Texas Water Resources: Vulnerability from Contaminants

Numerical models of flow and transport are commonly applied for the sustainable management of water resources and for the selection of appropriate remediation techniques. However, these numerical models are not always accurate due to uncertain parameters and the disparity of scales across which observations are made, hydrological processes occur, and modeling is conducted. The modeling framework becomes further complex because hydrologic processes are coupled with chemical and biological processes. This dissertation focuses on the most widespread contaminants of surface and ground water, which are E. coli and nitrate, respectively. Therefore, this research investigates the linkages between bio-chemical and hydrologic processes for E. coli transport, explores the spatio-temporal variability of nitrate, quantifies uncertainty, and develops models for both E. coli and nitrate transport that better characterize these biogeochemical linkages. A probabilistic framework in the form of Bayesian Neural Networks (BNN) was used to estimate E. coli loads in surface streams and was compared with a conventional model LOADEST. This probabilistic framework is crucial when water quality data are scarce, and most models require a large number of mechanistic parameters to estimate E. coli concentrations. Results indicate that BNN provides better characterization of E. coli at higher loadings. Results also provide the physical, chemical, and biological factors that are critical in the estimation of E. coli concentrations in Plum Creek, Texas. To explore model parameters that control the transport of E. coli in the groundwater (GW) and surface water systems, research was conducted in Lake Granbury, Texas. Results highlight the importance of flow regimes and seasonal variability on E. coli transport. To explore the spatio-temporal variability of nitrate across the Trinity and Ogallala aquifers in Texas, an entropy-based method and a numerical study were employed. Results indicate that the overall mean nitrate-N has declined from 1940 to 2008 in the Trinity Aquifer as opposed to an increase in the Ogallala Aquifer. The numerical study results demonstrate the effect of different factors like GW pumping, flow parameters, hydrogeology of the site at multiple spatial scales. To quantify the uncertainty of nitrate transport in GW, an ensemble Kalman filter was used in combination with the MODFLOW-MT3DMS models. Results indicate that the EnKF notably improves the estimation of nitrate-N concentrations in GW. A conceptual modeling framework with deterministic physical processes and stochastic bio-chemical processes was devised to independently model E. coli and nitrate transport in the subsurface. Results indicate that model structural uncertainty provides useful insights to modeling E. coli and nitrate transport

Hot Spots and Persistence of Nitrate in Aquifers Across Scales

Nitrate-N (NO3 -- N) is one of the most pervasive contaminants in groundwater. Nitrate in groundwater exhibits long-term behavior due to complex interactions at multiple scales among various geophysical factors, such as sources of nitrate-N, characteristics of the vadose zone and aquifer attributes. To minimize contamination of nitrate-N in groundwater, it is important to estimate hot spots (>10 mg/L of NO3 -- N), trends and persistence of nitrate-N in groundwater. To analyze the trends and persistence of nitrate-N in groundwater at multiple spatio-temporal scales, we developed and used an entropy-based method along with the Hurst exponent in two different hydrogeologic settings: the Trinity and Ogallala Aquifers in Texas at fine (2 km × 2 km), intermediate (10 km × 10 km) and coarse (100 km × 100 km) scales. Results show that nitrate-N exhibits long-term persistence at the intermediate and coarse scales. In the Trinity Aquifer, overall mean nitrate-N has declined with a slight increase in normalized marginal entropy (NME) over each decade from 1940 to 2008; however, the number of hot spots has increased over time. In the Ogallala Aquifer, overall mean nitrate-N has increased with slight moderation in NME since 1940; however, the number of hot spots has significantly decreased for the same period at all scales

Understanding and Predicting Vadose Zone Processes

Vadose zone hydrologic and biogeochemical processes play a significant role in the capture, storage and distribution of contaminants between the land surface and groundwater. One major issue facing geoscientists in dealing with investigations of the unsaturated zone flow and transport processes is the evaluation of heterogeneity of subsurface media. This chapter presents a summary of approaches for monitoring and modeling of vadose zone dynamics in the presence of heterogeneities and complex features, as well as incorporating transient conditions. Modeling results can then be used to provide early warning of soil and groundwater contamination before problems arise, provide scientific and regulatory credibility to environmental management decision-making process to enhance protection of human health and the environment. We recommend that future studies target the use of RTMs to identify and quantify critical interfaces that control large-scale biogeochemical reaction rates and ecosystem functioning. Improvements also need to be made in devising scaling approaches to reduce the disconnect between measured data and the scale at which processes occur

Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions

We computationally explore the relationship between surface–subsurface exchange and hydrological response in a headwater-dominated high elevation, mountainous catchment in East River Watershed, Colorado, USA. In order to isolate the effect of surface–subsurface exchange on the hydrological response, we compare three model variations that differ only in soil permeability. Traditional methods of hydrograph analysis that have been developed for headwater catchments may fail to properly characterize catchments, where catchment response is tightly coupled to headwater inflow. Analyzing the spatially distributed hydrological response of such catchments gives additional information on the catchment functioning. Thus, we compute hydrographs, hydrological indices, and spatio-temporal distributions of hydrological variables. The indices and distributions are then linked to the hydrograph at the outlet of the catchment. Our results show that changes in the surface–subsurface exchange fluxes trigger different flow regimes, connectivity dynamics, and runoff generation mechanisms inside the catchment, and hence, affect the distributed hydrological response. Further, changes in surface–subsurface exchange rates lead to a nonlinear change in the degree of connectivity—quantified through the number of disconnected clusters of ponding water—in the catchment. Although the runoff formation in the catchment changes significantly, these changes do not significantly alter the aggregated streamflow hydrograph. This hints at a crucial gap in our ability to infer catchment function from aggregated signatures. We show that while these changes in distributed hydrological response may not always be observable through aggregated hydrological signatures, they can be quantified through the use of indices of connectivity

