The Falling Lake Victoria Water Level: GRACE, TRIMM and CHAMP ...

Water Resour Manage (2008) 22:775–796 DOI 10.1007/s11269-007-9191-y

The Falling Lake Victoria Water Level: GRACE, TRIMM and CHAMP Satellite Analysis of the Lake Basin Joseph L. Awange · Mohammad A. Sharifi · Godfrey Ogonda · Jens Wickert · Erik W. Grafarend · Monica A. Omulo

Received: 23 June 2006 / Accepted: 10 May 2007 / Published online: 7 July 2007 © Springer Science + Business Media B.V. 2007

Abstract In the last 5 years, Lake Victoria water level has seen a dramatic fall that has caused alarm to water resource managers. Since the lake basin contributes about 20% of the lakes water in form of discharge, with 80% coming from direct rainfall, this study undertook a satellite analysis of the entire lake basin in an attempt to establish the cause of the decline. Gravity Recovery And Climate Experiment (GRACE), Tropical Rainfall Measuring Mission (TRMM) and CHAllenging Minisatellite Payload (CHAMP) satellites were employed in the analysis. Using 45 months of data spanning a period of 4 years (2002–2006), GRACE satellite data are used to analyse the variation of the geoid (equipotential surface approximating the mean sea level) triggered by variation in the stored waters within the lake basin.

J. L. Awange (B) Western Australia Center of Geodesy & The Institute for Geoscience Research, Department of Spatial Sciences, Curtin University of Technology, Bentley, Australia e-mail: [email protected] M. A. Sharifi Surveying and Geomatics Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran G. Ogonda Institute of Navigation, Stuttgart University, Geschwister-Scholl Str. 24D, 70174, Stuttgart, Germany J. Wickert Department 1: Geodesy and Remote Sensing, GeoForschungsZentrum Potsdam (GFZ), Telegrafenberg, 14473 Potsdam, Germany E. W. Grafarend Department of Geodesy and Geoinformatics, Stuttgart University, Geschwister-Scholl Str. 24D, 70174 Stuttgart, Germany M. A. Omulo Department of Environment, Maseno University, Private Bag, Maseno, Kenya

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TRMM Level 3 monthly data for the same period of time are used to compute mean rainfall for a spatial coverage of .25◦ × .25◦ (25 × 25 km) and the rainfall trend over the same period analyzed. To assess the effect of evaporation, 59 CHAMP satellite’s occultation for the period 2001 to 2006 are analyzed for tropopause warming. GRACE results indicate an annual fall in the geoid by 1.574 mm/year during the study period 2002–2006. This fall clearly demonstrates the basin losing water over these period. TRMM results on the other hand indicate the rainfall over the basin (and directly over the lake) to have been stable during this period. The CHAMP satellite results indicate the tropopause temperature to have fallen in 2002 by about 3.9 K and increased by 2.2 K in 2003 and remained above the 189.5 K value of 2002. The tropopause heights have shown a steady increase from a height of 16.72 m in 2001 and has remained above this value reaching a maximum of 17.59 km in 2005, an increase in height by 0.87 m. Though the basin discharge contributes only 20%, its decline has contributed to the fall in the lake waters. Since rainfall over the period remained stable, and temperatures did not increase drastically to cause massive evaporation, the remaining major contributor is the discharge from the expanded Owen Falls dam. Keywords Lake Victoria · Water balance · Tropopause temperature · Rainfall · CHAMP · GRACE · TRMM 1 Introduction Lake Victoria, the world’s third largest lake and the largest in developing world, is a source of water for irrigation, transport, domestic and livestock uses, and supports a livelihood of more than 30 million people living around it (Awange and Ong’ang’a 2006). Nicholson (1998, 1999) document its significance as an indicator of environmental and climate change on long term scales. Though the lake has continued to attract worldwide attention due to its importance, its recent decline has caused great alarm as to whether the lake is actually drying up! Since the 1960s, the lake level has experienced significant fluctuation (see, e.g., Nicholson 1998, 1999). However, the water levels is reported by Riebeek (2006) to have experienced a drastic drop in the last five years causing great alarm. According to Kull (2006), the lake levels have dropped by more than 1.1 m below the 10 year average. This value is however still low compared with those reported for other lakes, e.g., Lake Qinghai (Li et al. 2007). Decline of lakes have also been reported e.g., in Mendoza et al. (2006) and Xia et al. (2006). With the receding of the lake waters, acres of lands that were lost to the floods of the 1960s are fast being reclaimed, creating sources of conflicts between man and wildlife. In some beaches, e.g., Usoma in Kenya, wetlands that were once breeding places for fish are dying up leaving chunks of land as playing fields for children and farmlands. Ships are now forced to dock deep inside the lake, while the landing bays seem to be extended for the boats that dock. Those who directly depend on the lake waters for domestic use are now forced to go deep into the lake to draw water, thus exposing women and children to water borne diseases and risks of snakes and crocodiles. Water intakes supplying major towns and cities have to be extended deep into the lake, thus causing more financial burden to the already strained Municipalities.

