CN116451902A - Ecological system evaluation system based on water resource constraint - Google Patents
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Abstract
The invention provides an ecological system evaluation system based on water resource constraint, which comprises: the system comprises a data acquisition module, a data processing module, a construction module and an evaluation module; the data acquisition module is used for acquiring ecological environment data of a research area; the data processing module is used for processing the ecological environment data; the construction module is used for constructing an ecological vulnerability assessment model; the evaluation module is used for evaluating the processed ecological environment data according to the ecological vulnerability evaluation model. The invention establishes an ecological vulnerability assessment model, can provide guidance for ecological restoration of yellow river basin, and can be popularized and applied to bearing capacity assessment in other areas.
Description
Technical Field
The invention belongs to the technical field of sustainable development research of an ecological system, and particularly relates to an ecological system assessment system based on water resource constraint.
Background
In recent years, under the combined action of global climate change and human activities, the ecological environment is seriously damaged, and the ecological system of the vulnerable arid and semi-arid region is greatly threatened, so that great challenges are brought to regional and global sustainable development;
yellow river basin is a typical ecological barrier transition zone in northwest and North China, but the yellow river basin is in arid and semiarid regions, water resources are short, and the ecological environment is fragile.
Ecological vulnerability refers to the sensitive response and self-restoring ability of the ecosystem to external disturbances. Compared with abroad, the research of China in the aspect of ecological vulnerability is started later.
Along with the severe conditions of the ecological environment problems such as warming, water and soil loss, forest sharp reduction, water pollution and the like, great challenges are brought to the sustainable development of the areas of the yellow river basin; the river basin is used as a main population gathering area, a planting area of special agriculture and an important bearing area of industry, and the ecological problems faced by the river basin are as follows: the vegetation coverage is low, and the wind sand and soil erosion is serious; excessive agriculture development causes the increase of irrigation water, the super-mining of underground water, the reduction of soil organic matters and the like, and the biggest contradiction is water resource shortage, and the biggest problem is ecological environment weakness; with the wide attention of the country in the ecological protection of the yellow river basin, a series of ecological restoration projects are adopted, and on the basis that all industrial development is required to be stabilized on the basis of the safety pattern of the ecological environment of the basin, how to effectively diagnose the water-ecological-industrial interaction problem and evaluate the quality and the sustainability of the water-ecological-industrial interaction problem according to the local conditions is urgent.
Disclosure of Invention
In order to solve the technical problems, the invention provides an ecological system evaluation system based on water resource constraint, which realizes dynamic evaluation and early warning analysis of ecological vulnerability in a research area under different water resource constraints, different space development characteristics and different ecological restoration conditions.
To achieve the above object, the present invention provides an ecosystem evaluation system based on water resource constraint, comprising: the system comprises a data acquisition module, a data processing module, a construction module and an evaluation module;
the data acquisition module is used for acquiring ecological environment data of a research area;
the data processing module is used for processing the ecological environment data;
the construction module is used for constructing an ecological vulnerability assessment model;
the evaluation module is used for evaluating the processed ecological environment data according to the ecological vulnerability evaluation model.
Optionally, the data acquisition module includes: the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit;
the first acquisition unit is used for acquiring land utilization data of the research area; wherein the land use data includes: utilization data of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation, and water bodies;
the second acquisition unit is used for acquiring hydrological data of the research area; wherein the hydrologic data includes: ecological hydrologic remote sensing parameters and hydrologic meteorological data; the ecological hydrologic remote sensing parameters comprise: normalized vegetation index, land surface temperature, leaf area index, evapotranspiration, total primary productivity, and net primary productivity, the hydrographic data comprising: precipitation, runoff, vapor pressure deficiency, air temperature and land water reserves are abnormal;
the third acquisition unit is used for acquiring ecological destructive disturbance data of the research area; wherein the ecologically destructive perturbation data comprises: mining area change data, river change data and vegetation coverage change data;
the first acquisition unit, the second acquisition unit and the third acquisition unit are all connected with the data processing module.
Optionally, the data processing module includes: a decomposition unit and an analysis unit;
the decomposition unit is used for decomposing the ecological environment data into data of a preset scale through an STL time sequence decomposition method;
the analysis unit is used for analyzing the decomposed ecological environment data.
Optionally, the analysis unit includes: a first analysis subunit, a second analysis subunit, and a third analysis subunit;
the first analysis subunit is used for analyzing the land utilization data;
the second analysis subunit is used for analyzing the hydrologic data;
the third analysis subunit is configured to analyze the ecologically destructive perturbation data based on a visual interpretation method.
Optionally, the analyzing the land use data by the first analysis subunit includes:
counting land utilization areas of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation and water bodies, and analyzing spatial distribution and change conditions; the method comprises the steps of representing the mutual transfer direction and the transfer area among land utilization types of yellow river watershed in different periods by adopting a transfer matrix method;
the transfer matrix is:
wherein P is ij The area for converting the i-type land utilization types into j-type land utilization types in different periods is changed, and n is the total number of land utilization types in the research area.
