This study aims to (1) investigate whether two-big-leaf light use efficiency (LUE) models (TL) outperform big-leaf LUE (BL) by incorporating different gross primary productivity (GPP) responses in sunlit and shaded leaves; (2) explore the robustness of using leaf area index (LAI), clumping (Ω) spherical angle distribution partition canopies into leaves across canopy architectures; (3) identify ...

the major problem in the assessment of relationships between rainfall and runoff occurs when a study is carried out in ungauged watersheds in the absence of hydro-climatic data. this study aims to evaluate the applicability of natural resources conservation service-curve number (nrcs-cn) method together with gis in estimating runoff depth in a mountainous watershed. the study was carried out in...

in the past decades, much effort has been devoted to simulation of the rainfall-runoff process. hydrological models are simplified representations of the natural hydrologic system. in each case, the choice of the model to be applied depends mainly on the objective of the modeling but also on the available information. the relative performances of two lumped conceptual-based hydrology models (ta...

Root mean square deviation (RMSD) is often used to measure the difference between structures. We show mathematically that, for multiple structure alignment, the minimum RMSD (weighted at aligned positions or unweighted) for all pairs is the same as the RMSD to the average of the structures. Thus, using RMSD implies that the average is a consensus structure. We use this property to validate and ...

This paper proposes a Multiples Input-Multiples Ouput Autoregressive (MIMO-AR) model based on two stages to improve monthly anchovy catches forecasting of the coastal zone of Chile for periods from January 1958 to December 2011. In the first stage, the stationary wavelet transform (SWT) based on Fejer-Korovkin (FK) wavelet filter is used to separate the raw time series into a high frequency (HF...

An adaptive neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet works. The ANFIS model was employed to calculate vent air discharge in different gate openings for an embankment dam. A hybrid learning algorithm obtained from combining back-propagation and least square estimate was adopted to identify linear and...