Impact of local recharge on arsenic concentrations in shallow aquifers inferred from the electromagnetic conductivity of soils in Araihazar, Bangladesh

The high-degree of spatial variability of dissolved As levels in shallow aquifers of the Bengal Basin has been well documented but the underlying mechanisms remain poorly understood. We compare here As concentrations measured in groundwater pumped from 4700 wells <22 m (75 ft) deep across a 25 km2 area of Bangladesh with variations in the nature of surface soils inferred from 18,500 measurements of frequency domain electromagnetic induction. A set of 14 hand auger cores recovered from the same area indicate that a combination of grain size and the conductivity of soil water dominate the electromagnetic signal. The relationship between pairs of individual EM conductivity and dissolved As measurements within a distance of 50 m is significant but highly scattered (r2 = 0.12; n = 614). Concentrations of As tend to be lower in shallow aquifers underlying sandy soils and higher below finer-grained and high conductivity soils. Variations in EM conductivity account for nearly half the variance of the rate of increase of As concentration with depth, however, when the data are averaged over a distance of 50 m (r2 = 0.50; n = 145). The association is interpreted as an indication that groundwater recharge through permeable sandy soils prevents As concentrations from rising in shallow reducing groundwater

Site-specific seeding using multi-sensor and data fusion techniques : a review

Site-specific seeding (SSS) is a precision agricultural (PA) practice aiming at optimizing seeding rate and depth, depending on the within field variability in soil fertility and yield potential. Unlike other site-specific applications, SSS was not adopted sufficiently by farmers due to some technological and practical challenges that need to be overcome. Success of site-specific application strongly depends on the accuracy of measurement of key parameters in the system, modeling and delineation of management zone maps, accurate recommendations and finally the right choice of variable rate (VR) technologies and their integrations. The current study reviews available principles and technologies for both map-based and senor-based SSS. It covers the background of crop and soil quality indicators (SQI), various soil and crop sensor technologies and recommendation approaches of map-based and sensor-based SSS applications. It also discusses the potential of socio-economic benefits of SSS against uniform seeding. The current review proposes prospective future technology synthesis for implementation of SSS in practice. A multi-sensor data fusion system, integrating proper sensor combinations, is suggested as an essential approach for putting SSS into practice