Earth-Science Reviews 165 (2017) 81–109

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Invited review Design with nature: Causation and avoidance of catastrophic flooding, Myanmar

G.R. Brakenridge a,⁎, J.P.M. Syvitski a,E.Niebuhrb,I.Overeema,S.A.Higginsa,A.J.Kettnera, L. Prades c a University of Colorado, United States b U.S. National Weather Service, United States c UN World Food Programme, Italy article info abstract

Article history: Myanmar is among 15 nations that account for 80% of global population exposed to flooding. In 2008, the country Received 29 August 2016 suffered exceptional damage and human mortalities (N138,000) from tropical storm Nargis, which followed an Accepted 6 December 2016 unusual but not unprecedented storm track. In 2015, heavy monsoonal rains related to the tropical Madden– Available online 16 December 2016 Julian Oscillation plus a slow-moving tropical storm (Komen) together caused major flooding, ~130 fatalities, and very severe damage and losses. Both events triggered international food, medical, and other assistance, in- cluding efforts to design rebuilding with greater resilience to floods. Orbital remote sensing can be employed to characterize such damaging floods and quantify future flood risk; advanced lead-time flood prediction is also increasingly accurate and available. These capabilities must, however, be applied in a context of environmen- tal variables (climate, sea level, dams, and land cover) that are changing the hazard. In addition to the hydrome- teorology, distal causes for flood disasters include: high sediment loads carried by Myanmar rivers, locally rapid rates (N50–100 m/y) of channel migration, expansion of population into vulnerable locations, and anthropogenic modifications to floodplains, watersheds, and the coastal zone. Engineering projects can protect local communi- ties, but flood control structures will fail again unless the environmental changes that increase exposure to flood damage are also mitigated. Earth Science-based methods for long term reduction of societal exposure include floodplain reconnection, levee removal, controlled avulsions, and redirecting new housing and other economic development onto lands with less severe flood risk. © 2016 Elsevier B.V. All rights reserved.

Contents

1. Introduction...... 82 2. Sources of floodhazardinMyanmar...... 82 2.1. Myanmarphysiographyandrivers...... 82 2.2. Myanmar flood-producingprecipitationandrunoff...... 83 2.3. Flow variability and the floodplain...... 85 2.4. Effectsofhighsedimentload...... 88 2.5. Effects of dams, reservoirs, and artificiallevees...... 89 3. Non-stationary floodriskinMyanmar...... 90 4. Remote sensing measurements of Myanmar floods...... 91 4.1. Understanding floodhazard...... 91 4.2. MODIS floodmappingforMyanmar...... 92 4.3. Informationfrompassivemicrowavesatellites...... 93 4.4. Myanmar floodhistoryobservedviamicrowave...... 94 5. Recent floodhistory...... 97 5.1. Pre-1968 floods...... 97 5.2. 1968cycloneandstormsurge...... 100 5.3. The1970sthrough1990s...... 100

⁎ Corresponding author at: University of Colorado, 4001 Discovery Dr. Office N142, 80309 Boulder, CO, United States. E-mail address: [email protected] (G.R. Brakenridge).

http://dx.doi.org/10.1016/j.earscirev.2016.12.009 0012-8252/© 2016 Elsevier B.V. All rights reserved. 82 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

5.4. 2003monsoonrainfallandcyclone...... 101 5.5. 2004cyclone...... 101 5.6. 2006CycloneMalaand2010CycloneGiri...... 102 5.7. Floodsin2011and2012...... 102 6. The 2008 Cyclone Nargis storm surge and flood...... 102 7. CausationandavoidanceofNargisevents...... 103 8. The 2015 Cyclone Komen and intense monsoon floods...... 104 9. CausationandavoidanceofKomenevents...... 105 10. Conclusion...... 106 Acknowledgements...... 108 References...... 108

1. Introduction (The-World-Bank, 2011). In developing nations such as Myanmar, flood fatalities can be exceptional: entire communities have been Earth Science can help developing nations avoid the unwise water- drowned by coastal storm surges. Even in the 21st century, when related development pathways followed by other nations. Earlier mis- weather prediction has increased in accuracy (Webster, 2013), effective takes made since the Industrial Revolution are only recently being recti- warnings are not always accomplished. The locations of unusual South fied. For example, in North America and Europe, artificial levees Asian floods vary, but major damage occurs somewhere every year: blocking the connection of rivers to their floodplains are being removed thus begging the question as to whether it is the storms, or the failure (Galat, 1998). In the Mississippi delta, controlled flooding is being un- to prepare for them, that is the main cause for the losses (Ziegler et al., dertaken to restore the sediment influxes needed for landform stability 2012). (Day et al., 2016). Professional societies acknowledge the need for sur- Within the past 10 y, two exceptionally severe flood disasters oc- face process understanding to be communicated: “Geoscientists have curred in Myanmar. There were N138,000 fatalities in the Ayeyarwady a fundamental role in the engineering and architectural design, plan- delta in 2008, from storm surge and intense rain caused by tropical ning, construction, and maintenance of infrastructure systems with re- storm Nargis (Fritz et al., 2009). In 2015, tropical storm Komen and tor- spect to their relationship to local geology, hazards and the rential monsoonal rains inland caused 132 fatalities and another 1.6 environmental setting” (GSA, 2014). We review here a developing million affected while the flood wave made its way to the sea nation's experience with damaging floods, and describe from an Earth (Government-of-the-Union-of-Myanmar, 2015). We examine the cau- Science perspective the lessons for a safer recovery. The review presents sality and societal effects of these events, and within the relevant technologies now available for the rapid mapping of areas of flood risk, storm history. Satellite sensing is employed to investigate flood causa- and urges that they be applied in the context of modern science that has tion and evolution, and to demonstrate how space-based information invalidated certain widely-held assumptions (e.g. flood series statistical can be used in risk mapping. Also considered are the environmental stationarity). We consider that “designing with nature” using best- changes that are increasing the risk of catastrophic floods. These are available scientific knowledge is not only economically feasible, but nec- the changing variables that must be accommodated to foster greater essary (McHarg, 1969); otherwise even more catastrophic floods will “resilience” or a capacity to recover quickly from flood damage. certainly occur. Long term and effective disaster recovery requires understanding of 2. Sources of flood hazard in Myanmar why a particular event became exceptionally severe. In areas affected by the tropical monsoon, “flooding” is not unusual, but instead an annual Flood hazard can be usefully simplified to floodplain and coastal phenomenon. Inland river floodplains and coastal deltas are partially in- zone maps showing flood extent at different stages (river levels) or undated each summer; mountain snowmelt combined with heavy surge heights, and quantitative recurrence intervals/annual exceedance monsoonal rains fill river channels, and local tropical cyclones cause probabilities (Eychaner, 2015; Maidment, 1993). However, the hydro- coastal storm surges and intense precipitation inland. Important river- meteorological causes of flooding are diverse (Hirchboeck, 1988), and delta systems in the region include the Indus, Ganges-Brahmaputra- a region's unique suite of physiography, climate, and other environmen- Megna, Chao Phraya, Mekong, Red, Pearl, and, in Myanmar or Burma, tal variables such as river sediment load also exerts important controls the Ayeyarwady-Chindwin, Sittaung, and Salween. Many of the deltas over hazard. host large human populations: ~15 million out of Myanmar's 51 million presently reside on the Ayeyarwady delta. Residents and economies of 2.1. Myanmar physiography and rivers these deltas and the river floodplains are adapted to the annual flood: rice agriculture may depend on the monsoon, and, in coastal areas, pe- Myanmar is the largest country in Southeast Asia, with an area of fl riodic freshwater ooding counteracts saltwater intrusion and soil deg- 676,600 km2. It is among 15 nations that together account for 80% of fl radation. Seasonal ooding is expected and even necessary to the local population exposed to river flood risk world-wide (Ward et al., 2013; economies. Winsemius et al., 2013). It includes a long coastline along the Andaman fl Less frequently, ooding extends well beyond the normal annual Sea and the Bay of Bengal. The nation is divided into 7 states and 7 divi- fi fi fl limits. Arti cial reservoirs ll above capacity, overbank ows occur, riv- sions (Fig. 1). The natural landscape includes the northern and western ers erode their banks and/or avulse, and inter-channel islands and bars mountains with peaks as high as 5800 m (the Sino-Burman Range, are submerged. In the deltas, sedimentary regimes and landforms are Indo-Burman Range to the west); the Shan Plateau; the Central Basin fl adjusted to a balance of tides, waves, and river ows, but these low (also known as the rain-shadowed Dry Zone); and the coast, including areas may be completely inundated by extreme storm surges. As region- the Rakhine lowland (Fig. 1). Total cultivated area in 2009 was approx- al population increases and migration to urban areas continues, the neg- imately 12,100 km2; cultivated areas are concentrated in the fl ative socio-economic impacts of these unusual oods become larger. In Ayeyarwady river basin and the delta (Frenken, 2012). fl urban areas along the Chao Phraya, Thailand, inland river ooding in The principal drainage system in Myanmar is the north–south- 2011 affected international manufacturing supply chains for many flowing Ayeyarwady River and tributaries, which drain 66% of months, and caused 45.7 billion USD economic damages and losses Myanmar and empties into the Andaman Sea (Fig. 1). The upper G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 83

a b

Fig. 1. A. Shaded-relief map showing physical features of Myanmar. Numbered symbols are locations of microwave River Watch sites discussed in the text. B. Map of Myanmar showing cities, states and regions.

