Artigo Completo - Clique Aqui! - Universidade Federal de Viçosa
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Artigo Completo - Clique Aqui! - Universidade Federal de Viçosa
Projections of climate change effects on discharge and inundation in the Amazon basin Mino Viana Sorribas, Rodrigo C. D. Paiva, John M. Melack, Juan Martin Bravo, Charles Jones, Leila Carvalho, Edward Beighley, et al. Climatic Change An Interdisciplinary, International Journal Devoted to the Description, Causes and Implications of Climatic Change ISSN 0165-0009 Climatic Change DOI 10.1007/s10584-016-1640-2 1 23 Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media Dordrecht. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Climatic Change DOI 10.1007/s10584-016-1640-2 Projections of climate change effects on discharge and inundation in the Amazon basin Mino Viana Sorribas 1 & Rodrigo C. D. Paiva 1 & John M. Melack 2 & Juan Martin Bravo 1 & Charles Jones 3 & Leila Carvalho 3 & Edward Beighley 4 & Bruce Forsberg 5 & Marcos Heil Costa 6 Received: 21 August 2015 / Accepted: 21 February 2016 # Springer Science+Business Media Dordrecht 2016 Abstract Climate change and its effects on the hydrologic regime of the Amazon basin can impact biogeochemical processes, transportation, flood vulnerability, fisheries and hydropower generation. We examined projections of climate change on discharge and inundation extent in the Amazon basin using the regional hydrological model MGB-IPH with 1-dimensional river hydraulic and water storage simulation in floodplains. Future projections (2070–2099) were obtained from five GCMs from IPCC’s Fifth Assessment Report CMIP5. Climate projections have uncertainty and results from different climate models did not agree in total Amazon flooded area or discharge anomalies along the main stem river. Overall, model runs agree better with wetter (drier) conditions over western (eastern) Amazon. Results indicate that increased mean and maximum river discharge for large rivers draining the Andes in the northwest contributes to increased mean and maximum discharge and inundation extent over Peruvian floodplains and Solimões River (annual mean-max: +9 % - +18.3 %) in western Amazonia. Decreased river discharges (mostly dry season) are projected for eastern basins, and Electronic supplementary material The online version of this article (doi:10.1007/s10584-016-1640-2) contains supplementary material, which is available to authorized users. * Mino Viana Sorribas [email protected] 1 IPH/UFRGS - Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil 2 Bren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, CA, USA 3 Geography Department, University of California, Santa Barbara, Santa Barbara, CA, USA 4 Civil and Environmental Engineering, Northeastern University, Boston, MA, USA 5 Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil 6 Universidade Federal de Viçosa, Viçosa, Brazil Author's personal copy Climatic Change decreased inundation extent at low water (annual min) in the central (−15.9 %) and lower Amazon (−4.4 %). 1 Introduction The rivers and floodplains of the Amazon basin route large amounts of water, influence carbon and nutrient biogeochemistry, emit carbon dioxide and methane to the atmosphere, and support highly diverse ecosystems and productive fisheries. Rivers serve as major transportation corridors. As most settlements lie along the rivers and floodplains, local people utilize these environments for their subsistence. Energy demands rely on hydropower reservoirs, existing and planned in the Amazon (EPE 2012). Climate warming and climate variability are influencing the Amazon basin (Davidson et al. 2012). Large seasonal and inter-annual variations in depth and extent of inundation are characteristic and, as water levels vary, the proportion of aquatic habitats changes considerably. Results of simulations of flood height and extent in the 20th century (Coe et al. 2002, 2007; Costa et al. 2009; Foley et al. 2002; Decharme et al. 2008; Guimberteau et al. 2012, 2013; Rudorff et al. 2014; Yamazaki et al. 2011, 2012; Paiva et al. 2013) illustrate the potential scale of response of the system to climate variability. Exceptional hydrological events in the last decades, such as the floods in 2009, 2012 and 2014 and the droughts in 2005 and 2010 (Marengo and Espinoza 2015) impacted the region, alerting scientists, governments and general public to climate variability impacts. Espinoza et al. (2009a) found contrasting behavior in long-term trends in discharge based on historical data across different regions of the basin showing a decrease(increase) in minimum (maximum) annual discharge in the southern(northwestern) region More recently, Gloor et al. (2013) demonstrated an increasing trend of precipitation and maximum annual discharge of the Amazon