Journal of Hydrology 369 (2009) 165–174
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Journal of Hydrology
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The influence of historical and potential future deforestation on the stream flow of the Amazon River – Land surface processes and atmospheric feedbacks
Michael T. Coe a,*, Marcos H. Costa b, Britaldo S. Soares-Filho c a The Woods Hole Research Center, 149 Woods Hole Rd., Falmouth, MA 02540, USA b The Federal University of Viçosa, Viçosa, MG, 36570-000, Brazil c The Federal University of Minas Gerais, Belo Horizonte, MG, Brazil article info summary
Article history: In this study, results from two sets of numerical simulations are evaluated and presented; one with the Received 18 June 2008 land surface model IBIS forced with prescribed climate and another with the fully coupled atmospheric Received in revised form 27 October 2008 general circulation and land surface model CCM3-IBIS. The results illustrate the influence of historical and Accepted 15 February 2009 potential future deforestation on local evapotranspiration and discharge of the Amazon River system with and without atmospheric feedbacks and clarify a few important points about the impact of defor- This manuscript was handled by K. estation on the Amazon River. In the absence of a continental scale precipitation change, large-scale Georgakakos, Editor-in-Chief, with the deforestation can have a significant impact on large river systems and appears to have already done so assistance of Phillip Arkin, Associate Editor in the Tocantins and Araguaia Rivers, where discharge has increased 25% with little change in precipita- tion. However, with extensive deforestation (e.g. >30% of the Amazon basin) atmospheric feedbacks, Keywords: brought about by differences in the physical structure of the crops and pasture replacing natural vegeta- Amazon tion, cause water balance changes of the same order of magnitude as the changes due to local land surface Discharge processes, but of opposite sign. Additionally, changes in the water balance caused by atmospheric feed- Numerical models backs are not limited to those basins where deforestation has occurred but are spread unevenly through- Deforestation out the entire Amazon by atmospheric circulation. As a result, changes to discharge and aquatic environments with future deforestation of the Amazon will likely be significant and a complex function of how much vegetation has been removed from that particular watershed and how much has been removed from the entire Amazon Basin. Ó 2009 Elsevier B.V. All rights reserved.
Introduction and floods routinely disrupt communication, commerce, econom- ics, health and ecology over wide areas of the watershed (Marengo The Amazon River system provides habitat for one of the et al., 2008a,b). With increasing population and infrastructure world’s most diverse aquatic environments and is central to the within the Amazon, future variability and changes to stream flow existence of millions of people. It provides nearly all, domestic are likely to create more frequent and larger disruptions. and commercial transportation in the region. For example, there Global economic and regional population and development are no roads connecting Manaus, an important industrial city of pressures have resulted in high rates of deforestation in the Amazon about 1.2 million people in the center of the Amazon, with the ma- River basin (Achard et al., 2002; Fearnside and Graça, 2006; Kaim- jor population centers in northeastern and southern Brazil. The riv- owitz et al., 2004) and about 17% of the Amazon basin (excluding er also provides drinking water, livelihood, and protein in the form the Tocantins) has been deforested by 2007, mostly in the eastern of fish to the majority of the population of the Amazon. Addition- and southern portion of the basin (Fearnside, 1993; INPE, 1999, ally, major infrastructure investments are planned for the Amazon 2000; Nepstad et al., 1999; Skole et al., 1994; Skole and Tucker, basin, including hydroelectric dams, mining and industrial devel- 1993)(Fig. 1). Cattle ranching is the single largest use of cleared opment, and waterways for barge traffic (Carvalho et al., 2001; land in the Amazon, covering about 75% of total deforested area Laurance et al., 2001). These social, ecological, and economic actors (Faminow, 1998; Margulis, 2003) and herd size in the Amazon has all depend on a stable Amazon River system. doubled since 1996 from about 15 million to 30 million head Despite the popular view that the Amazon contains a near lim- (Nepstad et al., 2006; Simon and Garagorry, 2005). However, soy- itless supply of water, extreme climate events such as droughts bean production, primarily for export as animal feed to Europe and China (Nepstad et al., 2006), has become more important in the last decade and new land is now being converted directly from * Corresponding author. Tel.: +1 508 540 9900; fax: +1 508 540 9700. E-mail address: [email protected] (M.T. Coe). cerrado and forest for soybean production. Recent deforestation
0022-1694/$ - see front matter Ó 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2009.02.043 166 M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174
Fig. 1. Vegetation cover of the Amazon basin with three land covers classes, tropical evergreen forests (green), Cerrado (beige), and agriculture (yellow) shown for potential vegetation (CTL) as reconstructed by Ramankutty and Foley (1998), vegetation distribution of the year 2000 (MOD) as estimated by Eva et al. (2002), and two scenarios for the year 2050 by Soares-Filho et al. (2006) with strong governance of deforestation (GOV) and relatively weak governance (BAU).
