Water Temperature Observations Research Articles

An adaptive ensemble Kalman filter for assimilation of multi-sensor, multi-modal water temperature observations into hydrodynamic model of shallow rivers

There is lack of knowledge in assimilation of multi-sensor, multi-modal water temperature observations into hydrodynamic models of shallow rivers, specifically, (a) how does accuracy of shallow river model improve after assimilation of in-situ and remotely sensed temperature observations, and (b) how can data from disparate sensors and sources be assimilated into the prediction model without significant increase in computational burden. Multi-sensor, multi-modal observations used in this study are obtained from in-situ monitoring devices in the river with limited spatial coverage but dense temporal resolution, and from Landsat-7 satellite that has better spatial coverage but limited temporal coverage. Use of remotely-sensed observations from satellites poses the challenge that the physical region represented by satellite data does not directly correspond with the physical domain of the river simulated in hydrodynamic models. Satellites detects the skin water temperature, whereas numerical models estimate the bulk temperature in the surface layer that may be multiple meters in thickness. Furthermore, for rivers narrower than the resolution of satellite data, the temperature of each cell represents the weighted average temperature of land and water. These factors introduce biases into the updated numerical model, thereby impeding appropriate management of temperature, water quality, and aquatic ecology. We implemented an efficient ensemble Kalman filter method using Latin-hypercube sampling to assimilate multi-sensor water temperature observations into the hydrodynamic model of the Lower Klamath River located in northern California. Assimilation of remote sensing data from Landsat-7 improved the model prediction for the entire river. The average spatial error was reduced from 2.59 °C to 0.66 °C (i.e., 75% improvement). In-situ data assimilation reduced the error at the observation location, however, error in the water temperature predicted by the updated model reverted in less than two days to the same level as that of an un-updated model. On the other hand, it is not computationally efficient to assimilate all of the available data into the model as they become available. In order to overcome these challenges, in-situ data were adaptively assimilated into the model whenever the error exceeded a maximum allowable error. Adaptive assimilation of in-situ data for the Lower Klamath river application occurred one to three times per day, and reduced the average daily error up to 58% compared to assimilation of in-situ data only once each day.

Characteristics of reservoir water temperatures in high and cold areas of the Upper Yellow River

Several reservoirs have been built in the high and cold areas of the Yellow River. This study analyzed the annual and seasonal distributions and variation characteristics of the water temperatures of reservoirs in different reaches based on water temperature observations. The results show that (1) the temperature of the water released from the reservoirs is less than 2 °C and is 2–4 °C lower than the natural temperature in the research area in the spring. Reservoirs in this area freeze in the winter, the water temperature structures of the reservoirs exhibit thermal stratification with inversion profiles, and the inversion profiles are greater than 50 m thick. The reservoir water is mixed to 4 °C and then becomes stratified in mid-April. Similarly, the stratified conditions turn to mixed conditions in November. (2) The operating conditions of the reservoirs influence the water temperature distributions in the reservoirs and the water temperatures of the downstream river channels. (3) The temperature of the water released from the reservoirs is significantly lower than the natural water temperature in the spring, which affects the spawning of downstream fish. (4) A three-dimensional water temperature simulation model was created, and the simulation results show that stratified intake can reduce the impacts of low water temperatures.

Relative information from thermal infrared imagery via unoccupied aerial vehicle informs simulations and spatially-distributed assessments of stream temperature

