Estimation of daily stream water temperatures with a Bayesian regression approach

Sohrabi, Mohammad M.; Benjankar, Rohan; Tonina, Daniele; Wenger, Seth J.; Isaak, Daniel J.

doi:10.1002/hyp.11139

Cited by 48 publications

(45 citation statements)

References 65 publications

(131 reference statements)

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“…Dobra, Donja Mrežnica, Gornja Dobra, Korana, and Slunjčica respectively. The RMSE values compare reasonably with that inJackson et al (2018) (1.57ºC) andSohrabi et al (2017)…”

supporting

confidence: 71%

Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia

Zhu

Bonacci

Oskoruš

et al. 2019

Journal of Hydrology and Hydromechanics

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The bio-chemical and physical characteristics of a river are directly affected by water temperature, which therefore affects the overall health of aquatic ecosystems. In this study, long term variations of river water temperatures (RWT) in Kupa River watershed, Croatia were investigated. It is shown that the RWT in the studied river stations increased about 0.0232-0.0796ºC per year, which are comparable with long term observations reported for rivers in other regions, indicating an apparent warming trend. RWT rises during the past 20 years have not been constant for different periods of the year, and the contrasts between stations regarding RWT increases vary seasonally. Additionally, multilayer perceptron neural network models (MLPNN) and adaptive neuro-fuzzy inference systems (ANFIS) models were implemented to simulate daily RWT, using air temperature (T a ), flow discharge (Q) and the day of year (DOY) as predictors. Results showed that compared to the individual variable alone with T a as input, combining T a and Q in the MLPNN and ANFIS models explained temporal variations of daily RWT more accurately. The best accuracy was achieved when the three inputs (T a , Q and the DOY) were included as predictors. Modeling results indicate that the developed models can well reproduce the seasonal dynamics of RWT in each river, and the models may be used for future projections of RWT by coupling with regional climate models.

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“…Dobra, Donja Mrežnica, Gornja Dobra, Korana, and Slunjčica respectively. The RMSE values compare reasonably with that inJackson et al (2018) (1.57ºC) andSohrabi et al (2017)…”

supporting

confidence: 71%

Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia

Zhu

Bonacci

Oskoruš

et al. 2019

Journal of Hydrology and Hydromechanics

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“…Measured discharge and temperature time series are available for some of these tributaries for the period after 2011. Discharges and stream water temperatures for ungaged tributaries were estimated with the hydrological model (Sohrabi, ) and the Stream Water Temperature Model (Sohrabi, Benjankar, Tonina, Wenger, & Isaak, ) models, respectively.…”

Section: Methodsmentioning

confidence: 99%

An ecohydraulics virtual watershed: Integrating physical and biological variables to quantify aquatic habitat quality

et al. 2018

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Advances in remote sensing coupled with numerical modelling allow us to build a “virtual ecohydraulics watershed” at the micro‐habitat scale. This approach is an integrated modelling framework with a cascade of models including physical (hydrologic, hydraulic, and stream water temperature) and biological (fish habitat) modelling at a resolution and extent important for aquatic and terrestrial organisms. We applied this approach to quantify the impacts of discharges and water temperature on habitat quality and spatial/temporal habitat use patterns of bull trout, a federally listed species along the South Fork Boise River. We coupled process‐based snow melt and hydrologic models to predict water availability within the watershed. The model fed one‐ and two‐dimensional hydrodynamic models to predict stream hydraulics and water temperature using high‐resolution (meter scale) river bathymetric data. This information was then used in an aquatic habitat modelling to characterize habitat quality distribution as a function of discharges. Our results showed that the summer thermal regime of river system would alter available habitat. The high spatial resolution analysis allows modelling to predict the importance of lateral habitats, which serve as vital refugia during high‐flow events for many fish species. The advances in remote sensing, numerical modelling, and understanding of physical‐biological processes provide us an opportunity to conceptualize new process‐based integrated modelling tools to analyse human impacts at a catchment scale, for example, dam operation and climatic variability on aquatic habitat and status, and further to develop restoration protocols in a virtual domain before field studies are developed and/or structures built.

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“…Stefan and Preud'homme 1993, Mohseni and Stefan 1999, Caissie et al 2001, Webb et al 2003, Caissie 2006, Sahoo et al 2009. However, as pointed out by Arismendi et al (2014), Toffolon and Piccolroaz (2015) and Sohrabi et al (2017) (just to mention some recent works), the direct statistical link between AT and RWT may be not always exhaustive due to the additional influence from other factors, primarily streamflow. In many cases, purely statistical models based on AT are therefore not adequate to predict RWT (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the impact of the Three Gorges Dam on the thermal dynamics of the Yangtze River

Cai

Piccolroaz

Huang

et al. 2018

Environ. Res. Lett.

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This study examines the impact of the world's largest dam, the Three Gorges Dam (TGD), on the thermal dynamics of the Yangtze River (China). The analysis uses long-term observations of river water temperature (RWT) in four stations and reconstructs the RWT that would have occurred in absence of the TGD. Relative to pre-TGD conditions, RWT consistently warmed in the region due to air temperature (AT) increase. In addition, the analysis demonstrates that the TGD significantly affected RWT in the downstream reach. At the closest downstream station (Yichang) to the TGD, the annual cycle of RWT experienced a damped response to AT and a marked seasonal alteration: warming during all seasons except for spring and early summer which were characterized by cooling. Both effects were a direct consequence of the larger thermal inertia of the massive water volume stored in the TGD reservoir, causing the downstream reach to be more thermally resilient. The approach used here to quantify the separate contributions of climate and human interventions on RWT can be used to set scientific guidelines for river management and conservation planning strategies.

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Estimation of daily stream water temperatures with a Bayesian regression approach

Cited by 48 publications

References 65 publications

Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia

Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia

An ecohydraulics virtual watershed: Integrating physical and biological variables to quantify aquatic habitat quality

Quantifying the impact of the Three Gorges Dam on the thermal dynamics of the Yangtze River

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