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At least 19 recordsLinked to original sources
USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗
USGS2009

Field evaluation of a two-dimensinal hydrodynamic model near boulders for habitat calculation

Two-dimensional hydrodynamic models are now widely used in aquatic habitat studies. To test the sensitivity of calculated habitat outcomes to limitations of such a model and of typical field data, bathymetry, depth and velocity data were collected for three discharges in the vicinity of two large boulders in the South Platte River (Colorado) and used in the River2D model. Simulated depth and velocity were compared with observed values at 204 locations and the differences in habitat numbers produced by observed and simulated conditions were calculated. The bulk of the differences between simulated and observed depth and velocity values were found to lie within the likely error of measurement. However, the effect of flow simulation outliers on potential habitat outcomes must be considered when using 2D models for habitat simulation. Furthermore, the shape of the habitat suitability relation can influence the effects of simulation errors. Habitat relations with steep slopes in the velocity ranges found in similar study areas are expected to be sensitive to the magnitude of error found here. Comparison of habitat values derived from simulated and observed depth and velocity revealed a small tendency to under-predict habitat values.

River Research and Applications↗
USGS2025

Hyperspectral imaging of river bathymetry using an ensemble of regression trees

Remote sensing has emerged as an effective tool for characterizing river systems, and machine learning (ML) techniques could make this approach even more powerful. To explore this possibility, we developed an ML-based workflow for hyperspectral imaging of river bathymetry using an ensemble of regression trees (HIRBERT). This approach involves using paired observations of depth and reflectance to select wavelength bands as predictors and then train a depth retrieval model; applying the model to the image yields a spatially continuous bathymetric map. We used data from five rivers with diverse morphologies and optical characteristics to assess whether HIRBERT can (1) provide more accurate depth estimates than a band ratio-based algorithm and (2) extend the range of depths detectable via remote sensing. Relative to single band combinations identified via optimal band ratio analysis (OBRA), regression tree ensembles improved depth retrieval performance, with observed versus predicted (OP) regression R 2 values increasing for all five sites. Similarly, HIRBERT provided more reliable depth estimates than OBRA over the full range of depths present along each river. These results suggest that by incorporating additional spectral information from multiple wavelength bands, ML could enhance bathymetric mapping across a range of river environments. In addition, we show how graphical tools can facilitate interpretation of ML-based depth retrieval models and yield insight regarding relationships between depth and reflectance. The HIRBERT workflow is packaged in free, standalone software developed to support applications in river research and management. Although ML can enhance remote sensing of river bathymetry, the limitations of this approach must also be acknowledged: Field measurements of water depth are required to train a depth retrieval model and the resulting model should only be applied to the image from which the training data were derived. The inherently image-specific nature of this approach implies that developing generalized regression tree ensembles that could be applied at larger scales would require additional research.

California, Idaho, Nebraska, Oregon, Wyoming↗
USGS2021

Improving remotely sensed river bathymetry by image-averaging

Basic data on river bathymetry is critical for numerous applications in river research and management and is increasingly obtained via remote sensing, but the noisy, pixelated appearance of image‐derived depth maps can compromise subsequent analyses. We hypothesized that this noise originates from reflectance from an irregular water surface and introduced a framework for mitigating these effects by Inferring Bathymetry from Averaged River Images (IBARI). This workflow produces time‐averaged images from video frames stabilized to account for platform motion and/or computes a spatial average from an ensemble simulated by randomly shifting images relative to themselves. We used field observations of water depth and helicopter‐based videos from a clear‐flowing river to assess the potential of this approach to improve depth retrieval. Our results indicated that depths inferred from averaged images were more accurate and precise than those inferred from single frames; observed versus predicted regression R 2 increased from 0.80 to 0.88. In addition, IBARI significantly enhanced the texture of image‐derived depth maps, leading to smoother, more coherent representations of channel morphology. Depth retrieval improved with image sequence duration, but the number of images was more important than the length of time encompassed; shorter acquisitions at higher frame rates would economize data collection. We also demonstrated the potential to scale up the IBARI workflow by producing a mosaic of bathymetric maps derived from averaged images acquired at several hovering waypoints distributed along a 2.36 km reach. This approach is well‐suited to data collected from helicopters and small unmanned aircraft systems.

