Results 41 to 50 of about 412,263 (413)
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale [PDF]
Advances in Water Resources 136 (2020) 103470, 2019 Predictive hydrological uncertainty can be quantified by using ensemble methods. If properly formulated, these methods can offer improved predictive performance by combining multiple predictions. In this work, we use 50-year-long monthly time series observed in 270 catchments in the United States to explore the performances provided by an ensemble ...
arxiv +1 more source
Statistical post-processing of hydrological forecasts using Bayesian model averaging [PDF]
Water Resources Research 55 (2019), no. 5, 3997-4013, 2018 Accurate and reliable probabilistic forecasts of hydrological quantities like runoff or water level are beneficial to various areas of society. Probabilistic state-of-the-art hydrological ensemble prediction models are usually driven with meteorological ensemble forecasts. Hence, biases and dispersion errors of the meteorological forecasts cascade down
arxiv +1 more source
Hillslope Hydrology in Global Change Research and Earth System Modeling
Water Resources Research, 2019 Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at ...
Ying Fan +37 more
semanticscholar +1 more source
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models [PDF]
Advances in Water Resources 136 (2020) 103471, 2019 We introduce an ensemble learning post-processing methodology for probabilistic hydrological modelling. This methodology generates numerous point predictions by applying a single hydrological model, yet with different parameter values drawn from the respective simulated posterior distribution. We call these predictions "sister predictions". Each sister
arxiv +1 more source
Geodesy and Geodynamics, 2015 We use the average crustal structure of the CRUST1.0 model for the Tibetan Plateau to establish a realistic earth model termed as TC1P, and data from the Global Land Data Assimilation System (GLDAS) hydrology model and Gravity Recovery and Climate ...
Hansheng Wang +6 more
doaj +1 more source
The future of flood hydrology in the UK
Hydrology Research, 2022 A ‘roadmap’ for the future of UK flood hydrology over the next 25 years has been published, based on a wide-ranging and inclusive co-creation process involving more than 270 individuals and 50 organisations from different sectors and disciplines.
Rob Lamb +10 more
doaj +1 more source
, 2020 • Gained extensive experience on ecohydrologic modeling of dryland ecosystems • Modeling was influenced by the disciplines of hydrology, hydraulics, and savanna ecology • Worked on a field team to collect novel soil moisture measurements with near ...
Muhammad Ashraf
semanticscholar +1 more source
The Lake Chad hydrology under current climate change
Scientific Reports, 2020 Lake Chad, in the Sahelian zone of west-central Africa, provides food and water to ~50 million people and supports unique ecosystems and biodiversity. In the past decades, it became a symbol of current climate change, held up by its dramatic shrinkage in
Binh Pham-Duc +5 more
semanticscholar +1 more source
The hydrology of the Mississippi [PDF]
American Journal of Science, 1896 n ...
openaire +2 more sources