River coincident with an upward trend in tropical Atlantic sea surface temperatures for the 1990s. Characteristics of the complex dynamics of the climate system in the Amazon basin are summarized in Nobre et al. (2009); Betts et al. (2009); Costa et al. (2009) and Marengo et al. (2009, 2012). Limnological and ecological conditions in floodplain lakes and wetlands are intimately associated with flooding dynamics (Junk et al. 1989; Junk 1997; Melack et al. 2009). Amazon rivers and flooded areas outgas large amounts of CO2 and methane that are significant in the regional carbon cycle (Richey et al. 2002; Melack et al. 2004; Moreira-Turcq et al. 2004; Abril et al. 2014; Melack 2015). Also, inundation dynamics influence vegetation structure (FerreiraFerreira et al. 2014; Junk et al. 2011), sediment transport (Bourgoin et al. 2007; Dunne et al. 1998), fish distributions and fisheries yield (Junk et al. 2007; Lobón-Cervia et al. 2015). Future changes in climate and hydrology are likely to alter floodplain inundation and related ecological conditions in associated ecosystems (Melack and Coe 2013). Future climate projections have uncertainties related to greenhouse gases emission scenarios and performance of General Circulation Models (GCMs) from Coupled Model Intercomparison Project 3 (CMIP3) though a consensus suggests decreased annual precipitation in the eastern Amazon and increased precipitation in the western Amazon (Meehl et al. 2007; Alves and Marengo 2010). Past studies projected both positive (Nohara et al. 2006) or negative anomalies (Milly et al. 2005) for the mean discharge of the basin. Guimberteau et al. (2013) found a future decrease in low flow across the basin, especially in the southern Madeira and Xingu rivers and northern Branco River. Melack and Coe (2013) evaluated inundation Author's personal copy Climatic Change under altered climate and land uses for the Amazon using a basin-wide hydrological model forced with observed climate data (1950–2000) and reported10% and 25 % decreases in rainfall resulted in reductions in inundation similar to reductions in rainfall: -5 % to −20 % and −12 % to −30 %, respectively. This result corroborates sensitivity analyses by Paiva et al. (2013) which showed similar anomalies in total inundation, but also amplified anomalies in discharge, in response to changes in precipitation. Others have considered actual or potential climate change or land use impacts on hydrological conditions in the Amazon basin through sensitivity analysis, land surface models and Special Report Emission Scenarios (SRES) from past IPCC reports (Coe et al. 2009; Casimiro et al. 2011; Langerwisch et al. 2013; Lejeune et al. 2015). Present studies do not assess surface hydrology impacts in the Amazon of climate change projected from the new generation of General Circulation Modelsin IPCC’s Fifth Assessment Report (AR5) CMIP5, which improved simulations of main precipitation features of the rainy season and the South American Monsoon System (Alves and Marengo 2010; Chou et al. 2012; Solman et al. 2013; Jones and Carvalho 2013; Joetzjer et al. 2013; Boisier et al. 2015). There is now a better agreement among models regarding precipitation changes projected for most of the South America. CMIP3 and CMIP5 models agree better in projections of drier conditions in eastern Amazonia during the dry season and wetter conditions in western Amazonia (Malhi et al. 2008; Cook et al. 2012). Experiments with an ensemble of 25 models from the CMIP5 projected changes in annual precipitation ranging from −11 % to 1 % and temperature ranging from 3.7 °C to 5.7 °C (25th to 75th percentiles) for the Amazon at 2100 RCP 8.5 (Christensen et al. 2013). Finally, the use of regional hydrological models with better physical representation of hydrological processes in rivers and floodplains (Paiva et al. 2011, 2013; Yamazaki et al. 2012) are likely to improve realism of the predictions of land surface hydrology as river discharge and inundation dynamics. Two main scientific questions are investigated here: What are the potential impacts of climate change on land surface hydrology of the Amazon basin? How do projections of climate change impact discharge and inundation in different regions and seasons? This paper presents analyses of potential climatic impacts on Amazon hydrology including discharge and flood inundation dynamics based on new forcing data from IPCC AR5 CMIP5 and detailed regional scale hydrologic modeling using the MGB-IPH model (Paiva et al. 2013). 