rates reflect the global demand for Brazilian beef and soybeans with catchment to 17% in the pasture catchment. The second paired about 22,000 km2 deforested each year between 2000 and 2004 experiment compares two 1.2 km2 catchments, Colosso and Açú- (INPE, 2004). Economic conditions and recent trends suggest that Mirim, in Central Amazonia (Trancoso, 2006), concluding that the high rates of Amazonian deforestation for cattle and soybean runoff coefficient increases from 21% in the forest catchment to production will continue well into the future (Alencar et al., 2004; 43% in the pasture catchment. At the large scale, studies in the Carvalho et al., 2001; Kaimowitz et al., 2004; Laurance et al., Tocantins and Araguaia Rivers of eastern Amazonia conclude that 2001; Soares-Filho et al., 2004, 2006). The last 5 months of 2007 rapid land cover changes since 1960 are associated with about a saw a record 7000 km2 of deforestation in the Amazon. 25% increase in the annual mean discharge despite no significant The land surface of the Amazon is coupled to its rivers, streams change in precipitation (Coe et al., 2008; Costa et al., 2003). There- and wetlands, through hydrological processes. Human land cover fore, in eastern Amazonia land cover change appears to have and land use changes influence the quantity of surface water re- already significantly reduced evapotranspiration and increased sources by: Changing how incoming precipitation and radiation runoff and discharge. are partitioned among sensible and latent heat fluxes, runoff, and This reduction in evapotranspiration is a consequence of the river discharge (Bonan et al., 2004; Costa and Foley, 1997; Li land surface processes involved in the exchange of energy and et al., 2007) and altering regional and continental scale precipita- water from the biosphere to the atmosphere. The pastures, with tion patterns (Costa and Foley, 2000; Delire et al., 2001; Dickinson higher albedo, lower leaf area, lower roughness length and shal- and Henderson-Sellers, 1988; Malhi et al., 2008b; Nobre et al., lower roots, usually have a lower evapotranspiration rate than 1991). the forest, particularly during the dry season. Changes in the water and energy balance work at a variety of Global and meso-scale climate model studies indicate, however, time and space scales and the combined influences on the river dis- that once deforestation in the Amazon basin occurs on a very large charge are complex. Observations at micro (<1 km2) or meso scale (>100,000 km2), atmospheric feedbacks may significantly re- (100 s km2) spatial scales in the global tropics and extra-tropics duce regional precipitation. Replacement of forest with higher al- indicate that deforestation reduces evapotranspiration and in- bedo, less water-demanding crops and pastures leads to reduced creases stream flow because of the reduced leaf area index, de- net surface radiation, decreased moisture convergence over the ba- creased root density and depth, and increased soil compaction sin, decreased water recycling, and reduced precipitation (Costa (Bruijnzeel, 1990; Costa, 2005; Sahin and Hall, 1996; Scanlon and Foley, 2000; Dickinson and Henderson-Sellers, 1988; Malhi et al., 2007). Two microscale, paired experiments in Amazonia con- et al., 2008b; Nobre et al., 1991). Recent studies that evaluated firm the results obtained outside of the Amazon. The first paired the effects of partial deforestation on the climate of the region experiment compares two catchments of areas <0.01 km2 in Fazen- (Costa et al., 2007; Sampaio et al., 2007) found that significant da Vitória, eastern Amazonia (Moraes et al., 2006), and found that changes in precipitation occur only after more than 40% of the the ratio of runoff to precipitation increases from 3% in the forest Amazon basin is deforested. M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174 167
These two processes lead to competing influences on the stream inherent in that data; (2) Understanding the importance of contin- flow, with decreased local evapotranspiration consistent with in- ued and future efforts to reduce deforestation on the local and re- creased discharge and reduced regional precipitation consistent gional health of the Amazon River; continued efforts to reduce with decreased discharge (Costa, 2005; D’Almeida et al., 2006, deforestation can be strengthened by knowledge of the scale of dis- 2007). The combination of these two processes is therefore, likely ruption that can be avoided; (3) Beginning to quantify the impor- to create complex and unexpected changes in stream flow that tance of individual protected areas in maintaining the integrity of vary spatially as a function of local and non-local conditions. the Amazon; scenarios can provide more information on the stra- Brazilian law currently requires that 80% of any landholding in tegic importance of protected areas in reducing regional deforesta- the Amazon biome must remain as undisturbed forest and that tion rates and hence may be useful in informing policy (Soares riparian buffer zones must be maintained from 30 to 500 m from Filho et al., 2008). a stream depending on stream size. Further, Brazil continues to set aside large expanses of the Amazon basin as protected reserves: Model descriptions 23 million hectares since 2004 (Campos and Nepstad, 2006). How laws are enforced, and protected areas augmented, in the future All models used in this study have been extensively calibrated will have a significant effect on the magnitude and character of and validated for the Amazon River and are thoroughly described land use changes (Soares-Filho et al., 2006) and therefore on aqua- in documents listed in the sections below. Therefore, only a brief tic systems that support millions of people and vast biological description of each model is provided here. diversity. More focused research on the influences of heteroge- neous deforestation and differing management practices on the IBIS terrestrial ecosystem model aquatic systems of the Amazon are needed to better understand IBIS is a physically-based model that integrates a variety of ter- the scale of changes that have occurred and are