Dataset Information

The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset.

ABSTRACT: Floodplains provide essential ecosystem functions, yet >80% of European and North American floodplains are substantially modified. Despite floodplain changes over the past century, comprehensive, long-term land use change data within large river basin floodplains are limited. Long-term land use data can be used to quantify floodplain functions and provide spatially explicit information for management, restoration, and flood-risk mitigation. We present a comprehensive dataset quantifying floodplain land use change along the 3.3 million km² Mississippi River Basin (MRB) covering 60 years (1941-2000) at 250-m resolution. We developed four unique products as part of this work, a(n): (i) Google Earth Engine interactive map visualization interface, (ii) Python code that runs in any internet browser, (iii) online tutorial with visualizations facilitating classroom code application, and (iv) instructional video demonstrating code application and database reproduction. Our data show that MRB's natural floodplain ecosystems have been substantially altered to agricultural and developed land uses. These products will support MRB resilience and sustainability goals by advancing data-driven decision making on floodplain restoration, buyout, and conservation scenarios.

SUBMITTER: Rajib A

PROVIDER: S-EPMC8520011 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset.

Rajib Adnan A Zheng Qianjin Q Golden Heather E HE Wu Qiusheng Q Lane Charles R CR Christensen Jay R JR Morrison Ryan R RR Annis Antonio A Nardi Fernando F

Scientific data 20211015 1

Floodplains provide essential ecosystem functions, yet >80% of European and North American floodplains are substantially modified. Despite floodplain changes over the past century, comprehensive, long-term land use change data within large river basin floodplains are limited. Long-term land use data can be used to quantify floodplain functions and provide spatially explicit information for management, restoration, and flood-risk mitigation. We present a comprehensive dataset quantifying floodpla ...[more]

PMID: 34654838

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Project description:Continued large-scale public investment in declining ecosystems depends on demonstrations of "success". While the public conception of "success" often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.

Project description:Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying "high priority" areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Dataset Information

The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset.

Publications

The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset.

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