2 Methods 2.1 Study area The Amazon basin (Fig. 1) drains about 6 million km2 and discharges ~15 % of global freshwater arriving to the oceans. It is formed by the Andes, the Guyanese and Brazilian shields, and the Amazon plain. Extensive wetlands (~17 % of lowland Amazon, altitude <500 m) are seasonally inundated, with total flooded extent ranging from 300 to 600 ×103 km2 (Melack and Hess 2010; Hess et al. 2015). The lowland Amazon has complex river hydraulics, and low river slopes cause backwater effects (Meade 1991; Paiva et al. 2013). The Amazon has high rainfall (average, 2200 mm/yr) and large spatial variability with especially high rainfall (>3000 mm/yr) in the northeast, southeast, near the Amazon delta and in portions of the Andes (Espinoza et al. 2009b; Espinoza et al. 2015). Rainfall decreases to the southeast and at higher elevation in the Andes. Contrasting rainfall regimes are found in the northern and southern parts of the basin, with the rainy season in June to August (December to February) Author's personal copy Climatic Change Fig. 1 Amazon River basin: terrain relief (gray), stations in main rivers (black dots), wetland mask (Melack and Hess 2010) and wetland regions and in the north (south) with more (less) defined wet and dry seasons occurring in the southern and eastern (northern and western) parts of the basin (Espinoza et al. 2009b). 2.2 General circulation models CMIP5 GCMs (Taylor et al. 2012; Christensen et al. 2013) were used to provide future projections of climate. This study focuses on changes in surface energy and water balances by contrasting ‘historical’ (1970–1999) and one ‘high-emission’ scenario (2070–2099). In the historical, 20th century scenario, climate models were forced by observed atmospheric composition changes which include both anthropogenic and natural sources as well as timeevolving land cover. Simulations of climate projection are forced with specified concentrations referred to as representative concentration pathways (RCPs) and provide an estimate of the evolution of the radiative forcing until 2100, relative to preindustrial conditions (Moss et al. 2010; Taylor et al. 2012). To investigate future changes in inundation dynamics over the Amazon basin, simulations from the ‘high-emission’ scenario labeled as RCP8.5 (i.e., radiative forcing increases throughout the 21st century before reaching a level of about 8.5Wm−2 at 2100) was used. This scenario was used to estimate potentially large changes in the precipitation variability in the South American Monsoon and its consequences to hydrological characteristic of the Amazon basin. Monthly averages of the following surface variables were analyzed and used as input for the hydrologic model: precipitation, air temperature and relative humidity at 2 m height, surface winds at 10 m height, surface pressure and incoming shortwave solar radiation. Although additional models are available in CMIP5, the five models Author's personal copy Climatic Change used here, CNRM-CM5, GFDL-ESM2M, HADGEM2-CC, MRI-CGCM3 and MIROC5, were deemed to provide realistic simulations of the main climatological features of the South American Monsoon (as explained further in S1 in Online Resource). 2.3 Hydrologic-hydrodynamic model Several hydrologic models have been developed for the Amazon basin (Coe et al. 2007; Paiva et al. 2013; Beighley et al. 2009; Yamazaki et al. 2012). The MGB-IPH model in its implementation for the Amazon basin (Paiva et al. 2013), was selected due (i) its capability to represent physical processes, such as water balance components, river hydrodynamics and large-scale inundation in the Amazon, and (ii) its performance demonstrated by previous validation against observations (S2 in Online Resources). This model used as the reference run for the climate change projections presented in this paper. Inundation results, including for the was reference run and climate change projections, were post-processed to improve the representation when compared to estimates from synthetic aperture radar (SAR) images from the JERS-1 satellite (S4 in Online Resources). 2.4 Bias removal Climate models often have biases in precipitation and temperature such as under or overestimation and incorrect seasonal variations due conceptual errors, discretization and spatial averaging within grid cells (Christensen et al. 2008; Teutschbein and Seibert 2012). Bias correction methods can be applied to reduce errors from biased GCM outputs and several methods exist as described by Teutschbein and Seibert (2012). We used both distribution mapping (‘quantile-quantile’) and the delta-change methods to derive future scenarios (S3 Online Resource). 