After the SWAT (Soil and Water Assessment Tool) model was calibrated and validated to historic flow records for the current land use conditions, two additional land cover scenarios (a prehistoric land cover and a potential maximum plantation pine cover) were used to evaluate the impacts of land...

A regional low flow frequency analysis in the north of Iran using L-moments was carried out. Low flow events have been represented by the 7-day annual minimum series and the L-moments approach was used to assign these data into homogenous regions. According to the homogeneity measure and...

Streamflow appraisal in time and space particularly in semi arid and dry sub humid regions has vital importance in the formulation of round the year plan of water uses comprising domestic & industrial water supply, irrigation scheduling, reservoir operation, in-stream flow maintenance etc....

The objective of this study is to compare the effects of climate change on crop yields across different regions. A Principal Component Regression (PCR) model is developed to estimate the historical relationships between weather and crop yields for corn, soybeans, cotton, and peanuts for several...

Selected Paper prepared for presentation at the Agricultural & Applied Economics Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24-26, 2011. (Poster Presentation)

The price transmission between markets is often interpreted as providing insights into the market’s infrastructure efficiency and transaction costs. Thus, finding a possible explanation for the degree of integration has become an issue of special interest. Recent researchers have pointed out...

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not su¢ciently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a...

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not sufficiently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a...