Wind erosion from military training lands in the Mojave Desert, California, U.S.A.

Military training activities reduce vegetation cover, disturb crusts, and degrade soil aggregates, making the land more vulnerable to wind erosion. The objective of this study was to quantify wind erosion rates for typical conditions at the Marine Corps Air Ground Combat Center, Twentynine Palms, CA, U.S.A. Five Big Spring Number Eight (BSNE) sampler stations were installed at each of five sites. Each BSNE station consisted of five BSNE samplers with the lowest sampler at 0·05 m and the highest sampler at 1·0 m above the soil surface. Once a month, sediment was collected from the samplers for analysis. Occurrence of saltating soil aggregates was recorded every hour using Sensits, one at each site. The site with the most erosion had a sediment discharge of 311 kg m⁻¹ over a period of 17 months. Other sites eroded much less because of significant rock cover or the presence of a crust. Hourly sediment discharge was estimated combining hourly Sensit count and monthly sediment discharge measured using BSNE samplers. More simultaneously measured data are needed to better characterize the relationship between these two and reconstruct a detailed time-series of wind erosion. This measured time-series can then be used for comparison with simulation results from process-based wind erosion models such as the Wind Erosion Prediction System (WEPS), once it has been adapted to the unique aspects of military lands.     

A simulation model of morphological,vegetation and sediment changes in ephemeral streams

A model to simulate channel changes in ephemeral river channels and to test the effects of hydrological changes due to climate change and[sol ]or land use change was developed under the auspices of the EU funded MEDALUS programme (Mediterranean Desertification and Land Use). The model, CHANGISM (Channel Change GIS Simulation Model), is designed to simulate the effect of channel flow events and of climate conditions on morphology, sediment and vegetation, through sequences of events and conditions, over periods of up to several decades. The modelling is based on cellular automata but with calculations for water and sediment continuity. Process rules have both deterministic and stochastic elements. An important feature of the model is that it incorporates feedback elements between each event. The main aim of the model is to indicate the likely outcomes of events and combinations of conditions. It is linked to GIS for both input and output. The modelling is based on a channel reach and state is input as GIS layers of morphology (DEM), sediment and vegetation cover and state. Other initial conditions of soil moisture, groundwater level, and overall gradient are input. Parameters for processes are read from tables and can be easily changed for successive runs of the model. The bases for decisions on process specifications are discussed in this paper. Initial tests of the operation and sensitivity of the model were made on idealized reaches. The model was then tested using data from monitored sites in SE Spain. Simulations using clearwater flow worked well but initial simulations using events with sediment loads showed some tendency for excess deposition. Further tests and modifications are taking place. Overall, the model is one of the most sophisticated that simulates the interaction of flows with sediment and vegetation and the outcomes in terms of erosion, deposition, morphology, sediment cover, vegetation cover and plant survival over periods of up to 30 years for the scale of a channel reach. Copyright © 2005 John Wiley & Sons, Ltd.     

Stratigraphy of Pleistocene glaciations in the St Elias Mountains,southwest Yukon,Canada

At least five Middle to Late Pleistocene advances of the northern Cordilleran Ice Sheet are preserved at Silver Creek, on the northeastern edge of the St Elias Mountains in southwest Yukon, Canada. Silver Creek is located 100 km up‐ice of the Marine Isotope Stage (MIS) 2 McConnell glacial limit of the St Elias lobe. This site contains ~3 km of nearly continuous lateral exposure of glacial and non‐glacial sediments, including multiple tills separated by thick gravel, loess and tilted lake beds. Infrared‐stimulated luminescence (IRSL) and AMS radiocarbon dating constrain the glacial deposits to MIS 2, 4, either MIS 6 or mid‐MIS 7, and two older Middle Pleistocene advances. This chronology and the tilt of the lake beds suggest Pleistocene uplift rates of up to 1.9 mm a^?1 along the Denali Fault since MIS 7. The non‐glacial sediment consists of sand, gravel, loess and organic beds from MIS 7, MIS 3 and the early Holocene. The MIS 3 deposits date to between 30–36 ¹⁴C ka BP, making Silver Creek one of the few well‐constrained MIS 3‐aged sites in Yukon. This confirms that ice receded close to modern limits in MIS 3. Pollen and macrofossil analyses show that a meadow‐tundra to steppe‐tundra mosaic with abundant herbs and forbs and few shrubs or trees, dominated the environment at this time. The stratigraphy at Silver Creek provides a palaeoclimatic record since at least MIS 8 and comprises the oldest direct record of Pleistocene glaciation in southwest Yukon.     