Stream temperature is a measure of water quality that reflects the balance of atmospheric heat exchange at the air-water interface and gains or losses of water along a stream reach. In urban areas, stormwater sewers deliver water with varying magnitude and temperature to streams at variable timescales. Understanding the impacts of stormwater through space and time is therefore difficult to do with conventional approaches like in situ sensors. To study the impacts of stormwater on creek water temperatures, we combined in situ water temperature observations with thermal infrared (TIR) imagery collected via unoccupied aerial vehicle (UAV). Imagery was collected in May, June, and July of 2017. As ongoing work with UAV-based TIR suggests that this imagery is prone to poor accuracy, we focused on creating several data products beyond absolute water temperatures that can be used to assess temporal and spatial water temperature variations. In particular, TIR data products were used to extract the length of the observed stormwater plume as well as the width of the creek cross-section impacted by stormwater. From these values, we conclude that relatively narrow stormwater plumes affecting a small fraction of creek width can alter creek water temperatures for considerable distances downstream. We also applied TIR data to constrain results of a deterministic stream temperature model (HFLUX 3.0) that simulates the physical processes affecting stream heat exchanges. Stormwater plume lengths obtained from TIR imagery were used to refine spatially-distributed simulations, demonstrating that relative temperature information obtained from UAV imagery can provide useful calibration targets for stream temperature models. Overall, our work demonstrates the added value of UAV datasets for understanding urban stream temperatures, calibrating water quality models, and for modeling and monitoring of the impact of spatially explicit hydrologic processes on stream temperature.

A numerical analysis of the summertime Pearl River plume from 1999 to 2010: Dispersal patterns and intraseasonal variability

Abstract A three-dimensional unstructured-grid Finite Volume Community Ocean Model was applied to investigate the principal dispersal patterns and intraseasonal variability of the Pearl River plume in summer (June–August) during 1999–2010. The favorable forcing conditions and underlying dynamics for the formation of plume patterns were also explored. The model was validated against a suite of water level, salinity and temperature observations collected during the simulation periods. The simulated results agree well with the observed data, indicating that the model reasonably reproduces the main hydrodynamic processes occurring in the Pearl River estuary. Using Self-Organizing Maps, we extracted eight typical dispersal patterns of the Pearl River plume from the multiyear simulated daily surface salinity fields and estimated the occurrence frequency of each pattern. The eight plume patterns were further categorized into five types based on the morphologies and extension distances of each pattern, namely, west alongshore spreading, fettered spreading, offshore bulge spreading, bidirectional spreading and east offshore spreading; these five types account for 26.3%, 9.8%, 11.5%, 29.1% and 23.3% of the total occurrence frequency, respectively. The pattern that is characterized by bidirectional spreading with a strong eastward extension has the largest occurrence frequency among the eight patterns. Through an analysis of the best matching units derived from Self-Organizing Maps and the corresponding river discharge and wind conditions, we find that both wind and river discharge can significantly affect the Pearl River plume patterns. The plume orientation is mainly modulated by the wind, while the plume area and eastward extension distance are mainly affected by the river discharge. Generally, the favorable forcing conditions and underlying dynamics are different for each plume pattern, and various combinations of river discharge and wind can generate different dynamics to form different plume patterns. The climatological surface salinity field in summer shows a bidirectional structure with the plume extending westward attaching to the coast and eastward detaching from the coast. The areas and eastward extension distances of the Pearl River plume gradually decrease from June to August, affected by the intraseasonal changes in river discharge and wind. The statistical results of the daily plume patterns for June–August show that east offshore spreading, bidirectional spreading and west alongshore spreading are the primary types occurring in June, July and August, respectively. Furthermore, the occurrence frequencies of the west alongshore spreading and offshore bulge spreading increase, while the occurrence frequency of the east offshore spreading decreases from June to August.

Modeling the impacts of climate change on the thermal and oxygen dynamics of Lake Volta

Abstract Climatic changes influence the thermal and oxygen dynamics of a lake and thus its ecological functioning. The impacts of climatic changes on tropical lakes are so far poorly studied and the extent of the effects is therefore uncertain, most investigations describing only potential effects. In this study, we applied the one-dimensional lake ecosystem model GOTM-ERGOM to quantify the effects of climate change on thermal stratification, oxygen dynamics, and primary production in meso-oligotrophic Lake Volta. GOTM-ERGOM was calibrated and validated using two years of observed data. The validated model was used to evaluate a series of future climate change scenarios. The model simulations showed good agreement with observed water temperature, dissolved oxygen and chlorophyll-a and indicated intensified stratification and reduced oxygen levels in the productive water layers of the lake. However, the longer-lasting stratification (prolonged stability) did not translate into permanent stratification. A relatively small (1 m) upward shift of thermocline depth resulted in an 8%–12% volume loss of the oxygen-rich upper mixed layer, which may be significant for the fisheries of the lake as it diminishes the size of suitable fish habitats. Light limitation of primary production renders the lake somewhat resilient to intensive algae blooms, as traceable in both the present and in the future climate scenarios. In the long term, the ongoing climate change may affect riparian communities that depend on the lake's fisheries for their livelihood. In consequence, future lake management strategies for implementation need to account for the impacts of future climate change.