2.5 Assessment of climate change effects on discharge and inundation extent The models runs using different projections had considerable uncertainty (see results, Fig. 3), thus changes in discharge and inundation extent should be compared to the GCM model uncertainties. Also, it is reasonable to compare the magnitude of climate change induced differences to the interannual variability of discharge. To consider statistical significance, a ttest (Wilks 2006) was used to assess if changes in projected discharges from the five GCM climate forcing simulations are different from zero (n = 5). In a second step, a two sample t-test was used to assess the difference between projected future discharges from the 5 GCMs (n1 = 5) and annual values from the reference period (n2 = 12). All tests used a 5 % significance level and were applied to Qmean, Qmin and Qmax. The first test assesses changes in Q considering only GCM uncertainty and the second test accounts for the natural interannual variability. Changes in Q were considered significant only when not rejected by both tests. The same approach was used to evaluate the potential changes in inundation extent. 3 Results Climate change effects on the Amazon basin hydrology are presented using projected changes in water balance, discharges and inundation. We consider terms ‘change’ and ‘anomalies’ Author's personal copy Climatic Change interchangeable as a measure of relative change (%) in variables simulated for the future projection model runs when compared to the reference scenario (1998–2009). The water balance section describes local fluxes in precipitation, evapotranspiration and local runoff and we describe discharge separately, as it integrate all upstream hydrological processes. 3.1 Water balance Assessment of climate change in river basins hydrology can be evaluated by comparing anomalies in water balance components. Average anomalies in annual precipitation, evapotranspiration and local runoff have different patterns for the western and eastern Amazon (Fig. 2): (i) mean change of water balance components among the five model runs (Fig. 2, top), and (ii) variability between models runs, shown for runoff as it integrate changes in surface water availability (Fig. 2, bottom). Simulation results indicate increased (decreased) precipitation towards northwestern and western (northeastern and eastern) parts of the basin. Positive changes in evapotranspiration are observed mostly over the southeastern and central Amazon and are driven by positive changes in potential evapotranspiration and/or precipitation (fig. S2 and S3 in Online Resource). Projections indicate increased local runoff in the western Amazon related to increased precipitation, while increased ET and reduced P leaded to drier conditions in the eastern portion of the basin. Figure 2 also illustrates the uncertainty in runoff anomalies computed from different GCM climate projections. For instance, the model run forced with CNRM-CM5 indicates increased (decreased) runoff in west and south (central, east and north) and results using the GFDLESM2M have increased (decreased) runoff in the north and west (central, east and southeast). While runs with HADGEM2-CC projections result in decreased water availability in most of the basin, models agree with drier conditions only in the eastern Amazon. Simulations with MIROC-5 and MRI-CGCM3 projections produce less uniform patterns than others, but agree Fig. 2 Mean projected anomalies among GCM model runs in annual precipitation, evapotranspiration and local runoff (top) and anomalies in local runoff for each GCM model run (bottom) Local runoff integrates vertical water balance, thus summarizes changes in surface water availability. Blank values represent small changes (i.e. interval from −5 % to 5 %) Author's personal copy Climatic Change with wetter conditions in the western Amazon. Furthermore, projected effects on water availability in the central and southern Amazon are not clearly defined. 3.2 Discharge Projected changes in discharge integrate upstream hydrological processes by routing local runoff in the river network. Mean daily discharges over the annual cycle for the reference conditions and future predictions based on five model simulations for the main Amazonian rivers are shown in Fig. 3. Average anomalies in annual mean (Qmean), minimum (Qmin) and maximum (Qmax) discharge, based on the five models runs, have noteable spatial variability throughout the Amazon (Fig. 3). Fig. 3 Seasonal variation of discharges for the reference (black line) and future scenarios from CNRM-CM5 (orange), GFDL-ESM2M (pink), HadGEM2-CC(ciano), MIROC-5(red) and MRI-CGCM3 (green) GCM models Author's personal copy Climatic Change Models runs generally indicate wetter (drier) conditions in western (eastern) Amazon, and climate change effects on high or low waters are different throughout the basin. In the upper Solimões River discharge increases are mostly expected during high water. Annual mean and minimum discharges are expected to decrease in most of the basin. In the central and lower Amazon discharge predictions from different models are over and below the reference simulation, and in the Negro River the dispersion of the results is large. In general, models have better agreement for