CN108536908B - Method for evaluating watershed water environment safety based on non-point source nitrogen and phosphorus loss risk - Google Patents
Method for evaluating watershed water environment safety based on non-point source nitrogen and phosphorus loss risk Download PDFInfo
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Abstract
A method for evaluating the safety of watershed water environment based on non-point source nitrogen and phosphorus loss risk comprises the following steps: firstly, selecting a research area, and simulating nitrogen and phosphorus loss load by using a SWAT model; secondly, calculating rainfall runoff factors; thirdly, calculating a soil permeability factor; fourthly, calculating a transport distance factor; fifthly, data standardization processing; sixthly, calculating the weight of the evaluation index; seventhly, calculating a basin nitrogen and phosphorus pollution risk index and dividing risk levels; and eighthly, evaluating the safety of the watershed water environment. The method can realize accurate estimation of non-point source nitrogen and phosphorus loss of the watershed scale, is favorable for reflecting the time-space heterogeneity characteristic of the non-point source nitrogen and phosphorus loss, and is also favorable for optimizing and managing the watershed water environment. The method is beneficial to establishing the relationship between the watershed water environment safety and the non-point source nitrogen and phosphorus loss space-time distribution, can quickly and effectively identify the opinion loss key source region in the non-point source nitrogen and phosphorus loss risk key period, and can provide guidance and help for scientific management of the watershed water environment.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to a method for evaluating the safety of a watershed water environment based on non-point source nitrogen and phosphorus loss risks, which is used for quickly evaluating the safety of the watershed water environment by identifying and screening the watershed nitrogen and phosphorus loss risk level. Belonging to the technical field of comprehensive evaluation of drainage basin pollutants.
[ background of the invention ]
Nitrogen and phosphorus are one of essential elements for crop growth and are main limiting factors for water eutrophication. The loss of nitrogen and phosphorus caused by agricultural activities is one of the important reasons for water eutrophication. The eutrophication of water body poses serious threat to the water environment safety, resulting in a series of environmental, social and economic problems. As a world with a large population and limited cultivated land, china maintains a large and growing population by expanding the agricultural land area and applying fertilizers to improve the productivity of the farmland to produce sufficient food. In the agricultural production process, the non-point source pollution caused by the loss of nitrogen and phosphorus pollutants due to the unreasonable use of pesticides and fertilizers and the runoff effect of rainfall, irrigation and the like cannot be ignored.
The method for identifying the non-point source nitrogen and phosphorus loss to the water body pollution at the present stage mainly comprises a mechanism model and an experience model. The mechanism model is mainly used for finding out the time and the high-risk area of the pollution through continuous simulation of the output of the pollutants, the mechanism of the conversion process and the migration path. The common mechanism models are now compared, such as SWAT model, AGNPS model and the like. The SWAT model can better simulate the output load of pollutants on a unit area, but the attenuation simulation of the pollutants along with the migration path is insufficient, many scholars use the output load to carry out risk identification, and the risk assessment made by the method is only 'potential risk'. It does not consider the decay simulation of pollutants along the migration path, and can not quantify the actual river pollution amount at a certain spatial position. The empirical model can rapidly give pollution load or pollution potential in a drainage basin, such as common output coefficient method potential, pollution index, agricultural non-point source pollution potential index and the like. The method needs less input data and is simple in calculation, but is not suitable for being applied to other regions due to empirical statistical summary from a certain research region, meanwhile, the calculated nitrogen and phosphorus loss error in unit area is large, and the factor weight determination subjectivity is strong. The method can not accurately quantify the pollution risk of nitrogen and phosphorus loss to the receiving water body.
Based on the analysis of the two methods, the SWAT model can accurately quantify the nitrogen and phosphorus loss load and the like in unit area, and factors such as soil permeability coefficient, runoff depth, migration distance and the like in the empirical model evaluation method can quantify the attenuation of pollutants along with the migration path. By integrating the two methods, a SWAT model is adopted to quantify pollution source factors (nitrogen and phosphorus loss load in unit area), the attenuation of pollutants along with a migration path is quantified by adopting a soil permeability coefficient, a migration distance and a rainfall runoff factor, and finally the actual nitrogen and phosphorus river inflow from different units to a recently-received water body is determined, so that the influence of non-point source nitrogen and phosphorus loss on the watershed water environment safety is accurately evaluated.
