CN102737156B - In prediction surface water water environment, pollutant is to the method for the ecological risk of biology - Google Patents

Abstract

The invention discloses and a kind ofly predict that in surface water water environment, pollutant is to the method for the ecological risk of biology.The present invention, in conjunction with non-constant Model of Water Environment and Ecology toxicity unified model, has invented a kind of evaluation method of surface water water environment ecological risk, has comprised long-term ecological risk assessment and acute ecological risk evaluating method.The former stresses the long-term accumulated effect of pollutant, takes into account eco-toxicology effects and hydrodynamics, water quality time-space variation, is a kind of comprehensive ecological risk evaluating method; The latter stresses the acute ecological evaluation of pollutant, for the ecological risk Fast Evaluation provider science of law of surface water pollution event supports.

Description

In prediction surface water water environment, pollutant is to the method for the ecological risk of biology

Technical field

The present invention relates to and a kind ofly predict that in surface water water environment, pollutant is to the method for the ecological risk of biology.

Background technology

Scientifically predict the possibility that contamination accident occurs, specify the control factor that dissimilar contamination accident occurs, the pollution level that evaluate events may cause, coverage and risk level, carry out ecological risk assessment and have important Research Significance.

Ecological risk evaluating method mainly contains: the extrapolation method based on single species test, micro-, the middle universe Lake ecosystem model method based on several species test, the ecological risk modelling based on population or the ecosystem.The extrapolation technique of single species test plays a good precognition effect when assessing the effect of compound, and can be applied to the risk assessment to the whole ecosystem by certain hypothesis, but extrapolation method exists the hypothesis much not meeting actual conditions.It is interrelated that micro-, the middle Space simulation ecosystem can be observed between the indirectly-acting of compound and species, but source of species used is not usually in the species that the ecosystem is contained, and also do not meet the principle of ecosystem grab sample.In addition, micro-, middle universe ecological simulation comprises complicated technology and high expense.Ecological risk modelling based on population or the ecosystem had both considered the true ecosystem, consider again economical reliable, and ecological risk assessment to be combined conversion to toxicology and modeling by relying on merely ecological toxicology experimental tool, its advantage is the procedure relation mathematical formulae exposed between ecological effect to be quantized, by effect various in the ecosystem and ecological process mathematical formulae are described.Therefore, the ecological risk assessment that is applied as of ecosystem risk model provides wide development space.

At present, China still lacks urban eco landscape forest technology, and urban eco landscape forest research is in the exploratory stage, and in existing ecosystem risk evaluation model, the space characteristics of study area do not considered by some models, belongs to the zero-dimensional model of material balance in essence; Other models do not consider water quality, the HYDRODYNAMIC CHARACTERISTICS of study area, and it is a static box evaluation model in essence; Also there is department pattern only to pay close attention to the Transport And Transformation process of pollutant between multimedium, do not consider its eco-toxicology effects; The evaluation content that part stresses is only limitted to local factor, does not consider from comprehensive angle; Also have department pattern only to stress pollutant long-term accumulated effect, operand is large, can not take into account two kinds of demands that long-term accumulated evaluation and acute " fast, effectively " are evaluated.

Summary of the invention

The object of this invention is to provide and a kind ofly predict that in surface water water environment, pollutant is to the method for the ecological risk of biology.

In prediction surface water water environment provided by the invention, pollutant to be measured is to the method for the ecological risk of biology to be detected, comprises the steps:

(1) the following data group 1 of pollutant accident origination point is measured: current level, flow, roughness value and air speed value;

Obtain following data group 2: the landform of pollutant accident origination point, the longitude and latitude of pollutant accident origination point, pollutant to be measured, pollutant gross mass to be measured, pollutant proportion to be measured, pollutant rate of dissolution to be measured, pollutant saturation solubility to be measured, pollutant volatility to be measured and rate of contaminant degradation to be measured;

Every data of data group 1 and data group 2 are inputted non-constant Model of Water Environment, generates the concentration field data of pollutant to be detected in surface water water environment, as primary parameter; Described concentration field data are made up of supporting paper gridinfo.ini, gridding information file gridinfo.txt, network file grid.txt and grid composing document gridnet.txt;

The parameter of described supporting paper gridinfo.ini is as follows: the time of meshes number and dry run in node number, concentration field in the initial time of whole simulation, concentration field;

The parameter of described gridding information file gridinfo.txt is as follows: grid numbering, grid maximum length, grid area, mean depth, depth capacity, grid initial water capacity, grid enter the water yield, grid aquifer yield, grid water temperature and grid pollutant levels;

The parameter of described network file grid.txt is as follows: the X-coordinate on grid four summit, the Y-coordinate on grid four summit and grid area;

The parameter of described grid composing document gridnet.txt is as follows: the node numbering of quadrilateral four node;

(2) predict that in surface water water environment, pollutant to be measured is to the ecological risk of biology to be measured according to the method for following (a) or (b);

A () input exposes the pollutant levels Concentration (t) of each grid in moment t place and exposes moment t place pollutant to the MLC (median lethal concertration) LC50 (t) of aquatic animal to be detected, obtain the value-at-risk Risk (t) of described aquatic animal to pollutant; Risk (t)=Concentration (t)/LC50 (t);

Input exposes the pollutant levels Concentration (t) of each grid in moment t place and exposes moment t place pollutant to medium effective concentration EC50 (t) of hydrophyte to be detected, obtains the value-at-risk Risk (t) of described hydrophyte to pollutant; Risk (t)=Concentration (t)/EC50 (t);

Employing OpenGl combine with technique clustering algorithm, color fractal algorithm carry out image rendering to all grids, and in output surface water water environment, pollutant to be measured is to the ecological risk figure of biology to be measured;

B () gathers the water sample of described surface water water environment, detect water sample and obtain water quality parameter; Described water quality parameter comprises nutrient concentration, chip concentration, water plant biomass and aquatic animal biomass; Described nutrient concentration refers to ammonia nitrogen concentration, nitrate concentration, phosphate concn, gas concentration lwevel and dissolved oxygen concentration; Described chip concentration refers to the concentration value of solubility and non-solubility chip;

By above-mentioned data input Ecology toxicity model, select pollutant to be measured, then the primary parameter obtained with step (1), for input parameter, to apply in described Ecology toxicity model prediction surface water water environment pollutant to be detected to the ecological risk of biology to be detected;

Read gridding information file gridinfo.txt, extract the unstructured grids geometry distribution of surface water water environment, space lattice aggregation technique is adopted to be coupled with Ecology toxicity model, each grid after grid gathering is as an input block of Ecology toxicity model, and all space lattice information is by GIS platform MAPWINGIS assembly management and maintenance;

Read gridding information file gridinfo.txt, extract dynamic parameter, adopt time step coupling technique to be coupled with Ecology toxicity model; Described dynamic parameter comprises grid maximum length, grid area, mean depth, depth capacity, grid enter the water yield (dynamic change), grid aquifer yield (dynamic change), grid water temperature, grid pollutant levels;

Described Ecology toxicity model processes one by one to each input block, obtain the concentration change of biology to be measured in each grid, biotic population and biomass variety, employing OpenGL combine with technique clustering algorithm, color fractal algorithm carry out graph rendering to each grid, and in output surface water water environment, pollutant to be detected is to the ecological risk figure of biology to be detected.

The non-constant Model of Water Environment of existing maturation all can adopt, as Delft3D, MIKE21, EFDC etc.

Described Ecology toxicity model can be AQUATOX model.

Technical scheme of the present invention is specific as follows:

1, non-constant Model of Water Environment is utilized to obtain primary parameter

Non-constant Model of Water Environment is utilized to generate supporting paper gridinfo.ini (see table 1), gridding information file gridinfo.txt (see table 2), network file grid.txt (see table 3) and grid composing document gridnet.txt (see table 4);

Table 1gridinfo.ini file layout

Start-time

Point-num

Net-num

Frame-num

Table 1 describes simulation preparation.Start-time is the initial time of whole simulation, and set form is " 2007-01-04 "; Point-num is node number in concentration field; Net-num is meshes number in concentration field; Frame-num is the time of dry run, and unit is sky.

Table 2gridinfo.txt file layout

Table 2 describes the details of each computing grid.ID is grid numbering; Length is grid maximum length, and unit is rice; Area is grid area, and unit is square metre; Mean is mean depth, and unit is rice; Max is depth capacity, and unit is rice; InitVol is grid initial water capacity, and unit is cubic meter; Inflow is that grid enters the water yield, and unit is cubic meter/sky; Outflow is grid aquifer yield, and unit is cubic meter/sky; Temp is grid water temperature, and unit is degree Celsius; Tox is grid pollutant levels, unit mg/litre.Table 2 data layout is according to grid numbering, record successively each grid from initial time to the maximum length in the dry run time interval, the data such as grid area, mean depth, maximum water depth, pollutant levels.

