Category: Regional

This project addresses the research priority on the national-scale evaluation of the water budget
with emphasis on CONUS404. The proposed research involves comparing CONUS404 water-
budget components against in-situ and remotely-sensed observations as well as data from other
reanalysis and gridded datasets. Comparisons will be done at several spatial and temporal units of
Analysis of the U.S. water budget using CONUS404 analysis.

This proposal will implement two different methods to quantify uncertainties and errors,
Triple Collocation and Numerical Moment Matching. First, we will study uncertainties and biases
for each one of the components in the water budget equation independently. Second, we will study
how the component-wise calculated errors are correlated. In addition, this project will perform
storm frequency analysis using CONUS404 data and compare the results against values reported
in NOAA Atlas 14. There is a version of CONUS404 with bias-corrected precipitation and
temperature (using DAYMET and PRISM, Grim et al. 2022). The proposed work will provide a
more robust evaluation of CONUS404 precipitation since it is based on multiple gridded datasets.
In addition, this project will also assess bias and uncertainties of all the other components of the
water budget. Resources from this project will help to train a PhD student and the project results
will be disseminated through the collaboration with the USGS co-PIs, journal articles, and
conference presentations. In addition, the project will develop a web-based app to facilitate the
dissemination of the project findings. Co-PIs are involved with the evaluation team of the Hydro-
Terrestrial Earth System Testbed (HyTEST) project of the USGS Water Mission Area (WMA),
and the Illinois River Basin Integrated Water Availability Assessment (IWAA). These two
projects, as well as others at the USGS, stand to benefit from the proposed research.

The invasive Rusty Crayfish has caused tremendous ecological and
economic damage in glacial lakes in the Upper Midwest. Its range has recently expanded south
to shallow-eutrophic lakes of the Upper Mississippi Basin. The first lake-dwelling population in
Iowa was recently discovered in Storm Lake, Iowa, but little is known about the relative
abundance, distribution of Rusty Crayfish within Storm Lake or surrounding natural lakes, or
how its introduction will affect water quality populations of aquatic flora and fauna. Therefore,
we propose a project to assess the distribution and habitat and biotic associations of Rusty
Crayfish within Storm Lake and other shallow eutrophic lakes within southern portions of the
Upper Mississippi River Basin. This research will inform vulnerability assessments for early
detection and management of the species.

The central research objective will be evaluated via two specific project objectives and associated methods: 1) Quantify changes in CEC complex mixture composition through space and time, and 2) Measure and relate the biological impacts of organisms to changing chemical exposure. During Year 1, bimonthly water samples will be gathered at four previously established sites. Chemical composition of the 15 most abundant compounds / metabolites from preliminary investigation will be quantified via liquid chromatography with tandem mass spectrometry (UIowa). Select subsamples will be quantified at the USGS National Water Quality Lab. Water samples will also be used for laboratory quantitative PCR-based fish gene expression tests (UW-M) and bioluminescent yeast (estrogenicity) nuclear receptor activation bioassays (USGS). During Year 2, instream caged fish experiments will be conducted to evaluate CEC exposure effects during reproduction (UW-M). Concurrent streamflow (USGS) and CEC chemical measurements will occur (UIowa). Water samples will be collected for laboratory batch tests (UIowa) to determine bulk chemical attenuation kinetics. During Year 3, data and statistical analysis will determine relationships between changing chemical composition exposure and quantified biological effects, providing predictive power to CEC attenuation, linking CEC presence with effects. Results interpretation and report writing will occur Year 3.

Read the research findings here.

 

Visit Gregory’s faculty website here.

Visit Gregory’s lab website here.

