USE OF FEWS IN SUPPORT OF DROUGHT

MANAGEMENT AND PLANNING IN THE PO

RIVER IN ITALY

Fabrizio Tonelli and Enrica Zenoni

Hydrology and Hydrography Area

HydroMeteoClimate Service

Emilia -Romagna Region - ITALY

DEWS – Drought Early Warning System

TOPKAPI

PRECIPITATION TEMPERATURE LEVEL/DISCHARGES PIEZOMETRIC HEAD

METEOROLOGICAL MODELS

Observed/Telemeasure LM + 15 days/Seasonal Forecasts + 3 months

VALIDATION, INTERPOLATION AND DATA TRANSFORMATION (DEWS)

RIBASIM

Rainfall-runoff model

Water balance model

Monitoring network:

431 water level gauges (blue triangle)

1145 raingauges (green dots) 834 thermometers (green dots)

193 dams (violet)

Modeling chain for drought forecasting and mitigation

Infiltration

Percolation

Evapo-traspiration

Surface runoff

Groundwater flow

Snow melt

The hydrological model (TOPKAPI) is a distributed and physically based model. It represents discharge starting from meteorological input and physical and morphological characteristics of the river basin.

Hydrological model

HYDROLOGICAL MODELING SYSTEM IN THE PO RIVER BASIN

Here the scheme adopted for the Po river basin (70000 km2) in Italy; in the picture are shown diversion link, diversion node, general district used properly to represent the use of water in the basin object of study.

RIBASIM software (RIver BAsin SIMulation) has been developed by DELTARES, on the basis of MITSIM model of Massachusset Istitute of Technology, Massachusset (USA)

Modeling chain for drought forecasting and mitigation

This model enables an integrated management and an optimization of basin water resources use, by computing the discharge allocation, simulated by the hydrological model topkapi. Distribution networks consist of rivers, open channals, reservoirs or artificial control/hydropower production and aqueducts.

Water balance model

The simulation of discharge allocation is an evaluation of how water availability and network efficiency meet the water request.

SUMMER 2015

An example of application of DEWS to manage droughts can be taken from last summer, a season caracterized by high temperatures and low water levels.

Following, some images explaining how we used the system. In particular, DEWS results were required for the Po “Cabina di Regia”, a cometee oriented to decide how water can be used and managed in drought conditions in Po river.

HIGH OBSERVED TEMPERATURES 20/7 AT 12:00

COSMO I7 FORECASTS

+ 10 DAYS FORECASTS

PIACENZA – FORECASTS FOR SUMMER 2015 AND COMPARISON WITH OTHER YEARS

0

500

1000

1500

2000

2500

3000

3500

26-mag 5-giu 15-giu 25-giu 5-lug 15-lug 25-lug 4-ago

Port

ata [

m3 /s

]

Portate medie giornaliere a Piacenza

2006 2007 2014 Osservato Previsto

CREMONA – FORECASTS FOR SUMMER 2015 AND COMPARISON WITH OTHER YEARS

0

500

1000

1500

2000

2500

3000

3500

26-mag 5-giu 15-giu 25-giu 5-lug 15-lug 25-lug 4-ago

Port

ata [

m3 /s

]

Portate medie giornaliere a Cremona

2006 2007 2014 Osservato Previsto

BORETTO – FORECASTS FOR SUMMER 2015 AND COMPARISON WITH OTHER YEARS

0

500

1000

1500

2000

2500

3000

3500

26-mag 5-giu 15-giu 25-giu 5-lug 15-lug 25-lug 4-ago

Port

ata [

m3 /s

]

Portate medie giornaliere a Boretto

2006 2007 2014 Osservato Previsto

BORGOFORTE – FORECASTS FOR SUMMER 2015 AND COMPARISON WITH OTHER YEARS

0

500

1000

1500

2000

2500

3000

3500

26-mag 5-giu 15-giu 25-giu 5-lug 15-lug 25-lug 4-ago

Port

ata [

m3 /s

]

Portate medie giornaliere a Borgoforte

2006 2007 2014 Osservato Previsto

PONTELAGOSCURO – FORECASTS FOR SUMMER 2015 AND COMPARISON WITH OTHER YEARS

0

500

1000

1500

2000

2500

3000

3500

26-mag 5-giu 15-giu 25-giu 5-lug 15-lug 25-lug 4-ago

Port

ata [

m3 /s

]