GRACE, TRIMM and CHAMP satellite analysis of the lake basin

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Lake’s surface water, together with ground waters, soil moisture and snow constitute stored water. Changes in the lake level are directly related to the variation of the water stored in its basin which contributes 20% inform of river discharge. Since the lake is supplied both by direct rainfall (Phoon et al. 2004; Nicholson 1998) and the river discharges, a decrease in stored basin water will contribute to a drop in the lake level. An analysis of the stored water in the Lake Victoria basin in relation to rainfall and evaporation is therefore necessary as a first diagnosis to the fall. It provides water resource managers and planners with information on the state and changing trend of the stored water within the basin. This could be achieved through the use of the latest state of the art satellite known as GRACE (see, e.g., Dunn et al. 2003; Tapley and Reigber 2004). Previous methods for studying variation in stored water include e.g., the Artificial Neural Network (Altunkaynak 2006) and GIS (Geographical Information System) and remote sensing (Kalivas et al. 2003; Mendoza et al. 2006). Besides monitoring the variation in stored water within rivers and lake basins, GRACE satellite will also play a role of validating models which have been applied to study stored water e.g., (Owes and Taimeh 1996; Xu and Singh 2004; Xu et al. 2007; Loukas et al. 2006; Mylopoulos et al. 2006). GRACE satellites had been recognized by Hildebrand (2005) as having the potential to provide the first space based estimate of terrestrial stored ground water. Applications of GRACE satellite to monitor and analyse terrestrial water storage changes, e.g., those of Congo, Mississippi and Amazon basins, are documented e.g., in Rodell and Familglietti (2001); Tapley et al. (2004a,b), Rodell et al. (2004, 2005), Ramillien et al. (2004, 2005), Smith et al. (2005) and Crowley et al. (2006). In this contribution, we provide an in-depth satellite analysis of the lake basin during the period of 2002 to 2006, when the lake waters declined. GRACE satellites are used to analyse the variation in the basin’s stored water while TRMM and CHAMP satellites are used to analyse rainfall and temperature within the basin respectively. We organize the present contribution as follows; in Section 2, a brief background of Lake Victoria and its basin is presented, while Section 3 presents an overview of the GRACE, TRMM and CHAMP satellite missions. Section 4 looks at the Method, while Section 5 analyses the results. The study is concluded in Section 6.

2 Background of Lake Victoria and its Basin Here, only a brief background of Lake Victoria is presented, e.g., from Awange and Ong’ang’a (2006). For more details we refer the reader to this book. Lake Victoria is located at longitude 31◦ 39 E–34◦ 53 E and latitude 0◦ 20 N–3◦ S, and has a surface area of ca. 68,635 km2 . Its greatest length is about 400 km, and breadth of about 320 km. It contains about 2,760 km3 of water and is situated at an altitude of 1,135 m above mean sea level. The shoreline is very irregular and totals some 3,300 km in length. Much of the lake is relatively shallow, reaching a maximum depth of about 80 m, with the deepest zone (60–90 m) lying toward the shore. There is little annual variation in water temperatures, the mean surface being about 24◦ C and that of deeper waters to be 23◦ C. Its basin spreads from longitude 30◦ E–35◦ 50 E to latitude 0◦ N–3◦ 20 S. Of the total basin area of 193,000 km2 (Fig. 1), Burundi accounts for 7.2%, Kenya 21.5%, Rwanda 11.4%, Tanzania 44.0% and Uganda 15.9%. The entire drainage basin covers an area

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Fig. 1 Lake Victoria basin (from Kayombo and Jorgensen 2006)

of 258,000 km2 . The lake is also the source of the Victoria Nile (white Nile), the world’s second longest river after the Mississippi river in the USA. Lake Victoria contributes much to the regional rainfall and subsequently the hydrological cycle. Of particular importance to Lake Victoria are the South-East trade winds which picks moisture from the lake while passing. They move to the northern and western shores of Lake Victoria where they eventually condense to give heavy rainfall. Uganda benefits more due to the fact that winds carry more moisture to the Northwest shores of Lake Victoria. Major rainfall season is normally between March, April and May (MAM), with low rainfall season occurring between September, October and November (SON).

3 Basics of Satellite Missions 3.1 GRACE Satellites GRACE satellites, which comprise of twin satellites (see, e.g., Fig. 2) was launched on 17th of March 2002 with the main task of providing detailed measurements of Earth’s gravity field which will lead to more discoveries about gravity and Earth’s natural systems. These discoveries are expected to have far-reaching benefits to society and the world’s population. GRACE mission is a joint partnership between the National Aeronautics and Space Administration (NASA) in the USA and Deutsche Zentrum für Luft und Raumfahrt (DLR) in Germany.


