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Forecasting the flood-pulse in Central Amazonia by ENSO-indices
Journal of Hydrology (2007) 335, 124– 132
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journal homepage: www.elsevier.com/locate/jhydrol
Forecasting the flood-pulse in Central Amazonia by ENSO-indices ¨ngart Jochen Scho
a,b,*
, Wolfgang J. Junk
a
a
Max-Planck-Institute for Limnology, Working Group Tropical Ecology, August-Thienemannstr. 2, P.O. Box 165, ¨n, Germany 24302 Plo b ˆnia, Av. Andre ´ Arau ´jo 2936, P.O. Box 478, 69011-970 Manaus-AM, Brazil Instituto Nacional de Pesquisas da Amazo Received 9 February 2006; received in revised form 31 August 2006; accepted 10 November 2006
KEYWORDS Amazon; Maximum water level; Forecast; El Nin ˜o-Southern Oscillation (ENSO); Southern Oscillation Index (SOI); Sea surface temperature (SST)
The flood-pulse of the large rivers in Central Amazonia triggers ecological processes of the floodplain systems inducing a severe seasonality in the annual cycle between the aquatic and the terrestrial phase. The nutrient-rich floodplains (va ´rzea) have the highest human population density in Amazonia and economic activities such as fishing, agriculture, pasture and timber extraction are directly associated with water-level fluctuations. The discharge of many tropical river systems responds to the El Nin ˜o-Southern Oscillation (ENSO) originating from the tropical Pacific. Several studies show a strong relationship between the flooding regime of Amazonian rivers and ENSO-indices, such as the meteorological Southern Oscillation Index (SOI) and sea surface temperatures (SSTs). During warm ENSO-phases (El Nin ˜o) flood-levels are lowered and aquatic phases are shortened, while high and prolonged flooding is associated to cold ENSO-phases (La Nin ˜a). Here we present retrospective forecasts of the maximum water level in Central Amazonia from 1903 to 2004 – generally occurring in the second half of June – and the length of the aquatic phase along the flood-gradient by models based on the SOI and SST anomalies of the El Nin ˜o 3.4 region in February, four months before its appearance. The forecast of the flood-pulse allows also predicting parameters correlated with the flood-pulse (e.g., tree growth, biogeochemical cycles) and increases the efficiency in planning and executing of economic activities by the human population (e.g., fishery, timber extraction, agriculture). ª 2006 Elsevier B.V. All rights reserved. Summary
* Corresponding author. Address: Instituto Nacional de Pesquisas da Amazo ˆnia (INPA), Av. Andre ´ Arau ´jo 1756, P.O. Box 478, 69011970 Manaus-AM, Brazil. Tel.: +55 92 36433156; fax: +55 92 36421503. E-mail address: [email protected] (J. Scho ¨ngart).
Introduction The monomodal flood-pulse (Junk et al., 1989) – the regular, annual long-term flooding – is the dominating triggering factor of ecological processes in the large floodplains of the
0022-1694/$ - see front matter ª 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2006.11.005
Forecasting the flood-pulse in Central Amazonia by ENSO-indices tropical rivers like the Amazon, Mekong and Congo. The mean amplitude of annual water-level fluctuations in the Central Amazonian river-floodplain system amounts to about 10 m (Irion et al., 1997) as a result from intra-annual variations in precipitation of a catchment area with almost 3 million km2 corresponding to the sum of the Negro and Solimo ˜es drainage basins (Figs. 1 and 2a) (Richey et al., 1989; Williams et al., 2005). Since 1903 the water level is daily recorded at the harbour of Manaus close to the confluence of the Negro and Solimo ˜es rivers forming together the Amazon. The flood-pulse is more or less predictable: During 1903– 2004 the high-water level has occurred in 55% of the cases in the second half of June (Irion et al., 1997) (Fig. 2b), however, the height of the maximum flood varies considerably from one year to the other (Fig. 2c). The lowest high-water level has been recorded in the year 1926 at 21.76 m asl (above average sea level), the maximum flood was almost 8 m higher reaching 29.69 m asl in the year 1953. The flood-pulse, which exists in the Amazon basin since the Tertiary (Junk, 1989), induces a distinct seasonality in the annual cycle between the aquatic phase and the terrestrial phase. Thus the flood-pulse triggers biogeochemical cycles, growth rhythms and life cycles of many species of the biota such as algae, macrophytes, trees, fishes and invertebrates (Junk, 1997). Floodplains along sediment loaded, nutrient-rich white-water rivers (va ´rzea) have the highest human population densities in rural Amazonia due to the easy accessibility, richness in natural resources and high productive soils (Junk et al., 2000). Economic activities in the va ´rzea such as agriculture, fishery and timber extraction
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are directly associated with water-level fluctuations. Fishing is performed during low-water levels when fish stocks are concentrated in the remaining water-bodies. Agriculture is practiced during the terrestrial phase on higher elevations where flooding is shortened and crops have enough time to mature (Junk et al., 2000). Forestry is mainly restricted to the aquatic phase when the forests can easily be accessed and costs for skidding and transport are low (Barros and Uhl, 1995; Albernaz and Ayres, 1999). However, inter-annual differences of the high-water level and consequently varying length of the aquatic phase along the floodgradient have a strong impact on the execution of these activities and thus on the economic situation of thousands of riparian people. The success of planning and executing fishery, agriculture and forestry in the va ´rzea depends much on the development of the flood-pulse and thus affects the income and life-standard of the people from year to year. River systems are comprehensive integrators of precipitation anomalies on large scales. Many studies have shown that the El Nin ˜o-Southern Oscillation (ENSO) influences water-level fluctuations and discharge in the catchments of many tropical rivers such as the Nile, Congo, Orinoco, Parana ´, Tocantins and the mainstem and tributaries of the Amazon (Richey et al., 1989; Marengo, 1992; Whetton and Rutherfurd, 1994; Adis and Latif, 1996; Amarasekera et al., 1997; Marengo et al., 1998; Guyot et al., 1998; Uvo and Graham, 1998; Zeng, 1999; Dettinger et al., 2000; Uvo et al., 2000; Marengo and Nobre, 2001; Robertson et al., 2001; Coe et al., 2002; Foley et al., 2002; Aalto et al., 2003; Souza Filho and Lall, 2003; Potter et al., 2004;
Figure 1 Map of the Amazon basin indicating the location of Manaus (Central Amazonia) and the Negro and Solimo ˜es drainage basins with about 3 million km2 (Richey et al., 1989; Williams et al., 2005).
