Trend Analysis and Spatial Prediction of Groundwater Levels Using Time Series Forecasting and a Novel Spatio-Temporal Method Mohamad Sakizadeh 1,2 & Mohamed M. A. Mohamed 3,4 & Harald Klammler 5,6 Received: 16 July 2018 /Accepted: 3 February 2019/ # Springer Nature B.V. 2019 Abstract Overexploitation of groundwater in the Malayer Plain has resulted in a continuous decline of groundwater levels over recent years with associated risks to water security. Effective water resource management requires the identification of the most susceptible regions and periods to such risks and, hence, spatio-temporal prediction tools of groundwater levels. For this purpose, we use 27 years of groundwater level records (between 1984 and 2012) and apply time series forecasting models including seasonal Autoregressive Integrated Moving Average (ARIMA) and Holt-Winters Exponential Smoothing (HWES). The spatial variation of groundwater levels is investigated by a novel method known as Fixed Rank Kriging (FRK). The results demonstrate that ARIMA outperforms HWES in fitting the training data. In contrast, the 95% confidence bound of ARIMA predictions is wider than that of HWES and ARIMA ’ s predicted seasonal cycle is weaker. The time series forecasting by a stochastic simulation indicated that if the current situation continues, the level of groundwater is expected to decline from 1635 m to about 1605 m by 2022. The FRK showed that the amount of groundwater extraction in the western part of the aquifer was higher than that of the northern and central parts. Keywords Exponential smoothing . Fixed rank kriging . Groundwater . Seasonal ARIMA 1 Introduction Analysis of spatial and temporal trends of groundwater levels in over-exploited aquifers (e.g., Malayer Plain) facilitates the detection of factors that need to be managed. Modeling and prediction of groundwater fluctuations are the initial stage of effective management in this respect. There are many techniques for the evaluation of temporal trends of groundwater and Water Resources Management https://doi.org/10.1007/s11269-019-02208-9 Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11269-019- 02208-9) contains supplementary material, which is available to authorized users. * Mohamed M. A. Mohamed m.mohamed@uaeu.ac.ae Extended author information available on the last page of the article