Influence of raingauge network characteristics on hydrological

response at catchment scale

4th International Workshop on Hydrological Extremes AMHY-FRIEND group

15-17 September 2011, Cosenza, Italy

Domenico CARACCIOLO, Elisa ARNONE, Leonardo Valerio NOTO

Dipartimento di Ingegneria Civile, Ambientale ed Aerospaziale (DICA), Università di Palermo, 90128 Palermo, ITALY

The uniformity of precipitation monitoring network, in terms of spatial spatial scalescale (network density network density and location of location of

raingaugesraingauges) and resolution timeresolution time, allows the reproduction, with acceptable

accuracy, of the characteristics of the flood phenomenonflood phenomenon.

Precipitation data Precipitation data is one of the most important inputs required is one of the most important inputs required in hydrological modeling and forecasting. In an in hydrological modeling and forecasting. In an hydrological hydrological

modelmodel, accurate knowledge of precipitation is essential for an , accurate knowledge of precipitation is essential for an acceptable acceptable estimation of hydrograph floodestimation of hydrograph flood

Previous studiesPrevious studies

In this context, over the last thirty years, several studies concerning the influence of rainfall point

measurement for the estimation of total runoff volume have been carried out

In particular, some studies have been focused on the analysis of the influence of the spatial influence of the spatial

distribution of raingaugesdistribution of raingauges, others on the influence influence of the number of raingaugesof the number of raingauges; however the two

issues have nevernever been analyzed simultaneouslyanalyzed simultaneously

Wilson Wilson et al.et al. (1979): (1979):

Use 1 or 20 fictitious raingauges to record rainfall concerning to 15 eventsUse 1 or 20 fictitious raingauges to record rainfall concerning to 15 events The spatial distribution of rainfall has a strong influence on the runoff. The The spatial distribution of rainfall has a strong influence on the runoff. The number of number of

raingauges raingauges has an important role for the has an important role for the correct estimation of the hydrograph peakcorrect estimation of the hydrograph peak

The work is based on the determination of the appropriate raingauges network The work is based on the determination of the appropriate raingauges network for the estimation of flood hydrograph, using a physically based distributed-for the estimation of flood hydrograph, using a physically based distributed-parameter hydrologicparameter hydrologic modelmodel

Krajewski Krajewski et al.et al. (1991): (1991):

The cases considered were:The cases considered were:case 1: 87 raingauges, temporal interval: 5 minutes ("real")case 1: 87 raingauges, temporal interval: 5 minutes ("real")case 2: 1 raingauge, temporal interval: 1 hourcase 2: 1 raingauge, temporal interval: 1 hourcase 3: 5 raingauges, temporal interval: 1 hourcase 3: 5 raingauges, temporal interval: 1 hourcase 4: 87 raingauges, temporal interval: 1 hourcase 4: 87 raingauges, temporal interval: 1 hourcase 5: use of the lumped modelcase 5: use of the lumped model

Higher sensitivity Higher sensitivity of of basin response with basin response with

respect to the respect to the temporal resolution temporal resolution

than to the than to the spatial spatial resolution resolution of the of the

rainfall datarainfall data

Obled Obled et al.et al. (1994) (1994)

The use of 21 instead of 5 raingauges is The use of 21 instead of 5 raingauges is irrelevant to the estimation of the precipitationirrelevant to the estimation of the precipitation The The small differencessmall differences that we have in that we have in terms of estimation of the terms of estimation of the precipitationprecipitation become become importantimportant when the precipitation is when the precipitation is transformed to transformed to runoff runoff

TOPMODELTOPMODEL

Goodrich Goodrich et al.et al. (1995) (1995) Uncertainty of measuring rainfall due to the number and location of gaugesUncertainty of measuring rainfall due to the number and location of gauges Existence of sufficient spatial and temporal variability in rainfallExistence of sufficient spatial and temporal variability in rainfall

In this paper they show the In this paper they show the influence of the different influence of the different positionspositions of the raingauges of the raingauges for the for the estimation of the estimation of the runoffrunoff

The The aim of this workaim of this work is to use a physically based is to use a physically based distributed-parameter hydrologic model (distributed-parameter hydrologic model (tRIBStRIBS) to ) to

investigate investigate the influence of the raingauges the influence of the raingauges networknetwork configuration in terms of number and configuration in terms of number and

spatial distribution, on the estimation of :spatial distribution, on the estimation of : discharge hydrographdischarge hydrograph hydrograph peakhydrograph peak time-to-peaktime-to-peak total runoff volume total runoff volume

