CN115330261A - Ecological comprehensive treatment method for black and odorous river channel based on Internet of things technology - Google Patents
Ecological comprehensive treatment method for black and odorous river channel based on Internet of things technology Download PDFInfo
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Abstract
The invention discloses an ecological comprehensive treatment method for a black and odorous river channel based on the Internet of things technology, wherein sewage quality parameters corresponding to each sewage drain in each black and odorous river channel subregion and pollution parameters of each depth sludge sample at each monitoring point are monitored, water pollution proportion indexes at each sewage drain in each black and odorous river channel subregion and pollution degree proportion indexes of each depth sludge sample at each monitoring point are analyzed, and corresponding treatment is carried out after comparison and analysis, so that the sewage drain of the black and odorous river channel can be transformed pertinently and reasonably, the pollution degree of underwater sludge of the river channel can be accurately mastered, the implementation precision of dredging engineering is improved, the problem of secondary pollution of a river channel water body is avoided, meanwhile, the river water environment corresponding to each black and odorous river channel subregion is monitored, the river water environment pollution degree coefficients corresponding to each black and odorous river channel subregion are analyzed, corresponding treatment measures are carried out, and the ecological comprehensive treatment effect of the black and odorous river channel is further embodied.
Description
Technical Field
The invention relates to the technical field of river channel ecological management, in particular to an ecological comprehensive management method for a black and odorous river channel based on the Internet of things technology.
Background
Along with the increasing of population density along two banks of a river, the economic and people living standard is continuously improved, and more sewage containing high pollution load is discharged into the river channel. At the moment, the river channel is used as a sewage receiving channel, the water environment capacity space is relatively small, the self-purification capacity of the river channel water body is exceeded, the sensory effect of a black and odorous state is presented, and the normal living space of surrounding residents is influenced. Therefore, the ecological management of the black and odorous river is very important.
The existing ecological treatment method of the black and odorous river channel is mainly a conventional physical and chemical treatment method, namely the conventional physical and chemical method usually adopts sewage interception, desilting, water diversion, aeration and the like, but the existing ecological treatment method of the black and odorous river channel still has the following defects:
1. the existing ecological treatment modes of the black and odorous river channels are mostly used for completely blocking all sewage outlets of the black and odorous river channels, and the mode has certain irrationality and does not carry out current situation investigation and analysis on the sewage outlets of the black and odorous river channels, so that the sewage outlets of the black and odorous river channels cannot be improved in a targeted manner, and the sewage outlets of the black and odorous river channels cannot be accurately and effectively intercepted;
2. at present, for treatment of black and odorous watercourses, dredging engineering is mainly embodied in an ex-situ treatment technology, namely, watercourse sludge is excavated and transported to other places and then treated, but the pollution degree of the watercourse underwater sludge cannot be accurately mastered in the prior art, so that the later-stage watercourse underwater sludge is not cleaned in place, the implementation precision of the dredging engineering is reduced, and further the watercourse sludge releases pollutants into a water body to cause secondary pollution of the watercourse water body;
3. the existing black and odorous river sewage treatment method mainly comprises a physical method and a chemical method, but generally has the problems of temporary solution and permanent solution, has higher treatment cost, cannot ensure that the water quality of the river can maintain a normal state for a long time, causes the water quality of the river to repeatedly generate black and odorous phenomena, and further cannot embody the effect of ecological comprehensive treatment of the black and odorous river.
Disclosure of Invention
In view of this, in order to solve the problems in the background art, an ecological comprehensive treatment method for black and odorous river channels based on the internet of things technology is provided.
The purpose of the invention can be realized by the following technical scheme:
the ecological comprehensive treatment method for the black and odorous river channel based on the Internet of things technology comprises the following steps:
step one, monitoring sewage quality parameters of a sewage discharge outlet: dividing the black and odorous river channel area to be treated into black and odorous river channel sub-areas according to a preset dividing mode, and monitoring sewage quality parameters corresponding to each sewage outlet in each black and odorous river channel sub-area;
step two, analyzing and treating the parameters of the sewage quality: analyzing to obtain water pollution ratio indexes of each sewage discharge port in each black and odorous river sub-area, and performing corresponding treatment after comparative analysis;
step three, monitoring deep sludge pollution parameters: collecting sludge samples at each depth of each monitoring point in each black and odorous river sub-area, and monitoring pollution parameters of the sludge samples at each depth of each monitoring point in each black and odorous river sub-area;
step four, analyzing the pollution degree of the deep sludge: analyzing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river sub-area, and comparing to obtain the sludge depth needing to be cleaned corresponding to each black and odorous river sub-area;
step five, monitoring the water environment of the black and odorous riverway: monitoring river water environments corresponding to the black and odorous river sub-areas to obtain river water quality parameters and water floating object information corresponding to the black and odorous river sub-areas;
step six, regional river water environment treatment: analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river sub-area, screening the river water environmental pollution level corresponding to each black and odorous river sub-area, and performing corresponding treatment measures on each black and odorous river sub-area.
