Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

The upper Bajocian of the Crimean Mountains: Paleogeography and sedimentation conditions from palynological data

Based on the spore-pollen data, the mineral composition of clay rocks, analyzed structures and facies, and a general paleogeographic analysis, the sedimentation conditions and landscapes of islands located during the Late Bajocian in the region of the present-day the Crimean Mountains have been reconstructed. It is shown that the sublatitudinally elongated insular land zone had a width of 30 km, the heights of the islands were no more than 1 km, with steep mudflow-affected northern slopes and with an extensive river system on the southern slopes.     

Conodont geothermometry in pyroclastic kimberlite: constraints on emplacement temperatures and cooling histories

Kimberlite pipes from Chidliak, Baffin Island, Nunavut, Canada host surface-derived Paleozoic carbonate xenoliths containing conodonts. Conodonts are phosphatic marine microfossils that experience progressive, cumulative and irreversible colour changes upon heating that are experimentally calibrated as a conodont colour alteration index (CAI). CAI values permit us to estimate the temperatures to which conodont-bearing rocks have been heated. Conodonts have been recovered from 118 samples from 89 carbonate xenoliths collected from 12 of the pipes and CAI values within individual carbonate xenoliths show four types of CAI distributions: (1) CAI values that are uniform throughout the xenolith; (2) lower CAIs in core of a xenolith than the rim; (3) CAIs that increase from one side of the xenolith to the other; and, (4) in one xenolith, higher CAIs in the xenolith core than at the rim. We have used thermal models for post-emplacement conductive cooling of kimberlite pipes and synchronous heating of conodont-bearing xenoliths to establish the temperature–time history of individual xenoliths within the kimberlite bodies. Model results suggest that the time-spans for xenoliths to reach the peak temperatures recorded by CAIs varies from hours for the smallest xenoliths to 2 or 3 years for the largest xenoliths. The thermal modelling shows the first three CAI patterns to be consistent with in situ conductive heating of the xenoliths coupled to the cooling host kimberlite. The fourth pattern remains an anomaly.

     

Methodology of Environmental Standardization for Natural Waters

Doklady Earth Sciences - This paper discusses sources of significant errors that occur in the course of determination of the primary environmental standard for natural waters: the maximum...