Water Level Short-Term Forecasting Using Statistical Approaches: A Case Study on the Parisian Region

2020 ◽  
pp. 453-463
Author(s):  
Nicolas Cheifetz ◽  
Hugo Senetaire ◽  
Cédric Féliers ◽  
Véronique Heim
Keyword(s):  
Water Level ◽  
Short Term ◽  
Statistical Approaches ◽  
Short Term Forecasting

scholarly journals The influence of long- and short-term volcanic strain on aquifer pressure: a case study from Soufrière Hills Volcano, Montserrat (W.I.)

2020 ◽  
Vol 223 (2) ◽  
pp. 1288-1303
Author(s):  
K Strehlow ◽  
J Gottsmann ◽  
A Rust ◽  
S Hautmann ◽  
B Hemmings
Keyword(s):  
Water Level ◽  
Pore Pressure ◽  
Crustal Deformation ◽  
Water Levels ◽  
Short Term ◽  
Soufriere Hills Volcano ◽  
Soufrière Hills Volcano ◽  
Water Level Changes ◽  
Soufriere Hills

Summary Aquifers are poroelastic bodies that respond to strain by changes in pore pressure. Crustal deformation due to volcanic processes induces pore pressure variations that are mirrored in well water levels. Here, we investigate water level changes in the Belham valley on Montserrat over the course of 2 yr (2004–2006). Using finite element analysis, we simulate crustal deformation due to different volcanic strain sources and the dynamic poroelastic aquifer response. While some additional hydrological drivers cannot be excluded, we suggest that a poroelastic strain response of the aquifer system in the Belham valley is a possible explanation for the observed water level changes. According to our simulations, the shallow Belham aquifer responds to a steadily increasing sediment load due to repeated lahar sedimentation in the valley with rising aquifer pressures. A wholesale dome collapse in May 2006 on the other hand induced dilatational strain and thereby a short-term water level drop in a deeper-seated aquifer, which caused groundwater leakage from the Belham aquifer and thereby induced a delayed water level fall in the wells. The system thus responded to both gradual and rapid transient strain associated with the eruption of Soufrière Hills Volcano (Montserrat). This case study gives field evidence for theoretical predictions on volcanic drivers behind hydrological transients, demonstrating the potential of hydrological data for volcano monitoring. Interrogation of such data can provide valuable constraints on stress evolution in volcanic systems and therefore complement other monitoring systems. The presented models and inferred results are conceptually applicable to volcanic areas worldwide.

scholarly journals Short-Term Forecasting for Water Level of a Flood by Radar Hyetometer

1989 ◽  
Vol 33 ◽  
pp. 85-90
Author(s):  
Toshiyuki MORIYAMA ◽  
Munei HIRANO ◽  
Hisao NAKAYAMA ◽  
Keiji MATSUO ◽  
Hiroyuki TETSUYA
Keyword(s):  
Water Level ◽  
Short Term ◽  
Short Term Forecasting

scholarly journals Improving applicability of neuro-genetic algorithm to predict short-term water level: a case study

2013 ◽  
Vol 16 (1) ◽  
pp. 218-230 ◽  
Author(s):  
Gooyong Lee ◽  
Sangeun Lee ◽  
Heekyung Park
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Water Level ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
River Management ◽  
Water Levels ◽  
Short Term

This paper proposes a practical approach of a neuro-genetic algorithm to enhance its capability of predicting water levels of rivers. Its practicality has three attributes: (1) to easily develop a model with a neuro-genetic algorithm; (2) to verify the model at various predicting points with different conditions; and (3) to provide information for making urgent decisions on the operation of river infrastructure. The authors build an artificial neural network model coupled with the genetic algorithm (often called a hybrid neuro-genetic algorithm), and then apply the model to predict water levels at 15 points of four major rivers in Korea. This case study demonstrates that the approach can be highly compatible with the real river situations, such as hydrological disturbances and water infrastructure under emergencies. Therefore, proper adoption of this approach into a river management system certainly improves the adaptive capacity of the system.

Case Study: Analysis and Predictions of Shipment Load in Festive Season

2017 ◽  
Vol 7 (7) ◽  
pp. 491
Author(s):  
Megha Chhabra
Keyword(s):  
Time Series Models ◽  
Multiplicative Decomposition ◽  
Short Term ◽  
Case Study Analysis ◽  
Use Of Time ◽  
Load Demand ◽  
Huge Impact ◽  
Short Term Forecasting ◽  
Festive Season

A time-phased forecasting in rest of the year has a huge impact shipping costs, however during a festive season of the year, well predicted and analyzed re-engineering of shipment load plays a major role in bringing up sales. The major concern of the customer is to get delivery on-time, whereas that of the wholesaler / retailer is to provide delivery without any complaint in order to retain the customer. In the framework of competitive supply chain market, necessary accurate Shipping load forecasting tools are required. With the focus of improving prediction accuracy, this case study presents use of Time-series models, multiplicative decomposition model (MDM) and smoothening techniques, on shipping load demand of Arora-Ludhiana-Handlooms during festive seasons for short-term forecasting.

A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study

2013 ◽  
Vol 4 (3) ◽  
pp. 34-46
Author(s):  
Farhad Soleimanian Gharehchopoghi ◽  
Freshte Dabaghchi Mokri ◽  
Maryam Molany
Keyword(s):  
Power Systems ◽  
Distribution Systems ◽  
Short Term ◽  
Forecasting Error ◽  
Load Fluctuation ◽  
Distribution Company ◽  
Short Term Forecasting ◽  
West Azerbaijan ◽  
Short Term Prediction

The accuracy of forecasting of electrical load for the electricity industry has a vital significance in the renewal of economic structure as well as various equations including: purchasing and producing energy, load fluctuation, and the development of infrastructures. Its short-term forecasting has a significant role in designing and utilizing power systems and in the distribution systems and having a variety of systems used to maintain security potentials for the system. In this paper, we attempted to carry out a short-term forecasting of electrical distribution company in west Azerbaijan state in Iran's electricity in a few days on the basis of regression multi linear model. This forecasting which was done during a three-day period is and categorized weekdays into three groups including working days, weekends, and holidays was carried out in an hourly manner. This model regardless of parameters like humidity, wind velocity, daylight time, etc. by minimizing the forecasting error managed to maximize the reliability of the results as well as the safety potential of the system. In this model the only influential parameter on the forecasting was the reliance of the forecasting day on previous days. The main purpose of the present study was to maximize the accuracy and reliability of forecasting for certain days (religious holidays, national holidays …). In this paper, the authors managed to decrease the error of forecasting for particular and regular off days to a great extent.

scholarly journals Case Study

2019 ◽  
pp. 85-96
Author(s):  
Maria Jacob ◽  
Cláudia Neves ◽  
Danica Vukadinović Greetham
Keyword(s):  
Chronological Order ◽  
Short Term ◽  
Short Term Forecasting

Abstract In the previous chapter, we looked at load measurements for all households together and we ignored their chronological order. In contrast, in this chapter, we are interested in short term forecasting of household profiles individually. Therefore, information about the time at which measurements were taken becomes relevant.

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