Preferably, the specific steps corresponding to the first step are as follows:
dividing the black and odorous river channel area to be treated according to a river channel length equal division mode to obtain each sub-area corresponding to the black and odorous river channel area to be treated, recording the sub-areas as each black and odorous river channel sub-area, and sequentially numbering the sub-areas of the black and odorous river channel as 1,2, 1, i, n;
counting each sewage discharge outlet in each black and odorous river sub-area, and counting each black and odorous river sub-areaSampling sewage at each sewage discharge outlet in each sub-region of the odorous river, monitoring sewage quality parameters corresponding to each sewage discharge outlet in each sub-region of the black and odorous river, wherein the sewage quality parameters comprise sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value, and respectively marking the sewage transparency, the sewage dissolved oxygen content, the sewage ammonia nitrogen content and the sewage pH value corresponding to each sewage discharge outlet in each sub-region of the black and odorous river as p ij a 1 、p ij a 2 、p ij a 3 、p ij a 4 I =1, 2.. N, i represents the number of the ith black and odorous river channel subregion, and j =1, 2.. M, j represents the number of the jth sewage outlet.
Preferably, in the second step, the analysis mode of the water pollution ratio index at each sewage discharge port in each black and odorous river sub-area is as follows:
extracting standard water quality parameters of river water corresponding to the normal river channel stored in a river channel ecological management database, and analyzing water pollution proportion indexes of sewage outlets in each black and odorous river channel subregion according to the sewage quality parameters corresponding to the sewage outlets in each black and odorous river channel subregion
Where e is expressed as a natural constant, δ 1 、δ 2 、δ 3 、δ 4 Respectively expressed as water quality influence weight factors, p, corresponding to preset sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value Sign board a 1 、p Sign a 2 、p Sign board a 3 、p Sign a 4 Respectively expressed as the standard transparency, the standard dissolved oxygen content, the standard ammonia nitrogen content, the standard pH value, delta pa of the river water corresponding to the normal river channel 1 、Δpa 2 、Δpa 3 、Δpa 4 Respectively representing the preset allowable deviation value of the river water transparency, the allowable deviation value of the river water dissolved oxygen content, the allowable deviation value of the river water ammonia nitrogen content and the allowable deviation value of the river water pH value;
the water pollution proportion index of each sewage outlet in each black and odorous river sub-area is compared with a preset river water pollution proportion index threshold, if the water pollution proportion index of a certain sewage outlet in a certain black and odorous river sub-area is greater than the preset river water pollution proportion index threshold, the sewage outlet in the black and odorous river sub-area is marked as an appointed sewage outlet, each appointed sewage outlet in each black and odorous river sub-area is counted, and sewage interception treatment is carried out on each appointed sewage outlet in each black and odorous river sub-area.
Preferably, the monitoring of the pollution parameters of the deep sludge samples at the monitoring points in the sub-area of each black and odorous river in the third step specifically includes:
uniformly arranging a plurality of monitoring points in each black and odorous river channel sub-area, collecting sludge at each depth of each monitoring point in each black and odorous river channel sub-area by using an unmanned aerial vehicle to obtain each depth sludge sample at each monitoring point in each black and odorous river channel sub-area, and monitoring pollution parameters of each depth sludge sample at each monitoring point in each black and odorous river channel sub-area, wherein the pollution parameters comprise physical and chemical indexes and element pollution indexes;
extracting the pH value, the water content and the salt concentration of the physicochemical indexes corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area, and analyzing the formula according to the pollution weight coefficient of the physicochemical indexes
Obtaining a physicochemical index pollution weight coefficient psi corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf Wherein gamma is 1 、γ 2 、γ 3 Respectively expressed as sludge pollution influence factors q corresponding to preset PH value, water content and salinity i rf b 1 、q i rf b 2 、q i rf b 3 Respectively expressed as PH value, water content and salt concentration of corresponding physicochemical indexes of an fth depth sludge sample at an ith monitoring point in an ith black and odorous river channel subregion, wherein r =1, 2. Allow for b 1 、q′ Allow for b 2 、q′ Allow for b 3 Respectively expressed as allowable PH value, allowable water content and allowable salt concentration per unit volume, delta q 'corresponding to the set river sludge' Allow for b 3 Expressing the concentration deviation value of the allowed salt corresponding to the preset unit volume of the sludge;
extracting the content of heavy metal elements, the content of total nitrogen elements, the content of total phosphorus elements and the content of total potassium elements in the element pollution indexes corresponding to the depth sludge samples at the monitoring points in the sub-areas of the black and odorous river channels, and analyzing to obtain the element pollution weight coefficient theta corresponding to the depth sludge samples at the monitoring points in the sub-areas of the black and odorous river channels i rf 。
Preferably, the specific steps corresponding to the fourth step include:
the pollution weight coefficient psi of the physicochemical index corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf And the element contamination weight coefficient theta i rf Substituting into a sludge pollution degree proportion index analysis formula
Obtaining the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river sub-area
Wherein λ 1 And λ 2 Respectively expressed as a pollution degree correction factor corresponding to a preset river sludge physicochemical index and a pollution degree correction factor corresponding to a river sludge element.
Preferably, the specific steps corresponding to the fourth step further include:
and comparing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river channel subregion with a preset sludge pollution degree proportion index threshold, if the pollution degree proportion index of a depth sludge sample at a monitoring point in a certain black and odorous river channel subregion is greater than the preset sludge pollution degree proportion index threshold, the depth sludge at the monitoring point in the black and odorous river channel subregion is heavy pollution sludge, screening the maximum depth of the heavy pollution sludge corresponding to each monitoring point in each black and odorous river channel subregion, and counting the maximum depth of the heavy pollution sludge corresponding to each black and odorous river channel subregion in a comparison mode to serve as the depth of the sludge required to be cleaned corresponding to each black and odorous river channel subregion.
