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Saturday, November 28, 2020 | History

2 edition of Geostatistical applications to salinity mapping and simulated reclamation found in the catalog.

Geostatistical applications to salinity mapping and simulated reclamation

Mohamad A. Taher

Geostatistical applications to salinity mapping and simulated reclamation

  • 74 Want to read
  • 17 Currently reading

Published .
Written in English

    Subjects:
  • Soil salinization.,
  • Soils, Salts in -- Mathematical models.,
  • Soil mapping -- Statistical methods.

  • Edition Notes

    Statementby Mohamad A. Al-Taher.
    The Physical Object
    Pagination132 leaves, bound :
    Number of Pages132
    ID Numbers
    Open LibraryOL15205192M

    The objectives of this study were to investigate the degree of spatial variability and variance structure of salinization parameters using classical and geostatistical method in Songnen Plain of China, which is one of largest saline-sodic areas in the World, and to analyze the relationship between salinization parameters, including soil salinity content (SC), electrical conductivity (EC Cited by: Castro MC, Singer BH. Controlling the false discovery rate: A new application to account for multiple and dependent tests in local statistics of spatial association. Geogr Anal. ; – Carranza EJM. Mapping of anomalies in continuous and discrete fields of stream sediment geochemical landscapes. Geochem Explor Environ Anal. Cited by: 2.


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Geostatistical applications to salinity mapping and simulated reclamation by Mohamad A. Taher Download PDF EPUB FB2

Geostatistical methods were used to find efficient and accurate means for salinity assessment using regionalized random variables and limited sampling. The random variables selected, sodium absorption ratio (SAR), electrical conductivity (EC), and clay content were measured on samples taken over an area of fifteen square : Mohamad A.

Al-Taher. Geostatistical applications to salinity mapping and simulated reclamation. Abstract. Graduation date: Geostatistical methods were used to find efficient and accurate means for\ud salinity assessment using regionalized random variables and limited sampling.

The\ud random variables selected, sodium absorption ratio (SAR), electrical. The papers assembled here cover topics such as technological advances in soil salinity mapping and monitoring, management and reclamation of salt-affected soils, use of marginal quality water for crop production, salt-tolerance mechanisms in plants, biosaline agriculture and agroforestry, microbiological interventions for marginal soils, opportunities and challenges in using marginal waters.

As we saw in the previous chapter, there are many geostatistical techniques that can be used to map environ-3 mental variables. In reality, we always try to go for the most flexible, most comprehensive and the most robust 4 technique (preferably implemented in a software with an user-friendly GUI).

In fact, many (geo)statisticians 5. In order to implement efficient agronomic and environmental management, as well as soil reclamation programs to prevent any further salinization of agricultural lands, accurate soil salinity.

Developments in Soil Salinity Assessment and Reclamation pp () Spatiotemporal Variability and Mapping of Groundwater Salinity in Tadla: Geostatistical Approach. In: Shahid S., Abdelfattah M., Taha F. (eds) Developments in Soil Salinity Assessment and Reclamation.

Cited by: 3. Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary information and a computer program that generates predictions.

The purpose of this guide is to assist you in producing quality maps by using fully-operational open source software packages: R+gstat/geoR and SAGA GIS. Developments in Soil Salinity Assessment and Reclamation The papers assembled here cover topics such as technological advances in soil salinity mapping and monitoring, management and reclamation of salt-affected soils, use of marginal quality water for crop production, salt-tolerance mechanisms in plants, biosaline agriculture and.

Geostatistical mapping can be defined as analytical production of maps by using field observations, auxiliary information and a computer program that calculates values at locations of interest. Geostatistical methods to identify and map spatial variations of soil salinity.

This study has elucidated the spatial correlations and variations in soil measures related to salinity. The results of the geostatistical analyses can be applied in making decisions regarding environmental monitoring, remediation, land management and planning.

Cited by:   Kriging with external drift (KED) is a valuable technique for improving the mapping of the shallow watertable but has received little application in salinity management.

It is a geostatistical. 4 Mapping Horizontal and Vertical Spatial Variability 37 electrical conductivity of 10 mS/m for both layers, a depth of m for the fi rst upper layer, and a depth of m for the bottom.

