AIMC Topic: Hydrology

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Enhanced rainfall prediction performance via hybrid empirical-singular-wavelet-fuzzy approaches.

Environmental science and pollution research international Mar 28, 2023
Rainfall is a vital process in the hydrological cycle of the globe. Accessing reliable and accurate rainfall data is crucial for water resources operation, flood control, drought warning, irrigation, and drainage. In the present study, the main objec...
Forecasting Hydrology Water Resources Floods Fuzzy Logic
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Prediction of monthly precipitation using various artificial models and comparison with mathematical models.

Environmental science and pollution research international Jan 11, 2023
Precipitation (PP) prediction is an interesting topic in the meteorology or hydrology field since it is directly related to agriculture, the management of water resources in hydrologic basins, and water scarcity. Selecting the right model to predict ...
Hydrology Environmental Monitoring Neural Networks, Computer Models, Theoretical Wind
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Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural network.

The Science of the total environment Sep 23, 2022
Data-driven models have been widely developed and achieved impressive results in streamflow prediction. However, the existing data-driven models mostly focus on the selection of input features and the adjustment of model structure, and less on the im...
Forecasting Reproducibility of Results Neural Networks, Computer Rivers Hydrology Bayes Theorem
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Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning.

Water research Aug 11, 2022
We propose and demonstrate a new approach for fast and accurate surrogate modelling of urban drainage system hydraulics based on physics-guided machine learning. The surrogates are trained against a limited set of simulation results from a hydrodynam...
Hydrodynamics Physics Water Hydrology Machine Learning
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Drought Assessment Based on Data Fusion and Deep Learning.

Computational intelligence and neuroscience Jul 31, 2022
Drought is a major factor affecting the sustainable development of society and the economy. Research on drought assessment is of great significance for formulating drought emergency policies and drought risk early warning and enhancing the ability to...
Hydrology Rivers Meteorology Droughts Deep Learning
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Rainfall prediction using multiple inclusive models and large climate indices.

Environmental science and pollution research international Jul 6, 2022
Rainfall prediction is vital for the management of available water resources. Accordingly, this study used large lagged climate indices to predict rainfall in Iran's Sefidrood basin. A radial basis function neural network (RBFNN) and a multilayer per...
Uncertainty Hydrology Algorithms Climate Neural Networks, Computer
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Reconstruction of missing spring discharge by using deep learning models with ensemble empirical mode decomposition of precipitation.

Environmental science and pollution research international Jun 25, 2022
A continuous and complete spring discharge record is critical in understanding the hydrodynamic behavior of karst aquifers and the variability of freshwater resources. However, due to equipment errors, failure of observation and other reasons, missin...
Deep Learning Algorithms Hydrology Neural Networks, Computer Texas
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MODWT-ANN hybrid models for daily precipitation estimates with time-delayed entries in Amazon region.

Environmental monitoring and assessment Mar 25, 2022
Hydrological analyses based on precipitation records in the Amazon are essential due to their importance in climate regulation and regional and global atmospheric circulation. However, there are limitations related to data series with short periods a...
Climate Neural Networks, Computer Hydrology Environmental Monitoring
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Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations.

The Science of the total environment Mar 23, 2022
The monthly high-resolution terrestrial water storage anomalies (TWSA) during the 11-months of gap between GRACE (Gravity Recovery And Climate Experiment) and its successor GRACE-FO (-Follow On) missions are missing. The continuity of the GRACE-like ...
Hydrology Hydrolases Groundwater Water Bayes Theorem Deep Learning
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Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale.

The Science of the total environment Mar 16, 2022
Despite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by m...
Cities Rain Cluster Analysis Artificial Intelligence Hydrology Water Movements
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