Modeling snowmelt runoff in an arctic coastal plain

Present and impending oil exploration and development activity on Alaska's Arctic Coastal Plain has created a need to better understand the region's water resources. The remoteness of the area and an almost complete lack of hydrologic data preclude the use of usual hydrologic analysis tech...

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Bibliographic Details
Main Authors: Carlson, Robert F., Norton, William, McDougall, James
Format: Report
Language:unknown
Published: University of Alaska, Institute of Water Resources 1974
Subjects:
Online Access:http://hdl.handle.net/11122/1105
Description
Summary:Present and impending oil exploration and development activity on Alaska's Arctic Coastal Plain has created a need to better understand the region's water resources. The remoteness of the area and an almost complete lack of hydrologic data preclude the use of usual hydrologic analysis techniques. Attempts by the Institute of Water Resources to synthesize this data led to the development of snowmelt runoff models which simulate the spring runoff, an important part of the hydrologic system. The snowmelt model produces a snowmelt hydrograph which is converted by the runoff model into a runoff hydrograph. The snowmelt model subdivides the snowpack into two layers. Daily climatological parameters govern the heat transfer between snowpack and atmosphere. Once the heat flux received or emitted by the snowpack has been computed, the melting processes within the snowpack are considered. Computed parameters of the snowpack are density, depth, water equivalent, water content, temperature, and thermal quality. The runoff model uses a three-parameter linear storage model to transform the snowmelt hydrograph into a runoff hydrograph. The parameters represent the amount of storage, the rate of runoff, and the lag between snowmelt and runoff. Using Prudhoe Bay weather data as input, and comparing the output to runoff data from the Kuparuk, Putuligayuk, and Sagavanirktok Rivers for the years 1970 and 1971, produced results which indicate that the models perform satisfactorily.