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Figure 2 (a) Regular flood-pulse patterns of the Negro River during the 1990s. (b) Occurrence of the maximum water level of the Negro River. (c) Inter-annual variations of the maximum water level over a 101-year long time series (data: Capitania dos Portos – port authority at Manaus).
Scho ¨ngart et al., 2004; Labat et al., 2005; Ronchail et al., 2005). The ENSO causes large-scale precipitation anomalies in the Amazon basin (Sombroek, 2001), which results in high flood-levels of the Amazon River during La Nin ˜a events (cold ENSO-phases) and low flood-levels during El Nin ˜o events (warm ENSO-phases). In this study, we test the correlation between flood-pulse data of Central Amazonia and ENSOindices to develop a model allowing an accurate forecast of the maximum water level and the duration of the aquatic phase in the floodplains.
Material and methods Daily records since 1903 of the river level in the harbour of Manaus (data: Capitania dos Portos – port authority at Manaus, http://www.snph.am.gov.br/Portal/index.php) were used to calculate the duration of the aquatic phase in the Central Amazonian floodplains for elevations between
22.5 m asl and 29.0 m asl in 50-cm intervals. The significance in the difference between flood-pulse data (maximum water level, duration of the aquatic phase at different elevations) during ENSO-events (La Nin ˜a and El Nin ˜o years) and other years was examined using T-tests (Scho ¨ngart et al., 2004). ENSO-years were defined by 5-month running means of SST anomalies in the El Nin ˜o 3.4 region (5N– 5S/120–170W) exceeding +0.4 C (El Nin ˜o) or 0.4 C (La Nin ˜a) for six or more consecutive months (Trenberth, 1997). To test the impact of ENSO-indices on the flood-pulse we used the meteorological Southern Oscillation Index (SOI), defined as the normalized pressure difference between Tahiti and Darwin, Australia, and oceanographic sea surface temperature data (monthly SST anomalies) of the traditional El Nin ˜o regions 1 + 2, 3, 3.4 and 4 (Table 1) (Trenberth and Stepaniak, 2001). The correlations between the high-water level and ENSO-indices were performed for a 12-month period before the appearance of the maximum
Table 1 Information on the dataset of the ENSO-indices: Southern Oscillation Index (SOI) and sea surface temperatures anomalies (SSTs) in the tropical Pacific ENSO-index SST El Nin ˜o SST El Nin ˜o SST El Nin ˜o SST El Nin ˜o SOI (UEA)
Latitude 1+2 3 3.4 4
0–10S 5N–5S 5N–5S 5N–5S Atmospheric pressure anomalies Darwin (Australia) and Tahiti
Longitude 90–80W 150–90W 170–120W 160E–150W between
Period 1950–2000 1950–2000 1903–2000 1950–2000 1903–2004
Forecasting the flood-pulse in Central Amazonia by ENSO-indices water level in Central Amazonia commonly in the second half of June (Irion et al., 1997). Data for the monthly SOI and SST anomalies were obtained from the Climatic Research Unit (University of East Anglia) http:// www.cru.uea.ac.uk/cru/data/soi.htm and the Climate Prediction Centre (National Oceanic and Atmospheric Administration) http://www.cpc.ncep.noaa.gov/data/indices/ index.html, respectively. Statistical analyses were performed with the programs STATISTICA 6.0 and SigmaPlot 8.2.
Results The high-water level of the Negro River shows significant correlations with ENSO-indices of different geographic regions (Fig. 3). Differences can be observed among the strength and period of the correlations between the floodlevel and the ENSO-indices. Maximum correlations between high-water level in Central Amazonia and SST anomalies occurs first in the El Nin ˜o regions 1 + 2 in November, afterwards in the El Nin ˜o region 3 in December and in February in the El Nin ˜o region 4. However, the correlations between the flood-level and these SST anomalies are not very strong.
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Relatively high correlations are found between the maximum water level of the Negro River and the SOI in February (r = 0.45, p < 0.001) and the SST anomalies in the El Nino 3.4 region in February (r = 0.49, p < 0.001). During El Nin ˜o events the water level of the Negro River is significantly lower (27.05 m asl) compared to other years (28.09 m asl) (T-value = 3.97, p < 0.001), while in La Nin ˜a years the flood-level is significantly higher (28.19 m asl) than in other years (27.54 m asl) (T-value = 3.02, p < 0.01) (Table 2). Fig. 4 indicates the difference in the duration of the aquatic phase for elevations of 22.5–29.0 asl in the Central Amazonian floodplains comparing ENSO-events with other years. The aquatic phase is shortened in El Nino years and extended in La Nina years. These differences are significant at all elevations, but most pronounced at middle elevations of 26.0 m asl (Fig. 4) where the aquatic phase is shortened by 44 days in average during El Nin ˜o events and extended by 31 days in La Nin ˜a years. The significant relationship between the flood-pulse and ENSO-indices allows forecasting the flooding in Central Amazonia. Therefore, we relate the high-water level as dependent variable to the mean water level and SOI of February as independent variables using a multiple regression
Figure 3 Correlation between the maximum water level of the Negro River and ENSO-indices (SOI, SST anomalies for the El Nin ˜o regions 1 + 2, 3, 4, 3.4) for a 12-months period before the occurrence of the maximum flood level in June. Grey bars indicate significant correlations at the 95% confidence-level.
