Downstream Stations Research Articles

A Physically‐Based Reverse‐Stage Routing Model Considering Lateral Flow for Establishing Normal Rating Curves at Ungauged Upstream River Sections

AbstractMany of the world‐rivers are often ungauged or poorly gauged due to inadequate streamflow monitoring networks. Even with the limited available monitoring stations, only a few of them monitor both stage and discharge data. But when there is a need for estimation of discharges at a gauging station, where only stage data is monitored, one may employ a reverse routing technique using the stage data monitored at a nearby downstream gauging station. This study develops a novel single‐parameter reverse‐stage routing (RSR) model based on the second‐order approximate water surface gradient governing equation to estimate stage and discharge at any scantily‐gauged upstream river section using the known stage information available at the downstream section. A novel criterion is also developed for checking the applicability of the RSR model. Reverse routing experiments, carried out by the RSR model using different hypothetical downstream stage hydrographs in a number of hypothetical trapezoidal and rectangular channel reaches to reproduce the benchmark upstream stage and discharge hydrographs, demonstrate the good performance of the RSR model with the Nash–Sutcliffe Efficiency >98%, absolute volume conservation error <1.5%, and an absolute error in peak ≤1%. Subsequently, the RSR model was tested for three real‐river case studies in India and Italy with good reproduction performances, and along with the development of the corresponding normal rating curves at the upstream river sections. The study results reveal that the parsimonious RSR model has good potential for solving reverse routing problems with stable numerical solutions for rivers under ungauged and scantily‐gauged scenarios.

Uncertainty assessment for three-dimensional hydrodynamic and fecal coliform modeling in the Danshuei River estuarine system: The influence of first-order parametric decay reaction

Modeling fecal contamination in water bodies is of importance for microbiological risk assessment and management. This study investigated the transport of fecal coliform (e.g., up to 2.1 × 106 CFU/100 ml at the Zhongshan Bridge due to the main point source from the Xinhai Bridge) in the Danshuei River estuarine system, Taiwan with the main focus on assessing model uncertainty due to three relevant parameters for the microbial decay process. First, a 3D hydrodynamic-fecal coliform model (i.e., SCHISM-FC) was developed and rigorously validated against the available data of water level, velocity, salinity, suspended sediment and fecal coliform measured in 2019. Subsequently, the variation ranges of decay reaction parameters were considered from several previous studies and properly determined using the Monte Carlo simulations. Our analysis showed that the constant ratio of solar radiation (α) as well as the settling velocity (vs) had the normally-distributed variations while the attachment fraction of fecal coliform bacteria (Fp) was best fitted by the Weibull distribution. The modeled fecal coliform concentrations near the upstream (or downstream) stations were less sensitive to those parameter variations (see the smallest width of confidence interval about 1660 CFU/100 ml at the Zhongzheng Bridge station) due to the dominant effects of inflow discharge (or tides). On the other hand, for the middle parts of Danshuei River where complicated hydrodynamic circulation and decay reaction occurred, the variations of parameters led to much larger uncertainty in modeled fecal coliform concentration (see a wider confidence interval about 117,000 CFU/100 ml at the Bailing Bridge station). Overall, more detailed information revealed in this study would be helpful while the environmental authority needs to develop a proper strategy for water quality assessment and management. Owing to the uncertain decay parameters, for instance, the modeled fecal coliform impacts at Bailing Bridge over the study period showed a 25 % difference between the lowest and highest concentrations at several moments. For the detection of pollution occurrence, the highest to lowest probabilities for a required fecal coliform concentration (e.g., 260,000 CFU/100 ml over the environmental regulation) at Bailing Bridge was possibly greater than three.

Simulation of Water Level and Flow of Catastrophic Flood Based on the CNN-LSTM Coupling Network