Table 3grid.txt file layout

X1

Y1

X2

Y2

X3

Y3

X4

Y4

Area

Table 3 describes quadrilateral mesh structured file form, and X1-Y4 have recorded X-coordinate and the Y-coordinate on grid four summit, and Area have recorded grid area.

Table 4gridNet.txt file layout

Node1

Node2

Node3

Node4

Table 4 describes quadrilateral mesh composition information, and Node1-Node4 is the node numbering of quadrilateral four node.

2, with step 1 obtain primary parameter for input parameter, carry out acute ecological risk assessment;

Aquatic animal LC50 value and the hydrophyte EC50 value objective characterisation toxicological effect of biological contaminated thing, therefore uses the biological risk status of the mode dominant expression of pollutant levels and LC50 or EC50 ratio.For the means lacking " quick, effective " in current Ecology risk evaluating method, the present invention adopts the concentration value of each grid in contaminant density field divided by the method for aquatic animal LC50 value to calculate the acute risk of aquatic animal.LC50 and MLC (median lethal concertration) weigh to be present in poisonous substance in water to aquatic animal be present in poisonous substance in the air important parameter to the toxicity size of mammal and even the mankind.Concrete computation process is, obtain and expose moment t place pollutant to LC50 value LC50 (t) of aquatic animal effect, obtain the pollutant levels Concentration (t) exposing each grid in moment t place, finally calculate acute value-at-risk Risk (t)=Concentration (the t)/LC50 (t) of certain aquatic animal to pollutant.

Correspondingly, each grid concentration in contaminant density field is adopted to calculate the acute risk of hydrophyte divided by the method for hydrophyte EC50 value.EC50 and medium effective concentration, refer to and cause 50% test organism to produce a certain specific reaction, or the concentration of the suppressed half of certain indicator reaction.Concrete computation process is, obtain and expose moment t place pollutant to EC50 value EC50 (t) of hydrophyte effect, obtain and expose each grid pollutant levels Concentration (t) in moment t place, certain aquatic animal is to acute value-at-risk Risk (t)=Concentration (the t)/EC50 (t) of pollutant.

Employing OpenGl combine with technique clustering algorithm, color fractal algorithm carry out image rendering to all grids, export acute ecological risk figure.

3, with step 1 obtain primary parameter for input parameter, carry out long-term ecological risk assessment

The open source code AQUATOX model that the present invention adopts EPA to issue is as Ecology toxicity basic model, this model can predict multiple pollutant, as nutritive salt, the organic chemistry material home to return in water environment, and they are on the impact of Ecology, comprise the impact on fish, invertabrate, hydrophyte.Therefore the relation identifying and understand between water quality, physical environment, aquatic organism can be helped.The Transport And Transformation process of pollutant between multimedium both paid close attention to by this model, emphasizes eco-toxicology effects again, comparatively speaking, is a most comprehensive ecological risk assessment model.But this model using overall for whole study area as research object, and suppose any time water body Homogeneous phase mixing, therefore study area space characteristics do not considered by model, study area water quality, hydrodynamic force difference is not considered yet, be a static evaluation model in essence, therefore the present invention has carried out the improvement of time-space variation to model.

The method of the Ecology toxicity model of the non-constant Model of Water Environment of coupling and improvement is adopted to set up long-term ecological risk evaluating method.In the coupling process of model, step-length coupling service time, space lattice gathering and risk field develop visual three technology.Whole coupling process is: read the two-dimentional hydrodynamic force pollution concentration field data gridinfo.txt that non-constant Model of Water Environment generates, this concentration field provides two class parameters for Ecology toxicity model, one class is to provide study area unstructured grids geometry distribution, space lattice aggregation technique is adopted to be coupled with Ecology toxicity model, each grid after grid gathering is as a computing unit of Ecology toxicity model, and all space lattice information is by GIS platform MAPWINGIS assembly management and maintenance; Two be to provide Ecology toxicity model need input dynamic parameter, time step coupling technique is adopted to be coupled with Ecology toxicity model, non-constant Model of Water Environment comprises accident point scope (length), surface area, mean depth, depth capacity, enters streamflow (dynamic change), goes out streamflow (dynamic change), water temperature, point source load etc. for the dynamic parameter that Ecology toxicity model provides, and Ecology toxicity model carries out simulation trial one by one to each computing unit; The operation result of model is the concentration change of each independent grid cell, biotic population and biomass variety, employing OpenGL combine with technique clustering algorithm, color fractal algorithm carry out graph rendering to big data quantity grid, represent whole survey region risk field Dynamic Evolution.Long-term ecological risk evaluating method result exports as multiple pollutant, and as nutritive salt, the organic chemistry material home to return in water environment, and they are on the impact of Ecology, comprise the impact on fish, invertabrate, hydrophyte.

Know-why of the present invention: after contamination accident occurs, utilizes ripe non-constant Model of Water Environment analog result, as the input parameter of acute ecological risk assessment and long-term ecological risk assessment; Acute risk assessment adopts the method for pollutant levels and influenced hydrobiont LC50 (animal), EC50 (plant) ratio calculation; Long-term risk evaluation is then that each grid in the network used using non-constant Model of Water Environment is as computing unit, the parameters such as the hydrodynamic force of each grid, water quality are obtained from Model of Water Environment analog result, these parameters are supplied to the Ecology toxicity model AQUATOX also grid computing one by one of improvement, employing OpenGL combine with technique clustering algorithm, color fractal algorithm carry out graph rendering to result of calculation, export whole risk field Dynamic Evolution.Two kinds of risk evaluating methods had both considered towards emergent " fast, effectively " demand, and highlight again the long-term accumulated effect of pollutant in water environment, pollution level, coverage and the risk level that may cause for evaluate events provide scientific basis.

The present invention is owing to taking above technical scheme, it has the following advantages: (1) integrated use ecological toxicology mechanism and Model of Water Environment set up regional scale Method of Water Environmental Risk Assessment, take into account eco-toxicology effects and hydrodynamics, water quality time-space variation, overcome the shortcoming that existing ecological evaluation lacks space distribution and Time dynamic; (2) provide acute risk assessment and long-term risk to evaluate two kinds of methods, take into account long-term accumulated evaluation and acute " fast, effectively " evaluation two kinds of demands, towards practical application.

The present invention, in conjunction with non-constant Model of Water Environment and Ecology toxicity unified model, has invented a kind of evaluation method of surface water water environment ecological risk, has comprised long-term ecological risk assessment and acute ecological risk evaluating method.The former stresses the long-term accumulated effect of pollutant, takes into account eco-toxicology effects and hydrodynamics, water quality time-space variation, is a kind of comprehensive ecological risk evaluating method; The latter stresses the acute ecological evaluation of pollutant, for the ecological risk Fast Evaluation provider science of law of surface water pollution event supports.

Accompanying drawing explanation

Fig. 1 is region, Eight Diagrams continent, Nanjing quadrangular mesh partition.

Fig. 2 is Daphnia 48 hours risk distribution figure.

Fig. 3 is t=0 hour Daphnia ppb.

Fig. 4 is t=24 hour Daphnia ppb.

Fig. 5 is t=48 hour Daphnia ppb.

Fig. 6 is t=72 hour Daphnia ppb.

Fig. 7 is t=96 hour Daphnia ppb.

Fig. 8 is t=120 hour Daphnia ppb.

Fig. 9 is t=144 hour Daphnia ppb.

Figure 10 is t=168 hour Daphnia ppb.

Figure 11 is t=192 hour Daphnia ppb.

Figure 12 is t=216 hour Daphnia ppb.

Figure 13 is t=240 hour Daphnia ppb.

Figure 14 is t=264 hour Daphnia ppb.

Figure 15 is t=288 hour Daphnia ppb.

Figure 16 is t=312 hour Daphnia ppb.

Embodiment

Following embodiment is convenient to understand the present invention better, but does not limit the present invention.Experimental technique in following embodiment, if no special instructions, is conventional method.

Embodiment,

For region, Eight Diagrams continent, Nanjing nitrobenzene contamination, technical scheme of the present invention is set forth.

One, apply non-constant Model of Water Environment analog computation and generate pollutant levels field data, supporting paper gridinfo.ini, gridding information file gridinfo.txt, network file grid.txt and grid composing document gridnet.txt are set according to concentration field data creation.

Measure the following data in Eight Diagrams continent, Nanjing: river course current level, unit is rice; Flow, unit is a cube meter per second; Roughness value; Air speed value, unit is meter per second.

Obtain the following data of pollutant: the landform measured data of pollutant accident origination point; The longitude and latitude of pollutant accident origination point, pollutant (this example is nitrobenzene), pollutant gross mass, unit is ton; Pollutant proportion; Pollutant rate of dissolution, unit is Kg/ (5min.Kg); Pollutant saturation solubility (%); Pollutant volatility, unit is Kg/ (5min.Kg); Rate of contaminant degradation, unit is Kg/ (5min.Kg).

