Development and Application of a Three-Dimensional Integrated Hydrologic Model of East-Central Palm Beach County, Florida

2001 ◽  
Author(s):  
Brian L. Roy ◽  
Lee P. Wiseman ◽  
Kimberly M. McCue
Keyword(s):  
Three Dimensional ◽  
Hydrologic Model ◽  
Palm Beach County ◽  
East Central ◽  
Integrated Hydrologic Model

scholarly journals Development of a Deep Learning Emulator for a Distributed Groundwater–Surface Water Model: ParFlow-ML

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3393
Author(s):  
Hoang Tran ◽  
Elena Leonarduzzi ◽  
Luis De la Fuente ◽  
Robert Bruce Hull ◽  
Vineet Bansal ◽  
...  
Keyword(s):  
Deep Learning ◽  
Water Table ◽  
Overland Flow ◽  
Three Dimensional ◽  
Pressure Head ◽  
Hydrologic Model ◽  
Water Table Depth ◽  
Water Model ◽  
Physical Parameters ◽  
Integrated Hydrologic Model

Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine leaning (ML) and deep learning (DL) in particular could be used to emulate complex physical processes in the earth system. In this study, we demonstrate how a DL model can emulate transient, three-dimensional integrated hydrologic model simulations at a fraction of the computational expense. This emulator is based on a DL model previously used for modeling video dynamics, PredRNN. The emulator is trained based on physical parameters used in the original model, inputs such as hydraulic conductivity and topography, and produces spatially distributed outputs (e.g., pressure head) from which quantities such as streamflow and water table depth can be calculated. Simulation results from the emulator and ParFlow agree well with average relative biases of 0.070, 0.092, and 0.032 for streamflow, water table depth, and total water storage, respectively. Moreover, the emulator is up to 42 times faster than ParFlow. Given this promising proof of concept, our results open the door to future applications of full hydrologic model emulation, particularly at larger scales.

scholarly journals Improving Hydrologic Modeling Using Cloud-Free MODIS Flood Maps

2019 ◽  
Vol 20 (11) ◽  
pp. 2203-2214 ◽  
Author(s):  
Hoang Tran ◽  
Phu Nguyen ◽  
Mohammed Ombadi ◽  
Kuolin Hsu ◽  
Soroosh Sorooshian ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Large Scale ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Skill Score ◽  
Hydrologic Model ◽  
Probability Of Detection ◽  
Landsat 8 ◽  
Inundation Maps ◽  
Flood Maps

Abstract Flood mapping from satellites provides large-scale observations of flood events, but cloud obstruction in satellite optical sensors limits its practical usability. In this study, we implemented the Variational Interpolation (VI) algorithm to remove clouds from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area (SCA) products. The VI algorithm estimated states of cloud-hindered pixels by constructing three-dimensional space–time surfaces based on assumptions of snow persistence. The resulting cloud-free flood maps, while maintaining the temporal resolution of the original MODIS product, showed an improvement of nearly 70% in average probability of detection (POD) (from 0.29 to 0.49) when validated with flood maps derived from Landsat-8 imagery. The second part of this study utilized the cloud-free flood maps for calibration of a hydrologic model to improve simulation of flood inundation maps. The results demonstrated the utility of the cloud-free maps, as simulated inundation maps had average POD, false alarm ratio (FAR), and Hanssen–Kuipers (HK) skill score of 0.87, 0.49, and 0.84, respectively, compared to POD, FAR, and HK of 0.70, 0.61, and 0.67 when original maps were used for calibration.

scholarly journals Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model

2020 ◽  
Vol 580 ◽  
pp. 124358 ◽  
Author(s):  
Fadji Z. Maina ◽  
Erica R. Siirila-Woodburn ◽  
Michelle Newcomer ◽  
Zexuan Xu ◽  
Carl Steefel
Keyword(s):  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

scholarly journals Assessing the impact of model spin-up on surface water-groundwater interactions using an integrated hydrologic model

2014 ◽  
Vol 50 (3) ◽  
pp. 2636-2656 ◽  
Author(s):  
Hoori Ajami ◽  
Matthew F. McCabe ◽  
Jason P. Evans ◽  
Simon Stisen
Keyword(s):  
Surface Water ◽  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

Some results of COCORP seismic reflection profiling in the Grenville-age Adirondack Mountains, New York State

1985 ◽  
Vol 22 (2) ◽  
pp. 141-153 ◽  
Author(s):  
S. L. Klemperer ◽  
L. D. Brown ◽  
J. E. Oliver ◽  
C. J. Ando ◽  
B. L. Czuchra ◽  
...  
Keyword(s):  
New York ◽  
Lower Crust ◽  
Seismic Reflection ◽  
New York State ◽  
Three Dimensional ◽  
Upper Crust ◽  
Adirondack Mountains ◽  
East Central ◽  
York State ◽  
Seismic Reflection Profiling

COCORP deep seismic reflection profiling in the Adirondack Mountains of northern New York State has revealed a prominent zone of layered reflectors in the lower crust of the east-central Adirondacks. The strong, layered reflectors (here termed the Tahawus complex) occur between 18 and 26 km depth, beneath the sparsely reflective, granulite-grade, surface terrane, which has been uplifted from depths greater than 20 km. The Tahawus complex apparently represents layered rocks of some type in the lower crust of the Adirondacks. Possibilities include gneissic layering, cumulate igneous layering, a layered sill complex, and underthrust sedimentary strata, The Tahawus complex may be spatially coincident with a previously detected, high-conductivity zone in the lower crust, suggesting that either unusual mineralogies or interstitial electrolytes are present in the Tahawus complex. In contrast to layered reflections discovered in the lower crust of the east-central Adirondacks and southeast of the Adirondacks, cross-cutting and discontinuous reflections are recorded from the upper crust on all the COCORP Adirondack lines, including lines in both the Adirondack Highlands and Lowlands. Available three-dimensional control suggests that reflections in the upper crust of the central Adirondacks are parallel to, and hence may be related to, the folded gneisses mapped at the surface. Shallow events are also observed on a COCORP profile close to the epicenter of the 7 October 1983 magnitude 5.2 earthquake in the central Adirondacks, but their relation to the earthquake is uncertain.

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