Portate medie giornaliere a Pontelagoscuro

2006 2007 2014 Osservato Previsto

10.5 14.7 8.9 11.4 11.6 16.6 8.2 12.2 9.3 11.1

10.6 14.8 9.0 11.5 11.8 16.8 8.3 12.3 9.3 11.1

10.7 14.9 9.1 11.6 11.9 16.9 8.3 12.3 9.4 11.2

10.7 14.9 9.0 11.5 11.9 16.9 8.3 12.3 9.4 11.2

10.7 14.9 9.1 11.6 11.9 16.9 8.4 12.4 9.4 11.2

10.9 15.1 9.3 11.8 12.2 17.2 8.5 12.5 9.6 11.4

10.9 15.1 9.4 11.9 12.3 17.3 8.6 12.6 9.6 11.4

10.9 15.1 9.3 11.8 12.2 17.2 8.5 12.5 9.6 11.4

10.7 14.9 9.1 11.6 11.9 16.9 8.4 12.4 9.4 11.2

10.6 14.8 9.0 11.5 11.8 16.8 8.3 12.3 9.3 11.1

10.6 14.8 8.9 11.4 11.7 16.7 8.2 12.2 9.3 11.1

10.5 14.7 8.9 11.4 11.6 16.6 8.2 12.2 9.3 11.1

10.6 14.8 8.9 11.4 11.6 16.6 8.2 12.2 9.3 11.1

10.7 14.9 8.9 11.4 11.6 16.6 8.2 12.2 9.3 11.1

10.9 15.1 8.9 11.4 11.7 16.7 8.2 12.2 9.3 11.1

10.9 15.1 9.1 11.6 11.9 16.9 8.4 12.4 9.4 11.2

03/08/2015

04/08/2015

Maistra

[km]

Tolle

[km]

Gnocca

[km]

Goro

[km]

29/07/2015

30/07/2015

31/07/2015

01/08/2015

02/08/2015

Pila

[km]Data

20/07/2015

21/07/2015

22/07/2015

23/07/2015

24/07/2015

25/07/2015

26/07/2015

27/07/2015

28/07/2015

PONTELAGOSCURO – SALT INTRUSION

WHAT IF SCENARIO

320

330

340

350

360

370

380

390

400

410

420

20/0

7/20

15 0

.00

21/0

7/20

15 0

.00

22/0

7/20

15 0

.00

23/0

7/20

15 0

.00

24/0

7/20

15 0

.00

25/0

7/20

15 0

.00

26/0

7/20

15 0

.00

27/0

7/20

15 0

.00

28/0

7/20

15 0

.00

29/0

7/20

15 0

.00

30/0

7/20

15 0

.00

31/0

7/20

15 0

.00

01/0

8/20

15 0

.00

02/0

8/20

15 0

.00

03/0

8/20

15 0

.00

04/0

8/20

15 0

.00

Port

ata,

m3/

s

Pontelagoscuro Base

Pontelagoscuro 5%

SOME CONSIDERATIONS ABOUT DISCHARGE

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Por

tata

[m³/s

]

Po a Pontelagoscuro

2015 2014 1923-2014 MINIMO STORICO

0.5

0.8

0.9

0.95

0.98

0.99

0.995

0.998

0.999

2

5

10

20

50

100

200

500

1000

Tr [anni]1-P

Q [m³/s]

Po a Pontelagoscuro

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

1 2 3 4 5 6 7 8 9 10 11 12

SFI

mese durante l'anno 2015

PONTELAGOSCURO - 1 mese

Month during the year

1 month

discharge 330 m3/s

SOME CONSIDERATIONS ABOUT RAINFALL

-10

10

30

50

70

90

110

130

150

Affl

usso

(Mill

imet

ri)

2015 2002-2011 1923-1972

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

1 2 3 4 5 6 7 8 9 10 11 12

SP

I

mese durante l'anno 2015

Pontelagoscuro - 1 mese

The graph of SPI calculated over a period of 1 month shows for Pontelagoscuro section conditions of normality in terms of precipitation, except for the month of Jule, where the conditions were “almost dry”. The comparison of SPI3 and SPI6 of this summer with historical values indicates that rainfall from march to august was not so low and far from the mean of the period, with exception of july for the duration of 1 month with impact to surface withdrawals. Month during the year

Rain

fall,

mm

USE OF FEWS IN WATER RESOURCES ASSESSMENT

FEWS has been used in SA version to generate long term simultations of discharge data (using observed data of precipitation and temperature)

Water management and water policies require long time series of river discharge data referred to several river sections. Unfortunately, not for all the river section long time series are available or the river bed has been modified and data are no more representative of the river regime in the section.

