REMOTE SENSING DATA ASSIMILATION IN WATER QUALITY NUMERICAL MODELS FOR SIMULATION OF WATER COLUMN TEMPERATURE

Indiana University-Purdue University Indianapolis (IUPUI)Numerical models are important tools for simulating processes within complex natural systems, such as hydrodynamics and water quality processes within a water body. From decision makers’ perspectives, such models also serve as useful tools for predicting the impacts of water quality problems or develop early warning systems. However, accuracy of a numerical model developed for a specific site is dependent on multiple model parameters and variables whose values are attained via calibration processes and/or expert knowledge. Real time variations in the actual aquatic system at a site necessitate continuous monitoring of the system so that model parameters and variables are regularly updated to reflect accurate conditions. Multiple sources of observations can help adjust the model better by providing benefits of individual monitoring technology within the model updating process. For example, remote sensing data provide a spatially dense dataset of model variables at the surface of a water body, while in-situ monitoring technologies can provide data at multiple depths and at more frequent time intervals than remote sensing technologies. This research aims to present an overview of an integrated modeling and data assimilation framework that combines three-dimensional numerical model with multiple sources of observations to simulate water column temperature in a eutrophic reservoir in central Indiana. A variational data assimilation approach is investigated for incorporating spatially continuous remote sensing observations and spatially discrete in-situ observations to change initial conditions of the numerical model. This research addresses the challenge of improving the model performance by combining water temperature from multi-spectral remote sensing analysis and in-situ measurements. Results of the approach on a eutrophic reservoir in Central Indiana show that with four images of multi-spectral remote sensing data assimilated, the model results oscillate more from the in-situ measurements during the data assimilation period. For validation, the data assimilation has negative impacts on the root mean square error. According to quantitative analysis, more significant water temperature stratification leads to larger deviations. Sampling depth differences for remote sensing technology, in-situ measurements and model output are considered as possible error source

Proactive Assessment of Climate Change and Contaminant Spill Impacts on Source Water Quality

Managing the water quality of surface drinking water sources has become an increasingly difficult task for water suppliers due to increased watershed urbanization and climate change. Changes in source water quality may affect public perceptions, treatment effectiveness, and ultimately costs to treat water to drinking standards. Although there are increased threats to current and future drinking water quality, current approaches to managing these threats are typically reactionary. Prior detailed modeling efforts of hypothetical events that may impair raw water quality allow for an understanding of constituent fate and transport, including potential maximum concentrations and travel times to the drinking water intake for constituents which may be of concern. The primary goal of this dissertation was to present proactive frameworks that utilize a hydrodynamic and water quality model to aid in developing scientifically-based management plans prior to an accidental or natural event occurring. The Wachusett Reservoir, a major drinking water supply for metropolitan Boston, Massachusetts, was used as a case study to illustrate proactive modeling efforts to quantify water quality impacts after both short and long-term potential events. This work used a process-based modeling approach to simulate reservoir hydrodynamic and water quality responses to changes in various model inputs (streamflow, constituents, meteorology) and also evaluated current and future management decisions which may mitigate water quality impacts. The approach is demonstrated through a series of proactive modeling studies conducted to evaluate water quality at the drinking water intake in response to contaminant incidences, long-term increasing air temperatures, and extreme precipitation events. For the Wachusett Reservoir, proactive contaminant modeling highlighted the importance of a rapid response by managers to contain a contaminant spill and therefore minimizing the mass of contaminant that is able to enter the water column following an event. In scenarios that simulated long term increasing air temperature increases, model results suggested increases in epilimnion and hypolimnion water temperatures, decreased ice cover, and increased stratification duration by 2112. Extreme precipitation event simulations during the spring and summer resulted in organic matter concentrations that exceeded recorded maximums at the drinking water intake while nutrients for this particular reservoir remained low. The modeling results provide valuable insights into water quality responses to changes in water body inputs and can help inform short and long-term management strategies, prior to water quality degrading events

Developing Efficient High-Order Transport Schemes for Cross-Scale Coupled Estuary-Ocean Modeling

