Daniel Andres Rodriguez

The drought of 2010 in the context of historical droughts in the Amazon region

[1] The year 2010 featured a widespread drought in the Amazon rain forest, which was more severe than the “once‐in‐a‐century” drought of 2005. Water levels of major Amazon tributaries fell drastically to unprecedented low values, and isolated the floodplain population whose transportation depends upon on local streams which completely dried up. The drought of 2010 in Amazonia started in early austral summer during El Nino and then was intensified as a consequence of the warming of the tropical North Atlantic. An observed tendency for an increase in dry and very dry events, particularly in southern Amazonia during the dry season, is concomitant with an increase in the length of the dry season. Our results suggest that it is by means of a longer dry season that warming in the tropical North Atlantic affects the hydrology of the Amazon Rivers at the end of the recession period (austral spring). This process is, sometimes, further aggravated by deficient rainfall in the previous wet season. Citation: Marengo, J. A., J. Tomasella, L. M. Alves, W. R. Soares, and D. A. Rodriguez (2011), The drought of 2010 in the context of historical droughts in the Amazon region, Geophys. Res. Lett., 38, L12703, doi:10.1029/2011GL047436.

Impacts of future climatic and land cover changes on the hydrological regime of the Madeira River basin

Brazilian strategic interest in the Madeira River basin, one of the most important of the southern Amazon tributaries, includes the development of hydropower to satisfy the country’s growing energy needs and new waterways to boost regional trade and economic development. Because of evidences that climate change impacts the hydrological regime of rivers, the aim of this study was to assess how global climate change and regional land cover change caused by deforestation could affect the river’s hydrological regime. To achieve this goal, we calibrated a large-scale hydrological model for the period from 1970–1990 and analyzed the ability of the model to simulate the present hydrological regime when climate model simulations were used as input. Climate change projections produced by climate models were used in the hydrological model to generate scenarios with and without regional land-use and land-cover changes induced by forest conversion to pasture for the period from 2011–2099. Although results show variability among models, consensus scenarios indicated a decrease in the low-flow regime. When the simulations included forest conversion to pasture, climate change impacts on low flows were reduced in the upper basin, while, in the lower basin, discharges were affected along the whole year due to the more vigorous land-use conversion in the Brazilian region of the basin.

On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins

ABSTRACT The MHD-INPE model was applied in the Ji-Parana Basin, a 30 000 km2 catchment located in the southwest of the Amazon Basin which has lost more than 50% of its forest since the 1980s, to simulate land use and land cover change impacts on runoff generation process and how they are related to basin topography. Simulation results agree with observational studies in the sense that fast response processes are significant in sub-basins with steep slopes while in basins with gentle topography, the impacts are most visible in slow-response hydrological processes. On the other hand, the model is not able to capture the dependence of LUCC impacts on spatial scales. These discrepancies are probably associated with limitations in the spatial representation of heterogeneities within the model, which become more relevant at larger scales. We also tested the hypothesis that secondary forest growth should be able to compensate the decrease in evapotranspiration due to forest–cropland or forest–grassland conversion at a regional scale. Results showed that despite the small fraction of secondary forest estimated on the basin, the higher evapotranspiration efficiency of this type of forest counterbalances a large fraction of the LUCC impacts on evapotranspiration. This result suggests that enhanced transpiration due to secondary forest could explain, at least in part, the lack of clear LUCC signals in discharge series at larger scales. EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR T. Wagener

Experiments using new initial soil moisture conditions and soil map in the Eta model over La Plata Basin

An effort towards a more accurate representation of soil moisture and its impact on the modeling of weather systems is presented. Sensitivity tests of precipitation to soil type and soil moisture changes are carried out using the atmospheric Eta model for the numerical simulation of the development of a mesoscale convective system over northern Argentina. Modified initial soil moisture conditions were obtained from a hydrological balance model developed and running operationally at INPE. A new soil map was elaborated using the available soil profile information from Brazil, Paraguay, Uruguay, and Argentina and depicts 18 different soil types. Results indicate that more accurate initial soil moisture conditions and incorporating a new soil map with hydraulic parameters, more representative of South American soils, improve daily total precipitation forecasts both in quantitative and spatial representations.