[ summary of the invention ]
1. The purpose is as follows: according to the method, nitrogen and phosphorus loss load output by a SWAT model is based on, the attenuation of pollutants is calculated by combining soil permeability coefficient, migration distance and rainfall runoff factor, space-time distribution characteristics of nitrogen and phosphorus loss risks in the watershed can be rapidly identified, and water environment safety of a research area can be rapidly and effectively evaluated.
2. The technical scheme is as follows: the invention aims to provide a watershed water environment safety assessment method based on non-point source nitrogen and phosphorus loss risks, which is characterized in that the watershed nitrogen and phosphorus pollution loss risks are calculated by combining pollutant attenuation factors on the basis of outputting nitrogen and phosphorus loss loads by a SWAT model, and the watershed water environment safety is rapidly and effectively assessed. The specific method comprises the following steps:
the method comprises the following steps: research area selection, SWAT model simulation nitrogen and phosphorus loss load
The selection of the investigation region is the first step, and is also a critical step, of the embodiments of the present invention. The research area should have the following basic characteristics: the drainage basin is typical, is influenced by agricultural activities for a long time, has complete regional meteorological, topographic and geomorphic and hydrological data, and has high model simulation precision. Collecting meteorological data in a flow domain in a China meteorological data network, and establishing a meteorological database required by a model; establishing a soil database required by a model by combining a Chinese soil attribute database on the basis of a 1:100 ten thousand soil type distribution map provided by Nanjing soil of a Chinese academy of sciences; according to Landsat-8 data, a land utilization database of a research area is obtained by utilizing supervision and classification and field investigation; obtaining DEM data with the spatial resolution of 30 x 30m in the drainage basin from the geospatial data cloud; through investigation on local departments and farmers, agricultural production information including the agricultural production conditions, main crops, fertilization modes, irrigation and drainage modes and the like of the drainage basin is supplemented and sorted, and a drainage basin agricultural management measure database is constructed. And after data collection is finished, inputting the database into a SWAT model system, carrying out parameter calibration and adjustment on the basis of sensitivity analysis, and establishing a SWAT model as a tool for calculating the non-point source nitrogen and phosphorus loss load of the basin.
Step two: calculation of rainfall runoff factor
Under the action of surface runoff scouring, the contents of dissolved nitrogen and phosphorus carried by the surface runoff are reduced. Generally, the greater the runoff, the higher the pollutant load; the higher the potential pollutant content, the greater the pollution load caused at the same runoff rate. Surface runoff is estimated in the SWAT model by an SCS curve number method and a Green & Ampt infiltration method, so that the method directly adopts the surface runoff output in the SWAT model as a rainfall runoff factor for calculation.
Step three: calculation of soil Permeability factor
The size of the soil particle size directly influences the permeability of the soil and the retention capacity of surface runoff, and the stability of the soil structure is also used as a main basis for the anti-erosion capacity of the soil. The soil permeability factor mainly reflects the risk of leaching loss of soil nitrogen and phosphorus along with infiltration water under the action of rainfall. The risk of loss from clay to sand increases gradually. The following empirical formula was used for the calculation:
X＝(20Y)1.8
Y＝ω/10*0.03+0.002
in the formula: x is the soil permeability coefficient, mm/h; y is the average soil particle diameter value, mm; omega is the percentage of the sand content.
Step four: calculation of transport distance factor
On the scale of the watershed, the distance between different farmlands and rivers is an important influence factor for migration and diffusion of nitrogen and phosphorus pollutants of non-point sources into a water environment. The potential risk to the water environment of the source region far away from the river is generally smaller than that of the source region near the river, because in the migration process of nitrogen and phosphorus pollutants, due to biological absorption, physical interception and chemical reaction (such as nitrogen denitrification and the like), the pollutants can be continuously degraded and intercepted, the concentration can be continuously reduced, and the influence to the water environment is smaller as the intercepted content is higher and the degraded content is higher as the distance is farther.
The calculation of the migration distance is to calculate the distance between each grid point and the water body based on the water flow diagram by using the distance calculation function of ArcGIS software. According to a river flow diagram generated by a SWAT model, a Distance tool in an ArcGIS space analysis module (spatialanalysis Tools) performs downstream calculation to obtain the Distance between each point and a water body.