Ayeyarwady valley includes three gorges separated by reaches with forest area decreased from 2345 km2 to 1786 km2 between 1924 and very wide (10 km+) alluvial floodplains. The largest tributary, the 1995 (Hedley et al., 2010): from clearance for agriculture and aquacul- Chindwin, drains the northwestern part of the country before meeting ture. Forest removal for urban firewood has recently increased near the Ayeyarwady downstream of Mandalay (Frenken, 2012; Ridd and Yangon and satellite cities. In fact, deforestation in the Ayeyarwady Racey, 2015). The Sittaung River, to the east of the downstream delta region is “catastrophic”, with N20% of the mangrove forests lost Ayeyarwady, drains 5.4% of the country and exhibits a broad floodplain in only 10 y (Leimgruber et al., 2005). In a global survey of deltas, and a delta that merges with that of the Ayeyarwady. The Pathein River the Ayeyarwady is listed as “in peril”:areductioninaggradation drains the southeastern Rakhine Yoma, (Arakan Mountains) and the rates plus accelerated compaction is occurring as global sea level Yangon River drains the southern Bago Yoma: both join a network of rises (Syvitski et al., 2009). The delta includes 1100 km2 waterways in the Ayeyarwady delta. Coastal storm surges there can area b 2ma.s.l.;~15,000km2 are affected by storm surges; a 30% sed- reach N50 km inland. The Salween River enters the sea east of the iment reduction is predicted from the tributary dams already con- Ayeyarwady and its lower portions also experience storm surges; it structed. Tidal gauge data indicate a 3.4–6 mm/y relative sea level drains the Shan Plateau. This river rises far to the north in the high Tibet- rise (Syvitski et al., 2009). an Plateau (Fig. 1). Myanmar deltas are heavily populated with an initial migration into In contrast to these major trunk rivers, which produce sustained the area in the late 1800s from the north, following the British seizure in floods from monsoon and tropical storm rainfall, a series of much 1852 and construction of drainage and levee flood protection structures shorter rivers drain the mountainous areas. Floodplains are narrow in that facilitated permanent settlements and rice agriculture. This agricul- the uplands, but broaden in the lowlands; flash floods and landslides ture remains a major contributor to South Asian rice production and to (Fig. 2) are a frequent occurrence and backwater effects may occur Myanmar's economy. In 1852 ~1 million inhabitants lived on the delta, from trunk stream flooding at their mouths. Much of hilly peninsular with 30,000 ha in cultivation (Tarling, 1992). The population of the southeastern Myanmar (Tanintharyi) is also drained by short steep riv- coastal and delta areas was 9.6 million in 1983 and 12.7 million in ers flowing westwards into the Gulf of Martaban (Ridd and Racey, 1997 (Hedley et al., 2010). 2015). These hilly uplands sometimes experience flood-induced land- slides and fatalities (Davies, 2015). 2.2. Myanmar flood-producing precipitation and runoff At the downstream end of these drainage systems, the Ayeyarwady and Sittaung deltas (Fig. 3) includes 20,570 km2 of low, fertile plain, Myanmar's climate is tropical monsoon, and its flood climate is with five major and many smaller distributaries. Both are mud-silt tex- “barotropic”: relatively low wind shear and less-intense severe thun- ture, tide-dominated systems with a mean tidal range of 4.2 m (4–6m). derstorms (Hayden, 1988). During the summer, the Indian and Asian Spring tide influence extends almost 300 km inland to the apex of the monsoons interact with rain-shadow effects, the Inter-Tropical Conver- delta area (Hedley et al., 2010). The land was naturally forested, and gence Zone (ITCZ) (Webster and Yang, 1992), and convective rainfall mangroves still grow in tidally-influenced areas, but the total mangrove from the Bay of Bengal to produce complex patterns of heavy rainfall 84 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 2. A record-setting, 5.9 km long landslide observed by NASA's EO-1 satellite in northern Chin state, northeast of Tonzang, after intense rains (150 mm/h, measured by the NASA GPM satellite) in July 2015. Note numerous smaller landslides (light brown colour). Slide debris dammed streams and created new temporary lakes. NASA Earth Observatory images by Jesse Allen, using EO-1 data from the NASA EO-1 team and Landsat data from the U.S. Geological Survey.

throughout Myanmar from the mountains to the shorelines. The ITCZ However, prolonged droughts also contribute to flood risk, by creating reaches its northernmost extent in June–August. Rainfall is concentrat- cracks in earthen dikes (Dapice, 2003). ed in the hot humid months of the southwest monsoon (May–October); The ENSO counterpart of El Niño (La Niña; equatorial Pacificcold the northwest monsoon (December–March) is relatively cool and al- water anomalies) influences flooding in Myanmar. The years most entirely dry. The mean annual rainfall is approximately 2300 mm, 1998–1999 and 2008 experienced global La Niña conditions (Rojas ranging from 4000 to 6000 mm along the coastal reaches and in the et al., 2014) and major flooding in Myanmar (Section 4.4). The 2001 mountains of Rakhine and Tanintharyi to 500–1000 mm in the Dry La Niña brought the wettest conditions between 1971 and 2010 (Sein Zone, due to orographic and rain shadow effects. Intermediate levels of et al., 2015). In contrast, unusual flooding (including tropical storm rainfall are found across the Ayeyarwady delta areas (2000–3000 mm) Komen) in 2015 occurred as El Niño conditions were underway and in- and the Shan Plateau (1000–2000 mm) (Frenken, 2012). In northern tensifying. In this regard, during the 2015 flooding a strong MJO moved and western Myanmar, common causes of intense heavy rain include eastward in the summer and was associated with the intense rainfall. mid-season persistence of a local monsoon trough, and also cyclonic Another control over Myanmar precipitation is the Indian Ocean Di- storms crossing the west coast during the early and late phases of the pole (IOD). Rainfall in Myanmar is negatively correlated with the posi- monsoon. To the east, low pressure waves (tropical storm remnants) tive phase of the IOD, which includes a warm, wet, western Indian move from east to west and also can induce very heavy rainfall. Ocean, and cool and dry conditions to the east. The IOD thereby modu- The region's rainfall is also affected by the inter-annual El Niño/ lates monsoonal rainfall, and its status influences the correlation be- Southern Oscillation or ENSO (Furuichi et al., 2009; Krishnamurthy tween ENSO and rainfall (Ashok et al., 2001). and Goswami, 2000) and the intra-seasonal Madden–Julian Oscillation Tropical cyclonic storms make landfall in Myanmar between May or MJO (Hendon and Salby, 1994). These are tropical to near-global al- and October. Slow-moving storms bring very heavy rainfall that cause ternations in atmospheric and oceanic circulation patterns and rainfall. additional flooding: “While Tropical Storm Komen was never particu- For example: tree rings demonstrate that (drought-limited) Myanmar larly intense, its circulation swept copious amounts of moisture inland teak growth in 1999, following the very strong 1997–1998 El Niño, from the warm waters of the Bay of Bengal” (Freedman, 2015). Tropical was the lowest of any year in the past 300 y (D'Arrigo et al., 2011). cyclones may also cause coastal storm surges, and these have ranged up Also, the strong 2009 El Niño (Rojas et al., 2014) was accompanied by to 4 m a.s.l.: they cause significant damage approximately every 5–6y low flows along Myanmar rivers (see below, Section 4.4). Between (Dube et al., 2010). The tracks, speeds, sizes, and intensities of tropical 1947 and 1979 there were five El Niño years (1953, 1957, 1965, 1972, storms are all important in major flood genesis. The Pacific Decadal Os- 1976) with three episodes showing a rainfall deficit of −7% to −10%; cillation (PDO) appears to affect tropical storm frequency: within the but 1953 and 1965 brought above-average rainfall of +3% and +1%, re- Indian Ocean, in 1945–1976, there were 476 storms during the East Pa- spectively. El Niño thus does not exhibit a simple relationship with cific Cold Phase, but only 162 storms during the Warm Phase between drought (Sen-Roy and Kaur, 2000). Lastly, drought effects are most pro- 1977 and 2008 (Hagag et al., 2010). A relatively short-lived change nounced in the Dry Zone. Dry conditions draw down reservoirs and riv- from warm to cold phases may have taken place in 1998, coincident ers, and thus delay the onset of flooding when heavy rain begins. with the demise of the 1997/98 El Niño; 2002 experienced a return to G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 85

Fig. 3. Topography from NASA SRTM of the Ayeyarwady (main part of figure) and Sittaung (right portion of figure) deltas. Yellow-blue is increasing altitude to elevations above 10 m (shown in black). The red area is satellite-mapped surge inundation by Cyclone Nargis in 2008. From (Overeem and Syvitski, 2009).

the warm phase and then a sustained cold phase occurred 2008–2015 2.3. Flow variability and the floodplain (Bond et al., 2003; Trenberth and Hurrell, 1994; Wikipedia, 2016d). Cli- matologists are utilizing these large-scale circulation pattern changes River discharge in Myanmar changes across several time scales, but (ENSO, MJO, IOD, and PDO) in extending their forecast capacity for ex- especially seasonally (Fig. 5). At Mandalay, annual variations between treme rainfall in this region. low and flood stages of 10 m have been recorded. The combined dis- Summer melting of the snow and glaciers in mountainous northern charge of the Ayeyarwady and Chindwin Rivers at Chauk ranges Myanmar also contributes to flow variability. Heavy rains in the moun- between ~30,000 m3/s and 1500 m3/s; or at the head of the delta tains coupled with snowmelt causes large flood volumes to be generat- from ~33,000 m3/s to b2000 m3/s (Van der Velden, 2015). As yet, ed, and this water can move long distances downstream to cause there are no large dams on the river. The natural flow variation requires overbank flooding. The ratio between the discharge of the Ayeyarwady river ports to have separate landings for low and high water, and low and that of the Chindwin River increases in March–June (Van der water causes navigation problems: in the Bamaw–Mandalay–Pyay sec- Velden, 2015) but, under winter conditions, a relatively clear-water tors, the river can be as shallow as 0.6 m. (Ayeyarwady) and sediment-rich (Chindwin) differentiation occurs at At what discharge or stage are channel conveyance capacities their confluence (Fig. 4). Sedimentological studies indicate that 60 ± exceeded and Myanmar floodplains flooded? Worldwide, many natural 10% of the total sediment flux downstream is supplied by the Chindwin river channels accommodate discharge with a ~1.5 y recurrence interval (Garzanti et al., 2016). (bankfull flow occurs every 1–2 y). The dominant discharge shaping Flooding of the lower Ayeyarwady is regulated by whether just one such channels is a relatively frequent high flow; less-frequent higher or both the Chindwin and upper Ayeyarwady are delivering flood dis- flows inundate parts or all of the floodplain. However, there is much charges. Also, the delta areas of Myanmar are not dry like some in variability in these relationships globally (Williams, 1978), and chan- South Asia (e.g., the Indus), but are instead runoff generators nels of seasonal tropical rivers (Syvitski et al., 2014) exhibit important (Kravtsova et al., 2009). Thus, heavy monsoon or tropical storm rains differences. Channel and floodplain morphology are instead controlled on the deltas directly cause local flooding. Some floods in Myanmar by the difference between wet and dry season discharges along these are therefore mainly from extra-local river water delivered downstream channels, by high magnitude, low frequency (recurrence onto relatively dry floodplains, but others occur via local rainfall on interval N 10 y) floods, and by transported sediment (Gupta, 2013). already-saturated lowlands (Mertes, 1997). These are sometimes called These channels record in their morphology the whole series of dis- “pluvial floods” due to their causation by high rainfall on wet low-relief charges that occur (Pickup and Rieger, 1979). landscapes. This type of local rainfall-induced flooding caused many fa- At some locations, tropical river channels are “box-shaped with talities inland during the Nargis storm surge and storm. steep banks and a channel-in-channel morphology: the smaller inner 86 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 4. DigitalGlobe winter-season image of the Ayeyarwady (right) and Chindwin (left) confluence, showing the comparatively sediment-rich character of the Chindwin during this season. The annual flood submerges the bright sandy areas of both. channel carries high flows of the wet season” (Gupta, 2013). Overbank monsoon-affected rivers instead are freely meandering, extensive, low flow rarely occurs along such river reaches: instead, the large floods relief floodplain landscapes are created and modified (Lewin and carve, modify, and occupy the outer channel. Where tropical Ashworth, 2014), and large areas are flooded by the monsoon nearly

