Month: October 2025

When the Lakes Remember: Unravelling the Sudd Floods of 2022

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By Douglas Mulangwa – d.mulangwa@pgr.reading.ac.uk

Between 2019 and 2024, East Africa experienced one of the most persistent high-water periods in modern history: a flood that simply would not recede. Lakes Victoria, Kyoga, and Albert all rose to exceptional levels, and the Sudd Wetland in South Sudan expanded to an unprecedented 163,000 square kilometres in 2022. More than two million people were affected across Uganda and South Sudan as settlements, roads, and farmland remained inundated for months.

At first, 2022 puzzled stakeholders, observers and scientists alike. Rainfall across much of the region was below average that year, yet flooding in the Sudd intensified. This prompted a closer look at the wider hydrological system. Conventional explanations based on local rainfall failed to account for why the water would not recede. The answer, it turned out, lay far upstream and more than a year earlier, hidden within the White Nile’s connected lakes and wetlands.

Figure 1: Map of the White Nile Basin showing delineated sub-catchments, lakes, major  rivers, and the Sudd Wetland extent. Sub-catchments are labelled numerically (1–15) with names listed in the legend. Observation stations (A–F) mark key hydrological data collection  locations used in this study: Lake Victoria (A), Lake Kyoga (B), River Nile at Masindi Port (C), Lake Albert (D), River Nile at Juba (E), and the Sudd Wetland (F). Background river networks and sub-catchment boundaries are derived from the HydroSHED dataset, and wetland extent is based on MODIS flood mask composites. The map is projected in geographic coordinates (EPSG:4326) with a graduated scale bar for accurate distance representation using UTM Zone 36N.

The White Nile: A Basin with Memory

The White Nile forms one of the world’s most complex lake, river, and wetland systems, extending from Lake Victoria through Lakes Kyoga and Albert into the Sudd. Hydrologically, it is a system of connected reservoirs that store, delay, and gradually release floodwaters downstream.

For decades, operational planning assumed that floodwaters take roughly five months to travel from Lake Victoria to the Sudd. That estimate was never actually tested with data; it originated as a rule of thumb based on Lake Victoria annual maxima in May and peak flooding in South Sudan in September/October.

Our recent study challenged that assumption. By combining daily lake-level and discharge data (1950–2024) with CHIRPS rainfall and MODIS flood-extent records (2002–2024), we tracked how flood peaks propagated through the system, segment by segment. Using an automated peak-matching algorithm, we quantified the lag between successive annual maxima peaks in Lake Victoria, Lake Kyoga, Lake Albert, and the Sudd Wetland.

The unprecedented high-water regime of 2019-2024

Figure 2: Lake Victoria water levels (1950–2024) and Sudd Wetland extents (2002–2024), with the 2019–2024 anomalous period shown in dark blue and earlier observations in black. The orange dotted line marks the pre-2019 maximum, while the solid vermillion line denotes the highest peak observed during 2019–2024. The dashed magenta line represents the reconstructed 1878 Lake Victoria peak (1137.3 m a.s.l.) from Nicholson & Yin (2001). The shaded grey band highlights the 2022 flood year, when the Sudd reached its largest extent in the MODIS record.

Between 2019 and 2024, both Lake Victoria and the Sudd reached record levels. Lake Victoria exceeded its historic 1964 peak in 2020, 2021, and 2024, while the Sudd expanded to more than twice its previous maximum extent. Each year from 2019 to 2024 stayed above any pre-2019 record, revealing that this was not a single flood season but a sustained multi-year regime.

The persistence of the 2019–2024 high-water regime mirrors earlier basin-wide episodes, including the 1961–64 and 1870s floods, when elevated lake levels and wetland extents were sustained across multiple years rather than confined to a single rainy season.  However, the 2020s stand out as the most extensive amongst all the episodes since the start of the 20th century. These data confirm that both the headwaters and terminal floodplain remained at record levels for several consecutive years during 2019–2024, highlighting the unprecedented nature of this sustained high-water phase in the modern observational era.

