Hourly Water Temperature Research Articles

Condensate loss estimation and transient solar-to-vapor conversion efficiency for effective performance evaluation of the inclined solar still

Previously, freshwater yields of the solar still were quantified only based on the actual distillate recovery, not considering condensate losses by any means. Likewise, solar-to-vapor conversion efficiencies of the solar still were conventionally considered and evaluated as one-off -rigid values- based on the latent heat of the average water temperature. In most cases, these approaches do not give a comprehensive performance details of the solar still. Thus, we suggest two considerations for effective performance evaluation of the inclined solar still. The first consideration is theoretical estimation of the condensate loss due to the condensate collection channel slope, while the other is the use of a transient method to evaluate the solar-to-vapor conversion efficiency. We demonstrated, geometrically, that the condensate loss on the inclined solar still can be significant—hence the need to consider it alongside the overall yield. We formulated a model to estimate the condensate loss and validated the model by comparing an estimated condensate loss with experimental loss. Similarly, we demonstrated a transient approach to evaluate the solar-to-vapor conversion efficiency by using the latent heat of the hourly water temperature. Accordingly, the optimum hourly efficiency of the investigated solar still prototype was 161.4%, with a daily average of 113.4% versus 108.4% from the conventional method. Overall, no study on the solar still had previously accounted for condensate losses by any means whatsoever, making our current study a reference and a pioneer in this concept and suggesting an advancement in the approach to report the performance productivity of the solar still.•Condensate loss on the inclined solar still due condensate collection channel slope was estimated geometrically and demonstrated to be significant.•Solar-to-vapor conversion efficiency was evaluated using an hourly transient approach.

Modelling dry-weather temperature profiles in urban stormwater management ponds

One of the unintended consequences of urban stormwater quality management wet ponds is the thermal enrichment of the shallow pond water during the summer months. The outflow from thermally enriched ponds can degrade the cold and cool water aquatic habitat in urban streams. An accurate model of the pond temperature profile is needed to assess the pond effluent thermal load. However, most models developed for this purpose are process-based and not simple to use, requiring a lengthy monitoring dataset to calibrate. This paper introduces a new design/assessment tool to predict the hourly water temperatures in these ponds at different depths during the summer season dry-weather warming periods and the diurnal cycles. We compiled monitoring data from five ponds in the Greater Toronto Area from 2013 − 2016 to evaluate the ponds' thermal impact on the receiving cold water streams. Using these datasets, we developed a new equation that allows for separating the active upper portion and stable lower portion of the pond. This ensures the focus is on the active upper part, where the majority of the heat transfer within the pond occurs and exhibits diurnal temperature fluctuations. We also used machine-learning tools to develop accurate equations for the bottom temperature and surface temperature, as well as, key equation parameters that characterize the thermal profiles. The developed thermal profile equation allows for the simple determination of other key thermal metrics such as average temperature, energy stored, thermocline location, which may be used as inputs to model wet weather flow conditions and pond outflow temperature. The results show that the proposed machine-learning model is acceptably accurate and capable, according to the low mean absolute percentage error (MAPE) and coefficient of determination (R2) values of 5% and 0.965, respectively, for temperature prediction for all depths. This work provides a building block for the overall objective to develop a new, easy to use, wet weather explicit equation for predicting the outlet temperature from stormwater management wet ponds since it establishes the initial thermal condition before the storm hits.

