Urban forests mitigate stormwater runoff, yet the contribution of particular trees depends partly upon form, structure, and configuration (location in the landscape relative to immediate surroundings). Additionally, these factors may be associated with ecohydrological landscape characteristics (ELCs) such as species, leaf area, and ground covers that also mediate ecohydrological processes. It is logistically challenging to assess individual attributes of every urban tree and their interactions with neighboring landscape features, but also difficult to link these individual attributes with policy or management. In this study, we asked can we meaningfully assess the stormwater mitigation impacts of urban forest types that include their ecohydrological differences and interactions?
We hypothesize that this can be achieved through development of an ecohydrological typology.
Our objectives are: (1) define common groupings of urban forest characteristics that influence ecohydrology, (2) qualitatively assess the runoff mitigation potential of each grouping.
We extracted ELCs from Urban Forest Inventory and Analysis (FIA) plots in Austin, Texas. Urban FIA data is currently being collected for many cities in the United States, making new types of analysis possible. Using hierarchical cluster analysis we derived distinct ELC groupings to define distinct urban forest types and qualitatively assessed stormwater interception potentials of these clusters.
Results/Conclusions
We classified plots into seven distinct urban forest types. About a quarter of the plots were grouped into predominantly “treed” clusters. The first treed cluster (10.7% of plots) was characterized by permeable ground surfaces (e.g., mulch or bare soil) and a tree configuration resembling remnant forests. The second treed cluster (14.5% of plots) was characterized by herbaceous cover such as grass and ivy and closely resembled parks or golf courses, with large grassy areas and widely spaced trees. The largest cluster (28.6% of plots) was characterized by herbaceous cover without trees. The plots in this cluster were similar to lawns. Over a third of the clusters were characterized by buildings and impervious surface. The treed clusters were further segregated into subgroups. We will present rankings of each of these groups based on the associated ELCs for their stormwater mitigation potential. Governments are grappling with how to employ urban forests for stormwater management; and an urban forest typology may be an effective policy tool. Future research will assess whether ecohydrological urban forest types can be detected with remote sensing techniques. Such an assessment method could offer a new framework for analysis of where and why specific urban forest “types” occur.