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USGS2022

A practical guide to understanding and validating complex models using data simulations

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4 ) and machine learning methods. These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal Nature Ecology & Evolution , and we found that the majority of published papers did not report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods. Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal Methods Ecology & Evolution . We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement. Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.

Methods in Ecology and Evolution↗
USGS2025

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California↗
USGS2017

Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands

The Little Plover River is a groundwater-fed stream in the sand plains region of central Wisconsin. In this region, sandy sediment deposited during or soon after the last glaciation forms an important unconfined sand and gravel aquifer. This aquifer supplies water for numerous high-capacity irrigation, municipal, and industrial wells that support a thriving agricultural industry. In recent years the addition of many new wells, combined with observed diminished flows in the Little Plover and other nearby rivers, has raised concerns about the impacts of the wells on groundwater levels and on water levels and flows in nearby lakes, streams, and wetlands. Diverse stakeholder groups, including well operators, Growers, environmentalists, local land owners, and regulatory and government officials have sought a better understanding of the local groundwater-surface water system and have a shared desire to balance the water needs of the he liagricultural, industrial, and urban users with the maintenance and protection of groundwater-dependent natural resources. To help address these issues, the Wisconsin Department of Natural Resources requested that the Wisconsin Geological and Natural History Survey and U.S. Geological Survey cooperatively develop a groundwater flow model that could be used to demonstrate the relationships among groundwater, surface water, and well withdrawals and also be a tool for testing and evaluating alternative water management strategies for the central sands region. Because of an abundance of previous studies, data availability, local interest, and existing regulatory constraints the model focuses on the Little Plover River watershed, but the modeling methodology developed during this study can apply to much of the larger central sands of Wisconsin. The Little Plover River groundwater flow model simulates three-dimensional groundwater movement in and around the Little Plover River basin under steady-state and transient conditions. This model explicitly includes all high-capacity wells in the model domain and simulates seasonal variations in recharge and well pumping. The model represents the Little Plover River, and other significant streams and drainage ditches in the model domain, as fully connected to the groundwater system, computes stream base flow resulting from groundwater discharge, and routes the flow along the stream channel. A separate soil-water-balance (SWB) model was used to develop groundwater recharge arrays as input for the groundwater flow model. The SWB model uses topography, soils, land use, and climatic data to estimate recharge as deep drainage from the soil zone. The SWB model explicitly includes recharge originating as irrigation water, and computes irrigation using techniques similar to those used by local irrigation operators. The groundwater flow model uses the U.S. Geological Survey’s MODFLOW modeling code which is freely available, widely accepted, and commonly used by the groundwater community. The groundwater flow model and the SWB model use identical high-resolution numerical grids having model cells 100 feet on a side, with physical properties assigned to each grid cell. This grid allows accurate geographic placement of wells, streams, and other model features. The 3-dimensional grid has three layers; layers 1 and 2 represent the sand and gravel aquifer and layer 3 represents the underlying sandstone. The distribution of material properties in the model (hydraulic conductivity, aquifer thickness, etc.) comes from previous published geologic studies of the region, updated by calibration to recent streamflow and groundwater level data. The SWB model operates on a daily time step. The groundwater flow model was calibrated to monthly stress periods with time steps ranging from 1 to 16 days. More detailed time discretization is possible. The groundwater model was calibrated to water-level and streamflow data collected during 2013 and 2014 by adjusting model parameters (primarily hydraulic conductivity, storage, and recharge) until the model produced a conditionally optimal fit between field observations and model output, subject to consistency with previously published geologic studies. Calibration was performed under both steady and transient conditions, and used a sophisticated parameter-estimation procedure (PEST) for the calibration process and to identify important model parameters. For the Little Plover River, the two most important parameters are the global recharge multiplier and the hydraulic conductivity of the stream bed. The calibrated model produces water-level and mass-balance results that are consistent with field observations and previous studies of the area. The completed model is a powerful tool for testing and demonstrating alternative water-management scenarios. Example model applications described in this report include simulating how the cumulative impacts of pumping and land-use change have affected average baseflow in the Little Plover River. Depletion-potential mapping represents a method for predicting which wells and well locations have the greatest impact on nearby surface-water resources. The completed model is publicly available, along with a companion user’s guide to assist with its operation, at http://wgnhs.org/littleplover- river-groundwater-model.