negative anomalies in discharge during low water in lower Amazon, Tapajos, Xingu and Negro rivers. Although projected changes in annual mean discharge of larger rivers are expected throughout the whole basin, they are not significant everywhere (Fig. 4a). There is consistency among models with local water balance and expected significant changes in Qmean, as highlighted for western and eastern Amazon contrasting patterns. The numerical simulations indicate a decrease in annual minimum discharge in most of the basin (Fig. 4b). In Peru, results for minimum discharge changes were positive (negative) in main stem of Marañon (Upper Ucayali) catchments, although not significant. Low-flow discharge changes were mostly significant in the Xingu River basin and lower Amazon, including its tributaries (ΔQmin < −20 %). Maximum annual discharges and Qmean have significant increase for the upper reaches of Solimões and decrease in the Xingu. Increased runoff and floods from the left bank tributaries contribute to higher flows in the main stem, further increasing maximum flow downstream (Fig. 4c). 3.3 Inundation extent Average anomalies among 5 GCMs in annual mean (IEmean), minimum (IEmin) and maximum (IEmax) inundation extent are spatially heterogeneous in Amazon (Fig. 4). As the inundation dynamics are closely related to the flood-pulse in most of the basin, projected changes of annual inundation extent followed runoff and discharge patterns. Figure 5 illustrates changes in seasonal inundation as monthly inundation extent (unbiased, see S3 in Online Resources) for the reference and five future scenarios for wetland regions (see Fig. 1). Assessment of the significance of projected changes was performed using the same methods as for discharge (GCM uncertainty x interannual variability, see Section 3.2). Table 1 summarizes average projected anomalies, standard deviation and interannual coefficient of variation (CV) for IEmean, IEmax, IEmin for five regions: Amazon basin, central Amazon, Peruvian Amazon, Bolivian Amazon and lower Amazon. Anomalies were found significant and positive for annual mean (+9 %) and maximum (+18 %) inundation extent in Peruvian Amazon wetlands. Anomalies for average mean inundation extent are negative in the central Amazon wetlands, but not significant (Fig. 4d). While positive anomalies occur for the Solimões River (in Brazil), negative anomalies occur for the Negro, Juruá, Purus and lower Madeira rivers. Likewise, maximum inundation extent in the central Amazon (Fig. 4f) haspositive anomalies for the main stem Amazon and Negro rivers, but negative for right bank tributaries. The projected anomalies in IEmin (Fig. 4e) are negative and significant for wetlands in the central (−16 %) and lower Amazon (−4.4 %). 4 Discussion Climate projections for the Amazon basin resulted in spatially heterogeneous effects on the basin’s hydrological regime. The surface hydrology response to climate forcing modeled by Author's personal copy Climatic Change Fig. 4 Average projected anomalies among five models runs in for mean (a), minimum (b) and maximum (c) annual discharge and mean (d) minimum (e) and maximum (f) annual inundation extent. Significant anomalies are presented as pink in bottom right figures MGB-IPH resulted in wetter (drier) conditions over northwestern (southeastern and eastern) regions in the Amazon basin, based on multi-model ensemble anomalies against interannual Author's personal copy Climatic Change Fig. 5 Seasonal variability of inundation extent (unbiased) for the reference (black line) and future scenarios simulated with CNRM-CM5 (orange), GFDL-ESM2M (pink), HADGEM2-CC(ciano), MIROC-5(red) and MRI-CGCM3 (green) GCM models. Wetland regions are defined in Fig. 1 variability. These results were derived from numerical experiments, thus interpretation must consider that GCM forcings are not always consistent with the present climate (see Fig. S1 of Online Resources). Hence, we used the delta change method to prevent model errors representing current variables to be propagated into the analysis of projected variables. Modeled future scenarios indicate an increase in mean and maximum discharge in large rivers draining the eastern Andes in northwestern Amazon, which also contributes to increase in maximum inundation extent over Peruvian wetlands and along the Solimões River. Projected changes in maximum inundation extend further downstream due to increased precipitation and discharges from northwestern tributaries. Langerwisch et al. (2013) reported an increase in inundation in the western Amazon using 24 IPCC GCM forcing in the Dynamic Global Vegetation and Hydrology Model LPJml. Similarly, Guimberteau et al. (2013) simulations with the land surface model ORCHIDEE forced with 8 AR4 GCMs showed an increase of 12 % in high flows in northwestern