IUPWARE MAster Thesis Carlos Muñoz

8/11/2019 IUPWARE MAster Thesis Carlos Muoz

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Acknowledgements

I would like to express my sincere gratitude to my promoter Prof. dr. ir. Patrick Willems for valuable

suggestions and guidance in this thesis and during the whole academic year.

I would also like to thank my advisor dr. ir. Lipen Wang for his permanent availability and valuable

comments and advises during the development of this Master thesis.

My sincere gratitude and admiration for each of my classmates. I have learned from them and I have

always received good advises and encouragement during all this time.

Remember all the staff of IPW!R" Master Programme# for this special academic year spent in $elgium.

$esides# I would like to thank the %lemish !&uafin Water 'ompany for providing the radar and rain gauge

series.

(pecial thanks to !melia and )offre# thanks for your support and invaluable help. !nd one last personal

comment# I will always be deeply thankful to all my family members to bring me up in humility values.

'arlos Mu*o+# (eptember ,-/


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TABLE OF CONTENTS I01R23'1I20 .......................... ...................... ............................ ................... ............................... ..

. Problem 3efinition ........................... ...................... ............................ ................... ...................

., Main 2b4ectives .......................... ...................... ............................... ................... ...................... ,

.5 1hesis (ummary ......................... ....................... ........................... ...................... ...................... 5

, R!I0%!LL M"!(R"M"01( ......................... ......................... ........................... .................... ............. 5

,. 1ypes of Precipitation ....................... ...................... ............................ ................... ................... 5

,., 1ipping $ucket Rain 6auges ...................... ............................ ..................... .......................... ..... 7

,.,. Working principle of the tipping bucket rain gauge .......................... .................... ............. 7

,.,., ncertainties in rain gauge measurements. ........................ ........................... ................... 7

,.5 Weather Radars .......................... ...................... ............................... ................... ...................... 8

,.5. Working principle ......................... ......................... ........................... .................... ............. 8

,.5., Radar e&uation ........................... .......................... ........................... .................... ............. 9

,.5.5 1ypes of radar ........................... ...................... ............................ ................... ................... :

,.5./ (patial and temporal resolution in weather radars. .......................... .................... ...........

,./ L!WR ;


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8. Duality !nalysis Results !nd 3iscussions. ........................ ............................ .................... ........ ,8

8., Linear Regression Method Results and 3iscussions ..................... ........................... ................. 5-

8.5 Marshall EPalmer Paramenters 'alibration Method....................................... ................... ...... 5,

8./ FG< 'alibration MethodH Results !nd 3iscussion. ........................... .......................... ................ 55

8./. (patial resolution influence. ...................... ............................ .................... ...................... 5:

8./., 'lutter influence .......................... ......................... ........................... ............................ ... /-

8./.5 'overed area influence ...................... ........................... ........................ ....................... ... /5

8././ Maximum intensities # total amount of rainfall and duration influence .......................... . /5

9 '20'L(I20( !03 R"'2MM"03!1I20( ......................... ............................ ................... .............. /8

9. 'onclusions ........................... ................... ............................ ................... ............................... /8

9., Recommendations !nd %uture Work ......................... ............................ ................... .............. /?

? R"%"R"0'"( ............................ ...................... ............................ .................... ........................... ...... /:

0ielsen# ).".# )ensen# 0.".# Rasmussen# M.R.# ,-5a. 'alibrating L!WR weather radar using laser

disdrometers. !tmospheric Research# ,, 87


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%ig 8.9 Range dependent curve for the 'alibration %actor to be applied to radar correction. .......... 5

%ig 8.? Radar and rain gauge rain rates time series for W/ Gauge for the event of 0th,une.............. 5

%ig 8.: #ccumulation radar and gauge rainfall curves after applying correction 1 $th,une ............. 57

%ig. 8.-#ccumulation radar and gauge rainfall curves after applying correction 1 '*th ,une .......... 58

%ig 8. Radar and gauge rain rates time series G and linear regression method :th)une ................. 59

%ig 8., Radar and gauge rain rates time series for 5 of the gauges during the event of -th )une .... 5?