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Fig. 2 GRACE satellites (source: http://earthobservatory. nasa.gov/Study/WeighingWater/ printall.php)

The GRACE mission is expected to accurately map variations in the Earth’s gravity field over its 5-years lifetime (at least 10 years are expected). Likewise, GRACE is also expected to exceed its design life, though atmospheric drag as the satellite descends will ultimately end the mission (cf. Wagner et al. 2006). It has two identical spacecrafts flying in tandem at about 220 km apart in a near polar (inclination = 89◦ ) orbit around 450 km (as of May 2007) above the Earth (Fig. 2). By measuring the range rate (change in distance between the satellite with time), using GPS and a microwave ranging system, time varying gravity field can be accurately mapped. The mission is currently providing scientists with an efficient and costeffective way to map the Earth’s gravity fields with unprecedented accuracy and in the process yield crucial information about the distribution and flow of mass within the Earth and it’s surroundings. GRACE satellites measures changes in Earth’s gravity field by measuring the distance between the two satellites every five seconds. The variation in the distance between the two twin satellites is believed to be caused by gravitational variation above, below, and beneath Earth’s surface which has a pull effect on the satellites. This variation in gravity could be due to rapid or slow changes caused, e.g., by mass of the Earth or mass redistribution of water in the oceans, movement of water vapor and other components in the atmosphere. GRACE data must therefore be pruned to isolate these effects so as to retain only those which correspond to stored water. GRACE satellites take almost one month to scan the entire Earth and as such, may not be suitable for detecting fast changing phenomenon (i.e., those changing in less than one month) such as ocean tides or weather systems moving across the planet. The gravity variations that GRACE will study include (e.g., Ramillien et al. 2004; Rodell and Famiglietti 2005); • • • • •

Changes due to surface and deep currents in the ocean, Runoff and ground water storage on land masses, Exchanges between ice sheets or glaciers and the oceans, Air and water vapour mass change within the atmosphere, and Variations of mass within the Earth.

Another goal of the mission is to create a better profile of the Earth’s atmosphere through satellite remote sensing (occultation) and thus contribute immensely to

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global climate change studies (Awange and Grafarend 2005; Awange and Ong’ang’a 2006). Consider the geoid to coincide with the mean sea level. Any vertical change in the sea level is equivalent to a vertical change in the geoid (i.e., geoidal variation). If the mean surface of the ocean was to be projected into land, any removal or addition of mass will alter its position. A change of mass within the lake’s basin through additional water (during precipitation) or removal of water (during evaporation or other means) will cause a positive or negative variation of the geoid respectively. An analysis of the variation of the geoid in the basin, therefore, will remotely sense the stored water. To use GRACE satellites to analyse the stored water in Lake Victoria basin, temporal geoidal variation has to be analysed using satellite observations of timedependent gravity data. Determination of the variation of geoid from gravity data has been elaborately presented by, e.g., Wahr et al. (1998) and Hinderer et al. (2006). In applying GRACE satellites to the analysis of stored water of Lake Victoria basin, it is important to note that exact amount of water stored within the basin is not measured from space. Instead, an indication of the changes in storage water with time (i.e., over a month, a season, or a year) is deduced from geoidal variation. For this study, GRACE monthly solution from Center for Space Research (CSR) Texas was used. For hydrological purposes, Rodell and Familglietti (2001) recommend basin sizes greater than 200,000 km2 for a precision of a few millimeters in water thickness. Since Lake Victoria’s entire drainage basin covers an area of 258,000 km2 (Awange and Ong’ang’a 2006), it is possible to apply GRACE satellite to study the changes in stored water within the lake’s entire drainage basin on monthly basis. 3.2 TRMM Satellite Due to the extreme difficulty of obtaining surface rainfall data for the entire basin and also directly over the lake, this study used the TRMM data (Kummerow and Barnes 1998; Viltard et al. 2006; Shige et al. 2006; Sanderson et al. 2006; Amitai et al. 2006; Dinku and Anagnostou 2006) are adopted. TRMM satellite, jointly managed by National Aeronautics and Space Administration (NASA) of the USA and Japan Aerospace Exploration Agency (JAXA) was designed to monitor and study tropical rainfall. It has the advantage of providing four dimensional (X,Y,Z,t) rainfall and latent heat data over inaccessible areas such as the ocean, un-sampled terrains, etc. The primary rainfall parameters on TRMM are the TRMM Microwave Imager (TMI), the Precipitation Radar (PR) and the Visible and Infrared Radiometer System (VIRS; Kummerow and Barnes 1998). 3.3 CHAMP Satellite Radio occultation with GPS takes place when radio signals from a transmitting GPS satellite, setting or rising behind the Earth’s limb, are received by a Global Positioning System (GPS) receiver aboard a Low Earth Orbiting (LEO, e.g., CHAMP) satellite. The meteorological products of occultation comprise the air pressure P, air temperature T and the water vapour pressure Pw . By measuring the occulting GPS signal due to the effect of the atmosphere, CHAMP satellite (see, e.g., Reigber et al. 2005) is capable of providing accurate tropospheric measurements to sub-kelvin


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accuracy (see, e.g., Awange and Grafarend 2005; Awange et al. 2004; Melbourne et al. 1994; Steiner 1998; Tsuda et al. 1998; Wickert et al. 2003, 2004, 2006a,b; Gurbunov et al. 1996; Vorob’ev and Krasil’nikova 1994).