likely to occur, restrial ecosystem processes within a single, mechanistic model to the relative importance of individual forest protected areas, and simultaneously calculate a wide range of processes, including the help guide future policy. land surface water and energy balances (Kucharik et al., 2000). In this study, regional land surface models and a coupled global The model has two vegetation canopies with an upper layer of climate and vegetation model are forced with historical potential trees and a lower layer of shrubs, grasses and crops, and 15 types vegetation, modern (year 2000) vegetation, and land cover scenar- of natural vegetation cover comprised of a combination of 12 plant ios for the year 2050 to address the complex ways in which defor- functional types including woody and herbaceous plants. estation, through local and non-local feedbacks, can influence the The soil module has six soil layers (with a total of 8-m depth in conversion of precipitation to runoff and discharge throughout this study). The dynamics of soil volumetric water content are sim- the Amazon River. The focus of this study is on the response of dis- ulated for each layer. The soil water infiltration rate is based on the charge within individual watersheds because the interaction of lo- Green–Ampt formulation (Green and Ampt, 1911). The soil mois- cal and non-local responses to deforestation can lead to ture simulation is based on Richards’ flow equation, where the soil consequences for river discharge that an analysis of precipitation moisture change in time and space is a function of soil hydraulic alone cannot clarify and because of the obvious environmental conductivity, soil water retention curve, plant water uptake, and and social importance of maintaining the integrity of the Amazon upper and lower boundary conditions. Plant transpiration is a River system. mechanistic process governed by stomatal physiology, in IBIS it is tightly coupled to photosynthesis through the Ball–Berry formula- tion (Ball et al., 1986). The plant root-water uptake is a function of Methodology atmospheric demand, soil physical properties, root distribution, and soil moisture profile (Kucharik et al., 2000; Li et al., 2005). IBIS Two sets of simulations are made; one with an offline land sur- explicitly simulates surface and sub-runoff on a grid cell basis as a face model and another with a fully coupled atmospheric general function of the soil, vegetation, and climate characteristics. Hori- circulation and land surface model. The land surface model IBIS zontal runoff transport between grid cells is subsequently simu- (Kucharik et al., 2000) is used with the river transport model THMB lated by the THMB hydrological routing model (described in (Coe et al., 2007) to evaluate the influence of historical and poten- ‘‘THMB terrestrial hydrology model”). IBIS has been validated and tial future deforestation on local evapotranspiration and the dis- applied to the Amazon (Botta et al., 2002; Coe et al., 2002, 2007; charge of the Amazon River system in the absence of Delire and Foley, 1999; Foley et al., 2002). atmospheric feedbacks to precipitation. The fully coupled CCM3/ IBIS global climate and land surface model (Delire et al., 2002, CCM3/IBIS coupled global climate land surface model 2004) is used with THMB to evaluate the response of the discharge The National Center for Atmospheric Research (NCAR) Commu- to the combined local evapotranspiration and regional precipita- nity Climate Model version 3 (CCM3) is an atmospheric general cir- tion feedbacks that result from deforestation. This combination culation model with spectral representation of the horizontal of offline land surface and fully coupled global climate models fields. It simulates the large-scale physics (radiative transfer, helps clarify the scale of the individual local and non-local pro- hydrologic cycle, cloud development, thermodynamics) and cesses and how in combination they affect the river system. dynamics of the atmosphere. In this study, we operate the model A suite of land cover scenarios is used: potential vegetation at a spectral resolution of T42 ( 2.81° 2.81° latitude/longitude (natural vegetation with no anthropogenic change (Ramankutty grid), 18 levels in the vertical, and a 15-min time step. The oceans and Foley, 1998) the vegetation distribution of the year 2000 are represented by monthly averaged fixed sea-surface tempera- (Eva et al., 2002), and two deforestation simulations for the year tures and serve as boundary conditions for the atmosphere. 2050, one with strict governance of deforestation and one with a The water, energy and carbon cycle of this version of the model continuation of business as usual deforestation practices (Soares- has been globally validated (Delire et al., 2002) and validated for Filho et al., 2006). This suite of scenarios is useful for: (1) Under- the Amazon by (Senna et al., submitted for publication). Simulated standing the location and scale of impact deforestation has already precipitation was compared (Fig. 2) against eight different precip- had on the Amazon River; observations alone cannot always itation databases (Senna et al., submitted for publication), includ- clearly provide this understanding because of the difficulties in ing three climatological surface rain gauge datasets – CRU obtaining long data records and because of the variability and error (Climatic Research Unit (New et al., 1999)), LW (Legates and 168 M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174
Fig. 2. Comparison of mean annual precipitation averaged over the area in gray in thumbnail of South America. Precipitation is simulated by CCM3-IBIS and reported by eight different data sources: CRU (Climatic Research Unit (New et al., 1999)), (Legates and Willmott, 1990), CMAP (CPC Merged Analysis of Precipitation (Xie and Arkin, 1997)), GPCP (Global Precipitation Climatology Project (Huffman et al., 1997)), TRMM (Tropical Rainfall Measuring Mission (Kummerow et al., 1998)), NCEP/NCAR (Kalnay et al., 1996), and ERA-40 (Uppala et al., 2005). All available data in the time series were used to describe the precipitation climatology.
