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Development and evaluation of a physically-based lake level model for water resource management: A case study for Lake Buchanan, Texas

Peirong Lin, Zong-Liang Yang, Xitian Cai, Cédric H. David
2015 Journal of Hydrology: Regional Studies  
The presented hindcast results also provide insight into the influences of baseline LSM resolutions, initialization months, and lead times, which would ultimately help improve lake-level forecast skills  ...  By conducting a case study for Lake Buchanan, we demonstrate the capability of the framework in predicting lake levels at seasonal lead times.  ...  Acknowledgements This work is supported by the NASA Interdisciplinary Science Program (award NNX11AJ43G), Microsoft Research and the Jackson School of Geosciences, University of Texas at Austin.  ... 
doi:10.1016/j.ejrh.2015.08.005 fatcat:m7nja6ntdfejpjecr33ysk5faq

Accurate Forecasting of the Satellite-Derived Seasonal Caspian Sea Level Anomaly Using Polynomial Interpolation and Holt-Winters Exponential Smoothing

Moslem Imani, Rey-Jer You, Chung-Yen Kuo
2013 Terrestrial, Atmospheric and Oceanic Sciences  
The modeling results of a 3-year forecasting time span (2005 -2008) derived using HWES agree well with the observed time series with a correlation coefficient of 0.86.  ...  Finally, the 3-year forecasted Caspian Sea level anomalies are compared with those obtained using an artificial neural network method with reasonable agreement found.  ...  An optimal forecasting technique is adopted based on the availability of information and the time scale of the data.  ... 
doi:10.3319/tao.2012.10.12.01(tibxs) fatcat:uy4mhebl5vf65e3tp5ikm4lxbu

Forecasting Reservoir Water Levels Using Deep Neural Networks: A Case Study of Angat Dam in the Philippines

Sebastian C. Ibañez, Carlo Vincienzo G. Dajac, Marissa P. Liponhay, Erika Fille T. Legara, Jon Michael H. Esteban, Christopher P. Monterola
2021 Water  
Forecasting reservoir water levels is essential in water supply management, impacting both operations and intervention strategies.  ...  In summary, we provide a comprehensive framework for evaluating water level forecasting by defining a baseline accuracy, analyzing performance across multiple prediction horizons, using time series cross-validation  ...  Data was obtained from Manila Water Company Inc. and are available from the authors with the permission of Manila Water Inc.  ... 
doi:10.3390/w14010034 fatcat:ubogqty2qvf5tnox73fvdf3kqe

Intercomparison and validation of continental water level products derived from satellite radar altimetry

Martina Ričko
2012 Journal of Applied Remote Sensing  
To explore these differences, particularly with their potential impact on climatebased research, an intercomparison of three web-based water-level products (produced by Laboratoire d'Etudes en Géophysique  ...  Satellite radar altimeter measurements of lake and reservoir water levels complement in situ observations by providing stage information for ungauged basins and by filling data gaps in existing gauge records  ...  over a meter (e.g., narrow reservoirs such as Lake Powell). 3, 4, 41 Dedicated retrackers for smaller lakes and narrow reservoirs may improve the RMS error, but the current error over Lake Powell is  ... 
doi:10.1117/1.jrs.6.063614 fatcat:upsthavuwncy5mnwfhwfkh5vui

Remote Sensing-Derived Water Extent and Level to Constrain Hydraulic Flood Forecasting Models: Opportunities and Challenges

Stefania Grimaldi, Yuan Li, Valentijn R. N. Pauwels, Jeffrey P. Walker
2016 Surveys in geophysics  
Field gauging data of water levels and discharge have traditionally been used for hydraulic model calibration, validation and real-time constraint.  ...  This paper presents a review of the availability of RS observations of flood extent and levels, and their use for calibration, validation and real-time constraint of hydraulic flood forecasting models.  ...  Acknowledgments This study is financially supported by the Bushfires and Natural Hazards CRC project-Improving flood forecast skill using remote sensing data.  ... 
doi:10.1007/s10712-016-9378-y fatcat:rmceq6a5h5a6do6qpyhzo62zve

Intercomparison and validation of continental water level products derived from satellite radar altimetry

Martina Ričko, Charon M. Birkett, James A. Carton, Jean-François Crétaux
2012 Journal of Applied Remote Sensing  
To explore these differences, particularly with their potential impact on climatebased research, an intercomparison of three web-based water-level products (produced by Laboratoire d'Etudes en Géophysique  ...  Satellite radar altimeter measurements of lake and reservoir water levels complement in situ observations by providing stage information for ungauged basins and by filling data gaps in existing gauge records  ...  This work forms part of the dissertation research of MR.  ... 
doi:10.1117/1.jrs.6.061710 fatcat:n5x2to526jerbbudjz7e5qseum

Artificial Intelligence Hybrid Deep Learning Model for Groundwater Level Prediction Using MLP-ADAM [article]

Pejman Zarafshan, Saman Javadi, Abbas Roozbahani, Seyed Mehdi Hashemy, Payam Zarafshan, Hamed Etezadi
2021 arXiv   pre-print
The root mean squared error, mean absolute error, mean squared error and the coefficient of determination ( ) are used to evaluate the accuracy of the simulated groundwater level.  ...  In the fields of hydrological, some researchers applied a neural network to forecast rainfall intensity in space-time and introduced the advantages of neural networks compared to numerical models.  ...  The Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and the coefficient of determination (R 2 ) were used to evaluate the accuracy of the simulated groundwater level  ... 
arXiv:2107.13870v1 fatcat:tc6actw7wbarxpo54cwqyepiqy

