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Results for “Journal of Flood Risk Management”

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At least 19 recordsLinked to original sources
USGS2021

Assessment and significance of the frequency domain for trends in annual peak streamflow

Risk management of nonstationary floods depends on an understanding of trends over a range of flood frequencies representing small (frequent) to large (infrequent) floods. Quantile regression is applied to the annual peak streamflow distributions at 2683 sites in the contiguous United States to test for trends in the 10th quantile (floods with a 0.9 annual exceedance probability), the 50th quantile (median annual flood), and 90th quantile (floods with a 0.1 annual exceedance probability). Trends are most common (36% of sites) for the median annual flood (50th quantile) and often coherent with trends in both frequent small floods (10th quantile) and infrequent large floods (90th quantile). Changes in the at-site variance of annual peak streamflow, indicated by convergence (decreasing variance) or divergence (increasing variance) of the 10th and 90th quantiles over time, are primarily in response to reservoir operation or urban development rather than climate. An analysis of synthetic series generated from nonstationary distributions demonstrates that quantile regression and standard trend tests used in flood frequency analysis have limited power and high rates of false negatives (>70%) when a test has a significance of p = 0.05. Quantile regression and tests with lower significance complement standard trend testing to inform flood risk management.

Journal of Flood Risk Management↗
USGS2011

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

Journal of Flood Risk Management↗
USGS2025

Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing

California's Central Valley is increasingly vulnerable to winter floods. A comprehensive spatial baseline of flood extents is critical for inundation analyses that can enhance future flood predictions, but cloud cover has prevented the regular observation of surface water extents with optical satellite imagery. In this study, we leveraged the daily resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to create a continuous series of monthly Dynamic Surface Water Extent (DSWEmod) images across the Central Valley from January 2003 to January 2023. We used the timeseries to assess the climatic driving forces of winter (Oct–April) surface water variability at sub-basin and pixel scales. At the sub-basin scale, we evaluated the influences of winter precipitation, occurrence of atmospheric rivers, and antecedent soil moisture on monthly surface water extents and found that the greatest correspondence occurs in mid-winter (Dec–Feb); in contrast, non-precipitation drivers such as water management play a stronger role in autumn and spring. The pixel-level analysis identified the probabilities of precipitation-driven surface water occurrences in the Sacramento basin are highest along rivers, conveyance channels, and floodways, with higher probabilities under wetter antecedent soil moisture conditions. Precipitation-driven surface water occurrences are also common in leveed areas and outside flood boundaries designated by state and federal agencies where exposure of structures to inundation was larger in terms of their value. Finally, areas with more frequent precipitation-driven flooding have poor recharge potential but are commonly within 5 km of areas classified as having good potential. This study demonstrates a novel approach for exploring the utility of MODIS for understanding surface water dynamics in mid-winter, a period characterized by peak precipitation, flood risk, and surface water extent. This information can provide valuable insights for (1) assessing flood risks for infrastructure and populations, (2) identifying areas most suited to strategic water management investments to increase recharge, and (3) analyzing precipitation thresholds that trigger flooding to allow proactive water management strategies to minimize damage and maximize recharge.

California↗
USGS2009

Mapping Hurricane Rita inland storm tide

Flood‐inundation data are most useful for decision makers when presented in the context of maps of affected communities and (or) areas. But because the data are scarce and rarely cover the full extent of the flooding, interpolation and extrapolation of the information are needed. Many geographic information systems provide various interpolation tools, but these tools often ignore the effects of the topographic and hydraulic features that influence flooding. A barrier mapping method was developed to improve maps of storm tide produced by Hurricane Rita. Maps were developed for the maximum storm tide and at 3‐h intervals from midnight (00:00 hours) through noon (12:00 hours) on 24 September 2005. The improved maps depict storm‐tide elevations and the extent of flooding. The extent of storm‐tide inundation from the improved maximum storm‐tide map was compared with the extent of flood inundation from a map prepared by the Federal Emergency Management Agency (FEMA). The boundaries from these two maps generally compared quite well especially along the Calcasieu River. Also a cross‐section profile that parallels the Louisiana coast was developed from the maximum storm‐tide map and included FEMA high‐water marks.

