A numerical model of the partitioning of trace chemical solutes during drop freezing

Partitioning of volatile chemicals among the gas, liquid, and solid phases during freezing of liquid water in clouds can impact trace chemical distributions in the troposphere and in precipitation. We describe here a numerical model of this partitioning during the freezing of a supercooled liquid drop. Our model includes the time-dependent calculation of the coupled processes of crystallization kinetics, heat transport, and solute mass transport, for a freezing hydrometeor particle. We demonstrate the model for tracer partitioning during the freezing of a 1000 μm radius drop on a 100 μm ice substrate, under a few ambient condition scenarios. The model effectively simulates particle freezing and solute transport, yielding results that are qualitatively and quantitatively consistent with previous experimental and theoretical work. Results suggest that the ice shell formation time is governed by heat loss to air and not by dendrite propagation, and that the location of ice nucleation is not important to freezing times or the effective partitioning of chemical solutes. Even for the case of nucleation at the center of the drop, we found that dendrites propagated rapidly to form surface ice. Freezing then proceeded from the outside in. Results also indicate that the solid-liquid interfacial surface area is not important to freezing times or the effective partitioning of chemical solutes, and that the rate aspects of trapping are more important than equilibrium solid-liquid partitioning to the effective partitioning resulting from freezing.     

Assessment of Nitrate—Nitrogen Distribution in Kansas Groundwater, 1990–1998

Nitrate-nitrogen (nitrate-N) in groundwater is a potential problem in many parts of Kansas.From 1990 to 1998, 747 water samples were collected from domestic, irrigation, monitoring,and public water supply wells primarily from the western two-thirds of the state, and analyzedfor nitrate-N by the Kansas Geological Survey. Nitrate-N concentrations of the 747 samplesanalyzed range from 29% with less than or equal to 3 mg/L, 51% between 3 and 10 mg/L,and 20% greater than or equal to 10 mg/L. Factors that show a statistically significantrelationship with the occurrence of nitrate-N in Kansas groundwater in this assessment includegeographic area of the state, depth of well, and age of well. Nitrate-N levels of wells screenedin the High Plains aquifer in south-central Kansas showed a statistically higher concentrationthan samples collected from the High Plains aquifer in the western portion of the state.Comparison of nitrate-N with depth of well indicated that shallower wells throughout the stategenerally have higher nitrate-N values than deeper wells. Irrigation wells older than 1975showed statistically higher nitrate-N concentration than wells installed during and since 1975,possibly related to changes in well-construction practices and regulations that occurred in 1975.     

Geoinformational Mapping of Landscapes in the Northwestern Part of Western Siberia Using the Hansen Mosaic Dataset

Presented are the technique and results of studying the landscape structure of the north-west of Western Siberia on the basis of the Hansen mosaic dataset consisting of elements covering the entire territory of the Earth. To study this area used a synthesis of classical methods of thematic system mapping as described in the doctrine of geosystems of V. B. Sochava, and automated interpretation of remote sensing data and mapping using GIS technologies. The method of geoinformational mapping of the landscape structure with the use of MultiSpec and Quantum GIS software programs for the purpose of drawing up real-time raster landscape maps is shown. In drawing up the map and the legend, the principle of geomic system-hierarchical representation of the territory as a complex multi-level “bottom-up” structure from topological-level geosystems (groups and classes of landscape facies) to regional-level geosystems (geoms, groups and classes of geoms) was used. Compilation of operational raster landscape maps of the north-west of Western Siberia involved multilevel automated interpretation of the Hansen mosaic dataset and mapping of areas (clusters) on images with different brightness characteristics, with the landscape structure of key areas and stationary physical and geographical profiles. A characteristic of this approach also implies using a dynamic classification of geosystems based on the study of their variable states. Such an approach permits a monitoring of changes in landscape structure and its areas and the intensity of anthropogenic impacts on forest and marsh landscapes, and determination of permissible pressure on geosystems in areas with high technogenic pressure of the oil and gas complex represented by the north-west of Siberia. An automated processing of data based on a supervised classification of territorial objects allows for the elimination of inaccuracies arising in visual image interpretation. Raster landscape maps can be used both for a further generation of vector maps and as a real-time information base for purposes of environmental management and protection.     

Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.     

Quantifying soil variability in GIS applications: II Spatial distribution of soil properties

Abstract

Application of Geographical Information Systems (GIS) to environmental problems requires a spatial delineation of soil properties and some a priori knowledge of their variability. In the U.S.A. estimated soil properties are available from soil surveys published by the National Cooperative Soil Survey. However, information on the extent and nature of their variability is generally lacking. To remedy the situation, variability of selected soil properties measured at farm and watershed scales was compared with published values using geostatistical methods. Results showed that the variability of bulk density and hydraulic conductivity can be estimated by comparing regularized variograms of measured and published values. An overlay method was proposed that combines measured and published delineations of soil properties into an overlay with the properties of both. The technique makes it possible to incorporate variability into a GIS analysis using data available from published soil surveys.