Regional modeling of climate change impacts on smallholder agriculture and ecosystems in Central America

Climate change will have serious repercussions for agriculture, ecosystems, and farmer livelihoods in Central America. Smallholder farmers are particularly vulnerable due to their reliance on agriculture and ecosystem services for their livelihoods. There is an urgent need to develop national and local adaptation responses to reduce these impacts, yet evidence from historical climate change is fragmentary. Modeling efforts help bridge this gap. Here, we review the past decade of research on agricultural and ecological climate change impact models for Central America. The results of this review provide insights into the expected impacts of climate change and suggest policy actions that can help minimize these impacts. Modeling indicates future climate-driven changes, often declines, in suitability for Central American crops. Declines in suitability for coffee, a central crop in the regional economy, are noteworthy. Ecosystem models suggest that climate-driven changes are likely at low- and high-elevation montane forest transitions. Modeling of vulnerability suggests that smallholders in many parts of the region have one or more vulnerability factors that put them at risk. Initial adaptation policies can be guided by these existing modeling results. At the same time, improved modeling is being developed that will allow policy action specifically targeted to vulnerable groups, crops, and locations. We suggest that more robust modeling of ecological responses to climate change, improved representation of the region in climate models, and simulation of climate influences on crop yields and diseases (especially coffee leaf rust) are key priorities for future research.

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO2 sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO2 fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.

Comparisons of the Noah-MP land surface model simulations with measurements of forest and crop sites in Amazonia

This study evaluates the simulations of the Noah-MP surface processes over a crop and a forest sites in Amazonia using tower observations. Soil moisture simulations agree with the observations in both land covers, mainly during the rainy season. However, simulations show cold biases in the soil temperature at both sites. The magnitude and seasonal cycle of the surface energy fluxes are better simulated at the crop site, although the model significantly underestimates the sensible heat flux at this site. The model reproduces the seasonal pattern of surface runoff at both sites. The Noah-MP model does not adequately simulate the base flow at the crop site, while the simulated total runoff at the forest site is closer to the observation than at the crop site. The results show that, in general, the Noah-MP model simulations for the two sites in Amazonia exhibit fairly realistic performance, particularly over the crop site. However, there are cold biases in soil temperature simulations, which could be related with the parameterization of the equilibrium relationship between soil moisture and soil temperature.

Satellite precipitation in southeastern South America: how do sampling errors impact high flow simulations?

Abstract Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes.

Extreme Seasonal Climate Variations in the Amazon Basin: Droughts and Floods

The last 10 years have featured intense climate-hydrological extremes in the Amazon region: 2005, 2009, 2010, 2012–2013, and 2014–2015 leading to great impacts, such as large-scale droughts and floods, some of them being classified as ‘once-in-a-century’ events. Historical records show previous droughts in 1926, 1964, 1980, 1983, and 1998 and floods in 1953, 1988, and 1989. These events have been linked to natural climate variability and they impact on natural and human systems. Main cities in the Amazon region were flooded or were isolated by the extremely low river levels during the droughts. Model projections suggest that such extremes could be more frequent/intense in the future and that human activities, mainly in the form of land use change leading to increases in greenhouse gas concentration, may aggravate such extremes and make the impacts on the populations stronger. In this chapter, we review climate-hydrological extremes in a historical context, assessing observed trends, projected climate change scenarios, and the likelihood and uncertainties inherent to those scenarios.

Impacts of landscape fragmentation on simulated precipitation fields in the Amazonian sub-basin of Ji-Paraná using the Eta model

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region. Results indicate that variability in precipitation in this region is mainly controlled by large-scale atmospheric characteristics and soil moisture conditions. However, some limitations are identified in the model simulations, mainly associated to the diurnal cycle of precipitation.