Floodplain Management Research Articles

Increasing Urban Flood Challenges: Spatial Analysis of the 2024 Flood in Rajabasa, Bandar Lampung, Indonesia

This study explores the spatial analysis of flood-prone areas in Rajabasa by utilizing Digital Elevation Model data from DEMNAS and high-resolution aerial photographs obtained via commercial drones. The research aims to understand the region’s flood dynamics and watershed characteristics. The elongated shape of the Rajabasa basin, with a calculated circularity ratio (Rc) of 0.19, indicates that runoff follows the existing stream network, resulting in gradual and prolonged flood events. Field surveys were conducted to validate land cover data, revealing that the majority of the area was residential and classified under Hydrology Soil Group (HSG) D, leading to high Curve Number (CN) values between 88 and 93. These values suggest that nearly all rainfall converts to runoff, exacerbating flooding conditions. Effective flood management strategies were proposed by focusing on areas with the highest CN values and integrating long-term land improvement with short-term flood control infrastructure. The study also highlights the importance of preserving natural drainage lines, which are often overlooked, for enhancing flood mitigation, educating residents about floodplain management, and implementing proper land use regulations. The findings underscore the necessity of combining spatial analysis, high-resolution data, and targeted flood management strategies to mitigate flood risks in Rajabasa and similar flood-prone areas.

Selection, Planning, and Modelling of Nature-Based Solutions for Flood Mitigation

The use of nature-based solutions (NBSs) for hazard mitigation is increasing. In this study, we review the use of NBSs for flood mitigation using a strengths, weaknesses, opportunities, and threats (SWOT) analysis framework for commonly used NBSs. Approaches reviewed include retention and detention systems, bioretention systems, landcover and soil management, river naturalisation and floodplain management, and constructed and natural wetlands. Existing tools for identification and quantification of direct benefits and co-benefits of NBSs are then reviewed. Finally, approaches to the modelling of NBSs are discussed, including the type of model and model parameterisation. After outlining knowledge gaps within the current literature and research, a roadmap for development, modelling, and implementation of NBSs is presented.

Effects of river infrastructure, dredged material placement, and altered hydrogeomorphic processes: The stress ecology of floodplain wetlands and associated fish communities

Recognition of the habitat values of coastal and floodplain wetlands has inspired research and engineering to restore biological functions after widespread species declines. However, the restoration and management of tidal river floodplains requires a more complete understanding of anthropogenic stressors on hydrogeomorphology and ecological processes. River floodplains near the ocean are affected by localized diking and dredging as well as basin-wide stressors such as dams. We evaluated the effects of stressors versus spatial position, both longitudinal and lateral to the mainstem, using physical and biological response variables in river floodplain wetlands. We categorized historical and modern stressors on the hydrogeomorphic regime of the lower Columbia River and estuary, northeast Pacific coast, including basin-scale management and local impacts. Using this categorization, we analyzed 44 attributes using field-collected data from 50 floodplain wetlands. Attributes represent channels, floods, plant communities, and fish communities. Here we show that plant and fish communities are stratified by position along the estuarine–riverine gradient, in contrast to physical habitat characteristics, which are stratified by stressors on hydrogeomorphic regimes and in some cases the lateral distance from the mainstem river on tributaries. Spatial position relative to water-level dynamics and salinity more strongly affect the biota than does stressor history. Stressor effects were greatest on the geomorphology observed in formerly diked, now reconnected wetlands and in wetlands with a history of dredged material placement; historically diked sites had anomalously deep channels with larger cross-sectional areas while sites with dredged material had shallow channels and lower levels of organic carbon in sediment. In wetlands subject only to landscape-scale stressors such as flow alterations by dams, organic carbon levels were higher. These findings provide natural resource managers with opportunities to enhance similarity to natural conditions and better understand future wetland evolution from different baselines of stressor history and river position.