Geophysical fluid dynamics (GFD) models have progressed greatly in simulating the world’s oceans and estuaries in the past three decades, thanks to the development of novel numerical algorithms and the advent of massively parallel high-performance computing platforms. Study of inter-related processes on multi-scales (e.g., between large-scale (remote) processes and small-scale (local) processes) has always been an important theme for GFD modeling. For this purpose, models based on unstructured-grid (UG) have shown great potential because of their superior abilities in enabling multi-resolution and in fitting geometry and boundary. Despite UG models’ successful applications on coastal systems, significant obstacles still exist that have so far prevented UG models from realizing their full cross-scale capability. The pressing issues include the computation overhead resulting from large contrasts in the spatial resolutions, and the relative lack of skill for UG model in the eddying regime. Specifically for our own implicit UG model (SCHISM), the transport solver often emerges as a major bottleneck for both accuracy and efficiency. The overall goal of this dissertation is two-fold. The first goal is to address the challenges in tracer transport by developing efficient high-order schemes for the transport processes and test them in the framework of a community supported modeling system (SCHISM: Semi-implicit Cross-scale Hydroscience Integrated System Model) for cross-scale processes. The second goal is to utilize the new schemes developed in this dissertation and elsewhere to build a bona fide cross-scale Chesapeake Bay model and use it to address some key knowledge gaps in the physical processes in this system and to better assist decision makers of coastal resource management. The work on numerical scheme development has resulted in two new high-order transport solvers. The first solver tackles the vertical transport that often imposes the most stringent constraint on model efficiency (Chapter 2). With an implicit method and two flux limiters in both space and time, the new TVD2 solver leads to a speed-up of 1.6-6.0 in various cross-scale applications as compared to traditional explicit methods, while achieving 2nd-order accuracy in both space and time. Together with a flexible vertical gridding system, the flow over steep slopes can be faithfully simulated efficiently and accurately without altering the underlying bathymetry. The second scheme aims at improving the model skill in the eddying ocean (Chapter 4). UG coastal models tend to under-resolve features like meso-scale eddies and meanders, and this issue is partially attributed to the numerical diffusion in the transport schemes that are originally developed for estuarine applications. to address this issue, a 3rd-order transport scheme based on WENO formulation is developed, and is demonstrated to improve the meso-scale features. The new solvers are then tested in the Chesapeake Bay and adjacent Atlantic Ocean on small, medium and large domains respectively, corresponding to the three main chapters of this dissertation (Chapter 2-4), with an ultimate goal of achieving a seamless cross-scale model from the Gulf Stream to the shallow regions in the Bay tributaries and sub-tributaries. We highlight the dominant role played by the bathymetry in nearshore systems and the detrimental effects of bathymetric smoothing commonly used in many coastal models (Chapter 3). With the new methods developed in this dissertation and elsewhere, the model has enabled the analyses on some important processes that are hard to quantify with traditional techniques, e.g., the effect of channel-shoal contrast on lateral circulation and salinity distribution, hypoxia volume, the influence of realistic bathymetry on the freshwater plume etc. Potential topics for future research are also discussed at the end. In addition, the new solvers have also been successfully exported to many other oceanic and nearshore systems around the world via user groups of our community modeling system (cf. ‘Publications’ under ‘schism.wiki’)

Issues Related to Incorporating Northern Peatlands into Global Climate Models

Northern peatlands cover ~3–4 million km2 (~10% of the land north of 45°N) and contain ~200–400 Pg carbon (~10–20% of total global soil carbon), almost entirely as peat (organic soil). Recent developments in global climate models have included incorporation of the terrestrial carbon cycle and representation of several terrestrial ecosystem types and processes in their land surface modules. Peatlands share many general properties with upland, mineral-soil ecosystems, and general ecosystem carbon, water, and energy cycle functions (productivity, decomposition, water infiltration, evapotranspiration, runoff, latent, sensible, and ground heat fluxes). However, northern peatlands also have several unique characteristics that will require some rethinking or revising of land surface algorithms in global climate models. Here we review some of these characteristics, deep organic soils, a significant fraction of bryophyte vegetation, shallow water tables, spatial heterogeneity, anaerobic biogeochemistry, and disturbance regimes, in the context of incorporating them into global climate models. With the incorporation of peatlands, global climate models will be able to simulate the fate of northern peatland carbon under climate change, and estimate the magnitude and strength of any climate system feedbacks associated with the dynamics of this large carbon pool

