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Sediment behaviour in grass filter strips
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Pergamon Pergamon
Wat. Sci. Tech. Vol. No. 9, pp. 129-136, 1999 Wat. Sci. Tech. Vol. 39, 39, No.9, 129-136, 1999 Q 1999IAWQ 1999 IAWQ ©
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SEDIMENT BEHAVIOUR IN SEDIMENT BEHAVIOUR IN GRASS FILTER FILTER STRIPS STRIPS GRASS Ana Deletic Ana Deletic Department of Engineering, University of Aberdeen, King’s College, Fraser Noble Department ofEngineering, University ofAberdeen, King's College, Fraser Noble Building, 3UE, UE, UK UK Building, Aberdeen, Aberdeen, AB24 AB24 3
ABSTRACT ABSTRACT Sediment in non-submerged non-submerged overland flow flow over over grass in aa laboratory. Artificial turf turf Sediment transport transport was was studied studied in overland grass in laboratory. Artificial (a&o-w was used simulate natural no infiltration infiltration was allowed allowed at this stage stage of of the the (astro-turf) was used to to simulate natural grass grass and and no was at this investigation. for different different grass densities, flow rates, sediment sediment inflows, inflows, and and investigation. Experiments Experiments were were conducted conducted for grass densities, flow rates, sediment tbat concentration of sediment sediment in in runoff runoff decreases decreases exponentially exponentially with the the sediment types. types. ItIt was was observed observed that concentration of with distance and reaches asymptotically constant value. value. Measured sediment deposition deposition was was compered with the the distance and reaches asymptotically aa constant Measured sediment compered with results calculated calculated by al., 1976). 1976). The The model the results by the the Kentucky Kentucky model model (Tollner (Tollner et et aI., model over-predicted over-predicted grossly grossly the trapping efficiency of all particle fractions, but it is unreliable particularly for small particles. A new trapping efficiency of all particle fractions, but it is unreliable particularly for small particles. A new simplified relationship was established between particle fall number, Nf, and percentage of particles trapped simplified relationship was established between particle fall number, Nf, and percentage of particles trapped in the grass. The relationship should be verified on natural grass before it is used in practice. Finally, in the grass. The relationship should be verified on natural grass before it is used in practice. Finally, infiltration of water and particles should be studied on natural turf, as well as, influence of grass blades infiltration of water and particles should be studied on Datural turf, as well as, influence of grass blades bending, before the complex model of sediment behaviour in grass is established. 0 1999 IAWQ Published bending, before the complex model of sediment behaviour in grass is established. © 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved by Elsevier Science Ltd. All rights reserved KEYWORDS
KEYWORDS
Grass filter strips; lawns; sediment; storm runoff; swales; water quality.
Grass filter strips; lawns; sediment; stonn runoff; swales; water quality.
INTRODUCTION INTRODUCTION Numerous studies showed that life in urban streams could be heavily damaged due to runoff from urban Numerous studies showed that life in urban streams could be heavily damaged due to runoff from urban areas (Forth River Purification Board, 1994). Techniques to reduce the impact of polluted urban runoff areas (Forth River Purification Board, 1994). Techniques to reduce the impact of polluted urban runoff discharges have been developed recently and collectively form a range of Best Management Practices discharges have been developed recently and collectively fonn a range of Best Management Practices (BMPs). These techniques deal with the problem by reducing quantity of runoff and slowing its velocity to (BMPs). These techniques deal with the problem by reducing quantity of runoff and slowing its velocity to allow pollutant settlement. Grass (turf) was extensively used in BMPs. Grass swales and grass filter strips allow pollutant settlement. Grass (turf) was extensively used in BMPs. Grass swales and grass filter strips (GFS) have been recognised as good management practices for localised containment of pollutants in urban of pollutants in urban (GFS) been recognised as good management for localised containment areas inhave association with suspended solids, e.g. practices heavy metals and organics. Unfortunately, only crude in association with suspended solids, e.g. heavy metals and organics. Unfortunately, only crude areas guidelines exist for their construction or implementation (SEPA, 1996).
guidelines exist for their construction or implementation (SEPA, 1996).
The sediment is the most important non-point pollutant in terms of mass. Besides its total discharge, it is
Besides are its total discharge, it is The sediment is thesediment most important pollutant in chemicals terms of mass. important to assess particle non-point size distribution, since and nutrients primarily associated important to assess sediment particle size distribution, since chemicals and nutrients are primarily associated with the erosion of the fine particles. The reliability of present models of sediment transport in runoff over with the erosion the fine The deterministic reliability of models present models of sediment transport in runoff rural areas is veryofpoor (Wu,particles. 1993), and of sediment discharge from urban areasover are of sediment urban areasofarea ruralyet areas poor (Wu, 1993), and deterministic models not fullyis very developed (Bertrand-Krajewski et al., 1993, Deletic, 1997).discharge Therefore,from development not yet fully developed (Bertrand-Krajewski et al., 1993, Deletic, 1997). Therefore, development of a 129 129
A. DELETIC A.DELETIC
130 130
for prediction transport by by overland flow will contribute reliable model for prediction of of sediment transport flow over grassed areas areas will highly and rural water highly to further further development of of both urban and water quality quality models.
The amount of of sediment trapped in, or released from, grass depends on two two processes occurring at different different processes occurring transformations in grass during dry dry weather, and sediment behaviour in runoff time scales: sediment transformations weather, and runoff during wet weather. slow biochemical process, however however the amount of of sediment trapped in the wet weather. The first first process is aa slow grass changes dramatically during storm storm events. The second process dramatically during process is therefore more important for assessment of release from grassed areas, areas, and and thus the the aim of of the work work currently currently of pollution pollution deposition and release carried out at at the University of Aberdeen Aberdeen is is to investigate sediment sediment behaviour behaviour in in runoff. runoff. This This is is a physical University of physical process where “filter”, and the the transport capacity of the overland flow flow should should be be studied studied as as aa where grass acts as aa "filter", transport capacity of the complex (1) sediment type: particle diameter and and density; (2) flow flow depth and complex function function of of the following: following: (l) velocity; and slope of of soil; (5) velocity; (3) (3) length and of grass; (4) (4) type and condition of (5) grass characteristics: characteristics: density, dimensions of grass grass blades; (6) (6) the the amount amount of of sediment sediment already trapped in in the grass. grass. dimensions and bending of A that there there is dearth of of research in this this area, area, so so far. far. Qualitative Qualitative studies studies showed showed research in A literature literature study study showed showed that is aa dearth that trap sediment sediment and and various pollutants (Dillaha (Dillaha et et ai., al., 1989), 1989), however however aa that GFS GFS could could be be used used efficiently efficiently to to trap various pollutants very behaviour in in grass. grass. The The most most detailed model very small small number number of of researches researches tried tried to to model model sediment sediment behaviour detailed model developed so far is the Kentucky model (Tollner et al., 1976, Bartield et al., 1979, Hayes et al., 1984), developed so far is the Kentucky model (Tollner et aI., 1976, Barfield et al., 1979, Hayes et al., 1984), which 70’s.It is a deterministicmodel on the the bias biasof of complex complexlaboratory laboratory which was was established established in in the the 70's. It is a deterministic model developed developed on investigations (the describedin in the appendix).Metal Metal rods usedto to mimic grass,and andinfiltration investigations (the model model is is described the appendix). rods were were used mimic grass, infiltration was In the early '80s, ‘80s the the Kentucky evaluatedon on real realgrass grassin in laboratory laboratoryand was not not studied studied at at all. all. In the early Kentucky model model was was evaluated and field (Hayeset 1984)with mix success. success.However, However, no applicationof of the the model modelhas has been been field (Hayes et al., al., 1984) with a a mix no further further application recorded in literature. modelCREAMS CREAMS was wasalso alsoused for prediction predictionof of sediment sedimentdeposition recorded in literature. The The rural rural runoff runoff model used for deposition in GFSwith with a success (Flanagan et al., al., 1989). 1989). in GFS a rather rather poor poor success (Flanagan et A investigationof of sediment in runoff over grass grasssurfaces surfacesis is undertaken at the University of of A new new investigation sediment behaviour behaviour in runoff over undertaken at the University Aberdeen. the project. project. The The experimental experimentalpart part of of the the study study was was Aberdeen. This This paper paper summarises summarises the the first first phase phase of of the carried out in the Fluids the Kentucky Kentucky model. model.An attempt carried out in the Fluids laboratory. laboratory. The The gathered gathered data data were were used used to to test test the An attempt was made to develop a new simplified model for assessment of sediment deposition in non-submerged was made to develop a new simplified model for assessment of sediment deposition in non-submerged overland over grass, grass,when no infiltration andgrass grassbending bendingare overland flow flow over when no infiltration and are allowed. allowed. LABORATORY LABORATORY EXPERIMENTS EXPERIMENTS In of the artificial grass grass was wasallowed. allowed.Only In the the first first phase phase of the investigation, investigation, artificial was used used and and no no infiltration infiltration was Only nonnonsubmerged and steady-state flow was studied. submerged and steady-state flow was studied. Experimentalurocedure Experimental procedure A 12.5 m long and 0.3 m wide flow channel,with adjustableslope,was adaptedfor the study (Fig. 1). A 12.5 m long and OJ m wide flow channel, with adjustable slope, was adapted for the study (Fig. I). Artificial grasswasgluedon varnishedmarineplywood boards.6 grassboards,with the following lengths: Artificial grass was glued on varnished marine plywood boards. 6 grass boards, with the following lengths: 0.7,0.8, 1.5,2.2,2.4, and2.4 m, wereplacedin a row on the channelbottomandthen fixed, forminga 10m 0.7,0.8, 1.5,2.2,2.4, and 2.4 m, were placed in a row on the channel bottom and then fixed, forming a 10 m long strip.The joints betweenthe boardsweremadeasFig. 1 shows(Cross-section 6) in orderto minimise long strip. The joints between the boards were made as Fig. I shows (Cross-section 6) in order to minimise sedimentmigrationbeneaththeboards.A 1.2m long metaltray wasplacedin front of the first grassboard. sediment migration beneath the boards. A 1.2 m long metal tray was placed in front of the first grass board. Isokinetic samplerswere developedfor samplingat intervals along the grassstrip for quantificationof Isokinetic samplers were developed for sampling at intervals along the grass strip for quantification of particulateconcentrationandsizedistribution.They wereconstructedto siphonwaterandsedimentfrom the particulate concentration and size distribution. They were cOfiStrocted to siphon water and sediment from the flow. Two setsof the samplers wereconstructed;with 10mm highorifice for higherflow rates,andwith 5 flow. Two sets of the samplers were constructed; with 10 mm high orifice for higher flow rates, and with 5 mm high orifice for low flow rates.The samplers arepositionedaccordingto Fig. 1. mm high orifice for low flow rates. The samplers are positioned according to Fig. I.
