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ASMET Phase II: Satellite Precipitation Products for Hydrological Management in Southern Africa
website:
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get link for asmet 4. where's 5??? the EU doesn't work!
link to 5
south africa:
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fix link to asmet website
get survey and quiz to work
ask david to translate description...
Is the title OK?
Still need copyright approval for:
 South African Weather Service (Lee-ann)
 South African Department of Water Affairs [LE or CR]
VERIFY THAT THE DESCRIPTION IS OK - THE PART ABOUT ASMET.
Greetings,
The COMET Program is pleased to announce the publication of Satellite
Precipitation Products for Hydrological Management in Southern Africa. This
one-hour module introduces a variety of meteorological and hydrological
products that can improve the quality of heavy rainfall forecasts and assist
with hydrological management during extensive precipitation events in
Southern Africa. Among them are the satellite-based ASCAT, SMOS, and ASAR GM
soil moisture products and the hydro-estimator. The products are presented
within the context of a case, the flooding of South Africa's Vaal Dam in
2009/2010. Please follow this link to start the module:
http://www.meted.ucar.edu/asmet/so_africa/index.htm.
The module is part of the ASMET (African Satellite Meteorology Education &
Training) project. Since 1997, ASMET has been producing online and CD-based
learning modules that teach African forecasters how to enhance their
forecasts by making better use of meteorological satellite images and
products. The modules are available in French and English. They are produced
by the ASMET team, which consists of meteorology instructors from the
Regional Training Centers (RTCs) in Kenya and Niger, and the South African
Weather Service (Pretoria). ASMET is a EUMETSAT/COMET project.
This module uses JavaScript for navigation, animation, and the presentation
of multimedia elements. Ensure that you have a browser updated to its latest
version with JavaScript enabled. For technical support for this module please
visit our Registration and Support FAQs at
https://www.meted.ucar.edu/resources_faq.php.
NOTE TO NWS and other NOAA EMPLOYEES: This module is available in the
Commerce Learning Center @ National Weather Service
(https://doc.learn.com/noaa/nws). Please access it in that system in order to
get credit.
We welcome any comments or questions you may have regarding the content,
instructional approach, or use of this module. Please e-mail your comments or
questions to Marianne Weingroff (marianne@ucar.edu).
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Sincerely,
Dr. Tim Spangler
Director, COMET
Description: This module introduces a variety of meteorological and hydrological products that can improve the
quality of heavy rainfall forecasts and assist with hydrological management during extensive precipitation events
in Southern Africa. Among them are the satellite-based ASCAT, SMOS, and ASAR GM soil moisture products
and the hydro-estimator. The products are presented within the context of a case, the flooding of South Africa's
Vaal Dam in 2009/2010.
Credits:
Lee-ann Simpson (SAWS), Colleen Rae (SAWS), Estelle De Coning (SAWS), Erik Becker (SAWS), Colleen De
Villiers (SAWS), Charlotte McBride (SAWS), Louis Van Hemert (SAWS), Hans-Peter Roesli (EUMETSAT),
Eugene Poolman (SAWS), Marianne Weingroff (COMET), Henk Verschuur (EUMETSAT), Marcela Doubkova,
Institute of Photogrammetry and Remote Sensing (IPF), Technical University in Vienna (TUWIEN), Austria
MODULE OUTLINE
SECTION 1: INTRODUCTION
Page 1: About the Module
Page 2: Flooding in South Africa
Page 3: About the Case
SECTION 2: OVERVIEW OF THE RAINFALL AND FLOODING SEASON
Page 1: Rainfall Accumulation Data
Page 2: Provincial Seasonal Rainfall Graphs
Page 3: Provincial Seasonal Rainfall Map
Page 4: Station Rainfall Maps
SECTION 3: COMBINING HYDROLOGIC AND RAINFALL DATA
Page 1: Combined 7-Day Rainfall Accumulation vs. Dam Capacity
SECTION 4: SATELLITE & NWP DATA
Page 1: Overview
Page 2: WV Imagery Overlaid with Model Wind Fields
Page 3: Low Pressure over Namibia
Page 4: Moisture Advection
Page 5: Comparing High- and Low-Pressure Systems
Page 6: Direction of the System
SECTION 5: RADAR Rainfall Estimates
Page 1: SAWS Radar
Page 2: Radar Data for 21 January 2010
SECTION 6: HYDRO-ESTIMATOR
Page 1: Overview
Page 2: HE Data for 21 January 2010
SECTION 7: INTEGRATING THE DATA
Page 1: Making the Forecast
Page 2: Taking Action
Page 3: Combined 15-Day Rainfall Accumulation vs. Dam Capacity
Page 4: Real-Time Vs. Predicted Capacity of the Dam
Page 5: Conclusion
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SECTION 8: SOIL MOISTURE PRODUCTS
Page 1: ASAR GM
Page 2: ASCAT Soil Moisture Product
Page 3: SMOS Soil Moisture Product
SECTION 9: FLASH FLOOD GUIDANCE
Page 1: SAWS Flash Flood Guidance System
SECTION 10: CONCLUSION & REFERENCES
Page 1: From 1996 to 2010
Page 2: Recommendations
Page 3: References
SECTION 1: INTRODUCTION
Page 1: About the Module
Short-term weather forecasting classically works in the one- to seven-day time frame. However, large-scale and
widespread flooding does not result from a single weather event that can be covered by a short-term forecast.