Willmott, 1990), and LC (Leemans and Cramer, 1990); three that off, sub-surface drainage, precipitation and evaporation over the blend remote sensing data with surface rain gauges – CMAP (CPC surface waters, and the flux of water from the upstream grid cells Merged Analysis of Precipitation (Xie and Arkin, 1997)), GPCP and to the downstream cell. The flux to downstream cells (dis- (Global Precipitation Climatology Project (Huffman et al., 1997)), charge) is based on the volume of water in the river reservoir and TRMM (Tropical Rainfall Measuring Mission (Kummerow et al., and river geomorphic characteristics, such as slope and hydraulic 1998)); and two reanalysis datasets – NCEP/NCAR (Kalnay et al., radius. The inundation of the river floodplain is a function of the 1996) and ERA-40 (Uppala et al., 2005). All available data in the time flux of water from the stream channel to the floodplain, the vertical series were used to describe the precipitation climatology. The use water balance, and the geomorphic characteristics of the river and of a large number of precipitation datasets is important because floodplain. The equations are solved with a 1-h time step. The re- regional precipitation estimates in Amazonia vary considerably sults of THMB are spatially explicit representations of the (in-chan- (Costa and Foley, 1998). nel) river volume, stage and discharge, and the (out-of-channel) Observed annual mean precipitation estimates vary consider- floodplain volume, stage, and inundated area at the temporal res- ably; from 4.98 to 6.70 mm/day. The CCM3-IBIS simulated esti- olution of the input data (1 h to 1 month) and spatial resolution mate (6.20 mm/day) is in the middle of the precipitation dataset of the topographic data (5-min in this case). range and is within 5% of the ERA-40, Leemans and Cramer, Legates and Willmott and TRMM datasets. The largest difference is 24.5% Experimental designs from the CRU dataset, in large part due to the negative precipita- tion bias in the CRU dataset in western Amazonia discussed in Offline IBIS and THMB simulations ‘‘Offline IBIS and THMB simulations”. The simulated seasonal Four simulations were made with IBIS and THMB forced with amplitude of the precipitation for the Amazon is within the ampli- prescribed identical climate and vegetation representing the fol- tude of the datasets although one month in advance (Fig. 2). lowing (Fig. 1): historical (CTL), modern (MOD), year 2050 with strict governance of deforestation (GOV), and year 2050 with a THMB terrestrial hydrology model business-as-usual scenario of deforestation (BAU). To generate The terrestrial hydrological model with biogeochemistry mean monthly surface and sub-surface runoff for THMB first, two (THMB) is forced by climate data and surface runoff and sub-sur- simulations were completed using IBIS with identical CRU-ts2 ob- face drainage provided by IBIS to simulate the water balance of served climate (Mitchell et al., 2005) forcing for the period January the Amazon River system. THMB is a distributed grid model at 1915–December 2000 at ½-degree horizontal resolution. The two 5-min horizontal resolution that has been applied in large to simulations had differing vegetation cover, one with the potential moderate scale watersheds throughout the world, including vegetation (IBIS-POT) as depicted by (Ramankutty and Foley, North America, Africa, and India (Coe, 1998, 2000; Coe and Foley, 1998) and another in which all vegetation in the Amazon is re-
2001; Donner et al., 2002; Li et al., 2005, 2007; Shankar et al., placed by C4 grass (IBIS-GRASS). 2004; Suprit and Shankar, 2007). The version used here has been Four simulations were completed with THMB using the surface developed, calibrated, and validated specifically for the Amazon and sub-surface runoff data from IBIS-POT and IBIS-GRASS interpo- and Tocantins River basins, as part of a NASA LBA-ECO project lated to the 5-min resolution of THMB: (1) a simulation represent- (Coe et al., 2007). ing no anthropogenic vegetation changes (CTL); (2) a modern THMB uses prescribed river paths and floodplain morphology, simulation (MOD) using the deforestation classification of (Eva derived from the SRTM digital elevation model, linked to a set of et al., 2002) to represent the forest distribution as of 2000; (3) a linear reservoir equations describing the change with time of the year 2050 simulation with deforestation simulated under the strict river and floodplain reservoirs. Mass in the river and floodplain res- governance scenario (GOV), in which moderate deforestation takes ervoirs is explicitly conserved. Variation of the total water within place; and (4) a year 2050 simulation with deforestation occurring the stream at any point in THMB is the sum of the land surface run- assuming a ‘‘business-as-usual” scenario (BAU), in which wide- M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174 169 spread deforestation takes place (Fig. 1). The land cover maps are The surface and sub-surface runoff for the last 10 years of the 2 at 1 km horizontal resolution and the total surface runoff (Rt) CCM3-IBIS ensemble runs were averaged to create monthly mean and sub-surface drainage (Dt) input to each 5-min THMB grid cell values and the differences of the individual experiments from the is determined as the sum of IBIS-POT and IBIS-GRASS over the potential vegetation run (POT) were created (GOV-POT and BAU- undisturbed and disturbed fractions of the grid cell respectively. POT). These difference files were interpolated to ½-degree resolu- tion of IBIS and added to the IBIS-simulated runoff used as input Rt ¼ Ff Rp þð1 Ff Þ Rg in the CTL simulation in THMB (‘‘Offline IBIS and THMB simula-