Louisiana↗
USGS2010

Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border

Appropriate land‐use, watershed‐management, and flood‐attenuation plans are critical in the cross‐border urban environment known collectively as Ambos Nogales. This paper summarizes methodologies for predicting the watershed response associated with land‐use change within a spatial and temporal context through the use of a hydrological model in a cross‐border setting. The KINEROS2 model is implemented via the Automated Geospatial Watershed Assessment 2.0 geographic information system interface to evaluate the watershed of Nogales, Arizona, and Nogales, Sonora, Mexico, to assess flood vulnerability by quantifying volumes of runoff and peak flow, based on alternative land‐use scenarios. Cross‐border geospatial data acquisition and input to models are described. Discussions about the KINEROS2 model results identify flood‐prone areas, simulate the impact of land‐use change, and evaluate the impact of potential flood‐control interventions in the Ambos Nogales watershed. Products from this research are being used in a comprehensive plan for sustainable development in Ambos Nogales.

Ambos Nogales watershed↗
USGS2008

Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

Journal of Flood Risk Management↗
USGS2009

Sources of uncertainty in flood inundation maps

Flood inundation maps typically have been used to depict inundated areas for floods having specific exceedance levels. The uncertainty associated with the inundation boundaries is seldom quantified, in part, because all of the sources of uncertainty are not recognized and because data available to quantify uncertainty seldom are available. Sources of uncertainty discussed in this paper include hydrologic data used for hydraulic model development and validation, topographic data, and the hydraulic model. The assumption of steady flow, which typically is made to produce inundation maps, has less of an effect on predicted inundation at lower flows than for higher flows because more time typically is required to inundate areas at high flows than at low flows. Difficulties with establishing reasonable cross sections that do not intersect and that represent water-surface slopes in tributaries contribute additional uncertainties in the hydraulic modelling. As a result, uncertainty in the flood inundation polygons simulated with a one-dimensional model increases with distance from the main channel.

Journal of Flood Risk Management↗
USGS2023

A web-based application for exploring potential changes in design peak flow of U.S. urban areas driven by land cover change

Floods have become increasingly prominent in recent decades, especially in urban areas causing devastating effects on lives and livelihoods worldwide. Efficient tools to assess the drivers of floods, such as increasing urbanization could help to minimize flood hazards. A Google Earth Engine (GEE) application was developed to explore the potential changes (1985-2020) in design peak-flow of urban areas across the conterminous United States driven by land cover change. The results indicate a potential increase in peak-flow in urban areas up to 126.6% in 2020 compared to 1985. Out of the total 3535 study urban areas, about 80% (2840) urban areas increased peak-flow and about 19% (654) decreased peak-flow. A general pattern of increasing peak-flow was observed during 1985-2010 and decreasing pattern during 2010-2020, primarily driven by respective increasing (decreasing) and decreasing (increasing) developed areas (croplands). The GEE application pro-vides crucial information by visualizing both spatial and temporal data that could be useful for decision-makers in developing and improving urban stormwater management plans and policies for efficient resource allocations and reducing flood risks.