Rather, it comes from persistent rainfall over a catchment region during an entire rainfall season, which saturates
the ground and leaves areas susceptible to flooding. This means that forecasters should have a comprehensive
understanding of the atmospheric and surface environment at all times and be able to incorporate information
about current surface conditions in their short-term weather forecasts.
This module examines a variety of meteorological and hydrological products that can improve the quality of
heavy rainfall forecasts and assist with hydrological management during extensive precipitation events. Some of
these are meteorology products that forecasters typically use, such as satellite imagery, numerical weather
prediction products, and radar data (when available). But there are a host of new satellite-based hydrological
products that are available to forecasters and provide critical information about surface conditions. We will
introduce four of them: the ASCAT, SMOS, and ASAR GM soil moisture products, and the Hydro-Estimator. The
products will be presented within the context of a case, the flooding of South Africa's Vaal Dam in 2009/2010.
The module is intended for operational forecasters. Meteorology students and weather enthusiasts should also
find the material useful. By the end of the module, learners should be able to do the following:
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Explain why it is important for weather forecasters to have a holistic understanding of atmospheric and
surface conditions at all times
Describe the benefits of combining data from different meteorological and hydrological sources when
dealing with heavy rainfall situations that can potentially lead to flooding
Describe the hydro-estimator and the ASCAT, SMOS, ASAR GM soil moisture products and the benefits
of using them in the forecast process
Describe the importance of communicating with hydrological management when heavy rainfall and
flooding are a concern
To get the most out of this module, learners should have a basic understanding of meteorology, forecasting, and
hydrology. For information about hydrology, see The COMET® Program’s online international hydrology course
at https://www.meted.ucar.edu/training_course.php?id=24.
Page 2: Flooding in South Africa
South Africa receives rainfall from cold fronts and other mid-latitude weather systems as well as tropically
sourced moisture and resultant precipitation during the Southern Hemispheric summer months (October to
March).
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The central and northern parts of South Africa (the summer rainfall region) can receive up to 30% of their
October-December rainfall totals, and 60% of their January rainfall total from tropical temperate troughs alone,
making them the single most important rainfall contributing system for this region (Asnani, 2005).
The South African Weather Service (SAWS) issues now-casts for flash flooding and localized flooding along with
heavy rainfall warnings when more than 50 mm of rainfall are expected over a 24-hour period. Early warnings for
flash flooding are issued as heavy rainfall warnings with “the potential for flash flooding.” These forecasts are
based on real-time satellite and radar imagery along with numerical weather prediction (NWP) model forecasts.
Until recently, they did not include information about the actual state of river basins or areas prone to flash
flooding. But SAWS and the National Disaster Management Centre (NDMC) are now operating South Africa’s
first operational flash flood warning system, known as the South African Flash Flood Guidance (SAFFG) system.
The system incorporates meteorological and hydrological data and lets SAWS issue flash flood warnings to
disaster management structures and the public.
Page 3: About the Case
The case covers the flooding of South Africa’s Vaal Dam during the 2009/2010 summer rainfall season. As you
will see, the extensive flooding resulted from the accumulation of rainfall over the catchment area, rather than a
single weather event. The seasonal forecast had, in fact, predicted an El Niño event, which usually results in
below-average rainfall amounts for the summer rainfall region. But almost all of the rainfall areas across South
Africa recorded near-normal or above-normal rainfall from November 2009 through January 2010.