The occurrence of catastrophic floods will increase the uncertainty of hydrological forecasting at downstream hydrological stations. In order to solve the problems of the unclear propagation law of catastrophic floods in the middle and lower reaches of the Yangtze River and the inadaptability of traditional forecasting methods, this paper uses the M-K trend test method to analyze the annual average flow and annual average water level of the Yichang and Hankou stations. For conventional floods and catastrophic floods, Random Forest (RF), Convolutional Neural Network (CNN), Long Short-Term Memory Network (LSTM), and CNN-LSTM neural networks are used to simulate the water level/flow of Hankou station. The simulation results are analyzed by Nash–Sutcliffe Efficiency Coefficient (NSE), Kling–Gupta efficiency coefficient (KGE), Root Mean Square Error (RMSE), and Symmetric Mean Absolute Percentage Error (SMAPE). The results show that the annual average flow and annual average water level of Yichang station show a downward trend and the annual average water level of Hankou station shows an upward trend. By comparing the four indicators of NSE, KGE, RMSE, and SMAPE, the CNN-LSTM coupling model was determined to be the best fitting model, with NSE and KGE greater than 0.995 and RMSE and SMAPE less than 0.200. The proposed coupling model can provide technical support for flood control optimization, scheduling, emergency rescue, and scheduling impact analysis of the Three Gorges Power Station.

A behavioral perspective on workload control concepts: The influence of order release on operators’ reaction behavior

Most research on production planning and control (PPC) focuses on control structures, mathematical models, and algorithms, without explicitly considering human behavior. To consider a behavioral perspective of the PPC concept of workload control (WLC), we conduct a laboratory experiment. The study’s aim is to investigate the effects of changing workload norms, the influence of feedback information, and coworker queue length information on operators’ reaction behavior. To do so, we perform an assessment across two dimensions: operators’ (i) performance and (ii) arousal level. We contribute to the literature on endogenous processing times and highlight the importance of considering behavioral aspects when companies define an implementation strategy and when conducting WLC studies. Furthermore, given that production systems are operated by people, our results show that behavioral effects need to be considered in the specification of workload norms. Based on our results, we conclude that operators exhibit substantial heterogeneity in their reaction behavior, depending on their positioning in a flow shop (gateway station vs. downstream station).

Validation of Synthetic Design Hydrographs through 2D hydrodynamic modelling

The procedure for the determination of Synthetic Design Hydrographs (SDHs), proposed in previous works, is validated by comparing the peak discharges obtained by routing a long series of historical floods and the synthetic floods at different stations along a complex river system.At this aim, the 60 km long terminal stretch of the Dora Baltea river (Northern Italy) has been modelled according to fully 2D high resolution hydrodynamic approach. The fluvial branch is of considerable complexity due to a strong contraction induced by the presence of a narrow Roman bridge, which, during the most important flood events, causes the reactivation of a paleochannel and the flooding of a part of the city of Ivrea. The hydraulic model has been calibrated on the basis of the main historical floods. Then, all the historical floods over a period of more than 80 years (1939–2020) and the SDHs derived by the same series have been routed. Historical and synthetic peak discharges at two downstream stations have been then compared in probability plots. The results show that the peak discharge distributions derived by routing the historical floods and the SDHs compare well. This suggests that SDHs construction procedure is reliable and has statistical significance.

Analysis of spatial and temporal trend of hydro-climatic parameters in the Kilombero River Catchment, Tanzania

Inadequate knowledge on actual water availability, have raised social-economic conflicts that necessitate proper water management. This requires a better understanding of spatial–temporal trends of hydro-climatic variables as the main contributor to available water for use by sectors of economy. The study has analysed the trend of hydro-climatic variables viz. precipitation, temperature, evapotranspiration and river discharge. One downstream river gauge station was used for discharge data whereas a total of 9 daily observed and 29 grided satellite stations were used for climate data. Climate Hazards Group InfraRed Precipitation was used for precipitation data and Observational-Reanalysis Hybrid was used for Temperature data. Mann–Kendall Statistical test, Sen’s slope estimator and ArcMap Inverse Distance Weighted Interpolation functionality were employed for temporal, magnitude and spatial trend analysis respectively. Results confirmed that, spatially, there are three main climatic zones in the study area viz. Udzungwa escarpment, Kilombero valley and Mahenge escarpment. On temporal analysis, with exception of the declining potential evapotranspiration trend, all other variables are on increase. This is with catchment rates of 2.08 mm/year, 0.05 °C/year, 0.02 °C/year, 498.6 m3/s/year and − 2.27 mm/year for precipitation, Tmax, Tmin, river discharge and PET respectively. Furthermore, rainfalls start late by a month (November) while temperatures picks earlier by September and October for Tmax and Tmin respectively. Water availability matches farming season. However, it is recommended to improve water resources management practices to limit flow impairment as expansions in sectors of economy are expected. Furthermore, landuse change analysis is recommended to ascertain actual trend and hence future water uptake.