4 Materials and Methods In order to obtain time varying gravity field due to mass redistribution of the lake basin water, the larger effect of gravity variation due to the mass of the Earth, which is always constant G0 corresponding to nearly 99% of the total field is computed from the model GGSM01S Tapley et al. (2004a) and removed by subtracting it from the monthly geoid (G(t)) measured by GRACE at a time t (Ramillien et al. 2005), i.e., δG(t) = G(t) − G0 ,

(1)

to give the monthly time-variable geoid δG(t). Changes mostly related to the atmosphere and ocean which occur over a timescale shorter than one month, are then removed using atmospheric and ocean models (see, e.g., Wahr et al. 1998). The resulting difference in Eq. 1, which is called gravity anomaly or geoid variation is due to water storage changes. If we consider δCnm (t) and δSnm (t) to be normalized Stokes coefficients expressed in terms of millimeters of geoid height, with n and m

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Fig. 3 Global monthly geoid variation for 2003. The Amazon basin’s signals are compared to those of Tapley et al. (2004b) in Fig. 4. The Amazon basins signals from both figures matches

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Fig. 4 Global monthly geoid variation for 2003 (Tapley et al. 2004b)

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being degree and order respectively, the time-variable geoid in Eq. 1 is expanded in-terms of spherical harmonic coefficients as δG(t) =

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where N is the maximum degree of decomposition, θ is the co-latitude, λ the longitude and Pnm fully normalized Legendre polynomial (Heiskanen and Moritz 1967). The first steps in the analysis of GRACE data of the lake basin would provide an estimate of total water storage change that includes all ground water, soil moisture, snow, ice, and surface waters within the basin. In the second step (still under intensive research), the changes can then be separated into various components as discussed in Ramillien et al. (2004, 2005). For the purpose of this study, we limit ourselves to the first step and apply Eq. 2 to compute the monthly time-varying geoid which is caused by variation of water within the lake basin. For the lake basin, TRMM rainfall data provides not only the frequency and aerial coverage of data, but also high resolution spatial (25 × 25 km) and temporal (monthly) data which are not achievable using surface methods such as rain gauges. This study employed data from Algorithm 3B-43 which produced monthly bestestimate gridded precipitation rate and root-mean-square (RMS) precipitation-error estimates at a spatial coverage of 25 × 25 km (TSDIS 2006). In order to access whether significant temperature change occurred during these period, we analyzed any significant change in tropopause temperature and height for the region. Due to difficulty in obtaining radiosonde data, CHAMP vertical profiles of temperature were analyzed. Level 3 CHAMP data which were obtained from GeoForschungsZentrum (GFZ) Potsdam, Germany, comprised of atmospheric


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and ionospheric products. The same data can also be obtained from Jet Propulsion Laboratory (JPL) and UCAR (University Corporation for Atmospheric Research). Level 3 data contain profiles of refractivity, dry air temperature, air density, air pressure, bending angles, position (latitude, longitude), height above mean sea level, impact parameters, and signal to noise ratio.

5 Analysis 5.1 GRACE Geoid Variation


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As a first step, we had to validate our GRACE algorithm by computing the global variation of geoid for the year 2003 (Fig. 3) and compare them to those of Tapley et al. (2004b) in Fig. 4. Looking at the Amazon basin in the figures, it is clearly evident that our algorithm picked the same signals as those of Tapley et al. (2004b), and therefore justify its use for analysis of Lake Victoria basin. Using Eq. 2, monthly geoid variation from GRACE data for the period April 2002 up to April 2006 were then computed. The results are presented in Figs. 5 to 8. A comparison of the monthly geoidal variations from 2002 to 2005 gives a clear picture of the variation in the stored water of the Lake Victoria basin. In 2002 (Fig. 5), GRACE satellite data were available only for 5 months. For these months, the month


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Fig. 9 Inter-annual comparison for geoidal variation during the high rainy season of MAM from 2002-2006

of August show decrease in geoid level. The other months of April, November and December indicate a positive variation of between 2 to 8 mm of the geoid indicating a net gain in mass, i.e., water. In 2003 (Fig. 6), January, May, and June recorded a rise in geoidal level by 4 mm. The rest of the months indicate values between 1–2 mm.

