CN104679985A - Method for improving DHSVM (distributed hydrology soil vegetation model) - Google Patents
Method for improving DHSVM (distributed hydrology soil vegetation model) Download PDFInfo
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Abstract
The invention discloses a method for improving a DHSVM (distributed hydrology soil vegetation model). The method is characterized by comprising the following steps of arranging an improving module for calculating influences of a sinkhole on a flow collecting process; recognizing the sinkhole and calculating overland flow concentration by using DEM (dynamic effect model) data which are not subjected to depression detention and an ESRI ArcGIS technology; and leading surface water gathered by the sinkhole into a subterranean river and performing underground river concentration calculation. In the method for improving the DHSVM, a karst region serves as a research object, a hydrologic process of surface and underground double flow collecting systems affected by a karst landform is considered, a rainfall-runoff response process is simulated by improvement on the DVSVM, and the improving effect of the model is analyzed; and a simulating result is displayed, an underground water flow process of the research region is simulated well, and a response relation of factors such as groundwater runoff, rainfall, hydrogeological conditions and underlying surface features is reflected.
Description
Technical field
The present invention relates to improving one's methods of a kind of DHSVM model, particularly relate to a kind of swallow hole and deep layer runoff zones of considering to the DHSVM model of the impact of Process of Confluence.
Background technology
DHSVM (Distributed Hydrology Soil Vegetation Model) be by Washington, DC university develop based on the interactional hydrological distribution model of soil, vegetation and the hydrology.The hydrologic processes such as the evapotranspiration of model watershed, the holard and runoff carry out Dynamic profiling, consider the impact of soil and vegetation watershed hydrologic process, reflect its spatial and temporal variation.
Model physical process mainly comprises evapotranspiration process, unsaturated soil infiltration process, interflow, slope ground surface flow through journey and concentration of channel process.
In DHSVM master mould, surface water and Epi-karst crevice water module can simulate peb processes.But when carrying out Long-Term Simulations to withered phase runoff, effect is poor.Mainly use a large amount of measured discharge data to be processed by statistical method or deviation correction method at present for this problem, and do not consider according to the hydrogeological condition of reality the reason causing this problem.
Comparatively big error is there is in DHSVM master mould when the streamflow change simulation carrying out karst drainage, therefore the present invention is directed to karst drainage earth's surface and lithic drainage structure and comprise the multi-dielectric water stream characteristics of soil, crack and pipeline, DHSVM model is improved, the crack current of consideration Epi-karst and subterranean stream, on the impact producing Process of Confluence, establish the hydrological distribution model being applicable to Karst Regions In Southwest China basin.Consider top layer Karst Fissures and deep karst cranny development degree difference, and the difference on the impact of rain flood characteristics of Runoff, the present invention also adds the hydrologic process of deep layer runoff zones on this basis; Consider the collect effect of the karst landforms such as swallow hole to rainwash, increase swallow hole identification and the effect of lithic drainage is entered to rainwash Process of Confluence.
Summary of the invention
Technical matters to be solved by this invention is, provides a kind of and considers swallow hole improving one's methods on the DHSVM model of the impact of karst drainage Process of Confluence; Further, the invention provides and a kind ofly consider deep layer runoff zones improving one's methods on the DHSVM model of the impact of karst drainage Process of Confluence.
For solving the problems of the technologies described above, the technical solution used in the present invention is:
Improving one's methods of a kind of DHSVM model, it is characterized in that: comprise and add the improvement module of swallow hole on the calculating that Process of Confluence affects: adopt without filling out hollow dem data, utilize ESRI ArcGIS technology to carry out swallow hole identification and earth's surface runoff concentration calculation, and the surface water collected by swallow hole count subterranean stream carries out subterranean stream runoff concentration calculation.
The present invention also comprises and adds the improvement module of deep layer runoff zones on the calculating that Process of Confluence affects:
Deep layer runoff zones storage capacity and connect each other between top Epi-karst increment and excretion, constantly transform, is in dynamic balance state.Due to supply and the excretion of underground water, the underground water in deep layer runoff zones is made constantly to replace and to upgrade.In different periods, deep layer runoff zones pondage along with increment and excretion size and change.
Deep layer runoff zones and the water yield exchange of moisture of Epi-karst that it covers are:
In formula (1): d
nethe thickness of Epi-karst;
it is t Epi-karst average moisture content;
that t soil horizon infiltrates the Epi-karst water yield;
that t Epi-karst side direction flows into and flows out the water yield respectively;
the water yield of t Epi-karst to the supply of deep layer runoff zones;
it is the reverse supply that t deep layer runoff zones rises to Epi-karst due to water level;
In formula (2): S
tit is t deep layer runoff zones moisture storage capacity;
with
the side direction inflow of t deep layer runoff zones and the outflow water yield respectively;
The calculating of deep layer runoff zones lateral stream adopts landform to drive the computing method of the lower saturated interflow of impact, utilizes the hydraulic gradient between underground water table calculating deep layer runoff zones computing grid unit;
Deep layer runoff zones do not store full before, the Epi-karst water on upper strata by under ooze and supply carried out to deep layer runoff zones, until deep layer runoff zones stores full; When in computing grid unit, the water yield of deep layer runoff zones is greater than its maximum reservoir capacity, then the unnecessary water yield " return " is to top Epi-karst;
When the deep layer runoff zones water level in computing grid unit goes to river riverbed above Ground, the water-bearing zone water yield will be retained by buried channel; It is identical that computing method and the river course, earth's surface of interception intercept interflow.
