River temperature research and practice: Recent challenges and emerging opportunities for managing thermal habitat conditions in stream ecosystems

Compare individual and combined bioretention systems on the reduction of thermal pollution from stormwater runoff

Urban surface temperatures are high in summertime, and thermal pollution caused by heat transfer from pavement to stormwater runoff is harmful to aquatic ecosystems. However, there is a lack of studies investigating the temperature change pattern during rainstorms and evaluating the effects of bioretention on dynamic characteristics of thermal pollution. Therefore, this study selected a 1.05 ha parking lot retrofitted with five individual bioretention cells in Beijing as the object to compare the temperature and volume of stormwater runoff before and after bioretention treatment. In the LID parking lot, the average EMT and EMXT (event maximum temperature) of runoff decreased by 2.28 °C and 4.18 °C, respectively, and the median percent thermal load reduction was 90.6%. Data analysis from 15 summer rainfall events showed that the sequence of factors affecting runoff EMT (event mean temperature) was average air temperature, max air temperature, max solar radiation, and rainfall peak 5-min intensity. Bioretention profoundly changed the thermal dynamic characteristics of stormwater runoff. Surface runoff temperatures generally showed a decreasing trend over time. The temperature change pattern of LID parking lot outflow was synchronized with that of the inflow and varied with different grades of precipitation. The probability of the peak temperature ahead of peak flow decreased from 80% to 53%, suggesting that 27% of the thermal first-flush effect of thermal pollution from the urban surface was alleviated by site-scale bioretention implementation. The site-scale bioretention combination had a lower effluent temperature and a higher thermal load reduction rate than single-scale solutions. These results fill the gap in research on the thermal pollution reduction process of bioretention. Furthermore, they can guide the optimization of bioretention design methods and strategies to protect urban water bodies from the stormwater runoff thermal pollution.

Effect of global climate change on the sustainability of cold-water fish habitat in the alpine region: A case study on the Gymnocypris eckloni in the source region of the Yellow River

Climate change at the global scale affects the watershed's hydrology and the river's hydrodynamic, water temperature (WT), and habitat conditions of organisms. This article proposes a quantitative assessment methodology framework for analyzing the impact of GCC on the cold-water fish habitat. This framework integrated GCC, downscaling, hydrological, hydrodynamic, water temperature, and habitat models and was applied to the source region of the Yellow River (SRYR), where there are Gymnocypris eckloni (G. eckloni) resource reduction problems. In this study, we developed a high-precision, loosely integrated hydrological, hydrodynamic, WT coupling model for SWAT-MIKE21 in the SRYR. The optimal latitude and longitude range (6° × 6°) covering the SRYR was established for downscaling, and future meteorological data under three GCC models was obtained. The main results present the discharge of spawning, and juvenile G. eckloni indicates an increasing trend from the radiation forcing low to high and from the near now to the future term. The WT increased (decreased) in April and June (May), with a maximum increase/decrease of 3.1°C (SSP370 in 2100)/1.4°C (SSP585 in 2050). The weighted useable area (WUA) demonstrated a trend of severe fluctuations in May, June, and October, and other months are equal to the base year. Total WUA (TWUA) displayed an increasing trend, with the maximum increase in spawning and juvenile period being 134.46% and 270.89%, respectively. Ultimately, the rise in confluence discharge and WT caused by GCC in the SRYR benefits spawning and juvenile G. eckloni. The results have guiding significance for the development of long-term and adaptive protection and restoration measures for G. eckloni, and provide a plan for predicting the impact of climate change on other organisms in river ecosystems in high-altitude cold regions.

Long-term patterns and changes of unglaciated High Arctic stream thermal regime

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

Spatial and Temporal Variability in Stream Thermal Regime Drivers for Three River Networks During the Summer Growing Season

Many cold-water dependent aquatic organisms are experiencing habitat and population declines from increasing water temperatures. Identifying mechanisms which drive local and regional stream thermal regimes facilitates restoration at ecologically relevant scales. Stream temperatures vary spatially and temporally both within and among river basins. We developed a modeling process to identify statistical relationships between drivers of stream temperature and covariates representing landscape, climate, and management-related processes. The modeling process was tested in 3 study areas of the Pacific Northwest USA during the growing season (May [start], August [warmest], September [end]). Across all months and study systems, covariates with the highest relative importance represented the physical landscape (elevation [1st], catchment area [3rd], main channel slope [5th]) and climate covariates (mean monthly air temperature [2nd] and discharge [4th]). Two management covariates (ground water use [6th] and riparian shade [7th]) also had high relative importance. Across the growing season (for all basins) local reach slope had high relative importance in May, but transitioned to a regional main channel slope covariate in August and September. This modeling process identified regionally similar and locally unique relationships among drivers of stream temperature. High relative importance of management-related covariates suggested potential restoration actions for each system.

