2018
DOI: 10.1590/2318-0331.0318170071
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Physical-based time series model applied on water table depths dynamics characteristics simulation

Abstract: Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the d… Show more

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Cited by 5 publications
(3 citation statements)
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“…It has been made through wells instrumented with automatic water level monitoring systems belonging to the National Groundwater Monitoring Network (RIMAS). The evaluation of water table uctuation is a data-based approach that enables the identi cation of the timing of recharge and its mechanisms, having signi cant consequences for the better management of water resources (Mangin, 1984;Maziero and Wendland, 2005;Manzione, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…It has been made through wells instrumented with automatic water level monitoring systems belonging to the National Groundwater Monitoring Network (RIMAS). The evaluation of water table uctuation is a data-based approach that enables the identi cation of the timing of recharge and its mechanisms, having signi cant consequences for the better management of water resources (Mangin, 1984;Maziero and Wendland, 2005;Manzione, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…최근에는 다양한 모델링 기법들을 적용해 대수층의 수 리 특성값들을 획득하고자 하는 연구들이 이어지고 있다 (Jeong and Park, 2017;Jeong et al, 2019). 모델링 기법 을 이용한 대수층 특성 연구는 크게 물리적 프로세스 기 반(physical process-based) 분석과 자료 기반(data-driven) 분석으로 분류할 수 있다 (Felisa et al, 2015;Manzione, 2017 (Bierkens, 1998;Knotters and Bierkens, 2000;Rai et al, 2006;Park and Parker, 2008;Cuthbert, 2010;Jeong and Park, 2017;Jeong et al, 2019 (Adamowski and Chan, 2011;Nourani et al, 2015;Han et al, 2015 (Delbart et al, 2014;Neto et al, 2015;Jeong et al, 2017 (Joo et al, 2009;Coulibaly et al, 2001;Yoon et al, 2011;, Nourani et al, 2012;Jeong and Park, 2019 (Coppola et al, 2005;Almasri and Kaluarachchi, 2005;Nayak et al, 2006;Jeong and Park, 2019;Jeong et al, 2020)…”
unclassified
“…O modelo Predefined Impulse Response Function In Continuous Time (PIRFICT) trabalha com tempo contínuo e tem as caraterísticas de resposta de sistemas de águas subterrâneas estimadas por funções de impulso e resposta. Estudos recentes sobre esta temática que utilizaram o modelo PIRFICT vêm sendo desenvolvidos, como Yihdego e Webb (2010), Lehsten, von Asmuth, e Michael Kleyer (2011), Yihdego e Webb (2011), Gunawardhana e Kazama (2012), Robson e Webb (2012), Nava e Manzione (2015), Hocking e Kelly (2016), Omran (2016), Manzione, Soldera e Wendland (2017) e Manzione (2018).…”
unclassified