Dt ¼ Ff Dp þð1 Ff Þ Dg tions”). We chose to force THMB with the difference between sim- ulations rather than the direct GCM output of each experiment, as Ff is the forested fraction (0–1) in each of the land cover scenarios, in (Broström et al., 1998; Coe, 2000), in order to reduce the influ- Rp (Dp) is the surface (sub-surface) runoff from IBIS-POT and Rg (Dg) ence of any GCM bias and facilitate direct comparison with the re- is the surface (sub-surface) runoff from IBIS-GRASS. Therefore in sults of the IBIS-offline experiments. These two datasets were used CTL where Ff = 1 the surface and sub-surface runoff come entirely as input to THMB and the model was run for the period 1915– from the IBIS-POT simulation, while in the MOD, GOV, and BAU sim- 2000, as above, to create CCM3 governance (CCM3-GOV) and busi- ulations the runoff input to each THMB grid cell is some mix of both ness-as-usual (CCM3-BAU) river discharge. The difference between IBIS-POT and IBIS-GRASS. Linear mixing of simulated results to cre- the discharge of the CCM3-GOV and CCM3-BAU experiments from ate individual scenarios is appropriate because it closely approxi- IBIS-offline CTL is a measure of the influence of deforestation on mates the linear averaging of land cover types that occurs within the coupled climate-biosphere system. each grid cell of IBIS. THMB was run for the period 1915–2000 with a 1-h time-step, and with the monthly mean climate data linearly interpolated to 1- Results h for each of the four scenarios. The first 2 years of each scenario were considered model spin-up and were discarded. The differ- Results of offline IBIS simulations – no deforestation (CTL) ences in simulated discharge of MOD, GOV and BAU from CTL quantify the sensitivity of the surface hydrology to prescribed land The area of interest in this study is the entire Amazon Basin cover changes. with specific emphasis on the major southern and western tribu- The CRU-ts2 dataset significantly underestimates the precipita- taries of the Tocantins, Xingu, Tapajós, Madeira, Purus and Juruá tion in the western portions of the Amazon outside of Brazil, as did basins where the greatest part of the historical deforestation has the CRU05 dataset previously used by (Coe et al., 2007). The bias is taken place and where much of the future deforestation is pre- due most likely to a lack of data and the interpolation technique dicted to occur (Figs. 1 and 3). The CTL simulation reproduces used in the creation of the dataset (Coe et al., 2007). The bias is re- the discharge of the Amazon River in good agreement with the duced in this study as by (Coe et al., 2007) by applying a discharge observations. The CTL results of this study differ somewhat from bias correction to the IBIS simulated surface and sub-surface runoff those of (Coe et al., 2007) because the version of IBIS used in this for the four tributaries affected by the bias and equal to the amount study includes more explicit representation of root and soil of discrepancy between simulated and observed annual mean dis- dynamics (Li et al.,2005,2006, 2007) and as a result the evapotrans- charge: Japurá-24%, Negro-16%, Solimões-49%, and Madeira-32% piration differs from the previous version of IBIS (Coe et al., 2002, before (and including) December 1984 and Japurá-52%, Negro- 2007). 24%, Solimões-66%, and Madeira-50% after December 1984. The The mean monthly hydrograph for 11 major streams of the large change after 1984 is most likely a result of a change in Amazon is in excellent agreement with the observations. The cor- the number of precipitation gauge stations reporting data in the relation coefficient (r2) is greater than 0.85 at all stations (Table 1, 1980s and used in creating the CRU products (New et al., 2000). Fig. 3). The discharge magnitude also agrees well with the observa- This constant correction was applied to all grid cells upstream of tions at most locations as indicated by the low percent relative er- the gauge station nearest the Brazilian border for all months in ror (%RE, Table 1), which is within ±16% for all streams except the the surface and sub-surface runoff files. The corrected runoff was Xingu (+25%). There is a relatively strong negative bias for the used as input data to provide the estimates of discharge and flood- Tocantins River also (RE = 15%) that will be discussed in ‘‘Results ing presented in this study. of offline IBIS simulations – year 2000 (MOD)”, and is most likely related to the fact that the Tocantins is largely deforested but in Coupled CCM3/IBIS simulations this control simulation has the potential vegetation of Cerrado A second series of simulations were made, with the National and forest. There is also a negative bias in the magnitude of the dis- Center for Atmospheric Research Community Climate Model-3 charge at the most downstream location on the Amazon coupled to the IBIS land surface model. The simulations correspond (RE = 11%) that is due, in part, to underestimated flux on the Ma- to the CTL, GOV, and BAU simulations described above and were deira River (RE = 16%). created in the following way. Twenty-year simulations were made with the potential vegetation and year 2050 governance and busi- Results of offline IBIS simulations – year 2000 (MOD) ness-as-usual simulated deforestation maps (Fig. 1) prescribed within CCM3-IBIS. The land use maps at the CCM3 resolution were The estimates of total deforestation by the year 2000 indicate made by aggregation of the higher resolution land use datasets. that about 10% of the roughly 5 million km2 area of rainforest in The land use type at each CCM3 cell was calculated as the domi- the Amazon has been altered (Fig. 1, Table 2). The Tapajós is about nant land use type (deforestation/natural vegetation) from the cor- 20% deforested and the Madeira, Xingu, and Japurá Rivers 12–13% responding area in the high-resolution dataset. Adjustments were deforested. The Purus and Juruá are relatively undisturbed made to keep the total deforested area equivalent between the with less than 5% of their rainforest affected. The Tocantins is the two datasets. Three simulations were made for each scenario and most disturbed with about 58% of the rainforest area in agriculture ensembles were created to reduce the effects of variability. CO2 (Table 2). concentrations and SST patterns were kept constant in all simula- The simulated influence of deforestation as of 2000 is modest in tions, so the results are the consequence of the changes in land use the MOD simulation, with the exception of the Tocantins, but leads only. to improvement of the agreement with observations compared to 170 M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174
Fig. 3. Major watersheds of the Amazon basin. Numbers correspond to the gauge stations for which results are presented in the text and tables. The cross-hatched area corresponds to the watershed of the Óbidos station (#33, Table 1).
