In this paper, downscaling models are developed using a Linear Multiple Regression (LMR) and Artificial Neural Networks (ANNs) for obtaining projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of these techniques is demonstrated through application to downscale the predictand (precipitation) for the Pichola lake region in Rajasthan state i...

Global warming due to greenhouse effect is expected to cause major changes in climate of some regions. The change of climate is likely to have a profound effect on hydrological cycle. Evapotranspiration (ET, as the major component of hydrological cycle, will affect crop water requirement and future planning and management of water resources. This study was conducted to investigate climate chang...

A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, ...

This study is intended to examine the past drought and predict future drought scenarios for Arkansas-Red River Basin with comprehensive drought indices ranging from meteorology, hydrometeorology to hydrology. In this proceeding, we present some early results and analysis with the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI). Historical climate data within ...

In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG), which occurred in the Sp1 domain of the promoter sequence. Combined with previous...

Two statistical downscaling models, the non-homogeneous hidden Markov model (NHMM) and the Statistical Down–Scaling Model (SDSM) were used to generate future scenarios of both mean and extremes in the Tarim River basin,which were based on nine combined scenarios including three general circulation models (GCMs) (CSIRO30, ECHAM5,and GFDL21) predictor sets and three special report on emission sce...