Contribution Rate Of Factors Research Articles

Improvements in the InVEST water purification model for detecting spatio-temporal changesintotal nitrogen and total phosphorus discharges in the Huai river watershed, China

Improving water quality to provide freshwater is an urgent requirement for regional and even global social development. More accurate simulation of non-point sources pollution, monitored mainly by total nitrogen (TN) and total phosphorus (TP), has always been a challenge for InVEST water purification model, particularly in agricultural areas. This can be attributed to the fact that there is no reference data for TN and TP to rectify the outcomes modelled by this model. This paper provided these data to rectify simulation results of TN and TP to ensure their accuracy. The Huai River watershed (HRW) is an important grain production area with slow economic development, and non-point source pollution has exceeded point-source pollution. There is an urgent need for water management authorities to obtain complete spatio-temporal data on TN and TP loads and their exports to improve water quality. The reference data onloads and exports of TN and TP were estimated for the entire watershed and its sub-watersheds through an investigation-evaluation technique during 1980–2018. TN and TP loads generated from the agricultural sector were the major pollution sources in the HRW and had similar time trends during the same period. The spatial distribution of TN and TP exports was modelled byusingthe InVEST water purification model, and it was found that the temporal trends for the final exports of TN and TP into river systems were similar to those for TN and TP loads in the HRW for 1980–2018. Key driving factors were detected using the Geo-detector method to quantify the contribution rates of factors to the spatiotemporal exports of TN and TP. Our results showed that individual factors, such as precipitation and land use/cover, were the most important factors driving spatio-temporal variations in TN and TP exports in the HRW from 1980 to 2018. Meanwhile, the contribution rates of interactions between land use/cover and other factors were consistently highest in this watershed during the same period. In this study, we estimated the loads and exports of TN and TP, and modelled their spatial patterns in this watershed from 1980 to 2018, providing important information on TN and TP for water-related management authorities. We also provide a method for other river systems to calibrate the parameters in the biophysical table of InVEST water purification model based on final exports of TN and TP.

Construct validity of the simplified Chinese version of the instrument ‘Picture My Participation’

Background Preliminary evidence of the content validity of the simplified Chinese version of ‘Picture My Participation’ (PMP-C; Simplified) items and reliability of the subscale attendance for the effectiveness of the use with children and youth in mainland China has been collected. However, evidence of construct validity for the instrument is not yet available. Aim To explore the construct validity of the attendance scale in PMP-C (Simplified). Methods A cross-sectional study using convenience sampling was conducted using PMP-C (Simplified) with a picture-supported interview for 290 children and youths aged 5–21 with and without ID in urban and rural areas of mainland China. Exploratory factor analysis (EFA) was performed using the principal component analysis (PCA) to analyse the resulting data. Results The EFA extracted five factors with eigenvalues greater than one and the cumulative contribution rate of factors accounted for 51.62% of the variance. All items had factor loadings above 0.50. The five subcomponents included: organised activities, social activities, taking care of others, family life activities and personal care and development activities. Conclusion The results of the factor analysis support the construct validity of the PMP-C (Simplified) attendance scale. It provides further psychometric evidence that PMP-C (Simplified) is a sound measure to assess participation for children and youths in mainland China.