Journal of Remote Sensing↗
USGS2018

100-year lower Mississippi floods in a global climate model: Characteristics and future changes

Floods in the Mississippi basin can have large negative societal, natural, and economic impacts. Understanding the drivers of floods, now and in the future, is relevant for risk management and infrastructure-planning purposes. We investigate the drivers of 100-yr-return lower Mississippi River floods using a global coupled climate model with an integrated surface water module. The model provides 3400 years of physically consistent data from a static climate, in contrast to available observational data (relatively short records, incomplete land surface data, transient climate). In the months preceding the model’s 100-yr floods, as indicated by extreme monthly discharge, above-average rain and snowfall lead to moist subsurface conditions and the buildup of snowpack, making the river system prone to these major flooding events. The meltwater from snowpack in the northern Missouri and upper Mississippi catchments primes the river system, sensitizing it to subsequent above-average precipitation in the Ohio and Tennessee catchments. An ensemble of transient forcing experiments is used to investigate the impacts of past and projected anthropogenic climate change on extreme floods. There is no statistically significant projected trend in the occurrence of 100-yr floods in the model ensemble, despite significant increases in extreme precipitation, significant decreases in extreme snowmelt, and significant decreases in less extreme floods. The results emphasize the importance of considering the fully coupled land–atmosphere system for extreme floods. This initial analysis provides avenues for further investigation, including comparison to characteristics of less extreme floods, the sensitivity to model configuration, the role of human water management, and implications for future flood-risk management.

Journal of Hydrometeorology↗
USGS2020

Potential impacts of future urbanization and sea level rise on Florida’s natural resources

As urban development continues to encroach into natural systems, these ecosystems experience increasing degradation to their form and function. Losses in biodiversity and ecosystem function are further compounded by changing climatic conditions. The State of Florida is known for its biodiversity but has experienced declines in species populations and habitats because of urbanization and sea level rise. These declines are particularly challenging in an economy that benefits from a multibillion-dollar income from natural resources tourism. In this study, we assessed the potential future impacts of urbanization and sea level rise on a suite of conservation targets that have been set for the State. We developed six scenarios of all combinations of intermediate and high sea level rise paired with two types of urbanization (sprawling and compact) in both 2040 and 2070 to examine the potential future threats to conservation targets in High Pine and Scrub, Coastal Uplands, and Freshwater Aquatics ecosystems. Our results show projected decreases in extent and area of these priority ecosystems into the future. Florida's current trend in urbanization practices are projected to have a greater impact on conservation targets than if sprawl reduction practices are implemented. Coastal Uplands are projected to experience the greatest loss in area, at up to 47%. Conservation-focused urban planning and climate adaptation strategies can help protect Florida's natural resources with benefits to Florida's tourism economy as well as critical ecosystem functions and services such as coastal flood protection and storm surge risk reduction.

Florida↗
USGS2017

Stochastic programming with a joint chance constraint model for reservoir refill operation considering flood risk

Reservoir refill operation modeling attempts to maximize a set of benefits while minimizing risks. The benefits and risks can be in opposition to each other, such as having enough water for hydropower generation while leaving enough room for flood protection. In addition to multiple objects, the uncertainty of streamflow can make decision making difficult. This paper develops a stochastic optimization model for reservoir refill operation with the objective of maximizing the expected synthesized energy production for a cascade system of hydropower stations while considering flood risk. Streamflow uncertainty is addressed by discretized streamflow scenarios and flood risk is controlled by a joint chance constraint restricting the occurrence probability. With the variability of flood risk level, two advancing refill scenarios for exploring operation benefit are presented. Scenario I loosens the current stagewise storage bounds conditions and allows advancing reservoir refills but keeps the flood risk level the same as the refill policies obtained under the current storage bounds. Scenario II keeps the current storage bounds unchanged but allows increases in flood risk level. The proposed methodology is applied to the Xiluodu cascade system of reservoirs in China and investigates the optimal refill policies obtained by both scenarios. Compared with the benchmark obtained under the current storage bounds and lowest flood risk level, the results show (1) the synthesized energy production can be improved by 2.13% without changing the flood risk level under Scenario I, and (2) the synthesized energy production can also be increased by 0.21% at the expense of increasing the flood risk level by 4.4% when Scenario II is employed. As Scenario I produces higher benefit and lower risk than Scenario II, it is recommended to loosen the current stagewise storage bounds but to keep the flood risk level unchanged during refill operations.

