Statistical downscaling methods describe a statistical relationship between large-scale atmospheric variables such as temperature, humidity, precipitation, etc., and local-scale meteorological variables like precipitation. This study examines the potential predictor variables selected from the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data set for downscaling monthly precipitation in Tahtali watershed in Turkey. An approach based on the assessment of all possible regression types was used to select the predictors among the NCEP reanalysis data set, and artificial neural network (ANN)–based downscaling models were designed separately for each station in the basin. The results of the study showed that precipitation, surface and sea level pressures, air temperatures at surface, 850-, 500-, and 200-hPa pressure levels, and geopotential heights at 850- and 200-hPa pressure levels are the most explanatory NCEP/NCAR parameters for the study a...

The emergence of the Gravity Recovery And Climate Experiment (GRACE) paved the way for remote tracking of hydrological water cycle components at large scales. With the main motivation of evaluating the feasibility of the coarse resolution GRACE data for small-scale analysis, the GRACE data and large-scale hydrological models were utilized in an integrated manner to monitor the variations of the flood potential index (FPI) over the Western Anatolian Basin (WAB). The results show an ascending trend for monthly and annual FPI over the WAB. The results also suggest that the monthly FPI in 2015, 2003, 2009, and 2016 was the highest, from which the highest potentiality of flood appertains to 2015/07 with an FPI of 0.92. The lowest and highest annual FPI is 0.26 (in 2007) and 0.76 (in 2015), respectively. The validation of the results indicates that variations of FPI coincide with that of the flood incidents, stream discharge, Standardized Precipitation Index (SPI), and the simulated flood risk. The findings accentuate the high feasibility of the GRACE JPL Mascons for better surveillance of floods over local scale areas.

A numerical modeling case study of groundwater flow in a diffuse pollution prone area is presented. The study area is located within the metropolitan borders of the city of Izmir, Turkey. This groundwater flow model was unconventional in the application since the groundwater recharge parameter in the model was estimated using a lumped, transient water-budget based precipitation-runoff model that was executed independent of the groundwater flow model. The recharge rate obtained from the calibrated precipitation-runoff model was used as input to the groundwater flow model, which was eventually calibrated to measured water table elevations. Overall, the flow model results were consistent with field observations and model statistics were satisfactory. Water budget results of the model revealed that groundwater recharge comprised about 20% of the total water input for the entire study area. Recharge was the second largest component in the budget after leakage from streams into the subsurface. It was concluded that the modeling results can be further used as input for contaminant transport modeling studies in order to evaluate the vulnerability of water resources of the study area to diffuse pollution.