青藏高原牧区家庭能源消费对生态环境和人体健康的影响研究现状与展望

PDF HTML阅读 XML下载 导出引用 引用提醒 青藏高原牧区家庭能源消费对生态环境和人体健康的影响研究现状与展望 DOI: 10.5846/stxb202202190395 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（72174197，41901241，71904189）；第二次青藏高原综合科学考察研究项目（2019QZKK0304） Research status and prospect of household energy consumption impact on eco-environment and human health in the pastoral of Qinghai-Tibet Plateau Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:探究家庭能源消费对生态环境和人体健康的研究是系统推进家庭能源绿色低碳转型和实现联合国2030可持续发展目标的关键。重点综述了目前家庭能源消费、影响因素及其对生态环境和居民健康影响的国际研究现状。目前研究不足主要聚焦在以下两个方面：一方面，影响家庭能源消费因素的贡献率和影响消费行为的驱动机制尚不清晰；另一方面，目前主要针对家庭能源消费或者生态系统或者环境或者居民健康其中的某一方面或者某两个方面开展研究，鲜有研究系统的考虑家庭能源消费对生态环境和人体健康影响的综合研究。基于上述研究现状，结合青藏高原的实际情况，提出未来需要在宏观层面和微观层面加强研究。宏观层面：（1）亟需厘清青藏高原家庭能源与生态环境和人体健康之间的内在联系与驱动机制，形成青藏高原牧区"家庭能源-生态效应-环境效应-健康效应"的理论分析框架；（2）构建模块化的牧区"能源-生态-环境-健康-经济"等多学科交叉的综合评估模型，形成完整的、系统的评估方法。微观层面：（1）迫切开展青藏高原家庭能源消费特征与变化规律的研究；（2）深入开展家庭能源消费特征和变化规律与生态系统的反馈机制与量化研究；（3）加强牧区室内空气污染物浓度测定，丰富高寒地区室内污染物浓度数据以及人群暴露特征及其健康风险的研究。 Abstract:Exploring the household energy consumption and its impacts on eco-environment and human health is essential to promote the green and low-carbon transition of household energy system and achieve the 2030 United Nations Sustainable Development Goals. This paper presents a review on the state of the art for the domestic and international research on the factors that influencing the household energy consumptions and the impacts on eco-environment and residents' health. At present, particular attention should be given to the following two research deficiencies. On one hand, the contribution rate of factors that influencing the household energy consumption and the mechanism that driving the consumption behavior are not well understood; on the other hand, the comprehensive studies that systematically consider the correlations among household energy consumption, ecological environment and human health are still lacking. Based on the research status and the actual situation of Qinghai-Tibet Plateau, this paper strengthens the study of household energy consumption and its impact on eco-environment and human health through macro level and micro level. On the macro level, we need to (1) clarify the correlation and driving mechanism between household energy, grassland ecology and human health and form the theoretical framework for analysis in the pastoral region of Qinghai-Tibet Plateau; (2) build a comprehensive modular assessment method around the energy-ecology-environment-health-economy nexus. On the micro -level, we should (1) carry out the research on the characteristics and dynamics changes of household energy consumption on the Qinghai-Tibet Plateau; (2) establish and quantify the feedback mechanism between household energy consumption and ecosystem; (3) strengthen the measurement of indoor air pollutant concentration in the pastoral areas and complete the data collection on the exposure characteristics and the associated health risks for the residents living in the alpine areas. 参考文献 相似文献 引证文献

Utility of Deep Learning Algorithms in Initial Flowering Period Prediction Models

The application of a deep learning algorithm (DL) can more accurately predict the initial flowering period of Platycladus orientalis (L.) Franco. In this research, we applied DL to establish a nationwide long-term prediction model of the initial flowering period of P. orientalis and analyzed the contribution rate of meteorological factors via Shapely Additive Explanation (SHAP). Based on the daily meteorological data of major meteorological stations in China from 1963–2015 and the observation of initial flowering data from 23 phenological stations, we established prediction models by using recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU). The mean absolute error (MAE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were used as training effect indicators to evaluate the prediction accuracy. The simulation results show that the three models are applicable to the prediction of the initial flowering of P. orientalis nationwide in China, with the average accuracy of the GRU being the highest, followed by LSTM and the RNN, which is significantly higher than the prediction accuracy of the regression model based on accumulated air temperature. In the interpretability analysis, the factor contribution rates of the three models are similar, the 46 temperature type factors have the highest contribution rate with 58.6% of temperature factors’ contribution rate being higher than 0 and average contribution rate being 5.48 × 10−4, and the stability of the contribution rate of the factors related to the daily minimum temperature factor has obvious fluctuations with an average standard deviation of 8.57 × 10−3, which might be related to the plants being sensitive to low temperature stress. The GRU model can accurately predict the change rule of the initial flowering, with an average accuracy greater than 98%, and the simulation effect is the best, indicating that the potential application of the GRU model is the prediction of initial flowering.