Availability of discharge data in Emilia Romagna Region

Since 2003 the hydrological network of RER had a continuous increase of points where the level and flow are monitored

In 2012 hydrological balances were published for 84 hydrometric sections

STAZIONE BACINO Km2 Zero ID

Pub.

2003

Pub.

2004

Pub.

2005

Pub.

2006

Pub.

2007

Pub.

2008

Pub.

2009

Pub.

2010

Pub.

2011

Pub.

2012

TIDONE

Ponte Nibbiano Tidone 102 270.426 H+Q H+Q H+Q H+Q H+Q H+Q

Pianello Val Tidone Tidone 223 145.642

Rottofreno Tidone 348 58.006 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

TREBBIA

Valsigiara Trebbia 217 452.766 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Cabanne Aveto 42 808.450 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Salsominore Aveto 200 398.326 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Bobbio Trebbia 653 257.150 H H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Rivergaro Trebbia 915 136.664 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

NURE

Ferriere Nure 47 617.100 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Farini Nure 206 421.317 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponteolio Nure 336 199.125

S.G. Piacentino Nure 361 92.116 H+Q

Ponte Nure Nure << 60.404 H

CHIAVENNA

Ciriano Chero 55 111.686 H+Q H H+Q H+Q H+Q H+Q

Saliceto Chiavenna 157 49.829 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Veggiola Riglio 30 196.421 H H

Montanaro Riglio 102 81.119 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

ARDA

Case Bonini Arda 72 338.336 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Lugagnano Arda 102 205.943 H+Q

Fiorenzuola Arda 134 76.643 H+Q H+Q H+Q

TARO

Tornolo Taro 105 479.128 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Pradella Taro 295 416.369 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Borgotaro Taro 349 344.956 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Solignano Taro 610 218.670 H+Q H+Q H+Q

Ponteceno Ceno 52 704.140 H+Q H+Q H+Q H+Q

Ponte Lamberti Ceno 330 326.065 H H+Q H+Q H+Q H+Q H+Q H+Q

Varanoidro (Rubiano) Ceno 407 245.830 H H+Q H+Q H+Q H+Q H

Fornovo Taro 711 135.350 H H

Pontetaro Taro 1372 57.300 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Noceto Recchio 39 75.112 H+Q H+Q H+Q H+Q H+Q

San Secondo Taro 1457 25.050 H H H H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Vigoleno Stirone 87 180.620 H H+Q

Salsomaggiore Ghiara 29 147.644 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Castellina di Soragna Stirone 166 43.989 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Toccalmatto Rovacchia 91 55.163 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

PARMA

Corniglio Parma 111 529.001 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Langhirano (Capoponte) Parma 297 252.634

Berceto Baganza 16 788.050 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Marzolara Baganza 128 301.793 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Nuovo Baganza 190 58.170 H

Ponte Verdi Parma 624 51.530 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

ENZA

Selvanizza Enza Enza 85 541.203 H+Q H+Q H+Q H+Q H+Q H+Q

Selvanizza Cedra Cedra 80 452.270 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H

Lonza Lonza 61 359.573 H+Q H+Q H+Q

Vetto Enza 297 311.970 H+Q H+Q H+Q H+Q H+Q H+Q

Compiano Tassobbio 101 << H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Currada Enza 429 231.205 H+Q H+Q H+Q H+Q H+Q

Sorbolo Enza 655 23.852 H H+Q H+Q H+Q H+Q H+Q H+Q H H+Q H+Q

EMILIA e PO

CROSTOLO

Puianello Crostolo 86 125.938 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Rivalta Crostolo 90 << H H H H H H

Cadelbosco Crostolo 215 25.414 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Santa Vittoria Crostolo 302 << H

SECCHIA

Gatta Secchia 234 381.258 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Gatta Secchiello Secchiello 72 388.349 H+Q H H+Q H+Q H+Q H

Pontedolo Dolo 134 363.530 H+Q H+Q H+Q H+Q H

Ponte Cavola Secchia 347 340.927 H H+Q H+Q H+Q H+Q H+Q H H+Q H+Q H+Q

Lugo Secchia 694 236.269 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Rossenna Rossenna 187 247.471 H+Q H+Q H H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Veggia Secchia 1004 << H

Ca de Caroli Tresinaro 150 94.017 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Rubiera SS9 Secchia 1303 47.330 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Alto Secchia 1321 28.849 H H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Bacchello Secchia 1324 23.447 H H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Pioppa Secchia 1331 18.688 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