Hydrodynamics of the Po River‐Delta‐Sea System

AbstractIn this study we investigated the hydrodynamics and the interaction between riverine and marine waters in the Po River‐Delta‐Sea (RDS) system (Italy). Through the application of an unstructured 3D numerical model to a domain comprising the Po river branches, seven coastal lagoons and the shelf sea, many of the hydrodispersive phenomena evolving from the interaction of the different water bodies of the RDS system were described. The model was successfully calibrated and validated for water levels, fluxes at the inlets and at the river branches, and water temperature and salinity observations. The use of such a comprehensive approach allows the characterization of the general hydrodynamics of all the components of the Po RDS system, of the water exchange between different water bodies as well as the Po river discharge distribution among all branches. The analysis of calculated coastal current patterns in the prodelta of two different years and during a flood event confirms that the Po River is the main driver of the baroclinic coastal sea circulation. However, when strong winds occur (Sirocco and Bora), the surficial circulation of the shelf area is significantly modified. Generally, the lagoons of the Po RDS system can be considered hydrodynamically active since their tidal prisms represent a relevant fraction of each lagoon's volume. The natural consequence is that the lagoons show an active flushing with water renewal times in the order of few days. The hydrodynamics is mainly forced by the tide and is locally enhanced by riverine inputs and wind. Where freshwater inputs are significant, they are responsible of the lagoons salinity patterns that show high spatial gradients (not all the lagoons are well mixed) and temporal variability. The variability of the freshwater discharges and the complex morphology of the Po RDS allows the presence of both marine and riverine environments.

Ocean‐Induced Melt Triggers Glacier Retreat in Northwest Greenland

AbstractIn recent decades, tidewater glaciers in Northwest Greenland contributed significantly to sea level rise but exhibited a complex spatial pattern of retreat. Here we use novel observations of bathymetry and water temperature from NASA's Ocean Melting Greenland mission to quantify the role of warm, salty Atlantic Water in controlling the evolution of 37 glaciers. Modeled ocean‐induced undercutting of calving margins compared with ice advection and ice front retreat observed by satellites from 1985 to 2015 indicate that 35 glaciers retreated when cumulative anomalies in ocean‐induced undercutting rose above the range of seasonal variability of calving‐front positions, while two glaciers standing on shallow sills and colder water did not retreat. Deviations in the observed timing of retreat are explained by residual uncertainties in bathymetry, inefficient mixing of waters in shallow fjords, and the presence of small floating sections. Overall, warmer ocean temperature triggered the retreat, but calving processes dominate ablation (71%).

Estimating river accommodation capacity for organic pollutants in data-scarce areas

Globally, water quality degradation severely threatens the security of water resources. Understanding a river’s capacity to accommodate pollutants (or water environmental capacity: WEC) can help efficiently protect rivers. However, the requirement for comprehensive ground-observed hydrological and water quality data in previous methods makes it difficult to estimate WEC in areas with limited ground observations. This paper proposes a new framework for WEC estimation in data-scarce areas based on remotely sensed skin water temperature and limited ground observations. Two new models were developed to calculate the two critical parameters for WEC estimation: water temperature, and integrated pollutant degradation coefficients (k). Images of ASTER Surface Kinetic Temperature (AST_08) 90 m grid product were used to retrieve water temperatures. The above results were subsequently used to calculate a river’s capacity to accommodate pollutants, or WEC, in agriculturally dominated areas. The use of remote sensing techniques enables the methods to be applied over large spatial scales and to areas with limited ground observations. The application and testing of the framework in four rivers, including two Chinese rivers (the Huai and the Wei Rivers) and two Australian rivers (the Ovens and the Gwydir Rivers), suggest that the models performed well to calculate the real-time water temperature and the coefficient k based on limited ground-observations. Uncertainty analysis on water temperature calculated from remotely sensed land surface temperature and ground-observed meteorological air temperature suggests that remotely sensed water temperature had high concurrence with ground observations (RMSE = 3.08 °C with R2 = 0.88), while the sparse-spatially distributed meteorological stations reduced the accuracy in estimating water temperature (RMSE = 4.39 °C with R2 = 0.91). We found that the coefficient (k) increased with water temperature over different seasons in an exponential form but in a logarithmical form with streamflow velocity. Comparison with previous research and other models with abundant data revealed the practicability and effectiveness of our models, which can be easily applied to rivers with insufficient ground observations across the globe.