Influence of irrigation and groundwater on the propagation of meteorological drought to agricultural drought

Research on drought propagation is of great significance for the scientific prediction of agricultural drought and reducing drought losses. In this study, based on the daily scale standardized precipitation evapotranspiration index (SPEI) and soil water deficit index (SWDI), the effects of irrigation and groundwater level change on the development and spread of drought were studied, and the dynamic change in the spread time from meteorological drought to agricultural drought was explored through a sliding window. Additionally, the critical value of the response of agricultural drought to meteorological drought was calculated. The results indicated that (1) under Scenario-1 (groundwater depth 19.4 m, no irrigation), Scenario-2 (groundwater depth 2 m, no irrigation), and Scenario-3 (groundwater depth 19.4 m, irrigation), the lag times of agricultural drought on meteorological drought were 23 d, 42 d, and 30 d, respectively. (2) The drought propagation time under Scenario-1 and 2 exhibited a significant upwards trend. According to the factor contribution rate and cross-wavelet analysis, the rising trend of the Arctic Oscillation (AO) and the decreasing trend of the Pacific Decade Oscillation (PDO) led to the shortening of sunshine duration, which was the key reason for the extension of drought propagation time. (3) Under Scenario-1, the critical values of the agricultural drought response to meteorological drought duration and intensity were 4.9 and 0.9, respectively. Under Scenario-2, the critical values increased to 5.1 and 2.0, revealing that the propagation of meteorological drought to agricultural drought would slow down when groundwater rose to an appropriate position.

Numerical investigation for optimization of spark-ignition internal combustion engine knock by Taguchi-Grey method.

This article carried out a numerical investigation of knock, using the Taguchi method and the grey relational analysis method to determine the importance and the contribution rate of multiple parameters on the peak pressure in the cylinder and the knock tendency under heavy load conditions. Four parameters, namely, compression ratio, spark timing, EGR rate, and inlet temperature, were set at four levels. The simulation was designed using a design of experiment method based on Taguchi's L16 orthogonal array. The simulation results of knock tendency and peak in-cylinder pressure were analyzed by the Taguchi-Grey method. According to the analysis results of the Taguchi-Grey method, the optimal level, the importance rank, and the contribution rate of factors on the knock tendency, peak in-cylinder pressure, and equivalent response were determined. The results demonstrate that the contribution rate of compression ratio, spark timing, EGR rate, and inlet temperature to the knock tendency is 45.9%, 22.98%, 19.46%, and 11.66%, respectively. The compression ratio, spark timing, EGR rate, and inlet temperature contribution to the peak in-cylinder pressure is 40.56%, 31.03%, 24.94 and 3.47%, respectively. The optimal conditions for the minimum knock tendency and the maximum peak in-cylinder pressure are obtained at CR1EGR4IT1ST1 and CR4EGR1IT1ST4, respectively.

Measurement and Analysis of Contribution Rate for China Rice Input Factors via a Varying-Coefficient Production Function Model

To explore the internal driving force of the growth of rice yield per unit area in China, a model based on varying-coefficient production function is proposed in this study, which comes from the idea that the constant elasticity parameters in the Cobb-Douglas production function can be extended to functional forms. Applying such model to economic growth analysis, on the one hand, the dynamic contribution rate of each input factor can be measured, and, on the other hand, the contribution rate of the input factor can be decomposed into net factor contribution rate and interaction factor contribution rate, thus expanding the explanatory ability of growth rate equation. Using such model, the output elasticity of capital and labor in China’s rice yield growth are calculated from 1978 to 2020, and the dynamic characteristics of the contribution rate of capital, labor and generalized technological progress are analyzed. Next, the capital contribution rate is decomposed according to the composition of the total capital. The results show that: (1) The capital elasticity and labor elasticity are indeed not constant in different years. In China, from 1978 to 2020 the value of capital elasticity was between 0.3209 to 0.3589, with a mean of 0.3437, and the value of labor elasticity was between −0.1759 to −0.1640, with a mean of −0.1730. (2) Natural disasters do affect capital elasticity and labor elasticity in rice production. (3) When the annual proportion of crop disasters increases, the contribution rate of interaction between capital and natural disaster (KDR) value is negative, whereas the contribution rate of interaction between labor and natural disaster (LDR) value is positive. (4) Compared with 1978, the generalized technological progress contribution rate (GTPR) of the rice yield growth in China from 1979 to 2020 shows a declining trend in fluctuations, whereas the total capital contribution rate (TKR) shows a rising trend in fluctuations and the total labor contribution rate (TLR) is relatively stable in the same period. Since 2000, capital investment has become the main factor for the rice yield growth per unit area in China, of which machinery, chemical fertilizer, seed and pesticide are the four most important input factors.