2019–2024: How Multi-Year Rainfall Triggers Propagated a Basin-Wide Flood

The sequence of flood events began with the exceptionally strong positive Indian Ocean Dipole of 2019, which brought extreme rainfall across the Lake Victoria basin. This marked the first in a series of four consecutive anomalous rainfall seasons that sustained elevated inflows into the lake system. The October–December 2019 short rains were among the wettest on record, followed by above-normal rainfall in the March–May 2020 long rains, another wet short-rains season in late 2020, and continued high rainfall through early 2021. Together, these back-to-back wet seasons kept catchments saturated and prevented any significant drawdown of lake levels between seasons. Lake Victoria rose by more than 1.4 metres between September 2019 and May 2020, the highest increase since the 1960s, and remained near the 1960s historical maximum for consecutive years. As that excess water propagated downstream, Lakes Kyoga and Albert filled and stayed high through 2021. Even when regional rainfall weakened in 2022, these upstream lakes continued releasing stored water into the White Nile. The flood peak that reached the Sudd in 2022 corresponded closely to the 2021 Lake Victoria high-water phase.

This sequence shows that the 2022 disaster was not driven by a single rainfall event but by cumulative wetness over multiple seasons. Each lake acted as a slow reservoir that buffered and then released the 2019 to 2021 excess water, resulting in multi-year flooding that persisted long after rainfall had returned to near-normal levels.

Transit Time and Floodwave Propagation

Quantitative tracking showed that it takes an average of 16.8 months for a floodwave to travel from Lake Victoria to the Sudd. The fastest transmission occurs between Victoria and Kyoga (around 4 months), while the slowest and most attenuated segment lies between Albert and the Sudd (around 9 months).

This overturns the long-held assumption of a five-month travel time and reveals a system dominated by floodplain storage and delayed release. The 2019–2021 period showed relatively faster propagation because of high upstream storage, while 2022 exhibited the longest lag as the Sudd absorbed and held vast volumes of water. By establishing this timing empirically, the study offers a more realistic foundation for early-warning systems.

Figure 3: Lake Victoria, Lake Kyoga, and Lake Albert water levels, and Sudd Wetland inundated extent, from 2016 to 2024. Coloured spline curves indicate annual flood-wave trajectories traced from the timing of Lake Victoria annual maxima through the downstream of the White Nile system. Blue shading on the secondary (right) axis shows 180-day rolling rainfall totals over each basin. The panel sequence (Victoria–Kyoga, Kyoga–Albert, Albert–Sudd) highlights the progressive translation of flood waves through the connected lake–river–wetland network.

Wetland Activation and Flood Persistence

Satellite flood-extent maps reveal how the Sudd responded once the inflow arrived. The wetland expanded through multiple activation arms that progressively connected different sub-catchments:

  • 2019: rainfall-fed expansion on the east (Baro–Akobo–Sobat and White Nile sub-basins)
  • 2020–2021: a central-western arm from Bahr el Jebel extending into Bahr el Ghazal and a north-western connection from Bahr el Jebel to Bahr el Arab connected around Bentiu in Unity State.
  • 2022: The two activated arms persisted so the JJAS seasonal rainfall in South Sudan and the inflow from the upstream lakes just compounded the activation leading to the massive flooding in Bentiu, turning the town into an island surrounded by water.

This geometry confirms that the Sudd functions not as a single floodplain but as a network of hydraulically linked basins. Once activated, these wetlands store and recycle water through backwater effects, evaporation, and lateral flow between channels. That internal connectivity explains why flooding persisted long after rainfall declined.

The Bigger Picture

Understanding these long lags is vital for effective flood forecasting and anticipatory humanitarian action. Current early-warning systems in South Sudan and Uganda mainly rely on short-term rainfall forecasts, which cannot capture the multi-season cumulative storage and delayed release that drive multi-year flooding.

By the time floodwaters reach the Sudd Wetland, the hydrological signature of releases from Lake Victoria has been substantially transformed by storage, delay, and attenuation within the intermediate lakes and wetlands. This means that downstream flood conditions are not a direct reflection of upstream releases but the result of cumulative interactions across the basin’s interconnected reservoirs.

The results suggest that antecedent storage conditions in Lakes Victoria, Kyoga, and Albert should be incorporated into regional flood outlooks. When upstream lake levels are exceptionally high, downstream alerts should remain elevated even if rainfall forecasts appear moderate. This approach aligns with impact-based forecasting, where decisions are informed not only by rainfall predictions but also by hydrological memory, system connectivity and potential impact of the floods.

The 2019–2024 high-water regime joins earlier basin-wide flood episodes in the 1870s, 1910s, and 1960s, each linked to multi-year wet phases across the equatorial lakes. The 1961–64 event raised Lake Victoria by about 2.5 metres and reshaped the Nile’s flow for several years. The 1870s flood appears even more extensive, showing that compound, persistent flooding is part of the White Nile’s natural variability.

Climate-change attribution studies indicate that the 2019–2020 rainfall anomaly was intensified by anthropogenic warming, increasing both its magnitude and probability. If such events become more frequent, the basin’s long-memory behaviour could convert short bursts of rainfall into multi-year high-water regimes.

This work reframes how we view the White Nile. It is not a fast, responsive river system but a slow-moving memory corridor in which floodwaves propagate, store, and echo over many months. Recognising this behaviour opens practical opportunities: it enables longer forecast lead times based on upstream indicators, supports coordinated management of lake releases, and strengthens early-action planning for humanitarian agencies across the basin.

It also highlights the need for continued monitoring and data sharing across national borders. Sparse observations remain a major limitation: station gaps, satellite blind spots, and non-public lake-release data all reduce our ability to model the system in real time. Improving this observational backbone is essential if we are to translate scientific insight into effective flood preparedness.

By Douglas Mulangwa (PhD researcher, Department of Meteorology, University of Reading), with contributions from Evet Naturinda, Charles Koboji, Benon T. Zaake, Emily Black, Hannah Cloke, and Elisabeth M. Stephens.

Acknowledgements

This research was conducted under the INFLOW project, funded through the CLARE programme (FCDO and IDRC), with collaboration from the Uganda Ministry of Water and Environment, the South Sudan Ministry of Water Resources and Irrigation, the World Food Programme(WFP), IGAD Climate Prediction and Application Centre  (ICPAC), Médecins Sans Frontières (MSF), the Red Cross Red Crescent Climate Centre, Uganda Red Cross Society (URCS), the South Sudan Red Cross Red Crescent Society (SSRCS) and the Red Cross Red Crescent Climate Centre (RCCC).

Models and Memories: Our NCAS CMSS 2025 Experience

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Piyali Goswami: p.goswami@pgr.reading.ac.uk

Mehzooz Nizar: m.nizar@pgr.reading.ac.uk

This September, we attended the NCAS Climate Modelling Summer School (CMSS), held at the University of Cambridge from 8th to 19th September. Five of us from the University of Reading joined this two-week residential programme. It was an intense and inspiring experience, full of lectures, coding sessions, discussions, and social events. In this blog, we would like to share our experiences.

 Picture 1: Group Picture of Students and teaching staff. One cohort, many time zones, zero dull moments…

About NCAS CMSS

The NCAS Climate Modelling Summer School (CMSS) is a visionary program, launched in 2007 with funding originating from grant proposals led by Prof. Pier Luigi Vidale. Run by leading researchers from the National Centre for Atmospheric Science and the University of Reading, it’s an immersive, practice-driven program that equips early-career researchers and PhD students with deeper expertise in climate modelling, Earth system science, and state-of-the-art computing. Held biennially in Cambridge, CMSS has trained 350 students from roughly 40 countries worldwide.

The CMSS 2025 brought together around 30 participants, including PhD students and professionals interested in the field of Climate Modelling. 