Concrete data are as follows:

River course current level is 2.3 meters, roughness value is 0.02, air speed value is 5.0 meter per seconds, and angle is positive north;

The flow value at nine monitoring stations (Nanjing import, hereditary property continent head, Zhu Jia Shan Zha, Ma Chahezha, Yue Zi river course, Liang Zhuan, new people, small rowboat mouth, the Chunhe river mouth) place in Eight Diagrams continent, Nanjing, in table 1.

The flow value at nine monitoring station places in Eight Diagrams continent, table 1 Nanjing

Time	Nanjing import	Hereditary property continent head	Zhu Jia mountain lock	Ma Chahezha	Yue Zi river course	Liang Zhuan	New people	Small rowboat mouth	The Lushui River river mouth
										2007-5-1 0:00	18824.961	2.131	1.303	22.838	-8.099	-3.01	-4.741	-1.581	24.93
2007-5-2 0:00	19941.99	2.369	0.548	-0.331	-10.202	-4.212	-6.57	-3.834	21.807
										2007-5-3 15:00	22120.133	2.686	-1.412	15.814	-7.421	-4.33	-6.368	3.117	32.999
2007-5-4 0:00	21974.219	2.75	-0.366	-16.797	-9.268	-5.23	-7.831	0.104	26.209
										2007-5-5 0:00	22831.436	2.947	-1.562	-34.085	-9.688	-6.099	-9.029	0.323	26.611
2007-5-6 0:00	23886.176	3.12	-3.039	-45.912	-9.404	-6.716	-9.747	1.598	27.901
										2007-5-7 0:00	24582.279	3.285	-4.473	-54.252	-8.686	-7.103	-10.104	2.95	28.777
2007-5-8 0:00	25221.674	3.302	-3.939	-1.326	-3.606	-4.337	-4.214	9.359	34.483
										2007-5-9 0:00	25271.215	3.215	-2.986	28.346	-1.775	-1.339	2.613	11.126	32.524
2007-5-10 0:00	25287.308	3.087	-1.69	51.726	-0.062	1.377	5.085	13.462	39.319
										2007-5-11 0:00	24583.152	3.014	-1.052	55.679	0.078	0.92	4.854	13.537	44.44
2007-5-12 0:00	24045.938	2.867	-0.635	55.299	-0.347	-0.595	2.625	12.987	45.657
										2007-5-13 0:00	22879.522	2.741	-0.374	48.686	-1.115	-1.536	-0.703	11.377	43.681
2007-5-14 0:00	21964.762	2.661	-0.455	42.377	-1.527	-1.729	-1.476	10.312	41.991
										2007-5-15 0:00	21203.042	2.569	0.141	46.483	-2.14	-1.931	-2.163	9.254	39.986
2007-5-16 0:00	20175.19	2.586	1.467	56.387	-3.186	-2.455	-3.267	7.412	37.136
										2007-5-17 0:00	19859.903	2.522	2.556	60.196	-2.654	-2.174	-2.838	7.65	36.581
2007-5-18 0:00	18795.307	2.507	3.231	49.466	-3.924	-2.618	-3.76	5.264	33.706
										2007-5-19 0:00	17751.305	2.422	2.095	1.221	-4.661	-2.6	-3.881	3.613	32.784
2007-5-20 0:00	17068.502	2.335	-0.521	-33.963	-3.366	-2.01	-2.898	5.07	35.057
										2007-5-21 0:00	17080.014	2.276	-2.869	-51.06	-3.16	-2.038	-2.873	4.915	31.51
2007-5-22 0:00	17385.37	2.197	-2.736	-28.841	-1.389	-0.934	-0.473	6.049	20.961
										2007-5-23 0:00	17940.624	2.094	-0.608	17.485	1.992	0.934	1.933	9.504	13.194
2007-5-24 0:00	18363.377	1.91	1.488	47.798	4.422	1.79	3.154	13.757	27.124
										2007-5-25 0:00	18217.104	1.78	1.898	51.482	3.947	1.711	3.005	14.049	38.665

2007-5-26 0:00	17758.474	1.752	1.906	48.362	2.562	1.326	2.489	12.291	40.798
										2007-5-27 0:00	17539.228	1.667	1.644	43.148	1.984	1.058	2.089	11.552	39.986
2007-5-28 0:00	17081.192	1.68	1.552	38.365	-0.279	-0.225	0.068	8.887	36.697
										2007-5-29 0:00	16992.963	1.798	1.623	39.85	-1.682	-0.769	-1.014	7.1	34.652
2007-5-30 0:00	17508.943	1.938	1.801	43.566	-2.876	-1.282	-1.851	5.919	33.407
										2007-5-31 0:00	17947.915	2.037	2.134	46.743	-2.862	-1.453	-2.06	6.216	33.538
2007-6-1 0:00	18142.264	2.096	2.137	34.964	-4.589	-2.055	-3.105	3.733	30.157
										2007-6-2 0:00	18479.732	2.291	1.812	13.963	-7.109	-3.132	-4.847	0.167	26.193
2007-6-3 0:00	19242.01	2.523	0.906	-17.797	-8.568	-4.14	-6.384	-1.292	25.152
										2007-6-4 0:00	20161.887	2.697	-0.603	-37.512	-7.943	-4.505	-6.776	0.671	27.694
2007-6-5 0:00	21094.083	2.818	-3.315	-61.094	-7.706	-4.913	-7.254	1.63	27.713
										2007-6-6 0:00	22030.857	2.925	-4.381	-53.79	-6.265	-4.794	-6.826	3.847	26.405
2007-6-7 0:00	23154.493	2.973	-3.981	-17.51	-4.159	-4.014	-4.902	6.692	21.305
										2007-6-8 0:00	24215.081	3.01	-2.827	18.341	-2.589	-3.039	-2.667	9.117	22.208
2007-6-9 0:00	24807.785	3.008	-1.813	40.913	-1.354	-1.91	0.083	11.747	35.996
										2007-6-10 0:00	24990.894	3.011	-1.574	44.646	-1.761	-2.305	-1.322	11.979	43.206
2007-6-11 0:00	25020.9	3.055	-1.631	40.189	-2.791	-3.176	-3.239	10.951	43.479
										2007-6-12 0:00	25204.941	3.123	-2.186	27.661	-4.262	-4.266	-5.255	9.332	41.38
2007-6-13 0:00	25667.246	3.233	-2.938	17.834	-5.659	-5.368	-7.032	7.995	39.451
										2007-6-14 0:00	26404.741	3.434	-3.301	15.329	-7.573	-7.144	-9.71	6.252	37.268
2007-6-15 0:00	27700.297	3.695	-3.543	9.035	-9.682	-9.542	-13.123	4.663	35.506
										2007-6-16 0:00	29079.145	3.962	-3.41	5.541	-9.784	-11.082	-14.945	5.44	38.334
2007-6-17 0:00	29962.459	4.189	-3.87	-7.915	-9.715	-12.373	-16.421	5.94	39.722
										2007-6-180:00	31278.234	4.378	-5.597	-23.538	-8.969	-12.927	-16.541	7.58	42.313
2007-6-19 0:00	32781.953	4.564	-7.194	-28.897	-9.071	-14.143	-17.67	8.4	43.097
										2007-6-20 0:00	34182.838	4.74	-7.772	-13.243	-8.29	-14.45	-17.103	10.157	44.427
2007-6-21 0:00	35265.351	4.866	-7.488	13.947	-6.742	-13.354	-13.989	12.703	48.696
										2007-6-22 0:00	35896.651	4.897	-7.288	30.457	-5.818	-12.251	-11.112	14.444	54.074
2007-6-23 0:00	36538.669	4.947	-7.6	27.261	-6.719	-13.832	-13.803	14.071	55.355
										2007-6-24 0:00	37696.491	5.053	-8.289	16.48	-8.338	-16.662	-18.118	13.306	57.002
2007-6-25 0:00	38856.762	5.214	-8.765	11.695	-9.086	-18.756	-20.524	13.314	58.332
										2007-6-26 0:00	40057.525	5.383	-9.258	10.179	-9.142	-20.034	-21.159	14.111	60.474
2007-6-27 0:00	40556.608	5.54	-8.958	35.132	-7.245	-18.16	-15.677	16.401	64.311
										2007-6-28 0:00	40578.826	5.609	-8.718	54.733	-6.162	-16.494	-10.514	17.465	65.365
2007-6-29 0:00	40966.498	5.674	-9.103	36.103	-7.308	-19.027	-15.791	16.475	64.283
										2007-6-30 0:00	41157.755	5.768	-9.149	25.262	-7.606	-20.2	-17.389	16.125	63.581

Within 2000, Eight Diagrams continent regional feature measured data is in table 2.