We propose to develop statistical models to describe the relation between inland flooding associated with North Atlantic tropical cyclones (TCs) and impacts (direct economic losses and insurance claims) in the United States. Inland flooding is of high societal and economic relevance, but regretfully has received very little attention as most U.S. TC loss assessment efforts are focused on coastal flooding. Moreover, it is often the case that the most severe impact from heavy rainfall and fresh water flooding is far removed from the center of circulation of these storms, up to hundreds of kilometers away. The main outcomes of the proposed research are: 1) the identification of the areas that are more at risk from inland flooding from North Atlantic TCs; 2) the characterization of the extent and magnitude of these events; 3) the development of statistical models relating flood magnitude to direct economic losses importantly controlling for the associated exposure and vulnerability aspects over the period 2000-2012; 4) the use of the resulting empirical relationships to perform sensitivity analysis examining the potential impacts of pre-2000 TCs under the current level of exposure and vulnerability. The project will be carried out over a two-year time period. During Year 1, we will assemble spatially and non-spatially hazard, vulnerability and exposure data sets, as well as the associated data regarding claims and losses from the time period of 2000-2012, during which 100 TCs passed at least 500 km from the U.S. coast. This data acquisition and proper assembling is a non-trivial effort given the typical geographic impact of North Atlantic TCs. The statistical modeling of the hazards, vulnerability and exposure will begin towards the end of Year 1. During Year 2, we will complete the statistical modeling of the TC flood hazard and economic losses. We will also measure the degree of flood insurance coverage in place, thus being able to measure how many people exposed to these TCs are not properly protected financially from an insurance perspective and consequently might be requesting federal disaster relief. We will also examine the temporal changes in magnitude and frequency of TC floods. Moreover we will be able to use these developed models to examine what economic impacts TC floods occurring during the 20th century would have had if they had happened in the first decade of the 21st century. Analyses will leverage heavily on USGS discharge data from the hazard side, a unique access to the federally-run National Flood Insurance Program (NFIP) data for flood claims (flood in the United States is mainly insured by this public program), damage and some exposure data, and Hazards-United States (HAZUS) for the remaining relevant exposure and vulnerability data. We will focus on the assessment of the areas that are more severely affected by North Atlantic TC floods east of the Rocky Mountains, and examine the relation between impacts, hazards, exposure and vulnerabilities. Because of the scale of the weather and climate systems at play, we adopt a regional approach from the hazard modeling perspective. One of the problems in dealing with streamflow data at the regional scale is that there is an intrinsic dependence of discharge on drainage area that needs to be accounted for. The approach we will use is to normalize the peaks caused by TCs by the at-site 2-year flood peak. We will describe the relation among impacts, hazards, exposure and vulnerabilities by developing risk assessment statistical models for TC flooding and explore variability in the relationships. The basic idea is that we have a predictand (either claims or losses) and a vector of potential predictors for each of the three main components hazard, exposure and vulnerability. Different modeling approaches will be tested, and different methods for the selection of the relevant predictors will be considered. The procedures and models that we will develop are designed for broad use by USGS National and District Offices for flood and water resource assessment studies. Additional users will include federal, state and local groups for emergency and recovery purposes.

Recent flooding in the U.S. Midwest has produced dramatic scenes of inundated farmlands and cities. Current watershed management plans to help mitigate floods call for installing Best Management Practices (BMPs), such as grassed waterways and retention basins, which reduce runoff. Yet, assessment of these BMPs is complicated by lag times between their implementation and an observed response, which can vary up to decades depending on the quantity (surface-subsurface flow, sediment, nutrients). Moreover, current BMPs may no longer be suitable to mitigate flooding, since the conditions for which they were developed have changed due to intensifying land management for elevated food/ fuel demands, extensive tiling, shifting populations, and climate shifts. Last but not least, most methods for assessing BMP effectiveness are not adequate. Field-based monitoring, for example, can be insightful but is too limited in scale and scope to analyze properly how land management and climate affect water cycle dynamics at the watershed scale. Clearly, there is a need for additional approaches to assess the type, number, and location of BMPs within a watershed for flood mitigation. Computer models may be an alternative form of adaptive management for evaluating watershed responses to different combinations of current and projected BMPs. Models can identify critical locations in terms of flooding contributions, quantify efficiencies for a full range of possible BMPs that reduce runoff under different land uses and climates, and route the flow across scales. Undoubtedly, models can make the entire BMP design/ assessment process more cost effective and more likely to succeed. However, current modeling approaches remain fragmented and isolated, either being performed at the field- or watershed-scale. Field-scale models, alone, cannot capture adequately the collective effects that specific BMPs have on downstream flows at the watershed scale due to routing limitations, while large-scale models, individually, cannot predict the optimal type, number, and location of needed BMPs within a field or sub-watershed due to lumping effects of watershed properties. To address these limitations, our proposed methodology involves a two-way, iterative approach that couples large- and field-scale models with GIS tools to identify the optimal type, number, and location of BMPs for reducing flooding in a representative, mixed agricultural-urban watershed of the Midwest, namely Clear Creek, IA (HUC-10). Our overarching goal is to develop an integrative suite of established models that account for the interplay between land management and climate on water cycle dynamics in rapidly changing Midwestern landscapes. We will first apply a Top-Down Approach using the Soil and Water Assessment Tool (SWAT) to identify critical sub-watersheds in CCW regarding their contributions to downstream flooding. We will then use a Bottom-Up Approach consisting of the geospatial version of the Water Erosion Prediction Project, or GeoWEPP), to distribute spatially and assess specific BMPs within the critical sub-watersheds. As part of the iterative nature of our methodology, we will “feed” the runoff volumes predicted by GeoWEPP back into SWAT to scale-up our field-scale results to the watershed scale and project downstream the BMP effectiveness. However, our modeling results for the different BMPs, even if they are technically sound and optimally designed, will never pay out in conservation benefits unless the stakeholders buy into and adopt them as policy. For this reason, we will use an Evolutionary Algorithm for identifying a spectrum of feasible management plans for accommodating multiple, competing stakeholder interests. The key products from this study include the development of adaptive management strategies that identify optimal BMP combinations for addressing multiple stakeholder concerns and a matrix rating the performance of different BMPs in terms of flow response for the Midwest. Overall, this research will improve water budget estimations in a representative, mixed agricultural-urban watershed of the Midwest under different land management and climates.