PANARO

Fiumalbo Aquicciola 18 936.617 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Pievepelago Scoltenna 130 719.045 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Val Sasso Scoltenna 271 356.490 H H H H+Q H+Q H H+Q H+Q H+Q

Fanano Leo 38 515.157 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Samone Panaro 583 214.493 H H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Spilamberto Panaro 758 62.583 H H H H+Q H+Q H+Q H+Q H+Q H+Q

Gorzano Tiepido 44 142.232 H+Q H H

San Donnino Tiepido 61 42.930 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Bomporto Panaro 1124 17.100 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Bondeno Panaro 1128 11.388 H H

Modena Naviglio Naviglio 72 27.081 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Navicello Panaro 1004 <<

Camposanto Panaro 1129 << H H H H H H

PO

Ponte Becca Po 36770 55.110 H H H H H H H H H H

Ponte Spessa Po 37372 52.090 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Piacenza Po 42030 41.880 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Cremona Po 50726 34.250 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Casalmaggiore Po 53460 23.210 H H H H H H H H H H

Boretto Po 55183 19.900 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Borgoforte Po 62450 14.500 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Sermide Po 68724 5.510 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ficarolo Po 62450 10.030 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Pontelagoscuro Po 70091 8.120 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Polesella Po << 1.170 H H H H H H H H H H

Ariano Delta PO << 1.760 H H H H H H

Mesola Delta PO << -1.700 H H H

Molo Farsetti Delta PO << << H H H H

Ca' Venier Delta PO << -0.140 H H HCa' Dolfin Delta PO << << H H H

STAZIONE BACINO Km2 Zero ID

Pub.

2003

Pub.

2004

Pub.

2005

Pub.

2006

Pub.

2007

Pub.

2008

Pub.

2009

Pub.

2010

Pub.

2011

Pub.

2012

RENO

Pracchia Reno 39.8 609.850 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Porretta Reno 153.3 336.560 H H H H H H H H H H

Silla Silla 82.3 335.020 H H H H H H H H H H

Lago Suviana Limenta 210 425.500 H H H H H H H H H

Vergato Reno 551.7 182.930 H H H H H H+Q H+Q H+Q H+Q H+Q

Panico Canale di Panico << << H+Q H

Panico2 Reno 650.2 114.900 H H H H H H H H H H

Sasso Marconi Setta 317.1 99.180 H H H H H H H

Casalecchio Chiusa Reno 1055.8 60.270 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Casalecchio Tiro Volo Reno 1055.8 47.820 H H H H H H H H H H

Bonconvento Reno 1055.8 17.200 H H H H H H H H H H

Calcara Samoggia 174.9 44.480 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Lavino di Sopra Samoggia/Lavino 86.2 60.160 H H H+Q H+Q H+Q H+Q H+Q H+Q

Anzola Ghironda 78.7 -2.300 H H H H H H H H H H

Forcelli Samoggia 371.7 16.510 H H H H H H H H H H

Cento Reno 1447.1 15.200 H H H H H H H H H H

Passo Gallo Reno 1584.5 4.680 H H H H H H H H H

Casalecchio Canale di Reno << 58.050 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

S.Ruffillo Canale di Savena 154 << H H H H H

Castelmaggiore Navile 10.47 45.600 H H H H H H H H H H

Arcoveggio Navile << << H+Q

Saletto Diversivo Saletto << 13.300 H H H H H H H H H H

Casoni Savena Abb 53.7 1.730 H H H H H H H H H H

Pizzocalvo Idice 211 10.470 H H H H H H H H H H

Loiano Savena 70.1 0.000 H H H H

Pianoro Savena << << H

S.Ruffillo Savena 154 << H H H H H H H H H

Ponte Caselle Savena << << H

Castenaso Idice 397.4 23.160 H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Palesio Quaderna 22.9 << H H H

Castel San Pietro Sillaro 69.45 136.500 H H H H H H H H

Sesto Imolese Sillaro 248.6 7.340 H+Q H+Q H H H H H+Q H+Q H+Q H+Q

S.Antonio Idice 546 <<

Ponte Bastia Reno 3425.4 -1.260 H+Q H+Q H H H H H H

Borgo Tossignano Santerno 319.6 << H H H+Q H+Q H+Q H H H+Q

Codrignano Santerno << << H

Imola Santerno 413.4 34.680 H H H H H H H H H H+Q

Mordano Santerno 465.4 9.550 H+Q H+Q H H H H+Q H+Q H+Q H+Q H+Q

Casola Val Senio Senio 135.9 << H+Q H+Q H+Q H+Q H+Q H+Q

Castelbolognese Senio 270.4 32.610 H H H H H H H H H H

Tebano Senio 251 <<

LAMONE

Marradi Lamone 103 305.360 H+Q H+Q H+Q H+Q H+Q

Strada Casale Lamone 192.6 134.830 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Sarna Lamone 255.6 51.199 H H+Q H+Q H+Q H+Q H+Q H+Q

