Journal
APPLIED WATER SCIENCE
Volume 7, Issue 2, Pages 689-698Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13201-015-0282-2
Keywords
Groundwater table; Time series analysis; Holt-Winters; ARIMA; ITS
Categories
Funding
- National Natural Science Foundation of China [41402202]
- Specialized Research Fund for the Doctoral Program of Higher Education [20130061120084]
Ask authors/readers for more resources
Accurate and reliable groundwater level forecasting models can help ensure the sustainable use of a watershed's aquifers for urban and rural water supply. In this paper, three time series analysis methods, Holt-Winters (HW), integrated time series (ITS), and seasonal autoregressive integrated moving average (SARIMA), are explored to simulate the groundwater level in a coastal aquifer, China. The monthly groundwater table depth data collected in a long time series from 2000 to 2011 are simulated and compared with those three time series models. The error criteria are estimated using coefficient of determination (R-2), Nash-Sutcliffe model efficiency coefficient (E), and root-mean-squared error. The results indicate that three models are all accurate in reproducing the historical time series of groundwater levels. The comparisons of three models show that HW model is more accurate in predicting the groundwater levels than SARIMA and ITS models. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available