My research vision and motivation
Across the world, water resources management is becoming more and more complex with the increasing pressures of climate change, population growth, and economic development. These challenges demand innovative research that can be readily put into action by stakeholders. However, after promising research is launched into the world, it often ends up in the "valley of death" rather than being effectively used by society (see figure below). This is largely because academic research is often conducted with little consideration of the needs and capacities of end-users. In light of this issue, the aim of my PhD research was to cross the "valley of death" by going from research that is "use-inspired" to "user-ready."
In addition to the information below, you can watch practice run of my PhD defense (which took place July 22, 2020) in the video to the right.
My core motivation is to improve livelihoods of the people that are most vulnerable to our changing environment as well as inequitable and unsustainable water management. The most vulnerable people are also often marginalized in water management and decision-making. I aim for my work to promote prudent management of rivers, land, and infrastructure so that humans- especially those that are vulnerable and marginalized- and the environment can thrive.
The guiding question of my PhD research:
How can state-of-the-art research approaches to understanding watershed sediment dynamics—particularly computational modeling and satellite remote sensing—be better oriented towards watershed planning, management, engineering, and decision-making?
I aim to work with stakeholders and decision-makers to advance adaptive watershed management approaches that are locally sustainable. I strive to develop a holistic understanding of local water resource systems; that is, not just the scientific and engineered aspects, but also the local history, context, and social power dynamics surrounding water (see figure on left). I prioritize developing trustful relationships with local partners and an authentic understanding of their water management challenges and opportunities.
Why study river sediment? Sediment plays a key role in the stability and functioning of rivers, floodplains, and deltas. It provides critical habitat for aquatic species. It carries nutrients that cultivate biodiversity and naturally fertilize agriculture. It influences water quality.
However, these important functions of sediment can be dramatically impacted by environmental change (e.g., climate, land use) and infrastructure (e.g., dams). In turn, sediment can degrade the lifespan and effectiveness of infrastructure (e.g., due to reservoir sedimentation).
Hence, it is imperative for water managers to be able to monitor, model, and understand changing watershed sediment dynamics.
Part 1: A channel network model for sediment dynamics over watershed management time scales: Case study in the Elwha River Basin of Washington State
In 2017, I visited the Elwha watershed for 1 week. During that time I enjoyed meeting with Lower Elwha Klallam Tribe members, city residents, local water managers, and scientists from the US Geological Survey and National Park Service. I learned about how these stakeholders have been involved in and impacted by the operation and removal of the two Elwha dams.
Background/Methods: I developed a river channel network model for estimating source-to-sink sediment dynamics in mountainous watersheds. The model is applicable over time (decadal to centurial) and space (1-100 km2) scales relevant to management of reservoirs, lakes, streams, and watersheds.
The model has three unique features: (1) it combines bedload and suspended load; (2) streamflow is simulated using a physically-based hydrology model (DHSVM); and (3) sediment inputs to streams are from a random mass wasting (i.e., landsliding) algorithm. Sediment mass balance is conducted each day for each stream segment in the watershed (see Figure 1 on left).
The model was demonstrated in the Elwha River Basin of Washington State, upstream of the former Glines Canyon dam (see Figure 2 on left). The removal of the two Elwha dams is the largest global dam removal yet in history.
Results: The model was run over the former Glines Canyon dam’s 84-year lifespan and compared to the volume of sediment that was measured in the reservoir just prior to dam removal. The model repeatedly predicted the lifetime reservoir sedimentation volume within the uncertainty range of the total measured volume. The model also predicted within the uncertainty range of the measured gravel, sand, and mud fractions in the reservoir. The network model sediment yields were improved compared to yields from sediment rating curves at the basin outlet, which are commonly used in practice. In addition, the network model provided sediment predictions distributed over time and space, which allow for inquiry and understanding of the watershed system beyond the sediment yields at the outlet.
This work advances cross-disciplinary and application-oriented watershed sediment yield modeling approaches, which are needed for better dam and sediment management under increasing environmental change.
More information: The publication is available here. The model code (written in Python programming language) is publicly available on GitHub.