A tine silt wasusedafter it hadbeensievedthrougha 750 p sieve(the mediandiameterwasabout50 1). It Il sievethe (theparticle mediandensity diameter was about 50 Il). It A fine silt wasin used afterestuary it had been sieved through a 750 was collected a local at different occasions therefore, and distribution were was collected in abulk. localWater estuary atmixed different therefore, thethroughout particle density and distribution were different for each was withoccasions sediment in a big tank the experiment andpumped different for eachvia bulk. Water placed was mixed with sediment in a allowed big tank uniform throughout the experiment and pumped into thechannel a diffuser on the metal tray. This inflow of the sediment into the into the channel via a diffuser placed on the metal tray. This allowed uniform inflow of the sediment into that the channel.During the experiments, a pondformedon the tray, which simulatedvery well thenaturalpond channel. During experiments, a pond on the tray, which simulated very well the natural pond that forms in front of the natural grassfilter stripsformed duringstorms. forms in front of natural grass filter strips during storms.
131 131
Sediment strips Sediment behaviour behaviour in in grass grass filter filter strips
Experiments Experiments were were performed performed in the following following manner. Clean water water was was run with with a constant constant flow flow rate through the grass in order order to set the isokinetic isokinetic samplers. Firstly, flow velocity velocity was was determined between between through Firstly, mean flow grass blades using dye. Secondly, the ends of of the sampler sampler tubes (Fig. (Fig. 1) I) were were placed at appropriate heights matching inflow inflow velocity velocity into into the samplers samplers with with the measured velocity velocity in the grass. Then, the flow flow was was stopped and stopped and sediment sediment mixed mixed with with water water in in the the tank tank for for lo-15 10-15 minutes. minutes. The The mixture mixture was was pumped pumped with with the the same constant constant flow flow rate during during the whole whole experiment. experiment. Flow Flow depth was was measured in the grass. Samples of of sediment of the strip, at sediment and and water water were were taken taken at at the the diffuser, diffuser, Tom from each each sampler, sampler, and and at at the the end end of the grass grass strip, at the the following after the experiment: 5, 15, 30,45 and of the the experiment: 5, 15,30,45 and 60 60 minutes. minutes. The The flow flow was was stopped stopped following times times after the beginning beginning of and samples and the the grass grass boards boards washed washed in in order order to to measure measure deposition deposition between between the the samplers. samplers. The The collected collected samples were were analysed analysed for for sediment sediment concentration concentration and and particle particle size size distribution. distribution. The The sediment sediment concentration concentration was was determined by evaporating evaporating water water from from the the samples samples and and measuring measuring the the sediment sediment residue, residue, while while aa Malvem Malvern determined by particle size analysis. particle sizer sizer was was used used for for particle particle size analysis.
CROSS-SECTION CROSS-SECTION 66
tank:
12.5m CHANNEL: 0.3m O.3m xx 12.Sm Plan view
manometer
water mixed with silt
wbeT\ rli~:-q,ter surface I !!r ~:~;;lumpllt=:::>Q!E.=ssJi!~--lh~os:e~~ ; plywoo
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Figure Figure 1. 1. Experimental Experimental apparatus. apparatus.
The are presented 1. The The experimental experimental variables variables are presented in in Table Table 1. The channel channel slope slope was was 22 % % for for all all experiments, experiments, while while two different grass densities, and two different sediment types were tested. Sediment and water input rates two different grass densities, and two different sediment types were tested. Sediment and water input rates were sedimentinflow were in in the the range range of of values values found found in in urban urban areas areas (Deletic (Deletic et et al., ai., 1997). 1997). This This meant meant that, that, the the sediment inflow rates were far below values studied in the previous works (Hayes et al., 1984). The experiments carriedout rates were far below values studied in the previous works (Hayes et ai., 1984). The experiments carried out with more densegrassare markedas A experimentsand the experimentswith lessdensegrassas B with more dense grass are marked as A experiments and the experiments with less dense grass as B experiments(Table 1). The length of grassbladeswas 2.56 cm for A experimentsand 3 cm for B experiments (Table 1). The length of grass blades was 2.56 cm for A experiments and 3 cm for B experiments. experiments. Table 1.Experimentalvariables(channelslopewas2% for all experiments) Table 1. Experimental variables (channel slope was 2% for all experiments)
Experiment Experiment
Al Al A2 A2 A3 A3 A4 A4 A5 A5 A6 A6 A7 A7 A8 A8 A9 A9 Bl Bl B2 B2 B3 B3 B4 B4
Grassdensity Grass densitl, [&etches/cm ] [stetches!cm ] 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.10 1.10 1.10 1.10 1.10 1.10 1.10 1.10
Sedimentdensity, Flow rate, Measuredflow Meansedimentinput Sediment density, Flow rate, Measured flow Mean sediment input concentration[g/l] E[kg/m31 Q dep% Q Wml [lIsm] depth, h h bl [cm] m3 concentration [gil] 2750 0.667 2.4 0.67 2750 0.667 2.4 0.67 2750 0.667 2.4 1.53 2750 0.667 2.4 1.53 2750 0.667 2.4 2.7 2750 0.667 2.4 2.7 2750 0.333 1.4 2.35 2750 0.333 1.4 2.35 2750 0.333 1.4 1.51 2750 0.333 1.4 1.51 2750 0.333 1.4 0.65 2750 0.333 1.4 0.65 2750 0.217 0.5 1.35 2750 0.217 0.5 1.35 2229 0.200 0.5 1.86 2229 0.200 0.5 1.86 2229 0.200 0.5 0.96 2229 0.200 0.5 0.96 2750 0.333 1.1 0.97 2750 0.333 1.1 0.97 2750 0.333 1.0 1.64 2750 0.333 1.0 1.64 2750 0.167 0.8 1.17 2750 0.167 0.8 1.17 2750 0.167 0.8 1.51 2750
0.167
0.8
1.51
A. DELETIC DELETIC A.
132 132
Exnerimental observations observations Experimental It was was intended intended to simulate simulate steady-state steady-state input input of of solids solids into into the grass, however however this this was was never never fully fully achieved. achieved. It The mixer mixer was powerful enough enough to keep keep bigger bigger particles particles in suspension suspension during during the experi.ments experiments with with high high The was not not powerful sediment inflows, inflows, and and a certain certain decrease decrease of of sediment sediment input input was was noticed noticed during during these these experiments. experiments. However, However, sediment sediment deposition deposition in the pond pond in in front front of of the grass, which which could could not be controlled controlled at any any time, time, always always sediment caused unsteady unsteady input input into into the grass. caused The deposition deposition front, front, that was was explained explained by by the developers developers of of the Kentucky Kentucky model model (Tollner (Tolhrer et al., al., 1976, The Barfield et al., al., 1979, 1979, Hayes Hayes et er al., al., 1984), 1984), was was not not very very prominent. prominent. The The first first 30 30 cm cm of of the the grass grass trapped trapped the the Barfield largest amount amount of of sediment sediment (Fig. (Fig. 2.b), 2.b), however however no no substantial substantial change change was was recorded recorded in in the the flow flow depth depth or or bed bed largest slope even even at at the the beginning of the the strip. strip. This This could could be be explained explained by by low low sediment sediment input input rates. rates. slope beginning of 160I=-;:::::===~-I---
160
loo Recorded in grass so.J-J=~==::j~~=:!-:..._- section: 9lJ -1st- 1 s t (O.3m) (0.3m) 60 60 --•--2thi(O.4m)
100
Recorded at
--Input 140 140 HI1-'--_----.J.-+---- --0--0.3 m .. 0.7m
120 120
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70 70
-
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20
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0 0
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50
150
100
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Psttkle % Particle size [mk] [mic]
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50
$.
-6th (4.6m)
.. . . .. . . .. .
loo 100 Particle size [II&] Particle size [mic]
150
150
b) b)
200
zw
Figure 2. Data A3. a) a) The of the concentration, SS, SS, with with particle particle sizes Figure 2. Data recorded recorded during during Experiment Experiment A3. The change change of the sediment sediment concentration, sizes in the samples collected after 30 min. b) The change of the sediment deposition measuredbetween two samplers in the samples collected after 30 min. b) The change of the sediment deposition measured between two samplers with with size. size.
1200
r;:======:::::;-i--i- Recorded at Frac\.tion 20-60 m ic
Ii
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I
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400 200
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4 x [m] ’ Time 4 ’ b) 4 X [m] 6 Time [min] [min] a) b) Figure 3. The change of the sediment fiaction concentration recorded during A3 experiment with: a) time for Figurefraction 3. The change of the sediment fraction concentration recorded during A3 experiment with: a) time for 20-60 p and b) grass length calculated as average over the experiment for four fractions. fraction 20-60 J.l and b) grass length calculated as average over the experiment for four fractions.