Evaluation of ten methods for estimating evaporation in a small high-elevation lake on the Tibetan Plateau

To quantify lake evaporation and its variations in time, ten methods for estimating evaporation at a temporal resolution of 10 days over a small high-elevation lake in the Nam Co lake basin of the Tibetan Plateau (TP) were evaluated by using eddy covariance (EC) observation-based reference datasets. After examination of the consistency of the parameters used in the different methods, the ranking of the methods under different conditions are shown to be inconsistent. The Bowen ratios derived from meteorological data and EC observations are consistent, and it supports a ranking of energy-budget-based methods (including the Bowen ratio energy budget, Penman, Priestley-Taylor, Brutsaert-Stricker and DeBruin-Keijman methods) as the best when heat storage in the water can be estimated accurately. The elevation-dependent psychometric constant can explain the differences between the Priestley-Taylor and DeBruin-Keijman methods. The Dalton-type methods (Dalton and Ryan-Harleman methods) and radiation-based method (Jensen-Haise) all improve significantly after parameter optimization, with better performance by the former than the latter. The deBruin method yields the largest error due to the poor relationship between evaporation and the drying power of the air. The good performance of the Makkink method, with no significant differences before and after optimization, indicates the importance of solar radiation and air temperature in estimation of lake evaporation. The Makkink method was used for long-term evaporation estimation due to lack of water temperature observations in lakes on the TP. Lastly, long-term evaporation during the open-water period (April 6 to November 15 from 1979 to 2015) were obtained; the mean bias was only 6%. A decreasing-increasing trend in lake evaporation with a turning point in 2004 was noted, and this trend corresponds to the published decreasing-increasing trend in reference evapotranspiration on the Tibetan Plateau and can be explained by variations in related meteorological variables.

Observation of Surface Water Temperature and Wave Height along the Coast of Pohang using Wave Gliders

ABSTRACT Ko, S. H.; Hyeon, J. W.; Lee, S. J, and Lee, J. H., 2018. Observation of Surface Water Temperature and Wave Height at the Coast of Pohang using Wave Glider.. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1211–1215. Coconut Creek (Florida), ISSN 0749-0208. Wave Gliders were launched to observe the surface water temperature and wave height at Hwajin-ri and Josa-ri on the coast of Pohang for the 11 days from March 24th to April 3rd. Wave Gliders SV2 and SV3 were operated within a radius of 100 m at two sites at depths of about 30~40 m. Both vehicles were equipped with a weather sensor, wave height sensor, and camera. Additionally, a conductivity sensor was installed in the SV2. During the observation period, the average surface water temperature and significant wave height were 13.0°C and 0.7 m, respectively. The differences in the surface water temper...

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

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.

Global lake response to the recent warming hiatus

Understanding temporal variability in lake warming rates over decadal scales is important for understanding observed change in aquatic systems. We analyzed a global dataset of lake surface water temperature observations (1985−2009) to examine how lake temperatures responded to a recent global air temperature warming hiatus (1998−2012). Prior to the hiatus (1985−1998), surface water temperatures significantly increased at an average rate of 0.532 °C decade−1 (±0.214). In contrast, water temperatures did not change significantly during the hiatus (average rate −0.087 °C decade−1 ±0.223). Overall, 83% of lakes in our dataset (129 of 155) had faster warming rates during the pre-hiatus period than during the hiatus period. These results demonstrate that lakes have exhibited decadal-scale variability in warming rates coherent with global air temperatures and represent an independent line of evidence for the recent warming hiatus. Our analyses provide evidence that lakes are sentinels of broader climatological processes and indicate that warming rates based on datasets where a large proportion of observations were collected during the hiatus period may underestimate longer-term trends.