The chromium migration risk from tannery sludge into shallow soil and groundwater: Influence factors, modeling, and microbial response

Combined pollution in tannery sludge landfill has become increasingly serious. Accurate identification of the contribution of coexisting substances to Cr migration in tannery sludge sites was essential for the selection of remediation methods for tannery contaminated sites. However, the effect of the coexisting substances on their contribution to Cr migration remained unclear. In this study, the analytical method of panel data and soil column experiments were combined for the first time to quantify the extent to which different contaminants contribute to Cr migration, and further identify the dominant microbial species. Results showed that NH3–N inhibited the migration of Cr(VI), while NO3––N and fatliquor agent promoted the migration of Cr(VI). The panel data analysis showed that the order of the contribution rate of the factors affecting the Cr(VI) migration was Cr(VI) concentration, coexisting substances, and environment factors. In addition, Veronii was the dominant popular in fatliquors-contaminated soils. The relative abundance of Veronii increased from 6.31% to 30.48% in the fatliquors treatment group, while it decreased to 21.65% in the fatliquors and Cr treatment group. This study provided a quantitative method to the contribution rate of various factors to Cr migration under rainfall, taken into account the response of the microbial community in each experimental group, and provided theoretical support for the selection of remediation methods in soil and groundwater for tannery sites.

Study on the path of Xi Jinping's ecological view for the high quality development of islands

PurposeThe island areas, in particular, are characterized by a more fragile ecological carrying capacity and higher value of resources and environment, which requires us to take Xi Jinping's green ecological development view as the theoretical basis and adhere to the high-quality development path of gradual development and ecological environment priority. Taking Shengsi and Daishan counties as examples, on the basis of their high-quality development evaluation and identification of the main influencing factors, this study explores the specific path of Xi Jinping's ecological development view in the high-quality development of typical island counties in China.Design/methodology/approachThis paper applies the interpretative structural model to construct an evaluation index system for the high-quality development of the island. In determining the factor weights of the index layer, the AHP hierarchical analysis method was combined with the Delphi method to increase the objectivity of the assignment process as much as possible. This study used the technique for order of preference by similarity to ideal solution to calculate island high quality development index. To measure the main obstacle factors, the index factor contribution rate, the index factor deviation, and the index factor obstacle degree were applied in this research.FindingsThe study is supported by Guangxi Key Laboratory of Marine Environmental Science, Guangxi Academy of Sciences (GXKLHY21-04), Special Funds for Fundamental Scientific Research Operation of Central Universities (202113011), Shandong Provincial Social Science Planning Research Youth Project (21DSHJ2) and Tianjin Philosophy and Social Science Planning Project of China (No. TJKS20XSX-015).Originality/valueThe connotation and extension of Xi Jinping's view of ecological development should be continuously studied in depth and enriched, with green development as the core idea to guide the correct direction of the high-quality development of the island. In this paper, it is suggested that researchers are supposed to focus on these problems, such as the changes of sea water quality, the reduction of urban greening, the continuous negative growth of population in island areas, the decline of forestry added value and air quality protection, so as to ensure the sustainable high-quality development of example islands.

