Geology topics

Julie E. Kiang

Publications and source records attributed to Julie E. Kiang.

27 records · Page 2Linked to original sources

USGS2015

Accelerating advances in continental domain hydrologic modeling

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Water Resources Research↗

USGS2015

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Iowa, Minnesota↗

USGS2015

A comparison of hydrologic models for ecological flows and water availability

Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.

Ecohydrology↗

USGS2015

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.

Scientific Investigations Report↗

USGS2013

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Hydrology and Earth System Sciences↗

USGS2013

Progress toward establishing a national assessment of water availability and use

The Omnibus Public Land Management Act of 2009 (Public Law 111-11) was passed into law on March 30, 2009. Subtitle F, also known as the SECURE Water Act, calls for the establishment of a "national water availability and use assessment program" within the U.S. Geological Survey (USGS). A major driver for this recommendation was that national water availability and use have not been comprehensively assessed since 1978. This report fulfills a requirement to report to Congress on progress in implementing the national water availability and use assessment program, also referred to as the National Water Census. The SECURE Water Act authorized \$20 million for each of fiscal years (FY) 2009 through 2023 for assessment of national water availability and use. The first appropriation for this effort was \$4 million in FY 2011, followed by an appropriation of \$6 million in FY 2012. The National Water Census synthesizes and reports information at the regional and national scales, with an emphasis on compiling and reporting the information in a way that is useful to states and others responsible for water management and natural-resource issues. The USGS works with Federal and non-Federal agencies, universities, and other organizations to ensure that the information can be aggregated with other types of water-availability and socioeconomic information, such as data on food and energy production. To maximize the utility of the information, the USGS coordinates the design and development of the effort through the Federal Advisory Committee on Water Information. A National Water Census is a complex undertaking, particularly because there are major gaps in the information needed to conduct such an assessment. To maximize progress, the USGS engaged stakeholders in a discussion of priorities and leveraged existing studies and program activities to enhance efforts toward the development of a National Water Census.

Circular↗

USGS2013

A national streamflow network gap analysis

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.

Puerto Rico↗

USGS2012

Calculating weighted estimates of peak streamflow statistics

According to the Federal guidelines for flood-frequency estimation, the uncertainty of peak streamflow statistics, such as the 1-percent annual exceedance probability (AEP) flow at a streamgage, can be reduced by combining the at-site estimate with the regional regression estimate to obtain a weighted estimate of the flow statistic. The procedure assumes the estimates are independent, which is reasonable in most practical situations. The purpose of this publication is to describe and make available a method for calculating a weighted estimate from the uncertainty or variance of the two independent estimates.

Fact Sheet↗

USGS2009

Climate Change and Water Resources Management: A Federal Perspective

Many challenges, including climate change, face the Nation's water managers. The Intergovernmental Panel on Climate Change (IPCC) has provided estimates of how climate may change, but more understanding of the processes driving the changes, the sequences of the changes, and the manifestation of these global changes at different scales could be beneficial. Since the changes will likely affect fundamental drivers of the hydrological cycle, climate change may have a large impact on water resources and water resources managers. The purpose of this interagency report prepared by the U.S. Geological Survey (USGS), U.S. Army Corps of Engineers (USACE), Bureau of Reclamation (Reclamation), and National Oceanic and Atmospheric Administration (NOAA) is to explore strategies to improve water management by tracking, anticipating, and responding to climate change. This report describes the existing and still needed underpinning science crucial to addressing the many impacts of climate change on water resources management.

Circular↗