Geochemical mapping using a geomorphologic approach based on catchments

The Extended Sample Catchment Basin (ESCB) mapping technique, discussed in this paper, can be used to display the spatial distribution of geochemical variables measured in stream sediments taking into consideration the geomorphologic settings and the hydrographic patterns of surveyed areas. This approach is based on the association of an area of statistical representativeness with each sample, and on the assumption that the concentrations measured in the stream sediments can be considered as average reference values for this area.ESCBs can be easily identified considering the position of the sampling points within the hydrographic network and using the confluences between the streams of highest rank as break points for representing changes of the geochemical background. This approach, different from the traditional geostatistical and deterministic ones, does not consider the Euclidean distance among the sampling points as a measure of geochemical similarity but only refers to their functional relationship along the streams (following the water and the sediment flow) to measure their proximity.ESCBs can be seen as a specific development of previous techniques based on catchments and proves to be especially useful for supporting land planning in a preliminary survey phase while it is not specifically suitable for the identification of point sources of geochemical anomalies.Due to the fractal nature of the hydrographic network, all the procedures can be driven in a GIS environment by using digital terrain models apart from their spatial resolution.     

Stream nitrate levels in a small catchment in south west England over a period of 15 years (1970-1985)

Stream nitrate levels in a small catchment of mixed land use (the Slapton Wood catchment) have been studied since September 1970; a record of this length is possibly unique in the United Kingdom for such a small basin (94 ha). A sustained increase in nitrate concentration has been observed during the study period. In addition to this long-term trend, short-term changes in nitrate concentrations relate to stream discharge levels and to seasonal variations. Multivariate statistical analysis has been used to quantify these trends and to identify those factors controlling the production and loss of nitrate from the catchment system. The main period of nitrate removal occurs in winter when high concentrations coincide with the main period of throughflow generation. The influence of climatic variability is illustrated by reference to the 1975/76 drought and post-drought period.     

Weighting of BLEG data with drainage and catchment properties to enhance Au anomalies

This research aims to take the effect of drainage sediment dilution into consideration by using catchment weighted-bulk leachable extractable gold (CW-BLEG) data in order to enhance and recognize Au anomalies. As a case study, an area in the Eskisehir region in Western Turkey was selected. In this area, gold-bearing crystalline quartz veins, of probable orogenic type, containing up to 20 g/t Au, occur in low-grade schists and marbles of the Karakaya Complex in the vicinity of the Sogut area. To classify the final geochemical maps of the BLEG data to differentiate Au anomalies from background, the singularity model was applied. After that, in order to take the sediments dilution effect (DE) into account, the other important factors in the study area such as the sinuosity index (SI) of the stream sediments per catchment, and the topography slope and area of each catchment were taken into consideration and implemented on the BLEG data. To do so, the CW-BLEG models based on the relation between the Au concentrations and each factor (i.e., C × sinuosity as DE-sinuosity, C × slope as DE-slope, and C × area as DE-area) were generated. Because of the insufficient number of known mineral deposits within the study area to evaluate the effectiveness of the models statistically, the models generated were compared with each other and studied using cross-validation. It demonstrated that the DE-area and DE-sinuosity models work better than the other model in recognizing strong and very strong anomalies considering the known mineral deposits. The cross-validation results show that the DE-area model provides a more robust result compared the other models. Considering the models generated, the very strong and strong Au anomalies in the western part of the study area are corresponded to the known gold mineralization (e.g., Sogut and Mayislar) hosted by the Karakaya Complex, and the anomalies in the eastern and central parts of the study area are associated with the Damdaca mineralization.     

On the validation of a coupled water and energy balance model at small catchment scales

Catchment runoff is the most widely used catchment scale measurement in modelling studies, and we have a reasonable degree of confidence in its accuracy. The advent of satellites gives access to a new suite of measurements taken over a defined spatial range. These measurements, principally reflected or emitted radiation, provide hydrologists with new possibilities for quantifying the state of a catchment. Surface temperatures can be readily measured by a satellite on a scale comparable to the size of a small catchment.

In this paper we show that satellite sensed temperatures can provide an important measure of catchment status, which can complement runoff measurements in water balance studies. A one-dimensional model, which couples the land surface energy balance with the soil and surface water balance is tested by comparison with runoff and with remotely sensed surface temperature measurements. Simulations have been run over four years for two small catchments which have a fairly homogeneous vegetation, one being forest and its neighbour pasture. Satellite “surface” temperatures have been interpreted in terms of the energy balance, and used as a test of modelling accuracy. An “effective” surface temperature is calculated as a weighted mean of temperatures of the separate soil and leaf surfaces. This modelled “effective” temperature correlates well with Landsat TM surface temperatures.

When pasture replaces forest, the model predicts a reduction in evapotranspiration of around 30%, a three-fold increase in runoff, and an increase in mean soil moisture status. The change to pasture also results in a rise in mean effective surface temperature of about 4°C, and an increase in summer diurnal temperature range from 10 to 22°C. The winter diurnal temperature range is similar for both vegetation systems.

Inclusion of soil moisture variability in thermal properties results in an increase in mean daily maximum temperature of about 2°C in summer and winter, without much change in daily minima. The daily mean temperature is not significantly affected.