This has been done considering the This has been done considering the spatial spatial distribution of soil typesdistribution of soil types in the basin as well in the basin as well

PurposePurpose

Physically based distributed-parameter hydrologic model

Developed at MIT (2003)

Representation of the surface with TIN (Triangular Irregular Network)

Hydrologic model Hydrologic model tRIBStRIBS(TIN Real-Time Integrated Basin Simulator)(TIN Real-Time Integrated Basin Simulator)

Triangle

Voronoi Cells

Voronoi Cells

The hydrologic The hydrologic model has been model has been applied to the applied to the Baron Baron Fork Fork at Eldon at Eldon watershed, a watershed, a catchment of catchment of Oklahoma (800 kmOklahoma (800 km22) )

Experimental partExperimental partAssumptions :Assumptions :

The The radarradar measurements, available in the area (NEXRAD), have been measurements, available in the area (NEXRAD), have been assumed as representative of the assumed as representative of the "real" "real" distribution of distribution of precipitationprecipitation

The The "real" "real" hydrological responsehydrological response of the catchment of the catchment was considered as was considered as obtained from the model obtained from the model tRIBStRIBS using as meteoric input using as meteoric input the real the real precipitationprecipitation ( (NEXRADNEXRAD))

The The position of 8 raingaugesposition of 8 raingauges was was generated randomly. generated randomly. Precipitation value is set equal to Precipitation value is set equal to the corresponding NEXRAD raster the corresponding NEXRAD raster cell valuecell value

9 events events of precipitation occurred during 1998 were taken into of precipitation occurred during 1998 were taken into account. The nine events were chosen according to the account. The nine events were chosen according to the average average intensity of precipitationintensity of precipitation ( (II) classified as ) classified as highhigh (I> 2.5 mm/h), (I> 2.5 mm/h), mediummedium (1.5 mm/h <I <2.5 mm/h) and (1.5 mm/h <I <2.5 mm/h) and lowlow (I<1.5 mm/h) and the (I<1.5 mm/h) and the coefficient of variationcoefficient of variation ( (CVCV) of average precipitation classified ) of average precipitation classified as as highhigh (CV> 0.6), (CV> 0.6), mediummedium (0.25 <CV <0.6) and (0.25 <CV <0.6) and lowlow (CV <0.25). (CV <0.25). CV, for each event, is calculated from the raster obtained by CV, for each event, is calculated from the raster obtained by adding the hourly precipitation raster (NEXRAD)adding the hourly precipitation raster (NEXRAD)

ID event hours h i m CVraster

- month day hour month day hour h mm mm/h -1 1 4 3 1 5 17 36 109,97 3,05 0,262 5 6 24 5 7 6 7 10,89 1,56 0,633 8 19 18 8 19 24 7 9,44 1,35 0,924 9 12 20 9 15 21 67 116,11 1,73 0,125 10 5 7 10 6 11 29 101,18 3,49 0,126 11 10 4 11 10 8 5 15,47 3,09 0,607 3 17 6 3 17 18 12 9,27 0,77 0,228 12 6 20 12 6 23 4 6,09 1,52 0,449 6 18 10 6 18 18 9 8,91 0,99 0,45

start event end event

im

- H M LH 6° 1° 5°M 2° 8° 4°L 3° 9° 7°

CVraster

Event classification

The analysis has been carried out assuming five different soil spatial distributions:

ss scsccscscc rr

two soil types: silty-claysilty-clay and sandy-clay-loamsandy-clay-loam (cs (cs and sc) sc)

the realreal (r) (r) spatial distribution of soil types

a single soil type: silty-clay silty-clay (c)(c) (Ks=1 mm/h) or sandy-clay-sandy-clay-

loam loam (s) (s) (Ks=235 mm/h)

a simplifiedsimplified fictitious spatial distribution of soil characteristics:

SimulationsSimulations Simulations considering Simulations considering "uniform""uniform" precipitation in space and precipitation in space and

measured by the 8 raingauges (interpolated with the measured by the 8 raingauges (interpolated with the Thiessen Thiessen polygonspolygons). After we have combined the raingauges in pairs, ). After we have combined the raingauges in pairs, three by three, four by four, five by five, six by six, seven by three by three, four by four, five by five, six by six, seven by seven and the complete networkseven and the complete network

The hydrographs flood obtained for each combination of The hydrographs flood obtained for each combination of raingauges are raingauges are comparedcompared with with the the "real""real" hydrological responsehydrological response calculating performance indices calculating performance indices

N. raingauges12

345678

total 255

Possible raingauges networks combinations

8

1

28

567056288

Performance IndexPerformance Index

N

QQRMSE

N

iRADiPLUVi

Q

1

2,, )(

statistical correlation indexstatistical correlation index:RMSERMSE (Root Mean Squared Error)