Optionally, the analyzing the hydrologic data by the second analysis subunit includes:
and analyzing the general development trend of the hydrologic data by adopting a slope estimation method, and performing significance test on the general development trend of the hydrologic data by adopting an MK test method.
Optionally, the ecological vulnerability assessment model constructed in the construction module adopts an exposure-sensitivity-adaptability framework model;
in the ecological vulnerability assessment model, the index parameters for representing the exposure comprise: precipitation index, topography index and human interference level;
in the ecological vulnerability assessment model, the index parameters for representing the sensitivity comprise: elasticity of the ecological system, activity of the ecological system, service function of the ecological system and water stress of vegetation;
in the ecological vulnerability assessment model, the index parameters for representing the adaptability comprise: protection zone coefficients.
Optionally, the ecological vulnerability assessment model includes: an ecological exposure evaluation unit, an ecological sensitivity evaluation unit and an ecological adaptability evaluation unit;
the ecological exposure evaluation unit is used for evaluating the degree of the ecological system subjected to external disturbance and pressure;
the ecological sensitivity evaluation unit is used for evaluating the response capability of the ecological system to disturbance or pressure of different degrees;
the ecological adaptability evaluation unit is used for representing an active measure for alleviating disturbance of an ecological system through an anti-interference mechanism or human behaviors;
the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit are sequentially connected.
Optionally, the building the ecological vulnerability assessment model in the building module further includes:
firstly, respectively setting a first-level weight for the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit, and then respectively setting a second-level weight for the precipitation index, the topography index, the human interference degree, the elasticity of an ecological system, the activity of the ecological system, the service function of the ecological system, the vegetation water stress and the protection area coefficient.
Compared with the prior art, the invention has the following advantages and technical effects:
the invention reveals the relevance of the water resource utilization of the long time sequence and the land ecological system in space;
the invention establishes a set of ecological vulnerability assessment model, and realizes ecological vulnerability dynamic assessment and early warning analysis in a research area under different water resource constraints, different space development characteristics and different ecological restoration conditions;
the invention establishes an ecological vulnerability assessment model, can provide guidance for ecological restoration of yellow river basin, and can be popularized and applied to bearing capacity assessment in other areas.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:
FIG. 1 is a schematic diagram of an ecological system assessment system according to an embodiment of the present invention;
FIG. 2 is a technical roadmap of an embodiment of the invention;
FIG. 3 is a schematic diagram of a space distribution of land utilization/land coverage of a yellow river basin in 1985-2019 according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of land utilization ratio in 1985-2019 according to an embodiment of the present invention;
FIG. 5 is a statistical representation of vegetation coverage areas for different years and different levels according to an embodiment of the present invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
As shown in fig. 1, the present invention proposes an ecosystem evaluation system based on water resource constraint, comprising: the system comprises a data acquisition module, a data processing module, a construction module and an evaluation module;
the data acquisition module is used for acquiring ecological environment data of the research area;
the data processing module is used for processing the ecological environment data;
the construction module is used for constructing an ecological vulnerability assessment model;
and the evaluation module is used for evaluating the processed ecological environment data according to the ecological vulnerability evaluation model.
Further, the data acquisition module includes: the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit;
the first acquisition unit is used for acquiring land utilization data of the research area; wherein, land use data includes: utilization data of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation, and water bodies;
the second acquisition unit is used for acquiring hydrological data of the research area; wherein the hydrologic data includes: ecological hydrologic remote sensing parameters and hydrologic meteorological data; the ecological hydrologic remote sensing parameters include: normalized vegetation index, land surface temperature, leaf area index, evapotranspiration, total primary productivity, and net primary productivity, hydrokinetic data includes: precipitation, runoff, vapor pressure deficiency, air temperature and land water reserves are abnormal;
the third acquisition unit is used for acquiring ecological destructive disturbance data of the research area; wherein the ecologically destructive perturbation data comprises: mining area change data, river change data and vegetation coverage change data;
the first acquisition unit, the second acquisition unit and the third acquisition unit are all connected with the data processing module.
Further, the data processing module includes: a decomposition unit and an analysis unit;
the decomposition unit is respectively connected with the first acquisition unit, the second acquisition unit and the third acquisition unit;
the decomposition unit is used for decomposing the ecological environment data into data of a preset scale through an STL time sequence decomposition method;
and the analysis unit is used for analyzing the decomposed ecological environment data.
Further, the analysis unit includes: a first analysis subunit, a second analysis subunit, and a third analysis subunit;
the first analysis subunit is used for analyzing the land utilization data;
a second analysis subunit for analyzing the hydrologic data;
and a third analysis subunit for analyzing the ecologically destructive perturbation data based on a visual interpretation method.
The first analysis subunit, the second analysis subunit and the third analysis subunit are all connected with the evaluation module.