Water Resources Research↗
USGS2011

Effects of dams in river networks on fish assemblages in non-impoundment sections of rivers in Michigan and Wisconsin, USA

Regional assessment of cumulative impacts of dams on riverine fish assemblages provides resource managers essential information for dam operation, potential dam removal, river health assessment and overall ecosystem management. Such an assessment is challenging because characteristics of fish assemblages are not only affected by dams, but also influenced by natural variation and human-induced modification (in addition to dams) in thermal and flow regimes, physicochemical habitats and biological assemblages. This study evaluated the impacts of dams on river fish assemblages in the non-impoundment sections of rivers in the states of Michigan and Wisconsin using multiple fish assemblage indicators and multiple approaches to distinguish the influences of dams from those of other natural and human-induced factors. We found that environmental factors that influence fish assemblages in addition to dams should be incorporated when evaluating regional effects of dams on fish assemblages. Without considering such co-influential factors, the evaluation is inadequate and potentially misleading. The role of dams alone in determining fish assemblages at a regional spatial scale is relatively small (explained less than 20% of variance) compared with the other environmental factors, such as river size, flow and thermal regimes and land uses jointly. However, our results do demonstrate that downstream and upstream dams can substantially modify fish assemblages in the non-impoundment sections of rivers. After excluding river size and land-use influences, our results clearly demonstrate that dams have significant impacts on fish biotic-integrity and habitat-and-social-preference indicators. The influences of the upstream dams, downstream dams, distance to dams, and dam density differ among the fish indicators, which have different implications for maintaining river biotic integrity, protecting biodiversity and managing fisheries.

Wisconsin and Michigan↗
USGS2024

An enhanced and expanded Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

Detailed, accurate information on flow patterns in river channels can improve understanding of habitat conditions, geomorphic processes, and potential hazards to help inform water management. Data describing flow patterns in river channels can be obtained efficiently via image-based techniques that have become more widely used in recent years as the number of platforms for acquiring images has expanded and the number of algorithms for inferring velocities has grown. Image-based techniques have been incorporated into various software packages, including the Toolbox for River Velocimetry using Images from Aircraft (TRiVIA). TRiVIA is a freely available, standalone computer program that provides a comprehensive workflow for performing particle image velocimetry (PIV)-based analyses within a graphical interface. This paper summarizes major enhancements incorporated into the latest release of TRiVIA, version 2.1. For example, a new Tool for Input Parameter Selection (TIPS) provides guidance for specifying key inputs to the PIV algorithm by allowing users to explore relationships between flow velocity, pixel size, output vector spacing, and frame interval. Improved visualization capabilities include the ability to create streamlines and display PIV output on an interactive web map. The program now provides greater flexibility for importing field data in various formats and selecting which observations to use for accuracy assessment. The most substantial additions to TRiVIA 2.1 are the ability to integrate bathymetric information with image-derived velocity estimates to calculate river discharge and to use images acquired from moving aircraft to efficiently map long segments of large rivers to support habitat assessment, contaminant transport studies, and a range of other applications.