Geoidal height variations [mm]

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Fig. 10 Time series of geoid 2002 to 2006

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Moving on to 2004 (Fig. 7), all the months except April indicated a drop in geoid level, thus loss of water. In May, only the North-West part of the basin shows an increase in geoid level of about 1 mm. This is the part of the basin which normally receives high amount of rainfall. July and August also show some 2 mm rise in geoidal level in the Eastern part of the basin. In 2005 (Fig. 8), a fall in the geoidal height occurs in all months except July, signifying a further drop in water level within the basin. Figure 9 presents the annual variation of the geoid in the lake basin during the high rainy season months of March, April and May (MAM) for the period 2002–2006. The figure clearly indicates decline of stored water in the basin. Since the monthly geoidal variation are triggered by variation in stored water, then clearly the basin is loosing its stored water. Inter-annual comparison from March 2003 to March 2006 indicate an annual reduction in the basin’s stored water as evidenced by a geoidal variation from 2 mm (in March 2003) to −6 mm in March 2006 (i.e., a drop of about 8 mm in the geoid level). From April 2002 to April 2006, a steady decline of the geoid from about 5 mm in 2002 to −3 mm in 2006 is seen, a general reduction of about 8 mm in geoid variation. For the month of May, comparison from 2003 to 2005 also

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Fig. 12 Time series of rainfall 2001 to 2006

show a drop in the geoidal variation from 5 mm to 1 mm, a reduction of about 6 mm in geoid. To observe a clear trend of the geoidal variation, a time series graph is plotted in Fig. 10. From this figure, the geoidal level is computed to fall at a rate of 0.13 mm/month (1.6 mm/year). Whereas this decline in geoidal level is in millimeter Fig. 13 Occultations within the lake basin 2001–2006


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range, the actual water volume loss caused by such variation for Lake Victoria basin with an area of 258,000 km2 is significant. Next, we analyse the rainfall pattern over the same period of time. 5.2 TRMM Rainfall Monthly TRMM rainfall data are sampled for the lake basin at a spatial resolution of 25 × 25 km from 2002 to 2006. In Fig. 11, annual comparison for the high rainfall seasons of MAM for the period 2002–2006 is provided. The figure indicates the direct rainfall on the lake to have been intense during the month of April throughout 2002 to 2006 (i.e., between 200–300 mm) but no clear pattern emerges to suggest any reduction in the basin rainfall. To provide a clear picture, we plotted a time series basin mean monthly rainfall for the entire period 2006–2006 (Fig. 12). From the figure, no clear trend is seen to suggest a drastic reduction in rainfall over the basin during this period. The rainfall data from TRMM as previously mentioned is an average over a 25 × 25 km spatial coverage. EAC (2006) surface rainfall data indicated a similar trend to the TRMM data. Though no drastic reduction in rainfall is noted in Fig. 12, EAC (2006) however suggest that the amount of the rainfall during this period is relatively

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Fig. 15 Temperature profile for occultation 195 of 25th July 2004

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small compared to previous years, and thus a long term reduction in rainfall could also have contributed to the fall in the lake level. This calls for future analyses of draught versus the lake level, which will be reported in our future contributions. 5.3 CHAMP Tropopause Analysis Temperature profiles computed are presented in CHAMP Level 3 data discussed in details by Wickert et al. (2004). Using the entire spectrum of CHAMP Level 3 data, those of Lake Victoria basin (longitude: 30◦ E–36◦ E; latitude: 1◦ N–3◦ 20 S) were selected. Figure 13 presents the position of occultation within the lake basin for the

Mean monthly tropopause temperatures (2001–2006) 200 198

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196 194 192 190 188 186 184 A S ON D J F MAM J J A S ON D J F MA M J J A S ON D J F MA M J J A S ON D J F MAM J J A S ON D J F MA M J J A S O Month

Fig. 16 Time series tropopause temperatures


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Mean monthly tropopause heights (2001–2006) 18.5

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Fig. 17 Time series tropopause heights

period 2001–2006. In total, 53 occultations took place directly within the lake basin and its neighbourhood. Whereas Fig. 13 show the position of the occultations to be well distributed within the basin, an understanding of the occultations which occurred every month for the period 2001 to 2006 is presented in Fig. 14. Though the occultation data within the lake basin is sparse compared to other mid-latitude regions, nonetheless, the data is sufficient to provide an indication on any significant change in tropopause temperature over the study period. For each occultation, temperature profile graphs are plotted and the tropopause temperature and height selected (see, e.g., Fig. 15). In this study, the tropopause is defined according to the World Meteorology Organization (WMO) definition

Fig. 18 Mean annual tropopause temperatures for the lake basin from 2001 to 2006

Mean Yearly Tropopause Temperatures (2001–2006) 195 194

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Fig. 19 Mean annual tropopause heights for the lake basin from 2001 to 2006

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(WMO 1986). For occultation number 195 which occurred at 1.9◦ S, 32.7◦ E on 25th of July 2004 from 21 h 20 min 27 s for example, the temperature profile are as plotted in Fig. 15. In order to obtain a meaningful deduction, we computed the time series for tropopause temperatures and height for the study periods (Figs. 16 and 17). Annual means of the basin’s tropopause temperatures and heights depicted in Figs. 18 and 19 respectively are thereafter computed. From the time series Figs. 16 and 17, a uniform trend is maintained where the tropopause temperatures are between 188–194 K, and the heights between 16.7–17.7 m. Figure 18 indicates an annual decrease in the tropopause temperature by 3.9 K from 2001 to 2002. Thereafter, there was an increase of 2.2 K in temperature in the following year. Though there was a drop from 2003 to 2005 by about 1.8 K, an increase is noticed thereafter up to 2006. A significant point to note from the Figure however, is the fact that these temperatures have remained relatively above the lowest value of 2002 by more than 0.4 K. This point is corroborated by the heights data of Fig. 19, where an increase is noticed from 2001 to 2002 of about 0.58m. This is followed by a subsequent fall in height by 0.33 m in 2003. Thereafter, the tropopause heights increase by 0.62 m to reach the highest value in 2005. Significant to note is the fact that the heights remain above the lowest value of 2001 by more than 0.87 m.

