Urban rainstorm and waterlogging scenario simulation based on SWMM under changing environment.

Urban rainstorm and waterlogging occurred more frequently in recent years, causing huge economic losses and serious social harms. Accurate rainstorm and waterlogging simulation is of significant value for disaster prevention and mitigation. This paper proposed a numerical model for urban rainstorm and waterlogging based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS), and the model was applied in Lianhu district of Xi'an city of China. Furthermore, the effects of rainfall characteristics, pipe network implementation level and urbanization level on waterlogging were explored from the perspectives of spatial distribution of waterlogging points, drainage capacity of pipe network and surface runoff generation and confluence. The results show that: (1) with the increase of rainfall recurrence period, the peak of total water accumulating volume, the average decline rate of water accumulating volume and the number of waterlogging nodes increase; (2) optimizing the pipe diameter can shorten the average overload time of the pipe network from the entire pipe network, but for a single pipe, optimizing the pipe diameter may lead to overloading of unoptimized downstream pipeline; (3) the lower the imperviousness, the less the number of waterlogging nodes and average time of water accumulating, and (4) the west, northwest and southwest areas are relatively affected by the imperviousness, only improving the underlying surface conditions has limited influence on waterlogging in the study area. This study can provide reference for urban waterlogging prevention and reduction and pipe network reconstruction.

High-performance grating couplers on 220-nm thick silicon by inverse design for perfectly vertical coupling.

Efficient grating couplers (GCs) for perfectly vertical coupling are difficult to realize due to the second-order back reflection. In this study, apodized GCs (AGCs) are presented for achieving perfectly-vertical coupling to 220 nm thick silicon-on-insulator (SOI) waveguides in the C-band. We compare the performance of the AGCs to that of uniform GCs (UGCs) and demonstrate the superiority of the former. The AGCs were obtained through inverse design using gradient-based optimization and were found to effectively suppress back reflection and exhibit better matching to the Gaussian beam profile. The design and measurement results show that AGCs have a 3 dB lower coupling loss than UGCs. We fabricated focusing AGCs by electron beam lithography with a single, 70 nm shallow etch and a minimum feature size of 100 nm, which makes them compatible with CMOS technology. The AGCs achieved a coupling efficiency of -5.86 dB for perfectly vertical coupling. Overall, our results demonstrate the potential of AGCs for achieving high-performance coupling in the C-band on the SOI platform.

Cotransport of microplastics and sulfanilamide antibiotics in groundwater: The impact of MP/SA ratio and aquifer media.

The aim of this study was to investigate the effects of the aquifer media, structure type, and initial concentration ratio of contaminants on the cotransport behavior of microplastics (MPs) and sulfanilamide antibiotics (SAs) through a series of one-dimensional column experiments in groundwater. Under a single suspension system, the relative mass recovery rates of fine sand, medium sand, and coarse sand were 25.65%, 37.50%, and 57.91%, respectively. The breakthrough curve of MPs showed a weak and slow upward trend, indicating that the migration of MPs in aqueous media is mainly blocked by the surface. The migration results of different structure type on SAs (ST, SM, SM2, SMX) in a single suspension system indicated that the deposition rate coefficients (kc) of the four SAs were 1.23 × 10-1, 9.09 × 10-2, 1.11 × 10-1, and 8.87 × 10-2. Under a binary suspension system (MPs:ST = 1:1), the maximum effluent concentration (MEC) of MPs in fine sand, medium sand, and coarse sand increased to 0.52, 0.64, and 0.88, respectively, and the relative mass recovery rates of ST were 22.79%, 23.59%, 20.25%. This results show that the coexistence of MPs and SAs significantly promotes the migration of MPs and inhibits that of SAs. It is mainly because of their carrier action, adsorption sites and additional deposit sites for MPs through SAs pre-deposition on media. When the initial concentration ratio was 2:1, the particles had the highest Zeta potential (-48.3 mV) and the highest potential barrier (3200 kBT), leading to the formation of complex aggregates (MPs-SAs-MPs) owing to the aggregation of colloidal MPs. The increase in the volume and number of MPs-SAs co-aggregates on the surface of the media as the initial concentration of MPs increases, which was mainly due to the disappearance of surface blocking effect and the occurrence of filtering maturation effect.

