A long short-term memory deep learning approach for river water temperature prediction DOI
Salim Heddam, Sungwon Kim, Ali Danandeh Mehr

et al.

Elsevier eBooks, Journal Year: 2022, Volume and Issue: unknown, P. 243 - 270

Published: Jan. 1, 2022

Language: Английский

Permafrost Promotes Shallow Groundwater Flow and Warmer Headwater Streams DOI Creative Commons
Ylva Sjöberg,

Ahmad Jan,

Scott Painter

et al.

Water Resources Research, Journal Year: 2020, Volume and Issue: 57(2)

Published: Dec. 12, 2020

Abstract The presence of permafrost influences the flow paths water through Arctic landscapes and thereby has potential to impact stream discharge thermal regimes. Observations from 11 headwater streams in Alaska showed that July temperatures were higher catchments with more near‐surface permafrost. We apply a fully coupled cryohydrology model investigate if on path depth could cause same pattern groundwater discharging hillslopes streams. simulates surface energy balances, snow, subsurface balances for two‐dimensional hillslope cases varying extent. find continuous have shallow twice as high rates evapotranspiration, compared no For our simulated cases, 6.7% horizontal flux moves top organic soil layers when there is permafrost, while only 0.5% without deeper permafrost‐free simulations buffer seasonal temperature extremes, so summer are highest Our results suggest thawing alters can lead decreases reductions evapotranspiration catchments. These changes importance biotic components ecosystems, however, full remains unknown.

Language: Английский

Citations

75

The influence of permafrost and other environmental factors on stream thermal sensitivity across Yukon, Canada DOI Creative Commons
András Szeitz, Sean K. Carey

Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(4), P. 1083 - 1101

Published: Feb. 27, 2025

Abstract. Thermal sensitivity, defined as the slope of a linear regression between stream and air temperatures, is useful indicator strength coupling meteorological forcings temperature or, conversely, presence non-atmospheric thermal influences such groundwater contributions to streamflow. Furthermore, sensitivity known be responsive environmental change. This study expands current state knowledge in cold northern regions across catchment scales, investigates controls range dispositions, assesses influence conditions unique regions, namely permafrost. We conducted analysis relating modelled mean daily temperatures 57 catchments Yukon, Canada, with areas ranging from 5.4 86 500 km2 permafrost probabilities 0.0 0.99. sensitivities obtained regressions ranged 0.14 0.84 °C °C−1, median 0.56 intercepts −0.07 7.60 °C, Nash–Sutcliffe efficiency 0.81. was positively related area, land covers representing surface water storage, streamflow flashiness or lack contributions. The greatest single characteristic explaining variance topography (9 % explained); however, 39 jointly explained by physiography, cover, indicators, suggesting result multiple interacting controls. primary on appeared indirect; properties affecting residence time, subsurface runoff processes provide separate counteracting effects that are influencing sensitivity.

Language: Английский

Citations

0

Long-term patterns and changes of unglaciated High Arctic stream thermal regime DOI Creative Commons
Marta Majerska, Marzena Osuch, Tomasz Wawrzyniak

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 923, P. 171298 - 171298

Published: Feb. 29, 2024

Although water temperature is one of the most important factors influencing hydrochemistry and river ecology, long-term monitoring modelling stream thermal temporal variability are uncommon. There sparse research regarding regimes Arctic rivers, especially in Svalbard, a geographical hotspot affected by extreme climate change amplification. need for improvement better understanding regime. To address this gap, we present study non-glaciated arctic catchment, Fuglebekken (Spitsbergen, Svalbard). We propose methods reconstructing regime based on available in-situ data. This evaluates different sets input variables with hourly time steps required to explain temperature. The comprises two approaches, stochastic transfer function Multiple Input Single Output supervised machine learning technique, Gaussian Process Regression, simulate years 2005–2022. ground at depth 20 cm total solar radiation were found be main forcings that variability. outputs both models showed similar tendencies patterns. A diurnal warming trend 0.5–3.5 °C per decade has been detected throughout summer season. highest increase 6.0 2005–2022 was second part June. outcomes prove sensitive ongoing climatic changes. an factor many environmental implications.