Rivalta Marzeno 181.3 44.950 H+Q H H+Q H+Q

Reda Lamone 519.6 16.362 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Mezzano Lamone 521 2.110 H+Q H+Q H H

FIUMI UNITI

Castrocaro Montone 238.2 53.480 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Predappio Rabbi 172.4 120.130 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Ponte Braldo Montone 508.6 << H H H

Ponte Vico Montone 510 8.056 H H+Q H+Q H+Q H+Q H+Q H+Q

Meldola Ronco 446 51.660 H+Q H+Q H H

Coccolia Ronco 593 4.555 H H+Q H+Q H+Q H+Q H+Q H+Q

BEVANO

Santa Maria Nova Bevano 32 <<

San Zaccaria Bevano 74 5.630 H

SAVIO

Castiglione Savio 620 2.260 H

Borello Borello 128.4 65.506 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

San Carlo Savio 585.8 42.984 H+Q H+Q H+Q H+Q H+Q H+Q H+Q

Matellica Savio 620 << H H H H

PISCIATELLO

Calisese Pisciatello 40 << H+Q H+Q H+Q

RUBICONE

Savignano Rubicone 39 << H+Q H+Q H+Q

USO

S.Arcangelo Uso 109 30.319 H+Q H+Q H+Q H+Q H+Q H+Q

MARECCHIA

Ponte Verucchio Marecchia 465.4 97.400 H H H

Rimini SS16 Marecchia 531.8 2.408 H H H H H H+Q H H+QCONCA

Morciano Conca 141 66.135 H+Q H+Q H+Q

ROMAGNA

But for water resources and water quality assessment in a very complex environment and whit a great number of stakeholders we need to estimate mean daily discharge on a great number of ungauged sections (more than 700) SOLUTION: A regionalization approach have been adopted in order to estimate daily discharges at ungauged sections using an assimilation technique.

The simulated time series can be assimilated through • a local approach, if long observed time series are available and sections of interest are monitored; • a regionalized approach if the observed timeseries are short or relatively scarse with respect to sections of interest (this is our case)

Methodology

Atlante Idroclimatico dell’Emilia Romagna 1961 – 2008 a cura di Arpa Servizio Idro-Meteo-Clima 2010

Area 1: affected by Tirrenian meteorological dynamics

Area 3: Appennine Area

Area 2: Po plain Area

To apply the regional approach we identified four areas homogeneous from climatic and hydrological point of view

Area 4: affected by Adriatic meteorological dynamics

Methodology The regional approach allows to correct either the simulated average discharge and the

distribution function by acting on two variables: the Qindex (average discharge) and X =

Q/Qindex (normalized value);

For the ungauged section k, an estimate of the correct Q*index,k is obtained from a multivariate

regression based on Basin Area (Ak) and Rainfall input(Rk) .

In special cases the proportionality among simulated and observed discharges at the section j

is used

jsimindex

jobsindex

ksimindex

m

k

m

k

kindex

Q

QQ

RAm

Q

,,

,,

,,

21

0

*

,

m2 m1 m0

AREA1 1.20774 0.87908 0.00001

AREA2 0.39193 0.89831 0.00113

AREA3 0.72584 0.80501 0.00038

AREA4 1.01387 0.78093 0.00003

The regional probability distribution function of the normalized variable X

(observed or simulated) are estimated by pulling togheter all the normalised

timeseries falling into the considered homogenous area.

The goodness of fit is tested by KS, Chi-Squared and Anderson-Darlington

tests.

