This document summarizes the development of an operational hydrologic forecast system in mountainous basins in Turkey using ensemble prediction systems (EPS) and satellite data. The system was developed for the Karasu basin using the HBV and SRM hydrologic models forced by ECMWF-EPS weather predictions. Probabilistic streamflow forecasts were produced out to 10 days lead time and evaluated against observations. The system was later expanded to include the Murat and Seyhan basins.

1. Gökçen Uysal1, Bulut Akkol1, Cansaran Ertaş1, Cihan
Çoşkun1, Arda Şorman1, Aynur Şensoy1,
Dirk Schwanenberg2
1 Anadol u Uni versi ty , Eski ş ehi r , Turkey
2 Uni versi ty of Dui sburg - E s s en , Germany
DEVELOPING AN OPERATIONAL
HYDROLOGIC FORECAST
SYSTEM USING EPS AND
SATELLITE DATA
IN MOUNTAINOUS BASINS OF
TURKEY

2. Between Asia and Europe,
Turkey is a high-altitude country with over 25 river
basins,
including the trans-boundary Tigris and
Euphrates rivers.
GEOLOGY AND TOPOGRAPHY OF TURKEY (1)

3. GEOLOGY AND TOPOGRAPHY OF TURKEY (2)

4. SNOW POTENTIAL OF TURKEY
NOAA Web Site – www.noaa.gov
 Hypsometric mean elevation is about 1130 m.
 Snow is major component in the mountanious Eastern Part.

5. HYDROPOWER POTENTIAL OF TURKEY
DSİ, 2012 report

6. HYDROPOWER DEVELOPMENT OF TURKEY (1)
* https://www.hydropower.org/country-profiles/turkey
** IHA 2015 Hydropower status report, https://www.hydropower.org/
 Turkey remains one of Europe’s leading markets for future hydropower
development…
 Turkey has plans for hydropower development over the coming decade
with a total installed electric power capacity of
2002  32 GW
2014  64 GW
2023  100 GW
(with 30 per cent of electricity generation coming from renewables*).
 In early 2015, the Turkish Government announced it would allocate
USD 16 billion to hydro development until 2018 as part of its Tenth
Development Plan**.

7.  Hydropower development
 In 2003,
 In recent years,
HYDROPOWER DEVELOPMENT OF TURKEY (2)
will be further supported by Turkey’s
interconnections into the European grid and
potential for further linkages east into Asia.
Turkey liberalized its energy market and embarked on
a process of privatizing existing assets.
international private companies have made major
investments in the country.

8. Considering the geographic location of Turkey and
hydroelectric power potential, our R&D activities as well
as the future operational implementation will provide;
 scientific outcomes,
 economic benefits,
 water resources benefits
also for downstream
stakeholders: flood mitigation,
irrigation, hydropower…
MOTIVATION FOR RESEARCH

9. KARASU (A PILOT BASIN)
 Keban, Karakaya, Atatürk etc. large dams
are located at the downstream of the basin
60–70% of the total runoff
volume originates during
snowmelt period….

10. Keban Dam
Karakaya Dam
Atatürk Dam
INSTALLED CAPACITY: 1 330 MW
ENERGY PRODUCTION: 6 000 GWh/year
INSTALLED CAPACITY : 1 800 MW
ENERGY PRODUCTION : 7 354 GWh/year
INSTALLED CAPACITY : 2 400 MW
ENERGY PRODUCTION : 8 900 GWh/year
Birecik Dam
Karkamış Dam
INSTALLED CAPACITY : 189 MW
ENERGY PRODUCTION : 652 GWh/year
CASCADE DAMS IN EUPHRATES RIVER
INSTALLED CAPACITY : 672 MW
ENERGY PRODUCTION: 2 516 GWh/year

11.  In 2004, flood risk occurred
due to sudden snow melt.
 At the time, there was
no real-time forecasting system.
 Governmental agencies decided to (pre-)release
additional 2,000 m3/s over 10 days from the most
upstream reservoir through the cascade.
 Post-event evaluation showed that
too much water was released and
lost for other objectives such as
irrigation or hydropower.
FLOOD EVENT IN 2004??