Further, the first analysis subunit analyzing the land use data includes:
counting land utilization areas of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation and water bodies, and analyzing spatial distribution and change conditions; the method comprises the steps of representing the mutual transfer direction and the transfer area among land utilization types of yellow river watershed in different periods by adopting a transfer matrix method;
the transfer matrix is:
wherein P is ij The area for converting the i-type land utilization types into j-type land utilization types in different periods is changed, and n is the total number of land utilization types in the research area.
Further, the second analysis subunit analyzing the hydrologic data includes:
and analyzing the general development trend of the hydrologic data by adopting a slope estimation method, and performing significance test on the general development trend of the hydrologic data by adopting an MK test method.
Further, an ecological vulnerability assessment model constructed in the construction module adopts an exposure-sensitivity-adaptability framework model;
in the ecological vulnerability assessment model, index parameters for characterizing exposure include: precipitation index, topography index and human interference level;
in the ecological vulnerability assessment model, index parameters for characterizing sensitivity include: elasticity of the ecological system, activity of the ecological system, service function of the ecological system and water stress of vegetation;
in the ecological vulnerability assessment model, index parameters for characterizing adaptability include: protection zone coefficients.
Further, the ecological vulnerability assessment model includes: an ecological exposure evaluation unit, an ecological sensitivity evaluation unit and an ecological adaptability evaluation unit;
the ecological exposure evaluation unit is used for evaluating the degree of the ecological system subjected to external disturbance and pressure;
the ecological sensitivity evaluation unit is used for evaluating the response capability of the ecological system to disturbance or pressure of different degrees;
the ecological adaptability evaluation unit is used for representing an active measure for alleviating disturbance of the ecological system through an anti-interference mechanism or human behavior;
the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit are connected in sequence.
Further, the building of the ecological vulnerability assessment model in the building module further comprises:
first, a first-level weight is set for the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit respectively, and then a second-level weight is set for the precipitation index, the topography index, the human interference degree, the ecosystem elasticity, the ecosystem activity, the ecosystem service function, the vegetation water stress and the protection area coefficient respectively.
Examples
In this embodiment, taking a Mongolian segment in a yellow river basin as an example, the technical scheme of the present invention is described in detail, as shown in fig. 2, and the technical roadmap provided for this embodiment includes: (1) And (3) analyzing evolution characteristics of an ecological system in a Mongolia section in a yellow river basin: combining with the land utilization data of the time sequence, carrying out grassland ecosystem evolution analysis of Mongolia sections in the yellow river basin from 2000, and defining different main and key driving factors. (2) Remote sensing extraction and water consumption estimation of information of an ecological system in a typical ecological fragile area: based on the land utilization, based on a multi-source remote sensing technology, developing crop types, irrigation area distribution, mining areas and pastures (including natural grasslands, feed planting and the like); and estimating the water consumption change of the main ecological system and the fluctuation characteristics of the underground water by combining the evapotranspiration data and the land water reserve data. (3) Analysis of correlation of ecosystem human activity-water consumption-vegetation (type and parameters): the evolution and response characteristics of the ecosystem type under the combined action of water resource constraint and human interference are defined, and the action characteristics and rules of the ecosystem type are revealed. (4) Ecological safety (or service function) assessment and sustainability analysis: the remote sensing and the ecological environment model are coupled, an index system for evaluation is established, comprehensive evaluation is carried out, development trend is predicted, important areas for conservation or restoration are defined, and sustainable development suggestions are provided by combining with the development characteristics of industry.
The embodiment relates to remote sensing, water resources, land ecology and the like, and the related technical problems include: (1) An ecological environment element and key sensitive factor remote sensing acquisition technology: the extraction technology of human action areas such as vegetation type extraction, coverage, leaf area index, earth surface temperature and the like is related, and how to accurately extract the characteristics of inner Mongolia is very critical; (2) model coupling technology of remote sensing-ecological environment and the like: in the ecological system monitoring and evaluation, relevant remote sensing parameters or elements and an ecological environment model are required to be coupled, and ecological environment sustainability research is carried out according to local conditions; (3) sustainable development analysis method: how to integrate social and natural elements, it is critical to propose a sustainable development strategy oriented to regional characteristics.
The evaluation system proposed in the present embodiment includes: the system comprises a data acquisition module, a data processing module, a construction module and an evaluation module; the data acquisition module is used for acquiring ecological environment data of the research area; the data processing module is used for processing the ecological environment data; the construction module is used for constructing an ecological vulnerability assessment model; and the evaluation module is used for evaluating the processed ecological environment data according to the ecological vulnerability evaluation model.
