scholarly journals Assessment of Groundwater Chemistry and Status in a Heavily Used Semi-Arid Region with Multivariate Statistical Analysis

Water ◽  
2014 ◽  
Vol 6 (8) ◽  
pp. 2212-2232 ◽  
Author(s):  
Xuedi Zhang ◽  
Hui Qian ◽  
Jie Chen ◽  
Liang Qiao
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Arid Region ◽  
Groundwater Chemistry ◽  
Multivariate Statistical ◽  
Semi Arid Region ◽  
Semi Arid

Assessment of groundwater chemistry in layered coastal aquifers using multivariate statistical analysis

2017 ◽  
Vol 3 (1) ◽  
pp. 55-69 ◽  
Author(s):  
R. Thilagavathi ◽  
S. Chidambaram ◽  
C. Thivya ◽  
M. V. Prasanna ◽  
Tirumalesh Keesari ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Coastal Aquifers ◽  
Multivariate Statistical Analysis ◽  
Groundwater Chemistry ◽  
Multivariate Statistical

scholarly journals Characterization agricultural vulnerability to drought in the Northeast of Brazil

2017 ◽  
Author(s):  
Bruce K. N. Silva ◽  
Paulo S. Lucio ◽  
Cláudio M. S. Silva ◽  
Maria H. C. Spyrides ◽  
Madson T. Silva ◽  
...  
Keyword(s):  
Arid Region ◽  
Early Warning Systems ◽  
Demographic Characteristics ◽  
Moderate Degree ◽  
Warning Systems ◽  
Multivariate Statistical ◽  
Agricultural Vulnerability ◽  
Agricultural Census ◽  
Semi Arid Region ◽  
Semi Arid

Abstract. The main objective was to create an indicator of agricultural vulnerability to drought in the Northeast of Brazil (NEB). The data used for precipitation belong to ANA (Agência Nacional das Águas) considering the climatological norm from 1979–2008. Data on agricultural productivity and demographic characteristics were obtained in the agricultural census of IBGE (Brazilian Institute of Geography and Statistics) in 2006 and, finally, data on natural disasters in the period 1991–2010 with CEPED (Centro de Estudose Pesquisasem Engenhariae Defesa Civil). The Multivariate Statistical Analysis Factorial technique allowed to reduce the number of variables and to estimate a model of the sensitivity component that reproduced 42 % of the original variance, besides the factors trying to represent the productive dynamics of the NEB. The results show that the Southern NEB presented the highest degree of agricultural vulnerability (17,81–121,44) in the 2000 census, when compared to the census of 2010. In the Southwest it is observed that a part of the semi-arid region presented a moderate degree (0,74–1,08) and much higher in extension when compared to the 2000 census, evidencing that exposure to drought does not directly influence the agricultural sensitivity in the most productive areas of the region. The adaptive capacity factor presented significant results for the composition of the indicator of agricultural vulnerability, mainly in the semi-arid region that varied from (0,71–5,42). In this way, it is concluded that, between the census, the southern and central part of the NEB reduced agricultural vulnerability, but the region should benefit from early warning systems as well as the development and adoption of natural resources and technology management, with the objective of ducating producers about the potential impacts of extreme events.

scholarly journals STATISTICAL ANALYSIS OF THE SPATIAL RELASHIONSHIP OF CAATINGA AND PHYSIOGRAPHIC FACTORS THROUGH REMOTE DATA

FLORESTA ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 755
Author(s):  
Janisson Batista de Jesus ◽  
Mariana Mizutani Ribeiro ◽  
Tatiana Mora Kuplich ◽  
Bruno Barros de Souza ◽  
Dráuzio Correia Gama
Keyword(s):  
Spatial Distribution ◽  
Statistical Analysis ◽  
Arid Region ◽  
Factors Associated ◽  
Independent Variables ◽  
Caatinga Vegetation ◽  
Semi Arid Region ◽  
Relationship Of ◽  
The Relationship ◽  
Semi Arid

The caatinga is characteristic of the semi-arid region of Brazil, of significant coverage in the northeast of the country and, therefore, geoprocessing and statistical techniques can be important tools to analyze the environmental factors associated with its distribution. The present study had the objective of analyzing the relationship of: altimetry, slope, soil type and river proximity in the spatial distribution of the caatinga vegetation, using a database generated by geoprocessing techniques. NDVI was used, and statistical analysis was based on multiple regression and Pearson's correlation. The results show that the weather station is the only variable that presented a high determination coefficient with the caatinga vegetation (R2 = 0.956), while the other independent variables have weak or nonexistent correlation. With the techniques of geoprocessing was allowed to observe that the Caatinga has a generalist spatial distribution of occurrence, not having a defined pattern.

scholarly journals The effects of geochemical processes on groundwater chemistry and the health risks associated with fluoride intake in a semi-arid region of South India

RSC Advances ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 4840-4859 ◽  
Author(s):  
D. Karunanidhi ◽  
P. Aravinthasamy ◽  
M. Deepali ◽  
T. Subramani ◽  
Priyadarsi D. Roy
Keyword(s):  
Health Risks ◽  
Arid Region ◽  
South India ◽  
Groundwater Chemistry ◽  
Geochemical Processes ◽  
Fluoride Intake ◽  
Semi Arid Region ◽  
Semi Arid

This study attempts to establish the effects of subsurface geochemical processes based on the hydrogeochemical attributes of 61 well samples collected in a semi-arid region of South India.

Sign in / Sign up

Export Citation Format

Share Document