Under landform drives and affects, the computing method of saturated interflow and the computing method of interception are the method in original DHSVM model.
Deep layer runoff zones current are chief components of subterranean stream dry season runoff; The crack aquifer that perviousness is less is there is, i.e. deep layer runoff zones in deep layer water-bearing zone under Epi-karst; Deep layer runoff zones current are chief components of karst drainage subterranean stream dry season runoff.
Described swallow hole recognition methods is: utilize ESRIArcGIS technology to carry out swallow hole and the identification of charge for remittance scope thereof; According to the development characteristics of swallow hole, utilize ESRI ArcGIS to differentiate depression on DEM figure, depression minimum point is swallow hole position, is swallow hole charge for remittance scope by border, depression to the scope of swallow hole; When place, depression computing grid unit or periphery computing grid element memory are at subterranean stream pipeline, institute collects surface water capacity and directly will enter subterranean stream, participates in subterranean stream Process of Confluence.
Described computing grid unit is according to DEM sizing grid, DHSVM model will wait that investigating river basins is divided into some computing grid unit, and in each computing grid unit, meteorological element and underground properties are different with change in time and space; Described meteorological element comprises rainfall, temperature and radiation; Described underground properties comprises the gradient, slope aspect, soil and vegetation.
The size of described computing grid unit is identical with DEM sizing grid.
Described improving one's methods of DHSVM model comprises the following steps:
Step one: adopt 1:1 ten thousand topomap to generate dem data;
Step 2: the generation of surface flow: according to dem data, utilizes ESRIArcGIS Software Create surface flow, and described surface flow is made up of river course, some sections of earth's surfaces;
Step 3: correct the surface flow in step 2 according to the actual surface drainage system waiting to investigate landforms;
Step 4: described surface flow is divided into some calculating sections according to DEM sizing grid, calculates according to DEM the gradient that each section calculates section; Step 4 is used for automatically determining calculate the section gradient and carry out automatic numbering to the order of connection in river course, every section of earth's surface, in order to calculate earth's surface interchannel water movement; Described water movement and the concentration of channel;
Step 5: the generation of the network of waterways, underground: the subterranean stream according to field exploration distributes, and draws the network of waterways, underground in ESRIArcGIS software, manually determines the order of connection of every section of buried channel and carries out manual numbering, in order to calculate confluxing of every section of buried channel; And according to DEM sizing grid, the network of waterways, described underground is divided into section, some calculating undergrounds;
Step 6: the fissuted medium that every section calculates endosexine, section, underground karst band and deep layer runoff zones is all generalized as equivalent continuum medium, and its perviousness is determined according to total water permeable ability that every section calculates section, underground implosion gap medium;
Described fissuted medium is corresponding with porous medium, is made up of the passage of crevice water various crack;
Crevice water is the underground water be present in rock fracture, and being the important sources supplied water in karst, is also the important sources of mine water filling;
Generalization is exactly be convenience of calculation, under the prerequisite be consistent, the crack passage of noncontinuity is originally replaced with successional pore channel according to calculating section water velocity and flow character.
Crack " noncontinuity " in other words crack possibility one is not connected with another, between them just not continuously, also just there is no current (just rock), and " continuity " of hole refers to hole Dou Shi UNICOM one by one all to there is the filling of water between them.
Step 7: collect the meteorological element in each calculating section in certain hour interval; Certain hour is spaced apart 5 ~ 60min;
Step 8: collect underground properties and give the parameter assignment of underground properties;
Step 9: the determination of computing grid dividing elements and simulated time: computing grid cell size adopts the sizing grid the same with DEM grid, is 100m × 100m; Described simulated time comprises parameter calibration phase and modelling verification phase, and the described parameter calibration phase is at least 1 year, and the described modelling verification phase is at least half a year, and the material calculation of described parameter calibration phase and modelling verification phase is at least 1 hour;
After the described modelling verification phase is positioned at the described parameter calibration phase;
The described parameter calibration phase is exactly according to measured value and the minimum each parameter of principle Confirming model of the error of calculation;
The described modelling verification phase is exactly choose the different periods, and the parameter that utilization factor is reserved calculates, the consistance of verification computation result and measured value;
Step 10: swallow hole identification;
Step 11: parameter calibration and modelling verification: according to waiting to investigate the subterranean stream and river, earth's surface measured discharge data that river basins export, adopt trial and error to carry out parameter calibration and modelling verification to model.
The surface water that swallow hole collects comprises swallow hole peripheral ground current, Epi-karst current and interflow.
Parameter assignment method in step 8 is the occurrence drawing parameter according to test observation means, then makes the parameter in model get these occurrences.
The different period in step 9 comprises rainfall initial stage, overflow stage and water-break phase.
Trial and error is method the most frequently used in DHSVM model, sees the difference of result of calculation and actual result exactly, if differed greatly, just changes parameter and recalculates, until error reaches cut-off in acceptable scope, and trial and error that Here it is.
Karst is divided into earth's surface river system to unify Underground river system, and what step 2 generated is earth's surface river system system, and what step 5 generated is Underground river system.Because river system system in earth's surface judges to generate according to landform, in generative process, automatic decision goes out the height in river course, each section of earth's surface and is assigned with linked numbering, confluxes in order to calculate.Subterranean stream runoff concentration calculation also needs to know the link order of every section of buried channel, and Underground river system is often grown and do not controlled by landform, therefore automatically cannot judge and compose numbering, therefore needing manual numbering.
For larger karst drainage, be often difficult to obtain detailed fracture water flow parameter, be thus difficult to accurate description tiny crack water movement process.The present invention is in model calculates, and the fissuted medium of computing grid unit endosexine karst band and deep layer runoff zones is all generalized as equivalent continuum medium, and its perviousness is determined according to the total water permeable ability in crack in computing grid unit.
In DHSVM master mould, surface water and Epi-karst crevice water module can simulate peb processes.But when carrying out Long-Term Simulations to withered phase runoff, effect is poor.Mainly use a large amount of measured discharge data to be processed by statistical method or deviation correction method at present for this problem, and do not consider according to the hydrogeological condition of reality the reason causing this problem.The present invention, according to the binary hydrogeologic structure of Karst District in Southwest China, also exists the crack aquifer that perviousness is less, i.e. deep layer runoff zones in the deep layer water-bearing zone under Epi-karst.Deep layer runoff zones current are chief components of karst drainage subterranean stream dry season runoff.Therefore, be necessary under Epi-karst, add deep layer runoff zones module, consider the hydraulic connection between Epi-karst and the deep layer runoff zones under it, and deep layer runoff zones be to the supply of subterranean stream.
River, earth's surface and the subterranean stream effect in current collect in the present invention:
1, surface drainage system calculation method
Surface drainage system calculation adopts linear groove to store method and calculates.River course, each earth's surface is divided into some independence and calculates section, each calculates section respective hydraulic parameter.Each calculates the side direction of section and becomes a mandarin to be confluxed by side direction in the overland flow of the basin computing grid unit of this calculating section process and Epi-karst or top layer soil layer and form, go out stream flow into neighborhood calculation section or flow out this basin, also likely get back in the basin computing grid unit at its place, now river course, this section of earth's surface outflow will be added in the surface water of computing grid unit, if surface drainage system is crossing with lithic drainage, likely again groundwater flow can be converted into.
Linear groove stores method and river course, each earth's surface is considered as the reservoir that width is constant, and supposes between every bar earth's surface river course outflow Q and the groove amount of storing S linear, i.e. Q=kS, wherein
In formula, Rr is with reference to the hydraulic radius (getting 3/4 of river course depth of cut) under the depth of water; So, Δ L and n represent gradient, earth's surface channel length and earth's surface channel roughness respectively.
Period Mo pondage
computing formula as follows:
In formula, Qin is upstream inbound traffics and side direction inbound traffics in the period.
The average outflow Q in river course
outby water balance Solving Equations:
2, lithic drainage calculation method
Underground river, underground, crack and buried channel play an important role in karst drainage current Process of Confluence.Wait to investigate landforms subterranean stream development characteristics according to studying, the network of waterways, underground is generalized as tree-type pipe network by the present invention, according to field study, grasps distribution range and the buried channel development characteristics of buried channel.The first connectable order of regulation buried channel and characteristic parameter, and according to DEM sizing grid, the network of waterways, described underground is divided into section, some calculating undergrounds; Utilize the network of waterways, ESRI ArcGIS Software Create underground, comprise the information such as buried channel length, the gradient, roughness and buried channel numbering.Adopt the linear groove same with earth's surface river facies to store method and carry out concentration of channel calculating to subterranean stream, side direction inbound traffics, except soil, Epi-karst supply, also comprise the supply of deep layer runoff zones and swallow hole.
2.1, river, earth's surface and subterranean stream current exchange
In some subterranean stream and river, earth's surface intersection, subterranean stream takes by surprise earth's surface streamflow.River course, earth's surface outflow enters subterranean stream as the side direction flow of subterranean stream, that is:
Vg side=Vsoil+Vf+Vs side
Vs side=Qsout × Δ t
In formula, Vg side is the side direction inbound traffics of section, a certain calculating underground; Vsoil be this section, calculating underground process computing grid unit in the supply of the holard; Vf is the supply of the computing grid unit endosexine karst band crevice water of this section, calculating underground process; Vs side is that subterranean stream takes by surprise earth's surface river water; Qsout is the outflow in river course, taken by surprise earth's surface.
2.2, swallow hole, skylight and funnel etc. collect surface water supply buried channel
DHSVM master mould adopts fills out hollow method generation flow concentration path.According to Karst Landform Process In Mid mechanism and field investigation data, geomorphic unit is multiple educates at hypsography low-lying place for swallow hole, skylight and funnel etc., after overflow stage, slope runoff was collected to depression, directly enter underground river, underground by geomorphic units such as swallow holes, therefore master mould cannot consider that the karst landforms such as swallow hole collect top layer runoff and concentrate the effect on underground river under charging point.
The present invention in a model, adopting the dem data without filling out hollow process, utilizing ESRI ArcGIS technology, in conjunction with field investigation, identifies landform depression and the charge for remittance scopes thereof such as swallow hole.When place, depression computing grid unit or periphery computing grid element memory are at subterranean stream pipeline, institute collects surface water capacity and directly will enter subterranean stream, participates in subterranean stream Process of Confluence.