%ig 8.5 "ffect of applying the filter algortihm in the accumulated map of )une .......................... ...... /,

%ig 8./ Snapshot of the $thevent of ,une ttenuation issue............................................................. /7

LIST OF TABLES

1able ,. dB/ scale for weather radar&. ............................................................................................ :

1able ,., Weather radar types ...................................................................................................... -

1able ,.5 L#WR city radar technical characteristics. ........................................................................ ,

1able 5. Characteristics of Leuven rain gauges& . ........................................................................... ?

1able 7. 2vents during ,une (*'+ and mean characteristics . ......................................................... ,5

1able 8. FaH values after applying calibration method during the events of )une ,-/. .................. 5,

1able 8., FbH values after applying calibration method during the events of )une ,-/. .................. 551able 8.5 G values during the events of )une ,-/ for an spatial resolution of ,7 meters. ............ 5/

1able 8./ 'oefficient of determination values during the events of )une ,-/ JJJJJJJJJJJ. 5/

1able 8.7 G values for an spatial resolution of ,7- m during the events of )une ,-/ ..................... /-

1able 8.8 G values after applying clutter filter during the events of )une ,-/. ............................... /,

1able 8.9 1otal average area covered during the event# K respect the total covered by the radar.. /5

1able 8.? Maximum intensities at every gauge during each of the events . .......................... ........... //

1able 8.: Total rainfall accumulation at every gauge during each of the events . ........................ ... //


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Abstract

Rainfall estimation is a driving force in the field of hydrology in general and urban hydrology in particular.

Rain observations are used in hydrological applications as main inputs in the hydrologic


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1he results of the static calibration method showed a large variability in the parameters involved and no

tendency was found on them. %actor that might influence on the results obtained were analy+ed and some

recommendation were given in order to faces the challenges of the L!WR radar for the Leuven case study

in future works.

Keywords urban hydrology# radar# rainfall spatial variability# radar


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vii

List of Symbols

!D!%I0 %lemish !&uafin Water 'ompany

'% 'oefficient factor lineal calibration method

3MI 3anish Meteorological Institute

3R2 3igital 2utputs Radar

3( 3iestestraat Rain 6auge

3(3 3rop (i+e 3istribution

"@ "gen@ovestraat Rain 6auge

6L" 6eneralised Likelihood ncertainty "stimation methodology for L!WR data calibration

@6 @ogeebeek Rain 6auge

IPW!R" Inter


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1111 INTRODUCTIONINTRODUCTIONINTRODUCTIONINTRODUCTION

1.1

Problem Definiion

Rainfall measurements is one of the most important topics in the field of urban hydrology. It is a very

dynamic variable and therefore# knowledge of its spatio


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!s it has been stated before# rain gauges have been used over the years and can certainly meet with the

temporal re&uirements but not with the spatial re&uirements unless a dense rain gauge network is

available# which can lead to unaffordable economic and maintenance costs.

It is here where the radar comes into play# and although it cannot replace the accuracy provided by a rain

gauge# it is considered as a good complement to know better the spatial and temporal variations on rainfall

events and improve the data input used in modelling. A"infalt et al ,--/C.

In this study# a specific ;


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1.' T(esis S)mm#ry

(& Rainfall measurements3 6ives some theoretical background about rainfall estimation# working principle

of weather radars and main differences between them# giving also the main characteristic of the L!WR

radar.

.& Leuven case study3 3escribes the case study under study.

+& Review of different calibration methods3 'overs a review of different calibration method related with

the methodology used in this study.

)& 4ethodology3 3escribes the methodology used and explains the calibration methods for the radar data

correction.

0& Results and discussion 3iscusses the results obtained.

