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Joint Spatial and Temporal Modeling for Hydrological Prediction
2020
IEEE Access
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INDEX TERMS Hydrologic prediction, spatial and temporal modeling, graph convolutional networks. ...
In this paper, we study a novel problem of exploiting both temporal patterns and spatial connections for hydrological prediction. ...
This model is built on the skeleton map sequence and each node corresponds to a joint of the human body. There are two sides, one is the spatial edge, the other is the temporal edge. ...
doi:10.1109/access.2020.2990181
fatcat:4uum33izfjbqfjqu7gjzxnygvu
A spatial time series framework for simulating daily precipitation at regional scales
2004
Journal of Hydrology
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This task calls for the joint spatial prediction of intercept bo and slope bl coefficients at any location u the study domain D. ...
Simple cokriging was used for the joint spatial prediction of the resulting regression residuals ro and 11, see Section 2.2 and equations (9) through (10). ...
doi:10.1016/j.jhydrol.2004.04.022
fatcat:oytfesv7frbajaubgw57cpsg7i
Challenges in modeling and predicting floods and droughts: A review
2021
WIREs Water
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Modeling challenges arise in frequency analysis, stochastic, hydrological, earth system, and hydraulic modeling. ...
We group challenges related to flood and drought prediction into four interrelated categories: data, process understanding, modeling and prediction, and human-water interactions. ...
Study droughts and floods in a joint framework: To understand temporal transitions between droughts and floods, the two phenomena must be studied in a joint framework, for example, using continuous instead ...
doi:10.1002/wat2.1520
fatcat:wg5nmeo36feehebxbwjwheeiom
Weather radar rainfall data in urban hydrology
2017
Hydrology and Earth System Sciences
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Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) ...
Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications ...
Thorndahl acknowledges Damian Murla Tuyls from the Department of Civil Engineering, Aalborg University, for constructive ideas and proofreading as well as David Getreuer Jensen, Envidan A/S, for contributions ...
doi:10.5194/hess-21-1359-2017
fatcat:wllz6566mjaczg62jxkzikcvye
Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations
2021
Hydrology Research
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Precipitation data are useful for the management of water resources as well as flood and drought events. ...
Subsequently, the spatial variability of the precipitation distribution is frequently represented incorrectly. Satellite precipitation data provide an attractive supplement to ground observations. ...
The optimal sum-metric spacetime model is composed of a spatial Matérn model (14) , a temporal spherical model (15) , and a joint Exponential model (16). ...
doi:10.2166/nh.2021.160
fatcat:4wezf22gybb47fztx5m4qq5bsy
Hydrogeology
[chapter]
2017
Encyclopedia of GIS
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Am Stat 64(4):325-334 Huang H-C, Cressie N (1996) Spatio-temporal prediction of snow water equivalent using the Kalman filter. ...
Biometrika 86(4):815-829 Wikle CK, Hooten MB (2006) Hierarchical Bayesian spatio-temporal models for population spread. ...
Cross-References Autocorrelation, Spatial Data Analysis, Spatial Hierarchical Spatial Models Semivariogram Modeling Uncertainty, Modeling with Spatial and Temporal ...
doi:10.1007/978-3-319-17885-1_100563
fatcat:pc6ao5iuwjeh3mopiapeokmkq4
Research Progress on Precipitation Accuracy Verification and Statistical Post-Processing in Ensemble Numerical Forecast System
[chapter]
2021
Advances in Transdisciplinary Engineering
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The temporal and spatial accuracy of precipitation of ensemble numerical forecast systems is an important factor that affects the level of meteorological and hydrological coupled forecasting. ...
Some mainstream statistical post-processing methods have strong performance of spatial downscaling and error correction, but they commonly have the defect of destroying the temporal and spatial dependent ...
the spatial scale of the hydrological forecast model. ...
doi:10.3233/atde210209
fatcat:xemzzieqmvckbd6hdxx6wmjlre
Assessing land water storage dynamics over South America
2019
Journal of Hydrology
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Based on the Bartlett's statistics, significant independent patterns of SST (Sea Surface Temperature) anomalies from the Pacific and Atlantic oceans were used in the PLSR scheme to model the temporal evolutions ...
The underlying uncertainties in the prediction of freshwater evolutions in some regions can be induced by several unmitigated human actions, multi-scale climatic drivers, and dynamic physical processes ...