Firstly, a data acquisition module collects data of inner Mongolia sections of a yellow river basin; the main usage data collected in this embodiment includes: 1. land use data: land cover year dataset (CLCD) in 1985-2019 based on Landsat was used; ndvi data: including EVI and NDVI, generated once every 16 days with a spatial resolution of 250 meters; 3. hydrological data: precipitation (Precipitation), runoff (Runoff), vapor pressure depletion (VaporPressure Deficit, VPD), air temperature (AirTemperature, TA), and land water storage anomaly (terrestrial water storage anomaly, TWSA) data; 4. normalizing monitoring data: MODIS data such as Land Surface Temperature (LST), leaf Area Index (LAI), evapotranspiration (ET), total primary production (GPP), net Primary Productivity (NPP), and ecological hydrodynamics; 5. destructive perturbation factor data were performed: landsat and Sentinel-2 data were analyzed in 1990-2020;
the land utilization area of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation and water bodies is counted by utilizing 30m resolution land utilization/coverage data in the inner Mongolia section 1985-2019 of the yellow river basin, and the spatial distribution and change conditions of the land utilization/coverage data are analyzed;
as shown in fig. 3, the coverage type of Mongolia sections in the yellow river basin mainly comprises grasslands, cultivated lands and barren lands, and contains a small amount of impermeable water surfaces and woodlands. The cultivated land is mainly distributed in an agricultural irrigation area in a north-biased area in the middle of the inner Mongolia section, extends in the east-west direction in a strip shape, and is inlaid with a small part of barren land in the south of the cultivated land. The town area is mainly built according to cultivated land and distributed in the northern area of the middle and middle stream of yellow river in a lump, and the impervious surface area is subjected to punctiform to planar development in the year 1985-2019, so that the town area is continuously enlarged along with the continuous development of economy.
As shown in fig. 4, the grassland occupation ratio is greater than 50%, the grasslands and the woodlands form an ascending trend, the cultivated lands, the barren lands and the irrigation areas form a descending trend, the irrigation area tends to 0, the phenomenon of 'barren grass turning' in the Mongolian area in the yellow river basin can be presumed, the overall improvement of the ecological environment condition is illustrated, and the 'greenness' of the basin is continuously improved. The impervious surface at the uppermost part of the histogram gradually increases, which indicates that the living level of people in the river basin is continuously improved.
Forest grass is in an ascending trend and reaches a peak in 2015. After 2015, the area of the barren land starts to be slightly increased again, the area of the grassland is reduced in a small range, the current situation of the ecological environment of the Mongolian area in the current yellow river basin is released, the ecological foundation is still fragile, desertification and desertification land in the basin are concentrated and serious in harm, part of cultivated land is salinized, the local area is located in an ecological sensitive area, the water source conservation function is weak, the water and soil loss phenomenon is serious, the ecological system is extremely easy to degrade, the recovery difficulty is large, and the process is slow. Therefore, enhancing the ecological environmental management has still its importance and necessity.
The area of irrigation and tillage in the Mongolia section in the yellow river basin in 2010-2020 is on the rise, especially in the last five years. Wherein the area of the irrigation farmland in 2010 is 9880.09km2 and in 2012 is 9898.50km 2 10335.58km in 2014 2 10231.63km in 2016 2 11147.34km in 2018 2 12954.29km in 2020 2 ；
In the embodiment, the accuracy evaluation is carried out on the classification result by adopting the confusion matrix, the calculation result of the confusion matrix shows that the classification effect of the forest land is optimal, and PA and UA are both more than 95 percent; the main extraction target of the classification, namely the classification effect of irrigation cultivated land is better, PA and UA are both more than 85%, and actually, as the samples of irrigation cultivated land and rain cultivated land are relatively more, the reliability of the calculation results of the confusion matrix in the two types is relatively higher.
The ecological hydrological remote sensing parameter extraction including normalized vegetation index (NDVI), land Surface Temperature (LST), leaf Area Index (LAI), evapotranspiration (ET), total primary productivity (GPP) and Net Primary Productivity (NPP) is realized by utilizing the inner Mongolia section of the yellow river basin; the NDVI spatial distribution has obvious geographic heterogeneity, namely, the north part is high and more than cultivated land; western is low, more than barren land; the northeast part is high, and is more closely related to forests; the lai spatial distribution has obvious geographic heterogeneity, namely, the northeast part is high and more than the forest; the north end of the west part is higher than cultivated land; the south is low, and grasslands are the main part; the npp spatial distribution has obvious geographic heterogeneity, namely, the western part is low and more than the barren land; northeast is tall, more than forests; the north end and the south of the western watershed are higher than the east; gpp is similar to npp; the et spatial distribution has a significant spatial heterogeneity: the et high value is mainly concentrated in northeast, the main forest and precipitation are more, and the average evaporation is larger; lst has significant spatial heterogeneity: the northern part is lower, the yellow river basin is covered by the northern cultivated land and forest, the vegetation evapotranspiration reduces the surface temperature in a latent heat mode, and the average LST is lower.