12. Karasu Basin is one of the pilot basins selected
for various;
 NATIONAL PROJECTS
(DPT – State Planning Organization,
TUBITAK – The Scientific and Technological
Research Council of Turkey),
 INTERNATIONAL PROJECTS
(NATO SfP-NATO Science for Peace,
EUMETSAT H-SAF – European Organization for
the Exploitation of Meteorological Satellites,
Satellite Application Facilities on Support to
Operational Hydrology and Water
Management).
PREVIOUS EFFORTS

13. The ongoing projects and execution periods;
- Developing an Operational Hydrologic Forecast
System using EPS and Satellite Data in
Mountainous Euphrates and Seyhan Basins,
TUBITAK Project, Oct 2013 - Dec 2015.
- Implementation of Hydrological Ensemble
Prediction System, Anadolu University Scientific
Research Project (1307F284), Dec 2013 – Dec
2015.
- Monitoring and Validation of Snow Components
using Satellite and Automated Ground Stations,
Anadolu University Scientific Research Project,
Apr 2014 – Apr 2015.
ONGOING NATIONAL EFFORTS

14. THROUGH INTERNATIONAL
PROJECTS
http://www.ecmwf.int/en/h-saf-and-hepex-workshops-coupled-hydrology
• TUBITAK project is extended through COST (European Cooperation in
Science and Technology) Project (ES1404) "A European network for
a harmonised monitoring of snow for the benefit of climate
change scenarios, hydrology and numerical weather prediction"
action,
• Moreover, preliminary DA results of H-SAF products (H-10, H-12 SCA
and SWE) in cooperation with Duisburg-Essen University for Karasu pilot
results are presented at the HSAF HEPEX WORKSHOP.

15. SCOPE & INNOVATION
It is aimed to deploy an operational hydrologic
forecast system in snow dominated mountainous
headwater basins in Turkey.
For the deterministic and probabilistic flow forecasts,
numerical weather predictions (WRF, ECMWF-EPS,
etc.) force hydrological models.
The main motivation and most novel part of this work
is the exploitation of ensemble forecasts for the first
time in Turkey within an operational hydrologic
forecasting system.

16. FLOW CHART
PROJECT
FLOW CHART

17. Elevation
zones
The Upper Euphrates
Basin (Karasu)
The main land-cover types
are pasture, cultivated land
and bareland.
Elevation
range (m)
Area
(km2
)
Hypsometric Mean
Elevation (m)
Slope
(%)
Karasu 1125-3487 10275 1983 19.24

18. RECENT EXTENTIONS TO NEW BASINS
Seyhan
Basin
Euphrates
Basin
MODIS satellite image February 2012
(white areas indicate snow cover)

19. SEYHAN BASIN HAS DEVELOPING
HYDROPOWER POTENTIAL
ex: water structures located in Seyhan Basin, Göksu River

20. CONTRIBUTIONS
Anadolu
University
University
of
Duisburg-
Essen
Institut Royal
Météorologique
de Belgique
State
Hydraulic
Works
Turkish
State
Meteorologi
cal Service
(TSMS)

21. MONITORING
Runoff for Upper Euphrates Basin
0
50
100
150
200
250
300
350
400
1-Feb
15-Feb
29-Feb
14-Mar
28-Mar
11-Apr
25-Apr
9-May
23-May
6-Jun
20-Jun
4-Jul
18-Jul
1-Aug
Discharge(m3/s)
2008
2009
2010
2011
2012
2013

22. Meteorological & SGS Point & SnoTel Stations
EUPHRATES OBSERVATION
NETWORK
FP ID River & SGS
Elevation
(m)
Basin
Area(km2)
Obs. Period
E21A019 Karasu - Kemah 1123 10350 1953 -
E21A022 Murat - Tutak 1552 5882 1953 -

23. FIELD WORK

24. 1-DAY LEAD TIME ACCURACY OF WRF
RELATED TO GROUND STATIONS

25. EPS DATA FOR PROJECT CATCHMENTS
ECMWF produced 28 km/grid resolution (T639/N320) EPS data
Total prec and mean air temp EPS data 6 x 10 pixels for Karasu Catc.,
4 x 6 pixels for Murat Catc. and 4 x 5 pixels for Seyhan Catch.

