Models for forecasting water demand using time series analysis: a case study in Southern Brazil

Technology has been increasingly applied in search for excellence in water resource management. Tools such as demand-forecasting models provide information for utility companies to make operational, tactical and strategic decisions. Also, the performance of water distribution systems can be improved...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Danielle C. M. Ristow, Elisa Henning, Andreza Kalbusch, Cesar E. Petersen
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	arima exponential smoothing forecasting water demand time series Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/b3076b2b9c8c4aeb9f98a6a4224b661b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:b3076b2b9c8c4aeb9f98a6a4224b661b
record_format	dspace
spelling	oai:doaj.org-article:b3076b2b9c8c4aeb9f98a6a4224b661b2021-11-05T19:29:38ZModels for forecasting water demand using time series analysis: a case study in Southern Brazil2043-90832408-936210.2166/washdev.2021.208https://doaj.org/article/b3076b2b9c8c4aeb9f98a6a4224b661b2021-03-01T00:00:00Zhttp://washdev.iwaponline.com/content/11/2/231https://doaj.org/toc/2043-9083https://doaj.org/toc/2408-9362Technology has been increasingly applied in search for excellence in water resource management. Tools such as demand-forecasting models provide information for utility companies to make operational, tactical and strategic decisions. Also, the performance of water distribution systems can be improved by anticipating consumption values. This work aimed to develop models to conduct monthly urban water demand forecasts by analyzing time series, and adjusting and testing forecast models by consumption category, which can be applied to any location. Open language R was used, with automatic procedures for selection, adjustment, model quality assessment and forecasts. The case study was conducted in the city of Joinville, with water consumption forecasts for the first semester of 2018. The results showed that the seasonal ARIMA method proved to be more adequate to predict water consumption in four out of five categories, with mean absolute percentage errors varying from 1.19 to 15.74%. In addition, a web application to conduct water consumption forecasts was developed. HIGHLIGHTS Monthly urban water demand forecasts are conducted by analyzing time series.; A case study in Southern Brazil is presented.; A web application to conduct water consumption forecasts is proposed, which can be used in other regions and countries.;Danielle C. M. RistowElisa HenningAndreza KalbuschCesar E. PetersenIWA Publishingarticlearimaexponential smoothingforecasting water demandtime seriesEnvironmental technology. Sanitary engineeringTD1-1066ENJournal of Water, Sanitation and Hygiene for Development, Vol 11, Iss 2, Pp 231-240 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	arima exponential smoothing forecasting water demand time series Environmental technology. Sanitary engineering TD1-1066
spellingShingle	arima exponential smoothing forecasting water demand time series Environmental technology. Sanitary engineering TD1-1066 Danielle C. M. Ristow Elisa Henning Andreza Kalbusch Cesar E. Petersen Models for forecasting water demand using time series analysis: a case study in Southern Brazil
description	Technology has been increasingly applied in search for excellence in water resource management. Tools such as demand-forecasting models provide information for utility companies to make operational, tactical and strategic decisions. Also, the performance of water distribution systems can be improved by anticipating consumption values. This work aimed to develop models to conduct monthly urban water demand forecasts by analyzing time series, and adjusting and testing forecast models by consumption category, which can be applied to any location. Open language R was used, with automatic procedures for selection, adjustment, model quality assessment and forecasts. The case study was conducted in the city of Joinville, with water consumption forecasts for the first semester of 2018. The results showed that the seasonal ARIMA method proved to be more adequate to predict water consumption in four out of five categories, with mean absolute percentage errors varying from 1.19 to 15.74%. In addition, a web application to conduct water consumption forecasts was developed. HIGHLIGHTS Monthly urban water demand forecasts are conducted by analyzing time series.; A case study in Southern Brazil is presented.; A web application to conduct water consumption forecasts is proposed, which can be used in other regions and countries.;
format	article
author	Danielle C. M. Ristow Elisa Henning Andreza Kalbusch Cesar E. Petersen
author_facet	Danielle C. M. Ristow Elisa Henning Andreza Kalbusch Cesar E. Petersen
author_sort	Danielle C. M. Ristow
title	Models for forecasting water demand using time series analysis: a case study in Southern Brazil
title_short	Models for forecasting water demand using time series analysis: a case study in Southern Brazil
title_full	Models for forecasting water demand using time series analysis: a case study in Southern Brazil
title_fullStr	Models for forecasting water demand using time series analysis: a case study in Southern Brazil
title_full_unstemmed	Models for forecasting water demand using time series analysis: a case study in Southern Brazil
title_sort	models for forecasting water demand using time series analysis: a case study in southern brazil
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/b3076b2b9c8c4aeb9f98a6a4224b661b
work_keys_str_mv	AT daniellecmristow modelsforforecastingwaterdemandusingtimeseriesanalysisacasestudyinsouthernbrazil AT elisahenning modelsforforecastingwaterdemandusingtimeseriesanalysisacasestudyinsouthernbrazil AT andrezakalbusch modelsforforecastingwaterdemandusingtimeseriesanalysisacasestudyinsouthernbrazil AT cesarepetersen modelsforforecastingwaterdemandusingtimeseriesanalysisacasestudyinsouthernbrazil
_version_	1718444059982299136

Models for forecasting water demand using time series analysis: a case study in Southern Brazil

Ejemplares similares