Fig. 5. River discharge time series (upper plot, daily values), 1998–present, as observed via satellite microwave radiometry (see text) for River Watch Site 26 on the Ayeyarwady (Figs. 1 and 6). The lower plot illustrates monthly runoff computed from the same data. The recurrence interval calculations use the Log Pearson III probability distribution. A typical year experiences daily discharge variation between ~3000 and ~12,000 m3/s, or 4×; the mean annual discharge is ~3800 m3/s. At this location, the 2015 peak discharge and total runoff volume was the flood of record, 1998–present, and may have reached ~24,000 m3/s, or approaching 7× the mean. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 87

Fig. 6. Inundation for (top) a normal winter flow, at ~200 m3/s in February 2000; (middle) normal monsoon season flow, recurrence interval of 1.1 y, ~9000 m3/s, in 2002, and (bottom) during a rare flood, recurrence interval of 21 y, 18,200 m3/s, in 2013. The recurrence interval and peak discharge estimates are from site 26 in the River Watch array described in the text; the site is defined by the white 10 km square. Along this reach of the Ayeyarwady, the inundation difference between annual and unusual flooding reflects a 2× increase in discharge; the normal annual maximum discharge is, however, N10× higher than annual low flow.

every year. Both situations occur in Myanmar. As visible from orbital expansions, which actually represent bankfull conditions (Fig. 6). In the sensors, annual monsoonal floods may appear as major “inundation” U.S., the area of near-yearly flooding mapped in Fig. 6 would likely be events along such meandering reaches, yet such high water occurs near- considered part of the “floodway” (FEMA, 2016), and subject to the ly every year (these areas are, in effect, part of the channel). The unusual most restrictive development/land use regulations: in order to preserve floods are only incrementally wider than the normal annual water area water conveyance and storage during major flooding. 88 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

2.4. Effects of high sediment load This load's interaction with fluvial dynamics causes changes in local flood hazard. For example, over time channel bed sedimentation may Extensive reaches of Myanmar Rivers are anabranching (Latrubesse, produce higher river levels for the same discharge (Pinter, 2005). In 2008) and transport high sediment loads (Furuichi et al., 2009). In a sea- Sagaing, the Chindwin channel is “silted up with ~280 tons of sand sonally dependent manner, the Ayeyarwady delivers 44,241 km3 of every year”. In Myanmar, ~1300 km of embankments were built in water containing 226–364 Mt of sediment to the ocean every year the late 19th/early 20th centuries to protect new agriculture; these (Robinson et al., 2007). Sediment discharge at Chauk (downstream) structures inhibit lateral channel migration and deposition in the ranges from 165 kg/s in winter to 18,000 kg/s in the monsoon. During protected land areas, and enhance channel bed aggradation. High sedi- high discharge at Chauk, the river carries approximately 3× as much ment loads can also induce channel avulsion or migration (Figs. 7 and 8) sediment as at Sagaing (Htwe et al., 2016). (Hajek and Edmons, 2014). However, lateral migration rates in

Fig. 7. LANDSAT image (from Google Earth Engine) of a migrating Ayeyarwady River reach about 25 km downstream of Myitkyina, northern Myanmar: in 1989 (top) and2004(bottom). The meander cutoff occurring during flooding in 2004, after progressive migration since 1989 moved the channel reaches into proximity. Sand bars define the level floor of the bankfull channel. Scenes are 8 km east to west. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 89

high sediment load river channels (Lewin and Ashworth, 2014). If mo- bile riverbanks are reinforced and raised, confinement of the river's sed- iment load further enhances channel bed and reduced floodplain aggradation. This in turn sets the stage for catastrophic breaching and channel avulsion (Syvitski and Brakenridge, 2013). On the coastline, landforms are (or were) adjusted to high sediment inputs, but levee protection may prevent deposition of river sediments during the flood season between the channels and on islands (Auerbach et al., 2015). This in turns facilitates island subsidence relative to sea level (Syvitski et al., 2009). In much of Myanmar, trunk river channels are mobile along exten- sive reaches. Average lateral migration rates of 50–100 m/y are com- mon; rapid movement and stable intervals are included in these averages (Figs. 10–12). Sudden meander cutoffs may divert flow from larger into smaller channels (Fig. 10), causing episodes of rapid bank erosion and sediment reworking. Final abandonment of the old channel may occur over a period of years, or the channel may remain partially occupied. Also, meanders can be relatively stable over some years, and then undergo rapid elongation and migration; e.g., Figs. 11 and 12.All of these processes must be included in attempts to understand and map future flood hazard.

2.5. Effects of dams, reservoirs, and artificial levees

Throughout much of Myanmar, ancient and newly built dams and other control structures (small red areas in Fig. 13)modifylocalexpo- sure to flood hazard and downstream transport of sediment. There are approximately 280 irrigation dams in Myanmar; most are earthen rath- er than concrete. Many are deteriorating, and spillways “are not always sufficient to handle large floods” (Hammond, 2015). New dam building is underway; storage capacity has expanded on tributaries of the Irra- waddy and Chindwin from 2.34 to over 18 km3 since 1988 (Myanmar Irrigation Works Department, 2004). Myanmar reservoirs are not designed or managed for flood control. As a result, they are not effective at reducing flood risk. The spillway de- signs instead pose potentially lethal risk of flash floods to downstream populations if these dams fail. For example, the 4 km2 Yazagyo reservoir on the Nayizaya River in northern Myanmar was completed in 2015 to provide irrigation and power (Steijn et al., 2015). The reservoir was full as unusual flooding commenced July 7 of that year. On July 9 spillway operation started. On July 28, the water level in the reservoir was 4 m below the dam top and sand bagging began. On August 1 large amounts of wooden debris entered the reservoir and partially blocked the spill- way. Heavy machinery dislodged some of the wooden debris to release the stored water. On August 2, the water level dropped by ~4 m to achieve a safe situation and failure was narrowly avoided. The dam and reservoir provided no flood control benefit, rather it put down- stream populations at grave risk. Large hydroelectric dams also change flood hazard, by trapping very Fig. 8. MODIS band 7,2,1 colour composite (from NASA Worldview), September 11, 2015 fl (top), and March 13, 2015 (bottom) showing monsoon filling of the same Ayeyarwady large quantities of sediment during large oods (Gupta et al., 2012). The river channel during the 2015 flood. The (low-flow) abandoned meander is re-occupied lack of sediment delivery then produce “sinking deltas” (and increased annually during the monsoon season; it thus provides flood water storage and flood hazard) downstream (Syvitski et al., 2009). Locally, dam-induced attenuates downstream-moving flood waves. backwater and channel aggradation may increase overbank flooding for considerable distances upstream of the reservoir; this occurred at sever- al locations during the 2015 flood (Fig. 14). There are almost 200 large Myanmar are locally variable: “Some sections are very stable…in the vi- dams in Myanmar. Installed capacity of hydroelectric plants tripled sualized 14 years … the river has eroded less than 30 m in southern di- from 253 to 745 MW between 1990 and 2002; the 2449 MW capacity rection and widens only during flood” (Van der Velden, 2015, p. 30). in 2010 is still just a small fraction (6%) of estimated 37,000 “economi- River junctions are especially prone to the effects of flow variability cally exploitable” megawatt hydroelectric potential. An Asian Develop- and high sediment load. Where the Chindwin enters the Ayeyarwady, ment Bank's 2012 assessment of the energy sector in Myanmar an inland delta has developed (Figs. 4 and 9). The channel connections identified 92 potential new large hydropower projects (Wikipedia, are ~35 km apart, separated by low (and populated) islands. The south- 2015), including the controversial Myitsone dam at the source of the ern mouth is, “according to tradition, an artificial channel, cut by one of Ayeyarwady. There may be many new large dams soon in Myanmar, the kings of Bagan”. It was then blocked for centuries until 1824, when it but none planned (to our knowledge) specifically for flood control. was re-opened by an exceptional flood (Gregory and Goudie, 2011). Numerous artificial levees are superimposed on Myanmar's dynamic This switching behavior, continuing up to today, is characteristic of sedimentary systems. They reduce local flooding and facilitate transit of 90 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 9. Google Earth Engine Landsat images of the mouth of the Chindwin River (left side, each image) where it joins the Ayeyarwady River, as a time series. A, 1989; B, 1999, C, 2000; D, 2002. Bright sand bar areas define the floor of the bankfull channel, which accommodates normal monsoonal discharges; 1999 experienced unusually large (r = 10 y) peak discharges, and a new meander bend was created. water and sediment to the sea (Gordon, 1893; Gordon, 1885), but they 3. Non-stationary flood risk in Myanmar decrease overbank deposition across a subsiding landform. When they fail, during exceptional floods, the flooding is more damaging than it Quantifying future flood risk is fundamentally based on the observed would be otherwise. In the delta, the levee network does provide oppor- history of past flood events. A variety of statistical approaches are used tunities for local flood mitigation, by improvements in design and loca- to predict future risk from such information: all require the past to be tion and by the integration and maintenance of individual structures used as a guide to the future. Within the United States, the relevant gov- within comprehensive flood control plans (Steijn et al., 2015). Remov- ernment agencies use the Log Pearson Type III probability distribution. It ing some levees could provide increased local flood storage and provides the values of discharges to expect in the river at various recur- overbank replenishment of needed sediment (Hedley et al., 2010). Re- rence intervals (yearly exceedance probabilities) based on the available inforcing others can protect critical facilities (Steijn et al., 2015). historical record of annual peak discharges. This is helpful when