Amazonia (i.e., Tamshiyacu station) for the end-of-century SRESA1B scenario. Also, Zulkafli et al. (2016) simulations using the JULES land surface hydrological modeling forced with 18 models from the RCP 4.5 and 8.5 scenarios showed an increase in severity of the wet season flood pulses in Western Amazonia. In this region, our study indicates that significant anomalies in mean and maximum discharges (Fig. 4a, c) are mostly between +5 to +20 %, while changes in mean (maximum) inundation extent for Peruvian Amazon was found +9 % (+18 %) (Table 1). Trend analyses for annual discharges (1974–2004) from Andean draining basins reported by Espinoza et al. (2009a) indicated (i) a decreasing trend in Tapajós River, upstream Madeira River, Peruvian Amazonas rivers, and Amazonas River, and (ii) increasing runoff in northwestern Putumayo and Napo rivers. 13.7 8.6 10.1 −6.5 −6.6 −2.9 Central Lower Amazon Significant values are marked as bold 5.2 20.6 +9.0 −6.1 Peru Bolivia 8.9 7.5 7.8 5.2 17.6 −0.7 −9.9 −15.9 −4.4 −12.8 8.6 11.2 2.1 10.3 6.3 Standard Dev. (%) Relative Change (%) Interannual CV (%) Relative change (%) Standard Dev. (%) Annual Min (IEmin) Annual Mean (IEmean) 8.3 11.1 1.9 9.7 9.1 Interannual CV (%) +3.5 +3.6 −5.0 −0.2 +18.3 Relative Change (%) 13.7 16.7 14.4 23.5 7.6 Standard Dev. (%) Annual Max (IEmax) 9.8 8.4 7.6 20.3 11.8 Interannual CV (%) Table 1 Average projected anomalies and standard deviation (from five GCMs climate forcing model runs) and interannual coefficient of variation in annual unbiased inundation extent (mean, maximum, minimum) for regions defined in Fig. 1 Author's personal copy Climatic Change Author's personal copy Climatic Change Projections of precipitation increase over the western Amazon and Andean region are currently under debate. This region is the least affected by historical climate variability, land use changes and has high biodiversity (Malhi et al. 2008). Although the precipitation patterns for the GCM historical period in this region are not in agreement with TRMM estimations (see Fig. S1 Online Resources), the accuracy of future projections were improved using bias removal methods. Neukom et al. (2015) reports that in mountain areas, climate models have limited capabilities simulate precipitation variability. Thus, while increasing rainfall for the Andean region is projected in our work and others (Seth et al. (2010); Thibeault et al. 2010), other recent papers suggest rainfall diminution by the end of the 21st century (Minvielle and Garreaud 2011; Urrutia and Vuille 2009; Neukom et al. 2015). These contrasting projections for rainfall results from the use of different methods. While our approach considers changes in rainfall directly from GCMs, the latter obtained projections for rainfall based on a proxy with projected winds at 200 hPa, based on significant correlations between these variables over the Andean region (Garreaud et al. 2003). This indicates that investigation of atmospheric transport mechanisms and climate proxies are needed to improve consistency of hydrological projections and evaluation of future changes in surface waters. Recent studies which couple climate and ecology suggest that south-southeastern Amazon is particularly vulnerable. Main impacts are related to climate feedbacks due deforestation, cropland and pasture expansion with reduction of flood-pulse magnitude and enhanced dry season (Costa et al. 2003, 2009; Sampaio et al. 2007; Coe et al. 2013). Recent simulations indicate a decrease in low-flows in the northern Branco river, southern Madeira and Xingu rivers (−50 %), and in lower Amazon at Óbidos (−4 %) (Guimberteau et al. 2013). Our simulations also indicated decreased river discharge, mainly during the dry season for south (not significant) and eastern basins, as well as decreased inundation extent during low water in the central and lower Amazon. We do not consider explicit changes in vegetation or land cover and their climate feedbacks. Some Amazonia regions have suffered large changes in land cover throughout the last decades. More than 60 % of the land in the Tocantins basin is under agricultural use today. Costa and Foley (1997) used the Land Surface Scheme coupled to a large-scale hydrological model and estimated that changes in land cover (natural vegetation to pasture) could decrease annual mean ET (3.4 mm/day to 2.7 mm/day). This reduction contributed to increased runoff routing from 0 (where natural vegetation is considered to be grasslands) to a maximum of 47 % (in regions with forest vegetation cover). A comparison of two periods where precipitation over the basin is not statistically different, one with relatively small changes in land cover (1949–1968) and the second with larger changes in land cover (1979–1998) indicated that annual mean discharge was 24 % greater in the