Table 1 Table 2 Analysis of simulated discharge compared to observed for potential vegetation (CTL) Deforested area of entire Amazon and selected watersheds. and year 2000 vegetation (MOD) simulated with IBIS offline. Area (km2) Deforested % n CTL MOD MOD (%) GOV (%) BAU (%) r2 RE% RMSE% r2 RE% RMSE% Entire basin 4970079 10 30 49 Amazon #33 350 0.9925 11 18 0.9938 10 17 Amazon #33 3702481 7 25 40 Negro #21 256 0.9887 3 24 0.9887 3 24 Negro #21 582064 3 15 29 Japurá #9 259 0.9652 2 43 0.9660 2 43 Japurá #9 217367 12 18 20 Solimões #10 120 0.9219 3 24 0.9192 224 Solimões #10 1858883 6 29 42 Solimões #5 297 0.8697 7 27 0.8637 528 Solimões #5 867257 8 21 23 Juruá #8 308 0.8581 1 48 0.8574 0 48 Juruá #8 156376 1 22 46 Purus #17 153 0.8483 7 33 0.8486 633 Purus #17 333480 3 21 43 Madeira #31 337 0.9252 16 32 0.9384 11 29 Madeira #31 906552 13 41 61 Tapajós #38 227 0.9252 12 53 0.9305 17 55 Tapajós #38 285072 20 50 82 Xingu #44 331 0.9757 22 49 0.9754 27 51 Xingu #44 377175 12 26 66 Tocantins #56 246 0.9213 15 35 0.9665 7 30 Tocantins #56 189048 58 80 93
Number of months of observed and simulated discharge used in the statistical Total watershed area (km2) and fraction deforested as of 2000 (from Eva et al., analysis, n, coefficient of correlation, r2, percent relative error, RE, and percent root 2002) and the year 2050 GOV and BAU deforestation scenarios of Britaldo Soares- mean square of the error, RMSE. Filho et al. (2006).
CTL for almost all locations (Tables 1 and 3). The discharge is in- Table 3 creased by 7% on the Madeira compared to CTL and by 5% or less Fractional change in simulated discharge, offline IBIS/THMB. on the Tapajós and Xingu. The simulated discharge of the Tocantins Discharge 2 is increased by 26% compared to CTL, the r is improved to 0.9665 MOD (%) GOV (%) BAU (%) (from 0.9213), and the RE is 7% compared to 15% for CTL. The re- Amazon #33 2 5 7 sults of the MOD simulation suggest that historical deforestation Negro #21 0 0 1 has had a large impact on the discharge of the Tocantins River Japurá #9 0 0 0 and small impact elsewhere in the southern tributaries. Solimões #10 1 3 4 The simulated results at the 175,000 km2 Porto Nacional sub- Solimões #5 2 5 6 watershed of the Tocantins River (not shown) illustrate the impor- Juruá #8 0 2 5 Purus #17 1 4 6 tance of the recent deforestation on the water balance and support Madeira #31 7 18 23 the analysis of observations at that location made by Costa et al. Tapajós #38 4 9 13 (2003). Costa et al. (2003) compared the mean discharge for two Xingu #44 5 9 15 20-year periods at Porto Nacional; 1949–1968 when the basin Tocantins #56 26 32 34 was less than 30% deforested and 1979–1998 when the basin Offline IBIS/THMB simulated change in discharge relative to the potential vegeta- was about 50% deforested. In that study the authors found a 25% tion simulation (CTL). M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174 171 increase in annual mean discharge about ½ of which, was attrib- be paved on time, compliance with laws regarding protected lands uted by the authors to a precipitation increase and about ½ to (public and private) is low, and no new protected areas are created. deforestation and the resulting increase in ET. As a result by the year 2050 total deforestation is almost 50% of the A comparison of the CTL and MOD simulated discharge for the tropical evergreen forests of the basin (Table 2). The Tocantins is two periods shows results similar to Costa et al. (2003). In CTL the most deforested, about 93% by 2050. The total deforested area the simulated mean annual discharge at Porto Nacional is 11% in the other basins ranges from about 20% of the Japurá to 61% of greater in the 1979–1998 period compared to the 1949–1968 per- the Madeira, 66% of the Xingu, and 82% of the Tapajós by 2050. iod. Since the land cover is unchanged in that simulation and the The two scenarios illustrate that in the future even under strict ET difference is minimal the 11% increase in discharge can be compliance with laws (GOV), deforestation is likely to be large: attributed to a precipitation increase between these periods. The about 1.5 million km2 of the basin deforested by 2050. However, difference between the MOD simulated discharge for the period the difference between the GOV and BAU scenarios also indicates 1979–1998 and the CTL 1949–1968 is 25%, which is comparable that compliance with existing laws on public and private lands to the observed change. Therefore, the simulations and observa- and additions to protected areas can have significant impacts, tions suggest that a large part of the observed change in discharge avoiding in these scenarios, almost 1 million km2 of future defores- over the last 50 years in the Tocantins is most likely due to tation. Given the sensitivity of local evapotranspiration and regio- deforestation. nal precipitation to large-scale deforestation (Bonan, 2008), the two scenarios suggest that there will be potentially large changes Implications for the future in river flow and aquatic ecosystems in the future.