Table 2 Significant differences of the maximum water level between ENSO-years (La Nin ˜a and El Nin ˜o events) and other years performed by T-tests Two sample test
El Nin ˜o events
Other years
Flood-pulse Max. water level (m asl)
n = 33 27.05
n = 64 28.09
T-value 3.98 (p < 0.001)
La Nin ˜a events
Other years
T -value
n = 29 28.19
n = 68 27.54
3.02 (p < 0.01)
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Figure 4 Difference in the length of the aquatic phase between normal years and ENSO-events (La Nin ˜a, El Nin ˜o) for elevations in 50-cm intervals along the flood-gradient in Central Amazonian floodplains. At all elevations the length of the aquatic phase differs significantly between the ENSO-events and other years (p< 0.05).
function. The model explains 51% of the variability (r = 0.71, p < 0.0001) between the parameters (Fig. 5). Partial regression analysis indicates that the mean water level in February (b = 0.565, T-value = 7.90, p < 0.0001) contributes more than the February SOI (b = 0.374, T-value = 5.23, p < 0.0001) to explain the variability of the maximum water level. The observed and the predicted high-water levels in Central Amazonia for the period 1903–2004 show a good congruence (Fig. 6). In 46.5% of the cases the differences between observed and forecasted flood-levels are less than ±50 cm and in 81.2% of the cases less than ±100 cm. In 97.0% of the cases the difference between observed and forecasted maximum water level is still less than ±150 cm. Only in the years 1924, 1926 and 1985 the model cannot accurately forecast the high-water level in Central Amazonia (Figs. 5 and 6). The model also allows predicting the length of the aquatic phase for different elevations by the SST anomalies in February of the El Nin ˜o 3.4 region (Fig. 7). Flooding increases form the higher elevations at 29.0 m asl towards lower elevations at 22.5 m asl and with decreasing SST anomalies grouped in 0.5 C classes. Flooding is extended in La Nin ˜a and shortened during El Nin ˜o years.
Discussion and conclusion Our results indicate that the water level in Central Amazonia is a comprehensive integrator of SST anomalies of the Pacific as suggested by many other studies (Adis and Latif, 1996; Amarasekera et al., 1997; Dettinger et al., 2000; Uvo et al., 2000; Coe et al., 2002; Foley et al., 2002; Ronchail et al., 2002; Aalto et al., 2003; Scho ¨ngart et al., 2004). Generally speaking, El Nin ˜o causes lower maximum flood levels and shortened aquatic phases and La Nin ˜a high flood-levels and prolonged inundation. Based on this relationship we develop a retrospective forecast model that
predicts the maximum flood level four months before its appearance in the second half of June (Irion et al., 1997). This model is a powerful instrument to increase the efficiency of planning and executing of economic activities such as agriculture, timber extraction and fishery, which are the main income sources of the riparian people (Albernaz and Ayres, 1999). In the Amazonian floodplains the main economic activity during the high-water period is the timber extraction due to the easy accessibility of the forests. Especially forests situated on higher elevations (high va ´rzea) have huge stocks of timber resources of mainly tree species with low wood densities (Worbes et al., 2001). Harvesting of timber starts in March/April before the water reaches the areas and the logs are skidded when the forests get flooded in June/July (Albernaz and Ayres, 1999). However, in years of low maximum water levels the high va ´rzea does not inundate and harvested logs cannot be skidded and get rotten causing economical deficits for the riverine people and ecological damages on the forest ecosystem. Our model allows predicting the maximum flood level already at the end of February. Areas for timber extraction can thus be selected according to the forecasted water level avoiding economic and ecological damages. From 1903 to 2004 our retrospective forecasts of maximum water levels has in 97% of the cases a high accuracy (differences between predicted and observed values are less than 150 cm). The lowest maximum stage in Central Amazonia (Manaus) of the century-long record has occurred during the strong El Nin ˜o event in 1926 (Quinn and Neal, 1992) at 21.76 m asl, almost 6 m lower than the average maximum water level (27.72 m asl). Our model still highlights this year as absolute minimum value (25.21 m asl), but our forecast differs more than 340 cm from the observed value. Exceptional drought associated with largescale fires in the basin of the Rio Negro and Venezuela has been reported for the period 1925/1926 (Sternberg, 1987;
Forecasting the flood-pulse in Central Amazonia by ENSO-indices
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Figure 5 Multiple regression model to forecast the maximum water level of the Negro River using the mean water level of February and the SOI of February. The model explains 51% of the variability of the parameters; only in three years (3% of the cases) the model fails to predict the maximum flood-level. To forecast the maximum water level a simple model can be applied using the relationships between mean water level of February and maximum water level (parameters a and b) and February SOI and maximum water level (parameter c). Parameters are indicated with standard errors.
Figure 6 Comparison between the observed (black line) and predicted (dotted line) maximum flood levels of the Negro River for the period 1903–2004. Only in the years 1924, 1926 and 1985 (indicated by arrows) the predicted and observed values of the maximum flood level differs more than 150 cm.
Sombroek, 2001) and instrumental records indicate severe negative precipitation anomalies within the catchment area of the Amazon River (Williams et al., 2005). The SOI record
indicates a sustained negative index for 16 months (average of 7.77) associated with the 1926 dry year, beginning in May 1925. From 1903 to 2004, a period of negative monthly
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Figure 7 Mean length of the aquatic phase in the Central Amazonian floodplains for the elevations from 22.5 m asl to 29.0 m asl in dependence of the SST anomalies in the El Nin ˜o 3.4 region (classes of 0.5 C).