Wisconsin↗
USGS1985

Maximum likelihood methods for investigating reporting rates of rings on hunter-shot birds

It is well known that hunters do not report 100% of the rings that they find on shot birds. Reward studies can be used to estimate what this reporting rate is, by comparison of recoveries of rings offering a monetary reward, to ordinary rings. A reward study of American Black Ducks (Anas rubripes) is used to illustrate the design, and to motivate the development of statistical models for estimation and for testing hypotheses of temporal and geographic variation in reporting rates. The method involves indexing the data (recoveries) and parameters (reporting, harvest, and solicitation rates) by geographic and temporal strata. Estimates are obtained under unconstrained (e.g., allowing temporal variability in reporting rates) and constrained (e.g., constant reporting rates) models, and hypotheses are tested by likelihood ratio. A FORTRAN program, available from the author, is used to perform the computations.

Book chapter↗
USGS2015

An updated conceptual model of Delta Smelt biology: Our evolving understanding of an estuarine fish

The main purpose of this report is to provide an up-to-date assessment and conceptual model of factors affecting Delta Smelt (Hypomesus transpacificus) throughout its primarily annual life cycle and to demonstrate how this conceptual model can be used for scientific and management purposes. The Delta Smelt is a small estuarine fish that only occurs in the San Francisco Estuary. Once abundant, it is now rare and has been protected under the federal and California Endangered Species Acts since 1993. The Delta Smelt listing was related to a step decline in the early 1980s; however, population abundance decreased even further with the onset of the “pelagic organism decline” (POD) around 2002. A substantial, albeit short-lived, increase in abundance of all life stages in 2011 showed that the Delta Smelt population can still rebound when conditions are favorable for spawning, growth, and survival. In this report, we update previous conceptual models for Delta Smelt to reflect new data and information since the release of the last synthesis report about the POD by the Interagency Ecological Program for the San Francisco Estuary (IEP) in 2010. Specific objectives include: 1. Provide decision makers with a practical tool for evaluating difficult trade-offs associated with management and policy decisions. 2. Provide scientists with a framework from which they can formulate and evaluate hypotheses using qualitative or quantitative models. 3. Provide the general public with a new way of learning about Delta Smelt and their habitat. Our updated conceptual model describes the habitat conditions and ecosystem drivers affecting each Delta Smelt life stage, across seasons and how the seasonal effects contribute to the annual success of the species. The conceptual model consists of two nested and linked levels of increasing specificity. The general life cycle conceptual model for four Delta Smelt life stages (adults, eggs and larvae, juveniles, and subadults) includes stationary ecosystem components and dynamic environmental drivers, habitat attributes, and Delta Smelt responses. The more detailed life stage transition conceptual models for each of the four Delta Smelt life stages describe relationships between environmental drivers, key habitat attributes, and the responses of Delta Smelt to habitat attributes as they transition from one life stage to the next. Our analyses and conceptual model show that good larval recruitment is essential for setting the stage for a strong year class; however, increased growth and survival through subsequent life stages are also needed to achieve and sustain higher population abundance. We used our conceptual model to generate 16 hypotheses about the factors that may have contributed to the 2011 increase in Delta Smelt relative abundance. We then evaluated these hypotheses by comparing habitat conditions and Delta Smelt responses in the wet year 2011 to those in the prior wet year 2006 and in the drier years 2005 and 2010. Larval recruitment was similarly high in both wet years and lower in the drier antecedent years, but juvenile and adult abundance increased only in 2011. In 2005 and 2006, the population was limited by very poor survival from the larval to the juvenile life stage. We found that in 2011, Delta Smelt may have benefitted from a combination of favorable habitat conditions throughout the year, including: 1. Adults and larvae benefitted from prolonged cool spring water temperatures, high 2011 winter and spring outflows which reduced entrainment risk and possibly improved other habitat conditions, and possibly enhanced food availability in late spring. 2. Juveniles benefitted from cool water temperatures in late spring and early summer as well as from improved food availability and low levels of harmful Microcystis. 3. Subadults also benefitted from improved food availability and from favorable habitat conditions in the large, low salinity zone (salinity 1-6) located more toward Suisun Bay,

California↗
USGS2013

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.) . Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Great Lakes↗
USGS1977

United States Geological Survey uranium and thorium resource assessment and exploration research program, fiscal year 1977

The U.S. Geological Survey Uranium and Thorium Resource Assessment and Exploration Research Program began in July 1974 (FY 1975). The first year was spent chiefly in redirecting an on-going effort and in staffing for the nearly fourfold increase in funding. A summary of the Fiscal Year 1976 program, including objectives, program model, and project descriptions, is published as Open-File Report 75-575. The overall objectives and program model remain essentially the same as in FY 1976. It should be noted that the beginning of the fiscal year was changed from July 1 to October 1 during the 1976 calendar year and that a transitional quarter was used to make this change. Some program changes were made during the transitional quarter, but these details are not recorded in the present summary.