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Before we begin the case, review this background information about the dam.
The Vaal Dam lies on the Vaal River, one of South Africa's strongest-flowing rivers. The dam covers an area over
three hundred square kilometers and is South Africa's largest dam by area and third largest by volume. It lies in
the Vaal Dam catchment, which is divided into the Upper Vaal, Middle Vaal, and Lower Vaal catchment regions.
The Middle and Lower regions occur below the level of the dam wall and will not be considered in the case.
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The Vaal River is the largest tributary of the Orange River and has its source in the Drakensberg Mountains in
Mpumalanga east of Johannesburg (about 30 km north of Ermelo). The river then flows westwards to its junction
with the Orange River southwest of Kimberley in the Northern Cape. The Vaal River is 1120 km in length and
forms the border between the Mpumalanga, Gauteng, and the North West provinces on its north bank and the
Free State on its south.
The Vaal Dam is a vital part of the water supply system for the Gauteng region. Water for the dam is supplied by
the Vaal and Wilge Rivers. We will focus on the Vaal River inflow to the dam, which is in the Vaal River catchment
area in Mpumalanga Province.
SECTION 2: OVERVIEW OF THE RAINFALL AND FLOODING SEASON
Page 1: Rainfall Accumulation Data
The South African Weather Service’s Climate Information Service provides rainfall accumulation data measured
in mm in five-minute intervals, 24 hours per day. The raw data are averaged for each day, and monthly averages
are provided for stations of interest. Graphs and maps are used to show the distribution of rainfall as well as
rainfall totals versus seasonal averages. For more information about these data, contact the SAWS Climate
Information Services at www.weathersa.co.za.
In this section, we will look at three types of rainfall data for the case: provincial seasonal rainfall graphs,
provincial seasonal rainfall maps, and station rainfall maps.
Page 2: Provincial Seasonal Rainfall Graphs
Here are the provincial seasonal rainfall graphs for the Mpumalanga and Gauteng Provinces from October 2009
to 21 January 2010. Compare the amounts measured against the climatologic averages, then answer the
question below.
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Based on the seasonal rainfall to date, which provincial areas might be at risk for flooding? Select all that apply,
then click Done.
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Mpumalanga
Gauteng **
Feedback: Recent trends in Gauteng make flooding a possible concern, while Mpumalanga has experienced a
shortage of rainfall over the past two months.
Page 3: Provincial Seasonal Rainfall Map
Provincial seasonal rainfall graphs provide useful information about a region’s rainfall but do not give a clear
indication of where the major rain events actually occurred. For that, we will look at a provincial seasonal rainfall
map from SAWS.
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According to these data, which areas are at risk of flooding? (Select all that apply.)
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All of Mpumalanga Province
Parts of Mpumalanga Province **
All of Gauteng Province **
Parts of Gauteng Province
Feedback: The regional map helps narrow our focus. All of Gauteng is at risk for flooding since it received
between 100% and 150% of its average rainfall. Significant portions of Mpumalanga are at risk as well, with some
areas receiving 100% to 150%. But some areas received below average rainfall, from 50% to 75%.
Page 4: Station Rainfall Maps
Review the provincial seasonal rainfall graphs
Review the provincial seasonal rainfall map
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To gauge the likely impact of significant rainfall on hydrological conditions, it's important to know when the major
rain events occurred. Were they spread out or clustered? Did they occur at the beginning or end of the season?
To find this out, we'll look at actual rainfall graphs for the weather stations in Ermelo (Mpumalanga Province) and
Johannesburg and Vereeniging (Gauteng Province). Review the data, then decide which statement is correct.
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All three stations show above average rainfall for the entire period
All three stations show below average rainfall for the entire period
All three stations show below average rainfall for January
All three stations show above average rainfall for January **
Feedback: The correct answer is D. As expected, rainfall rates increased at all three stations in January. But
Johannesburg had the largest spike at the end of the period and is therefore at greatest risk of flooding should
significant rain events occur.
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Note that the weather station rainfall records corroborate the data from the provincial seasonal rainfall map but
not the provincial seasonal rainfall graph. For example, the graph showed a decrease in rainfall over
Mpumalanga Province, while the Ermelo station rainfall map reported above average rainfall for the period. This
highlights the importance of monitoring different types of data at different scales. It helps ensure that you get an
accurate picture of meteorological and hydrological conditions throughout your area of responsibility.