SOIs greater than 16 months has only occurred during May 1911–October 1912 (average of 9.48) and August 1939– April 1942 (average of 11.79). However, for these years the forecast differs less than 100 cm from the observed water level. Also in other El Nin ˜o years with SOI values in February below that of 1926 ( 14.5), such as in 1905 ( 16.8), 1912 ( 17.3), 1931 ( 14.9), 1941 ( 15.4), 1978 ( 24.4), 1983 ( 33.3), 1990 ( 17.3) and 1998 ( 19.2) our model accurately predicts the maximum water level. It is possible that the severe drought in 1925 in the northern watershed of the Negro River associated with large-scale fires contributed to the major drought in 1926, by a negative feedback on rainfall in the Amazon basin from abundant smoke aerosols (Williams et al., 2005). Deforestation increased significantly during the last 15 years in the Amazon basin (Laurance et al., 2004). Two future scenarios with opposite trends may have an impact of the flooding patterns in Central Amazonia. The first scenario is that runoff and river discharge generally increase when natural vegetation (especially forest) is removed (Foley et al., 2005). For instance, the Tocantins River basin in Brazil showed a 25% increase in river discharge between 1960 and 1995, coincident with expanding agriculture in the catchment area but no major change in precipitation (Costa et al., 2003). The second trend is a decrease of inundations driven by increasing temperatures and CO2-concentrations (Foley et al., 2002). Models of Costa and Foley (2002) predict a basin-wide decrease of precipitation and increase of temperature by the effect of deforestation and doubled CO2-concentrations also including interactions between these processes. Temperature increase in the Amazon basin may exacerbate drought effects by accelerated evaporation (White et al., 1999). Severe droughts provoked by El Nin ˜o cause CO2-releases on large areas of the Amazo-
nian non-flooded ‘‘terra firme’’ forests (Prentice and Lloyd, 1998; Foley et al., 2002) and increase the fire risk of these forests in areas experiencing high rates of selective logging and fragmentation (Nepstad et al., 1999). Large-scale fires, pastures, agriculture and selective logging release huge amounts of greenhouse gases (Laurance et al., 2001; Cochrane, 2003; Asner et al., 2005) which feed back and accelerate climate changes (Houghton et al., 2001) and probably increase the strength of the ENSO (Timmermann et al., 1999). A dendroclimatic (based on tree rings) ENSO-sensitive proxy of the tree species Piranhea trifoliata Baill. (Euphorbiaceae) in the Central Amazonian floodplains (Scho ¨ngart et al., 2004) indicates an increasing El Nin ˜o activity during the last two centuries that may be already the result of increasing greenhouse gas concentrations in the atmosphere. However, the complexity of interaction between climate change, land use, changes in forest vegetation and atmospheric composition and the manifestation of these factors in the freshwater systems of the Amazon basin need more research effort in the future. It is difficult to interpret short-term changes in the flooding patterns during some years by land use changes in the Amazon basin as suggested by Gentry and Lopez-Parodi (1980) who related the high flood levels during several years at the beginning of the 1970s (Fig. 2c) with increasing deforestation in the Andean watershed. It is more likely that the high maximum water levels during these years have been the result of a persistent cold ENSO-phase (La Nin ˜a conditions) in the first half of the 1970s (Trenberth, 1997). The uncertainties in future scenarios underscore the need for long-term observational data. The century-long record at the harbour of Manaus is not long enough to explain if exceptional lowwater levels or high floodings are in the range of the natural climate variability or already a result of human-induced
Forecasting the flood-pulse in Central Amazonia by ENSO-indices changes of the global climate. Reconstructions of the preinstrumental flood-patterns by sediment cores or tree-ring records (Scho ¨ngart et al., 2004) may help to explain the appearance of severe low and high-water levels in the Amazon basin in the context of occurring land use changes and global climate change. Tree growth in the floodplains responds to water-level fluctuations (Scho ¨ngart et al., 2002) and dendrochronological analysis permits the detection of El Nin ˜o signals (Scho ¨ngart et al., 2004, 2005). However, ecosystems and socio-economic cultures and sectors may become more and more affected in the Amazon basin and other tropical regions by the high vulnerability to extreme climate events driven by increased greenhouse gas emissions caused by deforestation and population growth. This makes our model a powerful instrument avoiding human and economic damages in the Central Amazonian floodplains.
Acknowledgements This study was financed by the Max-Planck-Institute for Limnology.
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132 Potter, C., Zhang, P., Klooster, S., Genovese, V., Shekhar, S., Kumar, V., 2004. Understanding controls on historical river discharge in the world’s largest drainage basins. Earth Interactions 8 (2), 1–21. Prentice, I.C., Lloyd, J., 1998. C-quest in the Amazon Basin. Nature 396, 619–620. Quinn, W.H., Neal, V.T., 1992. The historical record of El Nin ˜o events. In: Bradley, R.S., Jones, P.D. (Eds.), Climate Since A.D. 1500. Routledge, London, pp. 623–648. Richey, J.E., Nobre, C.A., Deser, C., 1989. Amazon river discharge and climate variability: 1903–1985. Science 246, 101–103. Robertson, A.W., Mechoso, C.R., Garcia, N.O., 2001. Interannual prediction of the Parana River. Geophysical Research Letters 22, 4235–4238. Ronchail, J., Cochonneau, G., Molinier, M., Guyot, J.L., de Miranda Chaves, A.G., Guimara ˜es, V., de Oliveira, E., 2002. Interannual rainfall variability in the Amazon basin and sea-surface temperatures in the equatorial Pacific and tropical Atlantic Oceans. International Journal of Climatology 22, 1663–1686. Ronchail, J., Labat, D., Calle `de, J., Cochonneau, G., Guyot, J.L., Filizola, N., Oliveira, E., 2005. In: Discharge variability within the Amazon basinRegional Hydrological Impacts of Climatic Changes – Hydroclimatic Variability, 296. IAHS Publications, pp. 21–30. Scho ¨ngart, J., Piedade, M.T.F., Ludwigshausen, S., Horna, V., Worbes, M., 2002. Phenology and stem-growth periodicity of tree species in Amazonian floodplain forests. Journal of Tropical Ecology 18, 581–597. Scho ¨ngart, J., Junk, W.J., Piedade, M.T.F., Ayres, J.M., Hu ¨ttermann, A., Worbes, M., 2004. Teleconnection between tree growth in the Amazonian Floodplains and the El Nin ˜o-Southern Oscillation effect. Global Change Biology 10, 683–692. Scho ¨ngart, J., Piedade, M.T.F., Wittmann, F., Junk, W.J., Worbes, M., 2005. Wood growth patterns of Macrolobium acaciifolium (Benth.) Benth. (Fabaceae) in Amazonian blackwater and white-water floodplain forests. Oecologica 145, 654–661. Sombroek, W., 2001. Spatial and temporal patterns of Amazon rainfall. Ambio 30, 388–396.