Step five: data normalization process
The evaluation indexes extracted in the first step, the second step, the third step and the fourth step have different dimensions and magnitude levels, when the level difference among the indexes is large, if the original index value is directly used for analysis, the function of the index with a higher value in the comprehensive analysis is highlighted, the function of the index with a lower value level is relatively weakened, in order to eliminate the influence of the different dimensions and magnitude levels and enhance the reliability of the evaluation result, the original index data needs to be standardized, and each evaluation factor is standardized to be between 0 and 1 according to a standardized formula. In the evaluation factor, if the evaluation index value is larger, the evaluation result is larger, the factor is a positive correlation evaluation index, and conversely, the factor is a negative correlation factor.
The general standardized quantification formula of the positive correlation evaluation index is as follows:
the general standardized quantization formula of the negative correlation evaluation index is as follows:
in the formula: x is the number ofijThe index value of j (j is 1,2,3,4,5) of the ith (i is 1,2,3, …, m) number of basin units; r isijA value representing a normalization; x is the number ofjminRepresents the jth index minimum; x is the number ofjmaxRepresents the jth index maximum.
Step six: calculation of evaluation index weight
The influence degrees of different evaluation indexes on the evaluation results are different, and the determination of the weight is important for the final evaluation result. The method adopts an improved ideal solution (TOPSIS) to calculate the weight of the normalized factor, and utilizes the existing index data to establish a target planning model to solve the weight, and the target planning model is constructed as follows:
wherein f isi(w1，w2，w3，w4) The sum of the squares of the weighted distances of the ith and the most and the lightest contaminated land units:
wherein w1+ w2+ w3+ w4 is 1, and wi is not less than 0; r isijIs a factor normalized value.
Order to
The weight value can be obtained by solving the equation.
Step seven: basin nitrogen and phosphorus pollution risk index calculation and risk grade division
And multiplying each evaluation factor subjected to the standardization in the fifth step by the weight sum obtained in the sixth step to obtain a watershed non-point source nitrogen and phosphorus pollution risk evaluation value, wherein the calculation formula is as follows:
in the formula: NPA represents the non-point source risk assessment score; piRepresents the ith evaluation index; wiThe weight of the i-th evaluation index is represented.
Thus, the nitrogen and phosphorus loss risk index of each unit is obtained, the distribution range is between 0 and 1, and the nitrogen and phosphorus loss risk index is normally distributed instead of uniformly distributed. Therefore, uniform division cannot be simply carried out during division, the nitrogen and phosphorus loss risk indexes are classified by using a Jenks Natural break Classification Method, namely, the difference between each Classification datum and the average value is reduced through data search, the difference Classification threshold of the average value among the classifications is increased, the difference in the classifications is minimized, and the difference among the classifications is maximized.
Step eight: watershed water environment safety assessment
The classified non-point source nitrogen and phosphorus loss grade is imported into ArcGIS, the space visualization of the non-point source nitrogen and phosphorus loss risk is realized, the influence of the space distribution of farmlands in the drainage basin on the water flow water environment safety is researched by the aid of the space analysis function through the overlapped land utilization space distribution, and the non-point source nitrogen and phosphorus loss key source area of the drainage basin is identified. Based on the output files of SWAT month-by-month or day-by-day, the critical period of the non-point source nitrogen and phosphorus loss risk of the drainage basin can be identified by combining the cultivation schedule in the drainage basin and the rainfall time distribution characteristics. Provides more pertinent suggestions for the formulation of a basin non-point source pollution treatment policy and is beneficial to the development of water environment health.
3. The advantages and the effects are as follows:
the method for evaluating the safety of the watershed water environment based on the non-point source nitrogen and phosphorus loss risk, disclosed by the invention, is based on the SWAT model and combined with an empirical model evaluation method, can realize the accurate estimation of the non-point source nitrogen and phosphorus loss of the watershed scale, is favorable for reflecting the time-space heterogeneity characteristic of the non-point source nitrogen and phosphorus loss, and is also favorable for the optimal management of the watershed water environment.
The method for evaluating the safety of the watershed water environment based on the non-point source nitrogen and phosphorus loss risk fully considers the generation of nitrogen and phosphorus loss load in unit area of the watershed and the attenuation of the nitrogen and phosphorus loss load along with a migration path. The method is beneficial to establishing the relationship between the watershed water environment safety and the non-point source nitrogen and phosphorus loss space-time distribution, can quickly and effectively identify the non-point source nitrogen and phosphorus loss risk key period opinion loss key source region, and can provide guidance and help for the scientific management of the watershed water environment.