Published inthe first edition of Geostatistical Reservoir Modeling brought the practice of petroleum geostatistics into a coherent framework, focusing on tools, techniques, examples, and guidance. It emphasized the interaction between geophysicists, geologists, and engineers, and was received well by professionals, academics, and both graduate and undergraduate by: The potential of deterministic interpolation methods (IDW) and geostatistical techniques (Ordinary Kriging) in mapping surface soil salinity was evaluated in a GIS environment through cross.

The results indicate that MODIS imageries improve the capability of geostatistical methods for soil salinity mapping. The results showed that the use of MODIS imageries increased the G-Values of RK by 13%, 5%, 3%, 7% and 1% on average for OM, SAR, Na, K, and Mg : Sanaz Zare, Seyed Rashid Fallah Shamsi, Seyed Ali Abtahi.

Mapping Soil Salinity in El-Tina Plain in Egypt Using Geostatistical Approach 83 Fig. 1: Study area location and sampling design Geostatistical mapping of soil salinity Geostatistical techniques, including analyses of semivariograms, cross-validation, kriging and mapping of kriged estimates (GOOVAERTS ) were used to determine the variance.

A Practical Guide to Geostatistical Mapping by Tomislav Hengl | p. | ISBN About; Mapping population change index in Southern Serbia (–) as a function of environmental factors Data sets.

- Wed, 12/02/ - Data sets used in this book are provided as a supplement to the exercise. This data. Geostatistical Application to Salinity Mapping and Simulated Reclamation by Mohamad A. Al-Taper A THESIS submitted to Oregon State University in partial fulfillment of the requirement for the degree of Doctor of Philosophy Completed Decem Commencement June Title: A Practical Guide to Geostatistical Mapping of Environmental Variables Author(s): Tomislav Hengl Luxembourg: Office for Official Publications of the European Communities — pp.

— Ö cm EUR — Scientific and Technical Research series. Therefore, the application of geostatistical and multivariate statistical methods is recommended.

In principle, both types of statistics are able to detect spatial. Douaik A () Evaluation of the space-time variability of soil salinity by statistical, geostatistical, and Bayesian maximum entropy methods.

PhD thesis, Ghent University, Ghent Google Scholar Douaik A, Van Meirvenne M, Toth T, Serre ML () Space-time mapping of soil salinity using probabilistic Bayesian maximum by: 1. Journal of Integrative Agriculture18(2): – RESEARCH ARTICLE Available online at ScienceDirect Using proximal sensor data for soil salinity management and mapping GUO Yan1, 2, ZHOU Yin2, ZHOU Lian-qing2, 3, LIU Ting1, WANG Lai-gang1, CHENG Yong-zheng1, HE Jia1, ZHENG Guo-qing1 1 Institute of Agricultural Economics and Information, Henan Cited by: 1.

Key words: Map, IDW, soil salinity, Damghan plain, geostatistical analyses Introduction Soil salinity refers to the presence in soil and water of various electrolytic mineral solutes in concentrations that are harmful to many agricultural crops [4,16,17,18,20].

Postel [9] estimates that soil salinization costs the. Introduction. Soil salinization in the lower reaches of the Amudarya River is a constant threat. Khorezm is one of the downstream regions in Uzbekistan where moderate and high soil salinity levels affect 50–60% of the irrigated area (SIC–ICWC, ).Although the area has been known to have irrigation since ancient times (Tolstov, ), it has been further developed for irrigation until Cited by:   One solution is land reclamation from coastal tidelands, but soil salinization is problematic.

As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Some proximal sensors such as the EM38 allow for the rapid and cost-effective in situ collection of high-resolution : Yan Guo, Zhou Shi, Jingyi Huang, Laigang Wang, Yongzheng Cheng, Guoqing Zheng.

Soil salinization in the lower reaches of Amudarya is a constant threat. High seepage losses in irrigation water delivery network and deteriorated dra. Geostatistics in Genstat. in: Oliver, M. (ed.) Geostatistical applications for precision agriculture Springer, Berlin.

Weeds, worms and geostatistics B - Book chapters etc edited externallyCited by: Chapters cover the steps and methodologies involved in typical reservoir modeling, and examine preliminary statistical concepts, gridding reservoir layers, quantifying spatial correlation, mapping concepts, cell-based and object-based facies modeling, porosity and permeability modeling, simulated annealing for geostatistics, and uncertainty 5/5(3).