NDVI is increased in most areas of the study areaTrending and passing a 95% significance level test; the trend of about 70% of the area of study was examined by a 95% level of significance. The variation trend of the LAI of the Mongolian section in the yellow river basin has obvious spatial heterogeneity. Most of the regions in the west and north of the research area are LAI reduction trends, and the eastern LAI of the research area shows a significant increase trend; the GPP is an increasing trend in most areas of the research area, wherein the significant increasing trend of the GPP in the south and east areas of the research area is obvious; ET was increasing in most areas of the study area and was examined by a 95% level of significance. The trend of increasing ET increases gradually from east to west; the LST variation trend of the Mongolian section in the yellow river basin has larger spatial heterogeneity, and the LST variation trend of most areas in the research area fails to pass the 95% significance test. The north and south of the research area are mainly the increasing trend, and the LST increasing trend in the south of the research area is most obvious and reaches 0.01 K.a -1 The above.
In this embodiment, the decomposing unit decomposes the ecological environment data into the data of the preset scale by the STL time-series decomposition method, including:
STL time series decomposition decomposes the month scale data of NDVI, lai, gpp, et, lst and the like into season terms, period terms, and residual terms. Ndvi shows a fluctuating upward trend from 2001-2021, with a faster upward trend from 2016-2017. NDVI data are significantly seasonal with residuals concentrated between-0.05 and 0.05. And 2, the LAI has no obvious increasing trend from 2002 to 2012, and the LAI suddenly rises and then fluctuates after 2012. LAI data has significant seasonality and residuals are concentrated between-0.2 and 0.2. The GPP trend is stable from 2002 to 2005, the 2005 suddenly drops, the 2005 to 2012 keeps stable trend, the 2012 suddenly increases, 2012 to 2016 continuously drops, and 2016 to 2021 fluctuates. GPP data is significantly seasonal with residuals concentrated between-0.02 and 0.02. Et overall showed a fluctuating upward trend, with rising mutation points in 2006, 2012, 2016, 2018. ET data are significantly seasonal with residuals concentrated between-10 and 10. LST has strong fluctuation from 2001 to 2012 and has stable trend from 2014 to 2021. LST data is clearly seasonal with residuals concentrated between-5 and 5.
The analysis unit in this embodiment analyzes the decomposed ecological environment data including:
analyzing land utilization data: counting land utilization areas of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation and water bodies, and analyzing spatial distribution and change conditions; the method comprises the steps of representing the mutual transfer direction and the transfer area among land utilization types of yellow river watershed in different periods by adopting a transfer matrix method;
the calculation formula of the transfer matrix is as follows:
wherein P is ij The area for converting the i-type land utilization types into j-type land utilization types in different periods is changed, and n is the total number of land utilization types in the research area.
The method of using Sen's Slope estimation calculates the overall trend analysis of each parameter data over the last 40 years, and performs a significance test on the trend of the long-time sequence by an MK test method: the long-term dynamics of 5 hydrological parameter data of Precipitation, runoff, VPD, TA and TWSA are analyzed and calculated;
in this embodiment, the method of Sen's Slope estimation is used to calculate the general trend of each parameter data for about 40 years, and the trend of the long-time sequence is checked for significance by the MK test method. Calculating trend values beta for the satellite remote sensing data of 5 hydrologic parameters pixel by pixel at intervals of 1 year, so that spatial distribution data of trend change of each trial year in a long time sequence from 1980 to 2020 are obtained;
vpd: VPD has been in an increasing situation throughout the study area for the last 40 years, where there is a greater trend in north but no significance, and this conclusion, indicating gradual drought, is not statistically significant and therefore unreliable.
2. The trend of runoff change in this region over the last 40 years is shown, and in general, precipitation is reduced in the north and east regions of the study area, but is not significant, statistically significant, and therefore unreliable.
3. The trend of the highest and lowest temperatures in the region has been 40 years, and the temperature of the research region as a whole is increasing trend but not significant, not statistically significant, and therefore not reliable.
4. The trend of the TWSA in the region over the last 40 years is generally a decreasing trend, and the trend in the middle region is more obvious, but not significant, not statistically significant, and therefore unreliable.
The above-mentioned hydrokinetic parameter data were analyzed using the STL method:
the VPD is significantly affected by seasons, and smaller remainder values indicate that the seasons and trend components of the VPD are relatively accurate in describing the time series;
2. the change amplitude is gradually increased in the last 40 years, the influence of seasons is obvious, and the fact that the remainder value is scattered indicates that the season and trend components of the presentation are lower in accuracy in describing time sequences;
runoff highly coincides with the presupposition on the overall trend, indicating that there may be some potential correlation between the two;
4. the temperature of the research area is continuously improved, the influence of seasons is obvious, and the relatively concentrated remainder value also shows that the seasons and trend components of tmax and tmin in the experiment have relatively higher accuracy in describing time sequence
5. Gradually decreasing over the last 40 years and being significantly affected by the season, the more concentrated remainder values indicate that the season and trend components of TWSA are relatively accurate in describing the time series
According to the embodiment, landsat, sentinel-2 satellite data in 1990-2020 are utilized, and a visual interpretation method is adopted to analyze ecological destructive disturbance factors and mining area changes;
analysis revealed that during the fifteen years 1990-2005, the overall mining area was less and only slightly increased, but the change was not readily apparent. The upper and lower parts of the right side of the yellow river basin grow obviously in 2005-2010, and the mining areas in the areas are continuously increasing in 2010-2020 after 2010.