User needs for coastal inundation at climate time scales: A multi‐sectoral case study in the coproduction of knowledge

AbstractCoastal regions are becoming increasingly vulnerable to flooding. Due to growing risk, there is a need for a variety of accessible flood inundation services and information to improve resilience and adaptation outcomes. To better understand these needs the National Oceanic and Atmospheric Administration's Office for Coastal Management and the Center for Operational Oceanographic Products and Services collaborated to host five virtual workshops during the COVID‐19 pandemic to understand inundation needs and deficits of five professional sectors: coastal planning, transportation and navigation, realty and insurance, health and human services, and natural resource and floodplain managers. This paper outlines the information collected from these workshops, shares recommendations for future research to improve equitable coastal resilience and highlights the value of remote engagement for knowledge coproduction. From the project results, we share cross‐cutting topics that emerged and propose a need for greater equity, inclusive engagement, interagency coordination and future research directions through scientist‐stakeholder coproduction workshops for improved coastal resilience.

Scalability of CASCADE2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. As a result, there is a need to develop a flood risk screening tool to analyze watersheds and find vulnerable areas by leveraging the scientific and technological developments of the last decade to prioritize improvements. Because local municipalities are continuously challenged by the impacts of changes in precipitation and other climatic events, the screening tool needs to be scalable, while providing similar results of spatial inundation extent regardless of the scale. Likewise, the ability to perform this analysis without overwhelming limited modeling budgets is a goal for local governments who may spend large amounts of money on capital in the future to retrofit their stormwater management systems. The present study investigates the scalability of a GIS-based hydrologic-hydraulic model, CASCADE2001, to support development of watershed-based flood protection plans. The comparative analysis of the predicted flood response at three nested levels of scale were applied in south Florida to a 8-digit hydrologic unit code (HUC) level (the Caloosahatchee Watershed), a 12-digit HUC level (the Ninemile Canal Subwatershed within the Caloosahatchee Watershed), and a local municipal level (City of Clewiston, Florida within the Ninemile Canal subwatershed). The findings were that the model was scalable and the infrastructure that mattered with respect to results was driven by the scale.

Unsteady flow in a compound channel during flooding: Insights from a combined two-dimensional and three-dimensional numerical simulation

Natural channels often take the form of compound channels during flooding events. The unsteadiness of floods is crucial for flood management and river-floodplain ecosystems. However, the impact of unsteady flow on three-dimensional hydrodynamic processes within compound channels remains poorly understood. This study employed a validated two-dimensional/three-dimensional numerical model to examine how unsteady features influence key hydrodynamic indicators of compound channels, such as velocity distribution, turbulence characteristics, and discharge partitioning between the main channel and floodplain. A definitive positive correlation was found between water level fluctuation amplitudes and integrated discharge during unsteady events, as well as between mean water levels and mean discharges. The proportion of discharge conveyed by the main channel relative to the total was directly linked to the water depth ratio. The exchange at the main channel–floodplain interface exhibits a dual-layer flow pattern: surface waters spill into the floodplain, while deeper waters are siphoned into the main channel. Unsteady conditions principally modulate the intensity of these exchanges, altering hydraulic interactions and water transfer between areas. Pronounced wall shear stresses were detected at the main channel–floodplain interface due to swift channel flows and momentum exchange at the floodplain margin, with maxima adjacent to the floodplain edge correlating with peak flow velocities. Under deep conditions, cross-sectional flow across the compound channel's mixing layer was essentially two-dimensional. These findings elucidate the complex hydrodynamics inherent to unsteady overbank flows while holding implications for enhancing floodplain management and advancing the understanding of unsteady fluvial hydraulics.