Autocalibration of a one-dimensional hydrodynamic-ecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake

Abstract. Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook autocalibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimizing the root-mean-square error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash–Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10 000 simulation iterations. The “optimal” temperature calibration produced a RMSE of 0.54 ∘C, Nr value of 0.99, and r value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 and 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L−1, the Nr value was 0.75, and the r value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events from 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L−1 during summer of 2009–2011. The RMSE was 2.07 mg L−1, Nr value 0.62, and r value of 0.81, based on the available data set of 738 days. The autocalibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimization than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Thermal Regime of A Deep Temperate Lake and Its Response to Climate Change: Lake Kuttara, Japan

A deep temperate lake, Lake Kuttara, Hokkaido, Japan (148 m deep at maximum) was completely ice-covered every winter in the 20th century. However, ice-free conditions of the lake over winter occurred three times in the 21st century, which is probably due to global warming. In order to understand how thermal regime of the lake responds to climate change, a change in lake mean water temperature from the heat storage change was calculated by integrating observed water temperature over water depths and by numerical calculation of heat budget components based on hydrometeorological data. As a result, a temporal variation of lake mean water temperature from the heat budget calculation was very reasonable to that from the observed water temperature (determination coefficient R2 = 0.969). The lowest lake mean temperature for non-freeze was then evaluated at −1.87 °C, referring to the zero level at 6.80 °C. The 1978–2017 data at a meteorological station near Kuttara indicated that there are significant (less than 5% level) long-term trends for air temperature (+0.024 °C/year) and wind speed (−0.010 m/s/year). In order to evaluate the effects of climate change on freeze-up patterns, a sensitivity analysis was carried out for the calculated lake mean water temperature. It is noted that, after two decades, the lake could be ice-free once per every two years.

Thermal response of Moroccan lakes to climatic warming: first results

Water temperature plays a primary role in controlling a wide range of physical, geochemical and ecological processes in lakes, with considerable influences on lake water quality and ecosystem functioning. In this paper, we report on the ability of the one-dimensional lake model to simulate the water temperature of Moroccan lakes, i.e., Sidi Boughaba and Sidi Ali lakes, over a 35 yrs period from 1979 to 2014, affected by climate change and based on a freshwater lake model (FLake). During the study periods, two variables are studied, the epilimnion and metalimnion temperatures. The result analysis shows that epilimnion temperatures increased, while metalimnion temperatures decreased. Additionally, we calculate significant air temperature, wind speed and water temperature variation and illustrate, using a sequential t test analysis of regime shifts (STARS) based on the Rodionov method, a substantial increase in annually averaged of all variables, in response to an abrupt shift in the climate. Schmidt stability showed a significant increase for Sidi Ali Lake and near 0 for Sidi Boughaba Lake. On the other hand, the sensitivity analysis (i.e., one-at-a-time (OAT) method) of the atmospheric variable is discussed. The results show good agreement with water temperature observations that suggests that the predictive model can be used to obtain a first-order estimation of water temperature in Moroccan lakes. Hence, it is possible to apply this model in other Moroccan lakes to simulate the behavior of temperature and to investigate the potential future warming of the water column in lakes, affected by climate change.

