Assessing the performance of ECMWF reanalysis data on the hydrology of East Black Sea - PowerPoint Presentation

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Assessing the performance of ECMWF reanalysis data on the hydrology of East Black Sea Region

Presented by: Sead AhmedNovember 2017

Sead Ahmed, Ercan KahyaFaculty of Civil Engineering, Hydraulic and Water Resource Engineering division,m Istanbul Technical University, Istanbul-Turkey

8th Atmospheric Sciences Symposium – ATMOS 2017

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1.1. Introduction

Hydrological variability – direct social & economical impactHydrological cycle – driven by climatePrecipitation – major component of climate affecting hydrologic cycle & water balanceDensity of rainfall stations – essential in capturing the variability

Mountanious regions - large number of stations with long years of good quality data are critical.

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1.1. Introduction contd.

In the Rize Bain, only 5 stations with minimum of 20-year record length.1 station

for each 606 km² grid (far below the WMO standard of 1 station for 100 - 250 km² of area for mountainous region)The poor coverage of rain gauge hinders accuracy of prediction of discharge (both low flow and flood)

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1.1. Introduction contd.

Satellite derived rainfall estimates – tools to supplement the ground based rainfall estimatesAvailable spatially distributed rainfall estimates

:- Climate Forecast System Reanalysis (CFSR), Multi-Sensor Precipitation Estimate-Geostationary (MPEG), Tropical Rainfall Measuring Mission (TRMM), European Centre for Medium-Range Weather Forecasts (ECMWF), etc.

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1.1. Introduction contd.

The ECMWF rainfall product was selected as:-It is freely

available and have been widely used. Relatively high spatial resolution, global coverage and high temporal resolutionGeneral objective of the study: Examine the performance of the ECMWF satellite product to estimate the rainfall in the highlands of the Northern Black Sea region and, Evaluate the performance of the product on the river flow estimation.

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1.2. Study Area

Rize Basin -northern Black Sea region of Turkey covers an approximate area of 3031.7 km².A

verage yearly precipitation of 2250.5 mm (high Rainfall) and yearly total runoff of 2745 million m3 (Kahya, 2015)Frequent flood problem.

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1.3. SWAT – Soil & Water Assesment Tool

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1.3. SWAT Contd...

A river basin scale model developed by Dr. Jeff Arnold for the USDA Agricultural Research Service (ARS) - Neitsch, et al., 2005

It is a physically based model, i.e. it requires information about:-Topography (DEM)Soil properties (Soil Map)Land management practices (Land use Map) &Weather (prec., max-min temp., RH, Rad...)Using these input data; SWAT models the physical process associated with water movement, sediment movement, nutrient recycling, etc. The benefits are:-To model watersheds without monitoring data (e.g. Stream gauge data) &To quantify the relative impact of alternative data (e.g. change in climate, land use, etc.) on the water quantity, quality and other variables of interest

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1.3. SWAT

Contd...SWAT can be used to simulate a single watershed or a system of multiple hydrologically connected watersheds (Arnold et al., 2012). Each watershed is first divided into

subbasins and then in hydrologic response units (HRUs) based on the land use and soil distributions.where is the final soil water content (mm H2O). is the initial soil water content (mm H2O), t is the time (days). ,, is the amount of precipitation on days (mm H2O), is the amount of surface runoff on day

i (mm H2O).

is the amount of evapotranspiration on day i (mm H2O), is the amount of Percolation and bypass flow exiting the soil profile bottom on day

i (mm H2O). and

is the amount of return flow on day

i

(mm H

2

O).

 

 

Land Phase

:

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2.1. Data

DEMSoil MapLand Use MapStudy area & Gauge stations

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2.1. Data

MGM - Meteorology General Directorate Daily total precipitation (mm), and daily average temperature (°C

) for 29 weather gauging stations in the Black Sea Region (only 14 in Rize basin)European Centre for Medium-Range Weather Forecasts (ECMWF), Precipitation, max. and min. temperature, solar radiation, relative humidity, and wind speed were available in the SWAT format. III. River flow data,daily flow data for the Camlıkdere gauging station of DSI (Ikizdere)

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2.2.

Methods

DEM, Soil, Landuse Maps – Deliniation & Setup

Weather data – Preciptation, Temprature

Model Setup & Simulatlon

Calibration & Validaiton

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2.2. Methods contd...

Weather Data - (MGM vs ECMWF)

SWAT

Model

Output (MGM) vs Output (ECMWF)

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2.2. Methods contd...

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2.2. Methods Contd...

Annual data assessmentMonthly data assessmentSWAT model data build-upSWAT uses only one weather station for each

subbasins to run the model if the weather station is found within the subbasins; otherwise, it will use the average of multiple stations in the nearbySWAT model setup and simulationUsing the MGM data, SWAT model was run for the period 1965-1996 (32 years), Using the CFSR data, the SWAT model was re-run from the period 1979-2013 (35 years). These two simulations were compared for performance.

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2.2. Methods Contd...

Statistic parameter

CalibrationValidationNS0.720.69

R2

0.740.75RSR

0.53

0.56

PBIAS

10.7

22.7

Statistical Model Performance Indicators for the SWAT Model.

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3. Results

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3. Results Contd...

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3. Results Contd...

The MGM and ECMWF precipitation data comparision.

MGM(Rize)ECMWF(411406)MGM(Ikizdere)

ECMWF

(405405)Mean6.22

3.53

2.98

2.97

St.dev.

13.89

5.76

7.01

4.32

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3. Results Contd...

Data Type

Total Water Yield (mm)Base Flow (mm)Surface Flow (mm)Precipitation(mm)PET(mm)

ET

(mm)Observed1273.783

877.5187

381.525

1125.316

SWAT-CFSR

1102.38

750.45

351.92

1563.7

663.1

450.3

SWAT- MGM

1194.10

749.23

444.77

1607.4

639.7

422.2

The summary of the basin hydrology simulation

The

Kaptanpaşa

subbasin

SWAT model

output was used extensively

-

due

to the fact that the preliminary comparison

of

model output

were

all in all

in agreement with the previous work

report on the

subbasin

(

Kahya

et al., 2015

)

and was the only

station where precipitation and flow guages are present

.

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3. Results Contd...

Case i (MGM) – Components of hydrology for the basin after simulation.

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3. Results Contd...

Case ii (ECMWF) – The simulation has resulted in a similar patern for the commponents of flow as compared with simulations of observed precipitation. Water Yield was exaggerated on the month of May.

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3. Results Contd...

The precipitation for the Rize station is dissimilar with its CFSR counterpart. However for the Pazar station, there is a better similarity in the distribution pattern.

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3. Results Contd...

The initial SWAT model simulation has more or less captured the general hydrology of the basin. However, when we go to the seasonal simulation performance and local level, it is not as expected and more work needed.

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4. Conclusion

Observed data of MGM stations were extensively compared with that of the satellite estimates of ECMWF.The work

has shown the importance of satellite based weather estimation data for poorly gauged basins.ECMWF data has been proved to have a good similarity with the majority of the observed station records to a great extent.

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