Table 2 Eight Diagrams continent regional feature measured data in 2000

Sequence number	Longitude	Latitude	X-coordinate	Y-coordinate	The depth of water	Sequence number	Longitude	Latitude	X-coordinate	Y-coordinate	The depth of water
												1	118.728212	32.092232	39663151.4	3553389	-6.298	251	118.725995	32.099331	39662929.5	3554173	25.372
2	118.727957	32.092299	39663127.2	3553396	-3.334	252	118.725748	32.099443	39662906	3554185	25.367
												3	118.727699	32.092365	39663102.8	3553403	2.752	253	118.725501	32.099554	39662882.5	3554197	25.63
4	118.727441	32.092441	39663078.3	3553411	10.541	254	118.725253	32.099666	39662858.9	3554209	26.078
												5	118.727183	32.092508	39663053.8	3553418	18.288	255	118.725003	32.099786	39662835	3554222	26.413
6	118.726921	32.092583	39663028.9	3553426	23.329	256	118.724752	32.099907	39662811.1	3554235	26.661
												7	118.72666	32.092659	39663004.1	3553434	25.694	257	118.724499	32.100028	39662787	3554248	27.067
8	118.726394	32.092735	39662978.9	3553442	27.266	258	118.724245	32.100148	39662762.8	3554261	27.462
												9	118.726126	32.092802	39662953.5	3553449	27.326	259	118.723988	32.100269	39662738.4	3554274	27.435
10	118.725859	32.092886	39662928.1	3553458	26.155	260	118.723729	32.10039	39662713.7	3554287	27.208
												11	118.725588	32.092953	39662902.4	3553465	23.505	261	118.723472	32.10052	39662689.2	3554301	26.86
12	118.725315	32.093029	39662876.5	3553473	20.71	262	118.723212	32.100649	39662664.4	3554315	26.431

13	118.725045	32.093114	39662850.8	3553482	17.92	263	118.722949	32.100779	39662639.4	3554329	25.907
												14	118.724772	32.093199	39662824.9	3553491	15.332	264	118.722685	32.100909	39662614.2	3554343	25.369
15	118.7245	32.093293	39662799.1	3553501	13.604	265	118.722419	32.101039	39662588.9	3554357	24.772
												16	118.724224	32.093377	39662772.9	3553510	14.938	266	118.722154	32.101169	39662563.6	3554371	23.934
17	118.723949	32.093471	39662746.7	3553520	15.709	267	118.721889	32.101299	39662538.4	3554385	22.987
												18	118.72367	32.093565	39662720.2	3553530	15.879	268	118.721624	32.101428	39662513.1	3554399	22.08
19	118.723389	32.093659	39662693.5	3553540	16.022	269	118.721359	32.101558	39662487.9	3554413	20.969
												20	118.723109	32.093762	39662666.9	3553551	16.647	270	118.721094	32.101697	39662462.6	3554428	19.47
21	118.72283	32.093874	39662640.4	3553563	17.433	271	118.720829	32.101827	39662437.4	3554442	17.285
												22	118.722546	32.093977	39662613.4	3553574	18.28	272	118.720566	32.101966	39662412.3	3554457	12.634
23	118.722283	32.094116	39662588.3	3553589	19.154	273	118.720302	32.102105	39662387.1	3554472	5.306
												24	118.722005	32.094237	39662561.8	3553602	20.021	274	118.720042	32.102243	39662362.3	3554487	-0.39
25	118.721723	32.09434	39662535	3553613	20.907	275	118.719783	32.102382	39662337.6	3554502	-3.624
												26	118.721438	32.094452	39662507.9	3553625	21.854	276	118.719523	32.102521	39662312.8	3554517	-4.894
27	118.721151	32.094564	39662480.6	3553637	22.873	277	118.731463	32.09831	39663447.6	3554068	-6.861
												28	118.720862	32.094686	39662453.1	3553650	24.011	278	118.73121	32.098412	39663423.5	3554079	-5.778
29	118.720568	32.094798	39662425.2	3553662	25.14	279	118.730959	32.098515	39663399.6	3554090	-2.214
												30	118.720273	32.09491	39662397.1	3553674	26.267	280	118.73071	32.098618	39663375.9	3554101	4.806
31	118.719975	32.095031	39662368.8	3553687	27.513	281	118.730464	32.098729	39663352.5	3554113	9.833
												32	118.719676	32.095161	39662340.3	3553701	28.568	282	118.73022	32.098832	39663329.3	3554124	14.259
33	118.719374	32.095283	39662311.6	3553714	29.23	283	118.729979	32.098934	39663306.3	3554135	18.539
												34	118.719071	32.095413	39662282.7	3553728	29.607	284	118.729738	32.099037	39663283.4	3554146	23.701
35	118.718765	32.095543	39662253.6	3553742	29.349	285	118.729502	32.099139	39663260.9	3554157	28.373
												36	118.71846	32.095692	39662224.6	3553758	28.544	286	118.729268	32.099241	39663238.7	3554168	32.5
37	118.718158	32.09584	39662195.8	3553774	27.399	287	118.729036	32.099353	39663216.6	3554180	36.274
												38	118.717856	32.095998	39662167	3553791	25.972	288	118.728808	32.099464	39663194.8	3554192	39.187
39	118.717555	32.096164	39662138.3	3553809	24.519	289	118.728579	32.099575	39663173	3554204	39.745
												40	118.717252	32.09633	39662109.4	3553827	22.971	290	118.728351	32.099678	39663151.3	3554215	37.619
41	118.716948	32.096497	39662080.4	3553845	20.589	291	118.728121	32.099789	39663129.4	3554227	34.828
												42	118.716643	32.096672	39662051.3	3553864	15.609	292	118.727889	32.0999	39663107.3	3554239	32.252
43	118.716338	32.096857	39662022.2	3553884	9.832	293	118.727656	32.100003	39663085.1	3554250	30.731
												44	118.716034	32.097041	39661993.1	3553904	3.482	294	118.72742	32.100114	39663062.6	3554262	29.604
45	118.715726	32.097226	39661963.7	3553924	-1.817	295	118.727181	32.100226	39663039.9	3554274	28.602
												46	118.715419	32.09741	39661934.4	3553944	-3.974	296	118.726945	32.100346	39663017.4	3554287	27.702
47	118.728674	32.093209	39663193.3	3553498	-8.107	297	118.726704	32.100458	39662994.4	3554299	27.166
												48	118.728403	32.093284	39663167.6	3553506	-5.79	298	118.726464	32.100578	39662971.6	3554312	26.949
49	118.728134	32.09336	39663142.1	3553514	-0.593	299	118.72622	32.10069	39662948.3	3554324	26.882
												50	118.727868	32.093445	39663116.8	3553523	7.243	300	118.725973	32.10081	39662924.8	3554337	26.904
51	118.727605	32.093521	39663091.8	3553531	17.032	301	118.725724	32.100922	39662901.1	3554349	27.009
												52	118.727344	32.093605	39663067	3553540	22.258	302	118.725472	32.101042	39662877.1	3554362	27.086
53	118.727085	32.09369	39663042.4	3553549	25.194	303	118.725217	32.101154	39662852.8	3554374	27.123
												54	118.726828	32.093766	39663018	3553557	26.226	304	118.724961	32.101275	39662828.4	3554387	27.033
55	118.72657	32.09385	39662993.5	3553566	26.931	305	118.724706	32.101395	39662804.1	3554400	26.811
												56	118.726313	32.093935	39662969.1	3553575	26.762	306	118.724451	32.101525	39662779.8	3554414	26.511