Genetic-Algorithm-Optimized Sequential Model for Water Temperature Prediction

Advances in establishing real-time river water quality monitoring networks combined with novel artificial intelligence techniques for more accurate forecasting is at the forefront of urban water management. The preservation and improvement of the quality of our impaired urban streams are at the core of the global challenge of ensuring water sustainability. This work adopted a genetic-algorithm (GA)-optimized long short-term memory (LSTM) technique to predict river water temperature (WT) as a key indicator of the health state of the aquatic habitat, where its modeling is crucial for effective urban water quality management. To our knowledge, this is the first attempt to adopt a GA-LSTM to predict the WT in urban rivers. In recent research trends, large volumes of real-time water quality data, including water temperature, conductivity, pH, and turbidity, are constantly being collected. Specifically, in the field of water quality management, this provides countless opportunities for understanding water quality impairment and forecasting, and to develop models for aquatic habitat assessment purposes. The main objective of this research was to develop a reliable and simple urban river water temperature forecasting tool using advanced machine learning methods that can be used in conjunction with a real-time network of water quality monitoring stations for proactive water quality management. We proposed a hybrid time series regression model for WT forecasting. This hybrid approach was applied to solve problems regarding the time window size and architectural factors (number of units) of the LSTM network. We have chosen an hourly water temperature record collected over 5 years as the input. Furthermore, to check its robustness, a recurrent neural network (RNN) was also tested as a benchmark model and the performances were compared. The experimental results revealed that the hybrid model of the GA-LSTM network outperformed the RNN and the basic problem of determining the optimal time window and number of units of the memory cell was solved. This research concluded that the GA-LSTM can be used as an advanced deep learning technique for time series analysis.

Relationships of water temperature and aquatic macroinvertebrate community structure with non-native riparian plant densities in the southern Cape, South Africa

Non-native vegetation in the riparian zone impacts on water temperatures, flow patterns, degree of shading, channel modification, and changes to natural sediment loads. Freshwater ecosystems in the Garden Route Initiative planning domain are of particular conservation value, because of the rich Gondwanaland relict aquatic macroinvertebrate fauna found in the rivers there, which are vulnerable to thermal changes. Data were collected during 2013 and 2014 at 19 sites on seven river systems between George and Knysna in the southern Cape, South Africa. These included 12 months of hourly water temperatures at all sites, and quantitative sampling of aquatic macroinvertebrates at ten sites. Each site was characterised in terms of water quality (pH, conductivity and turbidity) and general characteristics, including impacts such as density of non-native riparian trees. At the family level, aquatic macroinvertebrate communities showed variation between sites and seasons. Differences were more pronounced on the basis of natural land cover type (fynbos versus indigenous forest) than densities of non-native invasive riparian vegetation. Conservation of these river systems will depend on maintaining a mosaic of natural vegetation types.

Thermal Stratification and Its Impacts on Water Quality in Shahe Reservoir, Liyang, China

Based on the one-year hourly water temperature profiles and the associated environmental drivers during the past eight years in Shahe Reservoir, Jiangsu Province, China from 2009 to 2016, the factors underlying the seasonal variation of thermal stratification and water quality response were investigated. It was shown that the thermal stratification was a typical subtropical one-cycle mixing model, lasting from May to September. The thermal stratification appeared and disappeared when the surface water temperature was 21 ℃ in the late spring and 19 ℃ in the middle of autumn. The difference between the water temperature at the epilimnion and hypolimnion increased with increasing solar radiation. When the air temperature was above 30 ℃, the stability of the thermal stratification increased. Heavy storms reduced the temperature of the surface water and weakened the temperature stratification of the column above a 5 m depth but had limited impact on the stratification of the hypolimnion deeper than 5 m. The thermal stratification greatly impacted the water quality of the lake. Hypoxia in the bottom water occurred by thermal stratification, leading to increased NH4+-N. The concentrations of dissolved oxygen, total phosphorus, and suspended solids in the hypolimnion increased after the disappearance of thermal stratification. Our results indicated that the thermal stratification was mainly controlled by solar radiation and the thermal stratification favored the growth of cyanobacteria and led to the release of nutrients from the sediment, threatening the water quality. Attention should be paid to thermal stratification to prevent algal blooms and related water quality deterioration.

