Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W1, 147-149, 2016
https://doi.org/10.5194/isprs-archives-XLII-2-W1-147-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
26 Oct 2016
MODELLING THE EFFECTS OF LAND-USE CHANGES ON CLIMATE: A CASE STUDY ON YAMULA DAM
Ü. Köylü and A. Geymen ERU, Engineering Faculty, Dept. of Geomatic Engineering, 38039 Melikgazi Kayseri, Turkey
Keywords: Geographical Information Systems, Remote Sensing, Time Series, Trend Analysis, Artificial Reservoir Effect, Curve Number Abstract. Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial’s land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spatial and temporal analysis of the research area. For this research humidity, temperature, wind speed, precipitation observations which are collected in 16 weather stations nearby Kızılırmak Basin are analyzed. After that these statistical information is combined by GIS data over years. An application is developed for GIS analysis in Python Programming Language and integrated with ArcGIS software. Statistical analysis calculated in the R Project for Statistical Computing and integrated with developed application. According to the statistical analysis of extracted time series of meteorological parameters, statistical significant spatiotemporal trends are observed for climate change and land use characteristics. In this study, we indicated the effect of big dams in local climate on semi-arid Yamula Dam.
Conference paper (PDF, 645 KB)


Citation: Köylü, Ü. and Geymen, A.: MODELLING THE EFFECTS OF LAND-USE CHANGES ON CLIMATE: A CASE STUDY ON YAMULA DAM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W1, 147-149, https://doi.org/10.5194/isprs-archives-XLII-2-W1-147-2016, 2016.

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