J. Scho ¨ngart, W.J. Junk Souza Filho, F.A., Lall, U., 2003. Seasonal to interannual ensemble streamflow forecasts for Ceara, Brazil: applications of a multivariate, semiparametric algorithm. Water Resources Research 39 (11), 1/1–1/13. Sternberg, H.O’R., 1987. Aggravation of floods in the Amazon River as a consequence of deforestation? Geografiska Annaler 69A, 201–219. Timmermann, A., Oberhuber, J., Bacher, A., Esch, M., Latif, M., Roeckner, E., 1999. Increased El Nin ˜o frequency in a climate model forced by future greenhouse warming. Nature 398, 694– 697. Trenberth, K.E., 1997. The definition of El Nin ˜o. Bulletin of the American Meteorological Society 78, 2771–2777. Trenberth, K.E., Stepaniak, D.P., 2001. Indices of El Nin ˜o evolution. Journal of Climate 14, 1697–1701. Uvo, C.B., Graham, N.E., 1998. Seasonal runoff forecast for northern South America. A statistical model. Water Resources Research 34 (12), 3515–3524. Uvo, C.B., To ¨lle, U., Berndtsson, R., 2000. Forecasting discharge in Amazonia using artificial neural networks. International Journal of Climatology 20, 1495–1507. Whetton, P., Rutherfurd, I., 1994. Historical ENSO teleconnection in the eastern hemisphere. Climatic Change 28, 221–253. White, A., Cannell, M.G.R., Friend, A.D., 1999. Climate change impacts on ecosystems in the terrestrial carbon sink: new assessment. Global Environmental Change 9, S21–S30. Williams, E., Antonia, A.D., Antonia, V.D., Almeida, J.D., Suarez, F., Liebmann, B., Malhado, A.C.M., 2005. The drought of the century in the Amazon basin: an analysis of the regional variation of rainfall in South America in 1926. Acta Amazonica 35 (2), 231–238. Worbes, M., Piedade, M.T.F., Scho ¨ngart, J., 2001. Holzwirtschaft im Mamiraua ´-Projekt zur nachhaltigen Entwicklung einer Region ¨ berschwemmungsbereich des Amazonas. Forstarchiv 72, im U 188–200. Zeng, N., 1999. Seasonal cycle and interannual variability in the Amazon hydrologic cycle. Journal of Geophysical Research 104 (D8), 9097–9106.
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journal homepage: www.elsevier.com/locate/jhydrol
Forecasting the flood-pulse in Central Amazonia by ENSO-indices ¨ngart Jochen Scho
a,b,*
, Wolfgang J. Junk
a
a
Max-Planck-Institute for Limnology, Working Group Tropical Ecology, August-Thienemannstr. 2, P.O. Box 165, ¨n, Germany 24302 Plo b ˆnia, Av. Andre ´ Arau ´jo 2936, P.O. Box 478, 69011-970 Manaus-AM, Brazil Instituto Nacional de Pesquisas da Amazo Received 9 February 2006; received in revised form 31 August 2006; accepted 10 November 2006
KEYWORDS Amazon; Maximum water level; Forecast; El Nin ˜o-Southern Oscillation (ENSO); Southern Oscillation Index (SOI); Sea surface temperature (SST)
The flood-pulse of the large rivers in Central Amazonia triggers ecological processes of the floodplain systems inducing a severe seasonality in the annual cycle between the aquatic and the terrestrial phase. The nutrient-rich floodplains (va ´rzea) have the highest human population density in Amazonia and economic activities such as fishing, agriculture, pasture and timber extraction are directly associated with water-level fluctuations. The discharge of many tropical river systems responds to the El Nin ˜o-Southern Oscillation (ENSO) originating from the tropical Pacific. Several studies show a strong relationship between the flooding regime of Amazonian rivers and ENSO-indices, such as the meteorological Southern Oscillation Index (SOI) and sea surface temperatures (SSTs). During warm ENSO-phases (El Nin ˜o) flood-levels are lowered and aquatic phases are shortened, while high and prolonged flooding is associated to cold ENSO-phases (La Nin ˜a). Here we present retrospective forecasts of the maximum water level in Central Amazonia from 1903 to 2004 – generally occurring in the second half of June – and the length of the aquatic phase along the flood-gradient by models based on the SOI and SST anomalies of the El Nin ˜o 3.4 region in February, four months before its appearance. The forecast of the flood-pulse allows also predicting parameters correlated with the flood-pulse (e.g., tree growth, biogeochemical cycles) and increases the efficiency in planning and executing of economic activities by the human population (e.g., fishery, timber extraction, agriculture). ª 2006 Elsevier B.V. All rights reserved. Summary
* Corresponding author. Address: Instituto Nacional de Pesquisas da Amazo ˆnia (INPA), Av. Andre ´ Arau ´jo 1756, P.O. Box 478, 69011970 Manaus-AM, Brazil. Tel.: +55 92 36433156; fax: +55 92 36421503. E-mail address: [email protected] (J. Scho ¨ngart).