Thermal variations of water in the Nam Song stream/Mekong River: II. Experimental data and theoretical predictions

The goals of this study were to use the Nam Song River as a case study for parameters determination and a comparison between the measured data and the mathematical model developed in the first paper of this study. The kinematic wave equation [especially Eq. 16a in Ben-Asher et al. (Sustain Water Resour Manag, 2016. doi: 10.1007/s40899-016-0044-9 )] was expanded to a Taylor series that was used to determine several system parameters including the thermal time constant, the steady state solution, and the daily thermal cycle. Water temperature measured and calculated by the model varied from minimum of 23–24 °C at night to maximum of 27–29 °C at midday. From March 16 to March 25 2004, stream and air temperature were monitored at a point located 4 km downstream from the Nam Song Dam. The average hourly water temperature and its standard deviation were extracted from a family of daily sinusoidal curves. Monitoring downstream data were similar to results assumed by the theoretical model. The effect of water discharge rate on its temperature and on the changing energy input during daytime hours was considered. The analysis indicated that the only controllable system variable is the water flow velocity (V). It can be optimized through a controlled release of water from the dam. The mathematical analysis also identified and quantified the parameters which govern the water environment. The theory as well as the experimental data indicated that for the conditions studied, an increase in water discharge at the dam prevents an increase in water temperature downstream and thus helps to keep the fisheries and domestic water quality of the river in a healthier condition.

New optimized model for water temperature calculation of river-water source heat pump and its application in simulation of energy consumption

The energy consumption calculation plays an important role in the analysis of project economic and social benefits. In order to calculate energy consumption accurately, this research presents a water temperature of condenser inlet calculation model of river-water source heat pump unit. The feasibility and calculation error of the model had been analyzed. Additionally, the new water temperature calculation model had been validated via an engineering case. The results showed that the hourly water temperature in 24 h could be replaced by daily average water temperature due to little change of the daily water temperature change. In this case, the calculation error could be less than 5%. It is found that despite water temperature has many influenced factors, there is a remarkable relationship between the daily average water temperature and daily average outdoor dry bulb temperature by data analysis (R2 ≈ 0.9). The influence of river sampling location on water temperature calculation of condenser inlet could be ignored due to slight temperature changes (within 0.15 °C). The method proposed in this paper met the engineering accuracy and provided a very effective method for the engineering calculation of energy consumption of water chilling unit.

Accuracy of Hourly Water Temperatures in Rivers Calculated from Air Temperatures

Water temperature is a critical variable for water quality control and management. The primary objective of this paper was to develop and compare simple methods to estimate hourly water temperatures in rivers. The wave function (WF) model, originally used to calculate hourly air temperature, was modified and applied to eight Alabama rivers. The results show significant improvement by using the modified WF model instead of direct linear and non-linear (polynomial and logistic) regression models with time lags (4–5 h). The average Nash–Sutcliffe coefficient (NS) used to evaluate model accuracy for the eight rivers improved from 0.71 for the linear model to 0.89 for the modified WF model with NS for most rivers exceeding 0.90. A lumped modified WF model was also developed by combining water temperature data for all eight rivers and can be applied for rivers in Alabama when no observed water temperatures are available to develop a site-specific WF model. The procedure to develop a modified WF model can be applied to other regions.

Relationship between water temperature predictability and aquatic macroinvertebrate assemblages in two South African streams

Variable seasonal stream temperatures are a critical factor in maintaining aquatic invertebrate community patterns. We investigated whether the degree of predictability in a stream's water temperature profile provides insights into the structure and functional predictability of macroinvertebrate communities. Quarterly macroinvertebrate sampling over 11 months at five paired sites along the longitudinal axes of the Keurbooms River, Western Cape, and the Kowie/Bloukrans River, Eastern Cape, was undertaken in conjunction with collection of hourly water temperatures. Macroinvertebrate taxonomic turnover across seasons was higher for sites having lower water temperature predictability values than for sites with higher predictability, while temporal partitioning was greater at sites with greater temperature variability. Macroinvertebrate taxa responded in a predictable manner to changes in their environment. Specialist taxa preferred sites with greater temperature variability, and generalist taxa those with less temperature variability. Water temperature is an important abiotic driver of stream ecosystems, and should be expressed in terms of predictability metrics, as mean values do not adequately measure the components of water temperature that are important for biotic communities. Water temperature predictability provided an indication of the structure, functional predictability and seasonal turnover in macroinvertebrate communities. These findings have implications for streams experiencing temperature modifications due to the onset of climate change.