Flood Potential Portal: A web tool for understanding flood variability and predicting peak discharges

AbstractThe Flood Potential Portal (https://floodpotential.erams.com/) has been developed for the contiguous United States, as a practitioner‐focused tool that uses observational data (streamgages) to enhance understanding of how floods vary in space and time, and assist users in making more informed peak discharge predictions for infrastructure design and floodplain management. This capability is presented through several modules. The Mapping module provides tools to explore variability using multiple indices, and provides detailed information, figures, and algorithms describing and comparing flooding characteristics. The Cross‐Section Analysis module allows users to cut regional‐scale sections to interpret the role of topography in driving flood variability. The Watershed Analysis module provides multiple methods for quantifying expected peak discharge magnitudes and flood frequency relationships at user‐selected locations, including the integration of observed trends in flood magnitudes due to climate change and other sources of nonstationarity into decision making. The Streamgage Analysis module performs streamgage flood‐frequency analyses. These modules are based in part on the flood potential method, through the use of 207 zones of similar flood response defined using more than 8200 streamgages with watershed areas <10,000 km2. Regression models that define each zone had high explained variance (average R2 = 0.93). An example is provided to illustrate use of the Flood Potential Portal for the design of a hypothetical bridge replacement.

Lateral connectivity maintains higher freshwater mussel biodiversity

Abstract The loss of lateral hydrological connectivity (LLHC) in freshwater ecosystems is increasingly threatening biodiversity; however, studies reporting this situation are limited, especially those assessing multi‐measure biodiversity features at large spatial scales. Here, and using one the most threatened taxonomic groups in freshwater ecosystems, we examined the possible influence of LLHC on the species diversity, density, and biomass of mussel assemblages and the genetic diversity and structure of Nodularia douglasiae (a common and widespread native species) in the Yangtze River floodplain. Results showed that the species diversity of freshwater mussels (α and β diversity) significantly differed between the connected and the disconnected areas, with higher α diversity and lower β diversity in the connected areas. At the same time, relative abundance, density, biomass, and genetic diversity of freshwater mussels were higher in the connected areas. High genetic differentiation and low gene flow were found among the 18 analysed N. douglasiae populations, indicating that LLHC is affecting genetic structure of this particular freshwater mussel species. Overall, results indicated that river–lake connectivity is affecting freshwater mussel biodiversity. In addition, this study highlights that multi‐measure biodiversity features provide distinct information about biodiversity dynamics, and are essential to evaluate the effects of floodplain disconnection. We advocate that an integrative approach to floodplain management embracing species and genetic diversity is needed for effective biodiversity conservation in large river ecosystems.

Towards sustainable agricultural landscapes: Lessons from an interdisciplinary research-based framework applied to the Saint Lawrence floodplain

Floodplains are unique environments that provide a dynamic link between terrestrial and aquatic systems. Intensification of human activity – particularly agriculture and urbanisation – has resulted in the degradation of floodplains worldwide. Restoration and sustainable management of floodplains requires holistic assessment and compromise between stakeholders to successfully balance environmental, economic, and social benefits. Yet, understanding these complex systems sufficiently to provide evidence-based recommendations is a challenge. We present the lessons learned from establishing an interdisciplinary research-based framework on the agricultural floodplain of Lake Saint Pierre, Québec, Canada, whose mandate was to a) understand and define key environmental, agricultural, and socioeconomic attributes of the landscape, b) quantify the trade-offs and synergies between these attributes across different agricultural practices, regions, and land uses, and c) explore novel agri-environmental management practices to assess their role in sustainable floodplain management. Within this manuscript, we explore the benefits that such an approach offers in evaluating sustainable floodplain land use. We found that an interdisciplinary research-based approach demonstrated important benefits such as knowledge transfer, more efficient use of resources (e.g., personnel, funding), and a flexible yet robust research framework. A framework of individual research projects connected to broader interdisciplinary themes allowed a more holistic synthesis of the floodplain systems and assessment of agri-environmental practices. By implicitly considering spatial and social scales, we conceptualised not just how redistribution of the land use types can meet sustainable management objectives, but also explored how compromises within existing uses can optimise socio-economic, agricultural and environmental dimensions and move towards a sustainable multifunctional landscape.