Synthesis, structural, DFT calculations and biological studies of rhodium and iridium complexes containing azine Schiff-base ligands

The reaction of [Cp*MCl2]2 (M = Rh/Ir) with N-Nʹ azine Schiff-base ligands (L1-L4) leads to the formation of mononuclear cationic half-sandwich complexes having the general formula [Cp*M(L)Cl]+ (1–8), (M = Rh/Ir and L = (2-hydroxy-4-methoxybenzylidene)2- pyridylamidrazone (L1), (2-hydroxybenzylidene)2-pyridylamidrazone (L2), (1-(2-hydroxyphenyl)ethylidene)2-pyridylamidrazone (L3) and (1-phenylethylidene)2-pyridylamidrazone (L4). All these complexes were isolated as their hexafluorophosphate salts and fully characterized by spectroscopic and analytical techniques. The molecular structure of complexes (1), (3), (4), (7) and (8) have been determined by single crystal X-ray crystallographic studies which displayed the coordination of the ligand to the metal in a bidentate N∩N fashion through nitrogen atom of pyridine and one azine nitrogen. The chemo-sensitivity activities of the complexes were evaluated against HT-29 (human colorectal cancer) cell line and non-cancer cell line ARPE-19 (human retinal epithelial cells) which revealed that the complexes are moderately cytotoxic to cancer cells over human cells although complex 5 was the most potent among all the compounds. Theoretical studies carried out using DFT and TD-DFT at B3LYP level shows good agreement with the experimental results

Biogeosciences perspectives on integrated, coordinated, open, networked (ICON) science

This article is composed of three independent commentaries about the state of ICON principles (Goldman et al. 2021) in the AGU Biogeosciences section and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: Global collaboration, technology transfer and application (Section 2), Community engagement, citizen science, education, and stakeholder involvement (Section 3), and Field, experimental, remote sensing, and real-time data research and application (Section 4). We discuss needs and strategies for implementing ICON and outline short- and long-term goals. The inclusion of global data and international community engagement are key to tackle grand challenges in biogeosciences. Although recent technological advances and growing open-access information across the world have enabled global collaborations to some extent, several barriers ranging from technical to organizational to cultural have remained in advancing interoperability and tangible scientific progress in biogeosciences. Overcoming these hurdles is necessary to address pressing large-scale research questions and applications in the biogeosciences, where ICON principles are essential. Here, we list several opportunities for ICON, including coordinated experimentation and field observations across global sites, that are ripe for implementation in biogeosciences as a means to scientific advancements and social progress

Biogeosciences Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles in the American Geophysical Union Biogeosciences section, and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (a) Global collaboration, technology transfer, and application (Section 2), (b) Community engagement, community science, education, and stakeholder involvement (Section 3), and (c) Field, experimental, remote sensing, and real-time data research and application (Section 4). We discuss needs and strategies for implementing ICON and outline short- and long-term goals. The inclusion of global data and international community engagement are key to tackling grand challenges in biogeosciences. Although recent technological advances and growing open-access information across the world have enabled global collaborations to some extent, several barriers, ranging from technical to organizational to cultural, have remained in advancing interoperability and tangible scientific progress in biogeosciences. Overcoming these hurdles is necessary to address pressing large-scale research questions and applications in the biogeosciences, where ICON principles are essential. Here, we list several opportunities for ICON, including coordinated experimentation and field observations across global sites, that are ripe for implementation in biogeosciences as a means to scientific advancements and social progress

The Extended Solar Cycle: Muddying the Waters of Solar/Stellar Dynamo Modeling or Providing Crucial Observational Constraints?

In 1844 Schwabe discovered that the number of sunspots increased and decreased over a period of about 11 years, that variation became known as the sunspot cycle. Almost eighty years later, Hale described the nature of the Sun's magnetic field, identifying that it takes about 22 years for the Sun's magnetic polarity to cycle. It was also identified that the latitudinal distribution of sunspots resembles the wings of a butterfly—showing migration of sunspots in each hemisphere that abruptly start at mid-latitudes (about ±35o) toward the Sun's equator over the next 11 years. These sunspot patterns were shown to be asymmetric across the equator. In intervening years, it was deduced that the Sun (and sun-like stars) possess magnetic activity cycles that are assumed to be the physical manifestation of a dynamo process that results from complex circulatory transport processes in the star's interior. Understanding the Sun's magnetism, its origin and its variation, has become a fundamental scientific objective—the distribution of magnetism, and its interaction with convective processes, drives various plasma processes in the outer atmosphere that generate particulate, radiative, eruptive phenomena, and shape the heliosphere. In the past few decades, a range of diagnostic techniques have been employed to systematically study finer scale magnetized objects, and associated phenomena. The patterns discerned became known as the “Extended Solar Cycle” (ESC). The patterns of the ESC appeared to extend the wings of the activity butterfly back in time, nearly a decade before the formation of the sunspot pattern, and to much higher solar latitudes. In this short review, we describe their observational patterns of the ESC and discuss possible connections to the solar dynamo as we depart on a multi-national collaboration to investigate the origins of solar magnetism through a blend of archived and contemporary data analysis with the goal of improving solar dynamo understanding and modeling