Agricultural water demand, groundwater extraction, surface water delivery and climate have
complex nonlinear relationships with groundwater storage in agricultural regions. As an …

Abstract Model parameter calibration is a fundamentally important stage that must be
completed before applying a model to address practical problems. In this study, we describe …

Accurate pre-harvest prediction of wheat yield through secondary traits helps to facilitate
plant breeding and reduce costs. Machine learning (ML) algorithms are increasingly applied …

The fidelity of climate projections is often undermined by biases in climate models due to
their simplification or misrepresentation of unresolved climate processes. While various bias …

This study examines the overall performance of the Noah with multiparameterization (Noah‐
MP) land surface model in simulating key land‐atmosphere variables at a global scale and …

Reservoir operation optimization is very important in water resource development and
management. This paper focuses on the bi-objective optimization problems via proposing a …

The numerical complexity of Discrete Element Method (DEM) simulations generally forces
an idealisation of DEM models, making the calibration process the key to realistic simulation …

Non-traditional optimization tools have proved their potential in solving various types of
optimization problems. These problems deal with either single objective or multiple/many …

Surrogate-assisted multi-objective evolutionary algorithms have become increasingly
popular for solving computationally expensive problems, profiting from surrogate modeling …

The process-based water system models have been transitioning from single-functional to
integrated multi-objective and multi-functional since the worldwide digital upgrade of urban …