The best results have been obtained with Wakeby distribution, both for

simulated and observed data

Wakeby

ligure obs a= 0.21618; b= 2.4056; c= 0.50989; d= 0.46762; e= -0.02122

sim a= 0.50624; b= 3.458; c= 0.49463; d= 0.45526; e= -0.02158

pedemontana obs a= 0; b= 0; c= 0.42286; d= 0.58039; e= -0.00107

sim a= 0.31023; b= 2.3372; c= 0.39995; d= 0.52331; e= 0.06803

appenninica obs a= -0.13658; b= 1.2414; c= 0.64405; d= 0.40216; e= -0.01635

sim a= 0.44987; b= 8.9832; c= 0.53485; d= 0.43991; e= 0

adriatica obs a= -0.65499; b= 2.3713; c= 0.81572; d= 0.31727; e= -5.0385E-4

sim a= -0.42942; b= 0.35063; c= 0.65352; d= 0.50285; e= 0.00341

Methodology

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.5 1 1.5 2 2.5 3

Cum

ulat

tive

Dist

ribut

ion

Func

tion

(CDF

)

Normalize discharge (Q/Qindex)

Observed

Simulated

x*(t) = F-1obs(Fsim(xsim(t)))

Once that the distribution functions have been identified it is possible to perform

a correction in probability of xsim(t)

Methodology

x*(assimilated)

x(simulated)

Results in terms of duration curves

0

10

20

30

40

50

60

70

80

90

100

0 50 100 150 200 250 300 350

Qobs Qsim Qassim

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300 350

Qobs Qsim Qassim

0

50

100

150

200

250

300

0 50 100 150 200 250 300 350

Qobs Qsim Qassim

Panaro at Spilamberto(Appenninic Area)

Savio at San Carlo (Area affected by Adriatic meteorological dynamics)

Stirone a Castellina di Soragna(Po plain Area)

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150 200 250 300 350

Qobs Qsim Qassim

Taro at San Secondo(Area affected by Ligurian meteorological dynamics)

USE OF FEWS IN CONNECTING SURFACE WATER MODELLING WITH GROUNDWATER MODELLING

In the real time system for drought

management, groundwater is simulated

inside Ribasim in a simplified way

A more accurate knowlege of the

groundwater system, and in particular of the

water exchange from/to the river, is very

important for water assessment and

management

river

urban area

river ground surface

groundwater

abstraction

groundwater

outflow

groundwater

recharge

ground water aquifer A

ground water aquifer B

E010823a

QQ

QQ

14

25

Q

Q

Q

Q

Q67

8

9

10

Q3

irrigated area

irrigation canal

A test application for a small acquifer have been

developed, in wich existing groundwater (Modflow)

and surface water (Topkapi + RIBASIM) models

have been integrated inside FEWS (Stand Alone)

THREE STEP APPROACH

Import of observed groundwater data inside FEWS

Insert existing groundwater models of Emilia

Romagna Region inside FEWS – Modflow 2k

adapter

Analysis of dinamical exchange processes between

surface and subsurface water

Groundwater levels observing network for Emilia

Romagna Region

Two different Modflow models have been inserted

into FEWS throught the develpment of a Modflow

2k FEWS adapter

MODLFLOW IN FEWS

Modflow 2k

Adapter

FEWS

XML

Native

format

Native

format MODFLOW

MANAGED MODFLOW MODULES

•RCH surface recharge

•GHB general head boundaries

•SFR2 river-groundwater exchange

•WEL groundwater abstraction

COMPARISON BETWEEN OBSERVED AND SIMULATED

VALUES AND IMPLEMENTATION OF WHAT-IF SCENARIOS

Coupling of RIBASIM and MODFLOW using SFR2 module

RIBASIM simulated

discharge injected in

Modflow through SFR2

module

-8

-6

-4

-2

0

2

4

6

8

9 101112 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112

2006 2007 2008 2009 2010 2011

po

rta

ta (

m3

/s)

WELLS In-out STREAM LEAKAGE In-out STORAGE In-out RECHARGE In-out HEAD DEP BOUNDS In-out DRAINS In-out

THANK YOU FOR YOUR ATTENTION!

INTEGRAZIONE RIBASIM - MODFLOW

RIBASIM contiene un modulo semplificato per la simulazione

delle acque sotterranee che computa il bilancio idrico

dell’acquifero considerando le caratteristiche dell’acquifero

stesso, gli ingressi esterni, le ricariche della falda, le estrazioni di

acqua di falda e le perdite laterali. river

urban area

river ground surface

groundwater

abstraction

groundwater

outflow

groundwater

recharge

ground water aquifer A

ground water aquifer B

E010823a

QQ

QQ

14

25

Q

Q

Q

Q

Q67

8

9

10

Q3

irrigated area

irrigation canal

L’innesto di MODFLOW in

FEWS permette una gestione

integrata della modellistica

(confronto/ricalibrazione)