Theoretical analysis of the effects of irrigation rate and paddy water depth on water and leaf temperatures in a paddy field continuously irrigated with running water

Water management techniques such as continuous irrigation with running water (CIRW) have been used by Japanese farmers to control the thermal environment for rice cropping. In this study, to optimize this method to control the thermal environment in paddy fields, theoretical equations for predicting water and vegetation temperatures in a paddy field were obtained. First, the equations to calculate water and vegetation temperatures in a paddy field were obtained by solving the heat balance equations of the paddy water and vegetation, taking into account the effect of horizontal heat convection driven by irrigation. The equations were validated by comparisons with observed water temperatures in a conventional paddy field under CIRW. The calculated changes in water temperatures over time and distance showed good agreement with observed values, with a root mean square error of 0.39°C. This result indicated that the equations satisfactorily expressed the features of paddy water temperature under CIRW. Next, these equations were used to determine the effects of irrigation rate, paddy water depth and wind speed on water and rice plant temperatures. The following results were obtained. 1) The area cooled by CIRW was positively related to irrigation rate and negatively related to water depth. 2) Low water depths were preferable for application of CIRW during the nighttime. 3) Slower wind speeds and latent heat flux from vegetation strengthened the effects of water management on vegetation temperature. The proposed equations and analyses represent the common features of the effect of irrigation on water and vegetation temperatures in a paddy field, and provide quantitative information about the effects of water management techniques on the thermal environment for rice cropping.

Air-sea heat flux control on the Yellow Sea Cold Water Mass intensity and implications for its prediction

The Yellow Sea Cold Water Mass (YSCWM), which occurs during summer in the central Yellow Sea, plays an important role in the hydrodynamic field, nutrient cycle and biological species. Based on water temperature observations during the summer from 1978 to 1998 in the western Yellow Sea, five specific YSCWM years were identified, including two strong years (1984 and 1985), two weak years (1989 and 1995) and one normal year (1992). Using a three-dimensional hydrodynamic model, the YSCWM formation processes in these five years were simulated and compared with observations. In general, the YSCWM began forming in spring, matured in summer and gradually disappeared in autumn of every year. The 8°C isotherm was used to indicate the YSCWM boundary. The modelled YSCWM areas in the two strong years were approximately two times larger than those in the two weak years. Based on the simulations in the weak year of 1995, ten numerical experiments were performed to quantify the key factors influencing the YSCWM intensity by changing the initial water condition in the previous autumn, air-sea heat flux, wind, evaporation, precipitation and sea level pressure to those in the strong year of 1984, respectively. The results showed that the air-sea heat flux was the dominant factor influencing the YSCWM intensity, which contributed about 80% of the differences of the YSCWM average water temperature at a depth of 50m. In addition, the air-sea heat flux in the previous winter had a determining effect, contributing more than 50% of the differences between the strong and weak YSCWM years. Finally, a simple formula for predicting the YSCWM intensity was established by using the key influencing factors, i.e., the sea surface temperature before the cooling season and the air-sea heat flux during the cooling season from the previous December to the current February. With this formula, instead of a complicated numerical model, we were able to roughly predict the YSCWM intensity for the following summer by using the data available online in winter.

Design of real-time and long-term hydrologic and water quality wetland monitoring stations in South Florida, USA

Hydrologic regimes in tropical and subtropical regions (e.g. hurricanes, tropical storms, and droughts) impact biogeochemical processes in created and restored wetlands with variability of wet/dry seasons and extreme weather events. Our South Florida Wetland Monitoring Network (SFWMN) with three real-time hydrologic, water quality, and meteorological field stations was established by the Everglades Wetland Research Park of Florida Gulf Coast University in the subtropical Southwest Florida, USA, beginning in 2012. The stations include a restored freshwater marsh (RFM) and adjacent meteorological field station; a restored brackish water marsh (RBM); and a created freshwater treatment wetland system and adjacent meterological station (CFTW). Continuous observations of water depth, temperature, salinity, and pH for the period of January 2012 to January 2016 indicate significant differences among the restored freshwater marsh, the restored brackish marsh, and the created freshwater treatment wetlands for water temperature and pH for wet and dry seasons. The brackish wetland salinity fluctuated between 26.16 (in the dry season) to 1.03ppt (in the wet season).The real-time dataset allowed up-to-date information of the frequency and duration of severe weather events illustrating, for example, that 70% of the 2012 annual rainfall (1129mm) occurring in July and August with a 75.4mm precipitation during one event—tropical storm Isaac on August 26–28, 2012. This storm led to a water stage peak in the brackish wetland due to excessive watershed runoff, not tidal surges, and salinity decreased from 22.3 to 5.5ppt.The coefficient of variation (CV) for water depth and water quality from all wetland monitoring stations exhibited similar variations during all seasons, except when the salinity for the brackish marsh (RBM) had the highest CV values (1.02) in the wet season. Principal component analysis (PCA) at each station identified the variance in water depth and water quality parameters as due to seasonal changes of precipitation in distinct wet and dry seasons. The data from these monitoring stations are also used for research by scholars and students as well as for teaching a better understanding of wetlands dynamics and function in the classroom. As a whole, these stations are being used to bring awareness about the fragile and unique hydrological conditions of wetlands in subtropical Southwest Florida, especially for long-term conditions related to sea level changes and more frequent tropical storms.

