13 research outputs found
The Future Water Risks Under Global Change in Southern and Eastern Asia: Implications of Mitigation
Understanding and predicting the future vulnerability of freshwater resources is a major challenge with important societal implications. Many studies have identified Asia as a hotspot of severe water stress in the coming decades, and also highlighted the large uncertainty associated with water resource assessment based on limited multi-model projections. Here we provide a more comprehensive risk-based assessment of water use and availability in response to future climate change, socioeconomic growth, and their combination in Southern and Eastern Asia. We employ a large ensemble of scenarios that capture the spectrum of regional climate response as well as a range of economic projections and climate policies in a consistent, integrated modeling framework. We show that economic growth increases water stress ubiquitously. The climate-only and combined climate-growth effects on water stress remain largely negative in China and Indus Basin, but largely positive in India, Indochina, and Ganges Basin. However, climate poses substantially large uncertainty in water stress changes than socioeconomic growth. By 2050, socioeconomic growth alone can lead to an additional 650 million people living under at least “heavy” water stress, with most of these located in India, Indus Basin, and China. The combined effects of socioeconomic growth and climate change reduce people under water stress to an additional 200 million, attributed mainly to the beneficial climate in India that moves its heavily-stressed condition into the slightly or moderately‑stressed conditions. These 200 million people primarily reside in Indus Basin and China under at least overly exploited water conditions— where total water requirements will consistently exceed surface water supply. Climate mitigation helps alleviating the risks of increasing water scarcity by midcentury, but to a limited extent. Therefore, adaptive measures need to be taken to meet these surface water shortfalls, or a combination of both approaches may be most effective.This work was supported by the Department of Energy under An Integrated Framework for Climate Change Assessment (DE-FG02-94ER61937) and other government, industry and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change. For a complete list of sponsors and U.S. government funding sources, see http://globalchange.mit.edu/sponsors
CliCrop: a Crop Water-Stress and Irrigation Demand Model for an Integrated Global Assessment Model Approach
http://globalchange.mit.edu/research/publications/2264This paper describes the use of the CliCrop model in the context of climate change general assessment
modeling. The MIT Integrated Global System Model (IGSM) framework is a global integrated assessment
modeling framework that uses emission predictions and economic outputs from the MIT Emission Prediction
and Policy Analysis (EPPA) model and earth system modeling predictions from the IGSM to drive a
land system component, a crop model (CliCrop) and a Water Resource System (WRS) model. The global
Agriculture and Water System are dependant upon and interlinked with the global climate system. As irrigated
agriculture provides 60% of grains and 40% of all crop production on 20% of global crop lands and
accounts for 80% of global water consumption, it is crucial that the agricultural-water linkage be properly
modeled. Crop models are used to predict future yields, irrigation demand and to understand the effect of
crop and soil type on food productivity and soil fertility. In the context of an integrated global assessment, a
crop water-stress and irrigation demand model must meet certain specifications that are different for other
crop models; it needs to be global, fast and generic with a minimal set of inputs. This paper describes
how CliCrop models the physical and biological processes of crop growth and yield production and its use
within the MIT Integrated Global System Model (IGSM) framework, including the data inputs. This paper
discusses the global data bases used as input to CliCrop and provides a comparison of the accuracy of
CliCrop with the detailed biological-based crop model DSSAT as well as with measured crop yields over
the U.S. at the country level using reanalyzed weather data. In both cases CliCrop performed well and the
analysis validated its use for climate change impact assessment. We then show why correctly modeling the
soil is important for irrigation demand calculation, especially in temperate areas. Finally, we discuss a
method to estimate actual water withdrawal from modeled physical crop requirements using U.S. historical