For each combination of raingauges and for each soil For each combination of raingauges and for each soil distribution the network of raingauges with the distribution the network of raingauges with the smallest RMSE smallest RMSE (RMSE(RMSEminmin) has been chosen) has been chosen

RMSERMSE is calculated for each event

Qi,PLUV : flow obtained with the precipitation misured by raingauges

Qi,RAD : flow obtained with the precipitation misured by RADAR

N: event hours number

Event 1: Event 1: 36 houres, CV=medium, I=high

For For high intensityhigh intensity, the , the raingauges are placedraingauges are placed in in the less permeable the less permeable soilsoil, but also , but also where the where the precipitation is highprecipitation is high

s c sc cs real s c sc cs real1 9,825 26,848 17,496 13,178 19,144 4 4 5 3 42 2,337 6,769 2,965 5,546 4,892 2,6 3,5 3,7 2,6 3,73 1,500 3,524 2,644 1,997 2,856 1,3,6 2,3,7 3,5,7 1,3,6 1,3,64 1,327 2,387 2,279 1,761 2,128 3,4,5,6 1,3,5,6 2,5,6,8 1,3,5,6 1,3,6,75 1,246 2,530 2,140 1,825 2,185 1,3,5,6,8 1,3,5,6,7 2,3,5,6,8 1,3,5,6,7 1,3,6,7,86 1,286 2,501 2,186 2,378 2,216 1,3,5,6,7,8 1,3,5,6,7,8 2,3,5,6,7,8 1,3,5,6,7,8 1,3,5,6,7,87 1,747 3,421 2,792 2,541 2,883 1,3,4,5,6,7,8 1,3,4,5,6,7,8 2,3,4,5,6,7,8 1,2,3,4,6,7,8 1,3,4,5,6,7,88 2,012 4,692 4,053 2,698 3,978

RMSE minQ Raingauges

1,2,3,4,5,6,7,8

Spatial pattern

Legend

mean rainfall

mm/h

0 - 0,5

0,5 - 1

1 - 1,5

1,5 - 2

2 - 2,5

2,5 - 3

3 - 3,5

3,5 - 4

4 - 4,5

4,5 - 5

Event 3: Event 3: 7 houres, CV=high, I=low

For For low intensitylow intensity, the , the raingauges are placed in raingauges are placed in the the less permeable soilless permeable soil

s c sc cs real s c sc cs real1 2,490 5,483 3,997 2,701 3,501 2 7 7 2 22 1,466 3,409 3,244 1,799 2,041 7,8 2,7 2,7 7,8 2,73 1,131 2,074 2,119 1,333 1,681 1,2,7 5,7,8 5,7,8 1,2,7 5,7,84 1,208 2,280 2,136 1,384 1,777 1,2,3,7 2,5,7,8 1,5,7,8 1,2,3,7 1,5,7,85 1,113 1,937 1,910 1,148 1,363 1,2,5,7,8 1,3,5,7,8 1,2,5,7,8 1,3,5,7,8 1,2,5,7,86 1,179 1,937 1,966 1,133 1,436 1,2,3,5,7,8 1,2,3,5,7,8 1,2,3,5,7,8 1,2,3,5,7,8 1,2,3,5,7,87 1,293 2,188 2,207 1,238 1,574 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,88 1,636 2,663 2,481 1,875 2,020

RaingaugesRMSE Qmin

1,2,3,4,5,6,7,8

Spatial pattern

Legend

mean rainfall

mm/h

0 - 0,5

0,5 - 1

1 - 1,5

1,5 - 2

2 - 2,5

2,5 - 3

3 - 3,5

3,5 - 4

4 - 4,5

4,5 - 5

Event 4: Event 4: 67 houres, CV=low, I=medium

For For CV=lowCV=low, varying , varying the distribution of the distribution of soil, the soil, the raingauges raingauges network is almost network is almost the samethe same

s c sc cs real s c sc cs real1 9,137 20,200 9,956 10,572 14,590 2 2 5 2 22 3,026 6,658 5,428 4,630 5,172 3,5 3,5 3,5 3,5 3,53 2,065 5,188 4,402 3,093 3,777 3,5,8 3,5,8, 3,5,8 3,7,8 3,7,84 1,951 3,805 3,116 2,685 2,815 3,5,7,8 3,5,7,8 2,4,5,8 3,5,7,8 3,5,7,85 1,764 2,960 2,345 2,576 2,664 2,3,4,5,8 2,3,4,5,8 2,3,4,5,8 2,3,4,5,8 2,3,4,5,86 1,976 3,640 2,834 2,773 3,004 1,2,3,5,6,8 1,2,3,5,6,8 1,2,3,4,5,8 1,2,3,5,6,8 1,2,3,5,6,87 2,175 4,313 4,574 2,667 3,375 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,88 3,501 9,008 7,172 5,340 6,672

