Estimation of salt storage in the deep lateritic soils of the darling plateau, Western Australia

Soil Research ◽  
1985 ◽  
Vol 23 (4) ◽  
pp. 533 ◽  
Author(s):  
EN Tsykin ◽  
GC Slessar
Keyword(s):  
Western Australia ◽  
Nonlinear Regression ◽  
Soil Salinity ◽  
Salt Content ◽  
Drainage Density ◽  
Regression Equation ◽  
Annual Rainfall ◽  
Regression Equations ◽  
Statistical Relationship ◽  
Drilling Data

The salt content of soils in the principal bauxitic area of the Darling Plateau is broadly known from drilling. Soil salinities averaged over 15 km2 grid blocks bear a strong statistical relationship to a number of easily measured parameters, including distance from the Darling Scarp, mean annual rainfall and drainage density. We have used a nonlinear regression equation (r=0.96) to prepare maps showing soil salinity isopleths estimated with two levels of reliability. Similar regression equations have been used to estimate average soil salt contents over selected depth intervals. These regression equations and maps provide a useful means of estimating average soil salinities in areas where no drilling data are available.

Salt content of lateritic profiles in the Darling Range, Western Australia

Soil Research ◽  
1974 ◽  
Vol 12 (2) ◽  
pp. 63 ◽  
Author(s):  
GM Dimmock ◽  
E Bettenay ◽  
MJ Mulcahy
Keyword(s):  
Soil Salinity ◽  
Agricultural Land ◽  
Surface Soil ◽  
Unit Area ◽  
Salt Content ◽  
Annual Rainfall ◽  
Mining Operations ◽  
Bauxite Mining ◽  
The Past ◽  
Forested Areas

Soil cores from some 40 complete laterite profiles as deep as 40 m in the Darling Range, W.A., have been examined for salt content, and in some cases, pH. The sites cover a range of topographic situations from divides to valley floors, and of rainfall from 560 to 1350 mm per annum. Increases in surface soil salinity and in the salt concentration of water yields following clearing of the native hardwood forest are related to the amounts of soluble salts stored in the lateritic pallid zones. Storage increases as rainfall decreases in all slope situations. In low rainfall areas (<800 mm per annum) the salt stored under unit area of landscape in the profile down to bedrock is five times greater than in high rainfall areas (≫1000 mm per annum). One area with an annual rainfall of 600 mm has an estimated storage of nearly a million kg of total salts per ha and marked increases in surface soil salinity have occurred within 10 years of clearing. Although in the past, increasing soil salinity has mainly affected agricultural land, the present emphasis on bauxite mining in the forested areas of the Darling Range, particularly in the drier parts, poses new problems in revegetating the exposed saline and acid pallid zone clays after mining operations have ceased.

scholarly journals THE RELIABILITY OF FORECASTS IN TRANSPORTATION

Transport ◽  
2002 ◽  
Vol 17 (6) ◽  
pp. 219-222
Author(s):  
Mindaugas Mazūra ◽  
Olga Fadina
Keyword(s):  
Linear Regression ◽  
Correlation Analysis ◽  
Mathematical Models ◽  
Nonlinear Regression ◽  
Empirical Data ◽  
Turnover Rate ◽  
Regression Equation ◽  
Regression Equations ◽  
Linear Regression Equation ◽  
Linear And Nonlinear

Major problems of forecasting the economic characteristics of transportation (i.e. the amount of freight and passengers carried, the turnover rate of freight and passengers, etc. in transportation as a whole and in particular areas using various transport facilities) are demonstrated. Methods for predicting the development of transportation based on multidimensional regression and correlation analysis and realizing mathematical models for choosing linear and nonlinear regression equations, more accurately approximating the empirical data, are presented. The research conducted has demonstrated that the most reliable forecasts may be made when the methods of choosing the proper non-linear regression equation described in Section 2 of the present paper are used.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

scholarly journals Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1535
Author(s):  
Tonggang Fu ◽  
Hui Gao ◽  
Jintong Liu
Keyword(s):  
Soil Salinity ◽  
Subsurface Layer ◽  
Salt Content ◽  
Spatial Prediction ◽  
Northern China ◽  
Sodium Adsorption Ratio ◽  
Interpolation Methods ◽  
Distance Weighting ◽  
Total Salt Content ◽  
Inverse Distance

