Limits on scalar-induced gravitational waves from the stochastic background by pulsar timing array observations.

Recently, the NANOGrav, PPTA, EPTA, and CPTA Collaborations independently reported their evidence of the Stochastic Gravitational Waves Background (SGWB). While the inferred gravitational-wave background amplitude and spectrum are consistent with astrophysical expectations for a signal from the population of supermassive black-hole binaries (SMBHBs), the search for new physics remains plausible in this observational window. In this work, we explore the possibility of explaining such a signal by the scalar-induced gravitational waves (IGWs) in the very early universe. We use a parameterized broken power-law function as a general description of the energy spectrum of the SGWB and fit it to the new results of NANOGrav, PPTA and EPTA. We find that this approach can put constraints on the parameters of IGW energy spectrum and further yield restrictions on various inflation models that may produce primordial black holes (PBHs) in the early universe, which is also expected to be examined by the forthcoming space-based GW experiments.

Developing a stochastic hydrological model for informing lake water level drawdown management.

Winter drawdown (WD) is a common lake management tool for multiple purposes such as flood control, aquatic vegetation reduction, and lake infrastructure maintenance. To minimize adverse impacts to a lake's ecosystem, regulatory agencies may provide managers with general guidelines for drawdown and refill timing, drawdown magnitude, and outflow limitations. However, there is significant uncertainty associated with the potential to meet management targets due to variability in lake characteristics and hydrometeorology of each lake's basin, making the use of modeling tools a necessity. In this context, we developed a hydrological modeling framework for lake water level drawdown management (HMF-Lake) and evaluated it at 15 Massachusetts lakes where WDs have been applied over multiple years for vegetation control. HMF-Lake is based on the daily lake water balance, with inflows simulated by a lumped rainfall-runoff model (Cemaneige-GR4J) and outflow rate calculated by a modified Target Storage and Release Based Method (TSRB). The model showed a satisfactory performance of simulating historical water levels (0.53 ≤ NSE ≤ 0.86), however, uncertainties from meteorological inputs and TSRB determined lake outflow rate affected the result accuracy. To account for these uncertainties, the model was executed stochastically to assess the ability of study lakes to follow the Massachusetts' general WD guidelines: drawdown by Dec 1 and fully refilled by Apr 1. By using the stochastic HMF-Lake, the probabilities of each lake to reach the drawdown level by Dec 1 were calculated for different drawdown magnitudes (1-6 ft). The probability results suggest it was generally less possible for most of study lakes to achieve a drawdown of 3 ft or more by Dec 1. Moreover, we employed the stochastic model to derive the annual latest refill starting dates that ensure a 95 % probability of reaching the normal water level by Apr 1. We found starting a refill in March for drawdowns up to 6 ft was feasible for most of study lakes. These results provide lake managers with a quantitative understanding of the lake's ability to follow the state guidelines. The model may be used to systematically evaluate current WD management strategies at state or regional scales and support adaptive WD management under changing climates.

Typhoon triggers estuarine heavy metal risk by regulating the multifractal grainsize of resuspended sediment.

The turbulent boundary layer generated by wind in the estuarine surface water serves as a main factor affecting the distribution of suspended particulate matter (SPM) and suspended sediment concentration (SSC). In this study, representative typhoon-induced variation of surface fine SPM (<63 µm) was simulated in the Yangtze River Estuary (YRE) under two time scenarios. Each scenario contained four grainsize SPM fractions named Fraction 1 (<8 µm), Fraction 2 (8-16 µm), Fraction 3 (16-32 µm), Fraction 4 (32-63 µm). The typhoon-induced resuspended multifractal SSC quantification (TRMSQ) based on the relationship between SPM grainsize and heavy metal adsorption capacity was proposed to assess the variation in the resuspended threat of heavy metal to 6 key estuarine protected objects (three reservoirs & three national reserves) between Scenarios 1 and 2. The results presented that Fraction 3 exhibited the maximum increment in SSC resuspension mass and longest regression time from typhoon. Combined with TRMSQ, chromium (Cr) was calculated to be the riskiest typhoon-induced factor. The integrated resuspended risk of heavy metals for each protected object tends to increase from the northwest of Chongming Island (1.2) towards the maximum turbidity zone (>9) downstream, with an estuary-wide mean of 3.3.

Multitasking device with switchable and tailored functions of ultra-broadband absorption and polarization conversion.