Improving one's methods of a kind of DHSVM model provided by the invention, take karst as research object, consider the dual convergence system hydrologic process in earth's surface-underground of karst features effect, use the improvement to DHSVM model, simulated rainfall-runoff responding process, and the effect that analytical model is improved; Analog result shows, and model simulate survey region groundwater flow process, reflects the response relation of the factor such as run in depth and rainfall, hydrogeological condition, underground properties; To conflux feature according to hillside fields, karst, swallow hole is mainly remarkable to storm flood process influence, is namely embodied in the impact on flood peak.
Accompanying drawing explanation
Fig. 1 is water movement schematic diagram in mesexine karst band of the present invention;
Fig. 2 is the flow concentration path after low-lying area is filled out in the landform depression such as master mould swallow hole;
Fig. 3 is that the landform depression such as swallow hole of the present invention are without filling out the actual flow concentration path behind low-lying area;
Fig. 4 is the regular rainfall runoff simulation result figure of subterranean stream rate of the present invention;
Fig. 5 is the regular rainfall runoff simulation result figure of river, earth's surface of the present invention rate;
Fig. 6 is subterranean stream of the present invention checking phase rainfall runoff simulation result figure;
Fig. 7 is river, earth's surface of the present invention checking phase rainfall runoff simulation result figure;
Fig. 8 is the effect diagram of swallow hole of the present invention to subterranean stream runoff;
Fig. 9 is that deep layer runoff zones of the present invention is to the effect diagram of subterranean stream runoff.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further described.
As shown in Fig. 1 ~ 9, after the present invention, stockaded village's river valley is research object, considers the dual convergence system hydrologic process in earth's surface-underground of karst features effect, uses the improvement to DHSVM model, simulated rainfall-runoff responding process, and the effect that analytical model is improved.
Improving one's methods of a kind of DHSVM model, it is characterized in that: comprise and add the improvement module of swallow hole on the calculating that Process of Confluence affects: adopt without filling out hollow dem data, utilize ESRI ArcGIS technology to carry out swallow hole identification and earth's surface runoff concentration calculation, and the surface water collected by swallow hole count subterranean stream carries out subterranean stream runoff concentration calculation.
Also comprise and add the improvement module of deep layer runoff zones on the calculating that Process of Confluence affects:
Deep layer runoff zones and the water yield exchange of moisture of Epi-karst that it covers are:
In formula (1): d
nethe thickness of Epi-karst;
it is t Epi-karst average moisture content;
that t soil horizon infiltrates the Epi-karst water yield;
that t Epi-karst side direction flows into and flows out the water yield respectively;
the water yield of t Epi-karst to the supply of deep layer runoff zones;
it is the reverse supply that t deep layer runoff zones rises to Epi-karst due to water level;
In formula (2): S
tit is t deep layer runoff zones moisture storage capacity;
with
the side direction inflow of t deep layer runoff zones and the outflow water yield respectively;
The calculating of deep layer runoff zones lateral stream adopts landform to drive the computing method of the lower saturated interflow of impact, utilizes the hydraulic gradient between underground water table calculating deep layer runoff zones computing grid unit;
Deep layer runoff zones do not store full before, the Epi-karst water on upper strata by under ooze and supply carried out to deep layer runoff zones, until deep layer runoff zones stores full; When in computing grid unit, the water yield of deep layer runoff zones is greater than its maximum reservoir capacity, then the unnecessary water yield " return " is to top Epi-karst;
When the deep layer runoff zones water level in computing grid unit goes to river riverbed above Ground, the water-bearing zone water yield will be retained by buried channel; It is identical that computing method and the river course, earth's surface of interception intercept interflow.
Deep layer runoff zones current are chief components of subterranean stream dry season runoff; The crack aquifer that perviousness is less is there is, i.e. deep layer runoff zones in deep layer water-bearing zone under Epi-karst; Deep layer runoff zones current are chief components of karst drainage subterranean stream dry season runoff.
Described swallow hole recognition methods is: utilize ESRIArcGIS technology to carry out swallow hole and the identification of charge for remittance scope thereof; According to the development characteristics of swallow hole, utilize ESRI ArcGIS to differentiate depression on DEM figure, depression minimum point is swallow hole position, is swallow hole charge for remittance scope by border, depression to the scope of swallow hole; When place, depression computing grid unit or periphery computing grid element memory are at subterranean stream pipeline, institute collects surface water capacity and directly will enter subterranean stream, participates in subterranean stream Process of Confluence.
Described computing grid unit is according to DEM sizing grid, DHSVM model will wait that investigating river basins is divided into some computing grid unit, and in each computing grid unit, meteorological element and underground properties are different with change in time and space; Described meteorological element comprises rainfall, temperature and radiation; Described underground properties comprises the gradient, slope aspect, soil and vegetation.
The size of described computing grid unit is identical with DEM sizing grid.