2. In 1990-2020, the area of mining areas in Mongolia sections in yellow river basin is wholly in an increasing trend; rapidly increased over 05-10 years;
there are a number of cases of expansion on the basis of the raw mine area within the year 3.2015-2020.
In 4.1990-2020, the general trend of the river channel in the research area is not obviously changed, but a large number of river channel changes exist. For example, there are some variations in what is originally straight to bend and what is originally curved to a biased shape.
In the embodiment, landsat, sentinel-2 satellite data in 1990-2020 are utilized, and a visual interpretation method is adopted to analyze the vegetation coverage change by using ecological destructive disturbance factors:
1) Data preprocessing:
first, in ENVI and ARCGIS, images are preprocessed.
2) NDVI index extraction
NDVI index is calculated according to the formula:
b nir and b red Representing near infrared and red band reflectance data, respectively.
3) Surface vegetation coverage estimation
A method for estimating vegetation coverage based on NDVI index is adopted:
VFC is vegetation coverage. Wherein, NDVI veg The NDVI value of the pixel completely covered by the vegetation, namely the NDVI value of the pure vegetation pixel; NDVI soil The NDVI value of the bare soil or the vegetation-free coverage area, namely the NDVI value of the vegetation-free coverage pixel.
4) Thematic map making and grading
Classifying vegetation coverage of remote sensing inversion: the earth surface vegetation coverage is in a superior state, 0.7-0.85 is in a good state, 0.55-0.7 is in a medium state, 0.4-0.55 is in a general state, and the earth surface vegetation coverage is in a poor state below 0.4.
5) Analysis of results
And analyzing the inversion result.
According to the embodiment, remote sensing inversion is carried out on the vegetation coverage of the earth surface of the research area by utilizing data such as Landsat, sentinel in 1990-2020, and inversion results are compared and analyzed;
as shown in FIG. 5, it can be seen that the areas of different vegetation coverage levels are counted, with the poorer vegetation coverage level being the largest in area, followed by a general and superior in 1990-2020. In 1990-2010, the area of the worse region was continuously increasing, and there was a general, medium and superior trend of decreasing. The vegetation coverage in 2010-2020 tends to increase, which may benefit from the ecological protection and repair of Mongolia sections in yellow river basin which is highly emphasized in recent years;
in the embodiment, landsat, sentinel-2 satellite data in 1990-2020 are used for analyzing the vegetation coverage change by adopting a visual interpretation method to the ecological destructive disturbance factors:
within fifteen years 1.1990-2005, the overall mining area was less, with only a small increase, but the change was not readily apparent. The upper and lower parts of the right side of the yellow river basin, namely the upper and middle parts of the right side of the research area, grow obviously in 2005-2010, and the mining areas of the areas are continuously increasing in 2010-2020.
2. In 1990-2020, the area of mining areas in Mongolia sections in yellow river basin is wholly in an increasing trend; rapidly increased over 05-10 years;
within the period 3.2015-2020, there are a large number of cases of expansion on the basis of the raw ore area
In this embodiment, based on the above correlation factors and index analysis results, in combination with the characteristics of the yellow river basin, an exposure-sensitivity-adaptability (E-S-se:Sup>A) framework model is adopted to construct se:Sup>A 3-level ecological vulnerability assessment index system, i.e., an ecological vulnerability assessment model.
The construction principle of the ecological vulnerability assessment model is based on simple operability, independence, scientificity and practicability; establishing a vulnerability assessment index system consisting of 3 levels and 9 specific standards;
ecological exposure: the degree to which the ecosystem is subject to external disturbances and stress; wherein the setting and description of the index weights are shown in the following table 1:
TABLE 1
Precipitation is the largest reflecting factor of the river basin ecological system, and has the most direct influence on vegetation, land utilization, soil and the like;
the difference of the east-west elevation of the research area is large, the relief of the topography is large, the steep topography can cause a large amount of runoffs and water and soil loss, and the method has great influence on the activities of regional human beings and the distribution of precipitation and vegetation.
In addition, compared with the elevation, the slope has more obvious influence on vegetation distribution in the research area, and NDVI and GPP are obviously reduced along with the increase of the slope.
From the results, the ecological restoration policy can effectively change the bearing capacity pattern of the resource environment, and the ecological restoration of the Mongolia section in the yellow river basin achieves remarkable effect.