Introduction The monomodal flood-pulse (Junk et al., 1989) – the regular, annual long-term flooding – is the dominating triggering factor of ecological processes in the large floodplains of the
0022-1694/$ - see front matter ª 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2006.11.005
Forecasting the flood-pulse in Central Amazonia by ENSO-indices tropical rivers like the Amazon, Mekong and Congo. The mean amplitude of annual water-level fluctuations in the Central Amazonian river-floodplain system amounts to about 10 m (Irion et al., 1997) as a result from intra-annual variations in precipitation of a catchment area with almost 3 million km2 corresponding to the sum of the Negro and Solimo ˜es drainage basins (Figs. 1 and 2a) (Richey et al., 1989; Williams et al., 2005). Since 1903 the water level is daily recorded at the harbour of Manaus close to the confluence of the Negro and Solimo ˜es rivers forming together the Amazon. The flood-pulse is more or less predictable: During 1903– 2004 the high-water level has occurred in 55% of the cases in the second half of June (Irion et al., 1997) (Fig. 2b), however, the height of the maximum flood varies considerably from one year to the other (Fig. 2c). The lowest high-water level has been recorded in the year 1926 at 21.76 m asl (above average sea level), the maximum flood was almost 8 m higher reaching 29.69 m asl in the year 1953. The flood-pulse, which exists in the Amazon basin since the Tertiary (Junk, 1989), induces a distinct seasonality in the annual cycle between the aquatic phase and the terrestrial phase. Thus the flood-pulse triggers biogeochemical cycles, growth rhythms and life cycles of many species of the biota such as algae, macrophytes, trees, fishes and invertebrates (Junk, 1997). Floodplains along sediment loaded, nutrient-rich white-water rivers (va ´rzea) have the highest human population densities in rural Amazonia due to the easy accessibility, richness in natural resources and high productive soils (Junk et al., 2000). Economic activities in the va ´rzea such as agriculture, fishery and timber extraction
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are directly associated with water-level fluctuations. Fishing is performed during low-water levels when fish stocks are concentrated in the remaining water-bodies. Agriculture is practiced during the terrestrial phase on higher elevations where flooding is shortened and crops have enough time to mature (Junk et al., 2000). Forestry is mainly restricted to the aquatic phase when the forests can easily be accessed and costs for skidding and transport are low (Barros and Uhl, 1995; Albernaz and Ayres, 1999). However, inter-annual differences of the high-water level and consequently varying length of the aquatic phase along the floodgradient have a strong impact on the execution of these activities and thus on the economic situation of thousands of riparian people. The success of planning and executing fishery, agriculture and forestry in the va ´rzea depends much on the development of the flood-pulse and thus affects the income and life-standard of the people from year to year. River systems are comprehensive integrators of precipitation anomalies on large scales. Many studies have shown that the El Nin ˜o-Southern Oscillation (ENSO) influences water-level fluctuations and discharge in the catchments of many tropical rivers such as the Nile, Congo, Orinoco, Parana ´, Tocantins and the mainstem and tributaries of the Amazon (Richey et al., 1989; Marengo, 1992; Whetton and Rutherfurd, 1994; Adis and Latif, 1996; Amarasekera et al., 1997; Marengo et al., 1998; Guyot et al., 1998; Uvo and Graham, 1998; Zeng, 1999; Dettinger et al., 2000; Uvo et al., 2000; Marengo and Nobre, 2001; Robertson et al., 2001; Coe et al., 2002; Foley et al., 2002; Aalto et al., 2003; Souza Filho and Lall, 2003; Potter et al., 2004;
Figure 1 Map of the Amazon basin indicating the location of Manaus (Central Amazonia) and the Negro and Solimo ˜es drainage basins with about 3 million km2 (Richey et al., 1989; Williams et al., 2005).
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Figure 2 (a) Regular flood-pulse patterns of the Negro River during the 1990s. (b) Occurrence of the maximum water level of the Negro River. (c) Inter-annual variations of the maximum water level over a 101-year long time series (data: Capitania dos Portos – port authority at Manaus).
Scho ¨ngart et al., 2004; Labat et al., 2005; Ronchail et al., 2005). The ENSO causes large-scale precipitation anomalies in the Amazon basin (Sombroek, 2001), which results in high flood-levels of the Amazon River during La Nin ˜a events (cold ENSO-phases) and low flood-levels during El Nin ˜o events (warm ENSO-phases). In this study, we test the correlation between flood-pulse data of Central Amazonia and ENSOindices to develop a model allowing an accurate forecast of the maximum water level and the duration of the aquatic phase in the floodplains.
Material and methods Daily records since 1903 of the river level in the harbour of Manaus (data: Capitania dos Portos – port authority at Manaus, http://www.snph.am.gov.br/Portal/index.php) were used to calculate the duration of the aquatic phase in the Central Amazonian floodplains for elevations between
22.5 m asl and 29.0 m asl in 50-cm intervals. The significance in the difference between flood-pulse data (maximum water level, duration of the aquatic phase at different elevations) during ENSO-events (La Nin ˜a and El Nin ˜o years) and other years was examined using T-tests (Scho ¨ngart et al., 2004). ENSO-years were defined by 5-month running means of SST anomalies in the El Nin ˜o 3.4 region (5N– 5S/120–170W) exceeding +0.4 C (El Nin ˜o) or 0.4 C (La Nin ˜a) for six or more consecutive months (Trenberth, 1997). To test the impact of ENSO-indices on the flood-pulse we used the meteorological Southern Oscillation Index (SOI), defined as the normalized pressure difference between Tahiti and Darwin, Australia, and oceanographic sea surface temperature data (monthly SST anomalies) of the traditional El Nin ˜o regions 1 + 2, 3, 3.4 and 4 (Table 1) (Trenberth and Stepaniak, 2001). The correlations between the high-water level and ENSO-indices were performed for a 12-month period before the appearance of the maximum
Table 1 Information on the dataset of the ENSO-indices: Southern Oscillation Index (SOI) and sea surface temperatures anomalies (SSTs) in the tropical Pacific ENSO-index SST El Nin ˜o SST El Nin ˜o SST El Nin ˜o SST El Nin ˜o SOI (UEA)
Latitude 1+2 3 3.4 4
0–10S 5N–5S 5N–5S 5N–5S Atmospheric pressure anomalies Darwin (Australia) and Tahiti
Longitude 90–80W 150–90W 170–120W 160E–150W between
Period 1950–2000 1950–2000 1903–2000 1950–2000 1903–2004
Forecasting the flood-pulse in Central Amazonia by ENSO-indices water level in Central Amazonia commonly in the second half of June (Irion et al., 1997). Data for the monthly SOI and SST anomalies were obtained from the Climatic Research Unit (University of East Anglia) http:// www.cru.uea.ac.uk/cru/data/soi.htm and the Climate Prediction Centre (National Oceanic and Atmospheric Administration) http://www.cpc.ncep.noaa.gov/data/indices/ index.html, respectively. Statistical analyses were performed with the programs STATISTICA 6.0 and SigmaPlot 8.2.
