Method for Normalization of Soil Salinity Data

2003 ◽  
Vol 129 (1) ◽  
pp. 64-66 ◽  
Author(s):  
V. Mirlas ◽  
Y. Benyamini ◽  
S. Marish ◽  
M. Gotesman ◽  
E. Fizik ◽  
...  
Keyword(s):  
Author(s):  
Olumuyiwa Idowu Ojo ◽  
Masengo Francois Ilunga

Irrigated agriculture has a major impact on the environment, especially soil degradation. Soil salinity is a critical environmental problem, which has great impact on soil fertility and overall agricultural productivity. Since, soil salinity processes are highly dynamic, the methods of detecting soil salinity hazards should also be dynamic. Remote sensing data are modern tools that provide information on variation over time essential for environmental monitoring and change detection, as they also help in the reduction of conventional time-consuming and expensive field sampling methods, which is the traditional method of monitoring and assessment. This chapter thus reviewed the concepts and applications of remote sensing, GIS-assisted spatial analysis and modelling of the salinity issue in irrigation fields. Generally, compared to the labour, time and money invested in field work devoted to collecting soil salinity data and analysis, the availability and ease of acquiring satellite imagery data and analysis made this concept very attractive and efficient.


Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 126
Author(s):  
Juan Herrero ◽  
Carmen Castañeda ◽  
Rosa Gómez-Báguena

This article presents and reviews the soil salinity data provided by a rescued vintage agronomic report on an irrigated area of 35,875 ha located in the center of the Ebro River basin, in the NE of mainland Spain. These data come from a soil sampling campaign conducted from May to the first half of July 1975 for the purpose of delineating saline and non-saline soils. The agronomic report was produced in response to demands from farmers to combat soil salinity, and represents the state of the art in those years for salinity studies. Our paper presents the scrubbed soil salinity data for this year, checking their consistency and locating the study sites. The main finding is the unearthing of this heritage report and the discussion of its soil salinity data. We show that the report supplies an assessment and a baseline for further soil salinity tracking by conducting new measurements either by direct soil sampling or by nondestructive techniques, providing an estimate of soil salinity at different locations. This task is feasible, as shown in our previously published articles involving nearby areas. A comparison of the salt amount in the soil over the years would provide a means to evaluate irrigation methods for sustainable land management. This comparison can be conducted simultaneously with analysis of other agricultural features described in the report for the irrigation district in 1975.


Author(s):  
G. Bourgault ◽  
A.G. Journel ◽  
J.D. Rhoades ◽  
D.L. Corwin ◽  
S.M. Lesch

2006 ◽  
Vol 55 (1) ◽  
pp. 89-98 ◽  
Author(s):  
D. Kovács ◽  
Tibor Tóth ◽  
P. Marth

The statistical analysis of salinity data from samples collected yearly from genetic soil horizons of 69 points of the Hungarian Soil Information and Monitoring System between 1992 and 2000 showed changes in time. There is a strong atmospheric control over the groundwater level and the resulting soil salinity. Weak statistical association was established between either the pattern of yearly soil salinity changes in the second (10-20 cm) and third (30-40 cm) genetic horizon and the groundwater observation stations or the soil types. In the area of Kecskemét there was a tendency of decreasing soil salinity patterns, while around Békéscsaba a tendency of increasing soil salinity patterns, as illustrated by the correspondence biplot. Regarding soil types, the solonetzic meadow soil showed a tendency of increasing salinity. It was concluded that the statistical analyses of the monitored data must be carefully planned in order to provide the optimal background data as independent data from all those available to accompany the monitored soil data as dependent variable.


2017 ◽  
Vol 49 (003) ◽  
pp. 525--528 ◽  
Author(s):  
N. H. CHANDIO ◽  
Q. H. MALLAH ◽  
M. M. ANWAR
Keyword(s):  

Hilgardia ◽  
1988 ◽  
Vol 56 (5) ◽  
pp. 17-44 ◽  
Author(s):  
James D. Rhoades ◽  
Frank T. Bingham ◽  
John Letey ◽  
Paul J. Pinter ◽  
Robert D. Lemert ◽  
...  

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