Ems Resubmit V3 No Track Changes New

8/9/2019 Ems Resubmit V3 No Track Changes New

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Journal: Environmental Modelling & SoftwareType of paper: Short communicationDate: June 16, !1"#er$ion: v%D': 1!(1!16)*(env$oft(!1"(!+(!!6ote: Su-mitted ver$ion

Rapid setup of hydrological and hydraulic models using OpenStreetMap and theSRTM derived digital elevation model

J( Schelle.en$ a,-,1, /(J( 0rol$ma a, /(J( Dahm a, (#( Donchyt$ a,c, 2(3( 4in$emiu$ a

aDeltare$, 0ou$$ine$5weg 1, 6 2# Delft, the etherland$- 3ritical 7one 2ydrology roup, #8 8niver$ity, De 0oelelaan 1!9+, 1!91 2#, m$terdam, the etherland$c3ivil Engineering and eo$cience$, Delft 8niver$ity of Technology, Stevinweg 1, 69 3, Delft, theetherland$

Abstract $tepwi$e procedure ha$ -een developed in ;ython to e for hydrological and hydraulic model$ u$ing e( The tool$ are developed in ;ython, an

interactive, o-*ect@oriented, e in

com-ination with DC, a geo$patial data a-$traction li-rary =http:))www(gdal(org> and

;3/a$ter, a li-rary for the development of environmental model$ =http:))www(pcra$ter(eu>(

1 Corresponding author: J. Schellekens, Deltare$, /otterdam$eweg 19%, 6 2D Delft, the etherland$,

;hone: 199%9, ?a


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1. Introduction

2ydrological and hydraulic model$ often rely on land cover map$ to determine $urface

model parameter$( 'mproving tho$e map$, $pecifically the placement and amount of paved

area G which generate$ a large proportion of 5uic. runoff G and water -odie$, can ultimatelylead to -etter hydrological model$( ?urthermore, hydraulic and hydrological model$ are

$trongly dependent on the 5uality of elevation data =$ee e(g( Sander$, !!+>( Trend$ in data

$haring activitie$ li.e Cand$at 9 =http:))land$at(u$g$(gov)land$at9(php>, penTopography

=http:))opentopography(org>, and 3H =http:))c.an(org)in$tance$> have opened new

po$$i-ilitie$ for rapid $etup of hydrological and hydraulic model$ in the la$t decade( Satellite

data provide$ information on a glo-al $cale that i$ con$i$tent in $pace although they u$ually

re5uire comple< algorithm$ for e


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$upplement other data $ource$( The rationale -ehind the automated procedure i$ that it

provide$ a mean$ to rapidly $etup $uita-le -uilding -loc.$ for hydrological and hydraulic

model$ from glo-al and freely availa-le data( The procedure i$ te$ted for ro-u$tne$$ -y

applying it on $everal location$ and catchment$ of different $iIe world@wide(

'n $ection we pre$ent the procedure while $ection focu$$e$ on application$ in Europe

South Ea$t $ia and Ea$t frica and on different hydrological $cale$( Section " provide$ a

di$cu$$ion on the developed approach and $ection % pre$ent$ our main conclu$ion$ and

idea$ for future re$earch(

2. Methods

'n $hort, the procedure fir$t clip$ a region of intere$t from an SM file, create$ $hape

file$ from $elected feature$ and u$e$ the$e to create gridded map$ with fraction of paved

area, fraction of open water and fraction of unpaved area in each cell( Thi$ information can

-e u$ed directly -y di$tri-uted hydrological model$ that operate on a grid or aggregated to

larger area$ for the u$e in lumped or $emi di$tri-uted model$( The tool$ furthermore

automatically download elevation data from the Shuttle Topography /adar Mi$$ion, which

can $u-$e5uently -e u$ed in con*unction with SM river reache$ to e$ta-li$h a $ound river

networ. topology with connection node$ and profile$ for 1D hydraulic modelling, a$ well a$ a

filtered elevation map for D inundation modelling( The procedure ha$ -een pac.aged in a

free and open@$ource li-rary written in ;ython called Ao$mhydroB(

'n more detail the developed method in Ao$mhydroB to e:

1. 3ut@out a $pecific region for the model from the downloaded SM file =o$mconvert, a

$tandard tool which we u$e unaltered and availa-le through

http:))wi.i(open$treetmap(org)wi.i)$mconvert>

2. 3onvert the SM file to a $et of polygon and line $hape file$ and filter for relevant land

u$e$ =ogrogr, part of the DC li-rary>

3. 3onvert the $hape file$ to a $et of two re$olution grid$ going from high to low to -e a-le

to get a fraction in each cell in the final grid$( =gdalLden$ity(py, a wrapper around

gdalLra$teriIe>( 0y default the high@re$olution grid$ cell $iIe i$ 1)1! of the final

re$olution(

4. ;erform correction$ on the grid$ =normaliIe> and $hape$ and merge the grid$ to the final

land cover product$ =o$mhydro(py>

3
http://wiki.openstreetmap.org/wiki/Osmconverthttp://wiki.openstreetmap.org/wiki/Osmconvert


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Figure 1 Flow chart of the steps taken to derive land use (and specifically paved area fraction) maps

from OSM.

'n $ome area$ the different land u$e =C8> polygon$ in SM nearly cover the whole area(

$ $uch, the C8 polygon$ derived from SM can -e u$ed to generate the paved, unpaved

and water covered area map$ we are aiming to derive( 2owever, in mo$t area$ the polygon

coverage i$ =very> incomplete( ?rom vi$ual in$pection it appear$ that road$ =line element$>

are mapped more fre5uently in SM than polygon feature$ of paved area$( Therefore, we

have u$ed road den$ity a$ an e


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Two other map$ are al$o created, one repre$enting the fraction of unpaved land u$e and

one repre$enting the fraction of open water( The fraction unpaved i$ derived from polygon$

that repre$ent AgreenB area$( The open water fraction map i$ derived from a com-ination of

all waterway$ in SM, ta.ing into account the river width if it i$ availa-le, and land u$e

cla$$ified a$ water( The com-ined water map$ are a$$igned a ma !

meter elevation map =Jarvi$ et al(, !!9>( Such land$cape feature$ are e$$ential to include in

hydraulic inundation model$ a$ they may -loc. flood$ and reroute water in other direction$(

The $tep$ to produce the $ound drainage networ. and the $moothed elevation map are a$

follow$:

1. S/TM data i$ downloaded for the u$er@defined target area( Tile$ are automatically

merged and the e


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6. gridded drainage networ. i$ prepared -y including all river $ection$ that have a

Strahler order a-ove a u$er@defined thre$hold( 'n each con$idered pi( The u$er mu$t provide an e$timate of the

width)depth ratio, yearly average and -an. full flow at the outlet of the catchment(

The channel geometrie$ are $caled to the whole drainage networ. -a$ed on

up$tream area and local $lope of each up$tream pi and rural area$ =Cimpopo delta

3hao ;hraya -a$in>, $ee Ta-le 1( ?or the fir$t four ca$e $tudie$, paved@area fraction$ were

e$ta-li$hed(

6


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Tale 1 !ase studies used in this research

o !ase Area "#m$% !ountry

1 Meu$e -a$in ,"6! ?rance, 0elgium, the etherland$

2o 3hi Minh 3ity province ,11% #ietnam

rnhem %+ The etherland$" Stamford "(6 Singapore

% Cimpopo -a$in "1%,!!! MoIam-i5ue =only down$tream area i$con$idered>

6 3hao ;hraya -a$in 16!,!!! Thailand =area up$tream of 0ang.o.>

$how$ $catter plot$ of $patially averaged paved@area fraction$ of local data $ource$, a$

compared to SM@-a$ed paved@area fraction$( ?or the Meu$e -a$in =upper@left> we

compared our re$ult$ with the 3orine data $et =0o$$ard et al(, !!!> acro$$ a $u-divi$ion of

thirteen $u-@catchment$( 'n the proce$$ing $tep$ an intermediate re$olution of 1!!, we calculated the paved fraction -a$ed on road

and -uilding den$ity( The$e value$ have -een compared to the original detailed data from

the Dutch 3ada$tre and the 3orine land cover data( 2ere, our method generally

overe$timate$ the paved fraction( The main rea$on$ for thi$ are the e$timation of the map

average road width$, which in reality differ$ -etween neigh-ourhood$ and the $implification

of $eparate hou$e$ to -uilding -loc.$ in SM in thi$ region( The lower part of =lower@left:

Singapore, lower@right: 23M3> $how$ an evident undere$timation of SM derived paved

fraction land u$e in compari$on to C8 map$ of local government$ in Singapore and 23M3(

The difference$ -etween the European ca$e$ and the South Ea$t $ian ca$e$ demon$trated

that large $patial varia-ility of the completene$$ of SM coverage( The SM derived paved

area in Singapore and 23M3 i$ clearly undere$timated while the compari$on with 3orine in

Europe $how$ that SM can -e fairly accurate compared to traditional data $ource$( 't i$

difficult to determine whether SM ha$ more active contri-utor$ in Europe or that high data

den$ity i$ due to ma$$ import of pu-lic and private data$et$( ?or e


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policy, while in !!+ utomotive avigation Data =D> added it$ road networ. to SM

=http:))wi.i(open$treetmap(org)wi.i)DLData>(

'n our $tudy we have $et the road den$ity thre$hold over which we a$$ume the area i$

ur-an, to the 9th percentile( Thi$ value wor.ed well in all ca$e$ we inve$tigated although for

2i 3hi Minh 3ity a lower value th> gave -etter re$ult$( Thi$ $how$ that thi$ value

influence$ the amount of paved area detected con$idera-ly and care mu$t -e ta.en to $elect

the value( $ an e(
http://wiki.openstreetmap.org/wiki/AND_Datahttp://wiki.openstreetmap.org/wiki/AND_Data


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Figure " !omparison of percentage paved area per su#catchment in OSM (y#a$is) and land use data

($#a$is). %pper left& Meuse asin' OSM compared to the !orine data set. %pper right& rnhem (the

etherlands)' OSM compared to the ational *oint +arge Scale Standard Map (http&,,www.gkn.nl,).

+ower left& Stamford catchment (Singapore)' OSM compared to land use map of the local

government. +ower right& -o !hi Minh !ity province (ietnam)' OSM compared to the land use map

of the local government. Su#catchment areas are aout /.1km"' 1km"' 0/km" and "///km" for

rnhem' Singapore' -i !hi Minh !ity and the Meuse catchment respectively.

!


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Figure . Sensitivity of parameter that determines over which the road density indicates an area is to

e treated as uran. The area shown is -o !hi Minh !ity. Four different values of the threshold are

investigated& the 23th' 24th' 25thand the 2"ndpercentile.

more detailed analy$i$ around the citie$ of Ciege and Cu


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included while in the SM derived map the paved fraction at thi$ $cale for the large road$ i$

fre5uently a-ove !(%( 3om-ining -oth data $ource$ may provide the -e$t re$ult$ although

thi$ mu$t -e done with care given the large $patial variation in coverage and accuracy(

Figure 5 6$ample of the area around +iege with a particularly poor OSM coverage. 7aved area

determined from !orine (top left)' paved area as estimated from OSM coverage indicating paved land

use (top right)' paved land use estimated from road density (ottom left) and a merger of the two

OSM#derived estimates

11


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Figure 0 7aved area fraction for the +u$emourg area at 1//$1//m resolution derived from !orine

(top) and OSM (ottom). The road network is shown as an overlay.