Intra-annual thermal patterns in the main rivers of the Sabie Catchment, Mpumalanga, South Africa

Water temperatures serve as indices of catchment condition, being a function of a multitude of variables acting as both drivers and buffers, at different temporal and spatial scales. Data loggers were used to record time series of hourly water temperatures within the Sabie, Sand and Marite Rivers of the Sabie catchment, Mpumalanga, South Africa. Two years of hourly water temperatures were scaled up to provide daily statistics of water temperatures, which provided information on intra-annual thermal variability as well as how this changed along the longitudinal axis of the Sabie River. In general, mean and maximum water temperatures, and thermal variability, increased with downstream distance in the Sabie River. Water temperatures in the two main tributaries of the Sabie River, viz. the Marite and Sand Rivers, displayed higher maxima and lower minima than corresponding sites in the Sabie River. Further research on the role of hyporheic water and the contribution of tributaries is proposed, together with additional long-term collection of water temperature time series. Key Words: Water temperatures, Sabie River, Intra-annual variability WaterSA Vol.30(4) 2004: 445-452

04/02898 Parametric study of a shallow solar-pond underthe batch mode of heat extraction: Aboul-Enein, S. et al. Applied Energy, 2004, 78, (2), 159–177

In this study, a theoretical model which is validated experimentally is used to predict the performance of a shallow solar pond in Tehran. The theoretical and experimental results show good agreement. The maximum hourly water temperature of the shallow solar pond is found to lag behind the maximum hourly ambient temperature and solar radiation by 1–2 and 3.5 h, respectively.The maximum monthly daily-average water temperature follows the trend of the monthly daily-average solar radiation but leads the monthly daily-average ambient temperature in one month. The shallow solar pond, with 10-cm water depth, cannot be used as a thermal source in winter but can be used for many thermal applications in summer. With 5-cm water depth, the shallow solar pond can be used as a thermal source for low heat applications in most of the winter but can be used, even for moderate applications, where high temperature up to 95°C is obtained in summer. Using a reflector makes the 10-cm depth shallow solar pond useful for low heat applications and the 5-cm depth useful for moderate heat applications in most of the winter. Using a double cover top glazing is found to have no effect on improving the system performance.

Temporal variability in the impact of river regulation on thermal regime and some biological implications

SUMMARY Ten years of hourly water temperature data for three river sites in south‐west England were used to investigate the longer‐term thermal effects of river regulation. The impact of reservoir impoundment on downstream invertebrate and trout development were simulated using daily mean temperature data in conjunction with published biological models. The main effects of regulation on water temperature were to increase the mean value, eliminate freezing conditions, depress summer maxima, delay the annual cycle and reduce diel fluctuation. These impacts persisted over a distance of at least 5km below the dam but declined downstream, especially for seasonal and diurnal variations. Simulations suggested that regulation is likely to have had a greater impact on the development of brown trout (Salmo trutta) than on the development of one Ephemeroptera and four Plecoptera species. Trout fry were predicted to emerge up to 57 days earlier, and to weigh up to 67% more by the end of the year following swim‐up, in the regulated compared with the unregulated river. Marked inter‐annual contrasts in the physical and biological consequences of impoundment were evident, indicating that long‐term studies are required to define properly the effects of river regulation.

Field Obserbations of Frazil Ice Formation and Water Temprature in Rivers during Winter

Frazil ice is an ice crystal formed in turbulent water. Its production is closely related to the ice cover formation in rivers and gives severe trouble for water intakes during winter. Field observations of frazil ice formation and water temerature were performed in Yubetsu and Niuppu river in Hokkaidou to investigate conditions for frazil ice production in rivers. From these observations it is concluded that massive production could occur when the daily air temperature is less than -7.5°C, and suppercooling of water is an indication of frazil ice initiation. A variation of hourly water temperature is simulated favorblly by a simple model using air temeperature as an input.