Closing the gap between science and management of cold-water refuges in rivers and streams

Human activities and climate change threaten coldwater organisms in freshwater ecosystems by causing rivers and streams to warm, increasing the intensity and frequency of warm temperature events, and reducing thermal heterogeneity. Cold-water refuges are discrete patches of relatively cool water that are used by coldwater organisms for thermal relief and short-term survival. Globally, cohesive management approaches are needed that consider interlinked physical, biological, and social factors of cold-water refuges. We review current understanding of cold-water refuges, identify gaps between science and management, and evaluate policies aimed at protecting thermally sensitive species. Existing policies include designating cold-water habitats, restricting fishing during warm periods, and implementing threshold temperature standards or guidelines. However, these policies are rare and uncoordinated across spatial scales and often do not consider input from Indigenous peoples. We propose that cold-water refuges be managed as distinct operational landscape units, which provide a social and ecological context that is relevant at the watershed scale. These operational landscape units provide the foundation for an integrated framework that links science and management by (1) mapping and characterizing cold-water refuges to prioritize management and conservation actions, (2) leveraging existing and new policies, (3) improving coordination across jurisdictions, and (4) implementing adaptive management practices across scales. Our findings show that while there are many opportunities for scientific advancement, the current state of the sciences is sufficient to inform policy and management. Our proposed framework provides a path forward for managing and protecting cold-water refuges using existing and new policies to protect coldwater organisms in the face of global change.

Substantial warming of Central European mountain rivers under climate change

Water bodies around the world are currently warming with unprecedented rates since observations started, but warming occurs highly variable among ecoregions. So far, mountain rivers were expected to experience attenuated warming due to cold water input from snow or ice. However, air temperatures in mountain areas are increasing faster than the global average, and therefore warming effects are expected for cold riverine ecosystems. In decomposing multi-decadal water temperature data of two Central European mountain rivers with different discharge and water source regime, this work identified so far unreported (a) long-term warming trends (with river-size dependent rates between  +0.24 and  +0.44 °C decade^-1); but also (b) seasonal shifts with both rivers warming not only during summer, but also in winter months (i.e., up to  +0.52 °C decade^-1 in November); (c) significantly increasing minimum and maximum temperatures (e.g., temperatures in a larger river no longer reach freezing point since 1996 and maximum temperatures increased at rates between +0.4 and +0.7 °C decade^-1); and (d) an expanding of warm-water periods during recent decades in these ecosystems. Our results show a substantial warming effect of mountain rivers with significant month-specific warming rates not only during summer but also in winter, suggesting that mountain river phenology continues to change with ongoing atmospheric warming. Furthermore, this work demonstrates that apart from a general warming, also seasonal shifts, changes in extreme temperatures, and expanding warm periods will play a role for ecological components of mountain rivers and should be considered in climate change assessments and mitigation management.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10113-023-02037-y.

The diadromous watersheds-ocean continuum: Managing diadromous fish as a community for ecosystem resilience

Diadromous fishes play important ecological roles by delivering ecosystem services and making crucial connections along the watersheds-ocean continuum. However, it is difficult to fully understand the community-level impacts and cumulative benefits of diadromous fish migrations, as these species are most often considered individually or in small groups. Their interactions at a community level (e.g., interdependencies such as predation, co-migration, and habitat conditioning) and the connections between their ecosystem roles and functions (e.g., cumulative marine-derived nutrient contributions, impacts on stream geomorphology) are yet to be fully understood. Similarly, freshwater, estuarine, and marine ecosystems are often considered as independent parts, limiting understanding of the importance of connections across systems. We argue that not considering the ecosystem interdependence and importance of diadromous fish as a community currently hinders the implementation of the large-scale management required to increase ecosystem resilience and fish productivity across the full range of these species. We developed a conceptual model, the Diadromous Watersheds-Ocean Continuum (DWOC), that uses ecosystem services to promote a more holistic approach to the management of the diadromous community and encourages an integrated understanding of the ecosystem connections made by these species. DWOC provides a framework for discussions that can help identify research and management needs, discuss the trade-offs of different management options, and analyze what pressing questions impede the implementation of large-scale management solutions toward a more ecosystem-based management approach.

