Plant Species Richness Increased Belowground Plant Biomass and Substrate Nitrogen Removal in a Constructed Wetland     

Hai Wang  Zheng‐Xin Chen  Xiao‐Yu Zhang  Si‐Xi Zhu  Ying Ge  Scott‐X. Chang  Chong‐Bang Zhang  Cheng‐Cai Huang  Jie Chang 《洁净——土壤、空气、水》2013,41(7):657-664

The effects of plant species richness on both above‐ and belowground plant biomass, plant nitrogen (N) pool size, and substrate N concentrations were studied in a full‐scale subsurface vertical‐flow constructed wetland (CW). Results showed that (i) plant species richness increased belowground plant biomass and its N pool size but had no effect on aboveground plant biomass and its N pool size; (ii) plant species richness increased substrate N removal, especially ammonium N removal; and (iii) plant species richness had no effect on plant N use efficiency, suggesting that the N pool size increased with increasing plant species richness. More N accumulation could be removed through harvesting plant biomass. We concluded that the N removal performance of the CW improved by plant species richness through increasing belowground biomass and relevant N pool size.  相似文献   

含富锂(钾)卤水断陷盆地的深部构造特征: 以中国华南吉泰盆地为例          下载免费PDF全文

刘志伟  侯献华  郑绵平  乜贞  司国帅  鹿颖  戴顺铭  李继 《地球科学》2022,47(1):110-121

中国华南吉泰盆地在白垩纪?古近纪发育大量蒸发岩,其中含富锂卤水矿床,由于盆地深部构造特征认识不清,导致富锂卤水矿勘查评价明显滞后.基于盆地东北部泰和坳陷二维地震数据和钻孔资料,经过精细保幅处理和综合构造解释,总结了含富锂卤水矿断陷盆地的深部构造特征.地震剖面和构造属性表明,盆地深部发育错断白垩系的NE-SW走向、NW倾...  相似文献   

Experiments of DSAEF_LTP Model with Two Improved Parameters for Accumulated Precipitation of Landfalling Tropical Cyclones over Southeast China     

秦思  贾莉  丁晨晨  任福民  约翰·L·麦克布莱  李国平 《热带气象学报(英文版)》2022,28(3):286-296

The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.  相似文献   

Numerical modelling of wave overtopping-induced erosion of grassed inner sea-dike slopes     

Tuan Thieu Quang  Hocine Oumeraci 《Natural Hazards》2012,63(2):417-447

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