ERRORS RELATED TO RANDOM STREAM TEMPERATURE DATA COLLECTION IN UPPER MISSISSIPPI RIVER WATERSHED1

ABSTRACT: Records of hourly water temperatures for two streams in the Upper Mississippi River basin were used to find the error between instantaneous measurements of stream water temperatures and true daily averages. The instantaneous summer water temperature measurements were assumed to be collected during daylight hours, and measurement times were selected randomly. The absolute error at the 95 percent confidence level of randomly collected stream water temperatures was less than 0.9°C for a 1 to 5m deep large river, but as large as 3.6°C for a 0.3 to lm deep small stream. Temperature readings of morning samples were usually below daily average values, and afternoon readings were usually above. Daily mean water temperatures were obtained with less than 0.23°C standard deviation from true daily averages if the daily maximum and minimum water temperatures were averaged. Sample results were obtained for the open water (summer) season only, since diurnal water temperature fluctuations in ice covered streams are usually negligible.

Experimental study in a shallow solar pond

In this study, a theoretical model which is validated experimentally is used to predict the performance of a shallow solar pond in Tehran. The theoretical and experimental results show good agreement. The maximum hourly water temperature of the shallow solar pond is found to lag the maximum hourly ambient temperature and solar radiation by 1–2 and 3.5 h, respectively. The maximum monthly daily-average water temperature follows the trend of the monthly daily-average solar radiation but leads the monthly daily-average ambient temperature in one month. The shallow solar pond with 10 cm water depth cannot be used as a thermal source in winter-time but can be used for many thermal applications in summer-time. With 5 cm water depth, the shallow solar pond can be used as a thermal source for low heat applications in most of the winter-time but can be used even for moderate applications where high temperatures up to 95°C are obtained in summer-time. Using a reflector makes the 10-cm-deep shallow solar pond suitable for use in low heat applications and the 5-cm-deep pond suitable to be used for moderate heat applications in most of the winter-time. Using a double cover top glazing is found to have no effect on improving the system's performance.

Study on shallow solar pond applications at Tehran

In this study, a theoretical model which is validated experimentally is used to predict the performance of a shallow solar pond in Tehran. The theoretical and experimental results show good agreement. The maximum hourly water temperature of the shallow solar pond is found to lag behind the maximum hourly ambient temperature and solar radiation by 1–2 and 3.5 h, respectively. The maximum monthly daily-average water temperature follows the trend of the monthly daily-average solar radiation but leads the monthly daily-average ambient temperature in one month. The shallow solar pond, with 10-cm water depth, cannot be used as a thermal source in winter but can be used for many thermal applications in summer. With 5-cm water depth, the shallow solar pond can be used as a thermal source for low heat applications in most of the winter but can be used, even for moderate applications, where high temperature up to 95°C is obtained in summer. Using a reflector makes the 10-cm depth shallow solar pond useful for low heat applications and the 5-cm depth useful for moderate heat applications in most of the winter. Using a double cover top glazing is found to have no effect on improving the system performance.

Factors Influencing the Seasonal and Daily Patterns of Alewife (Alosa pseudoharengus) Migration in a Rhode Island River

Continuous time series records of numbers of fish ascending a Denil-type fishway on the Annaquatucket River, North Kingstown, R.I., were obtained with a Smith-Root electronic fish counter during 1971 and 1972 spawning migrations. Seasonal trends in numbers of fish counted per day were unimodal and showed similar time patterns in both years. Water temperatures delimited the seasonal migration period. Short-term fluctuations in fish movement showed a significant zero-lag positive correlation with fluctuations in water temperature and a significant positive correlation with fluctuations in volume outflow when lagged 2 days behind outflow. A 10–14-day cycle appeared in fish migration data. Light intensity determined when alewife (Alosa pseudoharengus) movement would occur during a 24-h period, whereas water temperature controlled the pattern of movement exhibited during daylight hours. Fish responded to hourly water temperatures on the basis of their value relative to a changing baseline temperature.