, among which the proportion of vegetation interception evaporation is very small and can be ignored here. Soil evaporation, groundwater evaporation and vegetation transpiration can be measured using a lysimeter. The lysimeter mainly studies the relevant factors such as water migration and water balance in columnar soil through a soil weighing system, a monitoring system and a data acquisition system to determine the evapotranspiration of soil water and vegetation. This embodiment 2 plans to use a UGT portable small lysimeter to measure the evapotranspiration of four vegetation coverage levels under different meteorological conditions, measure the evapotranspiration of four vegetation areas once a month (at least 2 nighttime measurements), and achieve evapotranspiration measurement of all four types of underlying surfaces in the vegetation area under 12 climatic conditions, and obtain temperature, humidity, wind force and evapotranspiration values ​​at the same time.

[0124] Specifically, the specific locations of evapotranspiration measurement points in vegetation areas will be adjusted according to the vegetation coverage.

[0125] Specifically, the epikarst zone includes:

[0126] The epikarst zone is a unique surface morphology in tropical-subtropical karst areas. The evapotranspiration of the epikarst zone should be measured by selecting appropriate calculation methods based on the analysis of its evapotranspiration characteristics. The biggest feature of the epikarst zone is that there is no soil on the surface (the soil is scarce and discontinuous). Evapotranspiration is equal to vegetation transpiration and vegetation interception evaporation. The proportion of vegetation interception evaporation is very small and can be ignored here. A photosynthesis meter was used to measure the transpiration rate of 10 groups of plant leaves at different positions within a GF-4 image pixel scale (50m×50m). Considering the canopy structure of the vegetation in the epikarst zone (mainly shrubs), the transpiration rates of the upper, middle and lower layers of leaves were measured respectively. Two sunny leaves were selected for each layer, and each leaf was measured 3 times. The average value was the transpiration rate of the leaf. The transpiration rates of the four vegetation coverage levels under different meteorological conditions were measured respectively, and the transpiration amount was calculated according to formula (3-5).

[0127]

[0128] Where: T is the transpiration rate of plant leaves per unit area in the field (mm / h); k is the number of canopy layers of the plant (1, 2, ..., m); M k is the transpiration rate measured by photosynthesis instrument on the sun leaf of layer k [mmol / (m 2 ·s)]; α k and β k are the proportion of the k-layer sun leaf area to the total area (%) and the proportion of the shade leaf transpiration rate to the sun leaf transpiration rate (%); 6.48×10 -2 is the conversion factor; A k is the area of ​​the k-layer leaf (cm 2 ).

[0129] The vegetation transpiration of four vegetation coverage levels is measured once a month, and the evapotranspiration of all four underlying surface types in the surface karst zone under 12 climatic conditions is measured, while the temperature, humidity, wind speed and transpiration are obtained at the same time.

[0130] Specifically, the specific locations of the evapotranspiration measurement observation points in the surface karst zone will be adjusted according to the vegetation coverage.

[0131] In a specific embodiment, the multivariate statistical analysis method calculates the degree-day factor matrix and establishes a two-dimensional day model, including:

[0132] According to the evapotranspiration of various underlying surfaces and the corresponding meteorological factors obtained from the above-mentioned in-situ measurements, 12 sets of data were measured on each of the seven underlying surface types (water surface, four vegetation coverage levels of ordinary underlying surfaces, and four vegetation coverage levels of surface karst zones). The degree-day factor matrix was calculated by multivariate statistical analysis, and a two-dimensional day model was established.

[0133] Hydrogeological elements and meteorological factors change very quickly, and the time interval for their observation data is 10 minutes; while the changes in underlying surface elements are relatively slow, and the monitoring interval is 15 days. When calculating, the underlying surface at a 15-day interval is divided into 2160 10-minute intervals, achieving a unified observation time step. This 10-minute step corresponds to Δt in formulas (1-4) and (1-5).

[0134] In a specific embodiment, the two-dimensional daily model is verified and improved to calculate the evapotranspiration of the karst basin, including:

[0135] Based on the above-mentioned two-dimensional daily model of evapotranspiration and meteorological factors, the evapotranspiration of the Haiyang-Zhaidi karst basin is preliminarily calculated and the accuracy is evaluated. Based on this, the model is modified to improve the reliability of the model. The accuracy of the model includes mathematical accuracy and actual accuracy. The error of the two-dimensional daily model is calculated according to the law of error propagation to evaluate the mathematical accuracy; the evapotranspiration of the basin is calculated by comparing it with the water balance equation of the basin, and the actual accuracy of the two-dimensional daily model is evaluated. According to the accuracy evaluation, the error source is analyzed, the model parameters are corrected, and the two-dimensional daily model of evapotranspiration is improved.

[0136] The evapotranspiration of a typical karst basin is calculated based on the two-dimensional daily model of evapotranspiration.

[0137] In a specific embodiment, the feasibility analysis includes:

[0138] This embodiment 2 first summarizes the characteristics of evapotranspiration and its underlying surface, analyzes the advantages and disadvantages of various current evapotranspiration calculation methods, and proposes a two-dimensional daily model for calculating evapotranspiration in karst basins on this basis. Its theoretical basis is the physical basis of the evapotranspiration model. Evapotranspiration is significantly positively correlated with temperature, wind force, and saturated water vapor pressure difference among meteorological factors, and the contribution of meteorological factors is linearly added. This is a theory that has been basically proven by relevant studies and has sufficient theoretical basis. On the basis of the theoretical basis, according to the characteristics of the evapotranspiration underlying surface, a rigorous mathematical model is derived. According to the mathematical model, it is feasible to select appropriate observation methods to obtain the required parameters, especially to select appropriate methods to measure evapotranspiration in situ according to the characteristics of the surface karst zone according to local conditions. The overall accuracy is evaluated from the two aspects of mathematical accuracy and actual accuracy, and the reliability of the model is guaranteed. The evapotranspiration calculation results are cumulative in time and distributed in space, which conforms to the characteristics of evapotranspiration.