Does Rural Production–Living–Ecological Spaces Have a Preference for Regional Endowments? A Case of Beijing-Tianjin-Hebei, China

Production–Living–Ecological Space (PLES) is the functional projection of sustainable development in territory spatial planning. Its rational layout has become the most important task for developing countries to enhance ecological awareness and achieve sustainable goals. This study took the rural areas of Beijing-Tianjin-Hebei (BTH) as an example to analyze the relationship by means of quantitative cumulation between regional endowments (natural factors, location and facilities) and PLES to figure out the preference mechanism. The Boosted Regression Tree model (BRT) was used to obtain the contribution rate of factors and the internal marginal effect between 1980~2018. Our conclusions are as follows: Living space (LS) enjoyed the highest advantage of regional endowment level, followed by production space (PS). Except for the distance to water, other indicators were significantly different in the PLES, and the suitable range of various types was expanded from LS to PS and ecological space (ES). During the transfer, elevation had a universal effect. The process of increasing naturalness was affected by the distance of high-level urban areas, which verified the continuous effect of Chinese ecological civilization. This study clarified the selectivity of regional endowments to PLES, which will greatly guide the direction of regional territory spatial planning and the next step of regional sustainable development.

Potential interaction effect on obesity between sleep duration and dietary patterns in preschool children in Bengbu City in 2018-2019

To examine the interaction effect between sleep duration and dietary patterns on obesity, in order to explore the possible risk factors for preschool children's obesity. During September of 2018 to March of 2019(1148 boys and 981 girls, 1199 living in urban and 930 living in rural, 756 only child and 1373 not only child), a total of 2129 preschool children used two-stage cluster sampling method from 22 kindergartens aged 3-6 years old were investigated. Social-demographic information(included sex, age, only child or not, left-behind children or not, economic status of family, parents 'cultural level and caregivers' information), sleep duration and dietary intake were collected through "Sleep Duration and Physical Development Questionnaire(SDPDQ) of children aged 3-6 years old in Bengbu city". Factor analysis was applied to determine major dietary patterns, unconditional Logistic regression was used to analyze the multiplication interaction effect between sleep duration and dietary patterns on obesity. Four dietary patterns-"traditional", "animal", "calcium" and "snack" were identified in our study by principal component analysis. The factor contribution rate of the four dietary patterns was 16. 568%, 11. 462%, 7. 317% and 4. 562%, respectively, the total variance was 39. 909%. Among the preschool children, the prevalence of overweight and obesity were 18. 0%(n=383) and 10. 5%(n=223), respectively. After controlling the confounding factors, the shorter sleep duration(OR=1. 25, 95%CI 1. 07-1. 72), scores in the top quintile of "animal" pattern(OR=1. 32, 95%CI 1. 15-1. 54) and "snack" pattern(OR=1. 46, 95%CI 1. 16-1. 78) showed greater odds with the prevalence of overweight/obesity among preschool children. Both multiplication and additive interactions were observed between levels of low sleep duration and animal dietary pattern with overweight/obesity(OR=1. 23, 95%CI 1. 16-1. 32). Multiplication interaction was observed between lower sleep time and the snack dietary pattern(OR=1. 16, 95%CI 1. 09-1. 24), with RERI, AP and SI was 0. 38, 0. 20 and 1. 24, respectively. However, neither multiplication interaction or additive interaction was noticed between sleep duration and the traditional dietary pattern, the calcium dietary pattern with OR=0. 76(95%CI 0. 51-1. 11) vs. OR=1. 04(95%CI 0. 65-1. 73), respectively. Levels of low sleep duration presented a risk factor for overweight/obesity in preschool children. Both multiplication and additive interactions were observed between low sleep time and the animal dietary pattern. Multiplication interaction was noticed between children's sleep duration and the snack dietary pattern.

