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Forest management depends on forest condition data and the ability to quantify the impacts of management activities to make informed decisions. Spatially quantifying water yield (WY) from forests across large landscapes enables managers to consider potential WY changes when designing forest management plans. Current forest water yield datasets are either spatially coarse or too restricted to specific sites with in situ monitoring to support some project-level forest management decisions. In this study, we spatially apply a stand-level southern pine WY model over a forested landscape in the Florida panhandle. We informed the WY model with pine leaf area index inputs created from lidar remote sensing and field data, a spatial and temporal aridity index from PRISM and MODIS data, and a custom depth to groundwater dataset. Baseline WY conditions for the study area were created using the Esri and Python tools we developed to automate the WY workflow. Several timber thinning scenarios were then used to quantify water yield increases from forest management activities. The results of this methodology are detailed (10 m spatial resolution) forest WY raster datasets that are currently being integrated with other spatial datasets to inform forest management decisions.

Near drainage culverts located in the Apalachicola National Forest, and particularly within the New River (HUC8) subbasin, and the State of Florida Waterbody IDs (WBID) 1034B boundary, water quality commonly fails to attain designated minimum criteria for iron within surface waters established in the Surface Water Quality Standards (62-302, FAC), and the Impaired Waters Rule (IWR, FAC). Three iron release mechanisms, i.e., organic decomposition coupled with Fe(III) reduction (IRM I), iron-related mineral decomposition (IRM II), and elemental iron corrosion (IRM III) were identified and found to be responsible for ferrous iron release. The soil and water samples were collected from eleven culvert sites within the Apalachicola National Forest and analyzed. Various statistical methods were used to identify the correlation of iron release mechanisms with measured parameters. Using partial least square regression, four components were found to capture the variances that significantly contributed to the various iron concentration, among which P1 and P2 were the two dominating contributors and were associated with IRM I and IRM II. P3 accounted for 6.5% of the variance and was attributed to IRM III. Based on IRM II, ferrous iron was released from pyrite decomposition, which was correlated with elevated sulfate concentration in the water. The soil samples were analyzed together by X-ray powder diffraction (XRD) and X-ray fluorescence (XRF), further evidenced that sulfate-related mineral contributed to this process. For IRM I, the decomposition of organics releases electrons, which eventually reduces iron oxides to mobile ferrous iron. Corresponding to the organic decomposition, low dissolved oxygen (DO) was also observed. Although IRM III was found to be responsible for a smaller portion of iron release, it was deemed not to be the dominating mechanism of iron release.

Abstract. With a burgeoning world population that is expected to reach 10 billion by 2050, 30 % more than today, there is an urgent need to harness available water resources to support regions across the world. This study introduces a new method to identify, prioritize, and select areas for pine basal area reduction to maximize water yields in pine forests along the Northern Gulf of Mexico, USA. The method, demonstrated in the Apalachicola Region of Northwest Florida, an area covered by dense vegetation and pine plantation forests, has experienced freshwater loss due to increased upstream water demand, climate change, and past forest management practices. Potential initial water-yield gains were: 1) 469 m3 d−1 if all pine basal areas were reduced from current to a maximum of 18 m2 ha−1, and 53,400 m3 d−1 if pine basal areas were reduced from current to a maximum of 7 m2 ha−1 for the Apalachicola Region. The method identifies watersheds mainly along the Apalachicola and other rivers and near the Gulf coast that have the greatest potential to increase water yields. Increasing forest water yields translates to increased freshwater availability and improved forest and soil health, water quality, and ecosystem function, services, and resilience, as well as socioeconomic outcomes for communities and people who rely on ecotourism and fisheries for their livelihoods. This method will empower forest managers to focus scarce resources in targeted areas to maximize water-resource benefits per resource investment. Although demonstrated in the Apalachicola Region, the method is easily transferable throughout other pine forests of the Northern Gulf Coast Region. This scientifically sound method is repeatable, scalable, and easily upgraded and adapted as newer, higher resolution datasets become available and relationships between forest metrics, evapotranspiration, and water yields are improved.