The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.     

Integration of GIS with USLE in Assessment of Soil Erosion

A Geographic Information System (GIS) has been integrated with the USLE (Universal Soil Loss Equation) model in identification of rainfall-based erosion and the transport of nonpoint source pollution loads to the Gediz River, which discharges into the Aegean Sea along the western coast of Turkey. The purpose of the study is to identify the gross erosion, sediment loads, and organic N loads within a small region of the Gediz River basin. Similar studies are available in literature, ranging from those that use a simple model such as USLE to others of a more sophisticated nature. The study presented here reflects the difficulties in applying the methodology when the required data on soil properties, land use and vegetation are deficient in both quantity and quality, as the case is with most developing countries.