Preferably, in the fifth step, the river water quality parameters corresponding to the sub-areas of the black and odorous river channel are obtained in a manner that:
sampling river water corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle, monitoring river water quality parameters corresponding to each black and odorous river channel subregion, wherein the river water quality parameters comprise river water transparency, river water dissolved oxygen content, river water ammonia nitrogen content and river water pH value, obtaining river water pollution proportion indexes corresponding to each black and odorous river channel subregion according to a water pollution proportion index analysis mode of each sewage discharge outlet in each black and odorous river channel subregion, and recording the river water pollution proportion indexes as phi i ；
Carrying out image acquisition on the water surface corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle to obtain a water surface image corresponding to each black and odorous river channel subregion, processing the water surface image corresponding to each black and odorous river channel subregion according to the water surface image corresponding to each black and odorous river channel subregion to obtain the water floater information corresponding to each black and odorous river channel subregion, wherein the water floater information comprises the area and the type of each floater, analyzing the water floater information to obtain the water floater pollution ratio index corresponding to each black and odorous river channel subregion, and recording the water floater pollution ratio index as sigma i 。
Preferably, the analysis mode of the pollution ratio index of the floating objects in water corresponding to each black and odorous river sub-area is as follows:
the method comprises the steps of performing segmentation processing and enhancement processing on water surface images corresponding to black and odorous river channel sub-areas to obtain sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas, comparing the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas with preset set images, counting the similarity between the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas and the set images, screening the set images with the highest similarity corresponding to all floats in the water surface images corresponding to the black and odorous river channel sub-areas, recording the set images as target set images corresponding to all floats in the black and odorous river channel sub-areas, extracting the types of the target set images corresponding to all floats in the black and odorous river channel sub-areas, and recording the types of all floats in the black and odorous river channel sub-areas;
obtaining the area of each floater in each black and odorous river sub-area according to the subimage of each floater in the water surface image corresponding to each black and odorous river sub-area, counting the accumulated area and the accumulated quantity corresponding to each floater in each black and odorous river sub-area according to the type of each floater in each black and odorous river sub-area, and analyzing the pollution proportion index of the floaters in the water corresponding to each black and odorous river sub-area
Wherein x is ic Expressed as the accumulated number corresponding to the c-th floating species in the ith black and odorous river sub-area, c =1,2 c Expressed as a pre-set contamination weight factor, s, corresponding to the c-th float species ic Expressed as the cumulative area corresponding to the c-th floating object in the ith black and odorous river sub-area, S i Standard of merit The standard area of the water surface image corresponding to the ith black and odorous river channel subregion is expressed, and e is expressed as a natural constant.
Preferably, the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion is analyzed in the sixth step, and the specific analysis mode is as follows:
according to the river water pollution ratio index phi corresponding to each black and odorous river sub-area i And the pollution ratio index sigma of floating materials in water i Analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion
Wherein x i Expressed as the river water environmental pollution degree coefficient, eta, corresponding to the ith black and odorous river channel subregion 1 、η 2 Respectively expressed as a river water quality pollution influence weight factor and a floater pollution influence weight factor.
Compared with the prior art, the ecological comprehensive treatment method for the black and odorous river based on the Internet of things technology has the following beneficial effects:
according to the invention, the water quality parameters of the sewage corresponding to each sewage discharge outlet in each black and odorous river sub-area are monitored, the water pollution proportion index of each sewage discharge outlet in each black and odorous river sub-area is analyzed, and the corresponding treatment is carried out after the comparison and analysis, so that the current situation investigation and analysis of the sewage discharge outlets corresponding to the black and odorous river are realized, the targeted and reasonable transformation of the sewage discharge outlets of the black and odorous river is ensured, and the accurate and effective sewage interception treatment of the sewage discharge outlets in the black and odorous stage is further realized.
According to the method, the pollution parameters of the depth sludge samples at the monitoring points in the black and odorous river channel sub-regions are monitored, the pollution degree proportion indexes of the depth sludge samples at the monitoring points in the black and odorous river channel sub-regions are analyzed, and the depth of the sludge to be cleaned corresponding to the black and odorous river channel sub-regions is obtained through comparison, so that the pollution degree of the underwater sludge of the river channel can be accurately mastered, the phenomenon that the underwater sludge of the river channel is not cleaned in place in the later period is avoided, the implementation precision of dredging engineering is improved, the problem of secondary pollution of the river channel water body is further avoided, and the later period of enabling the ecological environment of the river channel water body to be unaffected.
According to the invention, the river water environment corresponding to each black and odorous river sub-area is monitored, the river water environment pollution degree coefficient corresponding to each black and odorous river sub-area is analyzed, the river water environment pollution level corresponding to each black and odorous river sub-area is screened, and corresponding treatment measures are carried out on each black and odorous river sub-area, so that the change of the original ecology of the black and odorous river is reduced to the maximum extent, the water quality of the river can be maintained in a normal state for a long time, the phenomenon of black and odorous repeated appearing in the water quality of the river is avoided, and the effect of the ecological comprehensive treatment of the black and odorous river is further embodied.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides an ecological comprehensive treatment method for a black and odorous river channel based on the technology of the internet of things, which comprises the following steps:
step one, monitoring sewage quality parameters of a sewage discharge outlet: and dividing the black and odorous river channel area to be treated into various black and odorous river channel sub-areas according to a preset dividing mode, and monitoring sewage quality parameters corresponding to various sewage outlets in the various black and odorous river channel sub-areas.
