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Jordan Read

Publications and source records attributed to Jordan Read.

22 records · Page 2Linked to original sources

Heterogeneous stream-reservoir graph networks with data assimilation

Accurate prediction of water temperature in streams is critical for monitoring and understanding biogeochemical and ecological processes in streams. Stream temperature is affected by weather patterns (such as solar radiation) and water flowing through the stream network. Additionally, stream temperature can be substantially affected by water releases from man-made reservoirs to downstream segments. In this paper, we propose a heterogeneous recurrent graph model to represent these interacting processes that underlie stream-reservoir networks and improve the prediction of water temperature in all river segments within a network. Because reservoir release data may be unavailable for certain reservoirs, we further develop a data assimilation mechanism to adjust the deep learning model states to correct for the prediction bias caused by reservoir releases. Our evaluation for the Delaware River Basin has demonstrated the superiority of our proposed method over multiple existing methods. We have extensively studied the effect of the data assimilation mechanism under different scenarios.

IEEE International Conference on Data Mining (ICDM

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report

Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate

Lakes support globally important food webs through algal productivity and contribute significantly to the global carbon cycle. However, predictions of how broad-scale lake carbon flux and productivity may respond to future climate are extremely limited. Here, we used an integrated modeling framework to project changes in lake-specific and regional primary productivity and carbon fluxes under 21st century climate for thousands of lakes. We observed high uncertainty in whether lakes collectively were to increase or decrease lake CO 2 emissions and carbon burial in our modeled region owing to divergence in projected regional water balance among climate models. Variation in projected air temperature influenced projected changes in lake primary productivity (but not CO 2 emissions or carbon burial) as warmer air temperatures decreased productivity through reduced lake water volume. Cross-scale interactions between regional drivers and local characteristics dictated the magnitude and direction of lake-specific carbon flux and productivity responses to future climate.

Geophysical Research Letters

Evaluating the “Gradual Entrainment Lake Inverter” (GELI) artificial mixing technology for lake and reservoir management

Thermal stratification is important to the structure and function of lake and reservoir ecosystems. Yet when lakes undergo eutrophication, thermal stratification can exacerbate water quality problems. As a result, lake management has sometimes involved artificial mixing and destratification, though the available technologies are few and costly. It is therefore important to test the efficacy of new technologies when they arise. Here, we evaluate a lake mixing technology, the “Gradual Entrainment Lake Inverter” (GELI), which was used to mix Crystal Lake, Wisconsin, a 34 ha, 21 m deep, dimictic lake during the summer months of 2012 and 2013. To assess the effect of the GELI treatment on thermal regime, we used DYRESM to model thermal conditions in the 2 treatment years but in the absence of treatment. We found GELI treatment slowly reduced stratification and the temperature range of the lake to 4.2 and 5.3 C in each treatment year, on average. Full destratification and oxygenation of the water column prevented fall hypoxia and anoxia. We found efficiency of the GELI averaged 1.9% during treatment, which is higher than efficiencies reported from field applications of bubble plume aeration. We used DYRESM to simulate bubble plume aeration to match the observed destratification from our GELI treatment and estimate aeration would have required 1.4–1.8 times the airflow and power costs of the GELI. Though considerable limitations of the current iteration of this technology exist, these may be reduced in future versions, possibly leading to a practical lake and reservoir management tool.

Land and Reservoir Management