- &Conclusions and recommendations 'onclusions about the different approaches are given as well as

some recommendations for future work for this particular case study.

?. References

2222

RAINFALLMEASUREMENTSRAINFALLMEASUREMENTSRAINFALLMEASUREMENTSRAINFALLMEASUREMENTS

Rainfall is one of the main processes in the hydrological cycle and a driving force in urban hydrology field.

It is crucial thus# to estimate it as accurate as possible when urban models are used for different

applications such as sewer system designs or flood prevention structures.

Rainfall can be measured in different ways being time and space accuracy difficult to achieve. In this section

two main measuring instrument are discussed Athe tipping bucket rain gauge and the weather radarC along

with its possible uncertainties and challenges.

!.1 Ty*es of Pre%i*i#ion

Precipitation is an atmospheric phenomenon that starts with the condensation of steam contained in

clouds. It can fall in li&uid Arain and dri++leC or solid phase Ahail# snow# ice needles# graupel and sleetC.

Precipitation can be classified as orographic# convective or stratiform.


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2rographic precipitation is caused when a moist mass of air find an orographic obstacle# and ascend

upwards in such a way that the air expands and cools forming clouds that eventually can produce rain

events.

nlike orographic events# convective precipitations typically happen in flat or not high topographically

developed areas. 1hey occur when moist air rises by temperature differences due to local heating. 1hus#

the warm air becomes less dense starting to rise and forming vertical clouds AcumulonimbusC when it

reaches condensation levels# leading to rain and thunderstorms.

(tratiform precipitation are produced when two masses of air which have different characteristics Adensity#

moisture and temperatureC contact each other AfrontC in such a way that one layer of air it is forced over

the other. If the warm and moist layer is moving towards the cold air# the moist air rises over the cold air

creating clouds which might release rain. 1his phenomenon is called warm front and precipitation occurs

close to the front. !lternatively# it can happen that the cold mass moves towards the warm air Acold frontC

pushing it up and causing heavy rain and thunderstorm.

Fig.2. 5escribes the formation process of convective 6Strahler and Strahler! (**( and stratiform rainfall

events &Source 6www&ucar&edu&

It is worth noting that convective precipitations are generally more intense than stratiform but shorter in

time and with a high variability of intensities during the event A@ou+e# ::5# pp. :9


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!.! Ti**in+ B)%,e R#in G#)+es

2.2.1 Workingprincipleoftetipping!"cketr#ing#"ge

1he most used techni&ue for measuring rainfall is the rain gauge and specially the tipping bucket A1$R6sC

rain gauge type due to its easy working principle.

!s can be seen in the figure ,., the 1$R6 consist in a funnel that leads the collected water to a small

triangular double bucket Ametal or plasticC with a hinge at its midpoint. It is a system balance which varies

with the amount of water in the buckets. 1he rotation is produced when the bucket reaches a certain

amount of water# generally -., mm emptying the full bucket# while the other begins to fill. 1his movement

is recorded and therefore precipitation intensities can be computed.

1here are 1$R6s that can make the measurement even in case of snow events since the funnel is e&uipped

with a thermal resistance# which turn the snow into water.

Fig. 2.2 Working principle of a TBRG 6Wheatershack&com

!s it was mentioned above# the volume of water needed to tip it is generally , mm and this is denoted as

the resolution of the rain gauge. 1he way of registering the tips will influence on the rainfall rate

measurements leading to a certain advantages and disadvantages which will be discuss in the section ,.,.,.

2.2.2 Uncert#intie$inr#ing#"ge%e#$"re%ent$.

Measurements on rain gauges are sub4ected to uncertainties originated from errors during the

registrations. 1hese uncertainties can come either from the environmental conditions or the device itself.

