Development of a GIS-based estimator for streamflow at ungaged catchments


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2017

Öğrenci: DUYGU ÖCAL

Danışman: ELÇİN KENTEL ERDOĞAN

Özet:

Water resources management has been a critical component of sustainable resources planning. One of the most commonly used data in water resources management is streamflow measurements. Daily streamflow time series collected at a streamgage provide information on the temporal variation in water quantity at the gage location. However, streamflow information is often needed at ungaged catchments. One conventional approach to estimate streamflow at an ungaged catchment is to transfer streamflow measurements from the spatially closest streamgage. Recently, the correlation between daily streamflow time series is proposed as an alternative to distance for reference streamgage selection. The Map Correlation Method (MCM) enables development of a map that demonstrates the spatial distribution of correlation coefficients between daily streamflow time series at a selected streamgage and all other locations within a selected study area. Due to its geostatistical analysis procedure MCM is time-consuming and hard to implement for practical purposes such as installed capacity selection of run-of-river hydropower plants during their feasibility studies. In this study, an easy-to-use GIS-based tool, called MCM_GIS is developed to apply the MCM. MCM_GIS provides a user-friendly working environment and flexibility in choosing between two types of interpolation models, kriging and inverse distance weighting. The main motivation of this study is to increase practical application of the MCM by integrating it to the GIS environment. MCM_GIS can also carry out the leave-one-out cross-validation scheme to monitor the overall performance of the estimation. The tool is tested on two study area; Western Black Sea Region and Çoruh Basin, Turkey. ArcGIS for Desktop product along with a Python script is utilized. The outcomes of inverse distance weighting and ordinary kriging are compared, no significant difference between the two interpolation methods was observed. Results of GIS-based MCM are in good agreement with the observed hydrographs according to NSE values.