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Y. Kerr

Publications and source records attributed to Y. Kerr.

2 recordsLinked to original sources

Seasonal estimates of riparian evapotranspiration using remote and in situ measurements

In many semi-arid basins during extended periods when surface snowmelt or storm runoff is absent, groundwater constitutes the primary water source for human habitation, agriculture and riparian ecosystems. Utilizing regional groundwater models in the management of these water resources requires accurate estimates of basin boundary conditions. A critical groundwater boundary condition that is closely coupled to atmospheric processes and is typically known with little certainty is seasonal riparian evapotranspiration ET). This quantity can often be a significant factor in the basin water balance in semi-arid regions yet is very difficult to estimate over a large area. Better understanding and quantification of seasonal, large-area riparian ET is a primary objective of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. To address this objective, a series of interdisciplinary experimental Campaigns were conducted in 1997 in the San Pedro Basin in southeastern Arizona. The riparian system in this basin is primarily made up of three vegetation communities: mesquite (Prosopis velutina), sacaton grasses (Sporobolus wrightii), and a cottonwood (Populus fremontii)/willow (Salix goodingii) forest gallery. Micrometeorological measurement techniques were used to estimate ET from the mesquite and grasses. These techniques could not be utilized to estimate fluxes from the cottonwood/willow (C/W) forest gallery due to the height (20-30 m) and non-uniform linear nature of the forest gallery. Short-term (2-4 days) sap flux measurements were made to estimate canopy transpiration over several periods of the riparian growing season. Simultaneous remote sensing measurements were used to spatially extrapolate tree and stand measurements. Scaled C/W stand level sap flux estimates were utilized to calibrate a Penman-Monteith model to enable temporal extrapolation between Synoptic measurement periods. With this model and set of measurements, seasonal riparian vegetation water use estimates for the riparian corridor were obtained. To validate these models, a 90-day pre-monsoon water balance over a 10 km section of the river was carried out. All components of the water balance, including riparian ET, were independently estimated. The closure of the water balance was roughly 5% of total inflows. The ET models were then used to provide riparian ET estimates over the entire corridor for the growing season. These estimates were approximately 14% less than those obtained from the most recent groundwater model of the basin for a comparable river reach.

Conference Paper

Compositing multitemporal remote sensing data sets

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Pecora 12 Symposium