Results for “Water (MDPI)”

USGS2021

An assessment of vertical land movement to support coastal hazards planning in Washington state

The sea and land change elevation spatially and temporally from a multitude of processes, so it is necessary to constrain the movement of both to evaluate how coastlines will evolve and how those evolving coastlines will impact the natural and built environment over time. We combine land movement observations from global navigation satellite systems (GNSSs), leveling of geodetic monuments, and tide gauge records with a tectonic model of the Cascadia subduction zone to constrain absolute rates of vertical land movement in coastal Washington. We infer rates of vertical land movement in areas lacking direct observations by interpolating high-quality land movement observations and a discretely sampled interseismic locking model. Here we present a model of absolute vertical land movement that is combined with sea level rise estimates to inform local relative sea level projections on a community-scale. The most rapid vertical uplift (~3.5 mm/year) of the land is found across the northwest Olympic Peninsula, which currently outpaces sea level rise. Conversely, some areas, including a stretch of the northern Pacific Ocean coast from La Push to Kalaloch and the southern Puget Sound, are found to be subsiding at 0.5–1.0 mm/year, exacerbating the rate of relative sea level rise and thereby increasing the vulnerability of coastal communities.

Washington↗

USGS2007

A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields

Accurate crop performance monitoring and production estimation are critical for timely assessment of the food balance of several countries in the world. Since 2001, the Famine Early Warning Systems Network (FEWS NET) has been monitoring crop performance and relative production using satellite-derived data and simulation models in Africa, Central America, and Afghanistan where ground-based monitoring is limited because of a scarcity of weather stations. The commonly used crop monitoring models are based on a crop water-balance algorithm with inputs from satellite-derived rainfall estimates. These models are useful to monitor rainfed agriculture, but they are ineffective for irrigated areas. This study focused on Afghanistan, where over 80 percent of agricultural production comes from irrigated lands. We developed and implemented a Simplified Surface Energy Balance (SSEB) model to monitor and assess the performance of irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250m Normalized Difference Vegetation Index (NDVI) data, both from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. We estimated seasonal actual evapotranspiration (ETa) over a period of six years (2000-2005) for two major irrigated river basins in Afghanistan, the Kabul and the Helmand, by analyzing up to 19 cloud-free thermal and NDVI images from each year. These seasonal ETa estimates were used as relative indicators of year-to-year production magnitude differences. The temporal water-use pattern of the two irrigated basins was indicative of the cropping patterns specific to each region. Our results were comparable to field reports and to estimates based on watershed-wide crop water-balance model results. For example, both methods found that the 2003 seasonal ETa was the highest of all six years. The method also captured water management scenarios where a unique year-to-year variability was identified in addition to water-use differences between upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water-balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields. ?? 2007 by MDPI.

Sensors↗