Soil texture and vegetation root density assessment on regulating erosion across river floodplains

Over the last few decades, floodplain management with best management practices has been utilized to treat areas susceptible to soil erosion and degradation. A major emphasis has been placed on the role of the above-ground vegetation to regulate soil erosion, but less attention has been directed to the floodplain soil types and root interactions. The goal of the current study was to quantify the effectiveness of soil texture and vegetation root density in reducing soil erosion in the highly agricultural Turkey River watershed in Iowa. For the purposes of this study, twenty-four topsoil samples were removed from various locations across the lower, i.e., active, and higher elevation river floodplain soils of five identified field sites along the Turkey River longitudinal profile. The topsoil sampling process was designed based on site-specific flood inundation maps. Using detailed particle size analyses and topsoil erodibility experiments, results indicated that the threshold values for the onset of erosion increased longitudinally, from upstream to downstream, matching the pattern identified for silt and clay particles in floodplain soils. Statistical analysis confirmed that there is a strong linear correlation between the threshold values for erosion to occur and the fine particle content in floodplain soils, as well as the existence of vegetation characterized by dense and well-developed root systems. Overall, the fine particle content of floodplains’ surface soils and the existence of vegetation with dense and well-developed roots determined the threshold values for erosion, whereas the presence of vegetation with non-dense and non-well-developed root systems had a negligible effect, similar to bare soil, on controlling soil erosion. The findings of the current research can be applied by watershed management authorities to protect floodplain areas at risk and prevent further soil degradation and water pollution.

Predicting peak inundation depths with a physics informed machine learning model

Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events. This study demonstrates that a proposed machine learning model, MaxFloodCast, trained on physics-based hydrodynamic simulations in Harris County, offers efficient and interpretable flood inundation depth predictions. Achieving an average R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2$$\\end{document} of 0.949 and a Root Mean Square Error of 0.61 ft (0.19 m) on unseen data, it proves reliable in forecasting peak flood inundation depths. Validated against Hurricane Harvey and Tropical Storm Imelda, MaxFloodCast shows the potential in supporting near-time floodplain management and emergency operations. The model’s interpretability aids decision-makers in offering critical information to inform flood mitigation strategies, to prioritize areas with critical facilities and to examine how rainfall in other watersheds influences flood exposure in one area. The MaxFloodCast model enables accurate and interpretable inundation depth predictions while significantly reducing computational time, thereby supporting emergency response efforts and flood risk management more effectively.

Assessment of longitudinal dispersion and flow resistance near floodplains through riparian woodlands

Riparian woodlands prevent bank erosions, recycle minerals, sustain biodiversity, act as flow resistance on floodplains, and filter pollutants. The emergent trees characterize woodlands with different spacing arrangements that dictate flow resistance and longitudinal dispersion of the pollutants in compound channel flow. The single- and multistage compound channels exist in urban and natural watercourses with riparian and transplanted trees on different stages of the floodplain. This study numerically validates the planting of vegetation in lines on single- and multistage floodplains using a wall-modeled large-eddy simulation model. Post-validation, the focus of the study was to assess the hydrodynamic behavior and mixing around the floodplain and main channel section of different tested configurations. The approximation of flow structures for the various configurations of tree plantations shows stronger vortices with significant characteristic length scales for floodplains closer to the main channel. The intensity of the secondary current is higher for denser planted trees at junctions of floodplains. For higher flow events, drag force contributions for staged floodplains with trees on both stages are 45–41%, and trees on the top stage contribute 27-22% to the total frictional force budget. The subsequent investigation shows that the in-line trees geometrical configuration and spacing arrangement on the floodplain dictates flow resistance and longitudinal dispersion of the pollutants and contamination in channel flow. The results show that the overall reduction in discharge for floodplains with tree planting is 19.8–36.2% for single-stage and 10.4–23.6% for multistage compound channels. The longitudinal dispersion coefficients for each multi-zone model predict a 61% and 41% dispersion reduction, respectively, in single- and multistage floodplains with planted trees. Floodplains with denser tree spacing have a maximum zonal discharge reduction of 45% for a single-stage and 27.2% and 28.0% for multistage channels. These findings strongly suggest that the planting parameters of spacing-to-diameter ratio and floodplain geometry play a pivotal role in floodplain management from the perspective of contaminant dispersion and flood risk reduction during high-flow events.