Described improving one's methods of DHSVM model comprises the following steps:
Step one: adopt 1:1 ten thousand topomap to generate dem data;
Step 2: the generation of surface flow: according to dem data, utilizes ESRIArcGIS Software Create surface flow, and described surface flow is made up of river course, some sections of earth's surfaces;
Step 3: correct the surface flow in step 2 according to the actual surface drainage system waiting to investigate landforms;
Step 4: described surface flow is divided into some calculating sections according to DEM sizing grid, calculates according to DEM the gradient that each section calculates section; Step 4 is used for automatically determining calculate the section gradient and carry out automatic numbering to the order of connection in river course, every section of earth's surface, in order to calculate earth's surface interchannel water movement; Described water movement and the concentration of channel;
Step 5: the generation of the network of waterways, underground: the subterranean stream according to field exploration distributes, and draws the network of waterways, underground in ESRIArcGIS software, manually determines the order of connection of every section of buried channel and carries out manual numbering, in order to calculate confluxing of every section of buried channel; And according to DEM sizing grid, the network of waterways, described underground is divided into section, some calculating undergrounds;
Step 6: the fissuted medium that every section calculates endosexine, section, underground karst band and deep layer runoff zones is all generalized as equivalent continuum medium, and its perviousness is determined according to total water permeable ability that every section calculates section, underground implosion gap medium;
Described fissuted medium is corresponding with porous medium, is made up of the passage of crevice water various crack;
Crevice water is the underground water be present in rock fracture, and being the important sources supplied water in karst, is also the important sources of mine water filling;
Generalization is exactly be convenience of calculation, under the prerequisite be consistent, the crack passage of noncontinuity is originally replaced with successional pore channel according to calculating section water velocity and flow character.
Step 7: collect the meteorological element in each calculating section in certain hour interval; Certain hour is spaced apart 5 ~ 60min;
Step 8: collect underground properties and give the parameter assignment of underground properties;
Step 9: the determination of computing grid dividing elements and simulated time: computing grid cell size adopts the sizing grid the same with DEM grid, is 100m × 100m; Described simulated time comprises parameter calibration phase and modelling verification phase, and the described parameter calibration phase is at least 1 year, and the described modelling verification phase is at least half a year, and the material calculation of described parameter calibration phase and modelling verification phase is at least 1 hour;
After the described modelling verification phase is positioned at the described parameter calibration phase;
The described parameter calibration phase is exactly according to measured value and the minimum each parameter of principle Confirming model of the error of calculation;
The described modelling verification phase is exactly choose the different periods, and the parameter that utilization factor is reserved calculates, the consistance of verification computation result and measured value;
Step 10: swallow hole identification;
Step 11: parameter calibration and modelling verification: according to waiting to investigate the subterranean stream and river, earth's surface measured discharge data that river basins export, adopt trial and error to carry out parameter calibration and modelling verification to model.
The surface water that swallow hole collects comprises swallow hole peripheral ground current, Epi-karst current and interflow.
Parameter assignment method in step 8 is the occurrence drawing parameter according to test observation means, then makes the parameter in model get these occurrences.
The different period in step 9 comprises rainfall initial stage, overflow stage and water-break phase.
In rear stockaded village river valley, meteorological data adopts Chen Qi many key elements weather station observational data, comprises the meteorological elements such as rainfall, temperature, wind speed, relative humidity, radiation, and observation step-length is 5 minutes.Be provided with Chen Qi, old Blackpool, Hou Zhai river in basin and emit rainfall observation station, puddle, observation step-length is 15 minutes.
Hydrologic data adopts debouchure in basin to emit puddle website and debouchment Hou Zhai river, earth's surface website 2007-2009 by a hour Flow Observation data.
Underlying surface data and parameter assignment: underlying surface in basin is mainly divided into 5 types according to on-site inspection, be respectively forest land, shrubbery, crop, solidification ground and the water surface.Wherein forest land, shrubbery and crop parameter, determines with reference to experience span and land surface models LDAS (Land Data Assimilation System), the root system band degree of depth and root system development as shown in table 1.Solidification ground and the water surface all do not consider Infiltration, and namely rainfall directly produces rainwash, confluxes to closing on computing grid unit.
Table 1, rear stockaded village river valley vegetation root system parameter attribute
Model of the present invention is divided into 3 layers on vertical, is respectively soil horizon, Epi-karst and deep layer current band, determines that each layer hydrogeological parameter is as model initial parameter according to factual survey and test.
According to field investigation, soil is divided into 3 classes generally, is respectively clay, clay loam and loam.Eastern Mountain Area thickness of soil 30 ~ 50cm, Western Plains district thickness of soil 1 ~ 2m.The factor of porosity recording three kinds of soil according to laboratory experiment is 0.3 ~ 0.45, and field capacity is 0.15 ~ 0.36.Adopt single-ring infiltration method to carry out the field in-site detecting of infiltration coefficient, recording clay vertical saturation permeability coefficient magnitude is 10
-7m/s, the vertical saturation permeability coefficient magnitude of clay loam and loam is respectively 10
-6with 10
-5m/s.Side direction saturation permeability coefficient magnitude gets 10 times of vertical saturation permeability coefficient magnitude respectively.
According to field study statistics, Epi-karst crack rate is 0.05 ~ 0.1, and measuring infiltration coefficient magnitude by site test is 10
-4~ 10
-3m/s.Obtaining rear stockaded village river valley Epi-karst growth thickness by ground penetrating radar exploration is 3 ~ 20m.The space distribution of Epi-karst thickness is generated according to watershed unit and the exploration of the typical investigation point Epi-karst degree of depth.
According to scholars such as Yu Jinbiao to rear stockaded village's river valley hydrogeologic survey result, this basin minimum runoff band buried depth about 20 ~ 40m, grows thickness exploration analysis result (3 ~ 20m), if deep layer runoff zones thickness is about 20m in conjunction with Epi-karst.
Epi-karst perviousness increases with the degree of depth and reduces, and bottom Epi-karst, it is more remarkable that perviousness reduces trend.With reference to the infiltration coefficient scope estimated, vertical for deep layer runoff zones and side direction saturation permeability coefficient initial value magnitude are decided to be 10 above
-6~ 10
-5m/s, according to measuring runoff to the further calibration of parameter.