Xiluodu Cascade Reservoir↗
USGS2013

Evaluating changes to reservoir rule curves using historical water-level data

Flood control reservoirs are typically managed through rule curves (i.e. target water levels) which control the storage and release timing of flood waters. Changes to rule curves are often contemplated and requested by various user groups and management agencies with no information available about the actual flood risk of such requests. Methods of estimating flood risk in reservoirs are not easily available to those unfamiliar with hydrological models that track water movement through a river basin. We developed a quantile regression model that uses readily available daily water-level data to estimate risk of spilling. Our model provided a relatively simple process for estimating the maximum applicable water level under a specific flood risk for any day of the year. This water level represents an upper-limit umbrella under which water levels can be operated in a variety of ways. Our model allows the visualization of water-level management under a user-specified flood risk and provides a framework for incorporating the effect of a changing environment on water-level management in reservoirs, but is not designed to replace existing hydrological models. The model can improve communication and collaboration among agencies responsible for managing natural resources dependent on reservoir water levels.

International Journal of River Basin Management↗
USGS2026

Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed

Study region The Russian River watershed, situated in coastal, northern California, experiences hydrologic extremes, including periodic droughts and flooding. Water managers are working to maintain sustainable water supplies and environmental flows, while mitigating flood risks. Study focus This paper introduces an integrated hydrology and river operations model for the Russian River watershed. This model is distinct from models in previous studies because it represents surface-groundwater interactions and uses climate forcings to estimate dynamic water use demands that are superimposed onto both reservoir operations and water supply constraints. The model was used to examine three historical (1990–2015) and eight future (2016–2099) water use and climate change scenarios. New hydrological insights for the region The direct connection between streams and aquifers facilitated both annual aquifer replenishment by high winter streamflows and streamflow depletion by groundwater wells (19 % of pumped groundwater in alluvial aquifers from stream leakage) during critical low flow periods. Simulated streamflow changes included 59 % longer and 54 % more severe streamflow droughts, 26 % lower seasonal low streamflows, and up to 125 % higher peak streamflows, averaged over future climate and water use scenarios, suggesting increased future flood and water availability risks. Results showed the importance of reservoir operations for mitigating the impacts of increased hydroclimatic volatility, despite a decrease in reservoir reliability at Lake Mendocino, suggesting that reservoir management may be used to decrease future risks.

California↗
USGS2017

Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web

Catastrophic flooding is responsible for more loss of life and damages to property than any other natural hazard. Recently developed flood inundation mapping technologies make it possible to view the extent and depth of flooding on the land surface over the Internet; however, by themselves these technologies are unable to provide estimates of losses to property and infrastructure. The Federal Emergency Management Agency’s (FEMA's) HAZUS-MH software is extensively used to conduct flood loss analyses in the United States, providing a nationwide database of population and infrastructure at risk. Unfortunately, HAZUS-MH requires a dedicated Geographic Information System (GIS) workstation and a trained operator, and analyses are not adapted for convenient delivery over the Web. This article describes a cooperative effort by the US Geological Survey (USGS) and FEMA to make HAZUS-MH output GIS and Web compatible and to integrate these data with digital flood inundation maps in USGS’s newly developed Inundation Mapping Web Portal. By running the computationally intensive HAZUS-MH flood analyses offline and converting the output to a Web-GIS compatible format, detailed estimates of flood losses can now be delivered to anyone with Internet access, thus dramatically increasing the availability of these forecasts to local emergency planners and first responders.