Fig. 10. Google Earth Engine Landsat images showing the Ayeyarwady River near Kywe Done, lower left corner of figure. Left, 2012; right, 1984. The earlier image shows the river near bankfull. The scenes measure 10.7 km west to east; north is up. The channel moved 2.2 km to the north in 24 y, for an average migration rate of 92 m/y. However, the complete time series shows that most of this change was accomplished by avulsion between 1992 and 1995 (a rate in excess of 700 m/y would apply). The channel to the south then progressively shrunk as more flow was diverted to the northern arm. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 91

Fig. 11. The Sittaung River east of Thone Gwa, showing channel change, 1988 (left)– 2012 (right). The scenes measure 10.7 km, west to east, north is up. The northern meander elongated 2 km to the southwest in 25 y, for an average lateral migration rate of 80 m/y. However, other images show that most change occurred after 1990 (87 m/y since then) and with most rapid movement after 2006.

designing structures in or near the river that may be affected by floods also be captured numerically. Surface process modeling can estimate (Klingeman, 2005) and for restricting certain kinds of development the reduction of sediment load caused by reservoir and dam construc- within the floodplain. “Stationarity” in the time series of annual peak tion (Kummu et al., 2010) and these changes can be incorporated into discharges is required for this approach, however: the mean, variance, delta compaction models and sea level rise predictions. In this regard, autocorrelation, and other descriptive statistics of the population must remote sensing documents the coastline of the Ayeyarwady-Sittaung be assumed constant over time. delta and also the Salween to be in approximate equilibrium; there In Myanmar, upland deforestation, mangrove logging in the deltas have not been major losses in coastline during the limited time interval (Webb, 2013), delta subsidence, sea level rise (Syvitski et al., 2009), res- of satellite observation (Hedley et al., 2010), although subsidence rates ervoir construction, a large number of artificial levees and embank- are poorly constrained. This is not a benign situation for the people of ments, channel bed sedimentation, and climate change may be acting Myanmar's delta coast: the same changes experienced along other together to add temporal trends and inflection points into flood peak deltas are predicted if the existing anthropogenic trends continue (e.g. time series. Such flood regime changes are globally widespread new reservoir construction, Fig. 13). Extensive dams are now being (Clarke, 2007; Kundzewicz et al., 2013). Although some hydrologists planned for the major rivers, and the resulting sediment retention will therefore recommend the “demise” of stationarity as a valid assumption likely cause delta shoreline retreat, impact the densely populated delta (Milly et al., 2008); others note the difficulty in characterizing the sup- region and increase the impacts of extreme events such as Cyclone posed temporal trends or change points in flood frequencies and magni- Nargis in 2008 (Hedley et al., 2010). tudes (Villarini et al., 2009). Without such defined trends, and given a) relatively short periods of records and b) the influence over flood hy- 4. Remote sensing measurements of Myanmar floods drology effected by the inter-annual and inter-decadal climate fluctua- tions described above, the outcomes of stationarity-based analyses are 4.1. Understanding flood hazard best treated as first approximations: onto which expected trends can be added once they are quantified. Since the mid-1970s, satellite observation has gathered a valuable One path beyond stationarity is to establish model-based prediction and still largely un-analyzed global record of flood inundation. Com- based on theory: e.g., changes in precipitation regimes with a warming mencing in late 1999, the two NASA MODIS sensors obtained daily sur- atmosphere, including extreme events, will cause accompanying chang- veillance of all of the Earth's surface waters. These data provide es in flood regime (Ward et al., 2014). For example, a global hydrological objective characterization of many damaging flood events, and, at a spa- model, simulating current and future river discharges has recently been tial resolution of 250 m, they can accurately define areas of flood risk applied to investigate future changes in flood risk (Kettner et al., in along many rivers, floodplains, and coastlines. Especially for the devel- press). The Hadley Global Environment Model 2 (HadGEM2- oping nations, the remote sensing archive provides the immediate op- Development-Team, 2011) with historical forcing and a representative portunity, without extensive or long-duration hydrological data concentration pathway (RCP 4.5) is used to simulate discharge for a infrastructure, to directly identify hazardous land areas (e.g., Figs. 6 30 y period (2070–2099) and the results are compared to a 30 y current and 13). climate conditions forced simulation over 1975–2004. The modeling in- Satellite passive microwave radiometry since 1998 has the comple- dicates global flood frequency increases by 2100 for all discharge recur- mentary ability to characterize flood hydrographs (Brakenridge et al., rence intervals (5–10, 10–25, 25–50, 50–100, and 100–200 y). The more 2007, 2012a; Revilla-Romero et al., 2014) and consistent daily data are frequent floods increase everywhere; increases in the less frequent available commencing in January 1998 (De Groeve et al., 2006; De events occur at a smaller number of places. In Asia, flood frequency for Groeve and Riva, 2009). When combined with mapped inundation, all recurrence intervals increases more than the average, globally. For this allows exceedance probabilities to be placed on observed inunda- Myanmar, increases in long recurrence interval (extreme) flooding is tion limits (Fig. 6). The remote sensing data can thereby be used to val- predicted along the Irrawaddy due to increased and more intense pre- idate flood modeling such as that accomplished at a global scale (UNEP/ cipitation upstream. UNISDR, 2013), or as a stand-alone method to map quantitative flood In a similar way, and in order to understand changing flood risk risk. The major limitation is the short period of record (19 y in 2016, along the coastlines and in the deltas, geomorphological changes can Fig. 5). 92 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 12. Detail of the Sittaung meander shown in Fig. 11. The outer channel bank moved 620 m to the southwest between March 21, 2004 and January 20, 2014, for an average rate of 62 m/y. The newly created floodplain land is already being farmed. A village southwest of the river in 2004 was swallowed by the river and no longer exists.

4.2. MODIS flood mapping for Myanmar band 1, and 841–876 nm, band 2) provide spatial resolution of 250 m; band 2 in particular strongly differentiates surface water from land. The two MODIS sensors provide 36 optical spectral bands; most Such information has been used to map the inundation extents reached bands offer spatial resolution of 1000 or 500 m. However, two bands, by floods at many locations worldwide, including in Myanmar in the visible and near-IR portions of the spectrum (620–670 nm, (Brakenridge et al., 2003, 2012b; Policelli, 2016, Figs. 6, 13, 16–18). G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 93

Fig. 13. MODIS-based mapping of Ayeyarwady and Salween floodplain and delta flooding, 2000 to present. Colours represent various years: 2000–2012 in blue-green to greenish brown, 2013–2015 in reddish brown or red. Small bright red areas include new reservoirs since early 2000 (they were not mapped as water at that time by the NASA SRTM mission). These reservoirs store water flowing to the Salween River (dark red areas, center part of map); large dams are planned also for the Salween itself. Some areas of red to the south are from newly developed aquaculture.

As floods evolve, frequent mapping of the inundation extents pro- determined by comparison of its inundation extent to the annual sur- vide a near real time indication of flood severity, and the flooding can face water extents reached in 2013 and 2014 (Figs. 16 and 18). Using be compared to previously mapped water, such as winter low flow con- this same approach, Fig. 17 shows the vast land areas affected by the ditions (Fig. 15) or typical annual maxima (Figs. 16–18). Flood duration Nargis coastal storm surge and unusual inland rainfall. Major flooding may affect flood damage and losses; the repeat imaging capability can was restricted to the delta and lower floodplain areas; major inland also provide this information. However, comparison of Figs. 15 and 16 river flooding in 2015 was mostly to the north of the Nargis-affected concisely illustrates the large amount of normal annual water variabili- area. ty. Water extent during the summer maximum is very much larger than in winter. Mapping sustained in this manner over some years provides 4.3. Information from passive microwave satellites increasingly comprehensive flood hazard information: unusual flood conditions are determined by comparison to typical annual high In contrast to optical remote sensing, certain spectral bands of mi- water. Thus, the effects of the damaging 2015 flooding are best crowave radiation emitted from the Earth's surface (e.g. data at the 94 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 14. Flood water (red) at the upstream end of the dual use (irrigation and hydropower) Thaphanseik Tha Pan Reservoir on the Mu River, July 24, 2015. Dam was completed in 2001. Flood expansion upstream occurred from monsoonal rains just prior to tropical storm Komen; no storage was available to mitigate subsequent even heavier rainfall. The reservoir filled to within 1 m of its crest. This is a portion of a map created by UNOSAT from ESA SENTINEL-1 satellite data acquired 18 July 2015 and NASA Landsat-8 satellite data acquired 29 April 2015 (UNITAR/UNOSAT, 2015).

37 GHz frequency) are relatively unaffected by cloud cover. Land sur- including for 5 “River Watch” sites in Myanmar (locations in Figs. 1a faces commonly exhibit much higher radiance values than water sur- and 15–18). To transform the water area-sensitive signal to discharge faces at this frequency, such that monitoring of a particular “satellite values, a calibration period, 2003–2007 is used and the signal values gauging site” centered over a river via microwave can provide a consis- are compared to the independent output of a global hydrological tent daily record of within-pixel surface water extent, a proxy of dis- model (WBM) driven by observed land surface variables and climatolo- charge changes (Brakenridge et al., 2007, 2012a; Van Dijk et al., 2016). gy (Cohen et al., 2011). This produces rating curves comparing remote Satellite microwave data at spatial resolutions of ~10 km are avail- sensing signal to discharge. The remote sensing and model output also able on a near-daily basis since 1998 from a constellation of NASA and allow assessments of the signal/noise and model/remote sensing agree- Japanese Space Agency (JAXA) satellites: TRMM, 1998–early 2015; ment exhibited by each gauging site (Table 1). As for in situ gauging sta- AMSR-E aboard Aqua, June 2002–September 2012; AMSR-2 on GCOM- tions, there is no expectation that each site records discharge changes W, and GPM (commencing in early 2014 and continuing to present). with equal precision and accuracy. For river observations, these data are processed at the European Commission's Joint Research Center to produce a consistent signal over selected measurement pixels. The signal tracks in-pixel surface 4.4. Myanmar flood history observed via microwave water extent changes and, with calibration via independent modeling, river discharge (Brakenridge et al., 2007, 2012a; De Groeve et al., Together, the River Watch microwave data (Figs. 5 and 19) provide 2006; De Groeve and Riva, 2009; Hirpa et al., 2013). an independent record of recent Myanmar flood and drought history. Based on this satellite microwave information, an automated pro- Table 2 is a chronological summary; “major” describes any annual cessor (http://floodobservatory.colorado.edu/DischargeAccess.html) flood that was as large or larger than the computed 5 y recurrence inter- provides daily-updated discharge information, commencing in 1998, val event. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 95

Fig. 15. Typical winter hydrography (February 2002, dark blue), as obtained by the NASA SRTM mission at a spatial resolution of 90 m. White dots are the location of microwave river measurement (River Watch) sites described in the text. Gray areas are urban light concentrations.

