Evaporation Water Balance In Arid Area Anbar Governorate – Iraq
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Date
2018-03-01
Authors
Mohammed, Ahmed Saud
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
Estimation of water balance for ungauged basin in arid area environment is a major
challenge.The main problem is there are no precise equations to estimate evaporation
and surface runoff in arid area due to lack of data in these regions. Multiple linear
regression (MLR) stepwise and backward regression methods were used to develop
evaporation and surface runoff models. The results showed that the evaporation
developed model in linear regression method has proven its efficiency and its
ability to predict evaporation and the superiority against most important models that
used for estimating the evaporation. The results for evaporation developed model
were R2(0.923), NAE (0.134) and NSE (0.91) better than Thornthwaite and Blanny
Criddle models with results of R2(0.884), NAE (0.583) and, NSE (0.278) and R2
(0.91), NAE (0.324) and NSE (0.611) respectivily. The significant influence factors
are temperaure, wind speed and sunshine. To identify the parameters for surface
runoff and to select the significant groups for main factors of runoff prediction model
in catchments, three groups of independent variables have been established for MLR
analysis.The results showed that the best surface runoff model for Group 2 backward
regression method with R2 (0.744) and NAE (0.146) and NSE (0.722) where the
significant influence factors were rainfall, catchment slope, catchment area and
runoff coefficient. To improve the accuracy of runoff prediction model, similiar three
groups of MLR surface runoff model were analysis for two ANNs models and AI
techniques(SVM).The results indicate that MLP showed better results compare to
RBF and SVM methods for the predictive process, where the surface runoff MLP
Group 2 produced the best results compared to other models. The results of surface
runoff MLP Group 2 were in Training Phase (R2= 0.846, RMSE 0.160, NAE = 1.251, NSE = 0.846 ) while in Testing Phase (R2= 0.788, RMSE 0.182, NAE = 0.628, NSE = 0.775). Regression equation for evaporation model was integrated in GIS software (ArcGIS 10) to map the spatial distribution for monthly and seasonal
evaporation, water surplu for whole catchment study area. Runoff regression
equation was used to estimate the sub-catchments runoff in the study area using
transposition approach. Transposition of surface runoff data process was carried out
to estimate runoff volume in sub-catchment study area (ungauged area). The runoff
volume ranged between 1,321,732 m3 to 2,488,979 m3. Spatial distribution for runoff
volume were carried out using GIS environment on the entire study area.