Acknowledgments The authors are grateful to NASA and NOAA for all the data used in this study. ...
doi:10.1016/j.jhydrol.2019.124339
fatcat:bydokqmbafewdgfnmy7lugiqti
Importance of soil moisture measurements for inferring parameters in hydrologic models of low-yielding ephemeral catchments
2003
Environmental Modelling & Software
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Low-yielding catchments with ephemeral streams provide a stern test of the capability of conceptual catchment models for predicting the hydrologic response of the natural landscape. ...
Future research efforts are discussed in terms of establishing the appropriate spatial and temporal resolution of soil moisture measurements needed to extend the results observed for this small experimental ...
A grateful acknowledgement is also made to George Kuczera for his insightful comments and assistance with the parameter-fitting package nlfit (Kuczera, 1994) . ...
doi:10.1016/s1364-8152(02)00038-5
fatcat:4jmxtfq65ne5ddtlypt6bll5wi
Weather radar rainfall data in urban hydrology
2016
Hydrology and Earth System Sciences Discussions
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spatial resolution of rainfall data required for different hydrological applications, 2) Rainfall estimation, radar data adjustment and data quality, and 3) Nowcasting of radar rainfall and real-time ...
Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology, necessitate an updated review of the state of the art in radar rainfall for urban hydrological ...
20
Impacts of temporal and spatial resolution of radar data in hydrological modelling In the literature, the impact of spatial and temporal radar data resolution on hydrological model response have been ...
doi:10.5194/hess-2016-517
fatcat:2dwx5f7axbhy5ptx6lorolfmzy
A probabilistic framework for floodplain mapping using hydrologic modeling and unsteady hydraulic modeling
2018
Hydrological Sciences Journal
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Given its flexibility, the framework can be applied to study other sources of uncertainty in hydrologic models and other watersheds. ...
Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have largely been based on a joint flood frequency-shape analysis, with only a very limited number of ...
We also appreciate Mahmud Bhuyian and Tigstu Dullo for their technical assistance with the hydraulic model. ...
doi:10.1080/02626667.2018.1525615
fatcat:2lxefjgliffqhejhvjnqaabufe
Hydropedology: Synergistic integration of pedology and hydrology
2006
Water Resources Research
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It is our hope that by working together, hydrologists and pedologists, along with scientists in related disciplines, can better guide data acquisition, knowledge integration, and model-based prediction ...
This paper presents a vision that advocates hydropedology as an advantageous integration of pedology and hydrology for studying the intimate relationships between soil, landscape, and hydrology. ...
Funding provided by the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. ...
doi:10.1029/2005wr004085
fatcat:nnke2pyuqbbbfpahicm7lz6pz4
Soil hydrology: Recent methodological advances, challenges, and perspectives
2015
Water Resources Research
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catchment scale, and to provide data for the development and validation of models. ...
Finally, we discuss recent developments in data assimilation methods, which provide new opportunities to better integrate observations and models and to improve predictions of the short-term evolution ...
Hypothesis-driven soil hydrology needs access to high-quality data with the best possible temporal and spatial resolution to falsify hypotheses. ...
doi:10.1002/2014wr016852
fatcat:46bfehgtqzegnijvqkbwr3naei
Page 278 of Hydrological Processes Vol. 12, Issue 2
[page]
1998
Hydrological Processes
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Using multitemporal images
Though winter 1992 was especially rich with respect to markedly different hydrological conditions, the saturated area extent could not be predicted for each image, with the notable ...
Predictions of saturated areas from TOPMODEL are indeed expected to be in error owing to the spatially variable lateral transmissivity of the soils on one hand and to the hydraulic structures of the catchment ...
Development of a data-driven model for spatial and temporal shallow landslide probability of occurrence at catchment scale
2020
Landslides. Journal of the International Consortium on Landslides
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) and the temporal one. ...
The model, developed through a data-driven approach basing on Multivariate Adaptive Regression Splines technique, was based on a joint probability between the spatial probability of occurrence (susceptibility ...
Combination between spatial and temporal probability of occurrence of shallow landslides: Dynamic Landslide Probability Index Spatio-temporal probability of occurrence is usually obtained through a joint ...
doi:10.1007/s10346-020-01592-3
fatcat:uarcnituyfh6tjwul6g3icacpq
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