Results The high-water level of the Negro River shows significant correlations with ENSO-indices of different geographic regions (Fig. 3). Differences can be observed among the strength and period of the correlations between the floodlevel and the ENSO-indices. Maximum correlations between high-water level in Central Amazonia and SST anomalies occurs first in the El Nin ˜o regions 1 + 2 in November, afterwards in the El Nin ˜o region 3 in December and in February in the El Nin ˜o region 4. However, the correlations between the flood-level and these SST anomalies are not very strong.
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Relatively high correlations are found between the maximum water level of the Negro River and the SOI in February (r = 0.45, p < 0.001) and the SST anomalies in the El Nino 3.4 region in February (r = 0.49, p < 0.001). During El Nin ˜o events the water level of the Negro River is significantly lower (27.05 m asl) compared to other years (28.09 m asl) (T-value = 3.97, p < 0.001), while in La Nin ˜a years the flood-level is significantly higher (28.19 m asl) than in other years (27.54 m asl) (T-value = 3.02, p < 0.01) (Table 2). Fig. 4 indicates the difference in the duration of the aquatic phase for elevations of 22.5–29.0 asl in the Central Amazonian floodplains comparing ENSO-events with other years. The aquatic phase is shortened in El Nino years and extended in La Nina years. These differences are significant at all elevations, but most pronounced at middle elevations of 26.0 m asl (Fig. 4) where the aquatic phase is shortened by 44 days in average during El Nin ˜o events and extended by 31 days in La Nin ˜a years. The significant relationship between the flood-pulse and ENSO-indices allows forecasting the flooding in Central Amazonia. Therefore, we relate the high-water level as dependent variable to the mean water level and SOI of February as independent variables using a multiple regression
Figure 3 Correlation between the maximum water level of the Negro River and ENSO-indices (SOI, SST anomalies for the El Nin ˜o regions 1 + 2, 3, 4, 3.4) for a 12-months period before the occurrence of the maximum flood level in June. Grey bars indicate significant correlations at the 95% confidence-level.
Table 2 Significant differences of the maximum water level between ENSO-years (La Nin ˜a and El Nin ˜o events) and other years performed by T-tests Two sample test
El Nin ˜o events
Other years
Flood-pulse Max. water level (m asl)
n = 33 27.05
n = 64 28.09
T-value 3.98 (p < 0.001)
La Nin ˜a events
Other years
T -value
n = 29 28.19
n = 68 27.54
3.02 (p < 0.01)
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Figure 4 Difference in the length of the aquatic phase between normal years and ENSO-events (La Nin ˜a, El Nin ˜o) for elevations in 50-cm intervals along the flood-gradient in Central Amazonian floodplains. At all elevations the length of the aquatic phase differs significantly between the ENSO-events and other years (p< 0.05).
function. The model explains 51% of the variability (r = 0.71, p < 0.0001) between the parameters (Fig. 5). Partial regression analysis indicates that the mean water level in February (b = 0.565, T-value = 7.90, p < 0.0001) contributes more than the February SOI (b = 0.374, T-value = 5.23, p < 0.0001) to explain the variability of the maximum water level. The observed and the predicted high-water levels in Central Amazonia for the period 1903–2004 show a good congruence (Fig. 6). In 46.5% of the cases the differences between observed and forecasted flood-levels are less than ±50 cm and in 81.2% of the cases less than ±100 cm. In 97.0% of the cases the difference between observed and forecasted maximum water level is still less than ±150 cm. Only in the years 1924, 1926 and 1985 the model cannot accurately forecast the high-water level in Central Amazonia (Figs. 5 and 6). The model also allows predicting the length of the aquatic phase for different elevations by the SST anomalies in February of the El Nin ˜o 3.4 region (Fig. 7). Flooding increases form the higher elevations at 29.0 m asl towards lower elevations at 22.5 m asl and with decreasing SST anomalies grouped in 0.5 C classes. Flooding is extended in La Nin ˜a and shortened during El Nin ˜o years.
Discussion and conclusion Our results indicate that the water level in Central Amazonia is a comprehensive integrator of SST anomalies of the Pacific as suggested by many other studies (Adis and Latif, 1996; Amarasekera et al., 1997; Dettinger et al., 2000; Uvo et al., 2000; Coe et al., 2002; Foley et al., 2002; Ronchail et al., 2002; Aalto et al., 2003; Scho ¨ngart et al., 2004). Generally speaking, El Nin ˜o causes lower maximum flood levels and shortened aquatic phases and La Nin ˜a high flood-levels and prolonged inundation. Based on this relationship we develop a retrospective forecast model that
predicts the maximum flood level four months before its appearance in the second half of June (Irion et al., 1997). This model is a powerful instrument to increase the efficiency of planning and executing of economic activities such as agriculture, timber extraction and fishery, which are the main income sources of the riparian people (Albernaz and Ayres, 1999). In the Amazonian floodplains the main economic activity during the high-water period is the timber extraction due to the easy accessibility of the forests. Especially forests situated on higher elevations (high va ´rzea) have huge stocks of timber resources of mainly tree species with low wood densities (Worbes et al., 2001). Harvesting of timber starts in March/April before the water reaches the areas and the logs are skidded when the forests get flooded in June/July (Albernaz and Ayres, 1999). However, in years of low maximum water levels the high va ´rzea does not inundate and harvested logs cannot be skidded and get rotten causing economical deficits for the riverine people and ecological damages on the forest ecosystem. Our model allows predicting the maximum flood level already at the end of February. Areas for timber extraction can thus be selected according to the forecasted water level avoiding economic and ecological damages. From 1903 to 2004 our retrospective forecasts of maximum water levels has in 97% of the cases a high accuracy (differences between predicted and observed values are less than 150 cm). The lowest maximum stage in Central Amazonia (Manaus) of the century-long record has occurred during the strong El Nin ˜o event in 1926 (Quinn and Neal, 1992) at 21.76 m asl, almost 6 m lower than the average maximum water level (27.72 m asl). Our model still highlights this year as absolute minimum value (25.21 m asl), but our forecast differs more than 340 cm from the observed value. Exceptional drought associated with largescale fires in the basin of the Rio Negro and Venezuela has been reported for the period 1925/1926 (Sternberg, 1987;
Forecasting the flood-pulse in Central Amazonia by ENSO-indices
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Figure 5 Multiple regression model to forecast the maximum water level of the Negro River using the mean water level of February and the SOI of February. The model explains 51% of the variability of the parameters; only in three years (3% of the cases) the model fails to predict the maximum flood-level. To forecast the maximum water level a simple model can be applied using the relationships between mean water level of February and maximum water level (parameters a and b) and February SOI and maximum water level (parameter c). Parameters are indicated with standard errors.