6 Conclusions The following facts have been established following the satellite analysis of the Lake basin: 1. From the GRACE analysis of the geoidal (gravity field) variation of the lake basin, a fall of the geoid level at a rate of 1.6 mm/year was observed. This signifies an annual loss of the basin’s stored water during the period of 2002 to 2006. Since the basin catchment discharge contributes about 20% of the Lakes hydrology,


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the reduction of the basins stored water contributed to the decline of the 20% input to the lake and thus reduction in the Lake’s waters. 2. Reduction in rainfall over the basin during the period from 2002 to 2006 from TRMM data was not so significant to trigger rapid fall in the lake level. However, EAC (2006) observes (from surface data) a general decline in the rains on the lake and its basin in recent years. A draught analysis of rainfall versus the lake levels spanning climatological time frame (30 years) is essential. This is subject of ongoing research and will be reported in future contributions. 3. CHAMP satellite data indicated there was an increase of 2.2 K in tropopause temperature in the from 2002 to 2003 and that the tropopause temperatures have remained relatively above the lowest value of 2002 by more than 0.4 K. Though the CHAMP satellite data used was sparse, EAC (2006) also not an increase in surface data by 1◦ C. This amount of increase in temperature could have contributed to evaporation but not at a scale to cause rapid decline of the lake. 4. The increased withdrawal of the water from the lake basin could also attributed to the expansion of the Owen Falls (now consisting of the original Naluabaale Dam and the new Kiira Dam extension) as pointed out in EAC (2006). GRACE analysis of Lake Victoria’s basin has thus helped to reveal the trend in the decline of the basin’s stored water. This however could have contributed to a reduction of the 20% discharge into the lake. Since the TRMM rainfall analysis does not show a drastic drop in rainfall over the same period and the CHAMP satellite does not show massive increase in temperature to cause significant evaporation, the main culprit is the expanded Owen Falls dam, one of the conclusion pointed out in EAC (2006). The GRACE, TRIMM and CHAMP satellites thus offers objective and unbiased means for future monitoring water storage changes within Lake Victoria’s basin. Acknowledgements The first author wishes to acknowledge the support of DAAD (Germany Academic Exchange Program) for the financial support for the months of May–June 2006, the period which part of the study was undertaken at the Department of Geodesy and Geoinformatics, Stuttgart University, Germany. The author is further grateful for the support and the good working atmosphere provided at that time by his host Prof. Erik W. Grafarend. JLA further thanks Curtin Research Fellowship, the current sponsors at Curtin University and Technology. We also thank the satellite teams from the CHAMP, GRACE and TRMM missions. The work of these engineers and scientists is the base for our investigations.

References Altunkaynak A (2006) Forecasting surface water level fluctuations of Lake Van by Artificial Neural Networks. Water Resour Manag 21:399–408 Amitai E, Marks DA, Wolff DB, Silberstein DS, Fisher BL, Pippitt JL (2006) Evaluation of radar rainfall products: lessons learned from the NASA TRMM validation program in Florida. J Atmos Ocean Technol 23:1492–1505 Awange JL, Ong’ang’a O (2006) Lake Victoria: ecology, resources and environment. Springer, Heidelberg Awange JL, Grafarend E (2005) Solving algebraic computational problems in geodesy and geoinformatics. The answer to modern challenges. Springer, Berlin Awange JL, Fukuda Y, Takemoto S, Wickert J, Aoyama Y (2004) Analytic solution of GPS atmospheric sounding refraction angles. Earth Planets Space 56:573–587

794

J.L. Awange et al.

