Analytical Solutions for Vertical Flow in Unsaturated, Rooted Soils with Variable Surface Fluxes

Analytical solutions to Richards\u27 equation have been derived to describe the distribution of pressure head, water content, and fluid flow for rooted, homogeneous soils with varying surface fluxes. The solutions assume that (i) the constitutive relations for the hydraulic conductivity and water content as function of the pressure head are exponential, (ii) the initial water content distribution is a steady-state distribution, and (iii) the root water uptake is a function of depth. Three simple forms of root water uptake are considered, that is, uniform, stepwise, and exponential functional forms. The lower boundary of the rooted soil profile studied is a water table, while at the upper boundary time-dependent surface fluxes are specified, either infiltration or evaporation. Application of the Kirchhoff transformation allows us to linearize Richards\u27 equation and derive exact solutions. The steady-state solution is given in a closed form and the transient solution has the form of an infinite series. The solutions are used to simulate the hydraulic behavior of the rooted soils under different conditions of root uptake and surface flux. The restricted assumptions for the solutions may limit the applicability, but the solutions are relatively flexible and easy to implement compared to other analytical and numerical schemes. The analytical solutions provide a reliable and convenient means for evaluating the accuracy of various numerical schemes, which usually require sophisticated algorithms to overcome convergence and mass balance problems

Understanding the Evolution of Landscape Planning Strategy in China: From Fragmented Urban Green Space System to Regional Greenway Network across Cities

In China, urban green space system (UGSS) is defined as a network of all sorts of green spaces in city built-up area which supports ecological and recreational functions (Wang, 2009). The implementation of UGSS indicates several common problems, such as overemphasizing green spaces in the built area of city, losing stability and rationality in spatial patterns, and mismatching the progress of ecological restoration cycles (Liu & Wen, 2007; Wang, 2009). Greenways represent a distinctly strategic approach to landscape planning through combinations of spatially and functionally compatible land uses within a network (Ahern, 1995). Specially, four principal strategies (Protective, Defensive, Offensive, and Opportunistic) are recognized as an overall planning strategy for greenway (Ahern, 1995). Inspired by the greenway concept, China has constructed 2,372 kilometers of greenway network at Pearl River Delta (PRD), in order to maintain regional ecological safety, to improve regional livability, to stimulate economic growth, and to protect cultural and historic resources (He et al, 2010). Meanwhile, various cities in China have initiated their own greenway network planning for implementation. This indicates a potential greenway movement during the next few years in this country, following the global interest in greenways as a sustainable landscape planning strategy. Through historical review of urban green space system in China and a case study of PRD greenway network, this research attempts to answer the following questions: (1) how contemporary greenway network is planned and implemented in China? (2) How Ahern\u27s four principal strategies (protective, defensive, offensive and opportunistic) have been applied within PRD regional greenway network as landscape planning strategy? The purpose of this research is to provide a holistic perspective on greenway planning and development in China. Specially, this paper will (1) present evolution of UGSS planning and recent greenway development in China; (2) discuss the practice of implementing greenway network as landscape planning strategy; and (3) discuss the future greenway development in China

SRMAE: Masked Image Modeling for Scale-Invariant Deep Representations

Due to the prevalence of scale variance in nature images, we propose to use image scale as a self-supervised signal for Masked Image Modeling (MIM). Our method involves selecting random patches from the input image and downsampling them to a low-resolution format. Our framework utilizes the latest advances in super-resolution (SR) to design the prediction head, which reconstructs the input from low-resolution clues and other patches. After 400 epochs of pre-training, our Super Resolution Masked Autoencoders (SRMAE) get an accuracy of 82.1% on the ImageNet-1K task. Image scale signal also allows our SRMAE to capture scale invariance representation. For the very low resolution (VLR) recognition task, our model achieves the best performance, surpassing DeriveNet by 1.3%. Our method also achieves an accuracy of 74.84% on the task of recognizing low-resolution facial expressions, surpassing the current state-of-the-art FMD by 9.48%

Stochastic uncertainty analysis for solute transport in randomly heterogeneous media using a Karhunen-Loève-based moment equation approach

This is the published version. Copyright American Geophysical Union[1] A new approach has been developed for solving solute transport problems in randomly heterogeneous media using the Karhunen-Loève-based moment equation (KLME) technique proposed by Zhang and Lu (2004). The KLME approach combines the Karhunen-Loève decomposition of the underlying random conductivity field and the perturbative and polynomial expansions of dependent variables including the hydraulic head, flow velocity, dispersion coefficient, and solute concentration. The equations obtained in this approach are sequential, and their structure is formulated in the same form as the original governing equations such that any existing simulator, such as Modular Three-Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems (MT3DMS), can be directly applied as the solver. Through a series of two-dimensional examples, the validity of the KLME approach is evaluated against the classical Monte Carlo simulations. Results indicate that under the flow and transport conditions examined in this work, the KLME approach provides an accurate representation of the mean concentration. For the concentration variance, the accuracy of the KLME approach is good when the conductivity variance is 0.5. As the conductivity variance increases up to 1.0, the mismatch on the concentration variance becomes large, although the mean concentration can still be accurately reproduced by the KLME approach. Our results also indicate that when the conductivity variance is relatively large, neglecting the effects of the cross terms between velocity fluctuations and local dispersivities, as done in some previous studies, can produce noticeable errors, and a rigorous treatment of the dispersion terms becomes more appropriate

An Empirical Study of Sentiment Analysis for Chinese Microblogging

This paper used three machine learning algorithms, three kinds of feature selection methods and three feature weight methods to study the sentiment classification for Chinese microblogging. The experimental results indicate that the performance of SVM is best in three machine learning algorithms; IG is the better feature selection method compared to the other methods, and TF-IDF is best fit for the sentiment classification in Chinese microblogging. Combining the three factors the conclusion can be drawn that the performance of combination of SVM, IG and TF-IDF is best

Interlayer Coupling Driven High-Temperature Superconductivity in La3_3Ni2_2O7_7 Under Pressure

The newly discovered high-temperature superconductivity in La$_3$Ni$_2$O$_7$ under pressure has attracted a great deal of attentions. The essential ingredient characterizing the electronic properties is the bilayer NiO$_2$ planes coupled by the interlayer bonding of $3d_{z^2}$ orbitals through the intermediate oxygen-atoms. In the strong coupling limit, the low energy physics is described by an intralayer antiferromagnetic spin-exchange interaction $J_{\parallel}$ between $3d_{x^2-y^2}$ orbitals and an interlayer one $J_{\perp}$ between $3d_{z^2}$ orbitals. Taking into account Hund's rule on each site and integrating out the $3d_{z^2}$ spin degree of freedom, the system reduces to a single-orbital bilayer $t$-$J$ model based on the $3d_{x^2-y^2}$ orbital. By employing the slave-boson approach, the self-consistent equations for the bonding and pairing order parameters are solved. Near the physically relevant $\frac{1}{4}$-filling regime (doping $\delta=0.3\sim 0.5$), the interlayer coupling $J_{\perp}$ tunes the conventional single-layer $d$-wave superconducting state to the $s$-wave one. A strong $J_{\perp}$ could enhance the inter-layer superconducting order, leading to a dramatically increased $T_c$. Interestingly, there could exist a finite regime in which an $s+id$ state emerges.Comment: Version accepted by Phys. Rev. Let