Figure 6 Comparison between the observed (black line) and predicted (dotted line) maximum flood levels of the Negro River for the period 1903–2004. Only in the years 1924, 1926 and 1985 (indicated by arrows) the predicted and observed values of the maximum flood level differs more than 150 cm.
Sombroek, 2001) and instrumental records indicate severe negative precipitation anomalies within the catchment area of the Amazon River (Williams et al., 2005). The SOI record
indicates a sustained negative index for 16 months (average of 7.77) associated with the 1926 dry year, beginning in May 1925. From 1903 to 2004, a period of negative monthly
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Figure 7 Mean length of the aquatic phase in the Central Amazonian floodplains for the elevations from 22.5 m asl to 29.0 m asl in dependence of the SST anomalies in the El Nin ˜o 3.4 region (classes of 0.5 C).
SOIs greater than 16 months has only occurred during May 1911–October 1912 (average of 9.48) and August 1939– April 1942 (average of 11.79). However, for these years the forecast differs less than 100 cm from the observed water level. Also in other El Nin ˜o years with SOI values in February below that of 1926 ( 14.5), such as in 1905 ( 16.8), 1912 ( 17.3), 1931 ( 14.9), 1941 ( 15.4), 1978 ( 24.4), 1983 ( 33.3), 1990 ( 17.3) and 1998 ( 19.2) our model accurately predicts the maximum water level. It is possible that the severe drought in 1925 in the northern watershed of the Negro River associated with large-scale fires contributed to the major drought in 1926, by a negative feedback on rainfall in the Amazon basin from abundant smoke aerosols (Williams et al., 2005). Deforestation increased significantly during the last 15 years in the Amazon basin (Laurance et al., 2004). Two future scenarios with opposite trends may have an impact of the flooding patterns in Central Amazonia. The first scenario is that runoff and river discharge generally increase when natural vegetation (especially forest) is removed (Foley et al., 2005). For instance, the Tocantins River basin in Brazil showed a 25% increase in river discharge between 1960 and 1995, coincident with expanding agriculture in the catchment area but no major change in precipitation (Costa et al., 2003). The second trend is a decrease of inundations driven by increasing temperatures and CO2-concentrations (Foley et al., 2002). Models of Costa and Foley (2002) predict a basin-wide decrease of precipitation and increase of temperature by the effect of deforestation and doubled CO2-concentrations also including interactions between these processes. Temperature increase in the Amazon basin may exacerbate drought effects by accelerated evaporation (White et al., 1999). Severe droughts provoked by El Nin ˜o cause CO2-releases on large areas of the Amazo-
nian non-flooded ‘‘terra firme’’ forests (Prentice and Lloyd, 1998; Foley et al., 2002) and increase the fire risk of these forests in areas experiencing high rates of selective logging and fragmentation (Nepstad et al., 1999). Large-scale fires, pastures, agriculture and selective logging release huge amounts of greenhouse gases (Laurance et al., 2001; Cochrane, 2003; Asner et al., 2005) which feed back and accelerate climate changes (Houghton et al., 2001) and probably increase the strength of the ENSO (Timmermann et al., 1999). A dendroclimatic (based on tree rings) ENSO-sensitive proxy of the tree species Piranhea trifoliata Baill. (Euphorbiaceae) in the Central Amazonian floodplains (Scho ¨ngart et al., 2004) indicates an increasing El Nin ˜o activity during the last two centuries that may be already the result of increasing greenhouse gas concentrations in the atmosphere. However, the complexity of interaction between climate change, land use, changes in forest vegetation and atmospheric composition and the manifestation of these factors in the freshwater systems of the Amazon basin need more research effort in the future. It is difficult to interpret short-term changes in the flooding patterns during some years by land use changes in the Amazon basin as suggested by Gentry and Lopez-Parodi (1980) who related the high flood levels during several years at the beginning of the 1970s (Fig. 2c) with increasing deforestation in the Andean watershed. It is more likely that the high maximum water levels during these years have been the result of a persistent cold ENSO-phase (La Nin ˜a conditions) in the first half of the 1970s (Trenberth, 1997). The uncertainties in future scenarios underscore the need for long-term observational data. The century-long record at the harbour of Manaus is not long enough to explain if exceptional lowwater levels or high floodings are in the range of the natural climate variability or already a result of human-induced
Forecasting the flood-pulse in Central Amazonia by ENSO-indices changes of the global climate. Reconstructions of the preinstrumental flood-patterns by sediment cores or tree-ring records (Scho ¨ngart et al., 2004) may help to explain the appearance of severe low and high-water levels in the Amazon basin in the context of occurring land use changes and global climate change. Tree growth in the floodplains responds to water-level fluctuations (Scho ¨ngart et al., 2002) and dendrochronological analysis permits the detection of El Nin ˜o signals (Scho ¨ngart et al., 2004, 2005). However, ecosystems and socio-economic cultures and sectors may become more and more affected in the Amazon basin and other tropical regions by the high vulnerability to extreme climate events driven by increased greenhouse gas emissions caused by deforestation and population growth. This makes our model a powerful instrument avoiding human and economic damages in the Central Amazonian floodplains.
Acknowledgements This study was financed by the Max-Planck-Institute for Limnology.
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