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Comparison of different ensemble precipitation forecast system evaluation, integration and hydrological applications

Tang Yehai, Wu Qiang, Soomro Shan-e-hyder, Li Xiang, Sun Yue, Hu Caihong

Acta Geophysica

2023

Vol. 71, no. 1

405--421

The examination and integration of numerical forecast products are essential for using and developing numerical forecasts and hydrological forecasts. In this paper, the control forecast products from 2010 to 2014 of four model data (China Meteorological Administration (CMA), the National Centers for Environmental Prediction (NCEP), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the United Kingdom Meteorological Office (UKMO)) from The Interactive Grand Global Ensemble (TIGGE) data center were evaluated comprehensively. On this basis, a study of runoff forecasting based on multi-model (multiple regression (MR), random forest (RF), and convolutional neural network-gradient boosting decision tree (CNN-GBDT)) precipitation integration is carried out. The results show that the CMA model performs the worst, while the other models have their advantages and disadvantages in different evaluation indexes. Compared with the single-index optimal model, CMA model had a higher root-mean-square error (RMSE) of 18.4%, and a lower determination coefficient (R2 ) of 14.7%, respectively. The integration of multiple numerical forecast information is better than that of a single model, and CNN-GBDT method is superior to the multiple regression method and random forest method in improving the precision of rainfall forecast. Compared with the original model, the RMSE decreases by 13.1 ~27.9%, PO decreases to 0.538 at heavy rainfall, and the R2 increases by 4~15.2%, but the degree of improvement decreases gradually with the increase in rainfall order. The method of multi-model ensemble rainfall forecasting based on a machine learning model is feasible and can improve the accuracy of short-term rainfall forecasting. The runoff forecast based on multi-model precipitation integration has been improved, and NSE increases from 0.88 to 0.935, but there is still great uncertainty about food peaks during the food season.

Evaluation of bearing capacity of multi-span spandrel-braced stone arch bridge based on static load test

Gao Hongshuai, Duan Hourui, Sun Yue, Jian Jiashuo, Zhang Jingyuan, Liu Hongbo

Archives of Civil Engineering

2022

Vol. 68, nr 4

633--651

Stone arch bridge is an important type in the early bridge construction process because of its beautiful shape, material saving and economic rationality. However, stone material will deteriorate after long-term operation, which results in a decrease in strength and bearing capacity of stone arch bridge. The vehicle load is increasing at the same time. Therefore, accurate evaluation of bearing capacity of stone arch bridge is essential to ensure safety. In this article, a three-span open-spandrel stone arch bridge was taken as research object. Firstly, the bridge damages were investigated and analyzed in detail, and bridge service state was evaluated. Then, based on the evaluation results of disease damages and considering stone material deterioration, a refined finite element model of stone arch bridge was established to analyze bending moment, axial force, strain and deformation. Finally, static load test was carried out to test vertical deformation and stress of arch ring, horizontal displacement of pier, settlement of foundation and development of cracks. The results show that static load test is the most accurate method for evaluating bearing capacity of stone arch bridge. The evaluation accuracy of finite element model based on material correction is in the middle, and the evaluation accuracy of disease damage assessment is the worst. In practical work, bearing capacity of stone arch bridge can be evaluated by combining the three methods with high accuracy and comprehensive results.

Degradation of toluene using UV/hydrogen peroxide process

Cai Shaokang, Sun Yue, Gao Canzhu, Li Pengfei, Cheng Zhongfa

Environment Protection Engineering

2021

Vol. 47, nr 1

5-15

Toluene in wastewater is volatile and difficult to degrade, and the longer it stays in the water, the higher is the risk. An advanced oxidation process (AOPs) has been used to degrade toluene rapidly and efficiently in wastewater by using ultraviolet light and hydrogen peroxide. Toluene in solution (initial concentration – 180 mg/dm3) with hydrogen peroxide (H2O2 dose – 2022 mg/dm3) was almost decomposed within 150 min. pH as well as the presence of various ions in waste water did not affect the degradation process. However, under strongly acidic conditions (pH less than 3), the chloride ions reduced the degradation efficiency of toluene. Based on the UV spectrophotometer and GC-MS analyses, the degradation pathways were observed: first, the methyl group was oxidized leading to the generation of benzoic acid, the benzene ring was subsequently opened by the action of hydroxyl radical, followed by the gradual decomposition of the intermediate products into small molecules such as water and carbon dioxide.