Filters








15,361 Hits in 4.1 sec

Joint Spatial and Temporal Modeling for Hydrological Prediction

Qun Zhao, Yuelong Zhu, Kai Shu, Dingsheng Wan, Yufeng Yu, Xudong Zhou, Huan Liu
2020 IEEE Access  
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

P.C. Kyriakidis, N.L. Miller, J. Kim
2004 Journal of Hydrology  
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

Manuela I. Brunner, Louise Slater, Lena M. Tallaksen, Martyn Clark
2021 WIREs Water  
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

Søren Thorndahl, Thomas Einfalt, Patrick Willems, Jesper Ellerbæk Nielsen, Marie-Claire ten Veldhuis, Karsten Arnbjerg-Nielsen, Michael R. Rasmussen, Peter Molnar
2017 Hydrology and Earth System Sciences  
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

Emmanouil A. Varouchakis, Dionissios T. Hristopulos, George P. Karatzas, Gerald A. Corzo Perez, Vitali Diaz
2021 Hydrology Research  
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  
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]

Lingjie Li, Yongwei Gai, Leizhi Wang, Liping Li, Xiaotian Li, Rongjin Zhu
2021 Advances in Transdisciplinary Engineering  
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

Christopher E. Ndehedehe, Vagner G. Ferreira
2019 Journal of Hydrology  
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

S.A Wooldridge, J.D Kalma, J.P Walker
2003 Environmental Modelling & Software  
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

Søren Thorndahl, Thomas Einfalt, Patrick Willems, Jesper Ellerbæk Nielsen, Marie-Claire ten Veldhuis, Karsten Arnbjerg-Nielsen, Michael R. Rasmussen, Peter Molnar
2016 Hydrology and Earth System Sciences Discussions  
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

Ebrahim Ahmadisharaf, Alfred J. Kalyanapu, Paul D. Bates
2018 Hydrological Sciences Journal  
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

Henry Lin, Johan Bouma, Yakov Pachepsky, Andrew Western, James Thompson, Rien van Genuchten, Hans-Jörg Vogel, Allan Lilly
2006 Water Resources Research  
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

H. Vereecken, J. A. Huisman, H. J. Hendricks Franssen, N. Brüggemann, H. R. Bogena, S. Kollet, M. Javaux, J. van der Kruk, J. Vanderborght
2015 Water Resources Research  
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  
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

M. Bordoni, V. Vivaldi, L. Lucchelli, L. Ciabatta, L. Brocca, J. P. Galve, C. Meisina
2020 Landslides. Journal of the International Consortium on Landslides  
) 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
« Previous Showing results 1 — 15 out of 15,361 results