[0139] Specifically, based on the analysis of existing evapotranspiration calculation methods, the present invention proposes for the first time to use a two-dimensional daily model to calculate evapotranspiration, and the research idea is innovative; the observation method adopted is high-frequency continuous observation, which focuses on the spatial heterogeneity and temporal variability of the underlying surface, accurately describes the underlying surface conditions, and the observation method is innovative; the reliability of the model is evaluated from two aspects: mathematical accuracy and measured accuracy, and the reliability of the model is guaranteed.

[0140] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0141] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model, characterized in that: include: Select typical karst basins for continuous hydrological and meteorological observations; Acquire multi-source remote sensing data, conduct continuous observation of the underlying surface of the watershed, and obtain information on changes in the underlying surface of typical karst watersheds; In-situ experiments were conducted to measure evapotranspiration and analyze the correlation between evapotranspiration and climate factors on different underlying surfaces; Based on the correlation between evapotranspiration of different underlying surfaces and climatic factors, multivariate statistical analysis was used to calculate the degree-day factor matrix and establish a two-dimensional daily model of evapotranspiration. Based on the two-dimensional daily evapotranspiration model, the distributed basin evapotranspiration is preliminarily calculated, and the accuracy of the two-dimensional daily evapotranspiration model is evaluated in combination with hydrological and meteorological observations to obtain the accuracy evaluation results. According to the results of the accuracy evaluation, the model parameters are corrected and the two-dimensional daily model of evapotranspiration is improved; Calculate the evapotranspiration of the target basin based on the two-dimensional daily model of evapotranspiration; Based on the correlation between evapotranspiration and climate factors on different underlying surfaces, multivariate statistical analysis is used to calculate the degree-day factor matrix and establish a two-dimensional daily model of evapotranspiration, including: Based on the correlation between evapotranspiration and climatic factors of different underlying surfaces, a degree-day model of evapotranspiration and meteorological factors was established. The degree-day model is expanded into a two-dimensional model based on meteorological factors and underlying surface, and a two-dimensional daily model of evapotranspiration is obtained. The degree-day model is expanded into a two-dimensional model based on meteorological factors and underlying surface, and a two-dimensional daily model of evapotranspiration is obtained, including: Write the degree-day factor of each underlying surface in the form of a row matrix to obtain the degree-day factor matrix; Write the meteorological factors in the form of a matrix to obtain the meteorological factor matrix; The number of pixels of the underlying surface type constitutes the underlying surface matrix; Based on the underlying surface matrix, the underlying surface degree-day factor matrix and the meteorological factor matrix, a two-dimensional daily model of evapotranspiration is obtained.

2. The method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model according to claim 1, characterized in that: The typical karst basins are selected for continuous hydrological and meteorological observations, including: Selecting a typical hydrogeological unit as a karst basin for continuous hydrological observation to obtain water cycle characteristics of the karst basin; A meteorological observation station is established to conduct continuous in-situ observation of meteorological elements related to evapotranspiration, obtain continuous meteorological data, and obtain the correlation between the water cycle and climate in the karst basin.

3. The method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model according to claim 1, characterized in that: The underlying surface includes the following two categories: Surface karst zone and ordinary underlying surface.

4. The method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model according to claim 3, characterized in that: The method of acquiring multi-source remote sensing data, conducting continuous observation of the underlying surface of the watershed, and obtaining information on changes in the underlying surface of the karst watershed includes: Remote sensing data is used to observe changes in vegetation coverage in the surface karst zone and ordinary underlying surface, and to obtain information on changes in the underlying surface of the karst basin.

5. The method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model according to claim 4, characterized in that: The in-situ experiment measures evapotranspiration and analyzes the correlation between evapotranspiration of different underlying surfaces and climate factors, including: The evapotranspiration of the surface karst zone and vegetation area under different climatic conditions was measured in the field using photosynthesis meters and lysimeters, and the correlation between evapotranspiration of different underlying surfaces and climatic factors was analyzed.

6. The method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model according to claim 1, characterized in that: Based on the two-dimensional daily model of evapotranspiration, the distributed basin evapotranspiration is preliminarily calculated. The accuracy of the two-dimensional daily model of evapotranspiration is evaluated using mathematical accuracy and actual accuracy in combination with hydrological and meteorological observations. The accuracy evaluation results include: Based on the two-dimensional daily model of evapotranspiration, the distributed observation values, cumulative observation values, annual evapotranspiration of each pixel and annual evapotranspiration of the karst basin are calculated; Calculate the error of the two-dimensional daily model of evapotranspiration according to the error propagation law, and output the mathematical accuracy of the two-dimensional daily model of evapotranspiration; The basin evapotranspiration is calculated based on the basin water balance equation, and the actual accuracy of the evapotranspiration two-dimensional daily model is output.

7. A computer storage medium, characterized in that: The computer storage medium stores a computer program, and when the computer program is executed by the processor, the method for estimating evapotranspiration in a karst basin based on a distributed two-dimensional daily model as claimed in any one of claims 1 to 6 is executed.

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