Open-File Report↗
USGS2013

Mapping monkeypox transmission risk through time and space in the Congo Basin

Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.

PLoS ONE↗
USGS1995

Use of solicited bands and separation of hunting and natural mortality: a comment

We previously presented (Conroy 1985, Conroy et al. 1989) models for analysis of band recovery data stratified into those voluntarily reported and those obtained by solicitation, similar to models described by Pollock et al. (1994). We discuss differences between the 2 modeling approaches and suggest designs and analyses involving overlapping samples of standard and reward bands to enable adjustment for temporal and geographic variation in reporting and solicitation rates,

Journal of Wildlife Management↗
USGS2006

Magnetotelluric Data, Rainier Mesa/Shoshone Mountain, Nevada Test Site, Nevada

Introduction: The United States Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) at their Nevada Site Office (NSO) are addressing ground-water contamination resulting from historical underground nuclear testing through the Environmental Management (EM) program and, in particular, the Underground Test Area (UGTA) project. During 2005, the U.S. Geological Survey (USGS), in cooperation with the DOE and NNSA-NSO, collected and processed data from twenty-six magnetotelluric (MT) and audio-magnetotelluric (AMT) sites at the Nevada Test Site. The 2005 data stations were located on and near Rainier Mesa and Shoshone Mountain to assist in characterizing the pre-Tertiary geology in those areas. These new stations extend the area of the hydrogeologic study previously conducted in Yucca Flat. The MT data presented in this report will help refine what is known about the character, thickness, and lateral extent of pre Tertiary confining units. Subsequent interpretation will include a three dimensional (3 D) character analysis and a two-dimensional (2 D) resistivity model. The purpose of this report is to release the MT sounding data. No interpretation of the data is included here.

Open-File Report↗
USGS2017

Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report

Public Summary We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises. In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention. In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.

Montana, Nebraska, North Dakota, South Dakota, Wyo↗
USGS2017

Enhanced and updated spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin

Approximately 6.4 million tons of dissolved solids are discharged from the Upper Colorado River Basin (UCRB) to the Lower Colorado River Basin each year. This results in substantial economic damages, and tens of millions of dollars are spent annually on salinity control projects designed to reduce salinity loads in surface waters of the UCRB. Dissolved solids in surface water and groundwater have been studied extensively over the past century, and these studies have contributed to a conceptual understanding of sources and transport of dissolved solids. This conceptual understanding was incorporated into a Spatially Referenced Regressions on Watershed Attributes (SPARROW) model to examine sources and transport of dissolved solids in the UCRB. The results of this model were published in 2009. The present report documents the methods and data used to develop an updated dissolved-solids SPARROW model for the UCRB, and incorporates data defining current basin attributes not available in the previous model, including delineation of irrigated lands by irrigation type (sprinkler or flood irrigation), and calibration data from additional monitoring sites. Dissolved-solids loads estimated for 312 monitoring sites were used to calibrate the SPARROW model, which predicted loads for each of 10,789 stream reaches in the UCRB. The calibrated model provided a good fit to the calibration data as evidenced by R 2 and yield R 2 values of 0.96 and 0.73, respectively, and a root-mean-square error of 0.47. The model included seven geologic sources that have estimated dissolved-solids yields ranging from approximately 1 to 45 tons per square mile (tons/mi 2 ). Yields generated from irrigated agricultural lands are substantially greater than those from geologic sources, with sprinkler irrigated lands generating an average of approximately 150 tons/mi 2 and flood irrigated lands generating between 770 and 2,300 tons/mi 2 depending on underlying lithology. The coefficients estimated for six landscape transport characteristics that influence the delivery of dissolved solids from sources to streams, are consistent with the process understanding of dissolved-solids loading to streams in the UCRB. Dissolved-solids loads and the proportion of those loads among sources in the entire UCRB as well as in major tributaries in the basin are reported, as are loads generated from irrigated lands, rangelands, Bureau of Land Management (BLM) lands, and grazing allotments on BLM lands. Model-predicted loads also are compared with load estimates from 1957 and 1991 at selected locations in three divisions of the UCRB. At the basin scale, the model estimates that 32 percent of the dissolved-solids loads are from irrigated agricultural land sources that compose less than 2 percent of the land area in the UCRB. This estimate is less than previously reported estimates of 40 to 45 percent of basin-scale dissolved-solids loads from irrigated agricultural land sources. This discrepancy could be a result of the implementation of salinity control projects in the basin. Notably, results indicate that the conversion of flood irrigated agricultural lands to sprinkler irrigated agricultural lands is a likely process contributing to the temporal decrease in dissolved-solids loads from irrigated lands.