Part 2: Impacts of dam development and landscape changes on suspended sediment concentrations in the Mekong River Basin’s ‘3S’ tributary: a satellite remote sensing perspective
Background/Methods: I used satellite remote sensing records to understand changes in river suspended sediment concentration (SSC) patterns due to dam development and landscape changes. I focused on the '3S' tributary of the Mekong River Basin (see figure on left), which has the largest tributary contribution of sediment and streamflow to the Mekong Basin. The 3S tributary has been undergoing rapid dam development in recent decades.
I developed a simple empirical model for predicting SSC from water surface reflectance (visible and near infrared) throughout the 3S tributary rivers. Using this empirical model and Landsat satellite records, I estimated seasonal SSC patterns over the past 31 years (1988-2019). I also used satellite data to explain how dams and landscape changes influenced the SSC patterns. Dam building timelines were derived from visible imagery (Landsat); landscape changes derived from land cover data (MODIS); and human settlement patterns derived from nighttime light data (DMSP).
Results: I quantified (1) SSC levels prior to major dam development; (2) SSC increases due to dam construction; (3) SSC increases due to deforestation and other land cover changes; and (4) SSC decreases due to dam operations. I also showed how SSC patterns from the 3S tributary outlet have impacted the SSC of the Mekong River mainstem over time.
Overall, this study demonstrated the capacity of satellite remote sensing to detect impacts of dams and landscape changes on suspended sediment at the sub-basin scale. This spatial scale is highly relevant to watershed management and decision-making. Furthermore, this study responds to the practical need for improved sediment monitoring in the Mekong River Basin, particularly with broad spatial and temporal coverage and with respect to the locations and lifecycles of dams. The approach used in this study can be implemented throughout the MRB and in other global river basins undergoing dam development. Findings from this study and future applications can inform where and how suspended sediment impacts can be managed and mitigated.
More information: The final publication is available here, however requires payment or subscription. A free, draft version is here.
Part 3: Stakeholder-driven development of a cloud-based, satellite remote sensing tool to support sediment management and engineering for major rivers in Bangladesh
Background/Methods: I conducted capacity building and stakeholder engagement work with the Bangladesh Water Development Board (BWDB). We co-developed cloud-computing tools for satellite-based monitoring of suspended sediment concentrations in Bangladesh’s major rivers. The goal of this tool was to help BWDB improve their prediction and understanding of riverbank erosion and accretion patterns throughout the country, which often has devastating impacts on riverbank communities.
In January 2020, I traveled to Bangladesh for two weeks. During this time, I met with BWDB and local partner institutions to present the prototype tool, train the staff on how to use it, and receive their feedback. I also visited various BWDB field sites to observe sediment and riverbank erosion challenges. I learned about the "real-world" water management and engineering constraints, and how the river sediment monitoring tool could be effectively incorporated into operations. I also visited multiple villages and learned about how riverbank erosion and sediment issues are impacting rural livelihoods.
Results: Two free, web-based "BROSS" (Bangladesh Remote Sensing of Suspended Sediment) tools have been released for satellite-based monitoring of SSC. One is in Google Earth Engine (figure below), and one is hosted on a local server using an open-source framework. The key elements of success in the engagement process were presented (figure on bottom left).
More information: The final publication is available here (Free, draft version is here).
Acknowledgements
Thank you to the following organizations for funding my doctoral research:
2017-2020: National Science Foundation (NSF) Graduate Research Fellowship (GRFP) (3 years)
2016-2017: Northwest Climate Adaptation Science Center Graduate Research Fellowship (2 quarters)
2016-2017: Hydro Research Foundation Fellowship (2 quarters)
2015-2016: UW Charles V. Tom and Jean C. Gibbs Endowed Presidential Fellowship in Environmental Engineering (1 year)
2019: UW Golder Fellowship ($2,000 funding for research travel to Bangladesh)
"Dhonnobad" to the Bangladesh Water Development Board for generously hosting me for two weeks in Bangladesh, as well as the ongoing support they provide for our collaborative work.