Peer Review Publications. Manchuk, J.G. and Deutsch, C.V., “Boundary Modeling with Moving Least Squares”, Accepted by CAGEO, February(31 pages) Reclamation and Environment, February,(13 pages) Using the Critical Temperature to Improve the Speed of Geostatistical Applications of Simulated Annealing, GEOSTATS In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field.

Significant correlation relationship between EC a and EC (i.e. r >) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal Cited by:   Abstract.

Soil salinity spreads in more than countries, and no continent is completely free from salinity. The level of salinity problem varies trans-country and even within the country at different locations, landforms, and irrigated agriculture regions to farmers’ by: Using Geospatial Techniques and Remote Sensing to Reduce the Number of Soil Salinity Samples Ahmed A.

Eldeiry1 Department of Civil and Environmental Engineering, Colorado State University,Luis A. García College of Engineering and Mathematical Sciences, University of Vermont, Burlington, VT Abstract. The papers assembled here cover topics such as technological advances in soil salinity mapping and monitoring, management and reclamation of salt-affected soils, use of marginal quality water for crop production, salt-tolerance mechanisms in plants, biosaline agriculture and agroforestry, microbiological interventions for marginal soils, opportunities and challenges in using marginal waters Pages:   A practical guide to geostatistical mapping using R+gstat/geoR, SAGA GIS and Google Earth combo of software packages.

Includes seven diverse data analysis exercises. Materials presented in this book have been used for the five-day advanced training course "GEOSTAT: spatio-temporal data analysis with R+SAGA+Google Earth", that is periodically.

Soil salinization is one of the most damaging environmental problems in coastal areas, including Indus River Delta (IRD). Due to the reduction of flow in the Indus basin, saline water from the Arabian Sea is intruding into the IRD and has degraded the agricultural lands drastically.

Focusing on the gravity of the problem, the present study was designed to explore the spatial distribution of Author: G.

Solangi, A. Siyal, M. Babar, P. Siyal. Mapping and monitoring of salt-affected soils using remote sensing and geographical information system for the reclamation of Canal Command Area of Jammu, India --Pt. Management and reclamation of salt-affected soils: Management of Saline Lands in Oman: learning to live with salinity Measurement, monitoring, and mapping of soil salinity distributions across the landscape of irrigated agricultural fields; EC a-directed soil sampling for precision agriculture applications including site-specific reclamation, site-specific crop management, and delineation of site-specific management units (SSMUs).

Introduction to the special section ‘Applications of electromagnetic induction to digital soil mapping’. Soil Use and Management. doi: /sum Multi-scale soil salinity mapping and monitoring with proximal and remote sensing - (Abstract Only).

GEOSTATISTICAL ANALYSIS OF A SOIL SALINITY DATA SET A. BROADVIEW SALINITY DATA SET As mentioned previously, the data set used in the following study is more a support for demonstration of geostatistical algorithms than the data base of an actual case study. For such demonstrative purposes, the name of the location.

Get this from a library. Developments in soil salinity assessment and reclamation: innovative thinking and use of marginal soil and water resources in irrigated agriculture. [Shabbir A Shahid; Mahmoud A Abdelfattah; Faisal K Taha;] -- This important addition to the technical literature of ecology is a storehouse of information on marginal soils and waters from around the world.

Remote Sensing from Ground to Space Platforms Associated with Terrain Attributes as a Hybrid Strategy on the Development of a Pedological Map by José A. M. Demattê, Leonardo Ramirez-Lopez, Rodnei Rizzo, Marcos R. Nanni, Peterson R. Fiorio, Caio T. Fongaro, Luiz G.

Medeiros Neto, José L. Safanelli and Pedro Paulo Da S. Barros. The salinity of the ocean also determines the density of seawater as well and that plays a large role in global ocean circulation and sea surface winds and temperature. Measuring sea surface salinity (SSS) is crucial for understanding how the input and output of .Geostatistical Analyst provides tools that make the best predic-tions possible by examining the relationships between all of the sample points and producing a continuous surface of ozone concentration, standard errors (uncertainty) of predictions, and probabilities that critical values are exceeded.

ArcGIS Geostatistical Analyst TutorialFile Size: 2MB.