Graduation Year

2018

Document Type

Thesis

Degree

M.S.E.V.

Degree Name

MS in Environmental Engr. (M.S.E.V.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Mauricio Arias, Ph.D.

Committee Member

Autar Kaw, Ph.D.

Committee Member

James Mihelcic, Ph.D.

Abstract

Hydropower relies on protection of watersheds to regulate water and sediment yields. Deforestation accelerates the rate of soil erosion, thereby increasing the amount of river sediments heading to the dam's reservoir, decreasing the longevity of the dam. In Cambodia in particular, recent deforestation rates are among the largest on the planet, and forests are expected to disappear within the lifespan of proposed dams. The cost of protecting and restoring forested watersheds can be considered as an annual investment towards sustainable reservoir management and hydropower generation. A modeling framework is developed to estimate the sediment accumulation in reservoirs from deforestation-driven soil erosion. Associated power generation loss is then calculated, and by relating it to current electricity tariffs, the annualized and present monetary value associated with the benefits of forest conservation to hydropower are estimated. This framework is applied to four large hydropower proposed dams in Cambodia. With an ongoing average deforestation rate of 0.85-1.65% in the past 5 years, some reservoir watersheds could lose all forest cover in the coming 40-75 years. This could increase the current sediment yield up by 1.5-1.8 times resulting in acceleration of reservoir filling with sediments, which depending on their size, could lose up to 60-100% of their storage capacity over a period of 120 years. This would incur additional sediment removal costs to the hydropower industry, which could be reduced through investments in forest conservation and restoration, potentially financed via a payments for ecosystem services scheme. The estimated net present values of power loss in Stung Sen, Pursat-I, Battambang-I and Battambang were found to be as high as US $0, $2.58, $44.8 and $28.8 million respectively. The modeling tool is designed to be generic and transferable to other rivers globally where hydropower development is accelerating.

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