[1] A new global optimization algorithm, dynamically dimensioned search (DDS), is introduced for automatic calibration of watershed simulation models. DDS is designed for calibration problems with many parameters, requires no algorithm parameter tuning, and automatically scales the search to find good solutions within the maximum number of user-specified function (or model) evaluations. As a re...

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for high-rise structures considering Soil Structure Interaction (SSI) effects. Three optimization methods, namely the ant colony optimization (ACO) technique together with artificial bee colony (ABC) and shuffled complex evolution (SCE) methods are utilized for the optimization of TMD Mass, damping coefficient and spr...

[1] The conditional nonlinear optimal perturbation (CNOP) method proposed by Mu et al. (2003) has been a useful tool for studying predictability dynamics. Its further applications are, however, hampered by the need of an adjoint model. Aiming to solve this problem, an ensemble conditional nonlinear optimal perturbation (EnCNOP) approach is proposed in this paper by merging the Monte Carlo metho...

Abstract The hydrological conceptual distributed model, called TETIS, divides river basins into regular cells, all of which are connected according to the network drainage. The rainfall-runoff process is modelled using linked tanks with different outflow relationships. The vertical movement is based on soil properties. Routing along the channel network has been coupled using geomorphologic basi...

[1] To overcome the difficulties in determining the optimal parameters needed for a radiative transfer model (RTM), which acts as the observational operator in a land data assimilation system, we have designed a dual-pass assimilation (DP-En4DVar) framework to optimize the model state (volumetric soil moisture content) and model parameters simultaneously using the gridded Advanced Microwave Sca...

[1] Markov Chain Monte Carlo (MCMC) methods have become increasingly popular for estimating the posterior probability distribution of parameters in hydrologic models. However, MCMC methods require the a priori definition of a proposal or sampling distribution, which determines the explorative capabilities and efficiency of the sampler and therefore the statistical properties of the Markov Chain...

Water is a limited resource and the dramatically increasing world population requires a significant increase in food production. For improving both crop yield and water use efficiency, the usual optimization strategy in irrigation at the field level considers scheduling parameters, i.e. when and how much to irrigate, as well as control parameters, i.e. the intensity and the irrigation time, for...