SECTION 3: COMBINING HYDROLOGIC AND RAINFALL DATA
Page 1: Combined 7-Day Rainfall Accumulation vs. Dam Capacity
The South African Department of Water Affairs (DWA) provides various hydrological data, including:
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Graphs of the relationship between rainfall accumulation and dam capacity
Graphs of the real-time and predicted capacities of dams
We'll look at both types of data, the first one now, the second in a later section.
Here are the rainfall totals for the three stations compared to the Vaal Dam capacity from 15 to 21 January 2010.
As you can see, the dam's capacity rose from approximately 90% on 15 January to 94% on 21 January. This was
due, in part, to the continued increase in precipitation in the areas around all three weather stations. If
precipitation continues, dam levels will keep rising, making flooding an even more likely possibility. Keep in mind
that there’s a time delay between an actual rain event and the water’s arrival at a dam. For the Vaal Dam
catchment area, it takes approximately two days for rain at the furthest edge to arrive at the dam.
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In the next section, we'll look at satellite, NWP, and radar data for 21 January 2010 and assess if they indicate
potential rainfall for the next days. Following that, we'll examine hydrological and rainfall data from late January
and early February and see what actually happened to the Vaal Dam.
SECTION 4: SATELLITE & NWP DATA
Page 1: Overview
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Observations from the Meteosat Second Generation (MSG) satellites are available across the Southern African
Development Community (SADC) and are an essential tool in weather forecasting. Many single channel and
composite images and products are useful when heavy rainfall and flooding are a concern, particularly from the
water vapour 6.2 µm and infrared 10.8 µm channels.
For the case, we'll examine MSG WV 6.2 µm channel images overlaid with ECMWF wind fields at 850 hPa, 700
hPa, and 500 hPa for 21 January at 12Z. The water vapour channel helps identify upper-level (400-hPa) moisture
content and is particularly useful for locating upper-level low-pressure systems. The wind barbs help us determine
the location of low-pressure systems and, if any are present, identify their depth through the atmosphere, their
intensity, and where the moisture is being drawn from to fuel any convective activity.
Throughout the following exercises, we'll refer to different parts of Southern Africa. If you're not familiar with the
region, please refer to the "Southern Africa Maps" link in the box on the bottom left.
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Page 2: WV Imagery Overlaid with Model Wind Fields
Click each tab, review the image, and then answer the question below it. When you have finished all three
questions, move on to the next page.
500-hPa: There’s at least one high and/or low-pressure system on this 500-hPa image. Drag an H for high or an
L for low to each system that you see on the image. When you are finished, click Done.
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Feedback: There are two systems in the image: a high-pressure system over the Maputo area; and a weakly
developed low-pressure system over northern Namibia, which appears as more of a wave than a closed low.
Scroll up to the top and click the 700-hPa tab.
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700 hPa: Do the same exercise for this 700-hPa image. Drag an H for high or an L for low to any systems that
you see on the image, then click Done.
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Feedback: There are two systems in the image: a high-pressure system just west of Swaziland in the region of
the anti-cyclonic flow; and a low-pressure system over northern Namibia in the region of cyclonic circulation.
Scroll up to the top and click the 850-hPa tab.
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850 hPa: Do the same exercise for this 850-hPa image. Drag an H for high or an L for low to any systems that
you see on the image, then click Done.
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Feedback: There are two high-pressure systems in the image, one northwest of Swaziland and the other to the
southeast of South Africa over the ocean. There’s also a low-pressure system over northern Namibia.
Click on the NEXT PAGE to proceed.
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Page 3: Low Pressure over Namibia
Show all 3 graphics
At what levels are the low-pressure systems over Namibia well developed? Review the data, then answer the
question below.
Select the levels at which the low-pressure systems over Namibia are well developed, then click Done.
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500
700 **
850 **
Feedback: The correct answers are B and C. There is a closed circulation at 850 hPa and 700 hPa, and a trough
at 500 hPa.
Page 4: Moisture Advection
Show all 3 graphics
From what direction is the moisture over Zambia and Botswana being drawn? Review the data, then answer the
question below.
Select the dominant direction from which the moisture over Zambia and Botswana is being being drawn. Then
click Done.
 Southeast
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Southwest
South
North
Northeast**
Northwest
Feedback: The correct answer is E. The wind converging into the low/trough at all levels comes from the
northeast. This is significant because it’s bringing a warm tropical air mass into the area, making moisture
available in a deep layer from 850 hPa to 500 hPa at least.