lo
10
The change in concentration of sediment in flow was plotted against sediment size and distance from the The beginning change in concentration of sediment flow for wasthe plotted against sediment and distance from2b). the strip (Fig. 2a). Similar plots wereinmade sediment washed from size the grass boards (Fig. stripconcentrations beginning (Fig.of 2a). were made for the sediment washed grass boards (Fig. 2b). The four Similar sedimentplots fractions: g-6,6-20,20-60 and 60-l 80 l.tfrom were the calculated in each sample The their concentrations fourstudied. sediment 6-20,fraction 20-60 and 60-180 lJ were in each sample and behaviour ofwas Thefractions: change 9-6, in each concentration was calculated plotted against time and and their studied. Theobtained change showed in eachthe fraction concentration was plotted against time and grass lengthbehaviour (Fig. 3). was The first results expected trends: grass length (Fig. 3). The first results obtained showed the expected trends:
133 133
Sediment Sediment behaviour behaviour inin grass grass filter filter strips strips
1) 1) Sediment Sediment concentration concentration in in flow flow decreases decreases with with grass grass length, length, and and the the highest highest disposition disposition isis at at the the beguming ofthe the grass grass strip. strip. beginning of 2) of the the strip strip while while smaller smaller particles particles travel travel longer. longer. Therefore, Therefore, the the 2) Large Large particles particles settle settle in in the the first first part part of majority majority of of trapped trapped particles particles are are bigger bigger particles particles (Fig (Fig 2b), 2b), while while aa big big proportion proportion of of particles particles less less than than 66 pIl isis not not trapped trapped at at all all (Fig. (Fig. 3b). 3b). 3) 3) Concentrations Concentrations along along grass grass strip strip are are changing changing very very slowly slowly even even when when sediment sediment inputs inputs change change rapidly rapidly (Fig of the the process process isis rather rather slow. slow. However However aa small small increase increase was was (Fig 3a). 3a). This This means means that that the the dynamic dynamic of noticed noticed in in concentrations concentrations of of particles particles above above 20 20 l.t Il with with time, time, even even for for decreasing decreasing input input concentrations concentrations (Fig (Fig 3a). 3a). Because Because of of trend trend (3), (3), for for this this stage stage of of the the investigation, investigation, itit was was suggested suggested that that the the process process will will be be regarded regarded as as quasi quasi steady-state steady-state and and data data for for each each point point along along the the strip strip will will be be derived derived as as average average over over an an experiment. experiment. This This approach approach was was used used to to generate generate graphs graphs such such as as the the one one presented presented in in Fig. Fig. 3b 3b for for experiment experiment A3. A3. From From these these graphs it was concluded that the concentration of each fraction decreases exnonentiallv with graphs it was concluded that the concentration of each fraction decreases exponentially with the the grass grass distance distance until until itit reaches reaches aa constant constant value. value. The The rate rate of of the the decrease decrease and and the the constant constant value value depend depend on on particle particle size and density, and flow depth and velocity. size and density, and flow depth and velocity. KENTUCKY
MODEL
KENTUCKY MODEL
The Kentucky model is presented in the appendix. It was used to calculate trapping efftciency in the studied The Kentucky model is presented in the appendix. It was used to calculate trapping efficiency in the studied 10 m long grass strip, using the following assumptions: (1) the process was regarded as steady-state; (2) only 10 m longA.5 grass(zone strip,D)using following (1) the process was regarded as steady-state; (2) only Equation was the used; (3) theassumptions: model is applied for each of the fractions studied. The second Equation (zone bearing D) was inused; thenomodel is applied for each fractionsand studied. assumptionA.5 is made mind(3)that distinctive sediment front of wastheobserved that forThe longsecond grass assumption is made bearing in mind that no distinctive sediment front was observed and that for long strips the front will have a very small influence on the effective length of the strip (a relative error willgrass be stripssmall). the front have atrapping very small influenceTr,,,, on is the effectivefor length the strip calculated eachof fraction as,(a relative error will be very Thewill measured efficiency, very small). The measured trapping efficiency, Trm, is calculated for each fraction as, Tr
m
= 4mi - 4mo
(1)
(1)
4mi
where,qmi- measuredincomingload of the fraction per unit channelwidth [g/sm], and q, - measured where, qrni - measured incoming load of thewidth fraction per at unit width outgoing load of the fraction perunit channel [p/sm] thechannel endof the strip.[glsm] , and qrno - measured outgoing load of the fraction per unit channel width [glsm] at the end of the strip.
The measured andpredictedtrappingefftcienciesarepresentedin Fig. 4 for the full lengthof the strip and thestrip. strip The and The measured and predicted trapping are presentedgrossly in Fig. the 4 for the full length all fractions studied. It is obvious thatefficiencies the modelover-predicts efficiency of the of grass all fractionsbetween studied. Itmeasured is obvious that the model over-predicts grosslyhigh the efficiency the grassItstrip. The differences and calculated values areparticularly for the tineofparticles. wasalso differencesthat between measuredofand values are particularly highversion for the presented fine particles. It wasetalso concluded an application thecalculated full Kentucky model (unsteady-state in Hayes al., concluded that application of thesubstantially. full Kentucky model (unsteady-state version presented in Hayes et al., 1984)would notanchange thisresult 1984) would not change this result substantially.
-1- -
~
0.8
.~
i j
0.6 0.4
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~
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!/
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a0 a Figure 4. Measured
/
/'1
0.2
Trapped 0.2
.,/
/
,.
I
~.!! l! ~
~,g
'1
1Kentucky model: ./
/~
/1
.Fraction:
~
0-6mic / 6-20 mic .l / 0 20-60 mic 60-180 mic 0.4 - -0.6 - Line of0.6equivalence1 I - measured, Trm rh] 0
•
0.4
0.6
0.8
and predicted trapping- measured, efficiency inTrm the rio] 10 m long artificial Trapped
grass strip.
Figure 4, Measured and predicted trapping efficiency in the 10m long artificial grass strip.
It is believed that differencesin the Kentucky experiments(Tollner et al., 1976) and the Aberdeen experimentscausedsuch a big discrepancybetweenthe modelledand measuredresults.The Kentucky It is believed that differences in the Kentucky experiments (Tollner et al., 1976) and the Aberdeen modelwas developedusingmetal roadsthat were placedat l-l.5 cm distances,while the more dense experiments caused such a big discrepancy between the modelled and measured results. The Kentucky artificial grasswasusedin the Aberdeenexperiments.The flow depthswere muchhigherin the Kentucky
model was developed using metal roads that were placed at 1-1.5 cm distances, while the more dense artificial grass was used in the Aberdeen experiments. The flow depths were much higher in the Kentucky
A. DELETIC A. DELETK
134 134
experiments (due to the media media difference) difference) and sediment and and water water inflow higher then experiments (due and the sediment inflow rates were were also higher then in the Aberdeen Aberdeen experiments. experiments. The The Kentucky Kentucky model not been tested before model has not been tested before for for the the range range of of flow flow and and sediment characteristics characteristics that usually occur in urban urban areas. Nevertheless, Nevertheless, it has not sediment that usually occur in not been been verified verified fully fully for for grass filter filter strips used in rural areas. strips used in rural
DEVELOPMENT NEW MODEL MODEL DEVELOPMENT OF OF A A NEW An attempt made to develop predict sediment sediment deposition deposition in in grass. In In the first stage of of the An attempt is made develop a new new model mOdel to predict the first model so-called “filtration” of the model model was was established. established. No No infiltration infiltration or or grass model development, development, a so-called "filtration" component component of bending therefore the “filtration” had to be as simple simple as as possible. possible. bending are modelled, modelled, therefore "filtration" component component had ItIt was that the trapping efficiency, Tr,, following: was speculated speculated that trapping efficiency, Tr,. depends depends on the following:
(2) (2)
Tr=fi(x,q,b,n,So,p,d,,p,) Tr = !i(x, q, b, n, So, p, d p , Ps)
where, length of [m], q flow rate per width of of the strip strip [1Ism], [Ysm], b - spacing spacing between between where, x -- length of the grass strip strip [m], g -- flow per unit unit width the grass of spacings per width of the the strip strip [m"], [m-l], So So - channel channel grass blades blades [ml, [m], n - number number of spacings between between grass blades blades per width of 3 Equation 2 slope, [kgim3],3], dd,,p -- particle particle diameter and pS particle density density [kg/m [kg/m3]. diameter [m], [m], and p, -- particle ]. Equation 2 slope, pp -- water water density density [kg/m could could be be written written in in aa more more concise concise way, way, Tr = f2(x, V, k V V,)s )= = fdN,,Tr= hex, V,h, h(N!)1
(3) (3)
where, V velocity [mls] [m/s] and depth [m] [m] are are functions functions of of g, q, b, 6, nn and andSo, So,and andV V,s is is the the where, V -- mean mean flow flow velocity and hh -- flow flow depth Stokes’ that is is aa function function of of p, p, ddp, and pS. These four variables can be grouped into one nonStokes' settling settling velocity velocity that and Ps. These four variables can be grouped into one non, p dimensional particle falling falling number, number, Nh Nf, dimensional value value called called particle N . _ xVs j -
(4) (4)
hV
According the measured measured trapping efficiencies, Tr,,,, calculated for for each each sampling sampling point point along along According to to Eq. Eq. 1, I, the trapping efficiencies, Trm . were were calculated the grass strip and each fraction (qso was the outgoing load measured at that point). The corresponding the grass strip and each fraction (gso was the outgoing load measured at that point). The corresponding particle were calculated at the same points (X = 0.3, 0.7, 1.5, 3, 5.2 and 10 m). In this particle falling falling numbers, numbers, Nh Nf' were calculated at the same points (x = 0.3, 0.7, 1.5, 3, 5.2 and 10 m). In this way, 24 pairs of Tr,,, and N/were obtained for for each Flow velocity, velocity, V, V, was was assessed assessed as: as: way, 24 pairs of Tr and Nfwere obtained each experiment. experiment. Flow m
v=-& V=-.!L
(5) (5)
nbh
In both Eq. 4 and Eq. 5, h was the measured ilow depth. In both Eq. 4 and Eq. 5, h was the measured flow depth. + Trm - A experiments Trm - B experiments Trm - B experiments
l
•
Tr - calculated
-
'#.
I
Tr= {TanH [1og(Nf)-O.92]+1}/2 Experiments A: RA2=O.84 Experiments B: RA 2=O.92
0.80
. '0.60
Q.
l!!
+
I-
+ + +
:? Figure 5. Trapping efficiency as a function of particle falling number, h” Figure 5. Trapping efficiency as a function of particle falling number, Nf .
log Nf
135 135
Sediment in grass Sediment behaviour behaviour in grass filter filter strips strips
Trm is plotted against IV/ Nfas shows. The trapping trapping efficiency efficiency ranges from from 0 to I. Trm values that are Tr,,, as Fig. 5 shows. 1. The Tr, less then zero are errors, which order to demonstrate the less are obviously obviously measurement measurement errors, which have not been discarded discarded in order accuracy following curve was of the measurements. The following was fitted fitted through the measured points, points, accuracy of Ml log(Nf) +1 Tr = ~ log(Nf) -- 0.92 0.92 J~ ?L 2
(6) (6)
Tr =
The correlation coefficients The correlation coefficients were were R=0.84 R=0.84 for for experiments experiments A, A, and and R=O.92 R=0.92 for for experiments experiments B. B. Bearing Bearing in in mind large number and not was regarded very of points points and not very very high high accuracy accuracy of of the the measurements measurements this this was regarded as as aa very mind the the large number of good good agreement. agreement. CONCLUSION CONCLUSION The out in The experiments experiments on on sediment sediment trapping trapping efficiency efficiency in in grass grass were were carried carried out in the the laboratory laboratory using using artificial artificial grass. grass. No No infiltration infiltration was was allowed allowed and and only only non-submerged non-submerged flow flow was was studied. studied. The The experiments experiments were were carried carried out of non-homogenous non-homogenous silt, silt, flow flow rates rates between between out with: with: one one channel channel slope, slope, two two grass grass densities, densities, two two types types of 0.167-0.667 Vsm, and sediment input It was was observed observed that that for for particles particles less less 0.167-0.667I/sm, and sediment input loading loading rates rates between between 0.6-2.4 0.6-2.4 g/l. gil. It than efficiency (sometimes Ii, the the studied studied grass grass had had aa very very low low trapping trapping efficiency (sometimes negligible), negligible), while while aa substantial substantial than 6 6 p, part It was of all all particles particles above above 60 60 ~1 Ii were were usually usually trapped. trapped. It was also also concluded concluded that that the the concentration concentration of of each each part of fraction fraction decreases decreases exponentially exponentially with with the the strip strip length length until until itit reaches reaches aa constant constant value. value. This This means means that that after after a a certain and all certain length, length, deposition deposition stops stops and all particles particles remaining remaining in in flow flow are are carried carried downstream. downstream. The The concentration capacity of of the of remaining remaining particles particles matches matches the the transport transport capacity the flow, flow, and and depends depends on on flow flow concentration of velocity depth, and and particle velocity and and depth, particle size size and and density. density. The Kentucky model 10 m long grass strip. long grass strip. The The calculated calculated trapping trapping efficiencies efficiencies were were far far The Kentucky model was was tested tested for for aa 10m above above the the measured. measured. This This was was particularly particularly pronounced pronounced for for small small particles, particles, where where the the measured measured efficiencies efficiencies were 0.98. It It was was concluded concluded that that the the Kentucky Kentucky model model can can not not predict predict were below below 0.3, 0.3, and and the the predicted predicted above above 0.98.
trapping
of the the studied studied conditions. conditions. trapping efficiency efficiency for for any any of
AA new attempt was made to develop a simple model for prediction of sediment trapping in non-submerged new attempt was made to develop a simple model for prediction of sediment trapping in non-submerged flow when no infiltration is allowed. A very simple relationship (equation 6) is proposed between the flow when no infiltration is allowed. A very simple relationship (equation 6) is proposed between the trapping efficiency and particle fall number. The accuracy of the proposed equation is satisfactory according trapping efficiency and particle fall number. The accuracy of the proposed equation is satisfactory according to the coefficients
of correlation
between
measured
and predicted
trapping
efficiencies.
to the coefficients of correlation between measured and predicted trapping efficiencies.
