Winston Yu

Arsenic in groundwater in Bangladesh: A geostatistical and epidemiological framework for evaluating health effects and potential remedies

[1] This paper examines the health crisis in Bangladesh due to dissolved arsenic in groundwater. First, we use geostatistical methods to construct a map of arsenic concentrations that divides Bangladesh into regions and estimate vertical concentration trends in these regions. Then, we use census data to estimate exposure distributions in the regions; we use epidemiological data from West Bengal and Taiwan to estimate dose response functions for arsenicosis and arsenic-induced cancers; and we combine the regional exposure distributions and the dose response models to estimate the health effects of groundwater arsenic in Bangladesh. We predict that long-term exposure to present arsenic concentrations will result in approximately 1,200,000 cases of hyperpigmentation, 600,000 cases of keratosis, 125,000 cases of skin cancer, and 3000 fatalities per year from internal cancers. Although these estimates are very uncertain, the method provides a framework for incorporating better data as it becomes available. Moreover, we examine the remedy of drilling deeper wells in selected regions of Bangladesh. By replacing 31% of the wells in the country with deeper wells the health effects of drinking groundwater arsenic could be reduced by approximately 70% provided that arsenic concentrations in deep wells remain relatively low. INDEX TERMS: 1831 Hydrology: Groundwater quality; 6309 Policy Sciences: Decision making under uncertainty; 6304 Policy Sciences: Benefit-cost analysis; 1829 Hydrology: Groundwater hydrology; KEYWORDS: arsenic, Bangladesh, geostatistics, health effects, risk assessment, mitigation

The future of water resources systems analysis: Toward a scientific framework for sustainable water management

This paper presents a short history of water resources systems analysis from its beginnings in the Harvard Water Program, through its continuing evolution toward a general field of water resources systems science. Current systems analysis practice is widespread and addresses the most challenging water issues of our times, including water scarcity and drought, climate change, providing water for food and energy production, decision making amid competing objectives, and bringing economic incentives to bear on water use. The emergence of public recognition and concern for the state of water resources provides an opportune moment for the field to reorient to meet the complex, interdependent, interdisciplinary, and global nature of todays water challenges. At present, water resources systems analysis is limited by low scientific and academic visibility relative to its influence in practice and bridled by localized findings that are difficult to generalize. The evident success of water resource systems analysis in practice (which is set out in this paper) needs in future to be strengthened by substantiating the field as the science of water resources that seeks to predict the water resources variables and outcomes that are important to governments, industries, and the public the world over. Doing so promotes the scientific credibility of the field, provides understanding of the state of water resources and furnishes the basis for predicting the impacts of our water choices.

Indus Basin of Pakistan : Impacts of Climate Risks on Water and Agriculture

This study, Indus basin of Pakistan: the impacts of climate risks on water and agriculture was undertaken at a pivotal time in the region. The weak summer monsoon in 2009 created drought conditions throughout the country. This followed an already tenuous situation for many rural households faced with high fuel and fertilizer costs and the impacts of rising global food prices. Then catastrophic monsoon flooding in 2010 affected over 20 million people, devastating their housing, infrastructure, and crops. Damages from this single flood event were estimated at US dollar 10 billion, half of which were losses in the agriculture sector. Notwithstanding the debate as to whether these observed extremes are evidence of climate change, an investigation is needed regarding the extent to which the country is resilient to these shocks. It is thus timely, if not critical, to focus on climate risks for water, agriculture, and food security in the Indus basin of Pakistan.

A Stochastic Simulation Approach to Estimating the Economic Impacts of Climate Change in Bangladesh

Climate change assessments often inadequately address uncertainty when estimating damages. Using a dynamic economy-wide model of Bangladesh, we estimate and decompose damages from historical climate variability and future anthropogenic climate change. Our stochastic simulation approach avoids biases caused by non-linear damage functions and fixed occurrences of extreme events in historical data. Using ten climate projections, we find that future anthropogenic climate change damages until 2050 are, on average, one-fifth of those from historical climate variability. Climate change also alters the temporal distribution of damages and slows Bangladeshâ..s long- run shift (adaptation) into dry (winter) season rice production.

An introduction to the IBMR, a hydro-economic model for climate change impact assessment in Pakistan's Indus River basin

The Indus Basin Model Revised (IBMR) is a hydro-agro-economic optimization model for agricultural investment planning across Pakistan’s Indus Basin provinces. This study describes IBMR-2012, an update and modification of the model that reflects the current agro-economic conditions in Pakistan for the purpose of evaluating the impact of climate change on water allocation and food security. Results of hydro-climatic parameter sensitivity and basin-wide and provincial-level climate change impacts on crop productions are presented. The study finds that compared to Punjab, Sindh faces both significantly larger climate change impacts on agriculture and higher uncertainty regarding climate change impacts in the future.

Estimation of flood damage functions for river basin planning: a case study in Bangladesh

Located at the low-lying deltaic floodplain of Ganges–Brahmaputra–Meghna river basin, Bangladesh suffers damages from flooding with regularity. From the perspective of long-term planning and management, a reliable flood damage function is a critical component in the estimation of flood-induced economic loss. Such functions are, however, notoriously difficult to develop. This study utilizes in-stream water level and flood-affected area (FAA) data from Flood Forecasting and Warning Center and Bangladesh Water Development Board to evaluate the best form and data input characteristics of flood damage functions for Bangladesh. The performance of various function configurations (geographic data, water level data, and function form) was tested. The Nash–Sutcliffe efficiency and residual error analysis results suggest that, in general, the logistic function performs better than the other two function forms, and the maximum of daily-maximal water level is the best suited to estimate (FAA). As expected, when information is available from all basins (the Ganges, the Brahmaputra, and the Meghna), the resulting flood damage functions provide the most accurate estimations of FAA. Furthermore, the comparison between single- and multivariable flood damage functions does not demonstrate a clear advantage of using multivariate function in our study area. When flood damage functions with finer spatial and temporal resolution can be constructed using remote sensing technology or hydrodynamic modeling, the intra-year and district-level changes to FAA can be evaluated. These findings provide a better flood management plan for Bangladesh and have potential to be generalized to other similarly flood-affected nations.

Exploring the effect of hydroclimate variability on economic growth in Sub-Saharan Africa: A water security index

Recent econometric studies provide evidence that climate variability in general, and rainfall variability in particular, has a negative effect on economic growth in the countries of Sub-Saharan Africa. In this study, we explore the factors that may explain why some countries are more resilient to climate variability than others. We use a range of data that is representative of the possible sources of resilience that are commonly hypothesized in the literature, including the state of water resources and water use, the inventory of infrastructure and the quality of institutions. Two analyses are undertaken. In the first, cross country regressions are used to explore aggregate associations of climate and resilience variables with economic growth. In the second, panel regressions for individual countries are performed with drought and flood indices. The results of these regressions are used to specify a water security index. The water security index is then analyzed through the prism of the resilience variables to draw inferences in regard to the sources of resilience that contribute to more water security. The results of these analyses are informative. Cross country regressions confirm the negative association between rainfall variability and economic growth within Sub-Saharan Africa. They also revealed strong associations between Foreign Direct Investment (FDI) and infrastructure inventory and economic growth. An index that accounts for climate variability and water storage (Seasonal Storage Index) is also strongly associated with both FDI and economic growth. The analysis of the Water Security Index revealed that more internal renewable water resources and irrigated agriculture as a percent of agricultural area were associated with more resilience to hydroclimate variability. Water storage was not a strong indicator of resilience, although when controlling for hydrologic variability with the SSI, it does become more important. There were no strong associations with institutions and weak positive associations with road density and phones.