Crowley JW, Mitrovica JX, Bailey RC, Tamisiea ME, Davis JL (2006) Land water storage within the Congo Basin inferred from GRACE satellite gravity data. Geophys Res Lett 33:L19402. doi:10.1029/2006GL027070 Dinku T, Anagnostou EN (2006) TRMM calibration of SSM/I algorithm for overland rainfall estimation. J Appl Meteorol Climatol 45:875–886 Dunn C, Bertiger W, Bar-Sever Y, Desai S, Haines B, Kuang D, Franklin G, Harris I, Kruizinga G, Meehan T, Nandi S, Nguyen D, Rogstad T, Thomas JB, Tien J, Romans L, Watkins M, Wu S-C, Bettadpur S, Kim J (2003) Instrument of GRACE – GPS augments gravity measurements. GPS World, 1 February 2003 EAC (East African Community) (2006) Lake Victoria basin commission. Special report on the decline of water levels of Lake Victoria. EAC Secretariat, Arusha, Tanzania Gurbunov ME, Gurvich AS, Bengtsson L (1996) Advanced algorithms of inversion of GPS/MET satellite data and their application to the reconstruction of temperature and humidity, Rep. No. 211, Max-Plunk-Institut für Meteorologie. Hamburg, Germany Heiskanen WA, Moritz H (1967) Physical geodesy. Freeman and Company, London Hinderer J, Andersen O, Lemoine F, Crossley D, Boy JP (2006) Seasonal changes in the European gravity field from GRACE: a comparison with superconducting gravimeters and hydrology model predictions. J Geodyn 41:59–68 Hildebrand PH (2005) Toward an improved understanding of the global fresh water budget. A symposium on living with a limited water supply 85th AMS Annual Meeting, 9–13 January, San Diego Kalivas DP, Kollias VJ, Karantounias G (2003) A GIS for the assessment of the spatio-temporal changes of the Kotychi lagoon, western Peloponnese, Greece. Water Resour Manag 17:19–36 Kayombo S, Jorgensen SE (2006) Lake Victoria: experience and lessons learned brief. International Lake Environment Committee, Lake Basin Management Initiative, Kusatsu, Japan. Available at: http://www.ilec.or.jp/eg/lbmi/reports/27_Lake_Victoria_27February2006.pdf Kull D (2006) Connections between recent water level drops in Lake Victoria, dam operations and drought. Available at: http://www.irn.org/programs/nile/pdf/060208vic.pdf. Cited 18th May 2006 Kummerow C, Barnes W (1998) The tropical rainfall measuring mission (TRMM) sensor package. J Atmos Ocean Technol 15:809–817 Li XY, Xu HY, Sun YL, Zhang DS, Yang ZP (2007) Lake-level change and water balance analysis at Lake Qinghai, West China during recent decades. Water Resour Manag doi:10.1007/ s11269-006-9096-1 (in press) Loukas A, Mylopoulos N, Vasiliades L (2006) A modeling system for the evaluation of water resources management strategies in Thessaly, Greece. Water Resour Manag doi:10.1007/ s11269-006-9120-5 (in press) Mendoza ME, Bocco G, Bravo M, Granados EL, Osterkamp WR (2006) Predicting water-surface fluctuation of continental lakes: a RS and GIS based approach in Central Mexico. Water Resour Manag 20:291–311 Melbourne WG, Davis ES, Duncan CB, Hajj GA, Hardy K, Kursinski R, Mechan TK, Young LE, Yunck TP (1994) The application of space borne GPS to atmospheric limb sounding and global change monitoring. JPL Publ 94–18 Mylopoulos N, Mylopoulos Y, Tolikas D, Veranis N (2006) Groundwater modeling and management in a complex lake-aquifer system. Water Resour Manag 21:469–494 Nicholson SE (1998) Historical fluctuations of Lake Victoria and other lakes in the Northern Rift Valley of East Africa. In: Lehman JT (ed) Environmental change and response in East African lakes. Kluwer, Dordrecht, pp 7–35 Nicholson SE (1999) Historical and modern fluctuations of lakes Tanganyika and Rukwa and their relationship to rainfall variability. Clim Change 41:53–71 Owes TY, Taimeh AY (1996) Evaluation of small basin water harvesting system in arid region of Jordan. Water Resour Manag 10:21–34 Phoon SY, Shamseldin AY, Vairavamoorthy K (2004) Assessing impacts on Lake Victoria basin, Africa. 30th WEDC International Conference. Vientiane, Lao PDR Ramillien G, Cazenave A, Brunau O (2004) Global time variations of hydrological signals from GRACE satellite gravimetry. Geophys J Int 158:813–826 Ramillien G, Frappart F, Cazenave A, Güntner A (2005) The variation of land water storage from an inversion of 2 years GRACE geoids. Earth Planet Sci Lett 235:283–301 Reigber C, Schwintzer P, Lühr H, Wickert J (2005) Earth observation with CHAMP: results from three years in orbit. Springer Verlag


