Bayesian Multi-Scale Spatio-Temporal Modeling of Precipitation in the Indus Watershed

On Bayesian spatio-temporal modeling

Spatio-Temporal Changes of Natural Vegetation Disturbance in the Ahle Iman Watershed, Ardabil Province

The present study aimed to assess the spatio-temporal changes in the natural vegetation cover of Ahl Iman watershed, Ardabil province. For this purpose, land use maps of the three years (2000, 2010, and 2020) were extracted from Landsat satellite images. Then, seven landscape metrics (patch density, edge density, patch richness, splitting index, contagion index, Euclidean nearest neighbor dista...

spTimer: Spatio-Temporal Bayesian Modeling Using R

Hierarchical Bayesian modeling of large point referenced space-time data are increasingly becoming feasible in many environmental applications due to the recent advances in both statistical methodology and computation power. Implementation of these methods using the Markov chain Monte Carlo (MCMC) computational techniques, however, requires development of problem specific and user written compu...

Modeling of spatio-temporal of albedo over Iran

The aim of this study is modeling spatiotemporal variations of albedo. This study was conducted using simultaneous effects of several components, such as wetness of surface layer of soil, cloudiness, topography and vegetation density (NDVI), using MEERA2 model with a resolution of 50 in 50 km during 2000-2010 in Iran. The results of spatial analysis of albedo values in Iran showed that the high...

Multi-scale Comparison of Stage Iv Nexrad (mpe) and Gauge Precipitation Data for Watershed Modeling

Watershed hydrologic and fate-andtransport models are widely used to forecast water quantity and quality responses to alternative land use and climate change scenarios. The ability of such tools to forecast changes in ecosystem services with reasonable accuracy depends on calibrating reliable simulations of streamflow, which in turn require accurate climatic forcing data. Precipitation is widel...