57	118.726051	32.094011	39662944.2	3553583	25.304	307	118.724197	32.101655	39662755.6	3554428	26.146
												58	118.725787	32.094087	39662919.2	3553591	24.236	308	118.723937	32.101785	39662730.9	3554442	25.636
59	118.725525	32.09418	39662894.3	3553601	24.745	309	118.723677	32.101914	39662706.1	3554456	25.068
												60	118.725262	32.094265	39662869.3	3553610	22.949	310	118.723412	32.102035	39662680.8	3554469	24.465
61	118.724999	32.094368	39662844.3	3553621	22.426	311	118.723147	32.102165	39662655.6	3554483	23.764
												62	118.724734	32.094462	39662819.1	3553631	20.344	312	118.722884	32.102286	39662630.6	3554496	22.831
63	118.724466	32.094555	39662793.6	3553641	18.82	313	118.722622	32.102407	39662605.6	3554509	21.848
												64	118.724197	32.094649	39662768.1	3553651	18.052	314	118.72236	32.102536	39662580.6	3554523	20.858
65	118.723924	32.094743	39662742.1	3553661	17.765	315	118.722099	32.102657	39662555.8	3554536	19.767
												66	118.723655	32.094855	39662716.5	3553673	18.226	316	118.72184	32.102787	39662531.1	3554550	18.394
67	118.723385	32.094958	39662690.8	3553684	18.911	317	118.721581	32.102908	39662506.4	3554563	16.419
												68	118.723113	32.09507	39662665	3553696	19.714	318	118.721324	32.103046	39662481.9	3554578	12.514
69	118.722852	32.095199	39662640.1	3553710	20.564	319	118.721068	32.103176	39662457.5	3554592	7.275
												70	118.722586	32.095311	39662614.8	3553722	21.44	320	118.720815	32.103306	39662433.4	3554606	2.068
71	118.722318	32.095423	39662589.3	3553734	22.351	321	118.720567	32.103435	39662409.8	3554620	-2.401
												72	118.722046	32.095544	39662563.4	3553747	23.309	322	118.720316	32.103565	39662385.9	3554634	-4.923
73	118.721772	32.095656	39662537.3	3553759	24.343	323	118.732053	32.099384	39663501.3	3554188	-7.192
												74	118.721494	32.095777	39662510.9	3553772	25.526	324	118.731808	32.099477	39663478	3554198	-6.198
75	118.721215	32.095898	39662484.3	3553785	26.548	325	118.731567	32.09958	39663455.1	3554209	-3.311
												76	118.720934	32.096019	39662457.6	3553798	27.438	326	118.731327	32.099682	39663432.3	3554220	2.012
77	118.720653	32.096149	39662430.8	3553812	28.053	327	118.731092	32.099794	39663409.9	3554232	7.776
												78	118.720371	32.096279	39662403.9	3553826	28.523	328	118.73086	32.099896	39663387.8	3554243	13.334
79	118.720087	32.096409	39662376.9	3553840	28.95	329	118.73063	32.099998	39663365.9	3554254	18.95
												80	118.719804	32.096548	39662349.9	3553855	29.147	330	118.730401	32.10011	39663344.1	3554266	24.646
81	118.719518	32.096687	39662322.7	3553870	28.7	331	118.730173	32.100221	39663322.4	3554278	30.079
												82	118.719231	32.096826	39662295.3	3553885	27.928	332	118.729948	32.100332	39663300.9	3554290	34.217
83	118.718941	32.096975	39662267.7	3553901	26.951	333	118.729724	32.100443	39663279.6	3554302	36.648
												84	118.718648	32.097123	39662239.8	3553917	25.656	334	118.729501	32.100564	39663258.3	3554315	38.369
85	118.718354	32.097271	39662211.8	3553933	24.17	335	118.729278	32.100675	39663237.1	3554327	39.151
												86	118.718061	32.097428	39662183.8	3553950	22.295	336	118.729055	32.100786	39663215.8	3554339	37.604
87	118.717764	32.097586	39662155.5	3553967	18.757	337	118.728827	32.100897	39663194.1	3554351	35.797
												88	118.717468	32.097752	39662127.3	3553985	13.783	338	118.728597	32.101009	39663172.2	3554363	34.198
89	118.717173	32.097927	39662099.1	3554004	8.905	339	118.728365	32.10112	39663150.1	3554375	32.812
												90	118.716875	32.098103	39662070.7	3554023	2.401	340	118.728131	32.101232	39663127.8	3554387	31.717
91	118.716579	32.098278	39662042.4	3554042	-2.451	341	118.727895	32.101343	39663105.3	3554399	30.521
												92	118.716284	32.098453	39662014.2	3554061	-3.817	342	118.727657	32.101454	39663082.6	3554411	29.291
93	118.729169	32.094131	39663238.4	3553601	-8.98	343	118.727417	32.101566	39663059.8	3554423	28.246
												94	118.728909	32.094242	39663213.7	3553613	-7.527	344	118.727176	32.101686	39663036.8	3554436	27.844
95	118.72865	32.094345	39663189	3553624	-2.512	345	118.726932	32.101807	39663013.6	3554449	27.732
												96	118.728389	32.094448	39663164.2	3553635	5.361	346	118.726688	32.101927	39662990.3	3554462	27.723
97	118.728128	32.094541	39663139.4	3553645	13.425	347	118.726438	32.102039	39662966.5	3554474	27.707
												98	118.727868	32.094635	39663114.7	3553655	20.3	348	118.726187	32.10216	39662942.6	3554487	27.625
99	118.727612	32.094729	39663090.3	3553665	23.852	349	118.725934	32.10228	39662918.5	3554500	27.233
												100	118.727357	32.094813	39663066.1	3553674	25.654	350	118.72568	32.102401	39662894.3	3554513	26.753

101	118.727103	32.094907	39663042	3553684	26.833	351	118.725428	32.102531	39662870.3	3554527	26.298
												102	118.726852	32.095001	39663018.1	3553694	27.842	352	118.725175	32.102669	39662846.2	3554542	25.84
103	118.726601	32.095085	39662994.3	3553703	29.624	353	118.724919	32.102799	39662821.8	3554556	25.239
												104	118.726348	32.09517	39662970.2	3553712	31.596	354	118.724659	32.102929	39662797	3554570	24.611
105	118.726093	32.095263	39662946	3553722	32.863	355	118.724394	32.10305	39662771.8	3554583	23.992
												106	118.725836	32.095348	39662921.6	3553731	30.909	356	118.72413	32.10317	39662746.6	3554596	23.251
107	118.725579	32.095442	39662897.1	3553741	28.115	357	118.723865	32.103291	39662721.4	3554609	22.393
												108	118.725322	32.095535	39662872.7	3553751	25.031	358	118.723604	32.103403	39662696.5	3554621	21.461
109	118.725063	32.095638	39662848.1	3553762	22.07	359	118.723343	32.103524	39662671.7	3554634	20.48
												110	118.724802	32.095732	39662823.3	3553772	20.152	360	118.723084	32.103636	39662647	3554646	19.567
111	118.724537	32.095826	39662798.1	3553782	19.592	361	118.722824	32.103756	39662622.3	3554659	18.58
												112	118.724273	32.095919	39662773	3553792	19.753	362	118.722567	32.103877	39662597.8	3554672	17.12
113	118.724009	32.096022	39662747.9	3553803	20.299	363	118.722313	32.104007	39662573.6	3554686	14.753
												114	118.723743	32.096125	39662722.6	3553814	21.015	364	118.722058	32.104127	39662549.3	3554699	11.334
115	118.723478	32.096237	39662697.4	3553826	21.846	365	118.721805	32.104248	39662525.2	3554712	6.746
												116	118.723215	32.096358	39662672.3	3553839	22.723	366	118.721556	32.104378	39662501.5	3554726	2.184
117	118.722952	32.096478	39662647.3	3553852	23.626	367	118.721309	32.104507	39662477.9	3554740	-1.95
												118	118.722684	32.09659	39662621.8	3553864	24.612	368	118.721063	32.104628	39662454.5	3554753	-5.352
119	118.722417	32.096711	39662596.3	3553877	25.781	369	118.732659	32.100493	39663556.6	3554312	-7.495
												120	118.722147	32.096841	39662570.6	3553891	26.982	370	118.732433	32.100587	39663535.1	3554322	-5.162
121	118.721877	32.096962	39662544.9	3553904	27.971	371	118.732211	32.100689	39663513.9	3554333	-1.012
												122	118.721606	32.097092	39662519.1	3553918	28.343	372	118.731989	32.100791	39663492.8	3554344	3.781
123	118.721332	32.097222	39662493	3553932	28.46	373	118.731769	32.100893	39663471.8	3554355	9.105
												124	118.721056	32.097352	39662466.7	3553946	28.522	374	118.731549	32.100995	39663450.9	3554366	14.455
125	118.720779	32.097491	39662440.3	3553961	28.551	375	118.73133	32.101107	39663430	3554378	19.767
												126	118.720502	32.097621	39662413.9	3553975	28.251	376	118.731109	32.101218	39663409	3554390	25.025
127	118.72022	32.09776	39662387.1	3553990	27.774	377	118.73089	32.101329	39663388.1	3554402	30.092
												128	118.719939	32.097899	39662360.3	3554005	27.041	378	118.730672	32.10144	39663367.3	3554414	34.28
129	118.719652	32.098029	39662333	3554019	25.944	379	118.730453	32.101551	39663346.4	3554426	36.557
												130	118.719365	32.098168	39662305.6	3554034	24.682	380	118.730232	32.101663	39663325.4	3554438	38.037
131	118.719078	32.098307	39662278.3	3554049	23.255	381	118.730009	32.101774	39663304.1	3554450	38.742
												132	118.718794	32.098455	39662251.2	3554065	21.272	382	118.729785	32.101885	39663282.8	3554462	38.538
133	118.71851	32.098612	39662224.1	3554082	17.447	383	118.72956	32.102005	39663261.3	3554475	37.455
												134	118.718227	32.09877	39662197.1	3554099	11.984	384	118.729332	32.102126	39663239.6	3554488	36.205
135	118.717948	32.098936	39662170.5	3554117	5.854	385	118.729101	32.102237	39663217.6	3554500	34.897
												136	118.71767	32.099102	39662143.9	3554135	0.12	386	118.728868	32.102357	39663195.4	3554513	33.574
137	118.717391	32.099277	39662117.3	3554154	-2.993	387	118.728634	32.102469	39663173.1	3554525	32.24
												138	118.717109	32.099452	39662090.4	3554173	-3.891	388	118.728399	32.102589	39663150.7	3554538	30.888
139	118.729738	32.095151	39663290.3	3553715	-8.268	389	118.728159	32.10271	39663127.8	3554551	29.627
												140	118.729479	32.095262	39663265.7	3553727	-6.779	390	118.727917	32.10283	39663104.7	3554564	28.739
141	118.729221	32.095374	39663241.1	3553739	-2.051	391	118.727673	32.102951	39663081.5	3554577	28.477
												142	118.728962	32.095486	39663216.5	3553751	4.449	392	118.727428	32.103071	39663058.1	3554590	28.354
143	118.728704	32.095589	39663191.9	3553762	11.137	393	118.727178	32.103183	39663034.3	3554602	28.124
												144	118.728446	32.095691	39663167.4	3553773	17.055	394	118.726925	32.103304	39663010.2	3554615	27.694