Colorado River Basin↗
USGS1995

Regional rainfall-runoff relations for simulation of streamflow for watersheds in Lake County, Illinois

Rainfall and streamflow data collected in Lake County, Ill., from March 1990 through September 1993 were used to (1) calibrate a rainfall-runoff model for an area encompassing three watersheds (individual areas of 17.2, 35.7, and 37.0 mi 2 (square miles) and (2) verify the regional model parameter set obtained from the calibration by applying the parameter set to rainfall-runoff models for an additional small (6.3 mi 2 ) watershed and a large (59.6 mi 2 ) watershed. In addition, rainfall and streamflow data collected from April 1991 through September 1993 were used to calibrate the rainfall-runoff model for three single land-use watersheds (38.2-305 acres), called hydrologic response units (HRU's). Significant differences were found between the best parameters used in the HRU models and in the larger watershed models. The main channels in the HRU's are intermittent streams; thus, the parameters in the HRU models were selected such that a fluctuating water table could be simulated; runoff from the larger watersheds is not as sensitive to the effects of a fluctuating water table. Classification of land cover into two pervious subareas (forest and grass) and one impervious subarea (including parking lots, streets, and rooftops, among others) was sufficient to simulate the rainfall-runoff relations for all watersheds accurately. The model parameters presented in this report, which were refined through regional calibration and verified for watersheds not considered in the calibration, allow simulation of runoff in watersheds in Lake County, Ill., with approximately 93-percent accuracy in the total water balance, an average absolute error in the annual- flow estimates of 10.9 percent (and an error rarely exceeding 25 percent for annual flow), and monthly water balances with correlation coefficients of 93 percent and coefficients of model-fit efficiency of 86 percent. The models closely reproduced the partial-duration series of runoff and storm-runoff frequencies for the modeled watersheds.

Illinois↗
USGS2000

Effects of hypothetical management scenarios on simulated water temperatures in the Tualatin River, Oregon

In 1994, the U.S. Geological Survey (USGS) and the Unified Sewerage Agency of Washington County, Oregon (USA) began a cooperative study to better understand water-temperature variations in the Tualatin River and to assess mitigative water-management solutions. Continuous water-temperature data were collected at locations along the main stem of the river and along the major tributaries during the lowflow periods of 1994 and 1995. The 1994 data were used to develop and calibrate flow and water-temperature models characterizing conditions in the main stem. The models were used to simulate 10 hypotheti3 cal water-management scenarios, which would enable water managers to understand the effects of various human activities on water temperatures. Modeling results from the study are presented in Risley (1997); the data collected are presented in Risley and Doyle (1997). This report presents the water-temperature model simulation results of 16 additional hypothetical water-management scenarios using the 1994 and 1995 data. The additional modeling was funded by the USGS and the USA under a cooperative agreement. For a comprehensive description of the water-temperature models and their underlying assumptions, refer to Risley (1997).