Numerical simulation of flow characteristics in nonprismatic compound channels

ABSTRACT The assessment of the flow characteristics of river systems is a very intricate undertaking in the development of hydraulic models for the purposes of flood control and floodplain management. Therefore, it is essential to use simulation models in order to calibrate and verify the experimental results. In this study, the Hydrologic Engineering Centre's – River Analysis System (HEC-RAS) is used to calibrate and validate the distribution of velocity and shear stress for different converging compound channels. Two separate flow regimes were assessed for validation based on experimental data obtained from converging compound channels with angles of θ = 5°, 9°, and 12.38°. The projected values for two relative depths (β = 0.15 and 0.20) exhibit a similar pattern of variation as the empirical observations and are marginally lower than the recorded values. This suggests that the HEC-RAS model accurately estimates the velocity and shear stress values. The disparity between the simulated and experimental outcomes shows a discrepancy of less than 10%. Hence, the implications of our results suggest that while dealing with nonprismatic rivers, it is advisable to take into account lower values. The used methodology and the outcomes focused on problem-solving might potentially inform the development of flood control infrastructure for nonprismatic watercourses.

Impacts of future climate and land use/land cover change on urban runoff using fine-scale hydrologic modeling

Future changes in land use/land cover (LULC) and climate (CC) affect watershed hydrology. Despite past research on estimating such changes, studies on the impacts of both these nonstationary stressors on urban watersheds have been limited. Urban watersheds have several important details such as hydraulic infrastructure that call for fine-scale models to predict the impacts of LULC and CC on watershed hydrology. In this paper, a fine-scale hydrologic model—Personal Computer Storm Water Management Model (PCSWMM)—was applied to predict the individual and joint impacts of LULC changes and CC on surface runoff attributes (peak and volume) in 3800 urban subwatersheds in Midwest Florida. The subwatersheds a range of characteristics in terms of drainage area, surface imperviousness, ground slope and LULC distribution. The PCSWMM also represented several hydraulic structures (e.g., ponds and pipes) across the subwatersheds. We analyzed changes in the runoff attributes to determine which stressor is most responsible for the changes and what subwatersheds are mostly sensitive to such changes. Six 24-h design rainfall events (5- to 200-year recurrence intervals) were studied under historical (2010) and future (year 2070) climate and LULC. We evaluated the response of the subwatersheds in terms of runoff peak and volume to the design rainfall events using the PCSWMM. The results indicated that, overall, CC has a greater impact on the runoff attributes than LULC change. We also found that LULC and climate induced changes in runoff are generally more pronounced in greater recurrence intervals and subwatersheds with smaller drainage areas and milder slopes. However, no relationship was found between the changes in runoff and original subwatershed imperviousness; this can be due to the small increase in urban land cover projected for the study area. This research helps urban planners and floodplain managers identify the required strategies to protect urban watersheds against future LULC change and CC.

Seeing the floods through the trees: Using adaptive shortwave infrared thresholds to map inundation under wooded wetlands

