Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

2015 ◽  
Vol 521-522 ◽  
pp. 11-18 ◽  
Author(s):  
William R. Selbig
2012 ◽  
Vol 13 (3) ◽  
pp. 1052-1065 ◽  
Author(s):  
Manuel Punzet ◽  
Frank Voß ◽  
Anja Voß ◽  
Ellen Kynast ◽  
Ilona Bärlund

Abstract Stream water temperature is an important factor used in water quality modeling. To estimate monthly stream temperature on a global scale, a simple nonlinear regression model was developed. It was applied to stream temperatures recorded over a 36-yr period (1965–2001) at 1659 globally distributed gauging stations. Representative monthly air temperatures were obtained from the nearest grid cell included in the new global meteorological forcing dataset—the Water and Global Change (WATCH) Forcing Data. The regression model reproduced monthly stream temperatures with an efficiency of fit of 0.87. In addition, the regression model was applied for different climate zones (polar, snow, warm temperate arid, and equatorial climates) based on the Köppen–Geiger climate classification. For snow, warm temperate, and arid climates the efficiency of fit was larger than 0.82 including more than 1504 stations (90% of all records used). Analyses of heat-storage effects (seasonal hysteresis) did not show noticeable differences between the warming/cooling and global regression curves, respectively. The maximum difference between both limbs of the hysteresis curves was 1.6°C and thus neglected in the further analysis of the study. For validation purposes time series of stream temperatures for five individual river basins were computed applying the global regression equation. The accuracy of the global regression equation could be confirmed. About 77% of the predicted values differed by 3°C or less from measured stream temperatures. To examine the impact of climate change on stream water temperatures, gridded global monthly stream temperatures for the climate normal period (1961–90) were calculated as well as stream temperatures for the A2 and B1 climate change emission scenarios for the 2050s (2041–70). On average, there will be an increase of 1°–4°C in monthly stream temperature under the two climate scenarios. It was also found that in the months December, January, and February a noticeable warming predominantly occurs along the equatorial zone, while during the months June, July, and August large-scale or large increases can be observed in the northern and southern temperate zones. Consequently, projections of decay rates show a similar seasonal and spatial pattern as the corresponding stream temperatures. A regional increase up to ~25% could be observed. Thus, to ensure sufficient water quality for human purposes, but also for freshwater ecosystems, sustainable management strategies are required.


2016 ◽  
Author(s):  
Heidelinde Trimmel ◽  
Philipp Weihs ◽  
David Leidinger ◽  
Herbert Formayer ◽  
Gerda Kalny

Abstract. The influence of expected changes in heat wave intensity during the 21st century on the temperatures of an pre-alpine river are simulated and the mitigating effects of riparian vegetation shade on the radiant and turbulent energy fluxes analysed. Minor stream water temperature increases are modelled within the first half of the century, but a more significant increase is predicted for the period 2071–2100. The magnitude of maximum, mean and minimum stream temperature rises for a 20 year return period heat event was estimated to be in the region of 3 °C. Additional riparian vegetation is not able to fully mitigate the expected temperature rise caused by climate change, but can reduce maximum, mean and minimum stream temperatures by 1 to 2° C. Removal of existing vegetation amplifies stream temperature increases. Maximum stream temperatures could increase by more than 4 °C even in yearly heat events.


PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242682
Author(s):  
Jennifer B. Rogers ◽  
Eric D. Stein ◽  
Marcus W. Beck ◽  
Richard F. Ambrose

Distributions of riparian species will likely shift due to climate change induced alterations in temperature and rainfall patterns, which alter stream habitat. Spatial forecasting of suitable habitat in projected climatic conditions will inform management interventions that support wildlife. Challenges in developing forecasts include the need to consider the large number of riparian species that might respond differently to changing conditions and the need to evaluate the many different characteristics of streamflow and stream temperature that drive species-specific habitat suitability. In particular, in dynamic environments like streams, the short-term temporal resolution of species occurrence and streamflow need to be considered to identify the types of conditions that support various species. To address these challenges, we cluster species based on habitat characteristics to select habitat representatives and we evaluate regional changes in habitat suitability using short-term, temporally explicit metrics that describe the streamflow and stream temperature regime. We use stream-specific environmental predictors rather than climatic variables. Unlike other studies, the stream-specific environmental predictors are generated from the time that species were observed in a particular reach, in addition to long term trends, to evaluate habitat preferences. With species occurrence data from local monitoring surveys and streamflow and stream temperature modeled from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) climate projections, we predict change in habitat suitability at the end-of-century. The relative importance of hydrology and stream temperature varied by cluster. High altitudinal, cold water species’ distributions contracted, while lower elevation, warm water species distributions expanded. Modeling with short-term temporally explicit environmental metrics did produce different end-of-century projections than using long-term averages for some of the representative species. These findings can help wildlife managers prioritize conservation efforts, manage streamflow, initiate monitoring of species in vulnerable clusters, and address stressors, such as passage barriers, in areas projected to be suitable in future climate conditions.


Fact Sheet ◽  
2012 ◽  
Author(s):  
John F. Walker ◽  
Randall J. Hunt ◽  
Lauren E. Hay ◽  
Steven L. Markstrom

Author(s):  
Jana S. Stewart ◽  
Stephen M. Westenbroek ◽  
Matthew G. Mitro ◽  
John D. Lyons ◽  
Leah E. Kammel ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document