RaingaugesRMSE Qmin

1,2,3,4,5,6,7,8

Spatial pattern

Legend

mean rainfall

mm/h

0 - 0,5

0,5 - 1

1 - 1,5

1,5 - 2

2 - 2,5

2,5 - 3

3 - 3,5

3,5 - 4

4 - 4,5

4,5 - 5

In order to summarize all results in a single table, the In order to summarize all results in a single table, the average average flow flow was calculated from the flood hydrograph and each value of was calculated from the flood hydrograph and each value of RMSE is divided for the corresponding average flow. RMSE is divided for the corresponding average flow. Normalized Normalized valuesvalues obtained for each event, were added together and divided obtained for each event, were added together and divided by the number of events in order to calculate the by the number of events in order to calculate the average value average value of RMSE/Qof RMSE/QMM minimum minimum

n.gauges\soil s c sc cs real s c sc cs real1 0,416 0,451 0,429 0,347 0,447 3 3 8 3 32 0,248 0,279 0,257 0,237 0,271 3,7 3,7 7,8 3,8 3,73 0,175 0,192 0,175 0,188 0,174 3,7,8 3,7,8 3,7,8 3,7,8 3,7,84 0,153 0,154 0,136 0,175 0,158 2,3,7,8 3,5,7,8 3,5,7,8 1,3,7,8 3,5,7,85 0,138 0,148 0,134 0,151 0,145 1,3,5,7,8 1,3,5,7,8 1,3,5,7,8 1,3,5,7,8 1,3,5,7,86 0,142 0,155 0,138 0,164 0,152 1,2,3,5,7,8 1,2,3,5,7,8 1,2,3,5,7,8 1,3,5,6,7,8 1,2,3,5,7,87 0,150 0,160 0,152 0,174 0,163 1,2,3,5,6,7,8 1,2,3,4,5,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,8 1,2,3,5,6,7,88 0,174 0,163 0,161 0,180 0,173 1,2,3,4,5,6,7,8 1,2,3,4,5,6,7,8 1,2,3,4,5,6,7,8 1,2,3,4,5,6,7,8 1,2,3,4,5,6,7,8

(mean(RMSE Q/Qm))min Raingauges

ss scsccc

cscs rr

Using only Using only a a raingaugeraingauge, it is placed in the , it is placed in the less permeable soilless permeable soilWith a network of two raingauges follows the same patternWith a network of two raingauges follows the same patternWith a With a networknetwork of three, four, …. raingauges of three, four, …. raingauges there is not a clear there is not a clear criterion for the best position of the i-th gaugecriterion for the best position of the i-th gauge

ss

… … in conclusion...in conclusion...

in case of in case of highhigh average rainfall average rainfall intensityintensity, the influence of , the influence of precipitation patternprecipitation pattern is is greatergreater than that of than that of soil types distributionsoil types distribution;;

in case of in case of mediummedium oror lowlow average rainfall average rainfall intensityintensity, the effect of the effect of precipitation precipitation is is lowerlower than the effect of than the effect of soil types distributionsoil types distribution;;

if the if the rainfall spatial variation rainfall spatial variation is is medium or low medium or low the the distribution of raingauges distribution of raingauges varies littlevaries little with the change of the distribution of soils. with the change of the distribution of soils.

There There is notis not an an optimal raingauges network optimal raingauges network finalized to the estimation finalized to the estimation of all the considered flood events.of all the considered flood events.

The The network finalizednetwork finalized to the best reconstruction of to the best reconstruction of rainfall rainfall field field does does not coincidenot coincide with the with the network finalizednetwork finalized to the best to the best flood hydrographflood hydrograph estimation.estimation.

For a fixed event, the best For a fixed event, the best raingauges configurationraingauges configuration is strongly is strongly dependent on thedependent on the soil types distribution.soil types distribution.

The best The best raingauges configurationsraingauges configurations depend on thedepend on the precipitation precipitation eventsevents (in terms of intensity and spatial distribution) and on the (in terms of intensity and spatial distribution) and on the soil soil types distributiontypes distribution (general trend to locate the raingauges where the (general trend to locate the raingauges where the soil is less permeable):soil is less permeable):

Thank you for your attentionThank you for your attention