کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4393955 1618283 2009 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application and comparison of two prediction models for groundwater levels: A case study in Western Jilin Province, China
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Application and comparison of two prediction models for groundwater levels: A case study in Western Jilin Province, China
چکیده انگلیسی

Evaluation and prediction of groundwater levels through specific model(s) helps in forecasting of groundwater resources. Among the different robust tools available, the Integrated Time Series (ITS) and Back-Propagation Artificial Neural Network (BPANN) models are commonly used to empirically forecast hydrological variables. Here, we discuss the modeling process and accuracy of these two methods in assessing their relative advantages and disadvantages based on Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and coefficient of efficiency (CE). The arid and semi-arid areas of western Jilin province of China were chosen as study area owing to the decline of groundwater levels during the past decade mainly due to overexploitation. The simulation results indicated that both ITS and BPANN are accurate in reproducing (fitting) the groundwater levels and the CE are 0.98 and 0.97, respectively. In the validation phase, the comparison of the prediction accuracy of the BPANN and ITS models indicated that the BPANN models is superior to the ITS in forecasting the groundwater levels time series in term of the RMSE, MAE and CE.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Arid Environments - Volume 73, Issues 4–5, April–May 2009, Pages 487–492
نویسندگان
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