Application of Machine Learning Algorithms in Studying Water Quality in the Red River System

The Red River system plays an important role in the socio-economic development of the Northern of Vietnam. Therefore, regular monitoring and evaluation of water quality parameters in the Red River system are important in water resources management and protection. However, current monitoring methods are often quite expensive and time-consuming. To predict the downstream water quality, this study uses multiple machine learning algorithms to understand the correlation between environmental parameters measured at upstream and downstream stations of the Red River system. The environmental parameters that are chosen for this study include suspended sediment concentration (SSC), inorganic nitrogen content (total N), phosphorus content (total P), and dissolved silicon (DSi). The results show that machine learning algorithms can estimate the downstream DSi and sediment concentrations based on combining values of three upstream stations with relatively high efficiency (R2 equals 0.75 and 0.66, respectively). Meanwhile, these algorithms have limited performance in estimating total N and P content, due to the influence of many exogenous factors. The study introduces a new direction for applying machine learning algorithms in water quality research in the Red River system with the potential application in other river systems in Vietnam.

A multi-objective optimization model for the coordinated operation of hydropower and renewable energy

The rapid growth of wind and solar energy sources in recent years has brought challenges to power systems. One challenge is surging wind and solar electric generation, understanding how to consume such generation is important. Achieving the complementarity of hydropower and renewable energies such as wind and solar power by utilizing the flexible regulation performance of hydropower is helpful to provide firm power to help renewable energy consumption. However, the multi-energy complementary operation mode will change the traditional hydropower operation mode, causing challenges to the comprehensive utilization of hydropower. In this paper, a multi-objective optimal scheduling model is built by considering coordinated hydro-wind-solar system peak shaving and downstream navigation. First, the Gaussian mixture model is adopted to quantify the uncertainty of wind and solar power. Then, a hydro-wind-solar coordinated model was built to obtain the standard deviation of the residual load and the standard deviation of the downstream water level. Finally, the ε-constraint method is used to solve for the Pareto optimality. The results demonstrate the following: 1) The proposed model can effectively determine hydropower output schemes that can coordinate wind and solar power output to reconcile peak shaving and navigation; 2) The downstream hydropower stations’ reverse regulation of the upstream hydropower station is a positive factor in reconciling conflicts; and 3) Reasonable planning of wind power and solar power is helpful for hydro-wind solar power complement operation.

Geographic Information System-Based Analysis of Fish Diversity Trends of River Meenachil, Southern Western Ghats, Kerala.

In this study, the fish fauna of different geographical zones of Meenachil River was investigated using the spatial interpolation techniques of the Geographical Information System. The variations in fish diversity trends during the pre-monsoon, monsoon, and post-monsoon seasons from 2016 to 2020 along the longitudinal gradient of the Meenachil River were determined using the Kriging interpolation method and semivariograms. Sixty-seven fish species belonging to 15 orders, 29 families, and 46 genera were recorded from the river during the study period. Twenty-five were endemic to the Western Ghats, three were exclusive to Kerala, five were nearly threatened, and three were vulnerable. The midstream of the river recorded maximum diversity indices ranging from (H’) 2.608 to 3.171, reflecting the outcome of local river conservation efforts, and the downstream station with the lowest range (H’) 2.305 -2.643. Cluster analysis showed the spatial similarities in fish diversities between sampling stations. Deterioration in water quality downstream was reflected in the fluctuating levels of TDS (ppm) (21.300±116.828 to 365.000±116.828), Conductivity(µSmcm-1) (42.500±252.372 to 815.000±252.372), Salinity(ppt) (0.100±0.083 to 0.400±0.083) and dissolved oxygen levels(mgL-1) (2.900±0.876 to 5.600±0.876). The study highlights the necessity to broaden local conservation efforts and implement legal measures to protect the habitats and the native fish fauna of the tourism-dominated lower stretches of the Meenachil River. By integrating data in spatial maps, the geographic component added by GIS gives a clearer insight into the various data and efficiently supports global conservation measures, enhancing biodiversity protection.