AbstractAccurate information about the extent, frequency and duration of forest inundation is required to inform ecological, biophysical and hydrological models and enables floodplain managers to quantify the efficacy of flood mitigation/modification activities. Open water classifiers derived from optical remote sensing typically underestimate or fail to detect floodplain forest inundation. This paper presents a new method for detecting forest inundation dynamics using freely available Landsat and Sentinel 2 data, referred to as short‐wave infrared mapping under vegetation. The method uses a dynamic threshold that accounts for the additional shortwave infrared reflectance caused by the presence of tree canopies over floodwater. The method is demonstrated at five Ramsar listed River Red Gum floodplain forest wetlands in southeastern Australia. Accuracy assessment based on independent drone imagery from a wide range of vegetated wetlands showed an absolute accuracy of 67%–70% and a fuzzy accuracy of 81%–83%. We found the method is conservative, and underestimates inundation (16%–18%) but very rarely misclassifies dry pixels as inundated (0.3%–0.6%). When compared to river gauge data, the method shows similar trends to an open water classifier (i.e., the area of inundated vegetation increases with increasing river height). The method is conservative compared to lidar‐based floodplain inundation models but can be applied wherever cloud‐free scenes of Landsat or Sentinel 2 have been acquired, thereby enabling floodplain managers with the ability to quantify changes in inundation dynamics in places/time‐periods where lidar is unavailable.

DIVERSITY AND REGENERATION OF WOODY PLANTS OF LOGONE BIRNI FLOODPLAIN VEGETATION IN THE FAR NORTH REGION OF CAMEROON

This study aims to contribute to the conservation and sustainable management of the Logone-Birni floodplains in Cameroon. In total, 27 plots of 100 m x 100 m plots of were laid out in 3 land use types (protected area, grazing area and agricultural area). Within each plot, all woody individuals having ≥ 10 cm circumference at breast height (> 1.3 m) were identified, and all the stems with a circumference ≤ 10 cm were considered as seedlings. A total of 43 timber species belonging to 35 genera and 21 families were harvested. Shannon-Weaver diversity ranged from 1.77-2.39 and the Pielou equitability index from 0.84-0.88 with low values in agricultural areas and higher values in protected and grazing areas. The distribution of stems according to diameter and height showed that all stands exhibit classic exponential decay distribution ‘‘L’’ or ‘‘J’’ inverted, reflecting the predominance of individuals with small diameters. The regeneration rates of the stand vary from 0.81 to 51.56%, indicating a difficult regeneration due partly to anthropogenic activities. It also appears that given the low diversity and the difficult regeneration of the stand, it is important, even crucial, to manage this plain to ensure the conservation and sustainable management of the biological resources that it hosts.

Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR

Frequent floods caused by monsoons and rainstorms have significantly affected the resilience of human and natural ecosystems in the Nam Ngum River Basin, Lao PDR. A cost-efficient framework integrating advanced remote sensing and machine learning techniques is proposed to address this issue by enhancing flood susceptibility understanding and informed decision-making. This study utilizes remote sensing geo-datasets and machine learning algorithms (Random Forest, Support Vector Machine, Artificial Neural Networks, and Long Short-Term Memory) to generate comprehensive flood susceptibility maps. The results highlight Random Forest’s superior performance, achieving the highest train and test Area Under the Curve of Receiver Operating Characteristic (AUROC) (1.00 and 0.993), accuracy (0.957), F1-score (0.962), and kappa value (0.914), with the lowest mean squared error (0.207) and Root Mean Squared Error (0.043). Vulnerability is particularly pronounced in low-elevation and low-slope southern downstream areas (Central part of Lao PDR). The results reveal that 36%–53% of the basin’s total area is highly susceptible to flooding, emphasizing the dire need for coordinated floodplain management strategies. This research uses freely accessible remote sensing data, addresses data scarcity in flood studies, and provides valuable insights for disaster risk management and sustainable planning in Lao PDR.