[ description of the drawings ]
FIG. 1 is a flow chart of a watershed water environment safety assessment method based on non-point source nitrogen and phosphorus loss risks.
Fig. 2a and b are schematic diagrams of spatial distribution of non-point source nitrogen and phosphorus pollution loads of HRU scale basin in year.
Fig. 3a, b and c are schematic diagrams of runoff depth, soil permeability coefficient and transportation distance spatial distribution of a watershed.
FIG. 4 is a schematic diagram of a nitrogen and phosphorus pollution risk classification zone.
Fig. 5 is a schematic diagram of spatial distribution of nitrogen and phosphorus loss risks in an HRU-scale watershed.
[ detailed description ] embodiments
The invention provides a watershed water environment safety assessment method, which is a method for rapidly estimating the watershed non-point source nitrogen and phosphorus loss risk by combining attenuation factors and utilizing a multi-criterion analysis method on the basis of a SWAT model simulation nitrogen and phosphorus pollution load result.
Referring to fig. 1, the invention discloses a watershed water environment safety assessment method based on non-point source nitrogen and phosphorus loss risks, which comprises the following specific steps:
the method comprises the following steps:
in the case, a pliable river small watershed in the east of Heilongjiang is selected as case analysis, a database of weather, land utilization and soil and farmland management required by SWAT model simulation is established through data collection, remote sensing interpretation and field investigation, the model is used for simulating non-point source nitrogen and phosphorus pollution loads of the watershed on the basis of parameter calibration and verification, and simulation results of total nitrogen (figure 2a) and total phosphorus (figure 2b) are respectively output to obtain the spatial distribution condition of the nitrogen and phosphorus pollution loads of the watershed.
Step two:
and (3) outputting the surface runoff quantity estimated by an SCS curve number method and a Green & Ampt infiltration method in the SWAT model by using the SWAT model established in the step one to obtain the spatial distribution condition of the rainfall runoff of the watershed, which is shown in figure 3 a.
Step three:
the soil type distribution map provided by Nanjing soil of Chinese academy of sciences is taken as the basis, and the soil attribute database of China is combined to obtain the soil space distribution map of the research area and the basic properties of each soil. And (4) calculating the content percentage of the soil gravel, and calculating the soil permeability coefficient of various soils through an empirical formula to obtain the spatial distribution condition of the soil permeability coefficient of the drainage basin, which is shown in figure 3 b.
Step four:
based on the river flow diagram and the river network distribution diagram generated by the SWAT model, forward flow calculation is performed by using the Euclidean Distance in the Distance tool of the ArcGIS spatial analysis modules (spatial analysis Tools) to obtain the Distance from each river basin unit to the water body, and the spatial distribution condition of the transportation Distance of each river basin unit can be obtained, which is shown in fig. 3 c.
Step five:
and among the five factors, the other four factors except the transmission distance are positive correlation evaluation indexes, and the evaluation factors are standardized according to a general standardized quantization formula and are standardized to be between 0 and 1.
Step six:
and calculating the weight of the normalized factor by using an improved ideal solution, wherein the calculation process can be realized by Matlab, and the obtained weights of the total nitrogen, the total phosphorus, the rainfall runoff factor, the soil permeability factor and the transport distance factor are respectively as follows: 0.1856, 0.1794, 0.1833, 0.2222, 0.2294.
Step seven:
and (4) calculating each evaluation factor after the standardization treatment obtained in the fifth step and each factor weight obtained in the sixth step by using a calculation formula to obtain evaluation values of nitrogen and phosphorus pollution risks of the basin non-point source, wherein the distribution range is between 0 and 0.78. As shown in fig. 4, the nitrogen and phosphorus loss risk indexes are classified into five categories by Jenks natural break classification: the risk of potential pollution (0-0.19), the risk of slight pollution (0.20-0.25), the risk of moderate pollution (0.26-0.32), the risk of intensity pollution (0.33-0.41) and the risk of severe pollution (0.42-0.78).
Step eight: watershed water environment safety assessment
And (3) leading the classified watershed non-point source nitrogen and phosphorus loss risk level into ArcGIS, so that the regional non-point source nitrogen and phosphorus loss risk spatial distribution condition can be obtained, as shown in figure 5. By further overlapping land utilization, the influence of different land utilization on the water environment safety of the region and the influence of the space distribution of different farmlands on the water flow water environment safety can be analyzed.