latter case, with high-flow season discharge greater by 28 % (Costa et al. 2003). Dias et al. (2015) assessed the influence of land cover changes in small catchments in the upper Xingu River (southeastern Amazon) and reported that observed and simulated mean annual streamflows in agricultural ecosystems (pasture and soybean croplands) were more than 100 % higher than in natural ecosystems (tropical rainforest and cerrado). In a recent comparative analysis, Lejeune et al. (2015) emphasized (i) the need for model improvements with large-scale feedbacks induced by land-use change on the climate system and that (ii) historical development of climate models led to a reduction of uncertainty, but did not modify median estimate of Amazonian climate sensitivity to deforestation. Other modeling studies in the Amazon basin have investigated discharge and inundation sensitivity to changes in precipitation, and basin responses to future climate and deforestation Author's personal copy Climatic Change scenarios (e.g., Costa and Foley 1997; Paiva et al. 2013; Melack and Coe 2013; Coe et al. 2009; Guimberteau et al. 2013). It is important to understand that modeling studies are in some degree dependent on both experiment design and model structure (Coe et al. 2009). When compared to other large scale climate-hydrology simulations for Amazonia the MGB-IPH provides improved in-stream and floodplain inundation and hydraulic response to changes in hydrological forcing. as it uses a full 1D hydraulic model with floodplain storage solution. Furthermore, as the reference scenario was subject to extensive validation using in situ and remote sensing data, it represents a reliable baseline for comparison with future climate projections. Another important aspect was the use of robust bias removal techniques on GCM climate historical and future data to build the future scenario model runs. While discharges integrate the whole upstream hydrological changes on water availability, the inundation extent is particularly important for floodplain ecosystems (Junk 1997; Junk et al. 2011; Melack et al. 2009). Hence, our findings provide useful information for aquatic ecosystem management strategies, other human related issues (i.e. flood vulnerability, transportation, fisheries and planned hydropower generation) and for investigation of the future of inland water carbon and biogeochemical cycles. 5 Conclusion This study focused on projections of potential climate change impacts on the hydrology of the Amazon basin for the end of the 21st century, using the regional model MGB-IPH forced by 5 AR5 GCMs from RCP8.5 scenario. Analyses indicated contrasting patterns for future hydrological conditions for the western and eastern Amazon. Results based on different climate forcings demonstrate a large variability among models, such that projections of hydrological change are highly dependent on the GCMs. Predictions did not agree on changes for total Amazon inundation extent or average discharge along the main stem of the Amazon River. Surface water projections agreed better with wetter (drier) conditions over western (eastern) regions of the basin. Results indicate increased mean and maximum river discharge for large rivers draining the eastern Andes in northwestern Amazon. Projections of increased in precipitation resulted in increased mean and maximum discharge and inundation extent over Peruvian floodplains and Solimões River in western and central Amazonia. Decreased river discharges (mainly in the dry season) are projected for eastern basins, and decreased inundation extent at low water period in the central and lower Amazon. Despite of the limitations regarding the adopted approach, our findings provide a reasonable overview of potential effects on Amazon basin discharge and inundation due climate change prescribed in RCP8.5 scenarios. While future climate and hydrological conditions are not certain, they are relevant to water and environmental conservation and management strategies, since hydrological changes have important implications for ecological and biogeochemical dynamics. Acknowledgments The synthetic work for this paper was supported by the Science for Nature and People (SNAP) sponsored by the National Center for Ecological Analysis and Synthesis (NCEAS), Wildlife Conservation Society (WCS) and the Nature Conservancy (TNC). SNAP funding was provided by the David and Lucile Packard Foundation (Grant # 2013-38757 & #2014-39828), Ward Woods (Grant # 309519), WCS and TNC. Also we thank the editor and reviewers for comments that improved this paper andWalter Collischonn for advice. Author's personal copy Climatic Change References Abril G, Martinez J-M, Artigas F, et al. (2014) Amazon River carbon dioxide outgassing fuelled by wetlands. 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