Fews in support of drought management and plangin in the Po River Italy

1. 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

2. 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

3. Monitoring network:
431 water level gauges (blue triangle)
1145 raingauges (green dots)
834 thermometers (green dots)
193 dams (violet)

4. 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

5. 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)

6. 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.

7. 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.

8. HIGH OBSERVED TEMPERATURES 20/7 AT 12:00

9. COSMO I7 FORECASTS

10. + 10 DAYS FORECASTS

11. 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
Portata[m3/s]
Portate medie giornaliere a Piacenza
2006 2007 2014 Osservato Previsto

12. 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
Portata[m3/s]
Portate medie giornaliere a Cremona
2006 2007 2014 Osservato Previsto

13. 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
Portata[m3/s]
Portate medie giornaliere a Boretto
2006 2007 2014 Osservato Previsto

14. 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
Portata[m3/s]
Portate medie giornaliere a Borgoforte
2006 2007 2014 Osservato Previsto

15. 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
Portata[m3/s]
Portate medie giornaliere a
Pontelagoscuro
2006 2007 2014 Osservato Previsto

16. 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

17. WHAT IF SCENARIO
320
330
340
350
360
370
380
390
400
410
420
20/07/20150.00
21/07/20150.00
22/07/20150.00
23/07/20150.00
24/07/20150.00
25/07/20150.00
26/07/20150.00
27/07/20150.00
28/07/20150.00
29/07/20150.00
30/07/20150.00
31/07/20150.00
01/08/20150.00
02/08/20150.00
03/08/20150.00
04/08/20150.00
Portata,m3/s
Pontelagoscuro Base
Pontelagoscuro 5%

18. SOME CONSIDERATIONS ABOUT DISCHARGE
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Portata[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

19. SOME CONSIDERATIONS ABOUT RAINFALL
-10
10
30
50
70
90
110
130
150
Afflusso(Millimetri)
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
SPI
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
Rainfall,mm

20. 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.

21. 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 Km
2
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 H
Ca' Dolfin Delta PO << << H H H
STAZIONE BACINO Km
2
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+Q
CONCA
Morciano Conca 141 66.135 H+Q H+Q H+Q
ROMAGNA

22. 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.

23. 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

24. 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
Q
Q
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

25. 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

26. 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
CumulattiveDistributionFunction(CDF)
Normalize discharge (Q/Qindex)
Observed
Simulated
x*(t) = F-1
obs(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)

27. 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)

28. 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

29.  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)

30. 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

31. Groundwater levels observing network for Emilia
Romagna Region

32.  Two different Modflow models have been inserted
into FEWS throught the develpment of a Modflow
2k FEWS adapter

33. MODLFLOW IN FEWS
Modflow 2k
Adapter
FEWS
XML
Native
format
Native
formatMODFLOW

34. MANAGED MODFLOW MODULES
•RCH surface recharge
•GHB general head boundaries
•SFR2 river-groundwater exchange
•WEL groundwater abstraction

35. COMPARISON BETWEEN OBSERVED AND SIMULATED
VALUES AND IMPLEMENTATION OF WHAT-IF SCENARIOS

36. Coupling of RIBASIM and MODFLOW using SFR2 module
RIBASIM simulated
discharge injected in
Modflow through SFR2
module

37. -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
portata(m3/s)
WELLSIn-out STREAM LEAKAGE In-out STORAGE In-out RECHARGE In-out HEAD DEP BOUNDS In-out DRAINS In-out

38. THANK YOU FOR YOUR ATTENTION!

39. 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)