Biodegradation of the herbicide mecoprop-p with soil depth and its relationship with class III tfdA genes

Mecoprop-p [(R)-2-(4-chloro-2-methylphenoxy) propanoic acid) is widely used in agriculture and poses an environmental concern because of its susceptibility to leach from soil to water. We investigated the effect of soil depth on mecoprop-p biodegradation and its relationship with the number and diversity of tfdA related genes, which are the most widely known genes involved in degradation of the phenoxyalkanoic acid group of herbicides by bacteria. Mecoprop-p half-life (DT50) was approximately 12 days in soil sampled from <30 cm depth, and increased progressively with soil depth, reaching over 84 days at 70–80 cm. In sub-soil there was a lag period of between 23 and 34 days prior to a phase of rapid degradation. No lag phase occurred in top-soil samples prior to the onset of degradation. The maximum degradation rate was the same in top-soil and sub-soil samples. Although diverse tfdAα and tfdA genes were present prior to mecoprop-p degradation, real time PCR revealed that degradation was associated with proliferation of tfdA genes. The number of tfdA genes and the most probable number of mecoprop-p degrading organisms in soil prior to mecoprop-p addition were below the limit of quantification and detection respectively. Melting curves from the real time PCR analysis showed that prior to mecoprop-p degradation both class I and class III tfdA genes were present in top- and sub-soil samples. However at all soil depths only tfdA class III genes proliferated during degradation. Denaturing gradient gel electrophoresis confirmed that class III tfdA genes were associated with mecoprop-p degradation. Degradation was not associated with the induction of novel tfdA genes in top- or sub-soil samples, and there were no apparent differences in tfdA gene diversity with soil depth prior to or following degradation.

Uncertainty in the estimation of potential evapotranspiration under climate change.

21st century climate change is projected to result in an intensification of the global hydrological cycle, but there is substantial uncertainty in how this will impact freshwater availability. A relatively overlooked aspect of this uncertainty pertains to how different methods of estimating potential evapotranspiration (PET) respond to changing climate. Here we investigate the global response of six different PET methods to a 2 °C rise in global mean temperature. All methods suggest an increase in PET associated with a warming climate. However, differences in PET climate change signal of over 100% are found between methods. Analysis of a precipitation/PET aridity index and regional water surplus indicates that for certain regions and GCMs, choice of PET method can actually determine the direction of projections of future water resources. As such, method dependence of the PET climate change signal is an important source of uncertainty in projections of future freshwater availability.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Trends in aerosol optical depth in the Russian Arctic and their links with synoptic climatology

Temporal and spatial variability of aerosol optical depth (AOD) are examined using observations of direct solar radiation in the Eurasian Arctic for 1940-1990. AOD is estimated using empirical methods for 14 stations located between 66.2 degrees N and 80.6 degrees N, from the Kara Sea to the Chukchi Sea. While AOD exhibits a well-known springtime maximum and summertime minimum at all stations, atmospheric turbidity is higher in spring in the western (Kara-Laptev) part of the Eurasian Arctic. Between June and August, the eastern (East Siberian-Chukchi) sector experiences higher transparency than the western part. A statistically significant positive trend in AOD was observed in the Kara-Laptev sector between the late 1950s and the early 1930s predominantly in spring when pollution-derived aerosol dominates the Arctic atmosphere but not in the eastern sector. Although all stations are remote, those with positive trends are located closer to the anthropogenic sources of air pollution. By contrast, a widespread decline in AOD was observed between 1982 and 1990 in the eastern Arctic in spring but was limited to two sites in the western Arctic. These results suggest that the post-1982 decline in anthropogenic emissions in Europe and the former Soviet Union has had a limited effect on aerosol load in the Arctic. The post-1982 negative trends in AOD in summer, when marine aerosol is present in the atmosphere, were more common in the west. The relationships between AOD and atmospheric circulation are examined using a synoptic climatology approach. In spring, AOD depends primarily on the strength and direction of air flow. Thus strong westerly and northerly flows result in low AOD values in the East Siberian-Chukchi sector. By contrast, strong southerly flow associated with the passage of depressions results in high A OD in the Kara-Laptev sector and trajectory analysis points to the contribution of industrial regions of the sub-Arctic. In summer, low pressure gradient or anticyclonic conditions result in high atmospheric turbidity. The frequency of this weather type has declined significantly since the early 1980s in the Kara-Laptev sector, which partly explains the decline in summer AOD values. (c) 2004 Elsevier B.V. All rights reserved.

Remote estimation of thermal inertia and soil heat flux for bare soil

A method is presented which allows thermal inertia (the soil heat capacity times the square root of the soil thermal diffusivity, C(h)rootD(h)), to be estimated remotely from micrometeorological observations. The method uses the drop in surface temperature, T-s, between sunset and sunrise, and the average night-time net radiation during that period, for clear, still nights. A Fourier series analysis was applied to analyse the time series of T-s . The Fourier series constants, together with the remote estimate of thermal inertia, were used in an analytical expression to calculate diurnal estimates of the soil heat flux, G. These remote estimates of C(h)rootD(h) and G compared well with values derived from in situ sensors. The remote and in situ estimates of C(h)rootD(h) both correlated well with topsoil moisture content. This method potentially allows area-average estimates of thermal inertia and soil heat flux to be derived from remote sensing, e.g. METEOSAT Second Generation, where the area is determined by the sensor's height and viewing angle. (C) 2003 Elsevier B.V. All rights reserved.

Depth by The Rule

This note corrects a previous treatment of algorithms for the metric DTR, Depth by the Rule.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Observations of the depth of ice particle evaporation beneath frontal cloud to improve NWP modelling

The evaporation (sublimation) of ice particles beneath frontal ice cloud can provide a significant source of diabatic cooling which can lead to enhanced slantwise descent below the frontal surface. The strength and vertical extent of the cooling play a role in determining the dynamic response of the atmosphere, and an adequate representation is required in numerical weather-prediction (NWP) models for accurate forecasts of frontal dynamics. In this paper, data from a vertically pointing 94 GHz radar are used to determine the characteristic depth-scale of ice particle sublimation beneath frontal ice cloud. A statistical comparison is made with equivalent data extracted from the NWP mesoscale model operational at the Met Office, defining the evaporation depth-scale as the distance for the ice water content to fall to 10% of its peak value in the cloud. The results show that the depth of the ice evaporation zone derived from observations is less than 1 km for 90% of the time. The model significantly overestimates the sublimation depth-scales by a factor of between two and three, and underestimates the local ice water content by a factor of between two and four. Consequently the results suggest the model significantly underestimates the strength of the evaporative cooling, with implications for the prediction of frontal dynamics. A number of reasons for the model discrepancy are suggested. A comparison with radiosonde relative humidity data suggests part of the overestimation in evaporation depth may be due to a high RH bias in the dry slot beneath the frontal cloud, but other possible reasons include poor vertical resolution and deficiencies in the evaporation rate or ice particle fall-speed parametrizations.