Regarding the environmental conditions and according to WM2# losses might be produced by # the effect

of the wind which can lead to underestimations up to ,K


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/KC # by wetting on internal parts of the device and by splash


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When the electromagnetic wave from the radar is intercepted by a target# part of it is scattered in all

directions in a manner that a fraction is reflected back toward the radar and captured by the receiver#

which is normally located in the same antenna. 1he distance to the target is calculated by recording the

elapsed time between the emission and the reception# taking into account that electromagnetic waves are

transmitted at the speed of light. 1he working principle is shown in the figure ,.5.

Fig. 2.!Working principle of a weather Radar 6Cain! (**(

2.&.2 R#'#re("#tion

What the antenna records is actually the energy reflected back in the direction of the radar by the droplets

located within a certain volume Asee figure ,./C. 1hat energy# which is measured in the form of power# can

be expressed as

= .|| . A,.CWhere

Pr received power AWC

' radar constant

QGQ, refraction index.Adepend on the type of precipitationC

r distance from the radar to the target AmC

B radar reflectivity value Amm8Om5C


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Fig. 2." Scanned volume by a weather radar

1he reflectivity/is defined as the sum of the diameters of the droplets to the power of six contained within

a volume# i.e.

= A,.,C5iis the diameter of the raindrop in the volume 7. 1he reflectivity is an indirect measure of the rain rate.

(upported by experimental data it was found that the relationship between the two variables usually

responds to the following potential function

= . A,.5Cwhere Raccounts for the rain rate. 1he values of a and bdepend on drop si+e distribution A3(3C and

conse&uently on the type of storm that befalls. 1herefore the local conditions of the place where the radar

is working will lead to different values of the parameters. 1he relationship between Rand / was first

established by Marshall and Palmer in :/? with a ,-- and b .8# which in the following years it has

been the most used relation in this field for stratiform precipitation. Probert


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a larger concentration in space. Meanwhile# for the case of thunderstorm the opposite occurs since the

raindrops are bigger in average but with smaller concentrations.

(everal authors defend that in places where rainfall events are often a mixture of all types of rain# the

initial relation of Palmer and Marshall is the most appropriate. AMilan Slek et al# ,--/C.

1herefore# it seems that an accurate estimation of the precipitation with radar needs the use of a dynamic

relation in the Marshall and Palmer e&uation. @owever# in reality it is more common to use a fixed /


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Table 2.2 Weather radar types&

!s main concept# radars with higher wave lengths and low fre&uencies produce stronger signals# having a

larger measurement range capacity but re&uiring bigger and expensive antennas. (


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2.&.* Sp#ti#l#n'te%por#lre$ol"tionin+e#terr#'#r$.

In order to obtain better estimates of rainfall# the radar must provide an ade&uate spatio


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modelC AL!WR 'RC# A3@I#,--C. 1he model used in the study area is the L!WR 'R# whose technical

specifications are shown in the next table.

Table 2.!L#WR City Radar technical characteristics&

Parameter 'ity


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fact that the wide opening angle of the beam results in an increase of the volume targeted# which in turn#

depends on the range. 1his leads# for instance# to the fact that a relative small amount of rain drops can

be observed at a close range# while the same amount at further ranges# might escape to the observation

of the radar since this value would be averaged in a larger volume where no rain is present# leading thus

to values that might be below the cut


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nsamples 0umber of samples in a single scan line# typical value is ?---

X # ' "mpirical constants A.7 and ,--# respectivelyC

'lutter is defined as echoes in the radar not originated from precipitation. It is important in this case# to

keep in mind the opening of the radar beam# which deflects towards the ground# producing therefore a

fake signal called Fground clutterH. In this the Leuven case# the wall of the building where the radar is placed#

plays the role of a fence# in such a way that the lower part of the emission is cut


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reflectivity given by the disdrometers# the '


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calibration. !s a general rule# in this study area# the precipitations can be classified as convective or

stratiform. 3uring the summer convective storms predominates# while the stratiform type# usually occurs

more in winter# although the contrary is not as unusual. It might also happen that both types of events

may simultaneously occur in time A(teiner #::7C.

