Development and Operational Testing of a Super-Ensemble Artificial Intelligence Flood-Forecast Model for a Pacific Northwest River

2014 ◽  
Vol 51 (2) ◽  
pp. 502-512 ◽  
Author(s):  
Sean W. Fleming ◽  
Dominique R. Bourdin ◽  
Dave Campbell ◽  
Roland B. Stull ◽  
Tobi Gardner
2010 ◽  
Vol 39 ◽  
pp. 555-561 ◽  
Author(s):  
Qing Hua Luan ◽  
Yao Cheng ◽  
Zha Xin Ima

The establishing of a precise simulation model for runoff prediction in river with several tributaries is the difficulty of flood forecast, which is also one of the difficulties in hydrologic research. Due to the theory of Artificial Neural Network, using Back Propagation algorithm, the flood forecast model for ShiLiAn hydrologic station in Minjiang River is constructed and validated in this study. Through test, the result shows that the forecast accuracy is satisfied for all check standards of flood forecast and then proves the feasibility of using nonlinear method for flood forecast. This study provides a new method and reference for flood control and water resources management in the local region.


Author(s):  
Дмитрий Александрович Коростелев ◽  
Dmitriy Aleksandrovich Korostelev ◽  
Алексей Радченко ◽  
Aleksey Radchenko ◽  
Никита Сильченко ◽  
...  

The paper describes the solution to the problem of testing the efficiency of new ideas and algorithms for intelligent systems. Simulation of interaction of the corresponding intelligent agents in a competitive form implementing different algorithms is proposed to use as the main approach to the solution. To support this simulation, a specialized software platform is used. The paper describes the platform developed for running competitions in artificial intelligence and its subsystems: a server, a client and visualization. Operational testing of the developed system is also described which helps to evaluate the efficiency of various algorithms of artificial intelligence in relation to the simulation like "Naval Battle".


2020 ◽  
Vol 51 (6) ◽  
pp. 1312-1331
Author(s):  
Qian Li ◽  
Caisong Li ◽  
Huanfei Yu ◽  
Jinglin Qian ◽  
Linlin Hu ◽  
...  

Abstract Multiple factors including rainfall and underlying surface conditions make river basin real-time flood forecasting very challenging. It is often necessary to use real-time correction techniques to modify the forecasting results so that they reach satisfactory accuracy. There are many such techniques in use today; however, they tend to have weak physical conceptual basis, relatively short forecast periods, unsatisfactory correction effects, and other problems. The mechanism that affects real-time flood forecasting error is very complicated. The strongest influencing factors corresponding to this mechanism affect the runoff yield of the forecast model. This paper proposes a feedback correction algorithm that traces back to the source of information, namely, modifies the watershed runoff. The runoff yield error is investigated using the principle of least squares estimation. A unit hydrograph is introduced into the real-time flood forecast correction; a feedback correction model that traces back to the source of information. The model is established and verified by comparison with an ideal model. The correction effects of the runoff yield errors are also compared in different ranges. The proposed method shows stronger correction effect and enhanced prediction accuracy than the traditional method. It is also simple in structure and has a clear physical concept without requiring added parameters or forecast period truncation. It is readily applicable in actual river basin flood forecasting scenarios.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Mohammed Moishin ◽  
Ravinesh C. Deo ◽  
Ramendra Prasad ◽  
Nawin Raj ◽  
Shahab Abdulla

2009 ◽  
Vol 9 (6) ◽  
pp. 27063-27098
Author(s):  
F. L. Herron-Thorpe ◽  
J. K. Vaughan ◽  
B. K. Lamb ◽  
G. H. Mount

Abstract. Results from a regional air quality forecast model, AIRPACT-3, are compared to OMI tropospheric NO2 integrated column densities for an 18 month period over the Pacific Northwest. AIRPACT column densities were well correlated with cloud-free monthly averages of tropospheric NO2 (R=0.75) to NASA retrievals for months without wildfires, but were poorly correlated with significant model overpredictions (R=0.21) for months with wildfires when OMI and AIRPACT were compared over the entire domain. AIRPACT forecasted higher NO2 in some US urban areas, and lower NO2 in many Canadian urban areas, when compared to OMI. There are significant changes in results after spatially averaging model results to the daily OMI swath. Also, it is shown that applying the averaging kernel to model results in cloudy conditions has a large effect, but applying the averaging kernel in cloud free conditions has little effect. The KNMI and NASA retrievals of tropospheric NO2 from OMI (collection 3) are compared. The NASA product is shown to be significantly different than the KNMI tropospheric NO2 product, i.e. July 2007 (R=0.60) and January 2008 (R=0.69).


2012 ◽  
Vol 12 (12) ◽  
pp. 5603-5615 ◽  
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
S. H. Chung ◽  
...  

Abstract. Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R > 0.9) but were significantly biased (~25%) with consistent under-predictions for spring months when there is significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ± 10 ppb but not found to significantly affect peak ozone surface concentrations.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 312
Author(s):  
Robert Cifelli ◽  
Lynn E. Johnson ◽  
Jungho Kim ◽  
Tim Coleman ◽  
Greg Pratt ◽  
...  

Compound flooding, resulting from a combination of riverine and coastal processes, is a complex but important hazard to resolve along urbanized shorelines in the vicinity of river mouths. However, inland flooding models rarely consider oceanographic conditions, and vice versa for coastal flood models. Here, we describe the development of an operational, integrated coastal-watershed flooding model to address this issue of compound flooding in a highly urbanized estuarine environment, San Francisco Bay (CA, USA), where the surrounding communities are susceptible to flooding along the bay shoreline and inland rivers and creeks that drain to the bay. The integrated tributary-coastal forecast model (Hydro-Coastal Storm Modeling System, or Hydro-CoSMoS) was developed to provide water managers and other users with flood forecast information beyond what is currently available. Results presented here are focused on the interaction of the Napa River watershed and the San Pablo Bay at the northern end of San Francisco Bay. This paper describes the modeling setup, the scenario used in a tabletop exercise (TTE), and the assessment of the various flood forecast information products. Hydro-CoSMoS successfully demonstrated the capability to provide watershed and coastal flood information at scales and locations where no such information is currently available and was also successful in showing how tributary flows could be used to inform the coastal storm model during a flooding scenario. The TTE provided valuable feedback on how to guide continued model development and to inform what model outputs and formats are most useful to end-users.


2012 ◽  
Vol 12 (2) ◽  
pp. 3695-3730
Author(s):  
F. L. Herron-Thorpe ◽  
G. H. Mount ◽  
L. K. Emmons ◽  
B. K. Lamb ◽  
S. H. Chung ◽  
...  

Abstract. Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R>0.9) but were significantly biased (~25 %) with significant under-predictions for spring months with significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ±10 ppb but not found to significantly affect peak ozone surface concentrations.


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