145	118.728192	32.095794	39663143.2	3553784	21.879	395	118.72667	32.103424	39662986	3554628	27.142
												146	118.727937	32.095888	39663119	3553794	25.535	396	118.726415	32.103545	39662961.7	3554641	26.499
147	118.727685	32.09599	39663095	3553805	27.231	397	118.726159	32.103675	39662937.3	3554655	25.729
												148	118.727434	32.096084	39663071.1	3553815	29.302	398	118.725901	32.103805	39662912.7	3554669	24.997
149	118.727184	32.096177	39663047.4	3553825	32.15	399	118.725641	32.103925	39662887.9	3554682	24.315
												150	118.726936	32.096271	39663023.8	3553835	34.764	400	118.725377	32.104055	39662862.8	3554696	23.664
151	118.72669	32.096364	39663000.4	3553845	35.428	401	118.725113	32.104185	39662837.6	3554710	23.026
												152	118.726445	32.096458	39662977.1	3553855	33.304	402	118.724848	32.104306	39662812.4	3554723	22.197
153	118.7262	32.096551	39662953.8	3553865	30.209	403	118.724585	32.104427	39662787.3	3554736	21.267
												154	118.725953	32.096645	39662930.3	3553875	27.13	404	118.724325	32.104547	39662762.6	3554749	20.235
155	118.725706	32.096747	39662906.8	3553886	24.577	405	118.724065	32.104668	39662737.8	3554762	19.225
												156	118.725458	32.09685	39662883.2	3553897	22.817	406	118.723805	32.10478	39662713.1	3554774	18.276
157	118.725207	32.096953	39662859.3	3553908	21.883	407	118.723548	32.1049	39662688.6	3554787	17.23
												158	118.724953	32.097055	39662835.2	3553919	21.433	408	118.72329	32.105021	39662664	3554800	15.534
159	118.724697	32.097158	39662810.8	3553930	21.811	409	118.723034	32.105133	39662639.7	3554812	11.691
												160	118.724441	32.09727	39662786.4	3553942	22.434	410	118.722781	32.105254	39662615.6	3554825	7.006
161	118.724182	32.097372	39662761.8	3553953	23.132	411	118.722531	32.105374	39662591.8	3554838	2.083
												162	118.723922	32.097484	39662737.1	3553965	23.95	412	118.722283	32.105486	39662568.1	3554850	-1.874
163	118.72366	32.097596	39662712.1	3553977	24.786	413	118.722034	32.105606	39662544.4	3554863	-4.893
												164	118.723397	32.097708	39662687.1	3553989	25.574	414	118.721789	32.105718	39662521.1	3554875	-6.565
165	118.723132	32.097819	39662661.9	3554001	26.526	415	118.733236	32.10145	39663609.3	3554419	-8.604
												166	118.722866	32.09794	39662636.6	3554014	27.593	416	118.733035	32.101552	39663590.2	3554430	-4.709
167	118.722602	32.098061	39662611.4	3554027	28.304	417	118.732833	32.101663	39663570.9	3554442	-0.556
												168	118.722336	32.098191	39662586.1	3554041	28.423	418	118.732633	32.101774	39663551.8	3554454	3.964
169	118.722066	32.098312	39662560.4	3554054	28.328	419	118.732429	32.101885	39663532.4	3554466	9.13
												170	118.721798	32.098442	39662534.8	3554068	28.063	420	118.732226	32.101996	39663513	3554478	14.393
171	118.721526	32.098572	39662508.9	3554082	27.701	421	118.73202	32.102116	39663493.4	3554491	19.315
												172	118.721252	32.098701	39662482.8	3554096	27.268	422	118.731816	32.102236	39663473.9	3554504	23.964
173	118.720974	32.098831	39662456.4	3554110	26.748	423	118.731611	32.102365	39663454.3	3554518	28.52
												174	118.720696	32.098952	39662429.9	3554123	26.065	424	118.731401	32.102485	39663434.3	3554531	32.938
175	118.720416	32.099083	39662403.2	3554137	25.122	425	118.731188	32.102605	39663413.9	3554544	36.693
												176	118.720134	32.099213	39662376.4	3554151	23.941	426	118.730971	32.102725	39663393.2	3554557	38.158
177	118.719853	32.099343	39662349.6	3554165	22.556	427	118.73075	32.102846	39663372.2	3554570	38.669
												178	118.719572	32.099482	39662322.8	3554180	20.625	428	118.730526	32.102966	39663350.8	3554583	38.813
179	118.719289	32.099621	39662295.9	3554195	17.099	429	118.730301	32.103086	39663329.3	3554596	38.656
												180	118.719006	32.09976	39662268.9	3554210	12.347	430	118.730073	32.103207	39663307.6	3554609	37.75
181	118.718724	32.099908	39662242	3554226	6.312	431	118.729843	32.103327	39663285.7	3554622	36.591
												182	118.718443	32.100056	39662215.2	3554242	-0.84	432	118.729612	32.103456	39663263.6	3554636	35.304
183	118.718167	32.100213	39662188.9	3554259	-3.518	433	118.729378	32.103577	39663241.3	3554649	33.939
												184	118.717886	32.100379	39662162.1	3554277	-4.246	434	118.729142	32.103706	39663218.8	3554663	32.559
185	118.730283	32.096135	39663340	3553825	-7.131	435	118.728901	32.103827	39663195.9	3554676	31.2
												186	118.73002	32.096247	39663315	3553837	-5.405	436	118.728659	32.103947	39663172.8	3554689	29.966
187	118.729758	32.09635	39663290.1	3553848	-0.037	437	118.728418	32.104077	39663149.8	3554703	29.131
												188	118.729499	32.096461	39663265.4	3553860	6.868	438	118.728172	32.104206	39663126.4	3554717	28.611