Based on the output files of SWAT month-by-month or day-by-day, the critical period of the non-point source nitrogen and phosphorus loss risk of the drainage basin can be identified by combining the cultivation schedule in the drainage basin and the rainfall time distribution characteristics. Provides more pertinent suggestions for the formulation of a basin non-point source pollution treatment policy and is beneficial to the development of water environment health.
Claims (1)
1. A method for evaluating the safety of watershed water environment based on non-point source nitrogen and phosphorus loss risk is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: research area selection, SWAT model simulation nitrogen and phosphorus loss load
The research area should have the following basic characteristics: the drainage basin is typical and is influenced by agricultural activities for a long time, regional meteorological, topographic and geomorphic and hydrological data are complete, and the model simulation precision is high; collecting meteorological data in a flow domain in a China meteorological data network, and establishing a meteorological database required by a model; establishing a soil database required by a model by combining a Chinese soil attribute database on the basis of a 1:100 ten thousand soil type distribution map provided by Nanjing soil of a Chinese academy of sciences; according to Landsat-8 data, a land utilization database of a research area is obtained by utilizing supervision and classification and field investigation; obtaining DEM data with the spatial resolution of 30 x 30m in the drainage basin from the geospatial data cloud; supplementing and arranging relevant agricultural production data including the agricultural production conditions of the drainage basin, main crops, fertilization modes, irrigation and drainage modes and the like, and constructing a drainage basin agricultural management measure database; after data collection is finished, inputting the database into a SWAT model system, carrying out parameter calibration and adjustment on the basis of sensitivity analysis, and establishing a SWAT model as a tool for calculating the non-point source nitrogen and phosphorus loss load of a basin;
step two: calculation of rainfall runoff factor
Surface runoff is estimated in the SWAT model by adopting an SCS curve number method and a Green & Ampt infiltration method, and the surface runoff output in the SWAT model is directly adopted as a rainfall runoff factor for calculation;
step three: calculation of soil Permeability factor
The soil permeability factor mainly reflects the risk of soil nitrogen and phosphorus loss along with the leaching loss of infiltration water under the rainfall action, the risk of soil loss from clay to sandy soil is gradually increased, and the following empirical formula is adopted for calculation:
X＝(20Y)1.8
Y＝ω/10*0.03+0.002
in the formula: x is the soil permeability coefficient, and the unit is mm/h; y is the average soil particle diameter in mm; omega is the percentage of the sand content;
step four: calculation of transport distance factor
Calculating the migration Distance by using the Distance calculation function of ArcGIS software, calculating the Distance between each grid point and the water body based on a water flow map, and performing downstream calculation by using a Distance tool in an ArcGIS space analysis module according to a river flow map generated by a SWAT model to obtain the Distance between each point and the water body;
step five: data normalization process
According to a standardization formula, all evaluation factors are standardized to be 0-1, wherein in the evaluation factors, if the evaluation index value is larger, the evaluation result is larger, the factor is a positive correlation evaluation index, and otherwise, the factor is a negative correlation factor;
the general standardized quantification formula of the positive correlation evaluation index is as follows:
the general standardized quantization formula of the negative correlation evaluation index is as follows:
in the formula: x is the number ofijThe index value of j (j is 1,2,3,4,5) of the ith (i is 1,2,3, …, m) number of basin units; r isijThe normalized value of the expression factor; x is the number ofjminRepresents the jth index minimum; x is the number ofjmaxRepresents the jth index maximum;
step six: calculation of evaluation index weight
And calculating the weight of the normalized factor by adopting an improved ideal solution, establishing a target planning model by utilizing the existing index data to solve the weight, and constructing the target planning model as follows:
wherein f isi(w1，w2，w3，w4) The sum of the squares of the weighted distances of the ith and the most and the lightest contaminated land units:
wherein w1+ w2+ w3+ w4 is 1, and wi is not less than 0;
order to
Solving the equation to obtain the weight value;
