Abstract.Opisthorchis viverrini infection is associated with human cholangiocarcinoma and northeast Thailand has the highest incidence of this disease in the world. Bithynia siamensis goniomphalos is the major freshwater snail intermediate host of O. viverrini in this area and an analysis based on geographical information systems was used to determine the effect of variation in soil surface salt on the density and distribution of this snail. A malacological survey was carried out in 56 water bodies in the Khorat basin, northeast Thailand at locations with various soil surface salt levels. Mollusk samples were collected from 10 ecologically representative water body sites with 10-20 sampling stations in each. The shoreline of clear, shallow water bodies was found to be the preferred B. s. goniomphalos habitat. The snails were exclusively found in water with salinity levels ranging between 0.05 and 22.11 parts per thousand (ppt), which supports the notion that B. s. goniomphalos prefers water with some saline content over pure, freshwater. The highest snail population densities were in rice fields, ponds, road-side ditches and canals within a water salinity range of 2.5-5.0 ppt. However, the presence of B. s. goniomphalos was negatively correlated with water salinity (P ≤0.05), both with regard to density and distribution. The areas with the highest density of B. s. goniomphalos were those with less than 1% soil surface salt (potential index = 0.314), while the lowest densities were found in areas exceeding 50% soil surface salt (potential index = 0.015).

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In northeast Thailand, salinization caused by the discharge of salty groundwater is a serious problem. Locations where groundwater flows into surface water must be identified before measures against saliniza tion can be taken. Radon-222 (222Rn) is a useful indicator for determining areas of groundwater discharge. We measured 222Rn concentrations in surface waters in the region and found that groundwater flows into streams and lakes in low-elevation areas (below 180m). Our results agree with the results of published simulations of groundwater flow.

This paper presents an approach to estimate soil salinity through modelling of soil spectra using an inverted Gaussian (IG) function. The approach is tested on experimental datasets including measurements of soil physicochemical properties and their spectral reflectance which are obtained under controlled laboratory conditions. The near-infrared (NIR) and shortwave infrared (SWIR) region of the salt-affected soil spectra were fitted to an inverted Gaussian curve. Parameters of the fitted curve, such as functional depth, distance to the inflection point and area under curve, were then used as predictors in regression analysis to estimate soil salinity levels. The results suggest a successful estimation of salinity levels, especially, for soil samples treated with epsomite and bischofite solutions. Amongst the calculated IG parameters, the area under fitted curve resulted in the most accurate estimations. The results demonstrate the relative utility of high spectral resolution data for estimating soil salinity under laboratory controlled conditions.