River Research and Applications↗
USGS2006

Ecological consequences of hydropower development in Central America: Impacts of small dams and water diversion on neotropical stream fish assemblages

Small dams for hydropower have caused widespread alteration of Central American rivers, yet much of recent development has gone undocumented by scientists and conservationists. We examined the ecological effects of a small hydropower plant (Dona Julia Hydroelectric Center) on two low-order streams (the Puerto Viejo River and Quebradon stream) draining a mountainous area of Costa Rica. Operation of the Dona Julia plant has dewatered these streams, reducing discharge to ~ 10% of average annual flow. This study compared fish assemblage composition and aquatic habitat upstream and downstream of diversion dams on two streams and along a ~ 4 km dewatered reach of the Puerto Viejo River in an attempt to evaluate current instream flow recommendations for regulated Costa Rican streams. Our results indicated that fish assemblages directly upstream and downstream of the dam on the third order Puerto Viejo River were dissimilar, suggesting that the small dam (< 15 in high) hindered movement of fishes. Along the ~ 4 km dewatered reach of the Puerto Viejo River, species count increased with downstream distance from the dam. However, estimated species richness and overall fish abundance were not significantly correlated with downstream distance from the dam. Our results suggested that effects of stream dewatering may be most pronounced for a subset of species with more complex reproductive requirements, classified as equilibrium-type species based on their life-history. In the absence of changes to current operations, we expect that fish assemblages in the Puerto Viejo River will be increasingly dominated by opportunistic-type, colonizing fish species. Operations of many other small hydropower plants in Costa Rica and other parts of Central America mirror those of Doha Julia; the methods and results of this study may be applicable to some of those projects.

River Research and Applications↗
USGS2012

Predicting ecological flow regime at ungaged sites: A comparison of methods

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Kentucky, Tennessee↗
USGS2025

Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS

Hydrologic connectivity is a crucial determinant of aquatic ecosystem services, governing the exchange of nutrients, sediments, chemicals, and biota. Various indices and metrics exist for quantifying hydrologic connectivity across diverse environments and scales. However, existing methodologies often fail to adequately capture lateral connectivity between floodplain lakes and streams across vast, low-relief, multi-lake floodplain systems. This study introduces a novel approach for quantifying lateral hydrologic connectivity specifically tailored for floodplain lakes connecting to streams within the expansive floodplain of the Lower Mississippi River. This approach centers on the spatial and temporal intersection of lakes and streams, leveraging remote sensing and GIS data to estimate nine distinct metrics of hydrologic connectivity. To assess the reliability of the method, the study estimated connectivity metrics for 92 randomly selected floodplain lakes, comprising 53 lakes connected to large streams (Strahler order >7), 13 lakes connected to medium (order 4-6) streams, and 26 lakes connected to small (order 1-3) streams. As expected, there was significant variability in hydrologic connectivity across different stream size classes. The outlined approach contributes valuable insights into the hydrologic connectivity of floodplain lakes and offers a generalizable framework applicable to other floodplains. Its versatility makes it a practical tool for understanding connectivity requirements for biota and facilitating applications in conservation and water resources management. Thus, this work represents a meaningful step toward advancing our understanding of lateral hydrologic connectivity dynamics in complex aquatic ecosystems.

Arkansas, Illinois, Kentucky, Louisiana, Mississip↗
USGS2026

Software to support remote sensing of river discharge based on critical flow theory

Water resource management requires accurate observations of streamflow but standard field methods for measuring river discharge ( Q ) are costly and can be hazardous for equipment and personnel. Remote sensing has become a viable alternative, but many image-based techniques require field data for calibration and depth and velocity can seldom be mapped with a single sensor. A new approach based on critical flow theory, in contrast, allows both of these attributes to be inferred from readily available image data. This technique only pertains to sites with standing waves, called undular hydraulic jumps (UHJs), but a recent investigation demonstrated its potential to provide accurate discharge estimates. This paper introduces software designed to facilitate Inferring Q from UHJs Identified in River Images (InQUIRI). The package includes modules for retrieving data from image servers, making the measurements of wavelength and width required to calculate discharge, inferring a representative wavelength from a profile digitized along a wave train, combining multiple estimates to obtain an ensemble median discharge, and assessing accuracy via comparison to gage records from the U.S. Geological Survey. By making these steps easier to implement, InQUIRI enables users to apply the workflow to a variety of UHJ-containing images. Accumulating more case studies, some successful and others less so, would help constrain the range of applicability of the critical flow approach and foster development of refined guidelines for selecting and measuring waves. The software described herein could play an important role in promoting informed use of this new technique for non-contact streamflow measurement.