The results agree with the global analysis of (Ward et al., 2014)indi- discharge and total floodwater volume. Thus, version 3.4 of the Dart- cating El Niño to be generally associated with dryer-than-normal condi- mouth Flood Observatory's River Watch processor (http:// tions and La Niña with unusual monsoonal flooding in Myanmar. They floodobservatory.colorado.edu/DischargeAccess.html)alsoobtains also suggest the need for additional measures of flood “severity” other from the discharge information the total flood runoff volume and scales than instantaneous discharges and recurrence intervals/exceedance this as a ratio to that of the flood of record (Fig. 20), multiplied by 10, to probabilities. Flood severity may also be related to duration of overbank produce a simple flood magnitude statistic. 96 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 16. Blue is surface water mapped by the MODIS NRT Flood processor in 2013 and 2014; red is floodwater in 2015 that extends beyond water mapped in these previous years. Lettered locations show “hot spots” of annual flooding (compare with Fig. 15): A, along the Chindwin between sites 24 and 108 near Homalin, where a tributary enters; B, along the Ayeyarwady near site 26, downstream of Shwegu; C, where the Meza River enters the Ayeyarwady at site 27; D, flooding near Mandalay; E, near Monywa; F, south of the Chindwin junction at site 29 near Magway; G, near the head of the delta, by site 30, north of Hinthada, and junction with the Hlaing River distributary (town of Monyo is between the two watercourses); H and J are areas of flooding along the Pathein distributary; I is low delta land south of Bago, and K, flooding by the Myitmaka River near Maubin.

On this 0 (no flooding) to 10 (flood of record) magnitude scale, a upstream sites (#108 on the Chindwin and #26 on the Ayeyarwady) value of “8” indicates a severe flood, 0.8 of the flood volume of the larg- highlights the differences in the flood history between the two est observed. Examination of the flood magnitude times series for two branches, and also in comparison to the Ayeyarwady downstream of G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 97

Fig. 17. Tropical Cyclone Nargis flooding in deltaic Myanmar (2008), in light red, compared to typical winter hydrography (February 2002, dark blue), and annual maximum monsoonal flood extents for 2013 and 2014 (medium blue and light blue). Yangon is the gray shaded area in map's lower right quadrant.

the junction (#29, Fig. 20). The upper Chindwin experienced several This provides historical perspective: how frequent and damaging were major events in the early part of the record while the Ayeyarwady did previous floods? How was flooding affected earlier by ENSO status? not; both experienced major flooding in 2015 and again in 2016; the Then, two exceptionally damaging events are discussed in detail: the downstream site experienced major flooding for these two most recent 2008 Nargis storm surge, and the Komen tropical storm and monsoon events when both branches were contributing flood water (compare flooding in 2015. the sites in Fig. 20). In this regard, the tropical storm Komen in July 2016 brought unusually intense precipitation to northern and central 5.1. Pre-1968 floods Myanmar. Development of this storm, affecting both branches, and sub- sequent heavy monsoon rains overwhelmed the dryness experienced The records are discontinuous and cover only certain locations. Ac- earlier in the summer and caused major flooding along the lower cording to data from the British occupation, overbank inundation in Ayeyarwady. The El Niño began dissipating already in March 2016, the Ayeyarwady delta begins at a river discharge of approximately and by the 2016, weak La Niña conditions were already in effect; the 37,700 m3/s and stage of 12.95 m at Hintada (~50 km south from 2016 summer brought unusually heavy monsoonal rains and flooding River Watch site 30) and flooding occurs annually for a mean period along both Chindwin and upper Ayeyarwady, and again downstream of about 28 days. In 1877, a discharge value of 63,900 m3/s and stage (Figs. 19 and 20) of 13.37 m a.s.l. was reached. In 1947, a stage of 14.28 m a.s.l. was re- corded, and in 1939 flooding reached 13.94 m a.s.l. (Kravtsova et al., 5. Recent flood history 2009). This suggests that the 1947 flooding at this location is the flood of record for the late 19th/early 20th centuries. However, severe delta To extend the remote sensing record and better understand societal flooding is reported also for 1926 (Kravtsova et al., 2009). We located flood effects, we now examine the written record of recent major floods. no stage record for this event. In any case, at least 3 and possibly 4 98 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 18. 2015 flooding in deltaic Myanmar, colour symbology as for Fig. 17. River Watch sites 25 and 30 recorded the 2015 flooding. During flood season, the Hlaing River distributary, east and upstream of the Ayeyarwady near site 30, taps Ayeyarwady water and thus attenuates flood waves moving down the main channel.

exceptionally severe floods above ~60,000 m3/s apparently affected the Watch data are not calibrated to any ground station and may exhibit delta in the ~70 yr period, 1877–1947. Comparison to the site 30 River systematic bias). Watch record in Fig. 15 suggests that only the 2004 tropical cyclone- In the delta, the horseshoe dikes constructed for protection of the related flooding reached near this level since 1998 (but the River large delta islands were built mainly between 1880 and 1920; by then, they reached 1300 km in length and protected 6000 km2 from flooding. After the flood of 1939, where great damage occurred in residential Table 1 Summary of microwave discharge measurement (River Watch) site characteristics and ac- areas surrounded by dikes, it was noticed that these areas had not curacy for sites along the Chindwin (108 and 23) and Ayeyarwady (26, 29, 30). The signal aggraded as had un-diked areas that suffered less damage. There ensued range statistic records the total measured variability of the discharge-estimator signal; discussion about not rebuilding the dikes, but rebuilding occurred any- larger values indicate that the remote sensing signal is more sensitive to discharge varia- way (Kravtsova et al., 2009). tion. The noise statistic refers to the average signal variability on a daily basis; larger values On October 5, 1960, a severe cyclonic storm (Severe Cyclonic Storm indicate more non-hydrologic noise. The r2 (least squares coefficient of determination) values show the correlation of the independent WBM modeling discharge results to the Nine) moved westward from the South China Sea and crossed the remote sensing signal (over 5 y, 2000–2010, monthly daily maximum, mean, and mini- southern Myanmar Ayeyarwady delta, before proceeding into the Bay mum values, n = 180). of Bengal, turning northward, and inflicting severe damage on East Signal/model Signal Discharge Pakistan (now Bangladesh): with a 5.8 m surge on the coast that Site agreement range range Signal/noise r2 drowned villages (6000 killed and 100,000 homeless) (NOAA/NESDIS,

108 Very good 0.11 21,091 m3/s Good 0.66 2016; Wikipedia, 2016a). Based on its track, it may have caused storm 23 Good 0.08 25,507 m3/s Fair 0.57 surge or flooding damage in Myanmar as well. Also, from archived 26 Very good 0.09 17,242 m3/s Fair 0.67 Straits Times news reports (Hays, 2014): a coastal storm surge on May 3 29 Good 0.12 35,891 m /s Fair 0.57 16–18, 1967 flooded Rangoon (Yangon) with 100 fatalities and 800 3 30 Very good 0.20 35,245 m /s Very good 0.70 delta villages “ruined”. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 99

Fig. 19. The 1998–present time series of river discharge from four of the satellite gauging sites shown in Fig. 1a, proceeding from upstream to downstream. Sites 108 and 23 are on the Chindwin major tributary of the Ayeyarwady; 26 (see Fig. 5) is along the upper Ayeyarwady, and sites 29 and 30 are along the lower Ayeyarwady below the Chindwin junction. A low flow threshold (green line) is the 20th percentile discharge for each day of the year, 2003–2013. 100 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Table 2 Summary of Ayeyarwady and Chindwin river microwave discharge measurements from River Watch, 1998–2015, Figs. 5 and 19, and associated El Niño/La Niña conditions (Null, 2016).

