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Abstract Suspended sediment transport is one of the essential processes in the geochemical cycle. This study investigated the role of rainfall thresholds in suspended sediment modeling in semiarid catchments. The results showed that rainfall-sediment in the study catchment (HMTC) could be grouped into two patterns on the basis of rainfall threshold 10 mm. The sediment modeling based on LSTM model with the rainfall threshold (C-LSTM scheme) and without threshold (LSTM scheme) were evaluated and compared. The results showed that the C-LSTM scheme had much better performances than LSTM scheme, especially for the low sediment conditions. It was observed that in the study catchment, the mean NSE was marginally improved from 0.925 to 0.934 for calibration and 0.911 to 0.924 for validation for medium and high sediment (Pattern 1); while for low sediment (Pattern 2), the mean NSE was significantly improved from -0.375 to 0.738 for calibration and 0.171 to 0.797 for validation. Results of this study indicated rainfall thresholds were very effective in improving suspended sediment simulation. It was suggested that the incorporation of more information such as rainfall intensity, land use, and land cover may lead to further improvement of sediment prediction in the future.

This study has developed a sensitive, simple, and reliable ultrahigh performance liquid chromatography tandem mass spectrometry method for the simultaneous determination of corydaline, tetrahydropalmatine, tetrahydroberberine, tetrahydrocoptisine, byakangelicin, and byakangelicol in beagle dog plasma after oral administration of Yuanhu Zhitong (YHZT) oral liquid, dispersible tablet, and dropping pills. A one-step protein precipitation method was used with methanol-acetonitrile (50 : 50, v/v) for plasma sample pretreatment. Six analytes and one internal standard were separated on a Waters Acquity UPLC BEH C18 column (2.1 mm × 100 mm, 1.7 μm) by gradient elution with 0.1% formic acid-water and 0.1% formic acid-acetonitrile at a flow rate of 0.4 mL/min. Detection was conducted by multiple reaction monitoring mode in the positive ionization. The calibration curves showed good linearity (r > 0.9920). The lower limit of quantization ranged from 0.1 to 1 ng/mL. Moreover, the other results of the method validation were within the acceptable range. After oral administration, the pharmacokinetic characteristics of the three YHZT preparations were different. Compared with the two solid preparations, the absorption of the six analytes in oral liquid was more rapid. Moreover, the area under the plasma drug concentration-time curve and the maximum plasma concentration of tetrahydropalmatine (the main analgesic component of YHZT prescription) in the oral liquid group were higher than those in the other two groups. The results showed oral liquid can exert its efficacy quickly, while dispersible tablet and dropping pills exhibit relatively slow release pattern. The comparative pharmacokinetic study would be helpful to the clinical rational selection and application of YHZT preparations.

A rapid, specific, and sensitive analysis for simultaneous determination of fourteen components (daidzein, fermononetin, apigenin, luteolin, puerarin, ononin, calycosin-7-O-β-D-glucoside, tanshinol, rosmarinic acid, alkanoic acid, salvianolic acid B, berberine, jatrorrhizin, and palmatine) of Yigan Jiangzhi formula (YGJZF, a clinical experienced formula for damp-heat syndrome) in rat plasma was developed and validated using ultraperformance liquid chromatography coupled with mass spectrometry. Lower limit of quantitation ranged from 0.2–10.0 ng/mL, and the calibration curves showed good linearity over 500 times of measuring range. The validated method was successfully applied to the pharmacokinetics investigation of the fourteen compounds in rat plasma after oral administration of two different doses of YGJZF. Compared with the low-dose group of YGJZF, the high-dose group showed significant increase (P

Satellite remote sensing precipitation is useful for many hydrological and meteorological applications such as rainfall-runoff forecasting. However, most studies have focused on the use of satellite precipitation on daily, monthly, or larger time scales. This study focused on flash flood simulation using satellite precipitation products (IMERG) on an hourly scale in a poorly gauged mountainous catchment in southwestern China. Deep learning (long short-term memory, LSTM) was used, merging satellite precipitation and gauge observations, and the merged precipitation data were used as inputs for flood simulation based on the HEC-HMS model, compared with the gauged precipitation data and original IMERG data. The results showed that the application of original IMERG data used directly in the HEC-HMS hydrological model had much lower accuracy than that of gauged data and merged data. The simulation using the merged precipitation in HEC-HMS exhibited much better performances than gauged data. The mean NSE improved from 0.84 to 0.87 for calibration and 0.80 to 0.84 for verification, while the lower NSE improved from 0.81 to 0.84 for calibration and 0.73 to 0.86 for verification, which showed that accuracy and robustness were both significantly improved. Results of this study indicate the advances of remote sensing precipitation with deep learning for flash flood forecasting in mountainous regions. It is likely that more significant improvements can be made in flash flood forecasting by employing multi-source remote sensing products and deep learning merging methods considering the impact of complex terrain.