The la$t two ca$e$ =Cimpopo and 3hao ;hraya> were u$ed to demon$trate the derivation

of map layer$ for hydraulic modelling( ?igure 6$how$ the effect of applying the tool$ for the

elevation model to the Cimpopo delta, MoIam-i5ue( Ma*or road$ a$ well a$ $econdary road$

have -een elevated in the S/TM coverage over the Cimpopo( n e


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converted into a $hapefile( The topology of thi$ river networ. wa$ then u$ed to derive lateral

inflow and confluence point$( The re$ulting networ. and lateral inflow$ are $hown in ?igure

+c(

Figure 4 6levation data from S8TM over the +impopo delta. +eft& 6levation data without OSM

treatment. 8ight& elevation data with OSM treatment. The road network is now clearly visile in the

elevation model

Figure 9. Step#wise derivation of drainage network in the lower !hao 7hraya 8iver from OSM. a) the

raw OSM waterways. This figure shows all waterways availale in OSM. ) :aterways with the OSM

tag waterway=river. These are filtered out from a). c) derived sound drainage network' to e used

13


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$ for the derivation of hydraulic model element$, $ome limitation$ are that we do not

account for the fact that elevated feature$ are not completely impermea-le due to the

pre$ence of culvert$ and fly@over$, and the fact that our algorithm to derive river networ.$

can only provide for converging river networ.$( 'n diverging area$ =e(g( in wetland$ and delta

area$> thi$ may re$ult in limitation$ in the networ. and $ome re5uirement for manual

correction of the topology of the river networ.( 't $hould al$o -e noted that the S/TM data

ha$ it$ limitation$ for hydraulic modelling( 'n particular in hydraulically comple< area$, ur-an

area$ and region$ with den$e vegetation =$ee e(g( #aleriano et al(, !!6 4il$on et al(, !!+>

S/TM may -e prone to noi$e and $y$tematic -ia$ that need$ to -e accounted for with other

method$ than pre$ented in thi$ wor.( ?inally, penStreetMap doe$ not provide enough

information on hydraulic$ in ur-an area$ =$uch a$ ur-an drainage networ.$, $ewerage

$y$tem$, pumping $cheme$ and retention -a$in$> to complete a reali$tic $chemati$ation

within ur-an area$(

The large variation in completene$$ of SM =a$ demon$trated -y the ca$e $tudie$ in

ur-an area$ in orth 4e$t Europe and South Ea$t $ia> ma.e$ that any application of the

tool$ mu$t -e guided -y $pot chec.ing u$ing alternative data $ource$( 't al$o $ugge$t$ that

u$ing the e$timate$ from SM =that can -e detailed -ut lac. $patial con$i$tency> together

with remotely $en$ed e$timate$ =that u$ually have a much -etter $patial con$i$tency> may -e

the -e$t way forward(

Ac#nowledgements4e ac.nowledge /i*.$water$taat under the Mini$try of 'nfra$tructure and the

Environment, the etherland$ for their funding of thi$ re$earch(

References

nnoni, (, 3raglia, M(, de /oo, (, San@Miguel, J(, !1!( Earth o-$ervation$ and dynamicmapping: .ey a$$et$ for ri$. management, in: eographic 'nformation and3artography for /i$. and 3ri$i$ Management( Springer, pp( G1(

0o$$ard, M(, ?eranec, J(, tahel, J(, !!!( 3/'E land cover technical guide: ddendum!!!( European Environment gency 3openhagen(

0utler, D(, !1( 3rowd$ourcing goe$ main$tream in typhoon re$pon$e( ature(doi:1!(1!9)nature(!1(1"196

3iepluch, 0(, Jaco-, /(, Mooney, ;(, 4in$tanley, (, !1!( 3ompari$on of the accuracy ofpenStreetMap for 'reland with oogle Map$ and 0ing Map$, in: ;roceeding$ of theinth 'nternational Sympo$ium on Spatial ccuracy $$e$$ment in atural/e$ource$ and Enviromental Science$ !@rd July !1!( p( +(

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?innegan, (J(, /oe, (, Montgomery, D(/(, 2allet, 0(, !!%( 3ontrol$ on the channel widthof river$: 'mplication$ for modeling fluvial inci$ion of -edroc.( eology , G(doi:1!(11!)11+1(1

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Ems Resubmit V3 No Track Changes New