In future work, a third grass density will be studied. The influence of pre-deposited sediment in grass will be In future work, a third grass density will be studied. The influence of pre-deposited sediment in grass will be also studied (clean water was run over pre-deposited sediment). This will eventually conclude the laboratory also studied (clean water was run over pre-deposited sediment). This will eventually conclude the laboratory experiments and the first stage of the investigation. In the second phase it was proposed to conduct similar experiments and the first stage of the investigation. In the second phase it was proposed to conduct similar experiments on a natural turf where infiltration will be studied. Finally, banding effect of grass blades should experiments on a natural turf where infiltration will be studied. Finally, banding effect of grass blades should be studied and incorporated in the model. be studied and incorporated in the model.
REFERENCES
REFERENCES
Barfield,
B. J., TolIner, E. W. and Hayes, J. C. (1979). Filtration of sediment by simulated vegetation I. Steady-state flow with Barfield, homogeneous B. J., Tollner,sediment. E. W. and Hayes, J. C.offhe (1979). of sediment by simulated vegetation I. Steady-state flow with Trunsucfions ASAEFiltration 22(3), 540-548. Transactions ofthe P. ASAE homogeneous Bertrand-Krajewski, J. sediment. L., Scrivener, 0. and Briat, (1993).22(3),540-548. Sewer sediment production and transport mode@: a literature Bertrand-Krajewski, J. L., Scrivener, and 435-460. Briat, P. (1993). Sewer sediment production and transport modelling: a literature review. J. Hydaulic Research O. 31(4), review. J Hydraulic Research 31(4),435-460. Deletic, A., Maksimovic, C., and Ivetic, M. (1997). Modelling of storm wash-off of suspended solids from impervious surfaces. J. Deletic, A., Maksimovic, C., and M. (1997). Modelling of storm wash-off of suspended solids from impervious surfaces. J Hydrmdic Research 35(I), Ivetic, 99- 119. 35(1),99-119. Hydraulic Research DiIIaha, T. A., Reneau, R. B., Mostaghimi, S. and Lee, D. (1989). Vegetative fiIter strips for agricultural non point source Dillaha, pollution T. A., Reneau, B., Mostaghimi, S. and32(2), Lee, 5D.13-5 (1989). Vegetative filter strips for agricultural non point source control. R.Transncfiom ofthe ASAE 19. Transactions ofthe ASAE 32(2),J. 513-519. pollution control. Flanagan, D. C., Foster, G. R., Heibling, W. H. and Burt, P. (1989). Simplified equations for filter strip design. Trmsacriom of Flanagan,theD.ASAE, C., Foster, R.,I-2007. Heibling, W. H. and Burt, J. P. (1989). Simplified equations for filter strip design. Transactions of 32(6), G.200 ASAE, 32(6), 2001·2007. Forth RiverthePurification Board, A Clear Future in the Forth Catchment (1994). Edinburgh. Forth River A Clear FutureR.in Ithe(1984). Forth Catchment Edinburgh. Hayes, J. C.,Purification Barifield. Board, B. J and Bamhisel, Performance (1994). of grass filters under laboratory and field conditions. Hayes, J.Transactions c., Barifield.of the B. ASAE J and Barnhisel, R. I (1984). Performance of grass filters under laboratory and field conditions. 27(5), 1321-133 1. Transactions o/the ASAE 27(5), 1321-1331. SEPA - Scottish Environmental Protection Agency, A Guide to Surface Water Best Management Practice (I 9%). Edinburgh. SEPA - Scottish Environmental Protection to Surface Water sediment Best Management Practice (1996). Edinburgh. TolIner, E. W., Barifield, B. .I., Haan, C. T. Agency, and Kao, AT.Guide Y. (1976). Suspended filtration capacity of simulated vegetation, C. T.678-682. and Kao, T. Y. (1976). Suspended sediment filtration capacity of simulated vegetation. Tollner, E. W., Barifield, B. 1., Haan, Transactions of the ASAE 19(4), Transactions ofthe ASAE 19(4), 678-682.
A.DELETIC A. DELETIC
136
J. A., and Boinla, J. V. (1993) Evaluation models. J1 Zrrigarion Irrigation and Eng. 119(4), Wu, T. H., Hall, J. Bointa, J. Evaluation of runoff runoff and and erosion erosion models. and Drainage Drainage Eng. 119(4), 364-382. 364-382.
APPENDIX
According (Tollner et al., 1976, Barfield Barfield et al., 1979, Hayes Hayes et al., al., 1984) 1984) the grass According to to the the Kentucky Kentucky model model (Tollner al., 1976, al., 1979, strip divided into into four B, C, and and D, Fig. 6 shows. shows. strip is is divided four zones: zones: A, A, B, D, as Fig. I iCi C
D
B
iAi
, , I
q,. %a II a
I
,
LL
6I a
N
x(t) X(t)
: : h
h' I+’
S,=tga S,=tga S,=tgp se=@
Figure 6: Schematic to Barfield ef al., 1979. Figure 6: Schematic of of sediment sediment deposition deposition according according to Barfield et al., 1979.
The followingis A all incomingsediment sedimentis is transported; transported;in in ~ zone B sediment sedimentis is deposited deposited The following is assumed: assumed: in in zone ~ all incoming all along the deposition front with slope corresponding to that required to yield a transport capacity between all along the deposition front with slope corresponding to that required to yield a transport capacity between zone andzone zoneC; C; in is transported transportedas asbedload; bedload;in in zone all sediment sedimentreaching reachingthe thebad is zone C C sediment sediment is zone D D all bad is zone A A and in zone trapped. trapped. The trappingefficiency efficiency is is calculated as: The trapping calculated as: Tr = -+-y,-%L$j 4s;- 4so Tr=qsi-qsO=l_qsd[1 qSd-qsO] (AI) 64.1) 4Sl qSI qsi qsd where q, - incomingsedimentload per unit channel width [g/sm], qsO - outgoing sediment load per unit where qs; - incoming sediment load per unit channel width [g/sm], qso - outgoing sediment load per unit channel andqsd· qsd- total total sediment sedimentload loadtransported transportedimmediately immediatelydownstream downstream of the the deposition deposition channel width width [gLsm], [g/sm], and of wedge [g/sm] wedge [g/sm]. The sedimentloadsarecalculatedusingthe following equations:
The sediment loads are calculated using the following equations:
X(t)=2(qsi-qSd)t (A2) 64.2) PsbgSe where,X(t) - lengthof the front, t - time after beginningof the flow, & - bulk densityof depositedsediment where, X(t) -length of the front, t· time after beginning of the flow, Psb - bulk density of deposited sediment acceleration[m/s2],S,- slopeof the front (calculatedasshownin Barfield et aI., 1979). 3 kh31, [g/m ] , gg -- gravity gravity acceleration [mls2], Se- slope of the front (calculated as shown in Barfield et al., 1979).
ZoneB:
Zone Zone C: C:
!(
I
1) d
qsd = Psv Ps P- g p
3
[
l.08 ScRs (Ps I p-l)d
]3.571 p
64.3)
(A.3)
where,p - densityof water [g/m3], 3 ps- densityof particles[g/m3], d,, - particle diameter[ml, S, - channel density hydraulic of water [g/m ], ps - density of particles [g/m\ dp - particle diameter [m], Sc - channel where,R,p -- spacing slope, radius [m] calculatedas, slope, R s - spacing hydraulic radius [m] calculated as,
Rs=& bh Rs=-b+2h where,b - spacingbetweentwo grassblades[m 1,h - flow depth[m]
(A.41 (A.4)
Zone D: D: Zone
(A5) (A.9
where, b· spacing between two grass blades [m], h - flow depth [m]
qsd - qso = eX [-1.05 x 1O-3(VRs ) 0.82 ( hV )0.91] P q~ v L~
where, V - meanflow velocity [m/s], Vs - terminalsettlingvelocity of particles(Stokes’velocity) [m/s], v where, V· viscosity mean flow [mls], Vs - terminal velocity of particles (Stokes' velocity) [mls],strip vkinematic of velocity the water sediment mixturesettling [m2/s], L =L~x(t)effective lengthof grassfilter 2 kinematic viscosity of the water sediment mixture [m /s], L =Lr-X(t)effective length of grass filter strip [ml, Lr - total length of grass filter strip. [m], L T • total length of grass filter strip.