data.The initial funding for CliCrop was provided by USAID under a program on climate change
adaptation in Niger. Further funding was provided by UN University World Institute for Development Economics
Research for the Application and Development of CliCrop in Africa, the authors would like to
particularly thank Prof. Finn Tarp, Prof. Channing Arndt and Dr. James Thurlow for their
support. The authors also would like to thank Dr. Jawoo Koo of IFPRI for his review and
contributions to the software development. The authors also gratefully acknowledge additional
financial support for this work provided by the MIT Joint Program on the Science and Policy of
Global Change through a consortium of industrial sponsors and Federal grants. Development of
the IGSM applied in this research was supported by the U.S. Department of Energy, Office of
Science (DE-FG02-94ER61937); the U.S. Environmental Protection Agency, EPRI, and other
U.S. government agencies and a consortium of 40 industrial and foundation sponsors
A Framework for Analysis of the Uncertainty of Socioeconomic Growth and Climate Change on the Risk of Water Stress: a Case Study in Asia
The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in how these factors change in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. If socio-economic growth is unconstrained by global actions to limit greenhouse gas concentrations, water-stressed populations may increase from about 800 million to 1.7 billion in this region.The Joint Program on the Science and Policy of Global Change is funded by a consortium of industrial and foundation sponsors. For the complete list see http://globalchange.mit.edu/sponsors/all
Analysis of U.S. Water Resources under Climate Change
The MIT Integrated Global System Model (IGSM) framework, extended to include a Water Resource System (WRS) component, is applied to an integrated assessment of effects of alternative climate policy scenarios on U.S. water systems. Climate results are downscaled to yield estimates of surface runoff at 99 river basins of the continental U.S., with an exploration of climate patterns that are relatively wet and dry over the region. These estimates are combined with estimated groundwater supplies. An 11-region economic model (USREP) sets conditions driving water requirements estimated for five use sectors, with detailed sub-models employed for analysis of irrigation and electric power. The water system of the interconnected basins is operated to minimize water stress. Results suggest that, with or without climate change, U.S. average annual water stress is expected to increase over the period 2041 to 2050, primarily because of an increase in water requirements, with the largest water stresses projected in the South West. Policy to lower atmospheric greenhouse gas concentrations has a beneficial effect, reducing water stress intensity and variability in the concerned basins.The Joint Program on the Science and Policy of Global Change is funded by the U.S.
Department of Energy, Office of Science under grants DE-FG02-94ER61937, DE-FG02-
93ER61677, DEFG02-08ER64597, and DE-FG02-06ER64320; the U.S. Environmental
Protection Agency under grants XA-83344601-0, XA-83240101, XA-83042801-0, PI-83412601-
0, RD-83096001, and RD-83427901-0; the U.S. National Science Foundation under grants SES-
0825915, EFRI-0835414, ATM-0120468, BCS-0410344, ATM-0329759, and DMS-0426845;
the U.S. National Aeronautics and Space Administration under grants NNX07AI49G,
NNX08AY59A, NNX06AC30A, NNX09AK26G, NNX08AL73G, NNX09AI26G,
NNG04GJ80G, NNG04GP30G, and NNA06CN09A; the U.S. National Oceanic and
Atmospheric Administration under grants DG1330-05-CN-1308, NA070AR4310050, and
NA16GP2290; the U.S. Federal Aviation Administration under grant 06-C-NE-MIT; the Electric
Power Research Institute under grant EPP32616/C15124; and a consortium of 40 industrial and
foundation sponsors (for the complete list see http://globalchange.mit.edu/sponsors/current.html
Modeling Water Resource Systems under Climate Change: IGSM-WRS
Through the integration of a Water Resource System (WRS) component, the MIT Integrated Global System Model (IGSM) framework has been enhanced to study the effects of climate change on managed water-resource systems. Development of the WRS involves the downscaling of temperature and precipitation from the zonal representation of the IGSM to regional (latitude-longitude) scale, and the translation of the resulting surface hydrology to runoff at the scale of river basins, referred to as Assessment Sub-Regions (ASRs). The model of water supply is combined with analysis of water use in agricultural and non-agricultural sectors and with a model of water system management that allocates water among uses and over time and routes water among ASRs. Results of the IGSM-WRS framework include measures of water adequacy and ways it is influenced by climate change. Here we document the design of WRS and its linkage to other components of the IGSM, and present tests of consistency of model simulations with the historical record.The Joint Program on the Science and Policy of Global Change is funded by the U.S. Department