26. ENSEMBLE VERIFICATION SYSTEM (EVS)
RESULTS

27. SNOW DEPLETION CURVES (SDC)
Upper Euphrates SDC (MODIS after cloud removal)

28. HBV
(Hydrologiska Byråns Vattenbalans)
SRM
(Snowmelt-Runoff Model )
HYDROLOGICAL MODELS
(HBV & SRM)
(Lindströmet al., 1997) (Martinec et al., 2008)

29. HBV
 Good at continuous
modeling
 More parameters
 Low response to
instantaneous
melting
 Does not require
SDC (output)
SRM
 Good at melting
period
 Less parameters
 Fast response to
instantaneous
melting
 Requires SDC
(input)
WHY MULTI-MODELS ?
Through SRM
Development

30. SRM DEVELOPMENT IN RTC-TOOLS
Model Inputs : for each zone,
1. Daily total precipitation
2. Daily average temperature
3. Daily snow covered area (Depletion curve)
 Model parameters (cr, cs, tcrit, RCA…)
Qn+1= [cSn* an(Tn+ Δ Tn) Sn+ cRnPn] * (A · 10000 / 86400) * (1-kn+1) + Qnkn+1

31. KARASU SRM MODELING

32.  Ensemble Streamflows are developed for three
different basins (Karasu, Murat, Çukurkışla,
Kilicmehmet), using two different models for the
2011 melting period.
 The next results are presented every 10 days
although the forecast is available daily.
 Ensemble Streamflows are compared with
simulations.
PROBABILISTIC FORECASTS

33. UNDER DELFT-FEWS PLATFORM (WITHOUT DATA
ASSIMILATION AND OUTPUT CORRECTION)
HBV
SRM
Spagetti
plot
Quartiles

34. PERFORMANCE COMPARISON
HBV
SRM

35. ADDED VALUE OF FEWS PLATFORM
 Import Data Module (in particular for EPS and satellite data),
 Grid processing (basin averages etc.),
 Forecast Handling (pre- and post processing,
administration, storage, analysis, export)
 Easy link with EVS for ensemble analysis,
 Data Assimilation (embedding of MHE and several Kalman
Filters via OpenDA and RTC-Tools in progress),
 Potential future use as operational platform (suitable to
transfer knowhow to governmental agencies)…

36. CONCLUSIONS AND OUTLOOK
 Streamflow forecasting accounting snow accumulation
and melt is a major topic for Turkey due to flooding
and hydropower
 Flood early warning may decrease inundation risk and
related damages based on forecasts to take the right action
 Flow forecasts assist the short-term operation of reservoirs
and HEPP and increase their economic value
 Potential for improvement in Numerical Weather
Predictions (higher resolution, bias correction, etc.)
 Data Assimilation and probabilistic forecasting are
necessary tool to issue accurate and robust forecasts
(further collaboration in H-SAF with Deltares and
University of Duisburg-Essen on various DA
approaches)

37. CONCLUSIONS AND OUTLOOK (2)
 HBV and SRM models perform OK, but may
have potential for improvement (further
collaboration with Federal Institute of
Hydrology, Germany and University of
Duisburg-Essen).
 Further work will also focus on the short-term
management of the HEPP by the use of
forecasts and predictive control techniques
 Interdisciplinary work brings together staff
from the government, private sector,
academia providing an environment for
sharing knowledge and creating beneficial
results for all members.

38. THANK YOU FOR YOUR ATTENTION
gokcenuysal@gmail.com
This study is funded by
 113Y075 TUBITAK (The Scientific and Technological
Research Council of Turkey) and
 BAP 113Y075 (Scientific Research Project) of Anadolu
University, Turkey.