Language: Английский

Citations

3

Lake Outflow and Hillslope Lateral Inflows Dictate Thermal Regimes of Forested Streams Draining Small Lakes DOI
Jason A. Leach, Bethany T. Neilson, Caleb A. Buahin

et al.

Water Resources Research, Journal Year: 2021, Volume and Issue: 57(6)

Published: May 10, 2021

Abstract Empirical studies have highlighted the important influence of lakes on stream temperature at landscape scales, even when comprise just a small fraction catchment area. However, only few focused hydrologic and thermal processes underpinning these patterns. We collected detailed field measurements boreal that drains headwater lake used data within process‐based model to, (a) document downstream extent influences both seasonal event‐based timescales, (b) assess control observed variability, (c) compare for streams with without lake. Summer autumn outlet temperatures were elevated compared to hillslope lateral inflow temperatures. During periods low outflow, decreased rapidly as local energy fluxes, primarily inflows from hillslopes hyporheic exchange, overwhelmed effects. The was greatest during high outflow persisted least 1.4 km downstream. Since can moderate delay upstream rainfall runoff response, rates generally out‐of‐phase. This difference in timing warm cool water creates dynamic environment Such are ubiquitous northern landscapes, accounting competing contributions is critical predicting how network‐scale regimes will respond environmental change.

Language: Английский

Citations

16

A High‐Resolution, Daily Hindcast (1990–2021) of Alaskan River Discharge and Temperature From Coupled and Optimized Physical Models DOI Creative Commons
Dylan Blaskey, M. N. Gooseff, Yifan Cheng

et al.

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(4)

Published: April 1, 2024

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

Language: Английский

Citations

1

The influence of permafrost and other environmental controls on stream thermal sensitivity across Yukon, Canada DOI Creative Commons
András Szeitz, Sean K. Carey

Published: June 27, 2024

Abstract. Thermal sensitivity, defined as the slope of a linear regression between stream and air temperature, is useful indicator strength coupling atmospheric forcings or conversely, presence non-atmospheric thermal influences such groundwater contributions to streamflow. Furthermore, sensitivity known be responsive environmental change. This study expands current state knowledge in cold, northern regions across catchment scales, investigates controls range dispositions, assesses influence conditions unique cold regions, namely permafrost. We conducted analysis relating mean daily temperature 57 catchments Yukon, Canada, with areas ranging from 5.4 86,500 km2, permafrost probabilities 0.0 0.99. sensitivities obtained regressions ranged 0.14 0.84 °C °C-1, median 0.56 intercepts -0.07 7.60 °C, Nash-Sutcliffe efficiency = 0.81. was positively related area, land covers representing surface water storage, streamflow ‘flashiness’ lack contributions. The greatest single characteristic explaining variance topography physiography (9 % explained); however, 39 explained jointly by physiography, cover, indicators, suggesting result multiple interacting controls. Permafrost appeared have indirect offsetting effects on through its separate counter-acting processes controlling sensitivity.

Language: Английский

Citations

1

Six decades of research on river temperature in Canada DOI
André St‐Hilaire, Muhammed A. Oyinlola, Eisinhower Rincón

et al.

Canadian Water Resources Journal / Revue canadienne des ressources hydriques, Journal Year: 2023, Volume and Issue: 48(4), P. 450 - 474

Published: Oct. 2, 2023

River temperature is a key water quality variable in rivers and streams, as it modulates many other variables well the metabolism, dispersion, behavior of lotic biota. This paper reviews research milestones related to river Canada. The text focuses mostly on how has been centrally motivated by need better understand mitigate anthropogenic impacts thermal regime rivers. for enhanced monitoring, both situ via remote sensing, especially Canadian North, highlighted.

Language: Английский

Citations

3

A long short-term memory deep learning approach for river water temperature prediction DOI
Salim Heddam, Sungwon Kim, Ali Danandeh Mehr

et al.

Elsevier eBooks, Journal Year: 2022, Volume and Issue: unknown, P. 243 - 270

Published: Jan. 1, 2022

Language: Английский

Citations

4