Computing grid dividing elements and simulated time: according to the rear stockaded village river valley dem data generated, computing grid cell size adopts the sizing grid the same with DEM, is 100m × 100m.Basin is divided into 96 row, 124 row.According to field data, modeling period rate is regularly on Dec 31 ,-2008 years on the 27th July in 2007, and the checking phase is on November 10 ,-2009 years on the 13rd March in 2009, and material calculation is 1 hour.
Swallow hole identification: educate because swallow hole is multiple in water logged zone place, mountain area, therefore adopting without filling out hollow dem data, utilizing ESRIArcGIS technology to carry out swallow hole and the identification of charge for remittance scope thereof.According to the development characteristics of swallow hole, utilize ESRI ArcGIS to differentiate depression on DEM figure, depression minimum point is swallow hole position, is swallow hole charge for remittance scope by border, depression to the scope of swallow hole.By hydraulic gradient and charge for remittance range effects, mountain area swallow hole collects insulated stream and has significant control action.Relative mountain area, it is more weak that region of no relief swallow hole collects effect to insulated stream.Therefore, this simulation watershed Eastern Mountain Area swallow hole and charge for remittance scope thereof identify.
Parameter calibration and modelling verification: go to river and river, earth's surface measured discharge data according to river valley export place, rear stockaded village, adopt trial and error to carry out parameter calibration and modelling verification to model.The parameter calibration result of soil and vegetation is as shown in table 2.Epi-karst parameter is: factor of porosity, field capacity and wilting percentage are respectively 0.1,0.02 and 0.01, and vertical and side direction saturation permeability coefficient is respectively 1 × 10
-4with 8 × 10
-4m/s.Deep layer runoff zones parameter is: factor of porosity is 0.08, and vertical and side direction saturation permeability coefficient is respectively 5 × 10
-6with 3 × 10
-5m/s.
Table 2, model soil and vegetable layer parameter calibration result
Result is weighed with efficiency factor NSE, relative error RE and root-mean-square error RMSE, and its computing formula is respectively:
In formula: Obs
ifor measured value, Sim
ifor the analogue value,
for the mean value of observed reading, n is data amount check.
Analog result is as also shown in e.g. figs. 4-7: for subterranean stream, rate regular subterranean river amount simulation precision coefficient NSE is 0.74, and water yield relative error RE is 2%, root-mean-square error RMSE is 0.36m
3/ s.The checking phase, subterranean river amount efficiency coefficient NSE was 0.71, and water yield relative error RE is-3%, root-mean-square error RMSE is 0.28m3/s.For river, earth's surface, rate regular earth's surface river flow simulation precision coefficient NSE is 0.67, and water yield relative error RE is 38%, root-mean-square error RMSE is 1.62m3/s.The checking phase, river flow efficiency factor NSE in earth's surface was 0.58, and water yield relative error RE is 34%, root-mean-square error RMSE is 1.43m3/s.
Earth's surface river flow simulate effect is good not as subterranean stream simulate effect, and this is mainly strong due to riverbed, river, river valley earth's surface, rear stockaded village perviousness, except heavy showers, dry in river course, river recharge groundwater.Therefore when low water and light rain, the simulation of river, earth's surface is bigger than normal, causes river, earth's surface simulation error bigger than normal.Therefore, to earth's surface river flow mainly to the simulation of peb process.
Analog result shows, and model simulate survey region groundwater flow process, reflects the response relation of the factor such as run in depth and rainfall, hydrogeological condition, underground properties.
As shown in Figure 8, swallow hole is on the impact of Process of Confluence: rear stockaded village river valley grows more swallow hole, overflow stage, swallow hole collected peripheral ground current and Epi-karst current and interflow, directly supply buried channel current are concentrated at hypsography low-lying place, being the important channel that karst drainage surface and ground water transforms mutually, is also the one of the main reasons causing karst and Non-karst area Process of Confluence difference.According to the swallow hole water catchment area identified, analyze swallow hole to the impact of hydrologic process.
Rate of choosing regular rainfall-subterranean stream runoff process, simulates respectively with or without the impact of swallow hole on Rainfall-Runoff.When not considering the situation that swallow hole affects, low-lying area is filled out to dem data, utilize and fill out hollow dem data and carry out slope concentration calculating.When considering the situation having swallow hole affect, then utilize the dem data without filling out low-lying area to carry out swallow hole identification and earth's surface runoff concentration calculation, and the surface water collected by swallow hole count subterranean stream carries out subterranean stream runoff concentration calculation.Analog result shows, and because swallow hole collects the concentrated alimentation of surface water to subterranean stream, consider the analog result of swallow hole impact, subterranean stream crest discharge is significantly greater than the analog result not considering that swallow hole affects.To conflux feature according to hillside fields, karst, swallow hole is mainly remarkable to storm flood process influence, is namely embodied in the impact on flood peak.
Choosing the subterranean stream discharge process of 27-28 day in May, 2008, there is twice flood peak in this period altogether, and when not considering that swallow hole affects, crest discharge is respectively 4.0 and 5.6m
3/ s, when considering that swallow hole affects, response crest discharge is respectively 8.0 and 9.1m
3/ s.Collect effect due to swallow hole, subterranean stream accepts surface water and concentrates supply, and flood peak significantly increases.Therefore, karst drainage swallow hole changes flow path and current binding mode, and the run-off major part that rainfall is formed enters ground water regime, thus affects this area's hydrologic process.
