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M.R. Clark

Publications and source records attributed to M.R. Clark.

3 recordsLinked to original sources
USGS2016

10,000 m under the sea: An overview of the HADES expedition to Kermadec Trench

The hadal zone of the world oceans (6000– 11,000 m) occupies <1% of the marine realm and is found almost exclusively in trenches but represents ~40% of the total ocean depth range. Jamison et al. (2010 & Jamison, 2015) have reviewed the current state of knowledge about the hydrology, physical characteristics, food supply, ecology and biodiversity of life in hadal trenches. This review concluded that, there appears to be a high level of endemism based on the few specimens collected from historical sampling efforts in the 1950s (Danish Galathea and Soviet Vitjaz expeditions), but because trenches are still largely unexplored there is a lot we do not know about the ecological structure and functioning of hadal environments. However, relatively recent advances in technology using remotely operated vehicles (ROV) and landers can help us explore hadal trenches in greater detail.

Conference Paper↗
USGS2011

Spatial interpolation schemes of daily precipitation for hydrologic modeling

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.

Colorado, Georgia↗