Future land use scenarios Results of offline IBIS simulations – land surface processes only In the (Soares-Filho et al., 2006) GOV scenario no deforestation The simulations with IBIS offline with GOV and BAU land cover takes place on protected areas, new protected lands are created, and identical prescribed climate illustrate the relative influence of and at least 50% of all private lands remain in forest. Despite the land surface processes alone on the local evapotranspiration and strict adherence to laws, by the year 2050, 30% of the Amazon ever- water balance. The simulated river discharge in all tributaries is in- green forest is deforested, three times the year 2000 value (Table 2, creased, relative to the control simulation, proportional to the area Fig. 1). Deforested area varies from 15% of the Negro in the far deforested, as a decrease in total LAI in any deforestation experi- north to 80% of the Tocantins in the southeast. The Xingu Basin ment results in reduced evapotranspiration and increased runoff is considerably less deforested than its neighbors (26%) because (Fig. 4a, Table 3). The annual mean discharge of the Amazon River of the Xingu Indigenous Park and associated protected lands, (station #33, Fig. 2) is increased by 5% in GOV relative to the CTL which occupy about 55% of the basin. simulation with about 25% of the basin deforested and by 7% in The (Soares-Filho et al., 2006) BAU scenario assumes that cur- BAU with 40% of the basin deforested (Tables 2 and 3). Greatest rent deforestation trends will continue, all scheduled roads will change in annual mean discharge (about 10–30% increase) is
Fig. 4. Change in annual mean discharge relative to the IBIS-offline CTL simulation for the GOV (blue) and BAU (red) simulations for (a) IBIS-offline simulations and (b) coupled CCM3-IBIS simulations. 172 M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174 simulated in the southern tributaries consistent with the largest ( 3%) and most of the tributaries (Fig. 4b, Tables 2 and 4). The net area deforested by 2050. The northern and western tributaries discharge decrease indicates that the regional precipitation changes have 5% or less increase in GOV consistent with about 25% or less that result from the feedback with deforestation are larger than the of those basins being deforested, and only a modest increase in local ET decrease and dominate the discharge response. In the case of BAU. The Tocantins River, with about 80% of the basin deforested the Negro there is a moderate precipitation decrease of 8% (Table in the GOV simulation, has a 32% simulated increase relative to 4), relatively small land cover change ( 15% Tables 2 and 4) and CTL, and 34% increase in BAU, with 93% deforestation. The Madeira therefore, a relatively large discharge decrease of 10%. The south- has an 18% increase in GOV that increases to 23% in BAU, while the ern tributaries, where deforestation is greatest respond in a more Tapajós and Xingu both have a 9% increase in GOV that increases to complex way. The Xingu River has a large precipitation decrease 13% and 15% respectively in BAU (Table 3). ( 15%) due to the regional atmospheric changes but the deforesta- The results of these offline simulations are consistent with tion within the basin is relatively low compared to its neighbors small, and in the case of the Tocantins and Araguaia (Coe et al., (26%). As a result, there is an 11% decrease in simulated discharge 2008; Costa et al., 2003), large-scale observations of the response in the Xingu, which is greater than any other basin (Tables 2 and of river discharge to deforestation and conversion to agriculture: 4). The neighboring Madeira, Tapajós, and Tocantins basins have a evapotranspiration decreases as native vegetation is replaced with similarly large precipitation decrease but the deforested area is less water demanding pasture and crops, and annual mean dis- much greater than the Xingu. As a result there is an increase in the charge increases. Therefore, as with the case of the Tocantins and discharge of the Madeira (3%) and Tocantins (12%) and a small de- Araguaia Rivers, which already show an increase in discharge of crease in the Tapajós ( 2%) (Tables 2 and 4). about 25%, in the absence of any significant atmospheric feedbacks In the BAU-CCM3 simulation about 40% of the Amazon up- to precipitation, future deforestation in any of these basins can be stream of Óbidos is deforested and precipitation is further de- expected to lead to locally increased discharge. However, as has creased in almost all basins, particularly where deforestation is been demonstrated in numerous global climate model simulations, greatest (Tables 2 and 4). The discharge is decreased in all tributar- with large-scale deforestation regional precipitation is expected to ies except the Japurá, Madeira, and Tocantins Rivers relative to the decrease because of the combined influences of increased albedo, GOV-2050 and CTL simulations (Table 4, Fig. 4b). Precipitation is decreased surface roughness and decreased water recycling that decreased by an additional 4% in the Madeira River compared to accompany deforestation (Costa, 2005; Delire et al., 2001; Dickin- GOV but the deforested area increases from 54% to 69% of the wa- son and Henderson-Sellers, 1988; Malhi et al., 2008a). Long-term tershed, as a result there is a slight increase in the discharge to 4% discharge is the residual of the precipitation minus the ET, there- greater than CTL. The discharge difference of the Tocantins River fore, any decrease in precipitation will act to decrease discharge relative to CTL decreases to about 8% compared to about 12% in and offset some or all of the increase in discharge that may result GOV-2050. from a local decrease in ET.
Results of coupled CCM3/IBIS simulations – land surface processes and Discussion and conclusions atmospheric feedbacks The GOV-CCM3 and BAU-CCM3 simulations illustrate the po- At the micro scale to meso-scale, deforestation generally results tential importance of the combined effects of the local ET decrease in decreased ET and increased runoff, and discharge. At the large- and regional precipitation decrease on the river discharge. scale, atmospheric feedbacks may significantly reduce precipita- The mean annual precipitation of the GOV-CCM3 simulation is tion regionally and, if larger than the local ET changes, may de- decreased in all tributaries of the Amazon compared to the precipi- crease water yield, runoff and discharge. tation used in the CTL. The greatest change, compared to the control The results presented here, as with all modeling studies, are to simulation, of as much as 15% occurs, in the southeastern tributaries some unknown-degree dependent on the experiment design and where deforestation is also greatest (Tables 2 and 4). In contrast to model assumptions. IBIS has been well-tested and validated for the offline IBIS-THMB results presented in ‘‘Results of offline IBIS historical climate for tropical and non-tropical vegetation types simulations – land surface processes only”, there is a small net de- and its sensitivity to land cover differences has been validated in crease in simulated discharge for the mainstem of the Amazon previous studies (Li et al., 2007). However, as pointed out by (Li et al., 2007) the sensitivity of IBIS simulated ET to deforestation Table 4 is, in part, a function of model specific parameters such as plant Change in coupled CCM3/IBIS model simulated precipitation and discharge relative to rooting depth and soil hydraulic properties, among others. The the offline IBIS/THMB CTL. simulated climate of the coupled CCM3-IBIS model has been exten- Precipitation Discharge sively validated and shown to reproduce historical climate of the GOV-CCM3 BAU-CCM3 GOV-CCM3 BAU-CCM3 Amazon in good agreement with the observations (Senna et al., (%) (%) (%) (%) submitted for publication). However, the exact response of the
Amazon #33 9 12 3 4 atmospheric circulation and climate simulated by CCM3-IBIS to Negro #21 8 12 10 10 deforestation is a function of numerous specific features of this Japurá #9 5 2 30model and experiment design such as resolution, convection Solimões #10 6 7 1 2 scheme, cloud parameterizations, prescribed sea-surface tempera- Solimões #5 5 50 1 tures, fixed CO , etc. For example, the potential feedbacks between Juruá #8 5 13 8 13 2 Purus #17 9 15 5 8 deforestation, globally increasing CO2 and temperature and plant Madeira #31 14 17 3 4 physiological and soil respiration responses not included in this Tapajós #38 12 16 2 5 study (Cox et al., 2000; Knorr et al., 2005; Korner and Arnone, Xingu #44 15 20 11 17 1992; Melillo et al., 2002) are not well understood but could poten- Tocantins 15 14 12 8 #56 tially affect hydrology through changes in plant water demand and ecosystem structure (Moorcroft, 2006). The precipitation values are the input data derived for the GOV-CCM3 and BAU- Despite the unknown aspects of the model sensitivity, the series CCM3 experiments minus the precipitation used as input to the offline-IBIS CTL simulation. The discharge values are the differences of the simulated THMB dis- of simulations presented in this manuscript clarify a few important charge forced with the coupled model data from the CTL. points about the impact of deforestation on the Amazon River. The M.T. Coe et al. / Journal of Hydrology 369 (2009) 165–174 173 simulations with IBIS and THMB offline indicate that the local ET However, as observations indicate (Bradshaw et al., 2007) it is rea- decrease and subsequent discharge increase can be a significant sonable to expect that a change in the mean state will result in an fraction of the water balance when greater than 50% of a watershed increase in the scale of flood and drought events. These simulations is deforested. The results of this study agree with the findings also do not address the potentially large morphological and bio- reported for a 175,000 km2 section of the Tocantins River (Costa chemical changes to rivers, that accompany land cover change et al., 2003) and an 82,000 km2 section of the Araguaia (Coe and that have important impacts on aquatic environments (Coe et al., 2008): observed discharge has increased by about 25%, et al., 2008; Gordon and peterson, 2008). These changes to extreme despite little precipitation change, in the last 50 years as these events, morphology, and biochemistry will be responsible for most watersheds were converted from predominantly forest and Cerra- of the social, ecological, and economic disruptions to come from do to pasture and agriculture. The model results suggest that in the deforestation and must be addressed with higher resolution mod- absence of a continental scale precipitation change, large-scale eling and observational studies in the future. deforestation can have a significant impact on a large river system In summary, the exact hydrological future of the Amazon is and appears to have already done so, at least in the Tocantins and uncertain but the results of this study suggest that a combination Araguaia Rivers. In the other large tributaries, where deforestation of land surface responses and atmospheric feedbacks from histor- has not yet exceeded 25% of the watershed area, any changes to ical deforestation has already influenced watersheds in the south- discharge are probably too small to be detected in the observations eastern Amazon basin significantly and that complex human- (<10%). However, smaller watersheds in which deforestation has induced impacts will spread throughout the basin as a larger area already exceeded 50% (e.g. the southern Xingu, and Tapajós) may is deforested and converted to pasture and agriculture. Under- already be experiencing large and as yet undocumented changes. standing future changes and mitigating future impacts in an indi- The coupled CCM3-IBIS results suggest that atmospheric feed- vidual watershed will only come by integrating continental-scale backs brought about by large-scale deforestation may be of the and local-scale information. same order of magnitude as the changes to local land surface pro- cesses, but of opposite sign. Additionally, changes in the water bal- Acknowledgements ance caused by atmospheric feedbacks are not limited to those basins where deforestation has occurred but are spread unevenly We gratefully acknowledge the contributions of Paul Lefebvre throughout the basin by atmospheric circulation. As a result, and Claudia Stickler and reviewer Dr. Christine Delire. This work changes to discharge and aquatic environments with future defor- was supported through grants from The National Aeronautic and estation of the Amazon will likely be a complex function of how Space Administration Large-Scale Atmosphere and Biosphere much vegetation has been removed from that particular watershed Experiment in Amazonia program and the Gordon and Betty Moore and how much has been removed from the entire Amazon Basin. Foundation. For example, in the GOV simulation the Purus River is about 20% deforested, which the offline IBIS simulations suggest should result in a very small positive discharge anomaly (<5% increase) from the References ET decrease. However, in the coupled simulations the Purus has a Achard, F. et al., 2002. Determination of deforestation rates of the world’s humid 5% decrease in mean discharge, illustrating the importance of pre- tropical forests. 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