795

Riebeek H (2006) Lake Victoria’s falling waters. http://earthobservatory.nasa.gov/Study/Victoria/ printall.php Rodell M, Familglietti JS (2001) Terrestrial water storage variations over Illinois: analysis of observations and implications for GRACE. Water Resour Res 37(5):1327–1340 Rodell M, Famiglietti JS, Chen J, Seneviratne SI, Viterbo P, Holl S, Wilson CR (2004) Basin scale estimates of evapotranspiration using GRACE and other observations. Geophys Res Lett 31:(L20504)1–4 Rodell M, Johnson N, Famiglietti JS, Chen J, Seneviratne SI, Holl S, Viterbo (2005) Comparison of GRACE derived terrestrial water storage changes with model, water budget, and observation based estimates. A symposium on living with a limited water supply 85th AMS Annual Meeting, 9–13 January, San Diego Rodell M, Famiglietti JS (2005) The potential of satellite based monitoring of ground water storage changes using GRACE: The high plains aquifer, Central US. J Hydrol 263:245–256 Steiner AK (1998) High resolution sounding of key climate variables using the radio occultation technique. Dissertation, Institute for Meteorology and Geophysics, University of Graz No. 3 Sanderson VL, Kidd C, McGregor GR (2006) A comparison of TRMM microwave techniques for detecting the diurnal rainfall cycle. J Hydrometeorol 7:687–704 Shige S, Sasaki H, Okamoto K, Iguchi T (2006) Validation of rainfall estimates from the TRMM precipitation radar and microwave imager using a radiative transfer model: 1. Comparison of the version-5 and -6 products. Geophys Res Lett 33:L13803. doi:10.1029/2006GL026350 Smith AB, Walker JP, Western AW, Ellet KM (2005) Using ground-based gravity measurements to monitor changes in terrestial water storage. Engineers Australia 29th Hydrology and Water Resource Symposium 21–23, February 2005, Canberra Tapley B, Reigber C (2004) GRACE (Gravity Recovery and Climate Experiment). In: McGraw-Hill Yearbook of Science and Technology Tapley BD, Bettadpur S, Watkins MM, Reigber CH (2004a) The gravity recovery and climate experiment: mission overview and early results. Geophys Res Lett 31, L09607. doi:10.1029/2004GL019920 Tapley BD, Bettadpur S, Ries JC, Thompson PF, Watkins MM (2004b) GRACE measurements of mass variability in the Earth system. Science 305:503–505 TSDIS (2006) Tropical rainfall measuring mission science data and information system. Interface control specification between the Tropical Rainfall Measuring Mission Science Data and Information System (TSDIS) and the TSDIS Science User (TSU) TSDIS-P907, vol 4: File Specifications for TRMM Products – Level 2 and Level 3 Release 6.07, code 902 Tsuda T, Heki K, Miyazaki S, Aonashi K, Hirahara K, Tobita M, Kimata F, Tabei T, Matsushima T, Kimura F, Satomura M, Kato T, Naito I (1998) GPS meteorology project of Japan – Exploring frontiers of geodesy. Earth Planets Space 50(10):i–v Viltard N, Burlaud C, Kummerow CD (2006) Rain retrieval from TMI brightness temperature measurements using a TRMM PR-based database. J Appl Meteorol Climatol 45:455–466 Vorob’ev VV, Krasil’nikova TG (1994) Estimation of the accuracy of the atmospheric refractive index recovery from Doppler shift measurements at frequencies used in the NAVSTAR system. Phys Atmos Ocean 29:602–609 Wagner C, McAdoo D, Klokocník J, Kostelecký J (2006) Degradation of geopotential recovery from short repeat-cycle orbits: application to GRACE monthly fields. J Geod 80:94–103 Wahr J, Molennar M, Bryan F (1998) Time variability of the Earth’s gravity field: hydrological and oceanic effects and their possible detection using GRACE. J Geophys Res 103(B12): 30205–30229 Wickert J, Beyerle G, Schmidt T, Marquardt C, König R, Grundwaldt L, Reigher C (2003) GPS radio occultation with CHAMP. In: Reigber C, Lühr H, Schwintzer P (eds) First CHAMP mission results for gravity, magnetic and atmospheric studies. Springer, Heidelberg, pp 371–383 Wickert J, Schmidt T, Beyerle G, König R, Reigber C, Jakowski N (2004) The radio occultation experiment aboard CHAMP: operational data analysis and validation of vertical atmospheric profiles. J Meteorol Soc Jpn 82(1B):381–395, special issue application of GPS remote sensing to meteorology and related fields Wickert J, Schmidt T, Beyerle G, Michalak G, König R, Heise S, Reigher C (2006a) GPS radio occultation with CHAMP and GRACE: recent results. In: Foelsche U, Kirchengast G, Steiner A (eds) Atmosphere and climate: studies by occultation methods. Springer, Berlin, pp 3–16 Wickert J, Schmidt T, Beyerle G, Heise S, Reigber C (2006b) Global atmospheric sounding with GPS radio occultation aboard CHAMP. In: Flury J, Rummel R, Reigber C, Rothacher, M,

796

J.L. Awange et al.

Boedecker G, Schreiber U (eds) Observation of the Earth system from space. Springer, Berlin, pp 55–67 WMO (1986) Atmospheric ozone, Tech. Rep. 16. World Meteorological Organisation, Geneva, Switzerland 1986 Xia J, Zhang L, Liu C, Yu J (2006) Towards better water security in North China. Water Resour Manag 21:233–247 Xu CY, Singh VP (2004) A review on monthly water balance models for water resources investigations. Water Resour Manag 12:20–50 Xu L, Zhang Q, Li H, Viney NR, Xu J, Liu J (2007) Modeling of surface runoff in Xitiaoxi catchment, China. Water Resour Manag doi:10.1007/s11269-006-9083-6 (in press)