Establishment of Landslide Groundwater Level Prediction Model Based on GA-SVM and Influencing Factor Analysis

Cao, Yin, Zhou, Ahmed
2020 Sensors  
The monitoring data indicated that the fluctuation of groundwater level is significantly consistent with rainfall and reservoir level in time, but there is a lag.  ...  We found that the prediction accuracy can be improved by considering the influencing factor.  ...  We also thank the assistance of the Research Center of Geohazard Monitoring and Warning in the Three Gorges Reservoir. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s20030845 pmid:32033307 pmcid:PMC7038680 fatcat:xccc5alv6feczioni4ar2fqixa

Model uncertainty reduction for real-time flood control by means of a flexible data assimilation approach and reduced conceptual models

E. Vermuyten, P. Meert, V. Wolfs, P. Willems
2018 Journal of Hydrology  
Prediction errors originating from hydrodynamic model mismatches, however, result in a deterioration of the real-time control performance.  ...  algorithm (RGA-MPC) has shown to be an efficient control technique for real-time flood control, making use of fast conceptual river models.  ...  The authors would like to thank Innovyze for the InfoWorks RS software license, and the Flemish Environment Agency (VMM) for the data and InfoWorks RS model of the Herk river.  ... 
doi:10.1016/j.jhydrol.2018.07.033 fatcat:5ygxkj2tv5ay5grtkgsrqi2g4q

Climatic Effects on Lake Basins. Part I: Modeling Tropical Lake Levels

Martina Ricko, James A. Carton, Charon Birkett
2011 Journal of Climate  
This study examines the capability of a simple basin model to estimate variations in water level for 12 tropical lakes and reservoirs during a 16-yr remotely sensed observation period (1992)(1993)(1994  ...  But for most of the records any of the rainfall products provide reasonable lake level estimates, a result which opens up the possibility of using rainfall to create seasonal forecasts of future lake levels  ...  However, improvements in processing techniques have dramatically improved the accuracy of this data (Birkett 1995) , and the availability of multiple satellites in different orbits has increased the number  ... 
doi:10.1175/2010jcli3602.1 fatcat:jggs36kchfhj7px26myxogzr2u

Quantifying the Risks that Propagate from the Inflow Forecast Uncertainty to the Reservoir Operations with Coupled Flood and Electricity Curtailment Risks

Qiumei Ma, Jiaxin Zhang, Bin Xiong, Yanke Zhang, Changming Ji, Ting Zhou
2021 Water  
The results indicated that the IGMD-based MCMC was capable of deriving robust ensemble forecasts.  ...  First, to incorporate the IFU, an improved Gaussian mixture distribution (IGMD) and Markov chain Monte Carlo (MCMC) algorithm were constructed to model the measured forecast errors and generate ensemble  ...  We also thank the anonymous reviewers for their constructive comments that helped improve the quality of this manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w13020173 fatcat:tzarfftrfvdjdamb6rs5ol2evm

Could electrical conductivity replace water level in rating curves for alpine streams?

Steven V. Weijs, Raphaël Mutzner, Marc B. Parlange
2013 Water Resources Research  
Analysis of the residuals of both predictive relations revealed errors in the gauged streamflows. These could be corrected by filtering disinformation from erroneous calibration coefficients.  ...  1] Streamflow time series are important for inference and understanding of the hydrological processes in alpine watersheds.  ...  Steven Weijs is a beneficiary of a postdoctoral fellowship from the AXA research fund, which is gratefully acknowledged.  ... 
doi:10.1029/2012wr012181 fatcat:eo4d5vwwgraczlqmbjlrgenbpy

A machine learning-based model to estimate PM2.5 concentration levels in Delhi's atmosphere

Saurabh Kumar, Shweta Mishra, Sunil Kumar Singh
2020 Heliyon  
This work aims to forecast the PM2.5 concentration levels in various regions of Delhi on an hourly basis, by applying time series analysis and regression, based on various atmospheric and surface factors  ...  A good model, to forecast the concentration level of these dissolved particles, may help to prepare the residents with better prevention and safety strategies in order to save them from many health-related  ...  Acknowledgements Authors would like to acknowledge the editors and the anonymous reviewers for their valuable suggestions in order to improve the manuscript.  ... 
doi:10.1016/j.heliyon.2020.e05618 pmid:33305040 pmcid:PMC7710640 fatcat:2ohe6fek4nh65az2f2airc56zy

A Novel Flood Forecasting Method Based on Initial State Variable Correction

Kuang Li, Guangyuan Kan, Liuqian Ding, Qianjin Dong, Kexin Liu, Lili Liang
2017 Water  
The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial  ...  The study results show that the ISVC is effective and applicable in flood forecasting tasks. It can significantly improve the flood forecasting accuracy in most cases.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w10010012 fatcat:cl3yayd6tfglji72uqoqzvxfrq

Utility of geospatial techniques in estimating dam water levels: insights from the Katrivier Dam

Sisipho Ngebe, Kasongo Benjamin Malunda, Anja du Plessis
2022 Water S.A  
The resulting water level values were derived using a proposed model that includes two correction factors, k and s.  ...  This study was consequently focused on the estimation of water levels with the use of geospatial techniques.  ...  In addition, acknowledgments are extended to the Department of Water and Sanitation for providing us with water level data of the Katrivier Dam, and the Copernicus data centre for the Sentinel-2 data used  ... 
doi:10.17159/wsa/2022.v48.i2.3890 fatcat:skacgqt47jfmdgn3jwubatzhhy
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