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a 3-Dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of Solar System and exoplanetary terrestrial planets. Its parent model, known as ModelE2 (Schmidt et al. 2014), is used to simulate modern and 21st Century Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (slowly rotating to more rapidly rotating than modern Earth, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the Solar System such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn's moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents we can then expand its capabilities further to those exoplanetary rocky worlds that have been discovered in the past and those to be discovered in the future. We discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.Comment: Revisions since previous draft. Now submitted to Astrophysical Journal Supplement Serie

An evaluation of the signature extension approach to large area crop inventories utilizing space image data

The author has identified the following significant results. Two examples of haze correction algorithms were tested: CROP-A and XSTAR. The CROP-A was tested in a unitemporal mode on data collected in 1973-74 over ten sample segments in Kansas. Because of the uniformly low level of haze present in these segments, no conclusion could be reached about CROP-A's ability to compensate for haze. It was noted, however, that in some cases CROP-A made serious errors which actually degraded classification performance. The haze correction algorithm XSTAR was tested in a multitemporal mode on 1975-76 LACIE sample segment data over 23 blind sites in Kansas and 18 sample segments in North Dakota, providing wide range of haze levels and other conditions for algorithm evaluation. It was found that this algorithm substantially improved signature extension classification accuracy when a sum-of-likelihoods classifier was used with an alien rejection threshold

Cross-Scale Baroclinic Simulation of the Effect of Channel Dredging in an Estuarine Setting

Holistic simulation approaches are often required to assess human impacts on a river-estuary-coastal system, due to the intrinsically linked processes of contrasting spatial scales. In this paper, a Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) is applied in quantifying the impact of a proposed hydraulic engineering project on the estuarine hydrodynamics. The project involves channel dredging and land expansion that traverse several spatial scales on an ocean-estuary-river-tributary axis. SCHISM is suitable for this undertaking due to its flexible horizontal and vertical grid design and, more importantly, its efficient high-order implicit schemes applied in both the momentum and transport calculations. These techniques and their advantages are briefly described along with the model setup. The model features a mixed horizontal grid with quadrangles following the shipping channels and triangles resolving complex geometries elsewhere. The grid resolution ranges from similar to 6.3 km in the coastal ocean to 15 m in the project area. Even with this kind of extreme scale contrast, the baroclinic model still runs stably and accurately at a time step of 2 min, courtesy of the implicit schemes. We highlight that the implicit transport solver alone reduces the total computational cost by 82%, as compared to its explicit counterpart. The base model is shown to be well calibrated, then it is applied in simulating the proposed project scenario. The project-induced modifications on salinity intrusion, gravitational circulation, and transient events are quantified and analyzed

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world\u27s largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system

A 3D unstructured-grid model for Chesapeake Bay: importance of bathymetry

We extend the 3D unstructured-grid model previously developed for the Upper Chesapeake Bay to cover the entire Bay and its adjacent shelf, and assess its skill in simulating saltwater intrusion and the coastal plume. Recently developed techniques, including a flexible vertical grid system and a 2nd-order, monotone and implicit transport solver are critical in successfully capturing the baroclinic responses. Most importantly, good accuracy is achieved through an accurate representation of the underlying bathymetry, without any smoothing. The model in general exhibits a good skill for all hydrodynamic variables: the averaged root-mean-square errors (RMSE‟s) in the Bay are 9 cm for sub-tidal frequency elevation, 17 cm/s for 3D velocity time series, 1.5 PSU and 1.9 PSU for surface and bottom salinity respectively, 1.1 °C and 1.6 °C for surface and bottom temperature respectively. On the shelf, the average RMSE for the surface temperature is 1.4 °C. We highlight, through results from sensitivity tests, the central role played by bathymetry in this estuarine system and the detrimental effects, from a common class of bathymetry smoothers, on volumetric and tracer fluxes as well as key processes such as the channel-shoal contrast in the estuary and plume propagation in the coast. Associated Data is available: https://doi.org/10.21220/V5HK5