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Spatial Variability of Arsenic in Soils in Arsenic Contaminated Shallow Tube Well Command Areas Used for Irrigated Wetland Rice Cultivation.

DNR Paul
CSO and Head
Agricultural Statistics Division, BRRI

Abstract/ Executive Summary:

Major objectives of this study were to map the spatial variability of arsenic concentration in the soils irrigated using arsenic contaminated ground water and to identify the means to reduce As contamination in rice soils. Ground water irrigated rice fields of STW command areas in four different locations in Bangladesh were intensively sampled on nearly regular grid spacing during Boro in 2003. As concentration in sample soils was determined using Hydride Generation method. This study indicates that micro elevation may be an impacting factor for As loading in soil. However, longer irrigation channels or ponded ground water prior to irrigation and discouraging standing water for longer period in rice field could be positive measure in reducing arsenic loading in irrigation rice soils.

Keywords: Spatial Variability, Arsenic, Soil, Arsenic Contaminated, Shallow, Tube Well, Rice Cultivation, Parameter, Water.

Location: Four different arsenic contaminated zones

Start Date: 01-07-2004

End Date: 30-06-2005

Program Area: Socio-economic and Policy

Commodity: Arsenic

Objectives:

To map the spatial variability of arsenic concentration in the soils irrigated using arsenic contaminated ground water.
To identify the means to reduce As contamination in rice soils.

Methodology:

Ground water irrigated rice fields of STW command areas in four different locations in Bangladesh were intensively sampled on nearly regular grid spacing (about 20m) during Boro in 2003. Composite soil sample from 0-15 cm depth were collected from grid points geo-referenced by GPS. As concentration in sample soils was determined using Hydride Generation method. As was measured in the irrigation channels at 20-meter intervals from the irrigation source(STW).for assessing the spatial dependency of soil as, semi-variance analysis was performed. Semi-variogram γh was defined as γh = 1/ 2[N 9(h)] ∑?( Zi-Zj)2 Where, N(h) is the number of pairs of data locations at lag distance of ‘h’ apart, and Zi and Zj are point locations, was calculate the spatial variability of soil As for each individual site using the software GS+ 5.3.2. Maximum lag distance and lag interval for the semi-variance were determined iteratively to best fit the model having highest R2 and the lowest residual sum of squares (RSS). Kriging interpolation was performed to creat As surfaces to spatially describe the distribution of As concentration in surface soils. Micro elevations model of the command area was created only at Faridpur site with elevation measured at 315 spots with the command area. These include 101 sampling points used for measuring soil As. Theodolite was used to measure the elevation. A wooden device with 6 x 6 platform was used to mount the stuff in order to avoid the depression of soil surface created due to foot pressing during transplanting and other cultural operations. Within the commend area, the mocro elevation model of relief was defined separately within each plot due to the fact that the variation in elevation is more between plots than within plot and that plowing and leveling of soils prior to transplanting are done by the farmers within the bunded plots. Inverse Distance weight (IDW) method Zj(est)= S[zi/(hij+s)p]/ S[1/(hij+s)p] Was used to create the elevation surface. The parameter of IDW used was determined iteratively to best fit the observed elevations. The relief so created for plots were then joined together to obtain the relief of the whole command area.

Source of Information: BRRI. Proceedings of the BRRI Annual Internal Review for 2004-2005 (Held on 18-22 December 2005). Bangladesh Rice Research Institute (BRRI). Gazipur -1701.

Article Link (Online Journal):

Funding Source:

1. United States Agency for International Development

Budget:

Total Budget (Tk.) :

Achievement/Findings:

• Micro elevation may be an impacting factor for As loading in soil. • Longer irrigation channels or ponded ground water prior to irrigation and discouraging standing water for longer period in rice field could be positive measure in reducing arsenic loading in irrigation rice soils.

Knowledge Management: Report/Proceedings