Pergamon Pergamon
Wat. Sci. Tech. Vol. No. 9, pp. 129-136, 1999 Wat. Sci. Tech. Vol. 39, 39, No.9, 129-136, 1999 Q 1999IAWQ 1999 IAWQ ©
Published Science Ltd Ltd Published by by Elsevier Elsevier Science Printed in Great Great Britain. Britain. All All rights rights reserved reserved Printed 0273-1223&J $20.00 + 0.00 0.00 0273-1223/99 $20.00 +
PII: SO273-1223(99)00225-5 PH: S0273-1223(99)00225-5
SEDIMENT BEHAVIOUR IN SEDIMENT BEHAVIOUR IN GRASS FILTER FILTER STRIPS STRIPS GRASS Ana Deletic Ana Deletic Department of Engineering, University of Aberdeen, King’s College, Fraser Noble Department ofEngineering, University ofAberdeen, King's College, Fraser Noble Building, 3UE, UE, UK UK Building, Aberdeen, Aberdeen, AB24 AB24 3
ABSTRACT ABSTRACT Sediment in non-submerged non-submerged overland flow flow over over grass in aa laboratory. Artificial turf turf Sediment transport transport was was studied studied in overland grass in laboratory. Artificial (a&o-w was used simulate natural no infiltration infiltration was allowed allowed at this stage stage of of the the (astro-turf) was used to to simulate natural grass grass and and no was at this investigation. for different different grass densities, flow rates, sediment sediment inflows, inflows, and and investigation. Experiments Experiments were were conducted conducted for grass densities, flow rates, sediment tbat concentration of sediment sediment in in runoff runoff decreases decreases exponentially exponentially with the the sediment types. types. ItIt was was observed observed that concentration of with distance and reaches asymptotically constant value. value. Measured sediment deposition deposition was was compered with the the distance and reaches asymptotically aa constant Measured sediment compered with results calculated calculated by al., 1976). 1976). The The model the results by the the Kentucky Kentucky model model (Tollner (Tollner et et aI., model over-predicted over-predicted grossly grossly the trapping efficiency of all particle fractions, but it is unreliable particularly for small particles. A new trapping efficiency of all particle fractions, but it is unreliable particularly for small particles. A new simplified relationship was established between particle fall number, Nf, and percentage of particles trapped simplified relationship was established between particle fall number, Nf, and percentage of particles trapped in the grass. The relationship should be verified on natural grass before it is used in practice. Finally, in the grass. The relationship should be verified on natural grass before it is used in practice. Finally, infiltration of water and particles should be studied on natural turf, as well as, influence of grass blades infiltration of water and particles should be studied on Datural turf, as well as, influence of grass blades bending, before the complex model of sediment behaviour in grass is established. 0 1999 IAWQ Published bending, before the complex model of sediment behaviour in grass is established. © 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved by Elsevier Science Ltd. All rights reserved KEYWORDS
KEYWORDS
Grass filter strips; lawns; sediment; storm runoff; swales; water quality.
Grass filter strips; lawns; sediment; stonn runoff; swales; water quality.
INTRODUCTION INTRODUCTION Numerous studies showed that life in urban streams could be heavily damaged due to runoff from urban Numerous studies showed that life in urban streams could be heavily damaged due to runoff from urban areas (Forth River Purification Board, 1994). Techniques to reduce the impact of polluted urban runoff areas (Forth River Purification Board, 1994). Techniques to reduce the impact of polluted urban runoff discharges have been developed recently and collectively form a range of Best Management Practices discharges have been developed recently and collectively fonn a range of Best Management Practices (BMPs). These techniques deal with the problem by reducing quantity of runoff and slowing its velocity to (BMPs). These techniques deal with the problem by reducing quantity of runoff and slowing its velocity to allow pollutant settlement. Grass (turf) was extensively used in BMPs. Grass swales and grass filter strips allow pollutant settlement. Grass (turf) was extensively used in BMPs. Grass swales and grass filter strips (GFS) have been recognised as good management practices for localised containment of pollutants in urban of pollutants in urban (GFS) been recognised as good management for localised containment areas inhave association with suspended solids, e.g. practices heavy metals and organics. Unfortunately, only crude in association with suspended solids, e.g. heavy metals and organics. Unfortunately, only crude areas guidelines exist for their construction or implementation (SEPA, 1996).
guidelines exist for their construction or implementation (SEPA, 1996).
The sediment is the most important non-point pollutant in terms of mass. Besides its total discharge, it is
Besides are its total discharge, it is The sediment is thesediment most important pollutant in chemicals terms of mass. important to assess particle non-point size distribution, since and nutrients primarily associated important to assess sediment particle size distribution, since chemicals and nutrients are primarily associated with the erosion of the fine particles. The reliability of present models of sediment transport in runoff over with the erosion the fine The deterministic reliability of models present models of sediment transport in runoff rural areas is veryofpoor (Wu,particles. 1993), and of sediment discharge from urban areasover are of sediment urban areasofarea ruralyet areas poor (Wu, 1993), and deterministic models not fullyis very developed (Bertrand-Krajewski et al., 1993, Deletic, 1997).discharge Therefore,from development not yet fully developed (Bertrand-Krajewski et al., 1993, Deletic, 1997). Therefore, development of a 129 129
A. DELETIC A.DELETIC
130 130
for prediction transport by by overland flow will contribute reliable model for prediction of of sediment transport flow over grassed areas areas will highly and rural water highly to further further development of of both urban and water quality quality models.
The amount of of sediment trapped in, or released from, grass depends on two two processes occurring at different different processes occurring transformations in grass during dry dry weather, and sediment behaviour in runoff time scales: sediment transformations weather, and runoff during wet weather. slow biochemical process, however however the amount of of sediment trapped in the wet weather. The first first process is aa slow grass changes dramatically during storm storm events. The second process dramatically during process is therefore more important for assessment of release from grassed areas, areas, and and thus the the aim of of the work work currently currently of pollution pollution deposition and release carried out at at the University of Aberdeen Aberdeen is is to investigate sediment sediment behaviour behaviour in in runoff. runoff. This This is is a physical University of physical process where “filter”, and the the transport capacity of the overland flow flow should should be be studied studied as as aa where grass acts as aa "filter", transport capacity of the complex (1) sediment type: particle diameter and and density; (2) flow flow depth and complex function function of of the following: following: (l) velocity; and slope of of soil; (5) velocity; (3) (3) length and of grass; (4) (4) type and condition of (5) grass characteristics: characteristics: density, dimensions of grass grass blades; (6) (6) the the amount amount of of sediment sediment already trapped in in the grass. grass. dimensions and bending of A that there there is dearth of of research in this this area, area, so so far. far. Qualitative Qualitative studies studies showed showed research in A literature literature study study showed showed that is aa dearth that trap sediment sediment and and various pollutants (Dillaha (Dillaha et et ai., al., 1989), 1989), however however aa that GFS GFS could could be be used used efficiently efficiently to to trap various pollutants very behaviour in in grass. grass. The The most most detailed model very small small number number of of researches researches tried tried to to model model sediment sediment behaviour detailed model developed so far is the Kentucky model (Tollner et al., 1976, Bartield et al., 1979, Hayes et al., 1984), developed so far is the Kentucky model (Tollner et aI., 1976, Barfield et al., 1979, Hayes et al., 1984), which 70’s.It is a deterministicmodel on the the bias biasof of complex complexlaboratory laboratory which was was established established in in the the 70's. It is a deterministic model developed developed on investigations (the describedin in the appendix).Metal Metal rods usedto to mimic grass,and andinfiltration investigations (the model model is is described the appendix). rods were were used mimic grass, infiltration was In the early '80s, ‘80s the the Kentucky evaluatedon on real realgrass grassin in laboratory laboratoryand was not not studied studied at at all. all. In the early Kentucky model model was was evaluated and field (Hayeset 1984)with mix success. success.However, However, no applicationof of the the model modelhas has been been field (Hayes et al., al., 1984) with a a mix no further further application recorded in literature. modelCREAMS CREAMS was wasalso alsoused for prediction predictionof of sediment sedimentdeposition recorded in literature. The The rural rural runoff runoff model used for deposition in GFSwith with a success (Flanagan et al., al., 1989). 1989). in GFS a rather rather poor poor success (Flanagan et A investigationof of sediment in runoff over grass grasssurfaces surfacesis is undertaken at the University of of A new new investigation sediment behaviour behaviour in runoff over undertaken at the University Aberdeen. the project. project. The The experimental experimentalpart part of of the the study study was was Aberdeen. This This paper paper summarises summarises the the first first phase phase of of the carried out in the Fluids the Kentucky Kentucky model. model.An attempt carried out in the Fluids laboratory. laboratory. The The gathered gathered data data were were used used to to test test the An attempt was made to develop a new simplified model for assessment of sediment deposition in non-submerged was made to develop a new simplified model for assessment of sediment deposition in non-submerged overland over grass, grass,when no infiltration andgrass grassbending bendingare overland flow flow over when no infiltration and are allowed. allowed. LABORATORY LABORATORY EXPERIMENTS EXPERIMENTS In of the artificial grass grass was wasallowed. allowed.Only In the the first first phase phase of the investigation, investigation, artificial was used used and and no no infiltration infiltration was Only nonnonsubmerged and steady-state flow was studied. submerged and steady-state flow was studied. Experimentalurocedure Experimental procedure A 12.5 m long and 0.3 m wide flow channel,with adjustableslope,was adaptedfor the study (Fig. 1). A 12.5 m long and OJ m wide flow channel, with adjustable slope, was adapted for the study (Fig. I). Artificial grasswasgluedon varnishedmarineplywood boards.6 grassboards,with the following lengths: Artificial grass was glued on varnished marine plywood boards. 6 grass boards, with the following lengths: 0.7,0.8, 1.5,2.2,2.4, and2.4 m, wereplacedin a row on the channelbottomandthen fixed, forminga 10m 0.7,0.8, 1.5,2.2,2.4, and 2.4 m, were placed in a row on the channel bottom and then fixed, forming a 10 m long strip.The joints betweenthe boardsweremadeasFig. 1 shows(Cross-section 6) in orderto minimise long strip. The joints between the boards were made as Fig. I shows (Cross-section 6) in order to minimise sedimentmigrationbeneaththeboards.A 1.2m long metaltray wasplacedin front of the first grassboard. sediment migration beneath the boards. A 1.2 m long metal tray was placed in front of the first grass board. Isokinetic samplerswere developedfor samplingat intervals along the grassstrip for quantificationof Isokinetic samplers were developed for sampling at intervals along the grass strip for quantification of particulateconcentrationandsizedistribution.They wereconstructedto siphonwaterandsedimentfrom the particulate concentration and size distribution. They were cOfiStrocted to siphon water and sediment from the flow. Two setsof the samplers wereconstructed;with 10mm highorifice for higherflow rates,andwith 5 flow. Two sets of the samplers were constructed; with 10 mm high orifice for higher flow rates, and with 5 mm high orifice for low flow rates.The samplers arepositionedaccordingto Fig. 1. mm high orifice for low flow rates. The samplers are positioned according to Fig. I.
A tine silt wasusedafter it hadbeensievedthrougha 750 p sieve(the mediandiameterwasabout50 1). It Il sievethe (theparticle mediandensity diameter was about 50 Il). It A fine silt wasin used afterestuary it had been sieved through a 750 was collected a local at different occasions therefore, and distribution were was collected in abulk. localWater estuary atmixed different therefore, thethroughout particle density and distribution were different for each was withoccasions sediment in a big tank the experiment andpumped different for eachvia bulk. Water placed was mixed with sediment in a allowed big tank uniform throughout the experiment and pumped into thechannel a diffuser on the metal tray. This inflow of the sediment into the into the channel via a diffuser placed on the metal tray. This allowed uniform inflow of the sediment into that the channel.During the experiments, a pondformedon the tray, which simulatedvery well thenaturalpond channel. During experiments, a pond on the tray, which simulated very well the natural pond that forms in front of the natural grassfilter stripsformed duringstorms. forms in front of natural grass filter strips during storms.