We present a multitasking tailored device (MTD) based on phase change material vanadium dioxide (VO2) and photoconductive semiconductor (PS) in the terahertz (THz) regime, thereby manipulating the interaction between electromagnetic waves and matter. By altering the control multitasking device, its room temperature, or pump illumination, we switch the function of absorption or polarization conversion (PC) on and off, and realize the tuning of absorptivity and polarization conversion rate (PCR). Meanwhile, the construction of cylindrical air columns (CACs) in the dielectric provides an effective channel to broaden the absorption bandwidth. For the MTD to behave as a polarization converter with VO2 pattern in the insulating phase (IP), exciting the PS integrated to the proposed device via an optical pump beam, the PCR at 0.82-1.6 THz can be modulated continuously from over 90% to perfectly near zero. When the PS conductivity is fixed at 3×104 S/m and VO2 is in the metal phase (MP) simultaneously, the MTD switched to an absorber exhibits ultra-broadband absorption with the absorptivity over 90% at 0.68-1.6 THz. By varying the optical pump power and thermally controlling the conductivity of VO2, at 0.68-1.6 THz, the absorbance of such a MTD can be successively tuned from higher than 90% to near null. Additionally, the influences of the polarization angle and incident angle on the proposed MTD are discussed. The designed MTD can effectively promote the electromagnetic reconfigurable functionalities of the present multitasking devices, which may find attractive applications for THz modulators, stealth technology, communication system, and so on.

Risk prediction of microcystins based on water quality surrogates: A case study in a eutrophicated urban river network.

Microcystins (MCs), the toxic by-products from harmful algal bloom (HAB), have caused world-wide concern due to their acute toxicity in freshwater ecosystems. Most studies on HAB have been conducted for shallow freshwater lakes, such as Taihu Lake in China. However, algal blooms in urban rivers located downstream of eutrophicated lakes are also a serious problem for local administrators. It is important for them to know the current and potential risk level of MCs. This environmental issue is rarely reported or discussed. Within this context, we monitored MC concentrations in the Binhu River Network (BRN) in the algal bloom season (Aug, Sep, and Oct) in 2019. To note if the MC concentrations were dangerous, we used 1.0 µg/L suggested by the World Health Organization as the standard value. The proportions of MC samples violating the standard value were 31.78% (Aug), 21.14% (Sep) and 30.77% (Oct). We also designed two statistical models to predict MC concentrations and the possibility to exceed the standard level based on 10 water quality surrogates: Artificial Neural Network (ANN) and Logistic Regression (LR) models. These two models were trained and validated by the monitoring dataset (n = 224). Both models had good performances during training and testing. Although the water quality varied diversely both in spatial and temporal scale, Cluster Analysis (CA) could detect similarities among the samples and separated them into 3 classes, with each class denoting different types of rivers based on the 10 water quality surrogates. Then the ANN and LR were applied as a function of chl-a in each class; by gradually increasing chl-a concentration, we detected chl-a thresholds in class 1, 2, 3 were 25.5, 224, and 109.5 µg/L, respectively, when MCs have a 50% possibility to exceed standard level. The threshold values provided important implications for MC management in the BRN.

Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake.

Microcystins (MCs), the algal toxins produced by cyanobacteria, raised a worldwide concern in recent decades. Limited monitoring stations for MCs make it hard to map the MC spatial distribution in certain areas. To tackle such problems, we selected Liangxi River as our research area and developed an integrated model to get spatial continuous MC data without too many sampling sites, which integrates a hydro-environment model and an artificial neural network algorithm (ANN). The ANN algorithm can estimate concentration MCs via environmental factors. In this paper, we selected chl-a, TN, TP, NO 2 - , NO 3 - , NH3 -N, and PO 4 3 - as stressors. The ANN model we established showed good performances both in train (R2  = 0.8407) and test set (R2  = 0.7543). In the hydro-environment model, by inputting river geometry and model boundary data, the spatial continuous water quality data could be simulated. The water quality data returned from the hydro-environmental model were used as input variables of the well-trained ANN model; the continuous MC data were derived. To evaluate this model on geo-mapping the MC distribution in Liangxi River, we compared the performance of this model and spatial interpolation on the test set, it turns out the integrated model showed a better performance. © 2020 Water Environment Federation PRACTITIONER POINTS: The cost of microcystin (MC) detection is too high for routine monitoring. We integrated regression method and hydro-environment model to predict MCs. Results derived from spatial interpolation are not robust in unmonitored area. The new integration model can minimize the drawback of spatial interpolation.