Page 5: Comparing High- and Low-Pressure Systems
show all graphics
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Compare the position of the high-pressure system in the east to the low-pressure system over Namibia. Which
region should experience maximum low-level convergence?
A
B
C**
Feedback: The region at C should experience the most low-level convergence since it’s between the two
systems. Areas A and B are both divergent areas, where the low-level flow is moving in opposite directions.
Page 6: Direction of the System
Show all 3 graphics
The three images show a great deal of moisture related to the convective activities over Zambia and Botswana.
Towards where is the moisture being driven?
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Angola
Zimbabwe
Central South Africa**
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Namibia
Feedback: At all three levels (850, 700, and 500 hPa), the winds have a strong northerly component over Zambia
and Botswana. This is steering the humidity mainly to the central part of South Africa, putting it at risk for a
considerable amount of rain. This assessment should be confirmed with forecast information from NWP models.
SECTION 5: RADAR Rainfall Estimates
Page 1: SAWS Radar
Radars can provide indirect measurements of rainfall but they need to cover an entire area of interest and be well
correlated with synoptic rain gauges. Due to the high cost of procuring and maintaining radars, they are a scarce
commodity in most of Africa. However, they are available in South Africa.
Until the end of 2009, the South African weather radar network consisted of ten C-band and two S-band radar
systems located across the country. This network was used extensively to support weather predictions, storm
identification, and aviation applications. Note some of the benefits and limitations of the system:
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Convective storms were observed very well given their relatively deep vertical dimensions; however, these
systems could only be partially seen at long range due to the curvature of the Earth away from the radar
beam
The spacing of the radars made it difficult to observe stratiform rain; these systems are relatively shallow and
radar beams overshoot the echo tops at long ranges
The system lacked Doppler capabilities, which can detect the relative movement of rain and ice particles
present in active clouds
As of 2010, SAWS is migrating to S-band radar systems in which the signals undergo far less attenuation than Cband signals. These radars have sensitive Doppler capabilities that can detect the internal wind structure of
storms, enabling better nowcasting of severe storms. This new radar technology is also very useful for
precipitation estimates.
For more information on radar, see the COMET module Radar Signatures for Severe Convective Weather at
http://www.meted.ucar.edu/radar/severe_signatures/. The module is free and available to all users but you must
register to access the site.
Page 2: Radar Data for 21 January 2010
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Here’s the 24-hour rainfall accumulation data from the SAWS radar network for the Johannesburg area on 21
January 2010 at 12Z. What does it indicate about rainfall in the area over the past 24 hours?
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It received no rain
It received 0 to 10 mm of rain
It received 10 to 30 mm of rain***
It received 30 to 80 mm of rain
Feedback: The correct answer is C. The radar rainfall accumulation indicates that 10 to 25 mm of rain on average
fell over the Johannesbug area during the previous 24 hours, with 40 mm calculated locally. Note that the daily
rainfall totals show differernt amounts: 35 mm were actually measured. This discrepancy is not unusual. Radar
and rain gauges are different technologies and have distinct advantages and disadvantages.
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SECTION 6: HYDRO-ESTIMATOR
Page 1: Overview
The Hydro-Estimator (HE) indicates how much rainfall (in mm) has accumulated over a given region during a
specified period and is useful for determining whether to issue warnings for heavy rainfall and flash flooding. HE
precipitation estimates are based on cloud-top temperatures derived from satellite imagery. This makes them a
good complement to radar data. But the HE is particularly valuable in data-sparse areas with limited groundbased observing systems, such as the Southern African Development Community (SADC).
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The South African Weather Service has an in-house version of the Hydro-Estimator, which uses the local version
of the UK Met Office Unified Model and MSG satellite data. The product can be visualised with the SUMO
software and internally at the SWFDP website hosted by SAWS. (Note that it’s for use by member countries
only.) s
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Page 2: HE Data for 21 January 2010
This graphic shows accumulated rainfall based on the Hydro-Estimator over South Africa, Namibia, and
Botswana from 22 December 2009 to 21 January 2010. Rainfall totals over the Mpumamlanga and Gauteng
Provinces are between 200 mm and 400 mm, while northern Namibia has accumulated values well above 300
mm.
How well do the HE data correlate with the seasonal rainfall data that we examined earlier? Review the data,
then answer the question below.
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How well do the HE data correlate with the seasonal rainfall data that we examined earlier?