Quantitative analysis of the factors influencing the dispersion of thermal pollution caused by coastal power plants

In recent years, to meet the needs of economic development, an increasing number of coastal nuclear power plants and thermal power plants (CNATPPs) have used seawater as the source and sink of cooling water. Considering six CNATPPs along the coast of China, based on the model of conservation of mass and energy for an environmental fluid medium, this study quantitatively evaluates the thermal diffusion capacity (TDC) and contribution rate of factors influencing the thermal plume. The results showed that (1) the current velocity, shoreline topography and horizontal diffusion coefficient are linearly correlated with the TDC. The former two variables were the same and the largest and are highly sensitive parameters; (2) the average contribution rates of the current velocity and shoreline topography were the largest at 0.32, and that of the water depth ranged from 0 to 0.28; (3) the shoreline topography close to the outfall affects the TDC of the emitting source of CNATPPs, rather than the geographical location; and (4) this study can provide a comprehensive measurement tool for the planning, site selection and layout of CNATPPs to reduce the impact of their thermal pollution on aquatic organisms in the receiving water. Considering the TDC and thermal sensitivity of marine organisms, it might be assumed that the same heat and the same volume of thermal pollution may have smaller impacts on marine organisms in the East China Sea than in the South China Sea.

Application of a modified CES production function model based on improved firefly algorithm

The conventional CES production function model fails to consider the influences of policy factors on economic growth in different stages. This paper proposes a modified model of the CES production function. Regarding model parameter estimation, the paper proposes a modern intelligent algorithm, the firefly algorithm (FA). The paper improves conventional FA to enhance the convergence rate and precision. To overcome the shortcomings of the conventional method in model application, the paper presents a new method of calculating the contribution rates of factors influencing economic growth and provides examples.

A Grey CES Production Function Model and Its Application in Calculating the Contribution Rate of Economic Growth Factors

In analyses of economic growth factors, people generally use the CES (Constant Elasticity of Substitution) production function model to calculate the contribution rates of the factors that influence economic growth. However, the traditional CES function model that is built directly from economic data often shows apparent errors in parameter estimation due to data fluctuations. Such a model also may cause a negative calculation of the contribution rates of economic growth factors, or it may create abnormal fluctuations for some periods, and thus it fails to meet economic growth laws. In this paper, we propose a grey CES production function that can eliminate the random fluctuations of data and make the estimated parameters more reasonable, and this model can reflect the relationship between inputs and outputs more accurately. With regard to model application, the paper puts forward a scientific calculation method to avoid the calculation deviations caused by the substitution of difference equation for a differential equation with Solow’s formula. With the grey two‐level nested CES production function model and the calculation method proposed, the paper makes an empirical analysis of the contribution rates of factors that influence China’s economic growth.

Parameter Estimation of a Mixed Production Function Model Based on Improved Firefly Algorithm and Model Application

Abstract In the analysis on economic growth factors, researchers usually use the production function model to calculate and measure influencing factors’ contribution rates to economic growth. Common production functions include the CD (Cobb-Douglas) production function, the CES (Constant Elasticity of Substitution) production function, the VES (Variable Elasticity of Substitution) production function, and so on. In consideration of the diversity and complementarity of models, the paper combines the CD production function with the CES production function and then proposes a mixed production function. With regard to the parameter estimation of model, the paper gives an improved firefly algorithm with the high precision and a fast rate of convergence. With regard to the calculation of factors’ contribution rates, traditional methods generally have big errors and are not applicable to complicated models, so the paper offers a new method which can calculate contribution rates scientifically. Finally, the paper calculates the contribution rates of factors affecting Chinese economic growth and gets a good result.

A novel assessment of urbanization quality and its applications

By establishing a network with related indices in urban system as nodes, urbanization quality can be defined as the structural features of the network. According to maximum information entropy principle (MIEP), structural parameter ξ of the index network and its dynamic equation have been derived. The dynamic equation can be calculated by self-organizing feature map (SOFM) artificial neural network algorithm in MATLAB platform. In this way, a new index network model (INM) of urbanization quality assessment (UQA) is constructed. The new INM is applied to the UQA of 37 major cities in China. Values of ξ quantitatively give the rank of the cities, which show that Shenzhen, Beijing and Suzhou have the highest quality scores more than 10 both in 2010 and 2014, reflecting much higher urbanization quality than other cities. The following cities are Xiamen, Tianjin, Nanjing, Hangzhou etc., then Chengdu, Zhengzhou, Shenyang and Tangshan etc. The quality scores of Guiyang, Kunming and Chongqing etc. are the lowest. With Xi’an and Wenzhou as sample cities, the contributions of each index to the urbanization quality are simultaneously revealed. Based on the structural parameter ξ of each mesoscope indexes derived from the new INM, we use the analysis method of factor contribution rate to reveal the contributions of each index to the urbanization quality. By recognizing the key factors, which influence the urbanization quality, the new INM can guide us take targeted measures for the improvement of urbanization quality. Beyond the application cases given, we finally state that the new INM is very universal and advantageous, which can be conveniently applied to the UQA of many other cities.