'.! Lo%#ion

1he chosen location for the radar installation AProvincieus building# fig. 5.,C and the reasons are specified

in the above section ,./.

Fig. !.2 a Leuven location in Belgium ! b "rovincieus building !c L#WR radar 65ecloedt!(*'(

3espite the low output power emitted# the radar is not allowed to broadcast electromagnetic waves

towards the airport direction upon the government authorities recommendation. 1he figure 5.5 illustrates

the situation.

Fig. !.! Rain gauges locations! and airport blocked beam area &Circles radius 6)! '* km L!WR

Leuven city radar.


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'.' LA-R Le)&en iy R#d#r

!s previously mentioned# the radar original intent was for marine application# this fact brings limitations

to its performance in meteorological cases. %or example# in the beginning# the outputs given by the system

did not provide reflectivity values as other types of weather radar.

1herefore# for the outputs given by the radar# the so called 3igital 2utputs Radar A3R2C the Marshall 1he green triangles represent the accumulated rainfall of the radar before calibration while the red dots the accumu

'rosses shows the gauge accumulation registrations. R,represents coefficient of determination between radar and gauge a

-.--

,.--

/.--

8.--

?.--

-.--

8O:O/ :I59 8O:O/ :I/5 8O:O/ :I/? 8O:O/ :I7/ 8O:O/ -I--

mm

Time

-3 Resol)ion 1!5 m ? 1!5 m

K @ 0!.' Dis#n%e o r#d#r @ !5!: m.

Radar accum

Rain gauge !ccum

2riginal radar !cc.

-

,

/

8

?

-.-- .-- ,.-- 5.--A%%)m)l#ed

+#)+e2mm4

A%%)m)l#

oeffi%ien of de

Resol)ion 1!5

!ccumulated rainfall

Linear A!ccumulated rainfallC

-.--

7.--

-.--

7.--

,-.--

8O:O/ :I59 8O:O/ :I/- 8O:O/ :I/5 8O:O/ :I/8 8O:O/ :I/? 8O:O/ :I7 8O:O/ :I7/

mm

Time

-B R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ 07.5 Dis#n%e o r#d#r @ !!' m.

Radar accumRain gauge !ccum2riginal radar !cc.

-

,

/

8

?

-.-- .-- ,.-- 5.-- /A%%)m

)l#ed+#)+e2mm4

A%%)m)l#e

-B oeffi%ien

Resol)ion

!cc. Rainfall

Linear A!cc. RainfallC

-.--

7.--

-.--

7.--

,-.--

8O:O/ :I5 8O:O/ :I5? 8O:O/ :I/8 8O:O/ :I75 8O:O/ -I-- 8O:O/ -I-9

mm

Time

E8 R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ '.>> Dis#n%e o r#d#r @ 5!' m.

Radar accum

Rain gauge !ccum

2riginal radar !cc.

-

7

-

7

,-

-.-- ,.-- /.-- 8.-- ?.--A%%)

m)l#ed+#)+e2mm4

A%%)m)l#

E8 oeffi%ien o

Resol)ion 1

Rainfall !cc.

Linear ARainfall !cc.C


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Fi+. 7.1:1he green triangles represent the accumulated rainfall of the radar before calibration while the red dots the accum

constant. 'rosses shows the gauge accumulation registrations. R,represents coefficient of determination between radar an

-.--

7.--

-.--

7.--

,-.--

8O-O/ I59 8O-O/ I/5 8O-O/ I/: 8O-O/ I77 8O-O/ ,I-- 8O-O/ ,I-8 8O-O/ ,I,

mm

Time

-3 Resol)ion 1!5 m ? 1!5 m

K @ 0'.>7 Dis#n%e o r#d#r @ !5!: m.

Radar accum

6auge !cc.

2riginal radar !cc.

-

,

/

8

?