Numerous methods have been used in the spatial prediction of soil salinity. However, the most suitable method is still unknown in arid irrigation regions. In this paper, 78 locations were sampled in salt-affected land caused by irrigation in an arid area in northern China. The geostatistical characteristics of the soil pH, Sodium Adsorption Ratio (SAR), Total Salt Content (TSC), and Soil Organic Matter (SOM) of the surface (0–20 cm) and subsurface (20–40 cm) layers were analyzed. The abilities of the Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and CoKriging (CK) interpolation methods were compared, and the Root Mean Square Error (RMSE) was used to justify the results of the methods. The results showed that the spatial distributions of the soil properties obtained using the different interpolation methods were similar. However, the surface layer exhibits more spatial heterogeneity than the subsurface layer. Based on the RSME, the nugget/sill value and range significantly affected which method was the most suitable. Lower nugget/sill values and lower ranges can be fitted using the IDW method, but higher nugget/sill values and higher ranges can be fitted using the OK method. These results provide a valuable reference for the prediction of soil salinity.

scholarly journals Empirical Model With Excellent Statistical Properties for Describing Temperature-Dependent Developmental Rates of Insects and Mites

2017 ◽  
Vol 110 (3) ◽  
pp. 302-309 ◽  
Author(s):  
David A. Ratkowsky ◽  
Gadi V. P. Reddy
Keyword(s):  
Nonlinear Regression ◽  
Empirical Model ◽  
Minimum Variance ◽  
Statistical Properties ◽  
Parameter Estimates ◽  
Regression Equations ◽  
Temperature Dependent ◽  
Temperature Range ◽  
Least Squares Estimators ◽  
Development Rates

Abstract Previous empirical models for describing the temperature-dependent development rates for insects include the Briére, Lactin, Beta, and Ratkowsky models. Another nonlinear regression model, not previously considered in population entomology, is the Lobry–Rosso–Flandrois model, the shape of which is very close to that of the Ratkowsky model in the suboptimal temperature range, but which has the added advantage that all four of its parameters have biological meaning. A consequence of this is that initial parameter estimates, needed for solving the nonlinear regression equations, are very easy to obtain. In addition, the model has excellent statistical properties, with the estimators of the parameters being “close-to-linear,” which means that the least squares estimators are close to being unbiased, normally distributed, minimum variance estimators. The model describes the pooled development rates very well throughout the entire biokinetic temperature range and deserves to become the empirical model of general use in this area.

scholarly journals The soil-adjusted vegetation index for soil salinity assessment in Uzbekistan

2020 ◽  
Vol 26 (3) ◽  
pp. 324-333
Author(s):  
Nozimjon Teshaev ◽  
Bunyod Mamadaliyev ◽  
Azamjon Ibragimov ◽  
Sayidjakhon Khasanov
Keyword(s):  
Soil Salinity ◽  
Information Technologies ◽  
Vegetation Index ◽  
Arable Land ◽  
Salt Content ◽  
Secondary Data ◽  
Soil Surface ◽  
Soil Salinization ◽  
Arid Zones ◽  
Agronomic Practices

Soil salinization, as one of the threats of land degradation, is the main environmental issue in Uzbekistan due to its aridic climate. One of the most vulnerable areas to soil salinization is Sirdarya province in Uzbekistan. The main human-induced causes of soil salinization are the insufficient operation of drainage and irrigation systems, irregular observations of the agronomic practices, and non-efficient on-farm water use. All of these causes considerably interact with the level of the groundwater, leading to an increase in the level of soil salinity. The availability of historical data on actual soil salinity in agricultural lands helps in formulating validated generic state-of-the-art approaches to control and monitor soil salinization by remote sensing and geo-information technologies. In this paper, we hypothesized that the Soil-Adjusted Vegetation Index-based results in soil salinity assessment give statistically valid illustrations and salinity patterns. As a study area, the Mirzaabad district was taken to monitor soil salinization processes since it is the most susceptible territory of Sirdarya province to soil salinization and provides considerably less agricultural products. We mainly formulated this paper based on the secondary data, as we downloaded satellite images and conducted an experiment against the in-situ method of soil salinity assessment using the Soil-Adjusted Vegetation Index. As a result, highly saline areas decreased by a factor of two during the studied period (2005–2014), while non-saline areas increased remarkably from a negligible value to over 10 000 ha. Our study showed that arable land suitability for agricultural purposes has been improving year by year, and our research held on this district also proved that there was a gradual decrease in high salt contents on the soil surface and land quality has been improved. The methodology has proven to be statistically valid and significant to be applied to other arid zones for the assessment of soil salinity. We assume that our methodology is surely considered as a possible vegetation index to evaluate salt content in arable land of either Uzbekistan or other aridic zones and our hypothesis is not rejected by this research.