Journal of Emergency Management↗
USGS2025

Where to restore and conserve? A regional benefit cost analysis of coral reef protection and restoration for coastal flood resilience

Momentum is growing for the management of coral reefs as a strategy to reduce climate risks in tropical coastlines. Yet, quantification of the life-time costs, impacts, and benefits remains limited. This study provides one of the first rigorous, spatially explicit, regional-scale Benefit:Cost Analyses (BCA) for coral reef restoration and was designed to meet the BCA requirements of major hazard mitigation funding and programs. This study simulates coastal flooding using a hydrodynamic model under different scenarios representing current coral reef conditions, reef degradation, and reef restoration. These coastal flood maps are used to estimate socioeconomic damages, which are included in a BCA to assess cost-effectiveness and priority areas for coral reef conservation and restoration. The United States Virgin Islands is used as a case study given recent impacts from storms and their new policy that declares reefs as natural infrastructure. The results show that flood risk across the islands of Saint Croix, Saint John, and Saint Thomas is $51.4 million USD per year. Annually, coral reefs prevent flood damages to 481 people and $43.6 million USD of infrastructure, which represents 87 % of the flood risk. These results identify the communities that could receive the greatest benefits from coral conservation and restoration, which overlap significantly. Coral reef restoration is found to be a cost-effective strategy for flood mitigation although how reefs are restored matters. Hybrid coral reef restoration provides greater flood mitigation benefits than ecological restoration, but its cost-effectiveness is overall lower given its greater costs. Many coastal areas have benefit:cost ratios exceeding 1.5, which complies with typical government agencies’ requirements for accessing hazard mitigation funds. This valuation framework helps provide rigorous regional-scale quantification of nature-based coastal protection solutions for coastal risk management decisions.

Journal of Environmental Management↗
USGS2023

Archaeological sites in Grand Canyon National Park along the Colorado River are eroding owing to six decades of Glen Canyon Dam operations

The archaeological record documenting human history in deserts is commonly concentrated along rivers in terraces or other landforms built by river sediment deposits. Today that record is at risk in many river valleys owing to human resource and infrastructure development activities, including the construction and operation of dams. We assessed the effects of the operations of Glen Canyon Dam – which, since its closure in 1963, has imposed drastic changes to flow, sediment supply and distribution, and riparian vegetation – on a population of 362 archaeological sites in the Colorado River corridor through Grand Canyon National Park, Arizona, USA. We leverage 50 years of evidence from aerial photographs and more than 30 years of field observations and measurements of archaeological-site topography and wind patterns to evaluate changes in the physical integrity of archaeological sites using two geomorphology-based site classification systems. We find that most archaeological sites are eroding; moreover, most are at increased risk of continuing to erode, due to six decades of operations of Glen Canyon Dam. Results show that the wind-driven (aeolian) supply of river-sourced sand, essential for covering archaeological sites and protecting them from erosion, has decreased for most sites since 1973 owing to effects of long-term dam operations on river sediment supply and riparian vegetation expansion on sandbars. Results show that the proportion of sites affected by erosion from gullies controlled by the local base-level of the Colorado River has increased since 2000. These changes to landscape processes affecting archaeological site integrity limit the ability of the National Park Service and Grand Canyon-affiliated Native American Tribes to achieve environmental management goals to maintain or improve site integrity in situ . We identify three environmental management opportunities that could be used to a greater extent to decrease the risk of erosion and increase the potential for in-situ preservation of archaeological sites. Environmental management opportunities are: 1) sediment-rich controlled river floods to increase the aeolian supply of river-sourced sand, 2) extended periods of low river flow to increase the aeolian supply of river-sourced sand, 3) the removal of riparian vegetation barriers to the aeolian transport of river-sourced sand.