step seven: basin nitrogen and phosphorus pollution risk index calculation and risk grade division
And multiplying each evaluation factor subjected to the standardization in the fifth step by the weight sum obtained in the sixth step to obtain a watershed non-point source nitrogen and phosphorus pollution risk evaluation value, wherein the calculation formula is as follows:
in the formula: NPA represents the non-point source risk assessment score; piRepresents the ith evaluation index; wiA weight indicating the i-th evaluation index;
thus, the nitrogen and phosphorus loss risk index of each unit is obtained, the distribution range is between 0 and 1, and the nitrogen and phosphorus loss risk index is normally distributed instead of uniformly distributed; therefore, uniform division cannot be simply carried out during division, and the Zhanjin natural break classification method is utilized to classify the nitrogen and phosphorus loss risk indexes, namely, the difference value between each classification data and the average value is calculated through data search, the difference value classification threshold value of the average value between classifications is increased, the difference in the classifications is minimized, and the difference between the classifications is maximized;
step eight: watershed water environment safety assessment
Importing the classified non-point source nitrogen and phosphorus loss grade into ArcGIS to realize the space visualization of the non-point source nitrogen and phosphorus loss risk, researching the influence of the space distribution of farmlands in the drainage basin on the water environment safety by superposing the land utilization space distribution and utilizing the space analysis function, and identifying the non-point source nitrogen and phosphorus loss key source region of the drainage basin; based on the output files of SWAT month-by-month or day-by-day, the critical period of the non-point source nitrogen and phosphorus loss risk of the drainage basin can be identified by combining the cultivation schedule in the drainage basin and the rainfall time distribution characteristics.
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| CN116399762B (en) * | 2022-11-25 | 2023-09-05 | 中国地质大学（北京） | Method for calculating pollution source supply groundwater flux based on HELP program and column experiment |
| CN116341898B (en) * | 2023-02-15 | 2023-11-03 | 中国科学院精密测量科学与技术创新研究院 | Agricultural non-point source pollution risk stage-partition-source cooperative identification method |
| CN116416108A (en) * | 2023-06-12 | 2023-07-11 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Urban small micro water body risk assessment method based on synchronous analysis of multiple factors |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103106347A (en) * | 2013-02-27 | 2013-05-15 | 北京师范大学 | Agricultural non-point source phosphorus pollution estimation method based on soil property space distribution |
| KR101467187B1 (en) * | 2013-05-06 | 2014-12-01 | (주)웹솔루스 | Terrain management method for analyzing hydrologic model and hydraulic model |
| CN105009768A (en) * | 2015-07-06 | 2015-11-04 | 中国农业科学院农业资源与农业区划研究所 | Determination method for maximum allowable input quantity of nitrorgenous fertilizer in watershed scale |
| CN107066808A (en) * | 2017-02-28 | 2017-08-18 | 西北农林科技大学 | A kind of hills area non-point source nitrogen and phosphorus loss morphosis distributed simulation method |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050273300A1 (en) * | 2003-09-29 | 2005-12-08 | Patwardhan Avinash S | Method and system for water flow analysis |
| WO2005054408A1 (en) * | 2003-11-29 | 2005-06-16 | Kasowskik Robert Valentine | Protective barrier composition comprising reaction of phosphorous acid with amines applied to a substrate |
-
2018
- 2018-03-01 CN CN201810172021.XA patent/CN108536908B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103106347A (en) * | 2013-02-27 | 2013-05-15 | 北京师范大学 | Agricultural non-point source phosphorus pollution estimation method based on soil property space distribution |
| KR101467187B1 (en) * | 2013-05-06 | 2014-12-01 | (주)웹솔루스 | Terrain management method for analyzing hydrologic model and hydraulic model |
| CN105009768A (en) * | 2015-07-06 | 2015-11-04 | 中国农业科学院农业资源与农业区划研究所 | Determination method for maximum allowable input quantity of nitrorgenous fertilizer in watershed scale |
| CN107066808A (en) * | 2017-02-28 | 2017-08-18 | 西北农林科技大学 | A kind of hills area non-point source nitrogen and phosphorus loss morphosis distributed simulation method |
Non-Patent Citations (2)
| Title |
|---|
| Utilizing water characteristics and sediment nitrogen isotopic features to identify non-point nitrogen pollution sources at watershed scale in Liaoning Province, China;Jian Ma 等;《Environmental Science and Pollution Research volume 22》;20140911;第2699-2707页 * |
| 流域水环境风险评估进展及其调控研究;董文平 等;《监测与评价》;20151222;第111-115+94页 * |
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