189	118.729241	32.096564	39663240.9	3553871	13.815	439	118.727925	32.104327	39663102.8	3554730	28.098
												190	118.728986	32.096676	39663216.6	3553883	19.188	440	118.727672	32.104448	39663078.7	3554743	27.553
191	118.728734	32.096778	39663192.6	3553894	22.274	441	118.72742	32.104577	39663054.7	3554757	26.912
												192	118.728484	32.09689	39663168.8	3553906	24.76	442	118.727167	32.104707	39663030.6	3554771	26.042
193	118.728238	32.097001	39663145.4	3553918	27.335	443	118.726915	32.104846	39663006.6	3554786	25.119
												194	118.727993	32.097104	39663122.1	3553929	30.34	444	118.726659	32.104975	39662982.2	3554800	24.218
195	118.727749	32.097206	39663098.9	3553940	33.598	445	118.726401	32.105105	39662957.6	3554814	23.493
												196	118.727507	32.097309	39663075.8	3553951	36.305	446	118.726141	32.105244	39662932.8	3554829	22.87
197	118.727267	32.097411	39663053	3553962	36.341	447	118.725879	32.105374	39662907.8	3554843	22.244
												198	118.727028	32.097514	39663030.3	3553973	34.384	448	118.725616	32.105503	39662882.8	3554857	21.47
199	118.726793	32.097616	39663007.9	3553984	31.801	449	118.725355	32.105633	39662857.9	3554871	20.38
												200	118.726555	32.097719	39662985.2	3553995	29.169	450	118.725095	32.105763	39662833.1	3554885	19.215
201	118.726314	32.097821	39662962.3	3554006	26.81	451	118.724836	32.105893	39662808.4	3554899	18.048
												202	118.72607	32.097924	39662939.1	3554017	25.236	452	118.724577	32.106014	39662783.8	3554912	16.916
203	118.725825	32.098026	39662915.8	3554028	24.082	453	118.724318	32.106143	39662759.1	3554926	15.52
												204	118.725579	32.098138	39662892.3	3554040	23.287	454	118.72406	32.106255	39662734.5	3554938	13.631
205	118.725332	32.098249	39662868.8	3554052	23.445	455	118.723802	32.106376	39662710	3554951	10.591
												206	118.72508	32.098352	39662844.9	3554063	23.929	456	118.723548	32.106487	39662685.8	3554963	6.266
207	118.724829	32.098463	39662821	3554075	24.505	457	118.723296	32.106608	39662661.8	3554976	1.73
												208	118.724576	32.098584	39662796.9	3554088	25.142	458	118.723046	32.10672	39662638	3554988	-2.852
209	118.724321	32.098696	39662772.6	3554100	25.788	459	118.722797	32.106831	39662614.3	3555000	-6.182
												210	118.724065	32.098807	39662748.2	3554112	26.398	460	118.722547	32.106943	39662590.5	3555012	-7.885
211	118.723806	32.098928	39662723.6	3554125	27.05	461	118.73413	32.102502	39663691.9	3554537	-8.525
												212	118.723547	32.099049	39662698.9	3554138	27.68	462	118.733932	32.102613	39663673	3554549	-4.999
213	118.72329	32.099179	39662674.4	3554152	28.018	463	118.733732	32.102733	39663653.9	3554562	-0.456
												214	118.723031	32.099308	39662649.7	3554166	27.87	464	118.733532	32.102862	39663634.8	3554576	4.276
215	118.722769	32.099429	39662624.8	3554179	27.572	465	118.733329	32.102982	39663615.4	3554589	9.174
												216	118.722505	32.099559	39662599.6	3554193	27.204	466	118.733126	32.103111	39663596	3554603	14.154
217	118.722237	32.099689	39662574.1	3554207	26.742	467	118.73292	32.10324	39663576.3	3554617	19.005
												218	118.721967	32.099819	39662548.4	3554221	26.244	468	118.732709	32.10336	39663556.2	3554630	23.087
219	118.7217	32.099949	39662522.9	3554235	25.694	469	118.732495	32.103489	39663535.8	3554644	26.986
												220	118.721429	32.100079	39662497.1	3554249	24.994	470	118.732281	32.103609	39663515.3	3554657	31.336
221	118.72116	32.100208	39662471.5	3554263	24.143	471	118.732065	32.103738	39663494.7	3554671	35.236
												222	118.720888	32.100329	39662445.6	3554276	23.205	472	118.731846	32.103868	39663473.8	3554685	37.128
223	118.720615	32.100459	39662419.6	3554290	21.975	473	118.731623	32.103997	39663452.5	3554699	37.759
												224	118.720342	32.100598	39662393.6	3554305	19.773	474	118.731396	32.104126	39663430.9	3554713	38.031
225	118.720067	32.100728	39662367.4	3554319	17.378	475	118.73117	32.104256	39663409.3	3554727	38.118
												226	118.71979	32.100867	39662341	3554334	13.629	476	118.730939	32.104385	39663387.3	3554741	37.961
227	118.719516	32.101006	39662314.9	3554349	5.477	477	118.730707	32.104514	39663365.1	3554755	37.423
												228	118.719239	32.101145	39662288.5	3554364	-1.31	478	118.730472	32.104644	39663342.7	3554769	36.42
229	118.718965	32.101293	39662262.3	3554380	-3.827	479	118.730235	32.104773	39663320.1	3554783	35.139
												230	118.718691	32.10145	39662236.2	3554397	-4.649	480	118.729996	32.104903	39663297.3	3554797	33.788
231	118.73084	32.097164	39663390.8	3553940	-6.605	481	118.729756	32.105041	39663274.4	3554812	32.413
												232	118.73058	32.097267	39663366	3553951	-3.988	482	118.72951	32.105171	39663251	3554826	31.004

33	118.730322	32.097379	39663341.5	3553963	0.906	483	118.729263	32.1053	39663227.4	3554840	29.731
												34	118.730066	32.09749	39663317.1	3553975	6.887	484	118.729013	32.105439	39663203.6	3554855	28.742
35	118.729812	32.097593	39663293	3553986	13.258	485	118.728763	32.105569	39663179.7	3554869	27.905
												36	118.729561	32.097705	39663269.1	3553998	17.549	486	118.728508	32.105707	39663155.4	3554884	27.226
37	118.729314	32.097807	39663245.6	3554009	20.89	487	118.728252	32.105837	39663131	3554898	26.426
												38	118.729073	32.097928	39663222.6	3554022	24.054	488	118.727995	32.105967	39663106.5	3554912	25.496
39	118.728834	32.098039	39663199.8	3554034	27.368	489	118.727737	32.106106	39663081.9	3554927	24.569
												40	118.728595	32.098151	39663177.1	3554046	30.872	490	118.727478	32.106235	39663057.2	3554941	23.663
41	118.72836	32.098262	39663154.7	3554058	34.801	491	118.727218	32.106374	39663032.4	3554956	22.784
												42	118.728125	32.098364	39663132.3	3554069	38.024	492	118.726956	32.106513	39663007.5	3554971	21.953
43	118.72789	32.098467	39663109.9	3554080	38.333	493	118.726695	32.106652	39662982.6	3554986	21.259
												44	118.72766	32.098578	39663088	3554092	36.405	494	118.726435	32.106782	39662957.8	3555000	20.383
45	118.727427	32.09868	39663065.9	3554103	33.84	495	118.726175	32.10692	39662933	3555015	19.234
												46	118.727196	32.098792	39663043.8	3554115	30.972	496	118.725916	32.107059	39662908.3	3555030	18.009
47	118.72696	32.098903	39663021.4	3554127	28.69	497	118.725655	32.107198	39662883.4	3555045	16.759
												48	118.726723	32.099006	39662998.8	3554138	27.33	498	118.725393	32.107328	39662858.5	3555059	15.394
49	118.726483	32.099117	39662976	3554150	26.295	499	118.725132	32.107458	39662833.6	3555073	13.921
												50	118.726241	32.09922	39662952.9	3554161	25.51	500	118.724872	32.107587	39662808.8	3555087	12.059

The longitude and latitude of pollutant accident origination point is 118.853983,32.229551;

Pollutant gross mass is 60 tons, and instantaneous discharge, pollutant proportion are 1.0, pollutant rate of dissolution is 0.08Kg/ (5min.Kg), pollutant saturation solubility is 35.0%, pollutant volatility is 0.002Kg/ (5min.Kg), rate of contaminant degradation is 0.001Kg/ (5min.Kg).

By above-mentioned data input Delft3D model (non-constant Model of Water Environment), utilize DELFT3D stress and strain model instrument to carry out quadrangular mesh partition to region, Eight Diagrams continent, Nanjing, obtain grid distribution plan as shown in Figure 1; Arrange Delft3D modeling initial time on January 4th, 2007, dummy spacers 86 days, output frequency is every day, runs and obtains pollutant levels field data; Data conversion is carried out to concentration field destination file and generates following four configuration files:

1, supporting paper gridinfo.ini

“2007-01-04,14425,13992,86”。

13992 quadrilateral meshs are divided into, 14425 nodes, as shown in Figure 1 by study area.Simulation from date is on January 4th, 2007, and simulating number of days in this example is 86 days.

2, gridding information file gridinfo.txt

0,117.180000,3040.649902,15.000000,15.000000,45609.750000,8546150.000000,8513213.000000,12.000000,0.000000

0,117.180000,3040.649902,15.000000,15.000000,45609.750000,8542502.000000,8508330.000000,12.000000,0.000000

0,117.180000,3040.649902,15.000000,15.000000,45609.750000,8569477.000000,8559622.000000,12.000000,0.000000

1,117.750000,3055.850098,15.000000,15.000000,45837.750000,8587538.000000,8452836.000000,12.000000,0.000000

1,117.750000,3055.850098,15.000000,15.000000,45837.750000,8583873.000000,8447987.000000,12.000000,0.000000

1,117.750000,3055.850098,15.000000,15.000000,45837.750000,8588975.000000,8455044.000000,12.000000,0.000000

13991,175.350006,9146.049805,15.000000,15.000000,137190.750000,12782663.000000,16650419.000000,10.001300,0.000000

Have recorded 13992 grids 86 days time dependent grid numberings, grid maximum length, grid area, mean depth, depth capacity, grid initial water capacity, grids successively and enter the water yield, grid aquifer yield, water temperature, pollutant levels.

3, network file grid.txt

118.728212,32.092232,118.728674,32.093209,118.728403,32.093284,118.727957,32.092299,3040.649902

118.727957,32.092299,118.728403,32.093284,118.728134,32.093360,118.727699,32.092365,3055.850098

118.725588,32.092953,118.726051,32.094011,118.725787,32.094087,118.725315,32.093029,3341.100098

Have recorded 13992 grids four successively and be out of shape four apex coordinates and area.

4, grid composing document gridnet.txt

0,46,47,1

1,47,48,2

…

14374,14423,14424,14375

Have recorded the node numbering on 13992 grid quadrilaterals, four summits successively.