1998–1999 Major flooding, Chindwin Strong La Niña and Ayeyarwady 2000 Normal flooding, most Dissipating La Niña sites 2001 Major flooding, site 23, Low flow or normal, both rivers Chindwin 2002 Major flooding, Chindwin Moderate El Niño Low flow, upper Ayeyarwady Major flooding, downstream Ayeyarwady 2003 Major flooding, Chindwin Severe cyclone (BOB 01) Rakhine coast, Minor flooding moderate El Niño downstream and Ayeyarwady 2004 Moderate flooding, Weak El Niño, severe cyclone upstream Chindwin and Ayeyarwady Major flooding downstream Record flood, head of Ayeyarwady delta 2005 Major, short-lived flooding, upstream Chindwin 2006 Unusually low Chindwin Weak El Niño peak discharges Normal flows along the Ayeyarwady 2007–2008 Major flooding, 2007 Moderate La Niña Somewhat less severe flooding, 2008 2009–2014 Normal or unusually dry Moderate El Niño (2009–2010), then Chindwin moderate La Niña (2010−2013) Normal or unusually dry Ayeyarwady Major local flooding, Ayeyarwady 2012 fl Major ooding, lower Fig. 20. The 1998–present time series of flood magnitudes measured by the River Watch Ayeyarwady 2013, 2014 sites, for the upper Chindwin (site 108), the upper Ayeyarwady (site 26), and the fl – 2015 Major ooding, Chindwin Strong El Niño (mid late 2015) Ayeyarwady below the Chindwin mouth (29). Flood discharges at site 29 reflect and Ayeyarwady upstream flooding along both rivers during 1998, 2015, and 2016. Flood of record along Ayeyarwady downstream 2016 Major flooding, Chindwin El Niño dissipating to weak La Niña and Ayeyarwady which “swept through central Burma and the western coastal state of Arakan … the Welfare Department said flood waters inundated the houses of over 100,000”. 5.2. 1968 cyclone and storm surge On September 12, 1977, another Reuters report indicates that 3 died and 3000 were left homeless; flooding was said to be the “worst in a Prior to Cyclone Nargis in 2008, the deadliest well-documented hundred years” and affected mainly the central parts of the country. storm surge to strike Myanmar was associated with the May 10, 1968 We also located reports of severe flooding in 1989 (2910 km2 were cyclone that made landfall in Sittwe, Rakhine. The United States Agency flooded): again during strong La Niña conditions, and on August 23, for International Development estimated that 1037 people and 17,537 1997, just before the record-breaking 1997–1998 El Niño arrived: livestock were killed. Close to 300,000 people were left homeless; “Myanmar's worst floods in decades have killed at least 13 people and 57,663 homes were destroyed (USAID, 1968). The surge associated left thousands homeless, according to government officials.” (Reuters, with this cyclone was 3 m high, and witnesses described a “tidal in Sentinel Times). wave” that “swallowed up whole villages” (USAID, 1968). Approximately 4 tropical cyclones/y traversed the Bay of Bengal each year between 1980 and 2000 and their tracks are recorded (NOAA/NESDIS, 2016; Wikipedia, 2016c). Most made landfall in eastern 5.3. The 1970s through 1990s India and in Bangladesh; 6 crossed the northwest (Rakhine) shoreline of Myanmar and flooded that region. Six others traversed Myanmar's A strong La Niña occurred in 1973–1976 (Null, 2016) and appears to southern delta region: in 1982, 1983, 1988, 1995, 1996, and 1999. have brought heavy rains to Myanmar. According to an August 23, 1974 Most of these approached the delta from the east, but the strong May Reuter news report, “the worst floods in a century” left 18 people dead 4, 1982 Cyclone Gwa formed in the Bay of Bengal, moved west to east, and two million homeless; floodwaters covered 77,700 km2.Allof and traversed the delta 60 km north of the coast. It was similar in Myanmar's five main rivers were reported to be flooding and eroding track, timing, and intensity to the Nargis event (Fig. 21). The storm embankments. Then, on May 5–8, 1975, 303 deaths occurred and surge at the shoreline (Jain et al., 2006) was also similar (3–4 m a.s.l.) 28,000 houses were destroyed by flooding in the delta. On June 23, to that observed for Nargis. In contrast to 2008, however: “Moderate 1976, a Reuters report indicates “200,000 made homeless by floods to heavy damage was experienced, but advance warning kept the G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 101

Fig. 21. Track of the 1982 Cyclone Gwa. The colour scheme uses the Saffir-Simpson Hurricane Wind Scale. Blue: tropical depression (winds b 62 km/h); green: tropical storm (winds 63–118 km/h); yellow to orange to red: category 1 to category 5 tropical cyclone (winds from 119 to N252 km/h). The coloured points show the location of the storm at six-hour intervals.

death toll at only five in an area where hundreds to thousands of deaths previous year (Heng and Wei-Yen, 2004). The monsoon flooding was are relatively common” (NOAA/NESDIS, 2016; Wikipedia, 2016c). exacerbated by an early tropical storm that made landfall over Rakhine State on May 19th, 2003. An upstream Chindwin River Watch site re- fl 5.4. 2003 monsoon rainfall and cyclone cords this exceptional ooding (Figs. 5, 19, and 20).

Monsoon flooding in 2003 was locally severe during a strong La 5.5. 2004 cyclone Niña. A UNICEF report states that 2003 saw Myanmar's worst flooding in 30 y, inundating N4000 km2 and left thousands homeless (UNICEF, On May 19th, 2004, a typhoon (Extremely Severe Cyclonic Storm 2004). The flooding caused a 14% drop in rice exports compared to the BOB 01) made landfall near Sittwe in Rakhine State, northwestern

Fig. 22. NASA Tropical Rainfall Measuring Mission (TRMM) estimate of cumulative rainfall between May 12th and May 19th, 2004 (Pierce and Lang, 2004). The location of Sittwe, capital of Rakhine State in Myanmar, is shown. N500 mm of rainfall fell over Rakhine State. 102 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Myanmar and continued across land to the east. UN documents describe 5.7. Floods in 2011 and 2012 the storm as “the worst to hit the region in nearly four decades” (UNICEF, 2004). After causing a storm surge and coastal flooding in Monsoon rain floods during a moderate La Niña in October 2011 in Rakhine, the cyclone dissipated as it traveled over land, bringing central Myanmar killed 100+ people and displaced thousands, mostly heavy rainfall and causing widespread crop damage, food shortages, from flash events and landslides in Magway (Fig. 1b). “One Seikphyu and damaged roads. River Watch sites along the upper Chindwin and resident told DVB that even two-story buildings were inundated to Ayeyarwady document severe flooding at this time (Figs. 5, 19, 20). the roof. Some residents … complained that they received little warning NASA Tropical Rainfall Measuring Mission (TRMM) data show about the impending disaster” (Hays, 2014). On October 11, 2011 500 mm of rainfall along the Myanmar coast (Fig. 22). Reuters further reported that: “At least 100 bodies had been found in The 2004 event was overwhelmed in global media by the Sumatran/ the low-lying parts of central Myanmar along the Irrawaddy River, Andaman Tsunami 7 months later, but that event had relatively little with at least 100 more missing after floods and torrential rains, accord- impact in Myanmar, with only 31 people reported killed, and limited ing to a reliable source in Pakokku, 450 km north of Yangon (Hays, shoreline inundation. Myanmar was much more severely affected by 2014). the 2004 tropical storm. The International Red Cross/Red Crescent esti- In 2012, monsoon rains during dissipating La Niña conditions in Au- mated that 220 people were killed by the surge and flooding (unofficial gust displaced into temporary shelters tens of thousands of people and estimates reached ~1000). An additional 14,000 people were left home- submerged large amounts of cropland. “The worst-affected southwest- less (IFRC, 2004). At least 300 schools and 2800 houses were damaged ern delta region…has been lashed by the heaviest rains in eight years, and many water supplies were contaminated. according to the authorities.”. No fatalities were reported in the delta, but N54,400 ha of farmland were inundated (Hays, 2014). River 5.6. 2006 Cyclone Mala and 2010 Cyclone Giri Watch sites 30 and 29 record this flooding (Fig. 19).

Two intense tropical cyclones affected Myanmar in 2006 (Maia, early season, April 29) and 2010 (Giri, late season, October 22). There 6. The 2008 Cyclone Nargis storm surge and flood were effective government warnings and evacuations, which may have kept fatalities relatively low. Three days before Mala made landfall, On May 2, 2008, landfall of Cyclone Nargis caused the worst natural the Department of Meteorology and Hydrology in Myanmar recom- disaster in the recorded history of Myanmar. The storm track is shown mended that officials broadcast storm warnings via state radio to in Fig. 23, which also provides the Komen storm path in 2015. Cyclone those in coastal regions. Twenty-two deaths were reported, most from Nargis flooded ~14,400 km2 in the delta (Tasnim et al., 2015). A post- inland rainfall and flooding in central Myanmar; River Watch site 26 re- flood survey team documented as much as 1 m of surface erosion on cords this short-lived flooding. this vulnerable delta, and N100 m of shoreline loss at some locations; fa- In 2010, memories of Cyclone Nargis (2008), see below, drove in- tality estimates exceed 138,000 (Fritz et al., 2009). tense government preparations for Giri, which struck Rakhine state as Nargis cyclogenesis was well monitored, but still the affected popu- category 4 and as the most intense cyclone recorded to landfall in lation was surprised. In the last week of April, an area of deep convec- Myanmar. Warnings were issued along the northwest coast of tion persisted near a low-level circulation in the Bay of Bengal Myanmar via radio, television, newspapers and loudspeakers. Approxi- 1150 km east-southeast of Chennai, India. With good outflow and low mately 53,000 people evacuated and fatalities were fewer than 160 peo- wind shear, the system slowly organized and consolidated its circula- ple despite a storm surge of 3.7 m and the destruction of 20,000+ tion. On April 28, the Indian Meteorological Department upgraded the homes (OCHA, 2010). Giri did not bring major inland flooding to system to Cyclonic Storm Nargis. Initially, the cyclone was forecast to Myanmar, either as reported in the media or recorded here via remote strike Bangladesh or southeastern India. It moved slowly northwest- sensing. ward, quickly strengthened, weakened on April 29 after encountering