Quantification of landuse changes driven by the dynamics of the Jamuna River, a giant tropical river of Bangladesh

Changes in river bank location have wide consequences on floodplain communities and the sustainability of floodplain ecosystems. Although river dynamics are monitored globally and locally, understanding the impact of riverine dynamics on land use change remains a challenge. Bangladesh, part of the Bengal Delta, is mostly made up of alluvial deposits and is crisscrossed by so many rivers. Jamuna is one of the prominent rivers in this region. This study presents a consistent evaluation of the dynamics of the Jamuna river and ensuing changes in land use over 48 years (1972–2020) depending on satellite observations and geospatial analysis. Changes in the presence of water were used to estimate the advance/retreat of the banks and loss/gain of land along 257 perpendicular transects along the common pattern of the centerlines of the river. We found that the overall loss of agricultural land was about 535.01 km2, sevenfold of the gained agricultural land. Other land use losses were bare lands 136.73 km2, waterbodies 80.37 km2, settlement 67.28 km2 and vegetation 132.79 km2 against 48.47 km2, 3.52 km2, 23.76 km2 and 6.14 km2 land use gains respectively. Agricultural land loss impacts the livelihood of the floodplain dwellers and settlement loss causes internal migration. This pattern of land use change driven by the river dynamics has created newer environmental challenges and additionally, climate change may intricate the situation in the future. The findings of this study throw insight into the fact and may aid in sustainable river training measures and floodplain management.

Modelling Floodplain Vegetation Response to Climate Change, Using the Soil and Water Assessment Tool (SWAT) Model Simulated LAI, Applying Different GCM’s Future Climate Data and MODIS LAI Data

Scientists widely agree that anthropogenically driven climate change significantly impacts vegetation growth, particularly in floodplain areas, by altering river flow and flood regimes. This impact will accelerate in the future, according to climate change projections. For example, in Australia, climate change has been attributed to a decrease in winter precipitation in the range of 56% to 72.9% and an increase in summer from 11% to 27%, according to different climate scenarios. This research attempts to understand vegetation responses to climate change variability at the floodplain level. Further, this study is an effort to enlighten our understanding of temporal climate change impacts under different climate scenarios. To achieve these aims, a semi-distributed hydrological model was applied at a sub-catchment level to simulate the Leaf Area Index (LAI). The model was simulated against future time series of climate data according to Global Climate Model (GCM) projections. The time series data underwent a non-parametric Mann–Kendall test to detect trends and assess the magnitude of change. To quantify the model’s performance, calibration and validation were conducted against the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI. The calibration and validation results show Nash–Sutcliffe efficiency (NSE) values of 0.85 and 0.78, respectively, suggesting the model’s performance is very good. The modeling results reveal that the rainfall pattern fluctuates under climate projections within the study site, in which vegetation tends to be more vibrant during the warmer seasons. Moreover, the modeling results highlighted increases in the average projected future winter temperatures, which can help vegetation growth during winter. The results of this study may be employed for sustainable floodplain management, restoration, land-use planning, and policymaking, and help floodplain communities better prepare for and respond to changing flood patterns and related challenges under a future changing climate.

Addressing inequities and meeting needs of Indigenous communities in floodplain management

Anthropogenic impacts have altered and degraded global ecosystems. Integrated resource management offers an important solution to enhance collaboration, holistic thinking, and equity by considering diverse perspectives in decision making. In Washington State, Floodplains by Design (FbD) is a floodplain management and habitat restoration program that emphasizes bringing together diverse stakeholders and supporting conversations between local, state, and Tribal governments while enhancing environmental justice in the region. Marginalized communities continue to be disproportionately impacted by environmental disturbances. Our project interviewed Tribal natural resource managers to assess the degree to which they felt FbD was supporting their community’s needs. Our research asked three questions: (1) What Tribal needs and inequities associated with floodplains are identified by Tribal natural resource managers? (2) Are these needs and inequities being addressed by FbD? and (3) How can FbD better address these needs and inequities moving forward? We found that while the integrated approach of FbD was driving solutions in some realms, there are ways in which the program could better support needs and address inequities in Tribal communities. Specifically, we found that conventional responses to environmental challenges are rooted in modernist paradigms that have created persistent dualities, including that of human-nature and human-nonhuman. Such a paradigm is in conflict with wellbeing and self-determination of Tribal cultures that are deeply connected to Pacific salmon. In closing, we provide insights on these mechanisms and offer solutions moving forward.