As shown in Figure 9, deep layer runoff zones is on the impact of subterranean stream runoff process: although deep layer runoff zones holds water-based and the little Epi-karst thereon of perviousness, but it has material impact to karst rainfall-runoff process, especially deep layer runoff zones current are chief components of subterranean stream dry season runoff.The present invention when considering deep layer runoff zones and not considering the effect of deep layer runoff zones, the regular subterranean stream runoff process of the rate that simulates respectively.Analog result shows, and in the dry season, compared with consideration deep layer runoff zones, the subterranean stream flow analog result without deep layer runoff zones is significantly less than normal; On the contrary, in overflow stage, the subterranean stream peak flow without deep layer runoff zones is significantly bigger than normal.This be due to rainy season the part rainfall infiltration water yield enter deep layer runoff zones through Epi-karst, therefore, deep layer runoff zones store rainy season the part water yield, the effect of slackening is played to river course flood peak.In withered season, being stored in the water yield slow releasing in deep layer runoff zones, carrying out supply to subterranean stream, is the chief component of dry season runoff.
The present invention improves DHSVM hydrological distribution model, adds the calculating that swallow hole and deep layer runoff zones affect Process of Confluence, is applied to Guizhou Hou Zhaihe karst drainage rainfall-runoff simulation, obtains following Main Conclusions:
(1) according to site test and observational data, show through parameter rating of the model and modelling verification, river, river valley earth's surface, stockaded village and subterranean stream discharge process after improved model energy simulate.
(2) model energy simulate swallow hole to conflux the impact in river of going underground on surface water.Analog result shows, karst drainage swallow hole changes flow path and current binding mode, and the run-off major part that rainfall is formed enters ground water regime, collects effect due to swallow hole, and subterranean stream accepts surface water and concentrates supply, and crest discharge significantly increases.
(3) model reflects the difference that Epi-karst and deep layer runoff zones are regulated and stored to current preferably, and analog result shows, compared with consideration deep layer runoff zones, in the dry season, the subterranean stream flow analog result without deep layer runoff zones is significantly less than normal; On the contrary, in overflow stage, subterranean stream peak flow is significantly bigger than normal.Therefore, deep layer runoff zones stores the part water yield in rainy season, plays to river course flood peak the effect of slackening.In withered season, being stored in the water yield slow releasing in deep layer runoff zones, carrying out supply to subterranean stream, is the chief component of dry season runoff.
The above is only the preferred embodiment of the present invention; be noted that for those skilled in the art; under the premise without departing from the principles of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (9)
1. the improving one's methods of a DHSVM model, it is characterized in that: comprise and add the improvement module of swallow hole on the calculating that Process of Confluence affects: adopt without filling out hollow dem data, utilize ESRI ArcGIS technology to carry out swallow hole identification and earth's surface runoff concentration calculation, and the surface water collected by swallow hole count subterranean stream carries out subterranean stream runoff concentration calculation.
2. the improving one's methods of a kind of DHSVM model according to claim 1, is characterized in that: also comprise and add the improvement module of deep layer runoff zones on the calculating that Process of Confluence affects:
Deep layer runoff zones and the water yield exchange of moisture of Epi-karst that it covers are:
In formula (1): d
nethe thickness of Epi-karst;
it is t Epi-karst average moisture content;
that t soil horizon infiltrates the Epi-karst water yield;
that t Epi-karst side direction flows into and flows out the water yield respectively;
the water yield of t Epi-karst to the supply of deep layer runoff zones;
it is the reverse supply that t deep layer runoff zones rises to Epi-karst due to water level;
In formula (2): S
tit is t deep layer runoff zones moisture storage capacity;
with
the side direction inflow of t deep layer runoff zones and the outflow water yield respectively;
The calculating of deep layer runoff zones lateral stream adopts landform to drive the computing method of the lower saturated interflow of impact, utilizes the hydraulic gradient between underground water table calculating deep layer runoff zones computing grid unit;
Deep layer runoff zones do not store full before, the Epi-karst water on upper strata by under ooze and supply carried out to deep layer runoff zones, until deep layer runoff zones stores full; When in computing grid unit, the water yield of deep layer runoff zones is greater than its maximum reservoir capacity, then the unnecessary water yield " return " is to top Epi-karst;
When the deep layer runoff zones water level in computing grid unit goes to river riverbed above Ground, the water-bearing zone water yield will be retained by buried channel; It is identical that computing method and the river course, earth's surface of interception intercept interflow.
Deep layer runoff zones current are chief components of subterranean stream dry season runoff; The crack aquifer that perviousness is less is there is, i.e. deep layer runoff zones in deep layer water-bearing zone under Epi-karst; Deep layer runoff zones current are chief components of karst drainage subterranean stream dry season runoff.
3. the improving one's methods of a kind of DHSVM model according to claim 1, is characterized in that: described swallow hole recognition methods is: utilize ESRIArcGIS technology to carry out swallow hole and the identification of charge for remittance scope thereof; According to the development characteristics of swallow hole, utilize ESRI ArcGIS to differentiate depression on DEM figure, depression minimum point is swallow hole position, is swallow hole charge for remittance scope by border, depression to the scope of swallow hole; When place, depression computing grid unit or periphery computing grid element memory are at subterranean stream pipeline, institute collects surface water capacity and directly will enter subterranean stream, participates in subterranean stream Process of Confluence.