Fig. 23. Cyclone Nargis, April 27–May 3, 2008, storm track (left), and Cyclone Komen, July 26 to August 2, 2015 (right). Nargis traversed the south Myanmar coastline; Komen moved very slowly, made landfall across the far northwestern Myanmar coastline, and then weakened to a tropical depression. G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 103 dryer air, then began a steady eastward motion and also intensified to a 7. Causation and avoidance of Nargis events category 4 storm on May 2. The rapidly strengthening cyclone moved ashore in Myanmar while The Nargis storm was an atypical tropical cyclone, hitting an unpre- at category 4 and with 215 km/h winds on May 2. After passing near pared and unwarned human population in its path. What caused the ex- Yangon, it gradually weakened until dissipating near the border of ceptional amount of losses, and what human actions could produce Myanmar and Thailand (Fig. 23). As noted, the time of year, track, inten- greater resilience and fewer losses in the future? The answers in part in- sity, and storm surge were somewhat similar to Cyclone Gwa in 1982 volve Earth Science, and in part societal responses or lack of responses (compare Figs. 21 and 23). However, the rate of movement, overall to such knowledge. size of storm, amount of rainfall on the delta, and timing with respect Flood damage (immediate) and losses (long term changes to the to the tidal cycle were different, and these factors acted to intensify economy) are most clearly affected by: a) flood intensity and duration, the flooding (Fritz et al., 2009). Nargis was a much larger storm, and re- b) the total population and economic assets located in harm's way, quired nearly 24 h to pass through (compared to only ~12 h for Gwa). c) warnings that can allow evacuation, and d) any protective measures The land crossing of this storm sent a storm surge at least 3.7 m high from wind and flood water. In regard to the Nargis storm intensity and 50 km inland across the Ayeyarwady delta (Fig. 17) and heavy rain on warnings, there was difficulty in accurately predicting this storm's path, the delta further inland (Fig. 24). and especially due to a sudden strengthening over unusually warm The destructiveness of the surge in part resulted from Nargis' direc- water (Lin et al., 2009). Predicting storm track and intensity are two tion of approach from the west to the southern delta region, which re- long-standing challenges in tropical storm meteorology. Both can be ad- sulted in maximum winds having a counterclockwise circulation in dressed by improved observational data and rapid assimilation of such the shallow offshore continental shelf area. These winds and the coastal data into predictive models. With millions living in areas now proven geomorphology of the region produced a high storm surge into the bay. to be vulnerable to lethal flooding (Fig. 17), accurate, advanced lead- Had Nargis made landfall further north (e.g. as for Gwa), the destruction time prediction of surge and rainfall are critical to future avoidance. would have been less. Storm surge modeling of Nargis is largely in Note that surge modeling (Dube et al., 2010) only generates part of agreement with the remote sensing (Brakenridge et al., 2012b). Land the picture: the coupled effects of surge and inland rainfall on saturated areas up to and sometimes above 7 m a.s.l. were flooded, and depending land must be included. on the topography that locally focused the incoming surge, but also due Another proximal cause of the Nargis catastrophe was the lack of to the local rainfall on the delta lowlands. communication of the storm warning, once the expected path was Labutta Township (along the Ywe River, one of the Ayeyarwady dis- known, directly to the inhabitants of the delta. As weather professionals tributaries in the southwest delta) reported 80,000 dead, with 10,000 in the outside world watched movement of the storm, the delta inhab- more deaths along the Bogale River, a distributary in the southeast itants slept. Addressing this is an urgent need. It requires, as well, local delta. Another ~55,000 people were reported missing, with allegations knowledge by the residents of the future risk from cyclones and surges. that government officials stopped updating the death toll after Remote sensing-derived maps, such as Fig. 17, are one way to commu- 138,000. Economic damage was estimated at over USD 10 billion. The nicate such risk. Myanmar government formally declared five regions—Yangon, Warning effectiveness, in turn, requires effective response options Ayeyarwady, Bago Divisions and Mon and Kayin States as disaster once warning is given. Evacuation routes must be identified and marked areas. It is estimated that at least 2.4 million people were severely affect- in advance throughout the coastal areas. Where quick evacuation to ed. Structural damage throughout Myanmar was extensive, causing higher ground is not possible (many settlements in the delta are acces- over a million to become homeless. In the first few days following the sible only via water), construction of elevated local storm shelters (as in cyclone, as many as 260,000 people were living in camps throughout Bangladesh) and protected access routes is needed. In this regard, many the Irrawaddy River Delta. An estimated 90–95% of the buildings in structures that existed pre-Nargis were overwhelmed by the height of the delta and much farmland, livestock, and fisheries were lost. the surge and the volume and intensity of the rain inland. The

Fig. 24. Rainfall rate from Cyclone Nargis over Western Bay of Bengal, as measured by the NASA TRMM satellite, May 3 (left) and May 5 (right). Heavy rainfall fell over the coast during the surge; the Yangon area was still receiving heavy rainfall on May 5. 104 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 destruction was particularly extensive because most structures in this would repeat the major problems created in other river basins in the region were not designed to withstand such events (Pulvirenti et al., region, such as the Indus and the Mekong (Kummu et al., 2010). The 2010). Rebuilding of the same dwellings without modification, in an effects of delta sediment starvation are also made more severe in the area clearly at grave risk, only sets the stage for the next disaster. context of global sea level rise (Syvitski et al., 2009). As early as 1939 We found no evidence to support a low probability of reoccurrence (Section 5.1), the differential in land elevation caused by levee- of a future event like Nargis. Thus, whereas the cyclone's path and protection of land in the delta from flooding and associated sedi- high surge were indeed “unusual” for this part of Myanmar (in contrast, ment was recognized; not rebuilding the levees was advocated. If 6 tropical storms made landfall in Rakhine in the two decades large dams are now constructed upstream, it will become even 1980–2000), the storm was not unprecedented, even in very recent his- more critical that some delta land areas be subject to controlled tory. Known similar storm trajectories, such as for Gwa in 1982, the ob- flooding in order to lesson such differential subsidence. Dam- served non-stationarity in tropical storm frequency (Hagag et al., 2010; related sediment starvation is a long term and progressive factor; Wang et al., 2013), and the historic record summarized here all empha- like deforestation and population growth in vulnerable areas, it size the probability of reoccurrence. Fig. 17 and any more-detailed maps sets the stage for severe losses of people and economies along the of the Nargis surge and its effects are an appropriate guide to future coast. Addressing these more-distal causes, however, can improve flood risk from Nargis-style events. the efficacy of better warnings, evacuation routes, local shelters, Finally, the Nargis disaster was also facilitated by long term causes, and increased risk awareness. all of which are presently increasing Myanmar's vulnerability: 8. The 2015 Cyclone Komen and intense monsoon floods 1) Population growth and migration. At the time of Nargis, the overall Myanmar population was much larger and also younger than in pre- The floods, damage, and losses in 2015 had a different meteorologi- vious decades. At the 1983 census the nation's population was 35.4 cal causation and location. As noted, intense lows often bring torrential million (Spoorenberg, 2013; Wikipedia, 2016b). The provisional re- rain to the Bay of Bengal in July and August and channel filling sults of the 2014 census show a total population of 51.4 million (of- “flooding” occurs in Myanmar at this time each year. However, 2015 fi N cial estimates of 60 million). This is an increase of nearly 150% in rainfall in Myanmar June through August was very much above average ~30 y. Some cities have grown much faster: the population of (~150–400%). Above average rainfall in June 2015, especially along the Hinthada, directly on the Ayeyarwady, was 82,500 in 1980 but by western coastal regions of Myanmar (Fig. 25), appeared to be strongly 2010 was 170,312. Population estimates for Yangon, upper delta, related to the MJO changes at this time. As the MJO continued to prog- the most populous city, are: 1980, 2.4 million, and 2010, 4.3 million ress farther east into the Pacific, it favored above average rainfall in (a 180% increase). This UN estimate is well below a 2009 U.S. State coastal Myanmar. By late June, the MJO was intensifying and became Department estimate of 5.5 million, which takes into account the ex- one of the strongest MJOs ever for July. Phases 5 and 6 of the MJO in par- pansion of city limits in the past two decades. Thus, in the 26 y since ticular are associated with high rainfall in Rakhine (Fig. 25). the last Nargis-like event (Gwa), both the region's total population As this occurred, and beginning in late July, a tropical cyclone and its location had very much changed. (Komen) also formed at the northern end of the Bay of Bengal, following 2) Deforestation. The expansion of population in the eastern delta, a near-stationary, week-long disturbance that itself brought very large where Yangon is situated, occurred together with deforestation amounts of rain. This cyclone moved very slowly. The nation experi- to the west. This may have substantially increased Nargis storm enced exceptionally heavy rainfall in the northern and the western damage and fatalities, via the removal of mangrove and other coastal areas July 16–August 2 (Figs. 25 and 26), and also flooding delta forests, and as compared to previous storms. The delta had long afterwards as the water traversed the country and made its way lost much mangrove forest along the coast to shrimp farms and to the sea (Figs. 18 and 27). Above average rainfall also continued rice paddies in the decade prior to Nargis, and continuing a through August. The Komen storm did not make landfall and there trend established for many years prior. Deforestation had long was no significant storm surge. However, 132 people were killed; 1.6 been underway: “by the late 19th century most of the dense low- million were temporarily displaced by floods and landslides, ~17,000 land evergreen forests, swamp and mangrove forests were homes were destroyed, and large amount of damage to agriculture cleared following human settlement” (Giri et al., 2010). As the and infrastructure was inflicted (Government-of-the-Union-of- 20th century ended, the remaining forests were concentrated to Myanmar, 2015). the west, in the less accessible estuaries of the delta. Just before Exceptional flooding occurred along the middle and lower reaches of Nargis, deforestation in the Ayeyarwady delta region had acceler- the Chindwin and Ayeyarwady rivers, and also on the Thanlwin, ated: “more than 20% of the mangrove forests…lost in only Sittoung, Shwegyin, Dokhtawady, and Ngawun rivers. The 2015 peak 10 years; the major cause being fuel wood collection” was the flood of record for ground-based gauging stations at Monywa (Leimgruber et al., 2005)(Giri et al., 2010) (Frenken, 2012).Yan- and second highest record for Kalewa (50 y of record). Similarly, for gon and its environs grew very fast in population, while the re- the Ayeyarwady River and at Pakokku, Nyaung Oo, Chauk, Minbu, maining populations in the southernmost delta areas lived in a Magway, Aunglan, Pyay, Seiktha, Hinthada and Zalun stations, the recently deforested landscape with increasingly little resistance peaks were the second or third highest on record. The duration at to surge flooding. Under a “business-as-usual” scenario, some re- high levels was approximately 3–17 days; but many floodplain lands searchers project that unprotected Ayeyarwady delta mangrove were inundated for much longer. The Mu River floodplain was entirely forests could be completely deforested by 2026 (Webb, 2013). inundated. Post-Nargis, however, sustainable forestry practices could in- Water supplies were also severely affected; and the flooding and salt stead help protect the millions of inhabitants now living in the water (from breached levees) severely damaged 0.5 million ha of rice delta. paddies, and 30,000 ha of fish and shrimp ponds (UN World Food Pro- 3) Dam and reservoir construction. The delta of the Ayeyarwady is clas- gramme). By August, the flooding was described as “the worst to affect sified as “in peril” on a global survey, and a contemporary 30% reduc- the country for decades”. Landslides during the June–July period (Fig. 2) tion in sediment influx was modeled from existing dams on the had already caused many fatalities, degraded road connectivity and tributaries (Syvitski et al., 2005, 2009; Syvitski and Milliman, communications, and affected relief operations. Also, during the 2007). Reduced sediment influx may have played a role in Nargis- prolonged flooding, the N-S trunk rivers such as the Ayeyarwady and related flooding and shoreline retreat. New large dams whose design Sittaung and their distributaries delivered large quantities of sediment do not fully account for the downstream effects of sediment trapping onto the delta and to the sea (Fig. 27). G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 105

Fig. 25. Weekly total rainfall during late June, and also from the weeks ahead and during Cyclone Komen development over Western Bay of Bengal, as measured by the NASA TRMM satellite, June 18–June 25, 2015 (left), June 25–July 01, 2015 (center), July 29–August 05 (right).

