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\begin{document}

\title{Integrating a double cropping model with groundwater-fed irrigation in
the North China Plain}



\author[1]{Yuwen FAN}%
\author[2]{Zhao Yang}%
\author[3]{Min-Hui Lo}%
\author[4]{Eun-Soon Im}%
\affil[1]{Hong Kong University of Science and Technology}%
\affil[2]{Pacific Northwest National Laboratory}%
\affil[3]{National Taiwan University}%
\affil[4]{The Hong Kong University of Science and Technology}%


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  \date{May 23, 2024}


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\begin{abstract}
Irrigated cultivation, as a prevalent anthropogenic activity, exerts a
significant influence on land use and land cover, resulting in notable
modifications to land-atmosphere interaction and the hydrological cycle.
Given the extensive cropland, high productivity, compact rotation,
semi-arid climate, intense irrigation, and groundwater depletion in the
North China Plain (NCP), the development of a comprehensive
crop-irrigation-groundwater model becomes imperative for understanding
agricultural-induced climate response in this region. This study
presents an integrated crop model explicitly tailored to the NCP, which
incorporates double-cropping rotation, irrigation practice, and
groundwater interactions into the regional climate model. The
modifications are implemented to: (1) enable a seamless transition from
field scale application to regional scale application, facilitating the
incorporation of spatial variability, (2) capture the distinctive
attributes of the NCP region, ensuring the model accurately reflects its
unique characteristics, and (3) reinforce the direct interaction among
crop-related variables, thereby enhancing the model's capacity to
simulate their dynamic behaviors. The integrated crop modeling system
demonstrates a commendable performance in crop simulations using
climatic conditions, which is substantiated by its identification of
crop stages, estimation of field biomass, prediction of crop yield, and
finally the projection of monthly leaf area index. In our next phase,
this integrated crop modeling system will be employed in long-term
simulations to enhance our understanding of the intricate relationship
between agricultural development and climate change.%
\end{abstract}%



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