Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
The Auto-Tuned Land Data Assimilation System ( ATLAS)
Date
2014-01-01
Author
Crow, W. T.
Yılmaz, Mustafa Tuğrul
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
201
views
0
downloads
Cite This
Land data assimilation systems are commonly tasked with merging remotely sensed surface soil moisture retrievals with information derived from a soil water balance model driven by observed rainfall. The performance of such systems can be degraded by the incorrect specification of parameters describing modeling and observation errors. Here the Auto-Tuned Land Data Assimilation System (ATLAS) is introduced to simultaneously solve for all parameters required for the application of a simple land data assimilation system to integrate satellite-based rainfall and soil moisture retrievals for drought monitoring applications. The approach is based on combining a triple collocation (TC) strategy with the statistical analysis of filtering innovations and designed to leverage the simultaneous availability of satellite-based soil moisture products acquired from both active and passive microwave remote sensing. A number of variants of the ATLAS approacheach based on a different strategy for leveraging TC and innovation analysis within an adaptive filtering frameworkare derived and evaluated through a synthetic twin experiment. In addition, a preliminary real data analysis is conducted using actual satellite-based products and evaluated against independent ground-based observations. Results illustrate the potential of ATLAS to improve the analysis of soil moisture anomalies using data products derived from the Global Precipitation Measurement (GPM) and the NASA Soil Moisture Active/Passive missions.
Subject Keywords
Water Science and Technology
URI
https://hdl.handle.net/11511/35118
Journal
WATER RESOURCES RESEARCH
DOI
https://doi.org/10.1002/2013wr014550
Collections
Department of Civil Engineering, Article
Suggestions
OpenMETU
Core
A process-based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model
Yılmaz, Koray Kamil; Wagener, Thorsten (American Geophysical Union (AGU), 2008-09-11)
Distributed hydrological models have the potential to provide improved streamflow forecasts along the entire channel network, while also simulating the spatial dynamics of evapotranspiration, soil moisture content, water quality, soil erosion, and land use change impacts. However, they are perceived as being difficult to parameterize and evaluate, thus translating into significant predictive uncertainty in the model results. Although a priori parameter estimates derived from observable watershed characteris...
Point-scale energy and mass balance snowpack simulations in the upper Karasu basin, Turkey
Sensoy, A; Sorman, AA; Tekeli, AE; Sorman, AU; Garen, DC (Wiley, 2006-03-15)
Since snowmelt runoff is important in the mountainous parts of the world, substantial efforts have been made to develop snowmelt models with many different levels of complexity to simulate the processes at the ground (soil-vegetation), within the snow, and at the interface with the atmosphere. Snow modifies the exchange of energy between the land surface and atmosphere and significantly affects the distribution of heating in the atmosphere by changing the surface albedo and regulating turbulent heat and mom...
Oil mound spreading and migration with ambient groundwater flow in coarse porous media
Corapcioglu, MY; Tuncay, Kağan; Ceylan, BK (American Geophysical Union (AGU), 1996-05-01)
When a light, immiscible oil leaks above an unconfined aquifer, it spreads and forms a floating mound on the water table. The oil mound migrates in the direction of ambient groundwater how. In this study we present a governing equation for the migrating mound thickness by averaging the oil phase mass balance equation. Analytical and numerical solutions to an advective-dispersive type equation are presented to estimate the temporal and spatial distribution of the migrating oil mound thickness for two problem...
Toward predicting climate change effects on lakes: a comparison of 1656 shallow lakes from Florida and Denmark reveals substantial differences in nutrient dynamics, metabolism, trophic structure, and top-down control
Jeppesen, Erik; Canfield, Daniel E.; Bachmann, Roger W.; Sondergaard, Martin; Havens, Karl E.; Johansson, Liselotte S.; Lauridsen, Torben L.; Tserenpil, Sh; Rutter, Robert P.; Warren, Gary; Ji, Gaohua; Hoyer, Mark (Informa UK Limited, 2020-04-01)
Rapid climate changes may potentially have strong impacts on the ecosystem structure and nutrient dynamics of lakes as well as implications for water quality. We used a space-for-time approach to elucidate such possible effects by comparing data from 1656 shallow lakes (mean depth 100 mu g L-1) in the FL lakes, but coverage was higher in the DK lakes at low TP. We also found lower oxygen saturation in the nutrient-rich FL lakes than in the DK lakes, suggesting lower net ecosystem production in the FL lakes....
Multiple-criteria calibration of a distributed watershed model using spatial regularization and response signatures
Pokhrel, Prafulla; Yılmaz, Koray Kamil; Gupta, Hoshin V. (Elsevier BV, 2012-02-08)
This paper explores the use of a semi-automated multiple-criteria calibration approach for estimating the parameters of the spatially distributed HL-DHM model to the Blue River basin, Oklahoma. The study was performed in the context of Phase 2 of the DMIP project organized by the Hydrology Lab of the NWS. To deal with the problem of ill conditioning, we employ a regularization approach that constrains the search space using information contained in a priori estimates of the spatially distributed parameter f...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
W. T. Crow and M. T. Yılmaz, “The Auto-Tuned Land Data Assimilation System ( ATLAS),”
WATER RESOURCES RESEARCH
, pp. 371–385, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35118.