Arizona↗
USGS2021

Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis

Accurate status assessments of long-lived, widely distributed taxa depend on the availability of long-term monitoring data from multiple populations. However, monitoring populations across large temporal and spatial scales is often beyond the scope of any one researcher or research group. Consequently, wildlife managers may be tasked with utilizing limited information from different sources to detect range-wide evidence of population declines and their causes. When assessments need to be made under such constraints, the research and management communities must determine how to extrapolate from variable population data to species-level inferences. Here, using three different approaches, we integrate and analyze data from the peer-reviewed literature and government agency reports to inform conservation for northwestern pond turtles (NPT) Actinemys marmorata and southwestern pond turtles (SPT) Actinemys pallida . Both NPT and SPT are long-lived freshwater turtles distributed along the west coast of the United States and Mexico. Conservation concerns exist for both species; however, SPT may face more severe threats and are thought to exist at lower densities throughout their range than NPT. For each species, we ranked the impacts of 13 potential threats, estimated population sizes, and modeled population viability with and without long-term droughts. Our results suggest that predation of hatchlings by invasive predators, such as American bullfrogs Lithobates catesbeianus and Largemouth Bass Micropterus salmoides, is a high-ranking threat for NPT and SPT. Southwestern pond turtles may also face more severe impacts associated with natural disasters (droughts, wildfires, and floods) than do NPT. Population size estimates from trapping surveys indicate that SPT have smaller population sizes on average than do NPT ( P = 0.0003), suggesting they may be at greater risk of local extirpation. Population viability analysis models revealed that long-term droughts are a key environmental parameter; as the frequency of severe droughts increases with climate change, the likelihood of population recovery decreases, especially when census sizes are low. Given current population trends and vulnerability to natural disasters throughout their range, we suggest that conservation and recovery actions first focus on SPT to prevent further population declines.

Journal of Fish and Wildlife Management↗
USGS2010

Depletion of rice as food of waterfowl wintering in the Mississippi Alluvial Valley

Waterfowl habitat conservation strategies in the Mississippi Alluvial Valley (MAV) and several other wintering areas assume carrying capacity is limited by available food, and increasing food resources is an effective conservation goal. Because existing research on winter food abundance and depletion is insufficient to test this hypothesis, we used harvested rice fields as model foraging habitats to determine if waste rice seed is depleted before spring migration. We sampled rice fields ( n = 39 [winter 2000–2001], n = 69 [2001–2002]) to estimate seed mass when waterfowl arrived in late autumn and departed in late winter. We also placed exclosures in subsets of fields in autumn ( n = 8 [2000–2001], n = 20 [2001–2002]) and compared seed mass inside and outside exclosures in late winter to estimate rice depletion attributable to waterfowl and other processes. Finally, we used an experiment to determine if the extent of rice depletion differed among fields of varying initial abundance and if the seed mass at which waterfowl ceased foraging or abandoned fields differed from a hypothesized giving-up value of 50 kg/ha. Mean seed mass was greater in late autumn 2000 than 2001 (127.0 vs. 83.9 kg/ha; P = 0.018) but decreased more during winter 2000–2001 than 2001–2002 (91.3 vs. 55.7 kg/ha) and did not differ at the end of winter (35.8 vs. 28.3 kg/ha; P = 0.651). Assuming equal loss to deterioration inside and outside exclosures, we estimated waterfowl consumed 61.3 kg/ha (48.3%) of rice present in late autumn 2000 and 21.1 kg/ha (25.1%) in 2001. When we manipulated late-autumn rice abundance, mean giving-up mass of rice seed was similar among treatments (48.7 kg/ha; P = 0.205) and did not differ from 50 kg/ha ( P = 0.726). We integrated results by constructing scenarios in which waterfowl consumed rice at different times in winter, consumption and deterioration were competing risks, and consumption occurred only above 50 kg/ha. Results indicated waterfowl likely consumed available rice soon after fields were flooded and the amount consumed exceeded our empirical estimates but was ≤48% (winters pooled) of rice initially present. We suggest 1) using 50 kg/ha as a threshold below which profitability limits waterfowl feeding in MAV rice fields; 2) reducing the current estimate (130 kg/ha) of rice consumed in harvested fields to 47.2 kg/ha; and 3) increasing available rice by increasing total area of fields managed, altering management practices (e.g., staggered flooding), and exploring the potential for producing second or ratoon rice crops for waterfowl.

Arkansas;Illinois;Kentucky;Louisiana;Mississippi;M↗