Two, acute ecological risk assessment

Pollutant to be measured is nitrobenzene.To be measured aquatic be Daphnia magna (Daphnia).Expose moment t=48 constantly little, the LC50 of Daphnia is 40667ug/L.

Input exposes the pollutant levels Concentration (t) of each grid in moment t place and exposes moment t place pollutant to the MLC (median lethal concertration) LC50 (t) of aquatic animal to be detected, obtains the value-at-risk Risk (t) of described aquatic animal to pollutant; Risk (t)=Concentration (t)/LC50 (t).

Employing OpenGl combine with technique clustering algorithm, color fractal algorithm carry out image rendering to all grids, export pollutant to be detected in surface water water environment and, to the ecological risk figure (acute risk map) of biology to be detected, see Fig. 2.

Fig. 2 is Daphnia magna (Daphnia) 48 hours acute risk assessment figure.Risk threshold value is calculated by automatic cluster algorithm, and in this example, RED sector is excessive risk distributed areas, and blue portion is low-risk distributed areas, and between redness to blueness, intermediate color region is the distributed areas of moderate risk.

Three, long-term ecological risk assessment

Gather the water sample in region, Eight Diagrams continent, Nanjing, detect water sample, obtain water quality parameter (comprising nutrient concentration, chip concentration) and hydrobiont parameter (water plant biomass, aquatic animal biomass).Nutrient concentration refers to ammonia nitrogen concentration, nitrate concentration, phosphate concn, gas concentration lwevel and dissolved oxygen concentration, and unit is mg/l.Chip concentration refers to the concentration of solubility chip and the concentration of non-solubility chip, and unit is g/m ².Water plant biomass refers to the biomass of diatom, green alga, blue-green algae, other algae and aquatic macrophyte, and unit is g/m ².Aquatic animal biomass refers to the biomass of animal plankton, benthic invertebrate, water-bed worm and fish, and unit is g/m ².

Concrete data are as follows:

Ammonia nitrogen concentration is 0.015mg/l, nitrate concentration is 4.3mg/l, phosphate concn is 0.2mg/l, gas concentration lwevel is 0.5mg/l, dissolved oxygen concentration is 12mg/l;

Solubility chip concentration is 0.3g/m ², non-solubility chip concentration is 1g/m ²;

Hydrophyte adopts green alga, biomass 0.05mg/l;

Aquatic animal adopts Daphnia magna, biomass 0.03mg/l.

Adopt the open source code AQUATOX model of EPA's issue as Ecology toxicity basic model.

In Ecology toxicity model, input water quality parameter and the hydrobiont parameter in region, Eight Diagrams continent, Nanjing, select pollutant to be measured (this example is nitrobenzene).

Read gridding information file gridinfo.txt, extract the unstructured grids geometry distribution of surface water water environment, space lattice aggregation technique is adopted to be coupled with Ecology toxicity model, each grid after grid gathering is as an input block of Ecology toxicity model, and all space lattice information is by GIS platform MAPWINGIS assembly management and maintenance;

Read gridding information file gridinfo.txt, extract dynamic parameter, adopt time step coupling technique to be coupled with Ecology toxicity model; Described dynamic parameter comprises grid maximum length, grid area, mean depth, depth capacity, grid enter the water yield (dynamic change), grid aquifer yield (dynamic change), grid water temperature, grid pollutant levels;

Ecology toxicity model processes one by one to each input block, obtain the concentration change of biology to be measured in each grid, biotic population and biomass variety, employing OpenGL combine with technique clustering algorithm, color fractal algorithm carry out graph rendering to each grid, and in output surface water water environment, pollutant to be detected is to the ecological risk figure (whole survey region risk field Dynamic Evolution) of biology to be detected.

Fig. 3 to Figure 16 be Daphnia ppb parameter characterization 0,24 ..., 312 hours risk maps.Ppb represents 10 ^-9, indicating ug/l (micrograms per litre) when expressing concentration, is originally that in strength, ppb represents ug/kg, namely contains the pollutant of how many micrograms in every kilogram of Daphnia biomass.

In Fig. 3 to Fig. 8, Daphnia ppb parameter variation tendency and concentration field variation tendency are consistent, after illustrating that contamination accident occurs, As time goes on, the content of nitrobenzene contamination thing in Daphnia body increases gradually, and pollutant is strengthened gradually to biosome influence; From Fig. 8 to Figure 12, concentration field weakens gradually, and Daphnia ppb parameter variation tendency weakens thereupon; But the variation tendency of the latter is significantly less than the variation tendency of the former concentration field, confirm that pollutant accumulation is in vivo a process slowly; Figure 12 to Figure 16, concentration field disappears substantially, and Daphnia ppb parameter variation tendency still exists, and the trend that maintenance slowly slows down, namely, under contaminant density field does not exist situation, pollutant affects sustainable existence to biosome, confirms that pollutant affects the long-term accumulated of biosome.

Claims (1)

1. predict that in surface water water environment, pollutant to be measured, to the method for the ecological risk of biology to be detected, comprises the steps:

(1) the following data group 1 of pollutant accident origination point is measured: current level, flow, roughness value and air speed value;

Obtain following data group 2: the landform of pollutant accident origination point, the longitude and latitude of pollutant accident origination point, pollutant to be measured, pollutant gross mass to be measured, pollutant proportion to be measured, pollutant rate of dissolution to be measured, pollutant saturation solubility to be measured, pollutant volatility to be measured and rate of contaminant degradation to be measured;

Every data of data group 1 and data group 2 are inputted non-constant Model of Water Environment, generates the concentration field data of pollutant to be detected in surface water water environment, as primary parameter; Described concentration field data are made up of supporting paper gridinfo.ini, gridding information file gridinfo.txt, network file grid.txt and grid composing document gridnet.txt;

The parameter of described supporting paper gridinfo.ini is as follows: the time of meshes number and dry run in node number, concentration field in the initial time of whole simulation, concentration field;

The parameter of described gridding information file gridinfo.txt is as follows: grid numbering, grid maximum length, grid area, mean depth, depth capacity, grid initial water capacity, grid enter the water yield, grid aquifer yield, grid water temperature and grid pollutant levels;

The parameter of described network file grid.txt is as follows: the X-coordinate on grid four summit, the Y-coordinate on grid four summit and grid area;

The parameter of described grid composing document gridnet.txt is as follows: the node numbering of quadrilateral four node;

(2) predict that in surface water water environment, pollutant to be measured is to the ecological risk of biology to be measured according to the method for following (a) or (b);

A () input exposes the pollutant levels Concentration (t) of each grid in moment t place and exposes moment t place pollutant to the MLC (median lethal concertration) LC50 (t) of aquatic animal to be detected, obtain the value-at-risk Risk (t) of described aquatic animal to pollutant; Risk (t)=Concentration (t)/LC50 (t);

Input exposes the pollutant levels Concentration (t) of each grid in moment t place and exposes moment t place pollutant to medium effective concentration EC50 (t) of hydrophyte to be detected, obtains the value-at-risk Risk (t) of described hydrophyte to pollutant; Risk (t)=Concentration (t)/EC50 (t);

Employing OpenGl combine with technique clustering algorithm, color fractal algorithm carry out image rendering to all grids, and in output surface water water environment, pollutant to be measured is to the ecological risk figure of biology to be measured;

B () gathers the water sample of described surface water water environment, detect water sample and obtain water quality parameter; Described water quality parameter comprises nutrient concentration, chip concentration, water plant biomass and aquatic animal biomass; Described nutrient concentration refers to ammonia nitrogen concentration, nitrate concentration, phosphate concn, gas concentration lwevel and dissolved oxygen concentration; Described chip concentration refers to the concentration value of solubility and non-solubility chip;

By above-mentioned data input Ecology toxicity model, select pollutant to be measured, then the primary parameter obtained with step (1), for input parameter, to apply in described Ecology toxicity model prediction surface water water environment pollutant to be detected to the ecological risk of biology to be detected;

Read gridding information file gridinfo.txt, extract the unstructured grids geometry distribution of surface water water environment, space lattice aggregation technique is adopted to be coupled with Ecology toxicity model, each grid after grid gathering is as an input block of Ecology toxicity model, and all space lattice information is by GIS platform MAPWINGIS assembly management and maintenance;

Read gridding information file gridinfo.txt, extract dynamic parameter, adopt time step coupling technique to be coupled with Ecology toxicity model; Described dynamic parameter comprises grid maximum length, grid area, mean depth, depth capacity, grid enter the water yield, grid aquifer yield, grid water temperature, grid pollutant levels;

Described Ecology toxicity model processes one by one to each input block, obtain the concentration change of biology to be measured in each grid, biotic population and biomass variety, employing OpenGL combine with technique clustering algorithm, color fractal algorithm carry out graph rendering to each grid, and in output surface water water environment, pollutant to be detected is to the ecological risk figure of biology to be detected;

Described non-constant Model of Water Environment is Delft3D, MIKE21 or EFDC;

Described Ecology toxicity model is AQUATOX model.