Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed

A Elsayed, S Rixon, J Levison, A Binns… - Journal of Environmental …, 2023 - Elsevier
Excess nutrients in surface water and groundwater can lead to water quality deterioration in
available water resources. Thus, the classification of nutrient concentrations in water …

Evaluation of Geospatial Interpolation Techniques for Enhancing Spatiotemporal Rainfall Distribution and Filling Data Gaps in Asir Region, Saudi Arabia

AM Helmi, M Elgamal, MI Farouk, MS Abdelhamed… - Sustainability, 2023 - mdpi.com
Providing an accurate spatiotemporal distribution of rainfall and filling data gaps are pivotal
for effective water resource management. This study focuses on the Asir region in the …

Application of machine learning and remote sensing for gap-filling daily precipitation data of a sparsely gauged basin in East Africa

M Faramarzzadeh, MR Ehsani, M Akbari… - Environmental …, 2023 - Springer
Access to spatiotemporal distribution of precipitation is needed in many hydrological
applications. However, gauges often have spatiotemporal gaps. To mitigate this, we …

[HTML][HTML] Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed

A Elsayed, S Rixon, J Levison, A Binns… - Journal of Environmental …, 2024 - Elsevier
Prediction and quantification of nutrient concentrations in surface water has gained
substantial attention during recent decades because excess nutrients released from …

[HTML][HTML] Classification of daily heavy precipitation patterns and associated synoptic types in the Campania Region (southern Italy)

V Capozzi, C Annella, G Budillon - Atmospheric Research, 2023 - Elsevier
Abstract Using a 20-year (2002− 2021) dataset of daily precipitation collected by 107 rain
gauges in the period from October to May, this study introduces a classification of the main …

[HTML][HTML] Comparison of methods for filling daily and monthly rainfall missing data: statistical models or imputation of satellite retrievals?

LV Duarte, KTM Formiga, VAF Costa - Water, 2022 - mdpi.com
Accurate estimation of precipitation patterns is essential for the modeling of hydrological
systems and for the planning and management of water resources. However, rainfall time …

Signals of change in the Campania region rainfall regime: An analysis of extreme precipitation indices (2002–2021)

V Capozzi, A Rocco, C Annella… - Meteorological …, 2023 - Wiley Online Library
It is widely known that precipitation is a key variable of the hydrological cycle that is strongly
affected by recent climate changes. Therefore, there is a growing interest in research …

Utilization of Machine Learning Approaches for Rainfall Data Imputation: A Systematic Literature Review

W Abdillah, S Fauziati… - … Conference on Computer …, 2023 - ieeexplore.ieee.org
Incomplete data is a frequent issue in rainfall observation data records which can affect the
results of analysis or modeling using rainfall data. Incompleteness of rainfall data can occur …

Enhancing the TRMM precipitation product in diverse regions of Iran through an intelligent-based post-processing approach

R Shahbazdashti, A Sharafati, Y Kheyruri… - Acta Geophysica, 2024 - Springer
The significant role of remote-sensed precipitation data lies in alleviating the absence of
readily accessible daily precipitation data, particularly in developing nations. The TMPA …

Developing high resolution monthly gridded precipitation dataset for Afghanistan

MU Rahil, S Ahmad, MW Khan, A Mubeen… - Theoretical and Applied …, 2024 - Springer
The analysis and sustainable management of water resources have been substantially
hampered by the absence of optimum precipitation data in Afghanistan. Using observational …