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Arctic and subarctic rivers are warming rapidly, with unknown consequences for migratory fishes and the human communities dependent on them. To date, few studies have provided a comprehensive assessment of possible climate change impacts on the hydrology and temperature of Arctic rivers at the regional scale, and even fewer have connected those changes to multiple fish species with input and guidance from Indigenous communities. We used climate, hydrologic, and fish-growth simulations of historical (1990–2021) and future (2034–2065) young-of-year (YOY) growth potential of Chinook salmon (Oncorhynchus tshawytscha) and Dolly Varden (Salvelinus malma) for seven river basins in the Arctic-Yukon-Kuskokwim (AYK) region of Alaska, USA and Yukon Territory, Canada. Historically, summer water temperatures of all river basins remained below thresholds regarded as deleterious for Chinook salmon (14.6 °C) and Dolly Varden (16 °C), even in the warmest years. However, by the mid-century, Chinook salmon growth was limited, with declines in the warmest years in most river basins. Conversely, Dolly Varden are expected to benefit, with a near-doubling in growth projections in all river basins. This suggests that there may be an increase in suitable habitat for Dolly Varden by mid-century. The results highlight species-specific consequences of climate change and can guide future research on refugia for these species of cultural and subsistence importance to Indigenous communities in the AYK region and throughout the Arctic. 

NetCDF files in this dataset can be accessed and downloaded from the ADC directory via: [https://arcticdata.io/data/10.18739/A25M62870/](https://arcticdata.io/data/10.18739/A25M62870/) The Regional Arctic System Model, the combined Weather Research & Forecasting Model and the Community Terrestrial Systems Model for climate and land surface processes, mizuRoute for river routing, and the River Basin Model for river temperature, was used to generate high-resolution spatial and temporal data for 49 major Alaskan river basins. This modeling framework was applied to compare Alaskan hydrology between historical (1990-2021) and mid-century (2035-2064) periods across six future scenarios. These scenarios include six dynamically downscaled projections: two pseudo-global warming simulations based on historical meteorology, and four directly downscaled global climate models under the Shared Socioeconomic Pathway (SSP) SSP2-4.5 and SSP3-7.0 emission pathways. The climate data encompass variables such as snowpack, evapotranspiration, precipitation (rain and snow), groundwater, river temperature and discharge, as well as heat flux to the ocean. 

High spatial and temporal resolution models are essential for understanding future climate impacts and developing effective climate resilience plans. However, existing regional and global river models often lack the resolution needed to accurately capture local conditions. This study uses a series of high-resolution models, including the Regional Arctic System Model, mizuRoute, and the river basin model, to analyze Arctic and sub-Arctic Alaskan hydrology. We compare a historical baseline (1991–2020) with six midcentury (2035–64) futures: two pseudo–global warming scenarios based on historical meteorology and four direct dynamically downscaled global climate models. The six futures reveal significant uncertainty in future annual discharge and peak flows, although a widespread increase in discharge during April (+63%) and October (+31%) is consistently shown across models. Projected increases in rain and shifting weather patterns lead to a transition from snow to rain in spring and autumn, reducing the fraction of snowmelt contributing to river discharge. Rising evapotranspiration moderates discharge changes, particularly in autumn, by offsetting precipitation increases. Average summer river temperatures are projected to increase by approximately 1.5°C, doubling the number of river segments that experience 18°C days, a critical threshold for salmon survival, and intensifying the heat flux to the ocean adding an average of 3.3 × 10¹²MJ yr⁻¹. These changes in the hydrologic cycle could profoundly impact riverine and oceanic ecosystems, posing substantial challenges to communities reliant on these environments. Significance StatementThe purpose of this study is to enhance our understanding of the midcentury climate change impacts on the Alaskan hydrologic cycle. In all six of the potential future scenarios, river flows in spring and autumn are predicted to increase and river temperatures are projected to be warmer throughout the year. These changes are significant as higher river temperatures could jeopardize fish survival. Additionally, the combined effect of increased river water and higher temperatures during spring and autumn will contribute more heat to the ocean, possibly reducing nearshore sea ice. This is crucial because many communities depend on rivers and sea ice for transportation and subsistence activities. 

Abstract Earth System Models (ESM)are crucial for quantifying climate impacts across Earth's interconnected systems and supporting science‐based adaptation and mitigation. However, not including end‐users, especially decision‐makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision‐making. While the ESM community increasingly values broad community engagement, end‐users may not initially perceive models as useful for local planning. Co‐designing models with end‐users fosters two‐way learning: users better understand models and their outputs, while modelers gain insights into fine‐scale local processes like monitoring practices and management priorities. Higher‐level co‐design can lead to more customized, priority‐driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co‐design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision‐makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high‐resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land‐atmosphere models. In the Mid‐Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four‐level framework: (a) Co‐design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co‐develop New Model Functions. We aim to help researchers consider and compare co‐design across diverse modeling projects systematically and coherently. 

Abstract Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic. 

Abstract Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate‐based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling‐Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non‐optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions. 

Abstract As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community‐engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project‐specific knowledge co‐production protocols. This paper provides a novel model of design and implementation to co‐produce knowledge with communities across a large study domain.