Forecasting Water Temperature in Cascade Reservoir Operation-Influenced River with Machine Learning Models

Water temperature (WT) is a critical control for various physical and biochemical processes in riverine systems. Although the prediction of river water temperature has been the subject of extensive research, very few studies have examined the relative importance of elements affecting WT and how to accurately estimate WT under the effects of cascaded dams. In this study, a series of potential influencing variables, such as air temperature, dew temperature, river discharge, day of year, wind speed and precipitation, were used to forecast daily river water temperature downstream of cascaded dams. First, the permutation importance of the influencing variables was ranked in six different machine learning models, including decision tree (DT), random forest (RF), gradient boosting (GB), adaptive boosting (AB), support vector regression (SVR) and multilayer perceptron neural network (MLPNN) models. The results showed that day of year (DOY) plays the most important role in each model for the prediction of WT, followed by flow and temperature, which are two commonly important factors in unregulated rivers. Then, combinations of the three most important inputs were used to develop the most parsimonious model based on the six machine learning models, where their performance was compared according to statistical metrics. The results demonstrated that GB3 and RF3 gave the most accurate forecasts for the training dataset and the test dataset, respectively. Overall, the results showed that the machine learning model could be effectively applied to predict river water temperature under the regulation of cascaded dams.

Integration of satellite image-derived temperature and water depth for assessing fish habitability in dam controlled flood plain wetland

The present study attempted to investigate the changes in temperature conducive to fish habitability during the summer months in a hydrologically modified wetland following damming over a river. Satellite image-driven temperature and depth data calibrated with field data were used to analyse fish habitability and the presence of thermally optimum habitable zones in some fishes, such as labeo rohita, cirrhinus mrigala, tilapia fish, small shrimp, and catfish. The study was conducted both at the water's surface and at the optimum depth of survival. It is very obvious from the analysis that a larger part of the wetland has become an area that destroyed aquatic habitat during the post-dam period, and existing wetlands have suffered significant shallowing of water depth. This has resulted in a shrinking of the thermally optimum area of fish survival in relation to surface water temperature (from 100.09 to 74.24 km² before the dam to 93.97 to 0 km² after the dam) and an improvement in the optimum habitable condition in the comfortable depth niche of survival. In the post-dam period, it increased from 75.49 to 99.76%. Since the damming effect causes a 30.53 to 100% depletion of the optimum depth niche, improving the thermal environment has no effect on fish habitability. More water must be released from dams for restoration. Image-driven depth and temperature data calibrated with field information has been successfully applied in data sparse conditions, and it is further recommended in future work.

Thermal renaturation of rivers in the post-industrial age - An example of the Przemsza River basin (Poland)

This article concerns temperature, which is one of the most important physical properties of surface waters. During the period of climate warming, tendencies of increasing river temperature have been repeatedly identified in the literature. This article discusses the lowering of the river temperature, a phenomenon rarely considered, which is occurring in a heavily industrialised area in the southern part of Poland (Upper Silesia Region), undergoing deep restructuring. The main aim of the study is to analyse and evaluate the unique Przemsza River basin, which differs from other river basins in terms of the thermal regime of its rivers and its tendencies for change. These changes are presented through the long period of 1961-2015, and additionally in two sub-periods, 1961-1994 and 1995-2015, differing with respect to the degree of the organisation of wastewater management. This was possible to demonstrate thanks to the high density of hydrological stations within a small area, which is rare, especially over such a long period. This work, therefore, fills the research gap on changes in the thermal regime of rivers caused by water management. Its results differ from those presented so far in the literature and expand the knowledge of this subject. In the years under consideration (1961-2015), the air temperature increased by 0.03 °C·per year^-1 on average. It was found that the temperature of rivers (or their sections) decreased by as much as -0.8 °C·year^-1. The greatest drops in temperature occurred in the winter season and amounted to a maximum of -0.12 °C·season^-1. In the first part of the analysed period (1961-1994), unnaturally high river temperatures caused by water management factors were recorded. In turn, in the years 1995-2015 there was a decrease in temperature caused by various technical operations carried out in the catchments, including the construction of modern sewage treatment plants, as well as limitation of the introduction of water into rivers from closed hard coal mines. This phenomenon is referred to as thermal renaturation. Maintaining positive changes in the thermal regime requires, inter alia, a further reduction in the amount of pollutants discharged into rivers by water discharges from mine drainage.