Assessment of Allowable Thermal Load for a River Reservoir Subject to Multi-Source Thermal Discharge from Operating and Designed Beloyarsk NPP Units (South Ural, Russian Federation)

This study develops a quantitative approach to the establishment of a maximum allowable thermal discharge into a freshwater body (the Beloyarsk Reservoir) incorporated in the once-through cooling technology at the Beloyarsk nuclear power plant (NPP) (South Urals, Russian Federation). The study is based on a 3-D hydrodynamic model, embracing water circulation, heat transfer, and ice-cover formation in the Beloyarsk Reservoir. The model is driven by atmospheric forcing, river runoff, and the discharge/intake of NPP cooling water. It was used to simulate the horizontal and vertical distribution of water temperature under the effect of the operation of existing (number 3) and anticipated (numbers 4 and 5) nuclear power units. The model is validated by the comparison of the computation results with observed water temperature distribution and ice-cover configuration obtained with remote sensing techniques. The model was also used to predict the future evolution of water temperature after the launching of two new power units, which, having a common cooling system, may affect each other. It was shown that the first of the new units, no. 4, will not dramatically affect the existing thermal conditions in the reservoir, while launching one more unit, no. 5, will apparently result in overheating of the reservoir water in response to the greater volume of cooling-water discharge from the two power units. Because of a specific configuration of the recirculation flow, the reservoir may fail to cope with the dissipation of the generated heat, leading to a steady (uncontrolled) rise of water temperature in the inlet channel to one of the power units. This will reduce the potential of NPP, using the once-through cooling technology, and will most likely have an adverse effect on the survival of aquatic organisms in the Beloyarsk Reservoir. Therefore, some other environment-saving technologies must be developed for removing surplus heat from the unit no. 5 of the Beloyarsk NPP.

The role of riparian vegetation density, channel orientation and water velocity in determining river temperature dynamics

A simulation experiment was used to understand the importance of riparian vegetation density, channel orientation and flow velocity for stream energy budgets and river temperature dynamics. Water temperature and meteorological observations were obtained in addition to hemispherical photographs along a ∼1km reach of the Girnock Burn, a tributary of the Aberdeenshire Dee, Scotland. Data from nine hemispherical images (representing different uniform canopy density scenarios) were used to parameterise a deterministic net radiation model and simulate radiative fluxes. For each vegetation scenario, the effects of eight channel orientations were investigated by changing the position of north at 45° intervals in each hemispheric image. Simulated radiative fluxes and observed turbulent fluxes drove a high-resolution water temperature model of the reach. Simulations were performed under low and high water velocity scenarios. Both velocity scenarios yielded decreases in mean (≥1.6°C) and maximum (≥3.0°C) temperature as canopy density increased. Slow-flowing water resided longer within the reach, which enhanced heat accumulation and dissipation, and drove higher maximum and lower minimum temperatures. Intermediate levels of shade produced highly variable energy flux and water temperature dynamics depending on the channel orientation and thus the time of day when the channel was shaded. We demonstrate that in many reaches relatively sparse but strategically located vegetation could produce substantial reductions in maximum temperature and suggest that these criteria are used to inform future river management.