scholarly journals Prediksi Tinggi Badan Ditentukan dari Panjang Rentang Lengan dan Panjang Telapak Kaki Pada Mongoloid Feminina Khususnya Etnis Jawa

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Nur Mujaddidah Mochtar
Keyword(s):  
Clinical Medicine ◽  
Pearson Correlation ◽  
Body Height ◽  
Regression Equation ◽  
The Body ◽  
Regression Equations ◽  
Foot Length ◽  
Arm Span ◽  
Knee Height ◽  
The Mean

Background: There are various circumstances where measurements are not actually possible, replacement parameters can be used to estimate body height. Many characteristics of body height measurement and how to measure it. These include anthropometric measurements that can be used for the identification of medicolegal-forensic processes. Body height in clinical medicine and in the field of scientific research can be easily estimated using various anthropometric parameters such as arm span, knee height, foot length and foot breadth, and others. The arm span and foot length has proved to be one of the most reliable predictors. This study was conducted to estimate of body height from arm span and foot length using the regression equation and to determine the correlation between the body height and arm span and foot length.Methods: This study was conducted at Universitas Muhammadiyah Surabaya with 182 Javanese female students. Stature, arm span and foot length measured directly using anthropometric technique and measuring tape. The data obtained were then analyzed with SPSS version 16. The regression equation was derived for the estimate of body height and the relationship between stature, arm span and foot length determined by the Pearson correlation.               Results: We found that the mean body height of Javanese women was 1534,45 ± 47,623  mm, mean of arm span 1543,25 ± 60,468 mm and the mean of foot length 226,14 ± 9,586 mm. The correlation between stature and arm span was positive and significant (r = 0,715  , p <0,05). The correlation between stature and foot length was positive and significant (r = 0,726 , p <0,05). The correlation between stature and arm span and foot length was positive and significant (r = 0,798, p <0,05).               Conclusion: Body height correlates well with the arm span and foot length so that it can be used as a reliable marker for high estimates using regression equations.

scholarly journals PROBLEMS FOR ANTI-CRISIS ANALYTICAL PROCEDURES OF FINANCIAL STABILITY OF TRADE ENTERPRISES

2020 ◽  
Author(s):  
Ludmila Anipko ◽  
◽  
Irina Klimovych ◽  
Keyword(s):  
Financial Stability ◽  
Regression Equation ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Financial Condition ◽  
Financial Audit ◽  
Analytical Procedures ◽  
Financial Monitoring ◽  
Complex Indicators

Anti-crisis analytical procedures the financial stability of trade enterprises (hereinafter – AP FS) are part of the internal financial audit of economic activity. The system of financial monitoring is practically acceptable for the implementation of AP FS. The developed classification allows to determine the ability of the enterprise to implement AP FS. An analytical method has been developed that allows, based on the analysis of the financial condition and multivariate forecast, to develop measures to ensure the financial stability of the trade enterprise continuously. By interpolation, the study of the current financial situation, and extrapolation – a multivariate forecast, the numerical value of the integrated (complex) indicator that characterizes financial stability is determined by the regression equation, including factors listed in the classification, the significance of which is determined by regression equations. Based on the analysis of the numerical values of the regression coefficients, it is possible to determine the most important factors that affect the financial stability of trade enterprises, and those that have almost no effect on it. Components with significantly small numerical values of the regression coefficients can be generally discarded. This will reduce the number of indicators that affect financial stability and thus, you can reduce the number of components in the regression equation to the two three most important, which allows you to solve the problem of optimization. The expediency of using integrated and complex indicators is shown. The obtained results are only an information basis for the economic administration of the trade enterprise in making management decisions, the formation of long-term plans. The developed approaches to assessing the financial stability of enterprises are universal and can be used for enterprises in other sectors of the economy.

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