Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
The welding residual stress has different effects on the mechanical properties of aluminum alloy welded joints, such as size stability, fatigue strength and stress corrosion cracking. Therefore, it is very important to evaluate the welding residual stress accurately. In this paper, the residual stress of A7N01 aluminum alloy welded joints was measured by X-ray diffraction. In contrast to the traditional method, the cos[Formula: see text] method was used in this paper, the results were compared with those obtained by the conventional [Formula: see text] method. In addition, the influence of oscillation unit on the test results of the cos[Formula: see text] method was studied.
In the last two decades, machine learning (ML) methods have been widely used in digital soil mapping (DSM), but the regression kriging (RK) model which combines the advantages of the ML and kriging methods has rarely been used in DSM. In addition, due to the limitation of a single-model structure, many ML methods have poor prediction accuracy in undulating terrain areas. In this study, we collected the SOC content of 115 soil samples in a hilly farming area with continuous undulating terrain. According to the theory of soil-forming factors in pedogenesis, we selected 10 topographic indices, 7 vegetation indices, and 2 soil indices as environmental covariates, and according to the law of geographical similarity, we used ML and RK methods to mine the relationship between SOC and environmental covariates to predict the SOC content. Four ensemble models—random forest (RF), Cubist, stochastic gradient boosting (SGB), and Bayesian regularized neural networks (BRNNs)—were used to fit the trend of SOC content, and the simple kriging (SK) method was used to interpolate the residuals of the ensemble models, and then the SOC and residual were superimposed to obtain the RK prediction result. Moreover, the 115 samples were divided into calibration and validation sets at a ratio of 80%, and the tenfold cross-validation method was used to fit the optimal parameters of the model. From the results of four ensemble models: RF performed best in the calibration set (R2c = 0.834) but poorly in the validation set (R2v = 0.362); Cubist had good accuracy and stability in both the calibration and validation sets (R2c = 0.693 and R2v = 0.445); SGB performed poorly (R2c = 0.430 and R2v = 0.336); and BRNN had the lowest accuracy (R2c = 0.323 and R2v = 0.282). The results showed that the R2 of the four RK models in the validation set were 0.718, 0.674, 0.724, and 0.625, respectively. Compared with the ensemble models without superimposed residuals, the prediction accuracy was improved by 0.356, 0.229, 0.388, and 0.343, respectively. In conclusion, Cubist has high prediction accuracy and generalization ability in areas with complex topography, and the RK model can make full use of trends and spatial structural factors that are not easy to mine by ML models, which can effectively improve the prediction accuracy. This provides a reference for soil survey and digital mapping in complex terrain areas.
Since soil general survey for the second time in Huaxian County ,the investigation results for four time on topsoil nutrients show that topsoil nutrients is wholly increasing trend ;the change of content of soil nutrients is mainly affected from by soil texture in the second soil general survey to by manmade farming fertilization In the year circulation of nutrients of soil and crop system ,soil nitrogen and phosphorus is wholly in the profit state ,While soil potassium in the wane state To increase application of organic manure and fertilization will put up the content of soil nutrients and keep soil fertility stable
近二十年的水质监测资料研究分析表明,抚仙湖生态系统相当脆弱,出现了加速富营养化趋势,浮游藻类数量增加了2.6倍,Chl.a含量增加了3倍,透明度减小了将近一半,综合营养状态指数呈急剧上升,揭示了发生富营养化的危险性. 促进因素主要有外来污染增加,氮、磷等营养盐在湖内迅速积累,湖泊生态系统过于简单、脆弱等因素. 呼吁加大对抚仙湖污染防治的力度,防患于未然.;Fuxian Lake is a deep lake with a capacity of 184×108 m3. Based on the incessant monitoring statistics during 1980-2000, the water quality as well as the eutrophication status was revealed in Fuxian Lake,.i.e. the phytoplankton density increased 2.6 times, Chl.a 3 times while SD decreased~50%. Comprehensive assenssment of nutrient status and evolution during the past 20 years indicated that a sharp growth of TSI would bring out a potential possibility and danger of eutrophication which has compelled us to take some efficient, effective measures to protect the lake from further deterioration or invaluable lose both economically and ecologically in the future would be seen.
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