On the basis of the above embodiment, the specific steps corresponding to the first step are as follows:
dividing the black and odorous river channel area to be treated according to a river channel length equal division mode to obtain each sub-area corresponding to the black and odorous river channel area to be treated, recording the sub-areas as each black and odorous river channel sub-area, and sequentially numbering the sub-areas of the black and odorous river channel as 1,2, 1, i, n;
counting each sewage outlet in each black and odorous river sub-area, sampling sewage at each sewage outlet in each black and odorous river sub-area, monitoring sewage quality parameters corresponding to each sewage outlet in each black and odorous river sub-area through a water quality monitor, wherein the sewage quality parameters comprise sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value, and respectively marking the sewage transparency, the sewage dissolved oxygen content, the sewage ammonia nitrogen content and the sewage pH value corresponding to each sewage outlet in each black and odorous river sub-area as p ij a 1 、p ij a 2 、p ij a 3 、p ij a 4 I =1, 2.. The n, i is indicated as the number of the ith black and odorous river channel subregion, and j =1, 2.. The m, j is indicated as the number of the jth sewage draining outlet.
Step two, analyzing and treating the parameters of the sewage quality: analyzing to obtain water pollution ratio indexes of each sewage discharge port in each black and odorous river sub-area, and performing corresponding treatment after comparative analysis.
On the basis of the above embodiment, in the second step, the analysis mode of the water pollution ratio index at each sewage discharge port in each black and odorous river sub-area is as follows:
extracting standard water quality parameters of river water corresponding to normal river channels stored in a river channel ecological management database, and analyzing water pollution proportion indexes of the sewage outlets in the sub-areas of the black and odorous river channels according to the sewage quality parameters corresponding to the sewage outlets in the sub-areas of the black and odorous river channels
Where e is expressed as a natural constant, δ 1 、δ 2 、δ 3 、δ 4 Respectively expressed as water quality influence weight factors, p, corresponding to preset sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value Sign a 1 、p Sign a 2 、p Sign board a 3 、p Sign board a 4 Respectively expressed as the standard transparency, the standard dissolved oxygen content, the standard ammonia nitrogen content, the standard pH value, delta pa of the river water corresponding to the normal river channel 1 、Δpa 2 、Δpa 3 、Δpa 4 Respectively representing the preset allowable deviation value of river water transparency, the allowable deviation value of river water dissolved oxygen content, the allowable deviation value of river water ammonia nitrogen content and the allowable deviation value of river water pH value;
the water pollution proportion index of each sewage outlet in each black and odorous river sub-area is compared with a preset river water pollution proportion index threshold, if the water pollution proportion index of a certain sewage outlet in a certain black and odorous river sub-area is greater than the preset river water pollution proportion index threshold, the sewage outlet in the black and odorous river sub-area is marked as an appointed sewage outlet, each appointed sewage outlet in each black and odorous river sub-area is counted, and sewage interception treatment is carried out on each appointed sewage outlet in each black and odorous river sub-area.
In the embodiment, the sewage quality parameters corresponding to the sewage outlets in the black and odorous river sub-areas are monitored, the water pollution proportion index of the sewage outlets in the black and odorous river sub-areas is analyzed, and the sewage outlets are correspondingly processed after comparative analysis, so that the current situation of the sewage outlets corresponding to the black and odorous river is investigated and analyzed, the sewage outlets of the black and odorous river can be improved in a targeted and reasonable manner, and the sewage outlets in the black and odorous stage can be accurately and effectively intercepted.
Step three, monitoring deep sludge pollution parameters: and collecting sludge samples at each depth of each monitoring point in each black and odorous river sub-area, and monitoring pollution parameters of the sludge samples at each depth of each monitoring point in each black and odorous river sub-area.
On the basis of the above embodiment, the monitoring of the pollution parameters of each deep sludge sample at each monitoring point in each black and odorous river sub-area in the third step specifically includes:
uniformly arranging a plurality of monitoring points in each black and odorous river sub-area, collecting sludge at each depth of each monitoring point in each black and odorous river sub-area by an unmanned aerial vehicle to obtain each depth sludge sample at each monitoring point in each black and odorous river sub-area, and monitoring pollution parameters of each depth sludge sample at each monitoring point in each black and odorous river sub-area by intelligent equipment respectively, wherein the pollution parameters comprise physical and chemical indexes and element pollution indexes;
extracting the pH value, the water content and the salinity concentration of the corresponding physicochemical indexes of the sludge samples at the depth of each monitoring point in each black and odorous river sub-area, and analyzing the formula according to the pollution weight coefficient of the physicochemical indexes
Obtaining a physicochemical index pollution weight coefficient psi corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf Wherein gamma is 1 、γ 2 、γ 3 Respectively expressed as sludge pollution influence factors q corresponding to preset PH value, water content and salinity i rf b 1 、q i rf b 2 、q i rf b 3 Individual watchShown as the PH value, the water content and the salt concentration of the corresponding physicochemical indexes of the fj deep sludge sample at the ith monitoring point in the ith black-odor river sub-area, wherein r =1, 2. Allow for b 1 、q′ Allow for b 2 、q′ Allow for b 3 Respectively expressed as allowable PH value, allowable water content and allowable salt concentration per unit volume, delta q 'corresponding to the set river sludge' Allow for b 3 Expressing the concentration deviation value of the allowed salt corresponding to the preset unit volume of the sludge;
extracting the content of heavy metal elements, the content of total nitrogen elements, the content of total phosphorus elements and the content of total potassium elements in the element pollution indexes corresponding to the depth sludge samples at the monitoring points in the sub-areas of the black and odorous river channels, and analyzing to obtain the element pollution weight coefficient theta corresponding to the depth sludge samples at the monitoring points in the sub-areas of the black and odorous river channels i rf 。
It should be noted that the intelligent equipment includes PH meter, soil moisture content apparatus, soil salinity detector and soil element analysis apparatus.