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The HE shows high rainfall values in the region in which the seasonal rainfall data showed above normal
conditions **
The HE shows very little rainfall compared with the seasonal data
There’s no correlation between the seasonal data and HE totals
Feedback: The correct answer is A. Although the seasonal rainfall is given as a percentage of the normal rainfall
over South Africa, the HE products compare well with the seasonal data. For example, over the Ermelo area,
seasonal rainfall data have values up to 150% of normal, while the HE indicates that the area received over 300
mm of rainfall between 22 December and 21 January. Although these datasets deal with different values, the
trend of heavy rainfall over the Vaal Dam catchment region remains constant throughout. This kind of information
should be of concern to meteorologists on duty and keep them on alert.
SECTION 7: INTEGRATING THE DATA
Page 1: Making the Forecast
We've examined various types of data for 21 January 2010. What do you expect to happen to the Vaal Dam
catchment area in the coming days?
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The low-pressure system over Namibia should move into a position that causes further rainfall over the
region **
Soil moisture values are high enough to make flooding of the Vaal Dam a serious possibility **
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Moisture at low and medium levels is being advected towards central South Africa, causing more
precipitation **
Subsidence over central South Africa will reduce shower activity
Feedback: The correct answers are A, B, and C. The low-pressure system over Namibia did, in fact, bring more
rainfall over the region, leading to the flooding of the Vaal Dam. Soil moisture levels in the region were very high
because of the persistent rainfall throughout January. The persistent rain and possibility of more rain from the
tropical low mean create a situation that must be monitored very closely.
Page 2: Taking Action
When flooding is possible, as it is in this situation, what should you do? What actions should yo take?
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Issue warnings to the public **
Wait for more actual precipitation data before making a decision
Contact the region’s hydrological management structures and alert them about the expected rainfall ***
Leave the situation to the hydrological authorities to address
Feedback: The correct answers are A and C. When flooding is possible, you should issue warning to regions in
danger, using print, online, and broadcast media, as soon as possible. Being proactive is important; it's better to
take action than to assume that someone else will do it. You should also contact the region's hydrological
management structures and give them an early warning that more rainfall is expected in the region. Waiting for
them to contact you would lead to the loss of valuable time and could undermine their ability to properly manage
an emergency situation.
Page 3: Combined 15-Day Rainfall Accumulation vs. Dam Capacity
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This rainfall accumulation vs. dam capacity graph shows what happened from 15 through to 30 January. When
did the Vaal Dam reach 100% capacity? Choose the correct answer.
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19 to 20 January
21 to 22 January
23 to 24 January **
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25 to 26 January
27 to 28 January
29 to 30 January
Feedback: The correct answer is C. The dam reached its capacity on 23 to 24 January. Because of the time lag
between the next rainfall event and its arrival at the dam, the dam reached 110% of its capacity on 30 January.
Page 4: Real-Time Vs. Predicted Capacity of the Dam
inflow_outflow_rates_vdaam.jpg spec and get CR. Department of Water Affairs
This hydrology graph shows actual and predicted inflow and outflow rates for the Vaal Dam and its capacity
levels through 15 February. The actual figures go from 20 January to 10 February, while the predicted figures
extend from 10 to 15 February.
Based on this information, when was it MOST critical to provide hydrological management structures with highly
accurate forecasts of precipitation amounts, timing, and intensity?
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21 to 27 January **
27 to 31 January
1 to 6 February
Feedback: The correct answer is A. As the green line shows, the dam’s capacity increased rapidly from 21 to 27
January from 94% to 105%. More rain was expected in the following days, which would increase already high
ground moisture levels. Since the hydrological situation was expected to worsen considerably, hydrological
management structures would need as much meteorological information as possible (possibly more than once
per day) as quickly as possible.
The situation from 27 to 31 January was also critical but the management structures would have been fully aware
of the risks by this stage and taken the necessary safety measures.
Note how conditions stabilized between 1 and 6 February, with the inflow of water into the dam decreasing
steadily.
Page 5: Conclusion
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inflow_outflow_rates_vdaam.jpg spec and get CR. Department of Water Affairs
To summarize the situation, the Vaal Dam reached 100% capacity on 23 to 24 January. It peaked on 30 January
from additional heavy rainfall. After that, inflow into the dam started to decrease. However, its capacity remained
above 100% due to the natural delay in the rainfall’s arrival at the dam.