Arizona, Colorado, New Mexico, Utah↗
USGS2014

Use of dynamic occupancy models to assess the response of Darters (Teleostei: Percidae) to varying hydrothermal conditions in a southeastern United States tailwater

During the past 100 years, most large rivers in North America have been altered for flood control, hydropower, navigation or water supply development. Although these activities clearly provide important human services, their associated environmental disturbances can profoundly affect stream-dwelling organisms. We used dynamic multi-species occupancy models combined with a trait-based approach to estimate the influence of site-level and species-level characteristics on patch dynamic rates for 15 darter species native to the Elk River, a large, flow-regulated Tennessee River tributary in Tennessee and Alabama. Dynamic occupancy modelling results indicated that for every 2.5 °C increase in stream temperature, darters were 3.94 times more likely to colonize previously unoccupied stream reaches. Additionally, large-bodied darter species were 3.72 times more likely to colonize stream reaches compared with small-bodied species, but crevice-spawning darter species were 5.24 times less likely to colonize previously unoccupied stream reaches. In contrast, darters were 2.21 times less likely to become locally extinct for every 2.5 °C increase in stream temperature, but high stream discharge conditions elevated the risk of local extinction. Lastly, the presence of populations in neighbouring upstream study reaches contributed to a lower risk of extinction, whereas the presence of populations in neighbouring downstream study reaches contributed to higher rates of colonization. Our study demonstrates the application of a trait-based approach combined with a metapopulation framework to assess the patch dynamics of darters in a regulated river. Results from our study will provide a baseline for evaluating the ecological consequences of alternative dam operations.

River Research and Applications↗
USGS2013

Estimating thermal regimes of bull trout and assessing the potential effects of climate warming on critical habitats

Understanding the vulnerability of aquatic species and habitats under climate change is critical for conservation and management of freshwater systems. Climate warming is predicted to increase water temperatures in freshwater ecosystems worldwide, yet few studies have developed spatially explicit modelling tools for understanding the potential impacts. We parameterized a nonspatial model, a spatial flow-routed model, and a spatial hierarchical model to predict August stream temperatures (22-m resolution) throughout the Flathead River Basin, USA and Canada. Model comparisons showed that the spatial models performed significantly better than the nonspatial model, explaining the spatial autocorrelation found between sites. The spatial hierarchical model explained 82% of the variation in summer mean (August) stream temperatures and was used to estimate thermal regimes for threatened bull trout (Salvelinus confluentus) habitats, one of the most thermally sensitive coldwater species in western North America. The model estimated summer thermal regimes of spawning and rearing habitats at <13 C&deg; and foraging, migrating, and overwintering habitats at <14 C&deg;. To illustrate the useful application of such a model, we simulated climate warming scenarios to quantify potential loss of critical habitats under forecasted climatic conditions. As air and water temperatures continue to increase, our model simulations show that lower portions of the Flathead River Basin drainage (foraging, migrating, and overwintering habitat) may become thermally unsuitable and headwater streams (spawning and rearing) may become isolated because of increasing thermal fragmentation during summer. Model results can be used to focus conservation and management efforts on populations of concern, by identifying critical habitats and assessing thermal changes at a local scale.

River Research and Applications↗
USGS2016

Informing watershed connectivity barrier prioritization decisions: A synthesis

Water resources and transportation infrastructure such as dams and culverts provide countless socio-economic benefits; however, this infrastructure can also disconnect the movement of organisms, sediment, and water through river ecosystems. Trade-offs associated with these competing costs and benefits occur globally, with applications in barrier addition (e.g. dam and road construction), reengineering (e.g. culvert repair), and removal (e.g. dam removal and aging infrastructure). Barrier prioritization provides a unique opportunity to: (i) restore and reconnect potentially large habitat patches quickly and effectively and (ii) avoid impacts prior to occurrence in line with the mitigation hierarchy (i.e. avoid then minimize then mitigate). This paper synthesizes 46 watershed-scale barrier planning studies and presents a procedure to guide barrier prioritization associated with connectivity for aquatic organisms. We focus on practical issues informing prioritization studies such as available data sets, methods, techniques, and tools. We conclude with a discussion of emerging trends and issues in barrier prioritization and key opportunities for enhancing the body of knowledge.

