We will establish an interdisciplinary student-led environmental observation and experimental watershed infrastructure and curriculum with field and lab research, data synthesis and analysis, formal classroom education, and targeted public outreach components. We will not only address fundamental aquatic ecosystem function questions in the Ala Wai watershed (Manoa and Palolo valleys), but also cross-train undergraduate and graduate students with environmental science methods and resilience and capacity-building strategies using cutting-edge and emergent innovations. Summarized below are our approaches for targeting: (i) technological innovation as a guiding principle for assisting watershed science;
(ii) watershed stream and groundwater hydrology; (iii) terrestrial, aquatic, and coastal water quality and biogeochemistry; (iv) microbiological diversity and function along a conservation-land-to-urban-corridor transition; (v) forecasting of Ala Wai Canal coastal dynamics and pathogens; and (vi) formal curriculum integration and informal public STEM training.
(i) Sensors and instruments: Recent technological innovations in consumer electronics have drastically reduced the cost of sensors that can be used for environmental monitoring. However, most of these advances have not yet been applied to aquatic sciences, and aquatic scientists have been forced to rely on expensive instruments developed for use by scientists with access to large research and development budgets. This has limited our understanding of dynamic, geographically complex ecosystems such as the Ala Wai watershed, which in turn limits efforts to build resilience and sustainability into such environments. We propose: (a) establishing a pool of low-cost sensors and instrumentation based on small single-board computers, (b) providing engineering expertise for student-led development of field-deployable sensor systems, (c) establishing a
coordinated monitoring program across the Ala Wai watershed, and (d) developing a public web-based visualization and dissemination system that will display near-real-time sensor data.
(ii) Hydrology: Quantifying hydrological interactions between precipitation, surface water runoff, and groundwater dynamics provides the basis for understanding sources and sinks for biogeochemical processes, and provides students with learning opportunities about the connectivity between different components along a gradient of urbanization in the Ala Wai watershed. In order to connect the coastal hydrodynamics in the Ala Wai with upland processes, a hydrological model will be developed and extended to the Ala Wai canal. A portion of the upper watershed (Manoa and Palolo Valley) has been modeled through a leveraged effort funded by the Water Resources and Research Center. A complete hydrological model of the Ala Wai watershed will provide necessary information on water fluxes at any given point and potentially describe the nutrient and sediment transport throughout the watershed. A successful hydrological model is driven by reliable meteorological data (e.g., precipitation and solar radiation) and the modeling output needs to be calibrated and validated with field observations, such as stream discharge, groundwater level, and corresponding loading/fluxes of nutrients, pesticides, and sediment. The proposed monitoring network will facilitate the capacity to achieve the necessary details in temporal and spatial scales of model development.
(iii) Biogeochemistry: Studying sources and sinks of nutrients and bio-reactive elements, as well as monitoring variations in the CO2-system parameters (pH, pCO2, DO, DIC), provides contextual information needed for ecosystem modeling and an understanding of the response of the estuarine and adjoining reef to forcing from the upper watershed. To achieve the above, it is critical to understand the spatial inputs of macronutrients (P, N and Si) and pre-formed organic matter into the watershed, and to establish the temporal variations of the fluxes of these materials under varying conditions of precipitation and hydraulic forcing of groundwater, as well as to measure the estuarine and coastal responses to these inputs. Quantifying sources of selected bioactive trace elements and pollutants within the watershed, and developing an understanding of the processes that modulate their fluxes to the coast, are also important to quantifying coastal productivity.
(iv) Microbial ecology: This proposal leverages existing strengths at UHM in the area of environmental microbiology and supports the UH Microbiome Initiative goals of broad sampling of microbiomes across the contiguous watershed. Student and community-led collection efforts, conducted synoptically with water quality fieldwork, will be paired with student and researcher analysis of microbial metagenomics to assess the holistic phylogenetic diversity and genetic content of microbial communities. These data are a direct window into the causes and consequences of shifting water quality on ecosystem process and human health, and existing courses (OCN 457 and others) and community outreach programs (ongoing through PICSC, WRRC and Sea Grant in cooperation with HDOH) already collect and generate these data using CMORE and WRRC infrastructure. Furthermore, these same sample sets will be used to implement testing for targeted human health risk indicator microbes, including both culture-based assays within HDOH regulatory frameworks and molecular assays being certified by USEPA. Together these approaches will provide training and outreach opportunities in both the basic microbial ecology of the watershed as well as direct links to water quality efforts ongoing across the state.
(v) Coastal hydrodynamics: The watershed empties into the Ala Wai canal, which collects runoff water, pollutants, and microbes. Through the narrow canal opening, these constituents are dispersed into the coastal ocean between the Ala Moana beach park and Waikiki. Using an existing 3D hydrodynamic model, we have developed a microbial model to understand the ecology of pathogen microbes in the Ala Wai (including
Vibrio vulnificus, Clostridium, and Enterococcus). Models serve to provide context and predictions for the observations in this program. This will be an integral component of the student-led observation effort by allowing students to integrate their observations with forecasts. The forecasts will be integrated into the PacIOOS framework such that the students will be helping to provide an important tool for stakeholders on the island.
(vi) Curriculum integration and outreach: We will augment UHM undergraduate courses with real-world data from within the Ala Wai watershed. We will integrate a coordinated field monitoring and sampling program into cross-cutting existing courses. OCN 101, 201, 310, 310L, 320, 363, 399, 401, 457, 623, 633; GG 106, 640; PLAN 620; NREM 301, 662, 664; and EDCS 640P, EDCS 623 can all use the data derived from the student observing system to teach basic environmental science principles and data evaluation. Classes such as OCN 310, 310L, and 401 could propose specific deployment and sampling strategies to guide new observational networked nodes for subsequent semesters. Students enrolled in OCN 318 and 418 would consult with the other classes for specific sampling needs and scientific rationale, and then design, build, test, and deploy new instruments to provide a complete collective student-led workflow.
The proposed work also provides a key focus for strengthening partnerships with local community organizations (Education Incubator, Purple Mai`a), private and public schools (Kamehameha Schools, ‘Iolani School, HIDOE), and budding synergies between diverse organizations within UH (STEM Pre-Academy, Lyon Arboretum, Sea Grant, PacIOOS, Ka Papa Loʻi O Kānewai). Further, OCN399, which prepares undergraduate students to select projects and mentors, could be a vehicle for these outside organizations to propose projects for senior-thesis research projects, and the OCN399 class could help match stakeholders with a GES student and a UH mentor.