Further, element pollution weight coefficients corresponding to deep sludge samples at monitoring points in sub-areas of the black and odorous watercourses
Wherein gamma is 4 、γ 5 、γ 6 、γ 7 Respectively expressed as sludge pollution influence factors corresponding to the preset contents of heavy metal elements, total nitrogen elements, total phosphorus elements and total potassium elements, q i rf b 4 、q i rf b 5 、q i rf b 6 、q i rf b 7 Respectively expressed as the content of heavy metal elements, the content of total nitrogen elements, the content of total phosphorus elements, the content of total potassium elements and V in the corresponding element pollution indexes of the fth deep sludge sample at the mth monitoring point in the ith black and odorous river sub-area i rf Expressed as the volume of the f-th deep sludge sample at the r-th monitoring point in the ith black and odorous river channel subregion, epsilon Allow for b 4 、ε Allow for b 5 、ε Allow for b 6 、ε Allow for b 7 Respectively representing the content threshold of allowable heavy metal elements, the content threshold of allowable total nitrogen elements, the content threshold of allowable total phosphorus elements and the content threshold of allowable total potassium elements corresponding to the set unit volume of sludge.
Step four, analyzing the pollution degree of the deep sludge: and analyzing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river channel subregion, and comparing to obtain the sludge depth required to be cleaned corresponding to each black and odorous river channel subregion.
On the basis of the above embodiment, the specific steps corresponding to the fourth step include:
the physicochemical index pollution weight coefficient psi corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf And the elemental pollution weight coefficient θ i rf Substituting into a sludge pollution degree proportional index analysis formula
Obtaining the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river sub-area
Wherein λ 1 And λ 2 Respectively expressed as a pollution degree correction factor corresponding to a preset river sludge physicochemical index and a pollution degree correction factor corresponding to a river sludge element.
On the basis of the above embodiment, the specific steps corresponding to the fourth step further include:
and comparing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river channel subregion with a preset sludge pollution degree proportion index threshold, if the pollution degree proportion index of a depth sludge sample at a monitoring point in a certain black and odorous river channel subregion is greater than the preset sludge pollution degree proportion index threshold, the depth sludge at the monitoring point in the black and odorous river channel subregion is heavy pollution sludge, screening the maximum depth of the heavy pollution sludge corresponding to each monitoring point in each black and odorous river channel subregion, and counting the maximum depth of the heavy pollution sludge corresponding to each black and odorous river channel subregion in a comparison mode to serve as the depth of the sludge required to be cleaned corresponding to each black and odorous river channel subregion.
In this embodiment, the pollution parameters of the depth sludge samples at the monitoring points in the black and odorous river sub-regions are monitored, the pollution degree proportion indexes of the depth sludge samples at the monitoring points in the black and odorous river sub-regions are analyzed, and the depth of sludge to be cleaned corresponding to the black and odorous river sub-regions is obtained through comparison, so that the pollution degree of the underwater sludge in the river can be accurately mastered, the phenomenon that the underwater sludge in the river is not cleaned in place in the later period is avoided, the implementation precision of a dredging project is improved, the problem of secondary pollution of the river water is further avoided, and the ecological environment of the river water in the later period is ensured not to be influenced.
Step five, monitoring the water environment of the black and odorous riverway: and monitoring the river water environment corresponding to each black and odorous river channel subregion to obtain river water quality parameters and water floating object information corresponding to each black and odorous river channel subregion.
On the basis of the above embodiment, the river water quality parameters corresponding to the black and odorous river sub-areas in the fifth step are obtained in the following manners:
sampling river water corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle, monitoring river water quality parameters corresponding to each black and odorous river channel subregion, wherein the river water quality parameters comprise river water transparency, river water dissolved oxygen content, river water ammonia nitrogen content and river water pH value, obtaining river water pollution proportion indexes corresponding to each black and odorous river channel subregion according to a water pollution proportion index analysis mode of each sewage discharge outlet in each black and odorous river channel subregion, and recording the river water pollution proportion indexes as phi i ；
Carrying out image acquisition on the water surface corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle to obtain a water surface image corresponding to each black and odorous river channel subregion, and processing the water surface image corresponding to each black and odorous river channel subregion according to the water surface image corresponding to each black and odorous river channel subregion to obtain the water floater information corresponding to each black and odorous river channel subregion, wherein the water floater information comprises the area and the type of each floater, and then analyzing the water floater pollution proportion finger corresponding to each black and odorous river channel subregion to obtain the water floater pollution proportionNumber, it is denoted as σ i 。
Further, the river water pollution ratio index analytical formula corresponding to each black and odorous river sub-area is
Wherein e is a natural constant, p' i a′ 1 、p′ i a′ 2 、p′ i a′ 3 、p′ i a′ 4 Respectively representing the river transparency, the river dissolved oxygen content, the river ammonia nitrogen content and the river acidity-basicity value corresponding to the ith black and odorous river subregion.
