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H. Rezaei-Sadr, A. M. Akhoond-Ali, F. Radmanesh, G. A. Parham,
Volume 17, Issue 66 (2-2014)
Abstract

In this study, the influence of spatial heterogeneity of rainfall on flood hydrograph prediction in three mountainous catchments in south west of Iran was studied. Two interpolation techniques including Thiessen polygons method and Inverse Distance Weighting method were applied to compare the rainfall patterns of surrounding rain-gages in hydrograph simulation with rainfall patterns of nearest rain-gage from the catchment outlet. It was found that the best simulated hydrograph is obtained from rainfall pattern of the nearest rain gage. Moreover, the results did not show any relationship between spatial variation of rainfall and outlet hydrograph. Formation of different local rainfall patterns due to non-stationary rainfall field provoked by irregular topography and their effect on interpolation procedure caused important biases in interpolated rainfall hyetographs obtained by Thiessen and IDW methods. It seems that the observed biases in the response of the catchments are the result of inaccurate representation of spatially averaged rainfall rather than its spatial variability. Hence, in mountainous catchments with irregular topography, the lack of sufficient records caused by poor rain gage arrangement can be highlighted as the dominant source of uncertainty in modeling the spatial variations of rainfall.
M. Isazadeh, R. Arabzadeh, S. Darbandi,
Volume 20, Issue 77 (11-2016)
Abstract

Selection of optimum interpolation technique to estimate water quality parameters in unmeasured points plays an important role in managing the quality and quantity of water resources. The aim of this study is to evaluate the accuracy of interpolation methods using GIS and artificial neural network (ANNs) model. To this end, a series of qualitative parameters of samples from water taken from Dehgolan aquifer located in Kurdistan, Iran including CL, EC and PH were evaluated by any of the models. In this study, qualitative data from 56 observation wells with good dispersion in the whole plain was used. The data of 46 observation wells were used for calibration and the data of other 10 wells were used for verification of models. The results showed ANNs, IDW, and Kriging excellence and accuracy over other models in estimation of quality parameters CL, PH and EC. However the ANNs model is more accurate than other models. In case of lack of time and the need for acceptable accuracy and less risk in the estimation of qualitative parameters, the use of ANNs model is superior to other statistical models used.



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