River Research and Applications↗
USGS2006

Applicability of the flood-pulse concept in a temperate floodplain river ecosystem: Thermal and temporal components

Annual growth increments were calculated for blue catfish (Ictalurus furcatus) and flathead catfish (Pylodictis olivaris) from the lower Mississippi River (LMR) to assess hypothesized relationships between fish growth and floodplain inundation as predicted by the Flood-Pulse Concept. Variation in catfish growth increment was high for all age classes of both species, and growth increments were not consistently related to various measures of floodplain inundation. However, relationships became stronger, and usually direct, when water temperature was integrated with area and duration of floodplain inundation. Relationships were significant for four of six age classes for blue catfish, a species known to utilize floodplain habitats. Though similar in direction, relationships were weaker for flathead catfish, which is considered a more riverine species. Our results indicate the Flood-Pulse Concept applies more strongly to temperate floodplain-river ecosystems when thermal aspects of flood pulses are considered. We recommend that future management of the LMR should consider ways to 'recouple' the annual flood and thermal cycles. An adaptive management approach will allow further determination of important processes affecting fisheries production in the LMR. Copyright ?? John Wiley & Sons, Ltd.

River Research and Applications↗
USGS2010

Novel plant communities limit the effects of a managed flood to restore riparian forests along a large regulated river

Dam releases used to create downstream flows that mimic historic floods in timing, peak magnitude and recession rate are touted as key tools for restoring riparian vegetation on large regulated rivers. We analysed a flood on the 5th‐order Green River below Flaming Gorge Dam, Colorado, in a broad alluvial valley where Fremont cottonwood riparian forests have senesced and little recruitment has occurred since dam completion in 1962. The stable post dam flow regime triggered the development of novel riparian communities with dense herbaceous plant cover. We monitored cottonwood recruitment on landforms inundated by a managed flood equal in magnitude and timing to the average pre‐dam flood. To understand the potential for using managed floods as a riparian restoration tool, we implemented a controlled and replicated experiment to test the effects of artificially modified ground layer vegetation on cottonwood seedling establishment. Treatments to remove herbaceous vegetation and create bare ground included herbicide application (H), ploughing (P), and herbicide plus ploughing (H + P). Treatment improved seedling establishment. Initial seedling densities on treated areas were as much as 1200% higher than on neighbouring control (C) areas, but varied over three orders of magnitude among the five locations where manipulations were replicated. Only two replicates showed the expected seedling density rank of (H + P) > P > H> C. Few seedlings established in control plots and none survived 1 year. Seedling density was strongly affected by seed rain density. Herbivory affected growth and survivorship of recruits, and few survived nine growing seasons. Our results suggest that the novel plant communities are ecologically and geomorphically resistant to change. Managed flooding alone, using flows equal to the pre‐dam mean annual peak flood, is an ineffective riparian restoration tool where such ecosystem states are present and floods cannot create new habitat for seedling establishment. This problem significantly limits long‐term river and riparian management options.

