Archaeological sites in Grand Canyon National Park along the Colorado River are eroding owing to six decades of Glen Canyon Dam operations.

The archaeological record documenting human history in deserts is commonly concentrated along rivers in terraces or other landforms built by river sediment deposits. Today that record is at risk in many river valleys owing to human resource and infrastructure development activities, including the construction and operation of dams. We assessed the effects of the operations of Glen Canyon Dam - which, since its closure in 1963, has imposed drastic changes to flow, sediment supply and distribution, and riparian vegetation - on a population of 362 archaeological sites in the Colorado River corridor through Grand Canyon National Park, Arizona, USA. We leverage 50 years of evidence from aerial photographs and more than 30 years of field observations and measurements of archaeological-site topography and wind patterns to evaluate changes in the physical integrity of archaeological sites using two geomorphology-based site classification systems. We find that most archaeological sites are eroding; moreover, most are at increased risk of continuing to erode, due to six decades of operations of Glen Canyon Dam. Results show that the wind-driven (aeolian) supply of river-sourced sand, essential for covering archaeological sites and protecting them from erosion, has decreased for most sites since 1973 owing to effects of long-term dam operations on river sediment supply and riparian vegetation expansion on sandbars. Results show that the proportion of sites affected by erosion from gullies controlled by the local base-level of the Colorado River has increased since 2000. These changes to landscape processes affecting archaeological site integrity limit the ability of the National Park Service and Grand Canyon-affiliated Native American Tribes to achieve environmental management goals to maintain or improve site integrity in situ. We identify three environmental management opportunities that could be used to a greater extent to decrease the risk of erosion and increase the potential for in-situ preservation of archaeological sites. Environmental management opportunities are: 1) sediment-rich controlled river floods to increase the aeolian supply of river-sourced sand, 2) extended periods of low river flow to increase the aeolian supply of river-sourced sand, 3) the removal of riparian vegetation barriers to the aeolian transport of river-sourced sand.

Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models.

Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.

Ad Hoc Modeling of Root Zone Soil Water with Landsat Imagery and Terrain and Soils Data.

Agricultural producers require knowledge of soil water at plant rooting depths,while many remote sensing studies have focused on surface soil water or mechanisticmodels that are not easily parameterized. We developed site-specific empirical models topredict spring soil water content for two Montana ranches. Calibration data sample sizeswere based on the estimated variability of soil water and the desired level of precision forthe soil water estimates. Models used Landsat imagery, a digital elevation model, and asoil survey as predictor variables. Our objectives were to see whether soil water could bepredicted accurately with easily obtainable calibration data and predictor variables and toconsider the relative influence of the three sources of predictor variables. Independentvalidation showed that multiple regression models predicted soil water with average error(RMSD) within 0.04 mass water content. This was similar to the accuracy expected basedon a statistical power test based on our sample size (n = 41 and n = 50). Improvedprediction precision could be achieved with additional calibration samples, and rangemanagers can readily balance the desired level of precision with the amount of effort tocollect calibration data. Spring soil water prediction effectively utilized a combination ofland surface imagery, terrain data, and subsurface soil characterization data. Rancherscould use accurate spring soil water content predictions to set stocking rates. Suchmanagement can help ensure that water, soil, and vegetation resources are usedconservatively in irrigated and non-irrigated rangeland systems.