131 131
Sediment strips Sediment behaviour behaviour in in grass grass filter filter strips
Experiments Experiments were were performed performed in the following following manner. Clean water water was was run with with a constant constant flow flow rate through the grass in order order to set the isokinetic isokinetic samplers. Firstly, flow velocity velocity was was determined between between through Firstly, mean flow grass blades using dye. Secondly, the ends of of the sampler sampler tubes (Fig. (Fig. 1) I) were were placed at appropriate heights matching inflow inflow velocity velocity into into the samplers samplers with with the measured velocity velocity in the grass. Then, the flow flow was was stopped and stopped and sediment sediment mixed mixed with with water water in in the the tank tank for for lo-15 10-15 minutes. minutes. The The mixture mixture was was pumped pumped with with the the same constant constant flow flow rate during during the whole whole experiment. experiment. Flow Flow depth was was measured in the grass. Samples of of sediment of the strip, at sediment and and water water were were taken taken at at the the diffuser, diffuser, Tom from each each sampler, sampler, and and at at the the end end of the grass grass strip, at the the following after the experiment: 5, 15, 30,45 and of the the experiment: 5, 15,30,45 and 60 60 minutes. minutes. The The flow flow was was stopped stopped following times times after the beginning beginning of and samples and the the grass grass boards boards washed washed in in order order to to measure measure deposition deposition between between the the samplers. samplers. The The collected collected samples were were analysed analysed for for sediment sediment concentration concentration and and particle particle size size distribution. distribution. The The sediment sediment concentration concentration was was determined by evaporating evaporating water water from from the the samples samples and and measuring measuring the the sediment sediment residue, residue, while while aa Malvem Malvern determined by particle size analysis. particle sizer sizer was was used used for for particle particle size analysis.
CROSS-SECTION CROSS-SECTION 66
tank:
12.5m CHANNEL: 0.3m O.3m xx 12.Sm Plan view
manometer
water mixed with silt
wbeT\ rli~:-q,ter surface I !!r ~:~;;lumpllt=:::>Q!E.=ssJi!~--lh~os:e~~ ; plywoo
Q. SS
tray
•
/6
Is
•
b Izli
14
samplen
Cross-section 6
~_-_< <
.._.-
4.8m
4.8m
+__-_--._--._._~._2m_ 2.2m
1
diffusor
-_.+_--~
1.sm _'_,s.m_.
+_.. .
T .. lOUI '-"'IOm"'-----_ _
q"
0.8
I_
,0.4 p. , 1‘1
lm
Figure Figure 1. 1. Experimental Experimental apparatus. apparatus.
The are presented 1. The The experimental experimental variables variables are presented in in Table Table 1. The channel channel slope slope was was 22 % % for for all all experiments, experiments, while while two different grass densities, and two different sediment types were tested. Sediment and water input rates two different grass densities, and two different sediment types were tested. Sediment and water input rates were sedimentinflow were in in the the range range of of values values found found in in urban urban areas areas (Deletic (Deletic et et al., ai., 1997). 1997). This This meant meant that, that, the the sediment inflow rates were far below values studied in the previous works (Hayes et al., 1984). The experiments carriedout rates were far below values studied in the previous works (Hayes et ai., 1984). The experiments carried out with more densegrassare markedas A experimentsand the experimentswith lessdensegrassas B with more dense grass are marked as A experiments and the experiments with less dense grass as B experiments(Table 1). The length of grassbladeswas 2.56 cm for A experimentsand 3 cm for B experiments (Table 1). The length of grass blades was 2.56 cm for A experiments and 3 cm for B experiments. experiments. Table 1.Experimentalvariables(channelslopewas2% for all experiments) Table 1. Experimental variables (channel slope was 2% for all experiments)
Experiment Experiment
Al Al A2 A2 A3 A3 A4 A4 A5 A5 A6 A6 A7 A7 A8 A8 A9 A9 Bl Bl B2 B2 B3 B3 B4 B4
Grassdensity Grass densitl, [&etches/cm ] [stetches!cm ] 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.33 1.10 1.10 1.10 1.10 1.10 1.10 1.10 1.10
Sedimentdensity, Flow rate, Measuredflow Meansedimentinput Sediment density, Flow rate, Measured flow Mean sediment input concentration[g/l] E[kg/m31 Q dep% Q Wml [lIsm] depth, h h bl [cm] m3 concentration [gil] 2750 0.667 2.4 0.67 2750 0.667 2.4 0.67 2750 0.667 2.4 1.53 2750 0.667 2.4 1.53 2750 0.667 2.4 2.7 2750 0.667 2.4 2.7 2750 0.333 1.4 2.35 2750 0.333 1.4 2.35 2750 0.333 1.4 1.51 2750 0.333 1.4 1.51 2750 0.333 1.4 0.65 2750 0.333 1.4 0.65 2750 0.217 0.5 1.35 2750 0.217 0.5 1.35 2229 0.200 0.5 1.86 2229 0.200 0.5 1.86 2229 0.200 0.5 0.96 2229 0.200 0.5 0.96 2750 0.333 1.1 0.97 2750 0.333 1.1 0.97 2750 0.333 1.0 1.64 2750 0.333 1.0 1.64 2750 0.167 0.8 1.17 2750 0.167 0.8 1.17 2750 0.167 0.8 1.51 2750
0.167
0.8
1.51
A. DELETIC DELETIC A.
132 132
Exnerimental observations observations Experimental It was was intended intended to simulate simulate steady-state steady-state input input of of solids solids into into the grass, however however this this was was never never fully fully achieved. achieved. It The mixer mixer was powerful enough enough to keep keep bigger bigger particles particles in suspension suspension during during the experi.ments experiments with with high high The was not not powerful sediment inflows, inflows, and and a certain certain decrease decrease of of sediment sediment input input was was noticed noticed during during these these experiments. experiments. However, However, sediment sediment deposition deposition in the pond pond in in front front of of the grass, which which could could not be controlled controlled at any any time, time, always always sediment caused unsteady unsteady input input into into the grass. caused The deposition deposition front, front, that was was explained explained by by the developers developers of of the Kentucky Kentucky model model (Tollner (Tolhrer et al., al., 1976, The Barfield et al., al., 1979, 1979, Hayes Hayes et er al., al., 1984), 1984), was was not not very very prominent. prominent. The The first first 30 30 cm cm of of the the grass grass trapped trapped the the Barfield largest amount amount of of sediment sediment (Fig. (Fig. 2.b), 2.b), however however no no substantial substantial change change was was recorded recorded in in the the flow flow depth depth or or bed bed largest slope even even at at the the beginning of the the strip. strip. This This could could be be explained explained by by low low sediment sediment input input rates. rates. slope beginning of 160I=-;:::::===~-I---
160
loo Recorded in grass so.J-J=~==::j~~=:!-:..._- section: 9lJ -1st- 1 s t (O.3m) (0.3m) 60 60 --•--2thi(O.4m)
100
Recorded at
--Input 140 140 HI1-'--_----.J.-+---- --0--0.3 m .. 0.7m
120 120
'Ia; .E. 3II) II)
-·"*-·1.5m 100 _. _. _. 3 m 100 tf-'\i~'""rrJ"o,,.___--+--___:7 ---<>-- 5.2 m BO B0 #-~\-';-~:+_-.::J:L-...:*"1'1'~...u:-=---
- - - -10 m
60 BO
~ ?w
60
-·-···5th(2.2m)
%l 50 C 5 0 iE@ 40 <:I 'ij 0 a. 30
I!
40
--D--2nd (DAm) -----srd(O.sm) •• - - -3rd (O.&n) -.-x-. •. 4th 4th(1.5m) _."* (1.5m)
70 70
-
20 "--'-
20
10
0 0
0
0
0
60
0
50
150
100
2w
150
Psttkle % Particle size [mk] [mic]
4 a)
0
50
0
200
50
$.
-6th (4.6m)
.. . . .. . . .. .
loo 100 Particle size [II&] Particle size [mic]
150
150
b) b)
200
zw
Figure 2. Data A3. a) a) The of the concentration, SS, SS, with with particle particle sizes Figure 2. Data recorded recorded during during Experiment Experiment A3. The change change of the sediment sediment concentration, sizes in the samples collected after 30 min. b) The change of the sediment deposition measuredbetween two samplers in the samples collected after 30 min. b) The change of the sediment deposition measured between two samplers with with size. size.
1200
r;:======:::::;-i--i- Recorded at Frac\.tion 20-60 m ic
Ii
I\..' ....
I
-->(-
600
1.5m
................._ _-j----··-10m
~'_',. ~_.~.__ !~.__ ._ ':'::~ --.:~.J:~~
r ....-:- ..._---t ....
400
+---=---'-------=--4'''--.=oc,...;-'_ _-i--::-7-'·~·-4
200 200
+-_
0
o
IO 10
20 20
30 30
t-_-_-_'+so-1'-'_-_'_'-160 40
40
600
-
II)
._M
......... ._ •.-
Average over Experiment A31 .. 0-6 mic . <> 6-20 mic 0 2O-6Omic • 6O-180mic !
!
'a; BOO t---t-!-"'''''.......: + - - - - - - - r - - -_.-. _. 3 .mm e: 52 .E. 0" I 1"-.... ~
II) II) 600
Fractions: -
1000
- - input --D--O.3m 1000 t-----""..-------_+_ ! . - - - - - - __ • -0.7 m I
50
60
II)
1\
~~
~~"
400 200
~
~
2
I
•
-------o0 o
-exp.trend
"
I I
!
, I
I
4 x [m] ’ Time 4 ’ b) 4 X [m] 6 Time [min] [min] a) b) Figure 3. The change of the sediment fiaction concentration recorded during A3 experiment with: a) time for Figurefraction 3. The change of the sediment fraction concentration recorded during A3 experiment with: a) time for 20-60 p and b) grass length calculated as average over the experiment for four fractions. fraction 20-60 J.l and b) grass length calculated as average over the experiment for four fractions.
lo
10
The change in concentration of sediment in flow was plotted against sediment size and distance from the The beginning change in concentration of sediment flow for wasthe plotted against sediment and distance from2b). the strip (Fig. 2a). Similar plots wereinmade sediment washed from size the grass boards (Fig. stripconcentrations beginning (Fig.of 2a). were made for the sediment washed grass boards (Fig. 2b). The four Similar sedimentplots fractions: g-6,6-20,20-60 and 60-l 80 l.tfrom were the calculated in each sample The their concentrations fourstudied. sediment 6-20,fraction 20-60 and 60-180 lJ were in each sample and behaviour ofwas Thefractions: change 9-6, in each concentration was calculated plotted against time and and their studied. Theobtained change showed in eachthe fraction concentration was plotted against time and grass lengthbehaviour (Fig. 3). was The first results expected trends: grass length (Fig. 3). The first results obtained showed the expected trends:
133 133
Sediment Sediment behaviour behaviour inin grass grass filter filter strips strips
1) 1) Sediment Sediment concentration concentration in in flow flow decreases decreases with with grass grass length, length, and and the the highest highest disposition disposition isis at at the the beguming ofthe the grass grass strip. strip. beginning of 2) of the the strip strip while while smaller smaller particles particles travel travel longer. longer. Therefore, Therefore, the the 2) Large Large particles particles settle settle in in the the first first part part of majority majority of of trapped trapped particles particles are are bigger bigger particles particles (Fig (Fig 2b), 2b), while while aa big big proportion proportion of of particles particles less less than than 66 pIl isis not not trapped trapped at at all all (Fig. (Fig. 3b). 3b). 3) 3) Concentrations Concentrations along along grass grass strip strip are are changing changing very very slowly slowly even even when when sediment sediment inputs inputs change change rapidly rapidly (Fig of the the process process isis rather rather slow. slow. However However aa small small increase increase was was (Fig 3a). 3a). This This means means that that the the dynamic dynamic of noticed noticed in in concentrations concentrations of of particles particles above above 20 20 l.t Il with with time, time, even even for for decreasing decreasing input input concentrations concentrations (Fig (Fig 3a). 3a). Because Because of of trend trend (3), (3), for for this this stage stage of of the the investigation, investigation, itit was was suggested suggested that that the the process process will will be be regarded regarded as as quasi quasi steady-state steady-state and and data data for for each each point point along along the the strip strip will will be be derived derived as as average average over over an an experiment. experiment. This This approach approach was was used used to to generate generate graphs graphs such such as as the the one one presented presented in in Fig. Fig. 3b 3b for for experiment experiment A3. A3. From From these these graphs it was concluded that the concentration of each fraction decreases exnonentiallv with graphs it was concluded that the concentration of each fraction decreases exponentially with the the grass grass distance distance until until itit reaches reaches aa constant constant value. value. The The rate rate of of the the decrease decrease and and the the constant constant value value depend depend on on particle particle size and density, and flow depth and velocity. size and density, and flow depth and velocity. KENTUCKY
MODEL
KENTUCKY MODEL
The Kentucky model is presented in the appendix. It was used to calculate trapping efftciency in the studied The Kentucky model is presented in the appendix. It was used to calculate trapping efficiency in the studied 10 m long grass strip, using the following assumptions: (1) the process was regarded as steady-state; (2) only 10 m longA.5 grass(zone strip,D)using following (1) the process was regarded as steady-state; (2) only Equation was the used; (3) theassumptions: model is applied for each of the fractions studied. The second Equation (zone bearing D) was inused; thenomodel is applied for each fractionsand studied. assumptionA.5 is made mind(3)that distinctive sediment front of wastheobserved that forThe longsecond grass assumption is made bearing in mind that no distinctive sediment front was observed and that for long strips the front will have a very small influence on the effective length of the strip (a relative error willgrass be stripssmall). the front have atrapping very small influenceTr,,,, on is the effectivefor length the strip calculated eachof fraction as,(a relative error will be very Thewill measured efficiency, very small). The measured trapping efficiency, Trm, is calculated for each fraction as, Tr
m
= 4mi - 4mo
(1)
(1)
4mi
where,qmi- measuredincomingload of the fraction per unit channelwidth [g/sm], and q, - measured where, qrni - measured incoming load of thewidth fraction per at unit width outgoing load of the fraction perunit channel [p/sm] thechannel endof the strip.[glsm] , and qrno - measured outgoing load of the fraction per unit channel width [glsm] at the end of the strip.
The measured andpredictedtrappingefftcienciesarepresentedin Fig. 4 for the full lengthof the strip and thestrip. strip The and The measured and predicted trapping are presentedgrossly in Fig. the 4 for the full length all fractions studied. It is obvious thatefficiencies the modelover-predicts efficiency of the of grass all fractionsbetween studied. Itmeasured is obvious that the model over-predicts grosslyhigh the efficiency the grassItstrip. The differences and calculated values areparticularly for the tineofparticles. wasalso differencesthat between measuredofand values are particularly highversion for the presented fine particles. It wasetalso concluded an application thecalculated full Kentucky model (unsteady-state in Hayes al., concluded that application of thesubstantially. full Kentucky model (unsteady-state version presented in Hayes et al., 1984)would notanchange thisresult 1984) would not change this result substantially.
-1- -
~
0.8
.~
i j
0.6 0.4
!
~
0.2
!/
!
["./
a0 a Figure 4. Measured
/
/'1
0.2
Trapped 0.2
.,/
/
,.
I
~.!! l! ~
~,g
'1
1Kentucky model: ./
/~
/1
.Fraction:
~
0-6mic / 6-20 mic .l / 0 20-60 mic 60-180 mic 0.4 - -0.6 - Line of0.6equivalence1 I - measured, Trm rh] 0
•
0.4
0.6
0.8
and predicted trapping- measured, efficiency inTrm the rio] 10 m long artificial Trapped
grass strip.
Figure 4, Measured and predicted trapping efficiency in the 10m long artificial grass strip.
It is believed that differencesin the Kentucky experiments(Tollner et al., 1976) and the Aberdeen experimentscausedsuch a big discrepancybetweenthe modelledand measuredresults.The Kentucky It is believed that differences in the Kentucky experiments (Tollner et al., 1976) and the Aberdeen modelwas developedusingmetal roadsthat were placedat l-l.5 cm distances,while the more dense experiments caused such a big discrepancy between the modelled and measured results. The Kentucky artificial grasswasusedin the Aberdeenexperiments.The flow depthswere muchhigherin the Kentucky
model was developed using metal roads that were placed at 1-1.5 cm distances, while the more dense artificial grass was used in the Aberdeen experiments. The flow depths were much higher in the Kentucky
A. DELETIC A. DELETK
134 134
experiments (due to the media media difference) difference) and sediment and and water water inflow higher then experiments (due and the sediment inflow rates were were also higher then in the Aberdeen Aberdeen experiments. experiments. The The Kentucky Kentucky model not been tested before model has not been tested before for for the the range range of of flow flow and and sediment characteristics characteristics that usually occur in urban urban areas. Nevertheless, Nevertheless, it has not sediment that usually occur in not been been verified verified fully fully for for grass filter filter strips used in rural areas. strips used in rural
DEVELOPMENT NEW MODEL MODEL DEVELOPMENT OF OF A A NEW An attempt made to develop predict sediment sediment deposition deposition in in grass. In In the first stage of of the An attempt is made develop a new new model mOdel to predict the first model so-called “filtration” of the model model was was established. established. No No infiltration infiltration or or grass model development, development, a so-called "filtration" component component of bending therefore the “filtration” had to be as simple simple as as possible. possible. bending are modelled, modelled, therefore "filtration" component component had ItIt was that the trapping efficiency, Tr,, following: was speculated speculated that trapping efficiency, Tr,. depends depends on the following:
(2) (2)
Tr=fi(x,q,b,n,So,p,d,,p,) Tr = !i(x, q, b, n, So, p, d p , Ps)
where, length of [m], q flow rate per width of of the strip strip [1Ism], [Ysm], b - spacing spacing between between where, x -- length of the grass strip strip [m], g -- flow per unit unit width the grass of spacings per width of the the strip strip [m"], [m-l], So So - channel channel grass blades blades [ml, [m], n - number number of spacings between between grass blades blades per width of 3 Equation 2 slope, [kgim3],3], dd,,p -- particle particle diameter and pS particle density density [kg/m [kg/m3]. diameter [m], [m], and p, -- particle ]. Equation 2 slope, pp -- water water density density [kg/m could could be be written written in in aa more more concise concise way, way, Tr = f2(x, V, k V V,)s )= = fdN,,Tr= hex, V,h, h(N!)1
(3) (3)
where, V velocity [mls] [m/s] and depth [m] [m] are are functions functions of of g, q, b, 6, nn and andSo, So,and andV V,s is is the the where, V -- mean mean flow flow velocity and hh -- flow flow depth Stokes’ that is is aa function function of of p, p, ddp, and pS. These four variables can be grouped into one nonStokes' settling settling velocity velocity that and Ps. These four variables can be grouped into one non, p dimensional particle falling falling number, number, Nh Nf, dimensional value value called called particle N . _ xVs j -
(4) (4)
hV
According the measured measured trapping efficiencies, Tr,,,, calculated for for each each sampling sampling point point along along According to to Eq. Eq. 1, I, the trapping efficiencies, Trm . were were calculated the grass strip and each fraction (qso was the outgoing load measured at that point). The corresponding the grass strip and each fraction (gso was the outgoing load measured at that point). The corresponding particle were calculated at the same points (X = 0.3, 0.7, 1.5, 3, 5.2 and 10 m). In this particle falling falling numbers, numbers, Nh Nf' were calculated at the same points (x = 0.3, 0.7, 1.5, 3, 5.2 and 10 m). In this way, 24 pairs of Tr,,, and N/were obtained for for each Flow velocity, velocity, V, V, was was assessed assessed as: as: way, 24 pairs of Tr and Nfwere obtained each experiment. experiment. Flow m
v=-& V=-.!L
(5) (5)
nbh
In both Eq. 4 and Eq. 5, h was the measured ilow depth. In both Eq. 4 and Eq. 5, h was the measured flow depth. + Trm - A experiments Trm - B experiments Trm - B experiments
l
•
Tr - calculated
-
'#.
I
Tr= {TanH [1og(Nf)-O.92]+1}/2 Experiments A: RA2=O.84 Experiments B: RA 2=O.92
0.80
. '0.60
Q.
l!!
+
I-
+ + +
:? Figure 5. Trapping efficiency as a function of particle falling number, h” Figure 5. Trapping efficiency as a function of particle falling number, Nf .
log Nf
135 135
Sediment in grass Sediment behaviour behaviour in grass filter filter strips strips
Trm is plotted against IV/ Nfas shows. The trapping trapping efficiency efficiency ranges from from 0 to I. Trm values that are Tr,,, as Fig. 5 shows. 1. The Tr, less then zero are errors, which order to demonstrate the less are obviously obviously measurement measurement errors, which have not been discarded discarded in order accuracy following curve was of the measurements. The following was fitted fitted through the measured points, points, accuracy of Ml log(Nf) +1 Tr = ~ log(Nf) -- 0.92 0.92 J~ ?L 2
(6) (6)
Tr =
The correlation coefficients The correlation coefficients were were R=0.84 R=0.84 for for experiments experiments A, A, and and R=O.92 R=0.92 for for experiments experiments B. B. Bearing Bearing in in mind large number and not was regarded very of points points and not very very high high accuracy accuracy of of the the measurements measurements this this was regarded as as aa very mind the the large number of good good agreement. agreement. CONCLUSION CONCLUSION The out in The experiments experiments on on sediment sediment trapping trapping efficiency efficiency in in grass grass were were carried carried out in the the laboratory laboratory using using artificial artificial grass. grass. No No infiltration infiltration was was allowed allowed and and only only non-submerged non-submerged flow flow was was studied. studied. The The experiments experiments were were carried carried out of non-homogenous non-homogenous silt, silt, flow flow rates rates between between out with: with: one one channel channel slope, slope, two two grass grass densities, densities, two two types types of 0.167-0.667 Vsm, and sediment input It was was observed observed that that for for particles particles less less 0.167-0.667I/sm, and sediment input loading loading rates rates between between 0.6-2.4 0.6-2.4 g/l. gil. It than efficiency (sometimes Ii, the the studied studied grass grass had had aa very very low low trapping trapping efficiency (sometimes negligible), negligible), while while aa substantial substantial than 6 6 p, part It was of all all particles particles above above 60 60 ~1 Ii were were usually usually trapped. trapped. It was also also concluded concluded that that the the concentration concentration of of each each part of fraction fraction decreases decreases exponentially exponentially with with the the strip strip length length until until itit reaches reaches aa constant constant value. value. This This means means that that after after a a certain and all certain length, length, deposition deposition stops stops and all particles particles remaining remaining in in flow flow are are carried carried downstream. downstream. The The concentration capacity of of the of remaining remaining particles particles matches matches the the transport transport capacity the flow, flow, and and depends depends on on flow flow concentration of velocity depth, and and particle velocity and and depth, particle size size and and density. density. The Kentucky model 10 m long grass strip. long grass strip. The The calculated calculated trapping trapping efficiencies efficiencies were were far far The Kentucky model was was tested tested for for aa 10m above above the the measured. measured. This This was was particularly particularly pronounced pronounced for for small small particles, particles, where where the the measured measured efficiencies efficiencies were 0.98. It It was was concluded concluded that that the the Kentucky Kentucky model model can can not not predict predict were below below 0.3, 0.3, and and the the predicted predicted above above 0.98.
trapping
of the the studied studied conditions. conditions. trapping efficiency efficiency for for any any of
AA new attempt was made to develop a simple model for prediction of sediment trapping in non-submerged new attempt was made to develop a simple model for prediction of sediment trapping in non-submerged flow when no infiltration is allowed. A very simple relationship (equation 6) is proposed between the flow when no infiltration is allowed. A very simple relationship (equation 6) is proposed between the trapping efficiency and particle fall number. The accuracy of the proposed equation is satisfactory according trapping efficiency and particle fall number. The accuracy of the proposed equation is satisfactory according to the coefficients
of correlation
between
measured
and predicted
trapping
efficiencies.
to the coefficients of correlation between measured and predicted trapping efficiencies.
In future work, a third grass density will be studied. The influence of pre-deposited sediment in grass will be In future work, a third grass density will be studied. The influence of pre-deposited sediment in grass will be also studied (clean water was run over pre-deposited sediment). This will eventually conclude the laboratory also studied (clean water was run over pre-deposited sediment). This will eventually conclude the laboratory experiments and the first stage of the investigation. In the second phase it was proposed to conduct similar experiments and the first stage of the investigation. In the second phase it was proposed to conduct similar experiments on a natural turf where infiltration will be studied. Finally, banding effect of grass blades should experiments on a natural turf where infiltration will be studied. Finally, banding effect of grass blades should be studied and incorporated in the model. be studied and incorporated in the model.
REFERENCES
REFERENCES
Barfield,
B. J., TolIner, E. W. and Hayes, J. C. (1979). Filtration of sediment by simulated vegetation I. Steady-state flow with Barfield, homogeneous B. J., Tollner,sediment. E. W. and Hayes, J. C.offhe (1979). of sediment by simulated vegetation I. Steady-state flow with Trunsucfions ASAEFiltration 22(3), 540-548. Transactions ofthe P. ASAE homogeneous Bertrand-Krajewski, J. sediment. L., Scrivener, 0. and Briat, (1993).22(3),540-548. Sewer sediment production and transport mode@: a literature Bertrand-Krajewski, J. L., Scrivener, and 435-460. Briat, P. (1993). Sewer sediment production and transport modelling: a literature review. J. Hydaulic Research O. 31(4), review. J Hydraulic Research 31(4),435-460. Deletic, A., Maksimovic, C., and Ivetic, M. (1997). Modelling of storm wash-off of suspended solids from impervious surfaces. J. Deletic, A., Maksimovic, C., and M. (1997). Modelling of storm wash-off of suspended solids from impervious surfaces. J Hydrmdic Research 35(I), Ivetic, 99- 119. 35(1),99-119. Hydraulic Research DiIIaha, T. A., Reneau, R. B., Mostaghimi, S. and Lee, D. (1989). Vegetative fiIter strips for agricultural non point source Dillaha, pollution T. A., Reneau, B., Mostaghimi, S. and32(2), Lee, 5D.13-5 (1989). Vegetative filter strips for agricultural non point source control. R.Transncfiom ofthe ASAE 19. Transactions ofthe ASAE 32(2),J. 513-519. pollution control. Flanagan, D. C., Foster, G. R., Heibling, W. H. and Burt, P. (1989). Simplified equations for filter strip design. Trmsacriom of Flanagan,theD.ASAE, C., Foster, R.,I-2007. Heibling, W. H. and Burt, J. P. (1989). Simplified equations for filter strip design. Transactions of 32(6), G.200 ASAE, 32(6), 2001·2007. Forth RiverthePurification Board, A Clear Future in the Forth Catchment (1994). Edinburgh. Forth River A Clear FutureR.in Ithe(1984). Forth Catchment Edinburgh. Hayes, J. C.,Purification Barifield. Board, B. J and Bamhisel, Performance (1994). of grass filters under laboratory and field conditions. Hayes, J.Transactions c., Barifield.of the B. ASAE J and Barnhisel, R. I (1984). Performance of grass filters under laboratory and field conditions. 27(5), 1321-133 1. Transactions o/the ASAE 27(5), 1321-1331. SEPA - Scottish Environmental Protection Agency, A Guide to Surface Water Best Management Practice (I 9%). Edinburgh. SEPA - Scottish Environmental Protection to Surface Water sediment Best Management Practice (1996). Edinburgh. TolIner, E. W., Barifield, B. .I., Haan, C. T. Agency, and Kao, AT.Guide Y. (1976). Suspended filtration capacity of simulated vegetation, C. T.678-682. and Kao, T. Y. (1976). Suspended sediment filtration capacity of simulated vegetation. Tollner, E. W., Barifield, B. 1., Haan, Transactions of the ASAE 19(4), Transactions ofthe ASAE 19(4), 678-682.
A.DELETIC A. DELETIC
136
J. A., and Boinla, J. V. (1993) Evaluation models. J1 Zrrigarion Irrigation and Eng. 119(4), Wu, T. H., Hall, J. Bointa, J. Evaluation of runoff runoff and and erosion erosion models. and Drainage Drainage Eng. 119(4), 364-382. 364-382.
APPENDIX
According (Tollner et al., 1976, Barfield Barfield et al., 1979, Hayes Hayes et al., al., 1984) 1984) the grass According to to the the Kentucky Kentucky model model (Tollner al., 1976, al., 1979, strip divided into into four B, C, and and D, Fig. 6 shows. shows. strip is is divided four zones: zones: A, A, B, D, as Fig. I iCi C
D
B
iAi
, , I
q,. %a II a
I
,
LL
6I a
N
x(t) X(t)
: : h
h' I+’
S,=tga S,=tga S,=tgp se=@
Figure 6: Schematic to Barfield ef al., 1979. Figure 6: Schematic of of sediment sediment deposition deposition according according to Barfield et al., 1979.
The followingis A all incomingsediment sedimentis is transported; transported;in in ~ zone B sediment sedimentis is deposited deposited The following is assumed: assumed: in in zone ~ all incoming all along the deposition front with slope corresponding to that required to yield a transport capacity between all along the deposition front with slope corresponding to that required to yield a transport capacity between zone andzone zoneC; C; in is transported transportedas asbedload; bedload;in in zone all sediment sedimentreaching reachingthe thebad is zone C C sediment sediment is zone D D all bad is zone A A and in zone trapped. trapped. The trappingefficiency efficiency is is calculated as: The trapping calculated as: Tr = -+-y,-%L$j 4s;- 4so Tr=qsi-qsO=l_qsd[1 qSd-qsO] (AI) 64.1) 4Sl qSI qsi qsd where q, - incomingsedimentload per unit channel width [g/sm], qsO - outgoing sediment load per unit where qs; - incoming sediment load per unit channel width [g/sm], qso - outgoing sediment load per unit channel andqsd· qsd- total total sediment sedimentload loadtransported transportedimmediately immediatelydownstream downstream of the the deposition deposition channel width width [gLsm], [g/sm], and of wedge [g/sm] wedge [g/sm]. The sedimentloadsarecalculatedusingthe following equations:
The sediment loads are calculated using the following equations:
X(t)=2(qsi-qSd)t (A2) 64.2) PsbgSe where,X(t) - lengthof the front, t - time after beginningof the flow, & - bulk densityof depositedsediment where, X(t) -length of the front, t· time after beginning of the flow, Psb - bulk density of deposited sediment acceleration[m/s2],S,- slopeof the front (calculatedasshownin Barfield et aI., 1979). 3 kh31, [g/m ] , gg -- gravity gravity acceleration [mls2], Se- slope of the front (calculated as shown in Barfield et al., 1979).
ZoneB:
Zone Zone C: C:
!(
I
1) d
qsd = Psv Ps P- g p
3
[
l.08 ScRs (Ps I p-l)d
]3.571 p
64.3)
(A.3)
where,p - densityof water [g/m3], 3 ps- densityof particles[g/m3], d,, - particle diameter[ml, S, - channel density hydraulic of water [g/m ], ps - density of particles [g/m\ dp - particle diameter [m], Sc - channel where,R,p -- spacing slope, radius [m] calculatedas, slope, R s - spacing hydraulic radius [m] calculated as,
Rs=& bh Rs=-b+2h where,b - spacingbetweentwo grassblades[m 1,h - flow depth[m]
(A.41 (A.4)
Zone D: D: Zone
(A5) (A.9
where, b· spacing between two grass blades [m], h - flow depth [m]
qsd - qso = eX [-1.05 x 1O-3(VRs ) 0.82 ( hV )0.91] P q~ v L~
where, V - meanflow velocity [m/s], Vs - terminalsettlingvelocity of particles(Stokes’velocity) [m/s], v where, V· viscosity mean flow [mls], Vs - terminal velocity of particles (Stokes' velocity) [mls],strip vkinematic of velocity the water sediment mixturesettling [m2/s], L =L~x(t)effective lengthof grassfilter 2 kinematic viscosity of the water sediment mixture [m /s], L =Lr-X(t)effective length of grass filter strip [ml, Lr - total length of grass filter strip. [m], L T • total length of grass filter strip.