-

,

-.-- ,.-- /.--A%%)m)l#ed

+#)+e2mm4

A%%)m

oeffi

Reso

!ccum. Rainfall

Linear A!ccum. RainfallC

-.--

7.--

-.--

7.--

,-.--

,7.--

5-.--

8O-O/ I58 8O-O/ I/5 8O-O/ I7- 8O-O/ I7? 8O-O/ ,I-7 8O-O/ ,I,

mm

Time

-B R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ 05.1 Dis#n%e o r#d#r @ !!' m.

Radar accumRain gauge !ccum2riginal radar !cc.

-

7

-

7

-.-- ,.-- /.--A%%)m)l#ed

+#)+e

2mm4

A%%)m

-B oef

ResoRainfall !cc.


-.--

,.--

/.--

8.--

?.--

-.--

,.--

/.--

8O-O/ I57 8O-O/ I/- 8O-O/ I/8 8O-O/ I7, 8O-O/ I7? 8O-O/ ,I-5

mm

Time

E8 R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @0:.77 Dis#n%e o r#d#r @ 5!' m.Radar !ccum.

Rain gauge !ccum

-

7

-

7

-.-- ,.-- /.--A%%)m)l#edr#in+#)+e2mm4

A%%)m

E8 oeffi%ien

Resol)io

Rainfall !cc.



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Fi+.7.11 Radar and gauge rain rate time series for 5 of the gauges during the event of :th)une. G method and Linear

--./

-.?

.,

.8

,

8O:O/ :59 8O:O/ :/ 8O:O/ :/7 8O:O/ :/: 8O:O/ :7/

R#i

ninensiies

2

mm9min4

Time

-B G#)+e Dis#n%e o r#d#r@!.!' mRadar G Method

6auge 2bservations

Radar L. Regres. Method

-

-./

-.?

.,

.8

,

8O:O/ :5 8O:O/ :59 8O:O/ :/5 8O:O/ :/: 8O:O/ :77 8O:O/

R#ininensiy

2mm9min4

Time

E8 G#)+e Dis#n%e o r#d#r@ 5!' m

Radar G Method

6auge 2bservations

Radar L. Regr. Method

-

-./

-.?

.,

.8

,

8O:O/ :59 8O:O/ :/5 8O:O/ :/: 8O:O/ :77 8O:O/ --- 8O:O/

R#inI

nensiy

2mm

9min4

Time

-3 G#)+e Dis#n%e o r#d#r !5!: m

Rada

6aug

Rada


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Fi+. 7.1!Radar and gauge rain rate time series for 5 of the gauges during the event of -th)une. G method and linea

-

-./

-.?

.,

.8

,

8O-O/ 5: 8O-O/ // 8O-O/ 7- 8O-O/ 78 8O-O/ ,-, 8O-O/ ,

R#inInensiy

2mm9min4

Time

-3 G#)+e Dis#n%e o r#d#r !5!: m

Radar

6auge observations

-

-./

-.?

.,

.8

,

8O-O/ 59 8O-O/ /, 8O-O/ /? 8O-O/ 7/ 8O-O/ ,-- 8O-O/

R#inInensiy

2mm9min4

Time

-B G#)+e Dis#n%e o r#d#r !5!: m

Rada G Method

6auge observations

-

-./

-.?

.,

.8

,

,./

,.?

5.,

8O-O/ 58 8O-O/ / 8O-O/ /9 8O-O/ 75 8O-O/ 7: 8O-O

R#ininensiy

2mm9min4

Time

E8 G#)+e Dis#n%e o r#d#r@5!' m

Radar G method

6auge 2bservations

Radar L. Regres. Met


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5:

'omparing the plots of the two methods it was reali+ed that the application of the linear method

regression is based in fact on the same strategy that the G method because watching the e&uation

A7.C# one can appreciate that by multiplying each of the rain rates comig from the application of

Marshall


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corrected.1he k values obtained after extracting the values and applying the same FG calibration

methodH are shown in the next table.