Nitroso compounds are a class that includes numerous carcinogens, mutagens, and tetraogens. Until recently it was believed that the occurrence of nitroso compounds in drinking water and wastewater was due to contamination of the source waters. Recent research indicates that N-nitrosodimethylamine (NDMA), a particularly potent carcinogen, can be produced from the chlorination of drinking water and wastewater. Its formation at concentrations that are likely to be of health concern has been observed in distribution systems of some utilities, especially those practicing chloramination of unprotected waters in the Midwest. It is hypothesized that drinking source waters receiving municipal and especially agriculture related wastes, are particularly susceptible to the formation of NDMA as well as other nitroso compound as disinfection by-products. This is likely because these wastes are sources of abundant organic nitrogen precursors required for the formation of nitroso compounds. The potential to form these compounds may therefore limit the use of some waters as a source of drinking water. The extent of this potential is, however, unknown. The primary objective of this study is to measure the nitroso compound formation potential of a variety of drinking source waters, and relate this to source water quality, organic nitrogen precursor sources, land use, and biogeochemical processes that may attenuate their formation. This will be accomplished with the collaboration of the USGS which will assist in the collection of water samples in coordination with a variety of their ongoing studies. Samples will be subjected to standardized procedures to produce nitroso compounds. These will be measured by GC- MS methodology.

Thirty years after enactment of the Clean Water Act, 40% of our nations rivers, lakes, and coastal waters are still considered unfit for fishing, swimming, drinking or aquatic life. At least 10 % of the nations impaired river miles are affected by pollution from livestock operations. Because of its volume, composition, and handling methods, swine fecal material is a serious threat to environmental quality in regional waterways and especially in Iowa. From 1995 to 1998, for example, over 13 million fish were killed in more than two hundred documented manure spills in the Midwest. Local citizens are becoming increasingly intolerant of the environmental cost of confinement livestock production. Although catastrophic pollution events attract the most attention, exposure of aquatic organisms to sub lethal pollutant concentrations can also have significant ecological impact by interfering with normal life processes such as feeding, reproduction, defense and disease resistance. This can result in gradual declines and even extirpations of animal populations and communities. Such chronic effects of manure pollution are poorly known, because of the difficulty of measuring them and placing them in ecological context. We suggest that innate immune response in fish can provide a tool for determining chronic and sub lethal impacts of manure on aquatic animals. The hypothesis is that low levels of swine liquid manure slurry and anaerobic lagoon liquid released to open water cause changes in immunological response in fish and increase fish susceptibility to infection. The first objectives of the project, therefore, are to evaluate this hypothesis through a series of laboratory immunological assays applied to a native test organism, the fathead minnow, and to develop one or more assays for use as a bio-monitoring technique to detect ecological impact of manure pollution in nature. Subsequently, we will characterize a number of Iowa watersheds and stream systems according to their potential susceptibility to hog manure pollution and use this information to design a water quality and fish sampling regime in order to quantitatively measure ecological impact of manure pollution on the streams. We will compare this approach to more traditional chemical and biological pollution measurement techniques and evaluate its utility as a biomonitoring tool for environmental protection agencies. The immune response of fathead minnows to swine manure will be determined by activity of phagocytic cells, through several forms of measurement. Evidence from limited research involving fish suggests that several respiratory burst activity (RBA) assays may be useful for determining phagocytic function, and the procedure also seems to hold promise as a bio-indicator for fish health. Additionally, histological examinations of melanomacrophage centers (MMC) in liver, spleen, kidneys, intestines, skin and gills will be used to measure effects of long term exposure to manure. The project will apply GIS technology and landscape modeling to calculate possible swine pollutant flow path patterns in Iowa watersheds having large hog confinements and in those where liquid manure fertilizer is applied on crop fields. Necessary data will be obtained from the Iowa Rivers Information System (IRIS) and Iowa Gap and Aquatic Gap databases that are maintained by the USGS BRD Iowa Cooperative Fish and Wildlife Research Unit. Using this approach, we will estimate temporal and spatial distribution of manure loads and concentrations that reach receiving waters from agricultural operations. This will provide the basis for a field sampling regime to determine actual conditions of water quality and fish communities at stream sites selected to represent a range of calculated manure pollutant loadings.