Flooding events such as this often have severe impacts on lives, property, and infrastructure. Roads and bridges
are often damaged or washed away, and people lose their lives as they try to cross raging rivers. Although
regular rainfall is mostly welcomed by the agricultural community, heavy and persistent rainfall events can leave
fields waterlogged and crops ruined.
SECTION 8: SOIL MOISTURE PRODUCTS
Page 1: ASAR GM Data
Soil moisture products provide important information for understanding the state of the land surface when rainfall
is expected. When soil moisture values are high, the ground may not be able to absorb heavy rainfall. It usually
becomes run-off, which can cause flash flooding in localized areas and increase the water level in broader
regions.
We'll look at three soil moisture products, ASAR GM, ASCAT, and SMOS.
The ASAR GM soil moisture product has been developed within the scope of the SHARE (Soil Moisture for
Hydrometeorological Applications) project. SHARE is an ESA DUE Tiger project that provides an operational soil
moisture monitoring service for user communities such as the Southern African Development Community
(SADC), Australia, and portions of Argentina. Using ENVISAT's ASAR sensor, SHARE provides frequent (up to
twice-weekly) high-resolution measurements of regional soil moisture dynamics. In particular, the data
demonstrate the level of saturation of the upper < 3 cm of the soil layer, with the values ranging from 0
(completely dry) to 100 (saturated). For more information, see http://www.ipf.tuwien.ac.at/radar/dv/asar/.
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These ASAR GM soil moisture maps for the South African region show the percentage of soil moisture on 7 and
29 January 2010. On which day was Area A at a higher risk of flooding?
 7 January
 29 January**
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Feedback: The correct answer is B. The soil moisture values at area A ranged from 25% to 50% on 7 January
and increased to 75% to 100% on 29 January. Clearly the area was at greater risk for flooding after 29 January if
more rainfall hit the area, especially if it was heavy.
You can see how ASAR GM data are useful complements to other types of data in heavy rainfall situations.
Remember that whenever there’s a risk of flash flooding, you should immediately issue a warning. Do so in
consultation with the hydrological department if at all possible. If it's not possible, it is important to be be proactive. Never assume that someone else will take care of the situation!
Page 2: ASCAT Soil Moisture Product
Polar-orbiting satellites equipped with scatterometers provide useful information about land surface conditions
since they measure global soil moisture values. Polar orbiters have relatively coarse spatial resolution (up to 12.5
km), but they scan almost all regions twice daily, providing data on a relatively frequent basis.
If you are not familiar with scatterometers, they are satellite-based microwave sensors that were originally
intended to derive wind vectors over the ocean surface. Many other applications have since been developed,
including estimates of soil moisture values.
The ASCAT scatterometer on the MetOp polar orbiter takes direct soil moisture observations, which are
converted into soil moisture products. These are available from EUMETSAT twice a day. Many environmental
fields make extensive use of these products, including meteorology and weather forecasting; water management
and drought monitoring; and crop yield forecasting. The data are also used by early warning systems. For more
information on the product, please visit:
http://www.eumetsat.int/Home/Main/DataProducts/ProductNavigator/index.htm and search for ASCAT soil
moisture.
Here's an sample soil moisture product from ASCAT from February 2007 (a different period than the case). The
product shows the moisture content of 5 cm of the topsoil layer in relative units ranging from 0 (dry) to 100%
(saturated).
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Which area has the highest soil moisture values and would be more prone to flooding if a heavy rainfall event
occurred?


Area A (the Netherlands) **
Area B (the eastern coast of Italy)
Feedback: Surface soil moisture values are at 100% in parts of the Netherlands, while the eastern coast of Italy
has values between 0 and 25%. Based solely on this information, you can assume that areas with high soil
moisture content are at a greater risk of flooding if a heavy rainfall event occurs.
Page 3: SMOS Product
The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission supplies global
observations of soil moisture over land.
Assimilating surface moisture information into models results in better estimates of the water content in soil down
to one to two meters, the area called the "root zone." Estimates of root zone moisture improve hydrological
modeling and short- and medium-term meteorological forecasts, and are used to forecast floods, droughts, and
other hazardous events.