Colorado↗
USGS2005

Application of wavelet analysis for monitoring the hydrologic effects of dam operation: Glen canyon dam and the Colorado River at lees ferry, Arizona

Wavelet analysis is a powerful tool with which to analyse the hydrologic effects of dam construction and operation on river systems. Using continuous records of instantaneous discharge from the Lees Ferry gauging station and records of daily mean discharge from upstream tributaries, we conducted wavelet analyses of the hydrologic structure of the Colorado River in Grand Canyon. The wavelet power spectrum (WPS) of daily mean discharge provided a highly compressed and integrative picture of the post-dam elimination of pronounced annual and sub-annual flow features. The WPS of the continuous record showed the influence of diurnal and weekly power generation cycles, shifts in discharge management, and the 1996 experimental flood in the post-dam period. Normalization of the WPS by local wavelet spectra revealed the fine structure of modulation in discharge scale and amplitude and provides an extremely efficient tool with which to assess the relationships among hydrologic cycles and ecological and geomorphic systems. We extended our analysis to sections of the Snake River and showed how wavelet analysis can be used as a data mining technique. The wavelet approach is an especially promising tool with which to assess dam operation in less well-studied regions and to evaluate management attempts to reconstruct desired flow characteristics. Copyright ?? 2005 John Wiley & Sons, Ltd.

River Research and Applications↗
USGS2018

Spectrally based bathymetric mapping of a dynamic, sand‐bedded channel: Niobrara River, Nebraska, USA

Methods for spectrally based mapping of river bathymetry have been developed and tested in clear‐flowing, gravel‐bed channels, with limited application to turbid, sand‐bed rivers. This study used hyperspectral images and field surveys from the dynamic, sandy Niobrara River to evaluate three depth retrieval methods. The first regression‐based approach, optimal band ratio analysis (OBRA), paired in situ depth measurements with image pixel values to estimate depth. The second approach used ground‐based field spectra to calibrate an OBRA relationship. The third technique, image‐to‐depth quantile transformation (IDQT), estimated depth by linking the cumulative distribution function (CDF) of depth to the CDF of an image‐derived variable. OBRA yielded the lowest depth retrieval mean error (0.005 m) and highest observed versus predicted R 2 (0.817). Although misalignment between field and image data did not compromise the performance of OBRA in this study, poor georeferencing could limit regression‐based approaches such as OBRA in dynamic, sand‐bedded rivers. Field spectroscopy‐based depth maps exhibited a mean error with a slight shallow bias (0.068 m) but provided reliable estimates for most of the study reach. IDQT had a strong deep bias but provided informative relative depth maps. Overprediction of depth by IDQT highlights the need for an unbiased sampling strategy to define the depth CDF. Although each of the techniques we tested demonstrated potential to provide accurate depth estimates in sand‐bed rivers, each method also was subject to certain constraints and limitations.

Nebraska↗
USGS2020

Quantifying and mapping inundation regimes within a large river‐floodplain ecosystem for ecological and management applications

Spatial information on the distribution of ecosystem patterns and processes can be a critical component of designing and implementing effective management programs in river‐floodplain ecosystems. For example, translating how flood pulses detected within a stream gauge record are spatially manifested across a river‐valley bottom can be used to evaluate whether the current distribution of physical conditions has the potential to support priority habitats or if intervention is needed to meet desired goals. The size and complexity of large river‐floodplain systems can make mapping inundation dynamics a challenging task. We used a geospatial model to simulate 40 years (1972–2011) of daily surface‐water inundation depths for 11,331 km 2 of the Upper Mississippi River System floodplain. We identified discrete inundation events at each 4‐m × 4‐m pixel in the model as sequential days of submergence. We then quantified and mapped four aspects of inundation regime – event frequency, duration, magnitude, and timing – for each pixel. The spatial distribution of inundation regime attributes varied within and among multiple levels of river organization, including navigation pools and geomorphic reaches, but only event timing exhibited a strong down‐river trend. Non‐linear relations among inundation attributes and their geospatial distributions likely reflect complex interactions among topographic, hydrologic, and anthropogenic constraints on flooding dynamics. Together, our results reveal spatial gradients in inundation dynamics not captured by hydrologic data alone. Characterizing such diversity in inundation dynamics is important for testing hypotheses about ecological processes, developing models of ecosystem functions, and informing management actions.

Illinois, Indiana, Iowa, Minnesota, Missouri, Wisc↗