Oregon↗
USGS2018

Estimating the effects of wetland conservation practices in croplands: Approaches for modeling in CEAP–Cropland Assessment

Quantifying the current and potential benefits of conservation practices can be a valuable tool for encouraging greater practice adoption on agricultural lands. A goal of the CEAP-Cropland Assessment is to estimate the environmental effects of conservation practices that reduce losses (exports) of soil, nutrients, and pesticides from farmlands to streams and rivers. The assessment approach combines empirical data on reported cropland practices with simulation modeling that compares field-level exports for scenarios “with practices” and “without practices.” Conserved, restored, and created wetlands collectively represent conservation practices that can influence sediment and nutrient exports from croplands. However, modeling the role of wetlands within croplands presents some challenges, including the potential for negative impacts of sediment and nutrient inputs on wetland functions. This Science Note outlines some preliminary solutions for incorporating wetlands and wetland practices into the CEAP-Cropland modeling framework. First, modeling the effects of wetland practices requires identifying wetland hydrogeomorphic type and accounting for the condition of both the wetland and an adjacent upland zone. Second, modeling is facilitated by classifying wetland-related practices into two functional categories (wetland and upland buffer). Third, simulating practice effects requires alternative field configurations to account for hydrological differences among wetland types. These ideas are illustrated for two contrasting wetland types (riparian and depressional).

CEAP-Wetlands Science Note↗
USGS2003

Fault slip and seismic moment of the 1700 Cascadia earthquake inferred from Japanese tsunami descriptions

The 1700 Cascadia earthquake attained moment magnitude 9 according to new estimates based on effects of its tsunami in Japan, computed coseismic seafloor deformation for hypothetical ruptures in Cascadia, and tsunami modeling in the Pacific Ocean. Reports of damage and flooding show that the 1700 Casscadia tsunami reached 1-5 m heights at seven shoreline sites in Japan. Three sets of estimated heights express uncertainty about location and depth of reported flooding, landward decline in tsunami heights from shorelines, and post-1700 land-level changes. We compare each set with tsunami heights computed from six Cascadia sources. Each source is vertical seafloor displacement calculated with a three-dimensional elastic dislocation model, for three sources the rupture extends the 1100 km length of the subduction zone and differs in width and shallow dip; for the other sources, ruptures of ordinary width extend 360-670 km. To compute tsunami waveforms, we use a linear long-wave approximation with a finite difference method, and we employ modern bathymetry with nearshore grid spacing as small as 0.4 km. The various combinations of Japanese tsunami heights and Cascadia sources give seismic moment of 1-9 ?? 1022 N m, equivalent to moment magnitude 8.7-9.2. This range excludes several unquantified uncertainties. The most likely earthquake, of moment magnitude 9.0, has 19 m of coseismic slip on an offshore, full-slip zone 1100 km long with linearly decreasing slip on a downdip partial-slip zone. The shorter rupture models require up to 40 m offshore slip and predict land-level changes inconsistent with coastal paleoseismological evidence. Copyright 2003 by the American Geophysical Union.

Journal of Geophysical Research B: Solid Earth↗
USGS2007

Report on the final completion of the Unified Lunar Control Network 2005 and Lunar Topographic Model

In order to highlight this project to the extraterrestrial mapping community, we repeat here our earlier abstract [1], with a corrected Figure 2. A report describing the Unified Lunar Control Network 2005 and the files associated with that network is now available as an on-line USGS Open-File Report [2] at the location http://pubs.usgs.gov/of/2006/1367/. A “Readme” file describes the available files, including the report text, the original photogrammetric solution input and output files, derived files such as information on all the control point positions, the expected vertical precision (EVP) of the points and the solution residuals, and a directory containing global DEMs derived from the point positions. While a paper providing further details about the solution is in preparation, we provide some useful additional information about the solution and possible uses for it here.

Conference Paper↗
USGS1984

Hydrogeology of well-field areas near Tampa, Florida, phase 2 — Development and documentation of a quasi-three-dimensional finite-difference model for simulation of steady-state ground-water flow

This report describes a quasi-three-dimensional finite-difference model for simulation of steady-state ground-water flow in the Floridan aquifer over a 932-square-mile area that contains 10 municipal well fields. The over-lying surficial aquifer contains a water table and is coupled to the Floridan aquifer by leakage term that represents flow through a confining layer separating the two aquifers. Under the steady-state condition, all storage terms are set to zero. Use of the head-controlled flux condition allows simulated head and flow changes to occur in the Floridan aquifer at the model boundaries. Procedures used to calibrate the model, test its sensitivity to input-parameter errors, and validate its accuracy for predictive purposes are described. Also included are attachments that describe setting up and running the model. Example model-interrogation runs show anticipated drawdowns under high, average, and low recharge conditions with 10 well fields pumping simultaneously at the maximum annual permitted rates totaling 186.9 million gallons per day.

Florida↗