The spatial distribution and hazard assessment of heavy metals in the soils of surrounding agricultural fields affected by mine drainage of Ledo coal mining area of Tinsukia district, Assam, India, were investigated using statistics, geostatistics and geographic information system techniques. The amounts of Cr, Cd, Ni and Pb were determined from 83 soil samples collected within the contaminated area. The maps based on ordinary kriging showed that high concentrations of heavy metals were located in the low-lying paddy field and near coal mining site. Indicator kriged probability maps were prepared based on the concentrations to exceed permissible limit (MPL). It was seen that more than 95 % of the studied area has a higher than 50 % probability to exceed the MPL value of Pb and Ni. Multivariate statistical analyses and principal component analysis suggest that Cd and Pb are derived from anthropogenic sources, particularly coal mining activities, whereas Ni and Cr are derived from lithogenic and/or anthropogenic sources.

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Soil properties like pH, organic carbon (OC), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) vary spatially from a field to a larger region scale and determine the soil fertility. This study addressed the spatial variability of soil properties in Brahmaputra plains, northeastern India using geostatistical method. For this, a total of 767 soil samples from a depth of 0-25 cm at an approximate interval of 1 km were collected over the entire Bongaigaon district of Assam. Data were analyzed both statistically and geostatistically on the basis of semivariogram. Soil properties showed large variability with greatest variation was observed in AP (86 %) where as the smallest variation was in pH (19 %). The semivariogram for all soil properties were best fitted by exponential models and showed a highest (2.7 km) range for OC and lowest (1.2 km) for AP. The nugget/sill ratio indicates a strong dependence for pH (12 %), moderate spatial dependence for available nutrients (53-72 %) and a weak spatial dependence for OC (77 %). Evaluation of spatial maps indicated that except for AN due to high root mean square error (61.8), kriging could successfully interpolate other soil properties. Soil pH highly negatively correlated with OC (−0.330**) and AN (−0.228**) and highly positive correlated with AP (0.334**) and AK (0.164**). A highly significant correlation was also found between OC and AN (0.490 ** ).

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Soil fertility has direct implications on the agricultural production scenarios of a region. Surface soil samples at 1 km grid were collected to assess the fertility status of Lakhimpur district (Assam) in North East India. Fertility parameters like soil organic carbon, available nitrogen, phosphorus, potassium, iron, manganese, zinc and copper were determined using standard analytical procedure. Spatial distribution maps of the soil parameters were generated using regularized spline method in ArcGIS 10.0. The average soil organic carbon content was 1.05% and the maximum area was under high availability status (78%). In the case of nitrogen, 57% of the area was under low availability status. In the case of available potassium and phosphorus, the areas under low availability status were 48% and 49% respectively. But for micronutrients, in general, the availability status was high except for zinc, which indicated that 40% of the area was under low availability. A methodology was developed to integrate the individual nutrient layers using a set of decision rules to identify the multinutrient deficient zones. The integrated map showed that 24% of the area had multiple nutrient deficiencies and fell under high priority zone that warrant immediate nutrient management interventions to mitigate the situation.