4. the improving one's methods of a kind of DHSVM model according to claim 1, it is characterized in that: described computing grid unit is according to DEM sizing grid, DHSVM model will wait that investigating river basins is divided into some computing grid unit, and in each computing grid unit, meteorological element and underground properties are different with change in time and space; Described meteorological element comprises rainfall, temperature and radiation; Described underground properties comprises the gradient, slope aspect, soil and vegetation.
5. the improving one's methods of a kind of DHSVM model according to claim 1, is characterized in that: the size of described computing grid unit is identical with DEM sizing grid.
6. the improving one's methods of a kind of DHSVM model according to claim 1, is characterized in that: described improving one's methods of DHSVM model comprises the following steps:
Step one: adopt 1:1 ten thousand topomap to generate dem data;
Step 2: the generation of surface flow: according to dem data, utilizes ESRIArcGIS Software Create surface flow, and described surface flow is made up of river course, some sections of earth's surfaces;
Step 3: correct the surface flow in step 2 according to the actual surface drainage system waiting to investigate landforms;
Step 4: described surface flow is divided into some calculating sections according to DEM sizing grid, calculates according to DEM the gradient that each section calculates section; Step 4 is used for automatically determining calculate the section gradient and carry out automatic numbering to the order of connection in river course, every section of earth's surface, in order to calculate earth's surface interchannel water movement; Described water movement and the concentration of channel;
Step 5: the generation of the network of waterways, underground: the subterranean stream according to field exploration distributes, and draws the network of waterways, underground in ESRIArcGIS software, manually determines the order of connection of every section of buried channel and carries out manual numbering, in order to calculate confluxing of every section of buried channel; And according to DEM sizing grid, the network of waterways, described underground is divided into section, some calculating undergrounds;
Step 6: the fissuted medium that every section calculates endosexine, section, underground karst band and deep layer runoff zones is all generalized as equivalent continuum medium, and its perviousness is determined according to total water permeable ability that every section calculates section, underground implosion gap medium;
Described fissuted medium is corresponding with porous medium, is made up of the passage of crevice water various crack;
Crevice water is the underground water be present in rock fracture, and being the important sources supplied water in karst, is also the important sources of mine water filling;
Generalization is exactly be convenience of calculation, under the prerequisite be consistent, the crack passage of noncontinuity is originally replaced with successional pore channel according to calculating section water velocity and flow character.
Step 7: collect the meteorological element in each calculating section in certain hour interval; Certain hour is spaced apart 5 ~ 60min;
Step 8: collect underground properties and give the parameter assignment of underground properties;
Step 9: the determination of computing grid dividing elements and simulated time: computing grid cell size adopts the sizing grid the same with DEM grid, is 100m × 100m; Described simulated time comprises parameter calibration phase and modelling verification phase, and the described parameter calibration phase is at least 1 year, and the described modelling verification phase is at least half a year, and the material calculation of described parameter calibration phase and modelling verification phase is at least 1 hour;
After the described modelling verification phase is positioned at the described parameter calibration phase;
The described parameter calibration phase is exactly according to measured value and the minimum each parameter of principle Confirming model of the error of calculation;
The described modelling verification phase is exactly choose the different periods, and the parameter that utilization factor is reserved calculates, the consistance of verification computation result and measured value;
Step 10: swallow hole identification;
Step 11: parameter calibration and modelling verification: according to waiting to investigate the subterranean stream and river, earth's surface measured discharge data that river basins export, adopt trial and error to carry out parameter calibration and modelling verification to model.
7. the improving one's methods of a kind of DHSVM model according to claim 1, is characterized in that: the surface water that swallow hole collects comprises swallow hole peripheral ground current, Epi-karst current and interflow.
8. the improving one's methods of a kind of DHSVM model according to claim 6, is characterized in that: the parameter assignment method in step 8 is the occurrence drawing parameter according to test observation means, then makes the parameter in model get these occurrences.
9. the improving one's methods of a kind of DHSVM model according to claim 6, is characterized in that: the different period in step 9 comprises rainfall initial stage, overflow stage and water-break phase.
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| CN108020649A (en) * | 2017-11-22 | 2018-05-11 | 济南大学 | A kind of method of definite karst big spring feed channel and intensity |
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| CN108920429B (en) * | 2018-06-12 | 2022-02-11 | 河海大学 | Abnormal data analysis method for dynamic water level monitoring |
| CN109472072A (en) * | 2018-10-30 | 2019-03-15 | 中国水利水电科学研究院 | Interaction prediction method between ephemeral stream and underground water based on simulating river |
| CN109472072B (en) * | 2018-10-30 | 2020-09-01 | 中国水利水电科学研究院 | Seasonal river and underground water interaction prediction method based on river simulation |
| CN110674469A (en) * | 2019-09-27 | 2020-01-10 | 长沙理工大学 | Hydrological frequency calculation method suitable for arid karst deficient data area |
| CN110674469B (en) * | 2019-09-27 | 2023-04-14 | 长沙理工大学 | Hydrological frequency calculation method suitable for arid karst-deficient data area |
| CN114429089A (en) * | 2021-12-16 | 2022-05-03 | 河海大学 | Distributed nonlinear hydrological simulation method for karst area |
| CN114429089B (en) * | 2021-12-16 | 2022-12-13 | 河海大学 | Distributed nonlinear hydrological simulation method for karst area |
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