Empirical Analysis on Contribution Rate of Factors of Production on China Oil and Gas Industry - Based on Provincial Panel Data

Empirical Analysis on Contribution Rate of Factors of Production on China Oil and Gas Industry - Based on Provincial Panel Data

Quantifying the Contribution of Sediment Load to Soil Detachment Rate by Sediment‐Laden Rill Flow

Core Ideas A standardization‐based method was adopted to quantify the contribution rate. The experiment was specifically designed to isolate the effect of sediment load on detachment rate. The negative contribution of sediment load on detachment rate was almost one‐third of the total. This study aimed at rill erosion of loessial soil. Sediment load changes with downslope distance during rill erosion process, and thus quantifying the potential contribution of sediment load on soil detachment rate is essential to accurately model the rill erosion process. A standardization‐based method was adopted to quantify the contribution for the first time, and the rill flume with a soil‐feeding hopper was specifically designed to insulate the effect of sediment load on detachment rate. Loessial soil was quantitatively fed into rill flow to produce different sediment loads. Seven flow discharges were combined with six slopes. Soil detachment rate was measured for each combination under five sediment loads (10, 25, 50, 75, and 90% of the sediment transport capacity, respectively). The results showed that soil detachment rate by sediment‐laden rill flow decreased linearly with the increase in sediment load. Stream power is the best hydrodynamic parameter in relation to the detachment rate under different sediment loads compared with shear stress and unit stream power. The comprehensive response relationship of soil detachment rate to sediment load and stream power is a binary linear equation (R2 = 0.9482). The contribution rate of sediment load to soil detachment rate is 30.43% and that of stream power is 64.39%. The negative effect of sediment load on soil detachment rate accounts for almost one‐third of the total contribution. It is important to draw sediment load as a negative factor into process‐based rill erosion model. This study can provide a feasible way for researchers to quantify the contribution rate of factors and can help to understand rill erosion process sufficiently.

Application of a New Superposition CES Production Function Model

Abstract In the analysis on economic growth factors, calculating the contribution rate of influencing factor to economic growth using the CES production function model is a common and important research field. The CES production function model has a variety of forms, and the superposition CES production function model proposed in the paper is a new model. With regard to the model’s parameter estimation, the paper proposes a modified particle swarm optimization which has a fast convergence rate and a high precision. With regard to the calculation of factor contribution rate, the paper offers a new scientific calculation method with the superposition CES production function model. At last, the paper makes an empirical analysis on the contribution rate of Chinese economic growth factors and the result obtained consists with the reality.

Parameter estimation of a composite production function model based on improved artificial fish swarm algorithm and model application

ABSTRACTThe traditional Cobb–Douglas production function uses the compact mathematical form to describe the relationship between the production results and production factors in the production technology process. However, in macro-economic production, multi-structured production exists universally. In order to better demonstrate such input–output relation, a composite production function model is proposed in this article. In aspect of model parameter estimation, artificial fish swarm algorithm is applied. The algorithm has satisfactory performance in overcoming local extreme value and acquiring global extreme value. Moreover, realization of the algorithm does not need the gradient value of the objective function. For this reason, it is adaptive to searching space. Through the improved artificial fish swarm algorithm, convergence rate and precision are both considerably improved. In aspect of model application, the composite production function model is mainly used to calculate economic growth factor contribution rate. In this article, a relatively more accurate calculating method is proposed. In the end, empirical analysis on economic growth contribution rate of China is implemented.