Long Days, Big Ideas: Inside Our Schedule

The school was full of activity from morning to evening. We started around 9:00 AM and usually wrapped up by 8:30 PM, with a good mix of lectures, practical sessions, and discussions that made the long days fly by.

Week 1 was led by Dr Hilary Weller, who ran an excellent series on Numerical Methods for Atmospheric Models. Mornings were devoted to lectures covering core schemes; afternoons shifted to hands-on Python sessions to implement and test the methods. Between blocks, invited talks from leading researchers across universities highlighted key themes in weather and climate modelling. After dinner, each day closed with a thought-provoking discussion on climate modelling, chaired by Prof. Pier Luigi Vidale, where participants shared ideas on improving models and their societal impact. 

The week concluded with group presentations summarising the key takeaways from Hilary’s sessions and our first collaborative activity that set the tone for the rest of the school. It was followed by a relaxed barbecue evening, where everyone finally had a chance to unwind, chat freely, and celebrate surviving our first week together. 

Picture 2 : Working on our group projects. Looks like NASA, feels like: ‘what’s our team name?’

Week 2 was all about getting hands-on with a climate model and learning how to analyse its output. We moved into group projects using SpeedyWeather.jl to design and run climate model experiments. It is a global atmospheric model with simplified physics, designed as a research playground. One of the developers of SpeedyWeather.jl, Milan Klöwer, was with us throughout the week to guide and support our work. Each team explored a different question, from sensitivity testing to analysing the model outputs, and spent the afternoons debugging, plotting, and comparing results. Evenings featured talks from leading scientists on topics such as the hydrological cycle, land and atmosphere interactions, and the carbon cycle. 

The week also included a formal dinner at Sidney Sussex, a welcomed pause before our final presentations. On Friday 19th of September, every group presented its findings before we all headed home. Some slides were finished only seconds before presenting, but the atmosphere was upbeat and supportive. It was a satisfying end to two weeks of hard work, shared learning, and plenty of laughter. A huge thank you to the teaching team for being there, from the “silly” questions to the stubborn bugs. Your patience, clarity, and genuine care made all the difference.

Picture 3: SpeedyWeather, as told by its favourite storyteller Milan, Picture 4: Pier Luigi probably preparing for the next summer school..

Coffee, Culture, and Climate Chat

The best part of the summer school was the people. The group was diverse: PhD students, and professionals from different countries and research areas. We spent nearly every moment together, from breakfast to evening socials, often ending the day with random games of “Would You Rather” or talking about pets. The summer school’s packed schedule brought us closer and sparked rich chats about science and life, everything from AI’s role in climate modelling to the policy levers behind climate action. We left with a lot to think about. Meeting people from around the world exposed us to rich cultural diversity and new perspectives on how science is practiced in different countries, insights that were both fresh and valuable. It went beyond training: we left with skills, new friends, and the seeds of future collaborations, arguably the most important part of research.

Picture 5: Barbecue evening after wrapping up the first week, Picture 6: Formal dinner at Sidney Sussex, one last evening together before the final presentations

Reflections and takeaways

We didn’t become expert modellers in two weeks, but we did get a glimpse of how complex and creative climate modelling can be. The group presentations were chaotic but fun. Different projects, different approaches, and a few slides that weren’t quite finished in time. Some of us improvised more than we planned, but the atmosphere was supportive and full of laughter. More than anything, we learned by doing and by doing it together. The long days, the discussions, and the teamwork made it all worthwhile.

If you ever get the chance to go, take it. You’ll come back with new ideas, good memories, and friends who make science feel a little more human.

For the future participants

The NCAS CMSS usually opens in early spring, with applications closing around June. With limited spots, selection is competitive and merit-based, evaluating both fit for the course and the expected benefit to the student.

Bring curiosity, enthusiasm, and a healthy dose of patience, you’ll need all three. But honestly, that’s what makes it fun. You learn quickly, laugh a lot, and somehow find time to celebrate when a script finally runs without error. By the end, you’ll be tired, happy, and probably a little proud of how much you managed to do (and probably a few new friends who helped you debug along the way).