SMOS provides global maps of soil moisture every three days. These maps have a spatial resolution of 50 km
and are accurate to within 4%. For more information on SMOS, see http://www.cp34smos.icm.csic.es/smos_mission/smos_mission.htm
SECTION 9: FLASH FLOOD GUIDANCE
Page 1: SAWS Flash Flood Guidance System
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As you'll recall, SAWS and the National Disaster Management Centre (NDMC) operate the South African Flash
Flood Guidance (SAFFG) system. SAFFG incorporates meteorological and hydrological data and is based on the
American system, which pre-calculates the amount of rainfall required in a basin for a river to overflow its banks.
SAFFG lets forecasters be very specific in their flash flood warnings as to which areas are at risk and/or need to
be monitored. The system lets SAWS issue flash flood warnings to disaster management structures and the
public, which can save lives and infrastructure.
If you work in a country with SAFFG or a comparable system, you should make full use of it and work towards
improving early warning systems for flash flooding and flooding events. If a system is not available, you should
find out where and how to obtain hydrological data and start integrating them with forecasting products. This will
improve the quality and timings of warnings for flooding and flash flooding events.
Since the system was not operational at the time of the case, no data are shown for it.
SECTION 10: CONCLUSION & REFERENCES
Page 1: From 1996 to 2010
If we compare the 2009/2010 Vaal Dam flood event to one that occurred in the same area in 1996, we can see
how much has changed in a relatively short time.
In 1996:



Meteorologists and forecasters relied on rainfall reports and communications with hydrological
departments to understand how much rain had fallen and how the soil was reacting to it
NWP models had much coarser temporal and spatial resolution
Forecasters in South Africa could not overlay NWP and satellite data
In 2010:



The range and quality of remote sensing products have improved vastly, based mainly on the upgrade
from Meteosat First Generation (MFG) to Meteosat Second Generation (MSG) satellite imagery
With 12 rather than 3 channels of data, MSG users have far more precise information about the
atmosphere and land surface and have many more channels to manipulate and develop into
multispectral products
Many meteorological and hydrological products have been developed based on MSG imagery, including
the Hydro-Estimator and soil moisture products; these products help today's forecasters more fully
understand the factors that influence flash flooding in their regions
Page 2: Recommendations
Having completed the module, we hope that you have a clear sense of the value of combining various types of
data and information when dealing with possible flooding events. If you rely solely on hydrological or
meteorological data, you will not have the holistic understanding of the state of the atmosphere and Earth’s
surface required to, for example:


Determine the amount of rain needed before flash flooding can occur
Determine whether the buildup of soil moisture over a rainfall season can result in flash flooding, even
with relatively low amounts of precipitation
Finally, we encourage you to do the following:
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


Use the latest tools in conjunction with real-time data and other forecast products when dealing with
potential flood situations
Be familiar with how and where to gather hydrological data in your country or region. Research how best
to combine these data with meteorological products so you have a full understanding of surface and
atmospheric conditions at all times
Share expertise and information about water management and predicted precipitation with hydrologists
Page 3: References
Asnani, GC, 2005: Tropical Meteorology. Noble Printers, Pune, India, 1202 pp, second Edition
De Coning, E., Forbes, G. S. and Poolman, E. R. March 1998. Heavy precipitation and flooding on 12-14
February 1996 over the summer rainfall regions of South Africa: synoptic and isentropic analyses. National
Weather Digest, 22(3), 25-36.
De Coning, E. and Poolman E., 2010. South African Weather Service Operational Satellite Based Precipitation
Estimation Technique: Applications and Improvements, South African Weather Service. http://www.hydrol-earthsyst-sci.net/15/1131/2011/
MetEd training modules: http://meted.ucar.edu/
Meteosat Second Generation satellites and ASCAT instrument: http://www.eumetsat.int
Poolman, E., 2010: ‘Too much water, too little time”: Enhancing preparedness against flash flooding disasters in
South Africa, South African Weather Service.
SHARE (Soil Moisture for Hydro-meteorological Applications), University of Vienna,
http://www.ipf.tuwien.ac.at/radar/share/
SMOS: http://www.cp34-smos.icm.csic.es/smos_mission/smos_mission.htm and
http://www.esa.int/SPECIALS/smos/SEMMP9BE8JG_0.html
Stream Order in the Orange-Senqu River Basin:
http://www.orangesenqurak.org/river/hydrology/principles+/stream+order.aspx
Vaal Dam: http://www.gautenghappenings.co.za/vaal_dam_homepage.htm
VAAL Dam Flood Monitoring System: http://www.delportdupreez.co.za/html/html/dpa_vwil.htm
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