The study and design of water-intakes on springs is based on the analysis of time series of
historical measurements to achieve prediction of incoming water volumes or future
expected.
The research aims to model the monthly water flows of AL-SIN Sp
ring in Syrian Coast
and future expectations of these flows, by adopting the Box-Jenkins models to analyze the
time series data, due to its reliable accuracy. Monthly water flows, thus, monthly volumes,
for 101 month (from June 2008 to October 2016) were processed. Performing the stability
of the time series on variance and median and non-seasonality and making the wanted tests
on model residuals, we found that the best model to represent the data is SARIMA(2,0,1)
(2,1,0)12 , and after dividing the data into 81 month to build the model and 20 month to test
it. Depending on the smallest of weighted mean of criteria RMSE, MAP, MAE,. The best
predicted model was SARIMA (3,1,0) (1,1,0)12 and the model gave the nearest predicted
values to actually measured data in spring.
AlSin Spring spurts at the foot of coastal mountains and pours in The Mediterranean sea
near Arab-Almulk village. Presently, spring water used for drinking, irrigation and
industry, while excess water goes to sea.
Current research aims to determin
e the daily discharge response to daily rainfall, and to set
an equation for recession discharge for predicting spring discharge and volumes of flow
after definite time from the beginning of spring base flow, which allows to operate and
manipulate available water resources through an optimum design of water intake from this
spring.
Response time of AlSin Spring between (3-5) days for average discrete daily rainfall with
high intensity which caused 0.5 ~ 1.0 m3/sec increasing in spring discharge value.
Yearly discharge trends to decrease with a rate of 0.0975 m3/sec between 1974 and 2016
years. While the monthly minimum discharges increase about 0.1284 m3/sec, and monthly
maximums decrease about 0.0752 m3/sec between 1994 and 2016.
We recommend adopting recession curve analysis to predict the optimal discharge of
springs within definite periods.