Reconstruction of Holocene paleohydrological and sedimentological characteristics of Umm Ar-Rimam basin (northern Kuwait)

The paleohydrological and sedimentological characteristics of a playa lake in northern Kuwait (Arabian Gulf) are reconstructed using sedimentological, geochemical, and isotopic techniques. The sequence consists of up to 8 cycles of S-poor, alluvial sediments capped by a thin organic soil interbedded with gravity-fall calcrete sediments. The succession is locally derived from mainly Quaternary sediments and is regressive with upsection filling of the subsiding basin by cycles of sheetwash flow in response to climatic change. There is no natural, open-water lake water as indicated by low total organic carbon (TOC) data, but the presence of incised calcrete yardangs suggests that more extensive open-water conditions were operative in the past. Stable isotope (δ¹⁸O‰ and δ¹³C‰) values of the authigenic carbonates indicate the following three distinct processes: evaporation, meteoric fluid infiltration, and rapid per-descensum flow (rapid downward movement of water and playa sediment through pipes) through a porous, clastic sequence. Because evaporites are scarce, other factors besides evaporation action control chemical and isotopic compositions of the per-decensum lake fluids. Consequently, the isotopic composition cannot be interpreted exclusively as an indicator of salinity or evaporation ratio. The degassing of CO₂ during groundwater discharge may explain the enriched carbon isotope values for the authigenic carbonates precipitated in the sediments. Hydrologically closed lake water bodies tend to show low negative carbonate oxygen and carbon isotopic signatures. Isotopically negative δ¹³C values imply a strong input of soil-zone carbon to the groundwater of the top 60 cm of the sediment. Lakes that are hydrologically closed and evaporate or equilibrate with atmospheric CO₂ will tend to have low negative δ¹⁸O and δ¹³C values in the carbonates as reported by Talbot (Chem Geol: Isotope Geosci Sect 80(4):261–279, 1990). Biologically active lakes will tend toward lower δ¹³C of dissolved carbon due to the photosynthetic effects of ¹²C withdrawal as reported by Dunagan and Driese (J Sed Res 69:772–783, 1999). Increased biological activity during sedimentation may account for low carbon isotope values where plants were abundant, but in shrinkage-dominated systems (those of clay-rich soil subjecting to wet-dry conditions), carbon isotopes will be largely inherited from the calcretic limestones in the land extending landward of the coast and not influenced by coastal processes (known as hinterland), such as Umm Ar-Rimam depression. This basin does not fit the classic shallow playa-type basins of the Arabian Peninsula but rather the recharge playas of the southwestern USA.     

Representation of Uncertainty and Integration of PGIS-based Grazing Intensity Maps Using Evidential Belief Functions

In a project to classify livestock grazing intensity using participatory geographic information systems (PGIS), we encountered the problem of how to synthesize PGIS-based maps of livestock grazing intensity that were prepared separately by local experts. We investigated the utility of evidential belief functions (EBFs) and Dempster's rule of combination to represent classification uncertainty and integrate the PGIS-based grazing intensity maps. These maps were used as individual sets of evidence in the application of EBFs to evaluate the proposition that " This area or pixel belongs to the high, medium, or low grazing intensity class because the local expert(s) says (say) so ". The class-area-weighted averages of EBFs based on each of the PGIS-based maps show that the lowest degree of classification uncertainty is associated with maps in which "vegetation species" was used as the mapping criterion. This criterion, together with local landscape attributes of livestock use may be considered as an appropriate standard measure for grazing intensity. The maps of integrated EBFs of grazing intensity show that classification uncertainty is high when the local experts apply at least two mapping criteria together. This study demonstrates the usefulness of EBFs to represent classification uncertainty and the possibility to use the EBF values in identifying and using criteria for PGIS-based mapping of livestock grazing intensity.     

World oil: Hotelling depletion or accelerating use?

In theoretical Hotelling-type models of resource depletion, oil use declines monotonically over time to depletion. However, world oil use has been increasing for several years. Can theory and reality be reconciled? The answer is affirmative, if theory is modified to accommodate outward-shifting demand functions that are rising in response to growth in world population and income. Under this assumption, a Hotelling depletion model projects a 50-year period of increasing world oil use before the decline to exhaustion. This holds for both competitive and monopolistic regimes. Hotelling theory has been criticized by Adelman and others, in part because of the unreality of the theoretical projections. By combining the modified Hotelling theory with U.S. Geological Survey resource estimates, the numerical projections seem congruent with Adelman's near-term expectations. Finally, a backstop technology, such as renewable biomass ethanol, introduces a new dimension. Assuming a $2-per-gallon cost for the ethanol, the modified Hotelling theory projects accelerating use of conventional oil until depletion or substitution. Consequently, it does not seem unreasonable to believe that a finite, limited resource of conventional oil is consistent with growing use for several decades. A projected exhaustion in 100 years is consisten with increasing use for 50 years.     

Wind erosion climatic erosivity

A physically based wind-erosion climatic factor has been derived: $$CE = \rho \int {[u^2 } - (u_T^2 + \gamma ^l /\rho a^2 )]^{3/2} f(u)du$$ where ? is the air density, a is a constant made up of other constants (von Karman, height of wind speed observation, roughness parameter), u is the horizontal wind speed, u _T is threshold wind speed, f(u) u) is a wind speed probability density function, and γ is the cohesive resistance caused by water on the soil particles. Cohesive resistance is proportional to the square of water content relative to water content at ?1500 J kg^?1. Relative water content is approximated from the Budyko dryness ratio and the Thornthwaite PE index with similar results. CE is calculable from wind speed and other generally available meteorological data, and is usable in the wind erosion equation without some of the limitations of a previously used wind erosion climatic factor.     

Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods

In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories.