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Arturs Kempelis, Inese Polaka, Andrejs Romanovs and Antons Patlins
Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor m...
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Maria Kofidou and Alexandra Gemitzi
The present work aims to highlight the possibility of improving model performance by assimilating soil moisture information in the calibration and validation process. The Soil and Water Assessment Tool (SWAT) within QGIS, i.e., QSWAT, was used to simulat...
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Khaled Mohammed, Robert Leconte and Mélanie Trudel
Soil moisture modeling is necessary for many hydrometeorological and agricultural applications. One of the ways in which the modeling of soil moisture (SM) can be improved is by assimilating SM observations to update the model states. Remotely sensed SM ...
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Niloufar Beikahmadi, Antonio Francipane and Leonardo Valerio Noto
Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integra...
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Matina Shakya, Amanda Hess, Bridget M. Wadzuk and Robert G. Traver
The recovery of soil void space through infiltration and evapotranspiration processes within green stormwater infrastructure (GSI) is key to continued hydrologic function. As such, soil void space recovery must be well understood to improve the design an...
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