A Water Level Measurement Approach Based on YOLOv5s.

Existing water gauge reading approaches based on image analysis have problems such as poor scene adaptability and weak robustness. Here, we proposed a novel water level measurement method based on deep learning (YOLOv5s, convolutional neural network) to overcome these problems. The proposed method uses the YOLOv5s to extract the water gauge area and all scale character areas in the original video image, uses image processing technology to identify the position of the water surface line, and then calculates the actual water level elevation. The proposed method is validated with a video monitoring station on a river in Beijing, and the results show that the systematic error of the proposed method is only 7.7 mm, the error is within 1 cm/the error is between 1 cm and 3 cm, and the proportion of the number of images is 95%/5% (daylight), 98%/2% (infrared lighting at night), 97%/2% (strong light), 45%/44% (transparent water body), 91%/9% (rainfall), and 90%/10% (water gauge is slightly dirty). The results demonstrate that the proposed method shows good performance in different scenes, and its effectiveness has been confirmed. At the same time, it has a strong robustness and provides a certain reference for the application of deep learning in the field of hydrological monitoring.

Adsorption of microplastics on aquifer media: Effects of the action time, initial concentration, ionic strength, ionic types and dissolved organic matter.

The adsorption of microplastic (MPs) on aquifer media is affected by their own properties and environmental factors. Research results have shown that the adsorption capacity of MPs on the three media has the following order: fine sand > medium sand > coarse sand, and the adsorption equilibrium times are 8 h, 12 h and 24 h, respectively. The adsorption process has three stages (fast linear distribution, slow adsorption and equilibrium stability), and the action law is compounded by the pseudo-second-order kinetic equation. After adsorption, MPs were observed on the three media, and there were single existence and aggregation phenomena. The energy spectrum analysis indicates that elemental carbon (C) appears on the surface of the medium after the action occurs, and the surface of the media adsorbs MPs to varying degrees. According to the results of infrared spectroscopy, after action, the peak areas of the absorption peaks at 680-880 cm-1 and 1450-1620 cm-1 increase. The absorption peaks are mainly C-H out-of-plane bending vibrations from aromatic hydrocarbons and C-H stretching vibrations on the benzene ring skeleton. As the initial concentration increases, the equilibrium adsorption capacity increases linearly. The isothermal adsorption of MPs in porous media conforms to the Freundlich model. The adsorption process is also affected by different anions and cations. The higher the ionic strength of NH4+ is, the weaker the electrostatic effect of negatively charged MPs, thereby increasing the adsorption capacity of microplastics on porous media. Ca2+ can promote the adsorption of MPs by the media through the formation of ternary complexes between cations, MPs and surface functional groups. The increase in SO42- and HCO3- concentrations gradually inhibits the adsorption of MPs.

Holocene terrestrialization process on the Sanjiang Plain (China) and its significance to the East Asian summer monsoon circulation.

A wide-spread terrestrialization process has been reported occurring across the Sanjiang Plain in the Holocene Epoch, while little is known for its detailed process and links to regional climate variation. Here, we present high-resolution palynological and lithological data of a peatland's sedimentary profile in the central Sanjiang Plain. The study aims to reconstruct the local terrestrialization process and discuss its significance to the Holocene East Asian summer monsoon (EASM) evolution. The results indicate that a paleolake surrounded by broadleaved forests developed during ~7.4-4.5 ka BP, corresponding to a wet and warm stage with strengthened EASM. Thereafter, a wetland dominated by Cyperaceae and Poaceae was initiated with the terrestrialization process. This process lasted until 3.9 ka BP when a lithological mud-to-peat transition occurred indicating a peatland began to develop after the extinction of the paleolake. Considering the prevalent EASM climate on the modern Sanjiang Plain, this paleolake-to-peatland transition during 4.5-3.9 ka BP was attributed to the mid-Holocene EASM retreat in addition to the paleolake's autogenic infilling process. During the peatland developing stage, four dry intervals with weakened EASM occurred in 3.9-3.2 ka BP, 2.0-1.3 ka BP, 1.0-0.5 ka BP, and 0.1-0.0 ka BP. They were alternated with three wet stages of the strengthened EASM during 3.2-2.0 ka BP, 1.3-1.0 ka BP, and 0.5-0.1 ka BP. Our findings are supported by a series of paleoclimatic records across the monsoonal regions of China. We suggest that the EASM evolution associated with the tropical ocean-atmosphere interactions was initially modulated by the solar output variation.