of Energy, Office of Science under grants DE-FG02-94ER61937, DE-FG02-93ER61677, DEFG02-
08ER64597, and DE-FG02-06ER64320; the U.S. Environmental Protection Agency under
grants XA-83344601-0, XA-83240101, XA-83042801-0, PI-83412601-0, RD-83096001, and RD-
83427901-0; the U.S. National Science Foundation under grants SES-0825915, EFRI-0835414,
ATM-0120468, BCS-0410344, ATM-0329759, and DMS-0426845; the U.S. National Aeronautics
and Space Administration under grants NNX07AI49G, NNX08AY59A, NNX06AC30A,
NNX09AK26G, NNX08AL73G, NNX09AI26G, NNG04GJ80G, NNG04GP30G, and
NNA06CN09A; the U.S. National Oceanic and Atmospheric Administration under grants
DG1330-05-CN-1308, NA070AR4310050, and NA16GP2290; the U.S. Federal Aviation
Administration under grant 06-C-NE-MIT; the Electric Power Research Institute under grant EPP32616/
C15124; and a consortium of 40 industrial and foundation sponsors (for the complete list
see http://globalchange.mit.edu/sponsors/current.html)
Water Body Temperature Model for Assessing Climate Change Impacts on Thermal Cooling
We develop and test a physically based semi-Lagrangian water body temperature model to apply climatological data and thermal pollution from river-based power plants to historical river flow data in order to better understand climate change impacts on surface water temperature and thermal power plant withdrawal allowances. The model is built for rapid assessment and use in Integrated Assessment Models. We first test the standalone model on a 190km river reach, the Delaware River, where we have detailed flow and temperature data. An R2 of 0.88 is obtained on hourly data for this initial test. Next, we integrate the standalone temperature model into a series of models—rainfall-runoff model, water demand model, water resource management model, and power plant uptake and release model—for the contiguous USA (CONUS), with about 19,000 segments total. With this system in place, we then validate the standalone water temperature model within the system for 16 river stations throughout the CONUS, where we have measured daily temperature data. The model performs reasonably well with a median R2 of 0.88. A variety of climate and emissions scenarios are then applied to the model to test regions of higher vulnerability to river temperature environmental violations, making use of output from two GCMs and six emissions scenarios focusing on projections out to 2050. We find that the two GCMs project significantly different impacts to water temperature, driven largely by the resulting changes in streamflow from the two models. We also find significantly different impacts on the withdrawal allowed by thermal power plants due to environmental regulations. Potential impacts on generation are between +3% and -4% by 2050 for the unconstrained emissions case and +3.5% to -2% for the stringent GHG mitigation policy (where 1% is equivalent to 32 TWh, or about 3 billion USD/year using 2005 electricity prices). We also find that once-through cooling plants are most vulnerable to climate change impacts, with summer impacts ranging from -0.8% to -6% for the unconstrained emissions case and +2.1% to -3.7% for the stringent GHG emissions case
Neurological Disease Detection and Monitoring from Voice Production
The dramatic impact of neurological degenerative pathologies in life quality is a growing concern. It is well known that many neurological diseases leave a fingerprint in voice and speech production. Many techniques have been designed for the detection, diagnose and monitoring the neurological disease. Most of them are costly or difficult to extend to primary attention medical services. Through the present paper it will be shown how some neurological diseases can be traced at the level of phonation. The detection procedure would be based on a simple voice test. The availability of advanced tools and methodologies to monitor the organic pathology of voice would facilitate the implantation of these tests. The paper hypothesizes that some of the underlying mechanisms affecting the production of voice produce measurable correlates in vocal fold biomechanics. A general description of the methodological foundations for the voice analysis system which can estimate correlates to the neurological disease is shown. Some study cases will be presented to illustrate the possibilities of the methodology to monitor neurological diseases by voic