Table $.#G values for spatial resol. of ,7- m during the events of )une ,-/. A\C0o rain registered

6auges WB GL @6 3( "@ 2@ R$

3istanceto radarAmC

,7,- 7?77 795/ 5,8, 7,95 /,/: ,/,5

"vent G values Res.,7- m

5


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1he new value for a clutter pixel would be the median of the values within a 7x7 matrix around each

of the pixel.

!s a result of applying the clutter filter it was found that it was useful but 4ust for the dry period#

cause it was not able to get rid of the clutter effect during storm events where systematically low

reflectivity values in specific values# were found with respect to the neighboring pixels. 1he

explanation for this was found by comparing original images during dry period with images during

storm events .

3uring the dry period# the areas where reflectivity values were found Asee figure 8./C# were

approximately the same ones found during the rain events. 1he reflectivity values were clearly lower

than the surroundings as shown in fig. 8. and fig 8.,. 1herefore# it seems that the reflectivity coming

from the storm for the pixels affected by this phenomenon is averaged in the whole beam volume

with those lower values coming from clutter effects.

1hus# a new condition is added by means of comparing two arrays# one with the original reflectivity

values and another after applying a 7x7 median filter to the previous one# in such a way that for

this second matrix# each pixel contains the median value of its neighbors . !fter collecting a large

data set for different pixels affected by clutter at different times# the ratios between the value of

the same pixels for each of the two arrays were computed# and after ad4usting a statistical

distribution for the whole set of ratios# that happened to be Log


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1he way how the filter performed# can be seen in the next figure

Fig $.! "ffect of applying the filter algortihm in the accumulated map during the whole month of)une ,-/.2@ gauge still not corrected by the filter.

1he k values obtained after applying the filter were the fllowing

Table $.$ G values after applying clutter filter during the events of )une ,-/. A\C0o rain registered

"vent G values

5


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/5

by checking the effects of the application of the filter in the regression line methodbut this approach

was not performed in this study.

.*.& Co3ere'#re#infl"ence

In order to check whether there was any relationship between the area covered and the G constant

which could explain the variabilty # the average area covered in each rain event during each event

was calculated and the the following data were obtained.

Table $.' 1otal average area covered during the event# and K respect the total area covered by the

radar.

"vent !verage areal covered AGm,C K

5


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Table $.( Maximum intensities at every gauge during each of the events.

Max .IntensitiesAmmOminC

WB GL @6 3( "@ 2@ W$

5


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(o# it can be seen how the path to WB gauge is affected by the presence of the high intensity cell

close to the radar in such a way the rest of the path is affected by attenuation and therefore in

average# the d$B values are lower. 2n the contrary for the W$ case# it can be seen how the high

intensity cell is placed 4ust above the gauge and therefore the path is free of high intensity cells in

such a way the attenuation less# and the d$B values in averaged larger since there is still considreavle

intensities rates in between.1hus# more correction had to be applied to reflectivity values in W$

than in WB # fact that is is reflected in the G values.

1his first approach was made by makinf use of the filtered image in order to have a more clean path

of pixels from the radar to the gauges.

!ltough the attenuation is not effectively calculated # this approach suggests that further

investigations has to be done in order to account for the attenuation and its effects on the

calibrations processes.

6666 CONCLUSIONSANDRECOMCONCLUSIONSANDRECOMCONCLUSIONSANDRECOMCONCLUSIONSANDRECOMMENDATIONSMENDATIONSMENDATIONSMENDATIONS

.1 on%l)sions

Rainfall estimation is a driving force in the field of hydrology# being a main input in the hydrologic E

hydraulic models used for decision taking in urban water management.

In this work# unlike previous research in this case study# the preprocessed data provided by the ;orkO 6reat $ritain#

8?/ pp.

1estik# %.>. and 6ebremichael# M.# ,-5. 3ual


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i4lenhoet# R.# ,--. Raindrop si+e distributions and radar reflectivity

IUPWARE MAster Thesis Carlos Muñoz

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