The overall resource environment bearing capacity level shows an improvement trend, and the areas with poor bearing capacity are mainly distributed in arid climate areas with sparse vegetation and urban areas with frequent human interference. The implementation of ecological restoration engineering and policies has a positive impact on the environmental load bearing capacity improvement of the regional resources. The research result of the embodiment can provide guidance for ecological restoration of the yellow river basin and can be popularized and applied to bearing capacity assessment in other areas.
Ecological sensitivity: the ability of the ecosystem to respond to varying degrees of disturbance or pressure;
ecological adaptability: the ecosystem mitigates the disturbing active measures by means of its own anti-interference mechanism or human behavior.
Wherein the setting and description of the index weights are shown in the following table 2:
TABLE 2
The upstream area of the yellow river basin is mainly recovered by large-scale artificial vegetation, the difference between the potential water consumption and the actual water consumption is large, so that the local ecological system is affected and aggravated by water stress, an excessive recovery condition of the ecological system can exist, and the excessive recovery aggravates the water resource burden of the arid area, which is one of key factors affecting the sustainability of the ecological system.
The water stress can well reflect the influence of water (evapotranspiration) on the growth and development of vegetation, and is an important parameter for representing drought and water shortage.
The aggravation of town and the rapid population increase directly lead to the excessive occupation of land resources and the destruction of ecological environment, and bring great pressure to the ecological sustainable development of yellow river basin.
The yellow river basin is a highly sensitive area of water and wind erosion, and at present, vegetation coverage of the basin is effectively increased, and land utilization type changes directly affect ecological system structure and service function changes in the basin.
It is worth noting that the upstream area in the yellow river basin is mainly recovered by large-scale artificial vegetation, the difference between the potential water consumption and the actual water consumption is large, so that the local ecological system is seriously affected by water stress, the situation of excessive recovery of the ecological system possibly exists, and the excessive recovery can aggravate the water resource burden of the arid area, which is one of the key factors affecting the sustainability of the ecological system.
The most direct ecological measures are to establish an ecological function protection area, and by limiting human behaviors, excessive interference to the natural environment is avoided.
Aiming at the problems of complex types, water resource shortage and the like of the Mongolian segment ecosystem in the yellow river basin, the embodiment spatially reveals the relevance of the water resource utilization of the long-time sequence of nearly decades and the terrestrial ecological system. Comparison analysis with the existing studies: the association of water and an ecological system is very complex under the natural and artificial actions of Mongolia sections in the yellow river basin. It has been studied how to analyze the region as a whole from a certain point in time, and it is difficult to dynamically reveal the relationship between the two in space
The embodiment establishes a set of vulnerability assessment index system facing the complex ecological environment of the inner Mongolia section of the yellow river basin, and generates an assessment index of RS parameter-ecological model coupling; under the conditions of different water resource constraints, different spatial development characteristics and different ecological restoration, the dynamic evaluation and early warning analysis of the ecological vulnerability of the inner Mongolia section of the yellow river basin are realized. Comparison analysis with the existing studies: under the long-term influence of climate change, artificial interference and ecological engineering, the ecological vulnerability of the yellow river basin in different periods is related to the ecological endowment, recovery and cumulative effect of problems, and the current vulnerability assessment index system is difficult to reflect the overall ecological condition of the basin. Therefore, the dynamic assessment of the ecological vulnerability of the watershed with long time sequence has obvious defects, and a set of index system capable of effectively identifying the ecological vulnerability of the watershed spatially is lacked.
According to the embodiment, the regional characteristics of Mongolia sections in the yellow river basin are combined, remote sensing parameters and an ecosystem service function model are coupled, the ecosystem service functions such as wind prevention and sand fixation, water conservation, water and soil conservation, biodiversity maintenance and the like are estimated, the synergistic and trade-off relations among different service functions are studied, and sustainable development suggestions are provided by combining the ecological vulnerability assessment results. Comparison analysis with the existing studies: at present, according to the time-space dynamic characteristics of the ecosystem in the Mongolia section in the yellow river basin and in combination with the result of the vulnerability assessment of the ecosystem, the trade-off and the system relation between the analysis ecosystem services of the system are still studied.
In summary, the embodiment establishes a resource environment bearing capacity evaluation index system which highlights natural and artificial interference. The indexes are generated through coupling of an ecological model and time series multi-source remote sensing data (such as NDVI data and night light images), climate analysis data (precipitation and wind speed) and the like. Finally, the bearing capacity of the resource environment in different policy periods is evaluated, and a drainage basin resource environment bearing capacity early warning system is established. The method can provide guidance for ecological restoration of the yellow river basin, and can be popularized and applied to bearing capacity assessment in other areas.
And carrying out correlation research on water resource utilization and ecological system recovery of the yellow river basin, and revealing the evolution characteristics and rules of the ecological system under the constraint of the water resource.
According to the time-space dynamic characteristics of the ecosystem in the Mongolian section in the yellow river basin, and in combination with the result of the vulnerability assessment of the ecosystem, the balance and the system relation between the ecosystem services are analyzed by the system.
