Forest operations,tree species composition and decline in rainfall explain runoff changes in the Nacimiento experimental catchments,south central Chile

Few long-term studies have explored how intensively managed short rotation forest plantations interact with climate variability. We examine how prolonged severe drought and forest operations affect runoff in 11 experimental catchments on private corporate forest land near Nacimiento in south central Chile over the period 2008–2019. The catchments (7.7–414 ha) contain forest plantations of exotic fast-growing species (Pinus radiata, Eucalyptus spp.) at various stages of growth in a Mediterranean climate (mean long-term annual rainfall = 1381 mm). Since 2010, a drought, unprecedented in recent history, has reduced rainfall at Nacimiento by 20%, relative to the long-term mean. Pre-drought runoff ratios were <0.2 under 8-year-old Eucalyptus; >0.4 under 21-year-old Radiata pine and >0.8 where herbicide treatments had controlled vegetation for 2 years in 38% of the catchment area. Early in the study period, clearcutting of Radiata pine (85%–95% of catchment area) increased streamflow by 150 mm as compared with the year before harvest, while clearcutting and partial cuts of Eucalyptus did not increase streamflow. During 2008–2019, the combination of emerging drought and forestry treatments (replanting with Eucalyptus after clearcutting of Radiata pine and Eucalyptus) reduced streamflow by 400–500 mm, and regeneration of previously herbicide-treated vegetation combined with growth of Eucalyptus plantations reduced streamflow by 1125 mm (87% of mean annual precipitation 2010–2019). These results from one of the most comprehensive forest catchment studies in the world on private industrial forest land indicate that multiple decades of forest management have reduced deep soil moisture reservoirs. This effect has been exacerbated by drought and conversion from Radiata pine to Eucalyptus, apparently largely eliminating subsurface supply to streamflow. The findings reveal tradeoffs between wood production and water supply, provide lessons for adapting forest management to the projected future drier climate in Chile, and underscore the need for continued experimental work in managed forest plantations.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

Simulations of multimode bolometric interferometers

We describe a procedure for the numerical modelling of astronomical interferometers, with particular relevance to far-infrared and submillimetre wavelengths. The scheme is based on identifying a set of modes that carry power from the sky to the detector. The procedure is extremely general, and can be used to model scalar or vector fields, in any state of coherence and polarization, the only limitation being that the propagation of a coherent field through the system be described by an integral transform, a constraint that is in practise always met.
We present simulations of ideal, multimode two-dimensional interferometers, and show that the modal theory reproduces the correct behaviour of both Michelson and Fizeau interferometers. We calculate simulated visibility data for a multimode bolometric Michelson interferometer, with a synthesized source, and produce a dirty map, recovering the original source with the usual artefacts associated with interferometers.     

Wavelet Analysis of Space Solar Telescope Images

The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

An efficient technique for pre-selecting low-redshift damped Lyα systems

The number of z ∼ 1 damped Lyα systems (DLAs, log  N (H  i ) ≥ 20.3) per unit redshift is approximately 0.1, making them relatively rare objects. Large, blind QSO surveys for low-redshift DLAs are therefore an expensive prospect for space-borne ultraviolet telescopes. Increasing the efficiency of these surveys by pre-selecting DLA candidates based on the equivalent widths (EWs) of metal absorption lines has previously been a successful strategy. However, the success rate of DLA identification is still only ∼35 per cent when simple EW cut-offs are applied, the majority of systems having 19.0 < log  N (H  i ) < 20.3. Here, we propose a new way to pre-select DLA candidates. Our technique requires high-to-moderate-resolution spectroscopy of the Mg  ii λ2796 transition, which is easily accessible from the ground for 0.2 ≲ z ≲ 2.4. We define the D -index, the ratio of the line equivalent width to velocity spread, and measure this quantity for 19 DLAs and eight sub-DLAs in archival spectra obtained with echelle spectrographs. For the majority of absorbers, there is a clear distinction between the D -index of DLAs compared with sub-DLAs (Kolmogorov–Smirnov probability = 0.8 per cent). Based on this pilot data sample, we find that the D -index can select DLAs with a success rate of up to 90 per cent, an increase in selection efficiency by a factor of 2.5 compared with a simple EW cut. We test the applicability of the D -index at lower resolution and find that it remains a good discriminant of DLAs for full width at half-maximum (FWHM) ≲ 1.5 Å. However, the recommended D -index cut-off between DLAs and sub-DLAs decreases with poorer resolution and we tabulate the appropriate D -index values that should be used with spectra of different resolutions.     

A Time Evolution Study of the Superhumps of the Dwarf Nova 1RXS J232953.9+062814 by Wavelet Transform

The time evolution behaviour of the superhumps of the dwarf nova1RXS J232953.9+ 062814 is investigated with the wavelet analysis method. On the basis of two nights CCD photometry performed during its first superoutburst as well as other published brightness data, we reveal the superhump's time-dependence as a function of periods and time. Our light curves, which phased in the rapid decay ending portion of the superoutburst and in the dawn of a following normal outburst, are important to help trace the superhump evolution for the star. Both the superhump period and the orbital period of the binary system are detected in the present data. We obtain P _sh=0.0458±0.0002d and P _orb=0.0450±0.0002d. They agree with those existing values. The two periods exchanged their roles during the superhump evolution. The general profile of brightness fading over the outbursts roughly followed an exponential decay law or a form of a five-order polynomial. This revised version was published online in July 2006 with corrections to the Cover Date.