Relationships between Forest Productivity and Water Yield Across Virginia's Forests

Landowners and managers are often incentivized solely for maximized forest productivity (i.e., increasing biomass or carbon); however, maximizing forest productivity can result in a decline in downstream water resources, highlighting the need for a better understanding of such tradeoffs to inform incentive programs aimed at influencing land management decisions. In this study, we use remotely sensed products to quantify forest productivity and water yield across the state of Virginia and analyze the relationships between them at differing spatial scales, across physiographic regions, and by forest cover type. Forest cover was delineated using annual National Land Cover Database (NLCD) land cover products. Net primary productivity, or carbon allocated to plant biomass after losses from respiration, was acquired using the MOD17 algorithm applied to Landsat (30-m resolution) and MODIS (250-m resolution) imagery. Water yield (WY), defined as precipitation minus evapotranspiration, was modeled using Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) along with PRISM precipitation data. Annual rates of WY and NPP were weakly correlated for both Landsat (ρ = 0.095) and MODIS (ρ = -0.088) ; however, ΔNPP and ΔWY, or the change in pixel-level annual WY and NPP over time, were more strongly and negatively correlated for both Landsat (ρ = -0.35) and MODIS (ρ = -0.5), suggesting strong tradeoffs. When observed by physiographic region, tradeoffs were most prominent in the Valley and Ridge and Blue Ridge. Comparing ΔNPP versus ΔWY rates, while excluding stand-varying environmental controls associated with annual rates, better isolates this tradeoff. Leveraging available remotely sensed information on forest productivity and water yield tradeoffs can better guide management decisions and better inform the provisioning of water yield in relation to other ecosystem services more commonly correlated with forest productivity.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Forestry

Department dc:contributor.department

Forest Resources and Environmental Conservation

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Finks, Lindsey Denise

Chairs dc:contributor.committeechair

• McLaughlin, Daniel L.
• Strahm, Brian

Committee members dc:contributor.committeemember

• Shao, Yang
• Thomas, Valerie Anne

• forest productivity
• forest water yield
• remote sensing

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:43101

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/132191