Water level forecasting
نویسندگان
چکیده
Water level forecasting through fuzzy logic and artificial neural network approaches S. Alvisi, G. Mascellani, M. Franchini, and A. Bárdossy Dipartimento di Ingegneria, Università degli Studi di Ferrara, Italia Institut für Wasserbau, Universität Stuttgart, Deutschland Received: 29 May 2005 – Accepted: 13 June 2005 – Published: 22 June 2005 Correspondence to: S. Alvisi ([email protected]) © 2005 Author(s). This work is licensed under a Creative Commons License.
منابع مشابه
Groundwater Level Forecasting Using Wavelet and Kriging
In this research, a hybrid wavelet-artificial neural network (WANN) and a geostatistical method were proposed for spatiotemporal prediction of the groundwater level (GWL) for one month ahead. For this purpose, monthly observed time series of GWL were collected from September 2005 to April 2014 in 10 piezometers around Mashhad City in the Northeast of Iran. In temporal forecasting, an artificial...
متن کاملForecasting of Groundwater Table and Water Budget under Different Drought Scenarios using MODFLOW Model (Case Study: Garbaygan Plain, Fars Province, Iran)
Groundwater drought is a natural hazard that develops when groundwater systems are affected by climatical drought, when climatical drought occures, first groundwater recharge, later groundwater levels and groundwater discharge decrease. The origin of drought is a deficit in precipitation and that takes place in all the elements that comprise the hydrological cycle (flow in the rivers, soil mois...
متن کاملForecasting Water Level at a Tidal River by the Nearest-Neighbor Method
The Barato River joins the Ishikari River near the river mouth. That river basin is sometimes in danger of flood because it is low, flat and tidal area around the tributaries influenced by the backwater of the Ishikari River. Therefore the gate is provided at the confluence of Ishikari River to avoid counter flow. Flood forecasting is necessary to determine the gate operation and disaster preve...
متن کاملIntelligent Decision Support Model Based on Neural Network to Support Reservoir Water Release Decision
Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. Th...
متن کاملA Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated...
متن کاملMobile ortsbasierte Messung von Wasserständen zur Verbesserung der Hochwasservorhersage in kleinen Einzugsgebieten (Mobile Crowd Sensing of Water Level to Improve Flood Forecasting in Small Drainage Areas)
Flood forecasting is particularly difficult and uncertain for small drainage basins. One reason for that is the absence of adequate temporal and spatial hydrological input variables for model-based flood predictions. Incorporating additional information collected by volunteers with the help of their smartphones can improve flood forecasting systems. Data collected in this way is often referred ...
متن کامل