9. Causation and avoidance of Komen events At Kalay, the situation “remains critical as a structural solution to avoid inundation under similar extreme conditions cannot easily be devel- Compared to Nargis, the 2015 tropical storm Komen- and heavy oped and implemented.”. At Monywa, severe erosion occurred and monsoon-related flooding was a slow-onset disaster. However, a signif- dikes were poorly maintained: repairs and improvements are icant cause of damage and losses was a lack of long lead-time prediction. recommended. The status of ENSO at this time indicated the possibility of summer These initial recommendations appear straightforward in the wake drought, not flooding. Some research underway may help advance pre- of major flooding: protect, extend, and strengthen the flood defenses al- dictive capability. The Madden–Julian Oscillation (MJO), like ENSO, af- ready in place, and especially those that failed. However, there are also fects Bay of Bengal weather during the monsoon (Sein et al., 2015). As drawbacks involved in rebuilding flood protection structures, recog- the low level convergence of the MJO propagates through the Bay, a nized locally as early as 1939, and they are especially relevant in this de- large cyclonic anomaly develops; this leads to a rapid intensification of veloping nation. Responsible flood protection engineering ideally westerlies, moisture influx, and deepening of the Bay of Bengal mon- requires knowledge of long-term flood hydrology, and of expected soon trough. In the meantime, vertical wind shear is reduced, providing changes thereof. Protective structures encourage settlement at locations a favorable environment for cyclones to form. When the MJO's positive where, if structures fail, the outcomes are severe for those thought to be phase coincides with development of the monsoon trough, tropical protected (this occurred in 2015). In regard to the long-existing major storm genesis and monsoon onset are likely to occur concurrently. delta levees, “a prerequisite for the proper functioning of the U- MJO exhibits a marked inter-annual variability. Via a combination of embankment … is that the whole system must survive under extreme magnitude and phasing, ENSO-coupled and uncoupled cases occur, conditions: one weak spot could threaten the whole protection system” but cyclogenesis and monsoon onset are most strongly affected by the (Steijn et al., 2015). MJO phasing. As these and other relationships continue to be Despite this need for secure knowledge about the probability and researched, and incorporated into predictive modeling (Sein et al., magnitude of future flooding, field surveys are unable to identify 2015; Webster and Yang, 1992), reliable advanced lead time prediction whether the river levels and damage experienced at a particular loca- may become possible. tion in 2015 were highly unusual, with low future exceedance probabil- Another proximal cause was flood protection structures that failed. ities, or were from flood discharges of relatively frequent return periods. In early September, a Dutch Risk Reduction Team visited two flood- The available remote sensing record provides the greatest opportunity affected regions in Myanmar: dike-protected areas in the upper and to fill this data need, as illustrated in Figs. 6, 19, and 20,butitstillsuffers middle parts of the Ayeyarwady delta, and Kalay/Monywa along the from a relatively short period of observation. Unlike the case for Nargis, Chindwin in the Sagaing Region (Steijn et al., 2015). In parts of the preparations for avoiding damage from future 2015-style inland first area, no breaches had occurred and the dikes were in generally flooding must extend throughout most of Myanmar, and require de- good condition. However, the report expresses concern for dike signing within the context of Myanmar's exceptionally dynamic, overtopping and indicates that all dikes should be improved to the “Au- sediment-rich, and flood-prone fluvial systems. thorized Crest Level”. Also, there is a recommendation to increase the The critical choices can be made clear by example. Thus, some possi- height of the dikes in the delta by 1.5 m. Another discussion involves ex- ble flood recovery projects described by the Dutch engineering team in- tending the dike along the Pathein river (in the delta) downstream; it is cluded: removing the “bottlenecks” in the Myittha river between Kalay noted that this would affect the upstream water levels, possibly worsen- and Kalaywa; protecting Kalay by a new dike and dredging secondary ing the situation there (more chance of overtopping and piping). At the channels; and constructing meander cut-offs and protection schemes upstream Chindwin location, at Nyaung Done, “the lives of hundreds of at various river bend locations. However, there are now widely- people depend on the strength of a poorly engineered, poorly main- understood failures of similar structural flood control measures in the tained and wrongly used dike which is undermined by river dynamics.”. industrialized nations to actually provide protection in the long term. 106 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109

Fig. 26. Rainfall rate from Cyclone Komen over Western Bay of Bengal, as measured by the NASA GPM satellite, July 30, 2015. The large size of the storm is illustrated, as well as the moisture flow inland over Myanmar.

Flood protection efforts in both North America and Europe are now em- 10. Conclusion phasizing very different approaches. These include: 1) levee removal or setback, thereby reconnecting the floodplain to the channel (Bayley, This paper reviewed the climatological, geomorphological and an- 1991); 2) preservation of the negative relief features of natural flood- thropogenic factors affecting flood risk in Myanmar. It described how plains (Lewin and Ashworth, 2014), including oxbow lakes and aban- these combined during the 2008 and 2015 storms to produce major hu- doned meanders that attenuate flood waves; 3) encouragement of manitarian disasters, and also how frequent similar events have been in appropriate uses of flood-prone land (such as some forms of agricul- the recent past, and, lastly, how long term trends are increasing the risk ture); 4) discouragement of other uses, such as housing; 5) elevation of future disasters. of structures where they must be located in the floodplain; and 6) con- Prior to the 2015 flooding, the government of Myanmar published a trolled channel avulsions, levee breechings, and flooding to facilitate National Adaptation Program for Action (NAPA) to analyze past and ex- continued inputs of sediment to large floodplains and delta areas (Day pected impacts of climate change in Myanmar and identify priority ac- et al., 2016; Galat, 1998; Opperman et al., 2009; Simonovic, 2001; tions for adaptation (NECC, 2012). According to NAPA, floods and Syvitski and Brakenridge, 2013; Tocker et al., 1998; Tockner and droughts are expected to become more frequent and intense. Tempera- Stanford, 2002). These recovery measures can be politically difficult to tures, rainfall, and runoff are likely to increase; extreme rainfall will be- accomplish, but they are based on increasingly secure surface processes come more frequent; and dry periods during the monsoon season may knowledge concerning the long-term effects of many flood control occur more than in the past. Within this context, building a more flood- structures. Coupled with the early warning of evolving flood events, resilient Myanmar may require a different approach than probabilistic all of these measures would facilitate avoidance of flood damage and hazard assessment and design criteria alone can provide. If stationarity losses such as occurred in 2015. assumptions are discarded, the most recent past may be the best guide G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 107

Fig. 27. August 8, 2015 NASA MODIS image showing sediment plumes along the southern Myanmar (Ayeyarwady and Sittaung delta) coastline.

to the near-term future. Flood recovery and rebuilding efforts would in processes pose both opportunities and constraints for further this case treat these recent disasters as “the new normal”, instead of as development. extreme events with low probabilities of reoccurrence in the near Myanmar is now in fact on the verge of a phase of rapid economic future. development. Many dams have recently been constructed along the In 2008, N138,000 citizens of Myanmar perished in a southern delta smaller rivers and more are planned for the largest ones. Experience storm surge/flood disaster: from a somewhat unusual tropical storm from the other southern Asian river deltas indicates that large dams (Nargis) that tracked west to east and just offshore the delta front, be- and side levees can have progressive and dramatic effects on the stabil- fore turning inland to pass over the capital city of Yangon. The storm ity of delta landforms downstream and on inland flooding. Unless the could have been anticipated: another delta surge-producing tropical cy- track of development occurs differently in Myanmar, the same negative clone had followed a roughly similar track in 1982; a major surge affect- effects will occur. To avoid these, the supply of sediment to the coast and ed the Yangon area in 1967. Between 1982 and 2008, the local delta to the floodplains must be maintained. As well, extensive mangrove de- population had increased by ~150–180%; the Nargis storm was errone- forestation has already occurred, and is still underway; this is an inde- ously considered by many to be an “unprecedented” event. Then, only pendent factor increasing damage from storm surge flooding there. 7 y later, Madden–Julian modulated intense monsoonal rainfall and an- Sustainable forestry practices, however, could increase coastal settle- other tropical storm (Komen) resulted in another major flood disaster. ment protection from storm surges. This affected most of western Myanmar and U.S. $1.5 billion of its econ- Finally, after the 2015 flooding, a Dutch Risk Reduction Team visited omy; 132 citizens perished; recovery and rebuilding is currently under- Myanmar to examine in the field the flood damage and make recovery way (Government-of-the-Union-of-Myanmar, 2015). For several major recommendations. Their report emphasizes the need for integrated, rivers, the return period of this inland flooding was only several de- whole-watershed planning for resilient flood recovery. For reservoirs, cades; our survey of past, late 20th century flooding also supports this embankments, sluices and canals for irrigation or drainage, and river conclusion. works, it may well pay off to “allow possibilities for flood management, The physiography and climatology of Myanmar amplify the surface sediment management, reduction of salt intrusion and nature develop- process effects of large storm events. The steep highlands are suscepti- ment”, rather than to restrict planning to a single sector (e.g. hydropow- ble to major and lethal landslides and flash floods. Upstream along the er development) (Steijn et al., 2015). Our review supports the same major trunk rivers, rapid lateral channel migration, meander-cutoffs, conclusion. There are alternative recovery strategies available for inte- and avulsions are common during the flood flows; they caused major grated watershed development: settlement and agriculture on levee- damage in 2015. In the lowlands, and in response to tropical storms protected but low-lying delta land areas can be protected by intermit- and intense monsoonal rains, major floods transport pulses of sediment tent levee-breaching and controlled flooding by sediment-rich water downstream, including to the delta landforms, which require such in- (Auerbach et al., 2015). Elsewhere, large infrequently activated river di- puts for their stability. Any post-flood remedial engineering, such as versions are being used for Mississippi delta restoration, where episodic levee rebuilding, thus occurs within an usually dynamic landscape, large diversions (N5000 m3/s) builds land quickly while having tran- both along the shorelines and inland, one that is strongly affected by cli- sient impacts on the estuarine system (Day et al., 2016). Along the mate variability, and in which standard quantitative hazard evaluations Ouachita River in the southern U.S., a 28 km levee installed in the late can only capture part of the actual flood risk. The landscape and surface 1960s has recently been breached in order to allow re-establishment 108 G.R. Brakenridge et al. / Earth-Science Reviews 165 (2017) 81–109 of productive bottomland forest, fishery, and downstream flood control Frenken, K., 2012. Irrigation in Southern and Eastern Asia in figures, AQUASTAT Survey – fi 2011. FAO Water Reports 37. 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