Aiming at the inner Mongolia section of the yellow river basin, a sustainable development evaluation system oriented to water resource constraint conditions is established, and a decision basis is provided for places.
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. An ecosystem evaluation system based on water resource constraints, comprising: the system comprises a data acquisition module, a data processing module, a construction module and an evaluation module;
the data acquisition module is used for acquiring ecological environment data of a research area;
the data processing module is used for processing the ecological environment data;
the construction module is used for constructing an ecological vulnerability assessment model;
the evaluation module is used for evaluating the processed ecological environment data according to the ecological vulnerability evaluation model.
2. The water resource constraint based ecosystem assessment system of claim 1, wherein the data acquisition module comprises: the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit;
the first acquisition unit is used for acquiring land utilization data of the research area; wherein the land use data includes: utilization data of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation, and water bodies;
the second acquisition unit is used for acquiring hydrological data of the research area; wherein the hydrologic data includes: ecological hydrologic remote sensing parameters and hydrologic meteorological data; the ecological hydrologic remote sensing parameters comprise: normalized vegetation index, land surface temperature, leaf area index, evapotranspiration, total primary productivity, and net primary productivity, the hydrographic data comprising: precipitation, runoff, vapor pressure deficiency, air temperature and land water reserves are abnormal;
the third acquisition unit is used for acquiring ecological destructive disturbance data of the research area; wherein the ecologically destructive perturbation data comprises: mining area change data, river change data and vegetation coverage change data;
the first acquisition unit, the second acquisition unit and the third acquisition unit are all connected with the data processing module.
3. The water resource constraint based ecosystem assessment system of claim 2, wherein the data processing module comprises: a decomposition unit and an analysis unit;
the decomposition unit is used for decomposing the ecological environment data into data of a preset scale through an STL time sequence decomposition method;
the analysis unit is used for analyzing the decomposed ecological environment data.
4. The system for assessing an ecosystem based on constraints of water resources of claim 3, wherein said analysis unit comprises: a first analysis subunit, a second analysis subunit, and a third analysis subunit;
the first analysis subunit is used for analyzing the land utilization data;
the second analysis subunit is used for analyzing the hydrologic data;
the third analysis subunit is configured to analyze the ecologically destructive perturbation data based on a visual interpretation method.
5. The water resource constraint based ecosystem assessment system of claim 4, wherein the first analysis subunit analyzing the land use data comprises:
counting land utilization areas of forest lands, shrubs, grasslands, permanent wetlands, farmlands, construction lands, sparse vegetation and water bodies, and analyzing spatial distribution and change conditions; the method comprises the steps of representing the mutual transfer direction and the transfer area among land utilization types of yellow river watershed in different periods by adopting a transfer matrix method;
the transfer matrix is:
wherein P is ij The area for converting the i-type land utilization types into j-type land utilization types in different periods is changed, and n is the total number of land utilization types in the research area.
6. The system for ecosystem assessment based on water resource constraints of claim 4, wherein the second analysis subunit analyzing the hydrographic data comprises:
and analyzing the general development trend of the hydrologic data by adopting a slope estimation method, and performing significance test on the general development trend of the hydrologic data by adopting an MK test method.
7. The system for evaluating an ecosystem based on water resource constraint according to claim 1, wherein the ecological vulnerability evaluating model constructed in the constructing module adopts an exposure-sensitivity-adaptability framework model;
in the ecological vulnerability assessment model, the index parameters for representing the exposure comprise: precipitation index, topography index and human interference level;
in the ecological vulnerability assessment model, the index parameters for representing the sensitivity comprise: elasticity of the ecological system, activity of the ecological system, service function of the ecological system and water stress of vegetation;
in the ecological vulnerability assessment model, the index parameters for representing the adaptability comprise: protection zone coefficients.
8. The ecosystem evaluation system based on water resource constraints of claim 7,
the ecological vulnerability assessment model comprises: an ecological exposure evaluation unit, an ecological sensitivity evaluation unit and an ecological adaptability evaluation unit;
the ecological exposure evaluation unit is used for evaluating the degree of the ecological system subjected to external disturbance and pressure;
the ecological sensitivity evaluation unit is used for evaluating the response capability of the ecological system to disturbance or pressure of different degrees;
the ecological adaptability evaluation unit is used for representing an active measure for alleviating disturbance of an ecological system through an anti-interference mechanism or human behaviors;
the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit are sequentially connected.
9. The system for assessing a water resource constraint based ecosystem of claim 8 wherein the building of the ecological vulnerability assessment model in the building module further comprises:
firstly, respectively setting a first-level weight for the ecological exposure evaluation unit, the ecological sensitivity evaluation unit and the ecological adaptability evaluation unit, and then respectively setting a second-level weight for the precipitation index, the topography index, the human interference degree, the elasticity of an ecological system, the activity of the ecological system, the service function of the ecological system, the vegetation water stress and the protection area coefficient.
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