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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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Shimelis Asfaw Wakigari and Robert Leconte
Soil moisture is an essential hydrological variable for a suite of hydrological applications. Its spatio-temporal variability can be estimated using satellite remote sensing (e.g., SMOS and SMAP) and in-situ measurements. However, both have their own str...
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Srinivasagan N. Subhashree, C. Igathinathane, Adnan Akyuz, Md. Borhan, John Hendrickson, David Archer, Mark Liebig, David Toledo, Kevin Sedivec, Scott Kronberg and Jonathan Halvorson
Farmers and ranchers depend on annual forage production for grassland livestock enterprises. Many regression and machine learning (ML) prediction models have been developed to understand the seasonal variability in grass and forage production, improve ma...
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Islombek Mirpulatov, Mikhail Gasanov and Sergey Matveev
Crop simulation models are an important tool for assessing agroecosystem performance and the impact of agrotechnologies on soil cover condition. However, the high uncertainty and labor intensiveness of long-term weather forecasting limits the applicabili...
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Hailiang Zhang, Junjian Liu, Huoqing Li, Xianyong Meng and Ablimitijan Ablikim
Soil moisture is a critical parameter in numerical weather prediction (NWP) models because it plays a fundamental role in the exchange of water and energy cycles between the atmosphere and the land surface through evaporation. To improve the forecast ski...
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Abdoul Oubeidillah, Glenn Tootle and Thomas Piechota
This study incorporates antecedent (preceding) soil moisture into forecasting streamflow volumes within the North Platte River Basin, Colorado/Wyoming (USA). The incorporation of antecedent soil moisture accounts for infiltration and can improve streamfl...
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Petr ?tepánek, Miroslav Trnka, Filip Chuchma, Pavel Zahradnícek, Petr Skalák, Ale? Farda, Rostislav Fiala, Petr Hlavinka, Jan Balek, Daniela Semerádová and Martin Mo?ný
In recent years, two drought monitoring systems have been developed in the Czech Republic based on the SoilClim and AVISO soil moisture models. The former is run by Mendel University and Global Change Research Institute (CAS), while the latter, by the Cz...
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Jun Liu, Donghui Shanguan, Shiyin Liu and Yongjian Ding
Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assi...
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Andrew R. Sommerlot and Zachary M. Easton
Agricultural non-point source (NPS) pollution is a source of water quality impairment, and demonstrates widely varying spatial and temporal pollution potential. Many efforts to protect water quality are based on seasonal and annual estimates of pollutant...
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Xuejun Zhang, Qiuhong Tang, Guoyong Leng, Xingcai Liu, Zhe Li and Zhongwei Huang
Initial conditions (ICs) and climate forecasts (CFs) are the two primary sources of seasonal hydrological forecast skill. However, their relative contribution to predictive skill remains unclear in China. In this study, we investigate the relative roles ...
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