Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

Dominika Dąbrowska,Jan Waligóra,Marek Sołtysiak

doi:10.1515/environ-2015-0074

Dominika Dąbrowska, Jan Waligóra + Show 1 more

Open Access

https://doi.org/10.1515/environ-2015-0074

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Abstract

Abstract The Ustroń S.A. Health Resort (southern Poland) uses iodide-bromide mineral waters taken from Middle and Upper Devonian limestones and dolomites with a mineralisation range of 110-130 g/dm3 for curative purposes. Two boreholes - U-3 and U3-A drilled in the early 1970s were exploited. The aim of this paper is to estimate changes in mineral water quality of the Ustroń Health Resort by taking into consideration chloride content in the water from the U-3 borehole. The data has included the results of monthly analyses of chlorides from 2005 to 2015 during the tests carried out by the Mining Department of the Health Resort. The triple exponential smoothing (ETS) function and the Seasonal Autoregressive Integrated Moving Average (SARIMA) method of modelling time series were used for the calculations. The ability to properly forecast mineral water quality can result in a good status of the exploitation borehole and a limited number of failures in the exploitation system. Because of the good management of health resorts, it is possible to acquire more satisfied customers. The main goal of the article involves the real-time forecast accuracy, obtained results show that the proposed methods are effective for such situations. Presented methods made it possible to obtain a 24-month point and interval forecast. The results of these analyses indicate that the chloride content is forecast to be in the range of 72 to 83 g/l from 2015 to 2017. While comparing the two methods of analysis, a narrower range of forecast values and, therefore, greater accuracy were obtained for the ETS function. The good performance of the ETS model highlights its utility compared with complicated physically based numerical models.

Highlights

Introduction accuracy and reliability in forecasting is based on Autoregressive Integrated Moving Average (ARIMA), Precise methods of forecasting data allow for a seasonal autoregressive integrated moving average better assessment of physical phenomena changing. (SARIMA) and exponential smoothing models
– assimilated precipitation and subsequent runoff of water used in health resorts for curative purposes. (RAHIMI ET AL., 2014; VALIPOUR, 2015) which show Among the many methods available for investigating that data-driven methods ensure the robustness environmental forecasts, integrated moving average of the model
There are many methods intended for groundwater chemical status assessments at the forecasting, such as physically based numerical Ustroń Health Resort

Summary

Introduction

1. Introduction accuracy and reliability in forecasting is based on Autoregressive Integrated Moving Average (ARIMA), Precise methods of forecasting data allow for a seasonal autoregressive integrated moving average better assessment of physical phenomena changing. The reliable assessment and forecasting of seasonal runoff forecasting systems constructed groundwater chemical status is extremely important from a statistical relationship between the model in determining the physico-chemical properties. (RAHIMI ET AL., 2014; VALIPOUR, 2015) which show Among the many methods available for investigating that data-driven methods ensure the robustness environmental forecasts, integrated moving average of the model. There are many methods intended for groundwater chemical status assessments at the forecasting, such as physically based numerical Ustroń Health Resort. Autoregressive integrated moving average (MENHAJ, 2012), and fuzzy or rough sets theory and exponential smoothing are very useful models (DUBOIS & PRADE, 1990).

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