Dynamic characteristics of immobilized microorganisms for remediation of nitrogen-contaminated groundwater and high-throughput sequencing analysis of the microbial community.

The aim of this study was to investigate the effect of adsorption by a composite active medium (nitrogen-degrading bacteria immobilized on scoria) on the removal of ammonium nitrogen (NH4+-N), nitrite nitrogen (NO2-N) and nitrate nitrogen (NO3-N). Transport of these three forms of nitrogen was investigated using columns with different flow rates, initial concentrations and depths. Immobilization of the bacteria on the scoria significantly enhanced the ability of the composite active medium to remove nitrogen during the remediation process. As the flow rate increased, the shear force increased and solute diffusion decreased, thereby improving the tolerance of the bacteria for the three forms of nitrogen and reducing the penetration time. Increasing the initial nitrogen concentration resulted in a decrease in the adsorption rate constant (KTh). The nitrogen-degrading bacteria immobilized on scoria rapidly reached saturation with regards to their nitrogen adsorption capacity. The initial nitrogen concentration of each media layer was different, and the composite active medium had a certain blocking effect, which resulted in a slow increase in the concentration of nitrogen in the deeper media layer. The transport experiments showed that the process accords with the thomas model and the Bohart-Adams model. The contents of the three forms of nitrogen were within acceptable standards for drinking water after 2 months of a column containing the composite active medium. The composite active medium can be used for in situ and ex situ remediation of groundwater containing excessive nitrogen. High-throughput sequencing analysis was used to monitor the composition of the bacterial community present within the composite active medium. During the remediation process, there were only slight changes in the structure and composition of the nitrogen-degrading bacterial community, although there were clear differences in abundance. Pseudomonas, Stenotrophomonas and Serratia were the three bacterial genera that were effective removal of all three forms of nitrogen.

High-resolution simulation and validation of soil moisture in the arid region of Northwest China.

Soil moisture plays an important role in land-atmosphere interactions, agricultural drought monitoring, and water resource management, particularly across arid regions. However, it is challenging to simulate soil moisture of high spatial resolution and to evaluate soil moisture at fine spatial resolution in arid regions in Northwest China due to considerable uncertainties in forcing data and limited in situ measurements. Then, the data set was used to produce the 1 km high-resolution atmospheric forcing datasets and to drive the Community Land Model version 3.5 (CLM3.5) for simulating spatiotemporally continuous surface soil moisture. The capabilities of soil moisture simulation using CLM3.5 forced by the XJLDAS-driven field were validated against data obtained at three soil layers (0-10, 0-20, and 0-50 cm) from 54 soil moisture stations in Xinjiang. Results show that the simulated soil moisture agreed well with the observations [CORR > 0.952], and the intra-annual soil moisture in Xinjiang gradually increased during May through August. The main factors that affect changes in soil moisture across the study region were precipitation and snowmelt. The overall finding of this study is that an XJLDAS, high-resolution forcing data driven CLM3.5 can be used to generate accurate and continuous soil moisture of high resolution (1km) in Xinjiang. This study can help understand the spatiotemporal features of the soil moisture, and provide important input for hydrological studies and agricultural water resources management over the arid region.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.