Further, the analysis mode of the water floating object pollution ratio index corresponding to each black and odorous river sub-area is as follows:
the method comprises the steps of performing segmentation processing and enhancement processing on water surface images corresponding to black and odorous river channel sub-areas to obtain sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas, comparing the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas with preset set images, counting the similarity between the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas and the set images, screening the set images with the highest similarity corresponding to all floats in the water surface images corresponding to the black and odorous river channel sub-areas, recording the set images as target set images corresponding to all floats in the black and odorous river channel sub-areas, extracting the types of the target set images corresponding to all floats in the black and odorous river channel sub-areas, and recording the types of all floats in the black and odorous river channel sub-areas;
obtaining the area of each floater in each black and odorous river sub-area according to the subimage of each floater in the water surface image corresponding to each black and odorous river sub-area, counting the accumulated area and the accumulated quantity corresponding to each floater in each black and odorous river sub-area according to the type of each floater in each black and odorous river sub-area, and analyzing the pollution proportion index of the floaters in the water corresponding to each black and odorous river sub-area
Wherein x ic Expressed as the accumulated number corresponding to the c-th floating species in the ith black and odorous river sub-area, c =1,2 c Expressed as a pre-set contamination weight factor, s, corresponding to the c-th float species ic Expressed as the cumulative area corresponding to the c-th floating object in the ith black and odorous river sub-area, S i Standard of merit The standard area of the water surface image corresponding to the ith black and odorous river channel subregion is expressed, and e is expressed as a natural constant.
Step six, regional river water environment treatment: analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river sub-area, screening the river water environmental pollution level corresponding to each black and odorous river sub-area, and performing corresponding treatment measures on each black and odorous river sub-area.
On the basis of the above embodiment, the river water environmental pollution degree coefficient corresponding to each black and odorous river sub-area is analyzed in the sixth step, and the specific analysis mode is as follows:
according to the river water pollution ratio index phi corresponding to each black and odorous river sub-area i And the pollution ratio index sigma of floating materials in water i Analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion
Wherein x i Expressed as the river water environmental pollution degree coefficient, eta, corresponding to the ith black and odorous river channel subregion 1 、η 2 Respectively expressed as a river water quality pollution influence weight factor and a floater pollution influence weight factor in the river water.
Further, in the sixth step, corresponding treatment measures are performed on the sub-areas of the black and odorous river channel, and the method specifically comprises the following steps:
extracting the depth of sludge to be cleaned corresponding to each black and odorous river channel subregion, and informing river channel management personnel to perform dredging treatment of the corresponding depth on each black and odorous river channel subregion; and simultaneously comparing the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion with the pollution degree coefficient range corresponding to each set river water environmental pollution grade, if the river water environmental pollution degree coefficient corresponding to a certain black and odorous river channel subregion is in the pollution degree coefficient range corresponding to a certain set river water environmental pollution grade, taking the black and odorous river channel subregion as the set river water environmental pollution grade, counting the set river water environmental pollution grade corresponding to each black and odorous river channel subregion, and informing river channel management personnel to carry out microbial treatment measures corresponding to the river water environmental pollution grade on each black and odorous river channel subregion.
In this embodiment, the river water environment corresponding to each black and odorous river channel subregion is monitored, the river water environment pollution degree coefficient corresponding to each black and odorous river channel subregion is analyzed, the river water environment pollution level corresponding to each black and odorous river channel subregion is screened, and corresponding treatment measures are performed on each black and odorous river channel subregion, so that the change of the original ecology of the black and odorous river channel is reduced to the maximum extent, the water quality of the river channel can be ensured to maintain a normal state for a long time, the phenomenon of black and odorous repeated occurrence of the water quality of the river channel is avoided, and the effect of ecologically comprehensive treatment of the black and odorous river channel is further embodied.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (9)
1. The ecological comprehensive treatment method for the black and odorous river channel based on the Internet of things technology is characterized by comprising the following steps of:
step one, monitoring sewage quality parameters of a sewage discharge outlet: dividing the black and odorous river channel area to be treated into black and odorous river channel sub-areas according to a preset dividing mode, and monitoring sewage quality parameters corresponding to each sewage outlet in each black and odorous river channel sub-area;
step two, analyzing and treating the parameters of the sewage quality: analyzing to obtain water pollution ratio indexes of each sewage discharge port in each black and odorous river sub-area, and performing corresponding treatment after comparative analysis;
step three, monitoring deep sludge pollution parameters: collecting sludge samples at each depth of each monitoring point in each black and odorous river sub-area, and monitoring pollution parameters of the sludge samples at each depth of each monitoring point in each black and odorous river sub-area;
step four, analyzing the pollution degree of the deep sludge: analyzing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river sub-area, and comparing to obtain the depth of sludge to be cleaned corresponding to each black and odorous river sub-area;
step five, monitoring the water environment of the black and odorous riverway: monitoring river water environments corresponding to the sub-areas of the black and odorous river channels to obtain river water quality parameters and floating object information corresponding to the sub-areas of the black and odorous river channels;
step six, regional river water environment treatment: analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river sub-area, screening the river water environmental pollution level corresponding to each black and odorous river sub-area, and performing corresponding treatment measures on each black and odorous river sub-area.
2. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 1, which is characterized in that: the first step corresponds to the following specific steps:
dividing the black and odorous river channel area to be treated in an equal channel length dividing mode to obtain each sub-area corresponding to the black and odorous river channel area to be treated, marking the sub-areas as each black and odorous river channel sub-area, and sequentially numbering the sub-areas of the black and odorous river channel as 1,2, a, i, a, n;
counting each sewage outlet in each black and odorous river sub-area, sampling sewage at each sewage outlet in each black and odorous river sub-area, monitoring sewage quality parameters corresponding to each sewage outlet in each black and odorous river sub-area, wherein the sewage quality parameters comprise sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value, and respectively marking the sewage transparency, the sewage dissolved oxygen content, the sewage ammonia nitrogen content and the sewage pH value corresponding to each sewage outlet in each black and odorous river sub-area as p ij a 1 、p ij a 2 、p ij a 3 、p ij a 4 I =1, 2.,. N, i denotes the number of the ith black-odor river sub-area,j =1, 2.. The m, j indicates the number of the jth drain.
3. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 2, characterized in that: and in the second step, the water pollution proportion index analysis mode at each sewage discharge port in each black and odorous river sub-area is as follows:
extracting standard water quality parameters of river water corresponding to the normal river channel stored in a river channel ecological management database, and analyzing water pollution proportion indexes of sewage outlets in each black and odorous river channel subregion according to the sewage quality parameters corresponding to the sewage outlets in each black and odorous river channel subregion
Where e is expressed as a natural constant, δ 1 、δ 2 、δ 3 、δ 4 Respectively expressed as water quality influence weight factors, p, corresponding to preset sewage transparency, sewage dissolved oxygen content, sewage ammonia nitrogen content and sewage pH value Sign board a 1 、p Sign a 2 、p Sign a 3 、p Sign board a 4 Respectively expressed as the standard transparency, the standard dissolved oxygen content, the standard ammonia nitrogen content, the standard pH value, delta pa of the river water corresponding to the normal river channel 1 、Δpa 2 、Δpa 3 、Δpa 4 Respectively representing the preset allowable deviation value of river water transparency, the allowable deviation value of river water dissolved oxygen content, the allowable deviation value of river water ammonia nitrogen content and the allowable deviation value of river water pH value;
the water pollution proportion index of each sewage outlet in each black and odorous river sub-area is compared with a preset river water pollution proportion index threshold, if the water pollution proportion index of a certain sewage outlet in a certain black and odorous river sub-area is greater than the preset river water pollution proportion index threshold, the sewage outlet in the black and odorous river sub-area is recorded as an appointed sewage outlet, each appointed sewage outlet in each black and odorous river sub-area is counted, and sewage interception treatment is performed on each appointed sewage outlet in each black and odorous river sub-area.
4. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 1, which is characterized in that: in the third step, the pollution parameters of each depth sludge sample at each monitoring point in each black and odorous river sub-area are monitored, and the method specifically comprises the following steps:
uniformly arranging a plurality of monitoring points in each black and odorous river channel sub-area, collecting sludge at each depth of each monitoring point in each black and odorous river channel sub-area by using an unmanned aerial vehicle to obtain each depth sludge sample at each monitoring point in each black and odorous river channel sub-area, and monitoring pollution parameters of each depth sludge sample at each monitoring point in each black and odorous river channel sub-area, wherein the pollution parameters comprise physical and chemical indexes and element pollution indexes;
extracting the pH value, the water content and the salinity concentration of the corresponding physicochemical indexes of the sludge samples at the depth of each monitoring point in each black and odorous river sub-area, and analyzing the formula according to the pollution weight coefficient of the physicochemical indexes
Obtaining a physicochemical index pollution weight coefficient psi corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf Wherein gamma is 1 、γ 2 、γ 3 Respectively expressed as sludge pollution influence factors q corresponding to preset PH value, water content and salinity i rf b 1 、q i rf b 2 、q i rf b 3 Respectively expressed as PH value, water content and salt concentration of corresponding physicochemical indexes of an fth depth sludge sample at an ith monitoring point in an ith black and odorous river channel subregion, wherein r =1, 2. Allow for b 1 、q′ Allow for b 2 、q′ Allow for b 3 Respectively expressed as allowable PH value, allowable water content and allowable salt concentration per unit volume, delta q 'corresponding to the set river sludge' Allow for b 3 Expressing the concentration deviation value of the allowed salt corresponding to the preset unit volume of the sludge;
extracting depth sludge samples corresponding to each monitoring point in each black and odorous river channel sub-regionAnalyzing the heavy metal content, the total nitrogen content, the total phosphorus content and the total potassium content in the element pollution indexes to obtain element pollution weight coefficients theta corresponding to depth sludge samples at monitoring points in each black and odorous river sub-region i rf 。
5. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 4, characterized by comprising the following steps: the fourth step comprises the following specific steps:
the physicochemical index pollution weight coefficient psi corresponding to each depth sludge sample at each monitoring point in each black and odorous river sub-area i rf And the elemental pollution weight coefficient θ i rf Substituting into a sludge pollution degree proportion index analysis formula
Obtaining the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river sub-area
Wherein λ 1 And λ 2 Respectively expressed as a pollution degree correction factor corresponding to a preset river sludge physicochemical index and a pollution degree correction factor corresponding to a river sludge element.
6. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 5, characterized by comprising the following steps: the fourth step further comprises the following specific steps:
and comparing the pollution degree proportion index of each depth sludge sample at each monitoring point in each black and odorous river channel subregion with a preset sludge pollution degree proportion index threshold, if the pollution degree proportion index of a depth sludge sample at a monitoring point in a certain black and odorous river channel subregion is greater than the preset sludge pollution degree proportion index threshold, the depth sludge at the monitoring point in the black and odorous river channel subregion is heavy pollution sludge, screening the maximum depth of the heavy pollution sludge corresponding to each monitoring point in each black and odorous river channel subregion, and counting the maximum depth of the heavy pollution sludge corresponding to each black and odorous river channel subregion in a comparison mode to serve as the depth of the sludge required to be cleaned corresponding to each black and odorous river channel subregion.
7. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 1, characterized by comprising the following steps: in the fifth step, the acquisition mode of the river water quality parameters corresponding to the black and odorous river channel subareas is as follows:
sampling river water corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle, monitoring river water quality parameters corresponding to each black and odorous river channel subregion, wherein the river water quality parameters comprise river water transparency, river water dissolved oxygen content, river water ammonia nitrogen content and river water pH value, obtaining river water pollution proportion indexes corresponding to each black and odorous river channel subregion according to a water pollution proportion index analysis mode of each sewage discharge outlet in each black and odorous river channel subregion, and recording the river water pollution proportion indexes as phi i ；
Carrying out image acquisition on the water surface corresponding to each black and odorous river channel subregion through an unmanned aerial vehicle to obtain a water surface image corresponding to each black and odorous river channel subregion, processing the water surface image corresponding to each black and odorous river channel subregion according to the water surface image corresponding to each black and odorous river channel subregion to obtain the water floater information corresponding to each black and odorous river channel subregion, wherein the water floater information comprises the area and the type of each floater, analyzing the water floater information to obtain the water floater pollution ratio index corresponding to each black and odorous river channel subregion, and recording the water floater pollution ratio index as sigma i 。
8. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 7, characterized in that: the analysis mode of the water floating object pollution proportion index corresponding to each black and odorous river channel subregion is as follows:
the method comprises the steps of performing segmentation processing and enhancement processing on water surface images corresponding to black and odorous river channel sub-areas to obtain sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas, comparing the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas with preset set images, counting the similarity between the sub-images of all floats in the water surface images corresponding to the black and odorous river channel sub-areas and the set images, screening the set images with the highest similarity corresponding to all floats in the water surface images corresponding to the black and odorous river channel sub-areas, recording the set images as target set images corresponding to all floats in the black and odorous river channel sub-areas, extracting the types of the target set images corresponding to all floats in the black and odorous river channel sub-areas, and recording the types of all floats in the black and odorous river channel sub-areas;
obtaining the area of each floater in each black and odorous river sub-area according to the subimage of each floater in the water surface image corresponding to each black and odorous river sub-area, counting the accumulated area and the accumulated quantity corresponding to each floater in each black and odorous river sub-area according to the type of each floater in each black and odorous river sub-area, and analyzing the pollution proportion index of the floaters in the water corresponding to each black and odorous river sub-area
Wherein x is ic Expressed as the accumulated number corresponding to the c-th floating species in the ith black and odorous river sub-area, c =1,2 c Expressed as a preset pollution weight factor, s, corresponding to the c < th > kind of floating objects ic Expressed as the cumulative area corresponding to the c-th floating object in the ith black and odorous river sub-area, S i Standard of merit The standard area of the water surface image corresponding to the ith black and odorous river channel subregion is expressed, and the natural constant is expressed as e.
9. The ecological comprehensive treatment method for the black and odorous river channel based on the technology of the internet of things according to claim 7, characterized in that: analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion in the sixth step, wherein the specific analysis mode is as follows:
according to the river water pollution ratio index phi corresponding to each black and odorous river sub-area i And the pollution ratio index sigma of floating materials in water i Analyzing the river water environmental pollution degree coefficient corresponding to each black and odorous river channel subregion
Wherein x i Expressed as the river water environmental pollution degree coefficient, eta, corresponding to the ith black and odorous river channel subregion 1 、η 2 Respectively expressed as a river water quality pollution influence weight factor and a floater pollution influence weight factor in the river water.
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| Publication number | Priority date | Publication date | Assignee | Title |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104005441A (en) * | 2014-06-11 | 2014-08-27 | 山东省环境保护科学研究设计院 | Polluted bottom sediment environment-friendly dredging system and dredging method thereof |
| CN106836114A (en) * | 2017-01-09 | 2017-06-13 | 中国科学院生态环境研究中心 | Administering method for eliminating rural area type black and odorous water |
| CN107311314A (en) * | 2017-07-06 | 2017-11-03 | 上海淘钿农业生物科技有限公司 | A kind of method of black-odor riverway restoration of the ecosystem in situ |
| US20180002209A1 (en) * | 2016-07-04 | 2018-01-04 | Xiaozhi GU | Ecological Remediation Method for Controlling Sulphur Pollution inBlack and Odorous Sludge of Rivers |
| CN111392869A (en) * | 2020-04-03 | 2020-07-10 | 清控环境(北京)有限公司 | System treatment method for urban black and odorous water body |
| CN112147291A (en) * | 2020-09-23 | 2020-12-29 | 上海城市水资源开发利用国家工程中心有限公司 | Coupling riverway water quality and sediment health monitoring system and method |
| CN112379070A (en) * | 2020-11-09 | 2021-02-19 | 安庆中春自动化技术有限公司 | River course water environment environmental protection administers pollution sources monitoring management system based on big data |
| CN112945298A (en) * | 2021-01-29 | 2021-06-11 | 南京国凰智能科技有限公司 | Online real-time monitoring method and cloud monitoring platform for river course slope protection safety based on Internet of things and image analysis technology |
| CN113109533A (en) * | 2021-04-14 | 2021-07-13 | 武汉军轩天防科技有限公司 | Water quality online intelligent monitoring, analyzing and processing method based on Internet of things and big data analysis |
| CN113239863A (en) * | 2021-05-31 | 2021-08-10 | 中冶京诚工程技术有限公司 | River channel monitoring method and device |
| CN114858207A (en) * | 2022-03-31 | 2022-08-05 | 同济大学 | Soft measurement-based gridding source tracing investigation method for drain outlet of river channel |
-
2022
- 2022-09-17 CN CN202211132466.8A patent/CN115330261B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN113239863A (en) * | 2021-05-31 | 2021-08-10 | 中冶京诚工程技术有限公司 | River channel monitoring method and device |
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