IMPACT OF SUSPENDED SEDIMENT ON PAHANG RIVER DEVELOPMENT USING GEOGRAPHIC INFORMATION SYSTEM

The measurement of different characteristics of a stream, including integrated water resource management, is dependent on sediment transport mechanisms. On the Pahang River, studies explored the spatial interpolation pattern of suspended sediment (SS) and water resource management. Sedimentation issues in the Pahang River have a significant impact on water resource management in the Pahang River basin. Furthermore, it may have an impact on local water consumption, recreational activities, and other factors, causing the river to become shallow and finally flood. This study was conducted to determine the SS pattern in the Pahang River with the approach of the Geographic Information System (GIS) technique and its significant colour based on spatial analysis. In addition, this study also evaluates the factors and effects of sedimentation through water source management. Three sampling stations from the Department of Irrigation and Drainage (DID) for three years (2000, 2004 and 2008) were selected along the Pahang River, where the parameter measured was suspended sediment (ton/year). The results obtained showed that the Pahang River receives a high amount of SS each year, where the higher amount was at the upper station (Sg. Yap), with an amount of 1876575 ton/year (2000), 613850.1 ton/year (2004) and 3458097 ton/year where it may be affected by sediment re-suspension and runoff from two outlets. Meanwhile, the downstream station (Lubuk Paku) received the least amount of SS, while the midstream station (Temerloh) received the most. The transit's speed and current may have an impact. This study's findings are critical in river and water resource management, especially of water resources for domestic use, ecotourism, river biodiversity, and hydrology.

Spatial-temporal variations of stage-area hysteretic relationships in large heterogeneous lake–floodplain systems

The hysteretic relationship between the water level and the inundated area is one of the basic non-linear characteristics of lake hydrology. However, it is difficult to obtain this relationship accurately, especially for large floodplain lakes that exhibit time-varying boundaries with rapid water-level fluctuations. Taking the largest lake-floodplain system of the Yangtze River basin – Poyang Lake and its extremely productive wetland – as an example, we investigated the spatial–temporal variation of the stage-area hysteretic relationship in large heterogeneous lake-floodplain systems by adopting the Enhanced Spatial and Temporal Adaptive Reflection Fusion Model (ESTARFM) based on the observed water levels and reconstructed high spatial–temporal resolution inundation datasets using multi-source remote sensing data. The major results indicate that the inundation dynamics in the regions of the main lake and seasonal floodplain lakes are remarkably inconsistent. Concerning the inundation behavior of the river and lake-floodplain, a conceptual model was established to explain the formation mechanism of the counter-clockwise and clockwise stage-area hysteretic relationships in the Poyang lake–floodplain system. Further investigation revealed that seasonal lakes exist widely in floodplain settings and have a crucial impact on increasing the hysteresis of upstream stations and decreasing that of downstream stations. The magnitude and direction of the stage-area hysteretic relationships varied with time in a changingenvironment. This study extends the understanding of the complexity of hydrological behavior in large heterogeneous lake-floodplain systems, which is of vital importance for lake water resources and ecological management.

Assessment of Heavy Metal Content and Human Health Risk of Orogodo River, Delta State, Nigeria

The Orogodo River is a major source of water for drinking, cooking, bathing, fishing, washing and recreation for the resident community. Apparently, anthropogenic activities threaten the sustainability of this resource, hence, the need for environmental monitoring studies. This study was carried out to investigate heavy metal content and to assess human health risk of Orogodo River vis-a-vis its suitability for human consumption. Water samples were collected from four sampling stations established along the stretch of the river with the upstream station at Site 1, two midstream stations (Sites 2 and 3) and the downstream station being Site 4 and analyzed for seven heavy metals: iron (Fe), copper (Cu), manganese (Mn), chromium (Cr), nickel (Ni), zinc (Zn) and lead (Pb) concentrations using the atomic absorption spectrophotometer. The results obtained from the study showed that the mean values for Fe (2.77±0.00 mg/l) in Site 4, Ni (0.15±0.19 mg/l) in Site 2, Pb (0.05±0.02 mg/l) in Site 3, Mn (0.30±0.30 mg/l) in Site 3 and Cr (0.06±0.03) in Sites 2 and 3 exceeded the Nigerian Standard for Drinking Water Quality (NSDWQ) maximum permissible limits (Fe: 0.3 mg/l; Ni: 0.02 mg/l; Pb: 0.01 mg/l; Mn: 0.2 mg/l and Cr: 0.05 mg/l) for Nigerian freshwater and thus warranted health risk assessment. Health risk assessment for all sites indicated that with exemptions of Cr (1.33 in Sites 2 and 3 for children), other metals showed no potential health risk, but their cumulative effects as indicated by the hazard index (1.19 and 2.50 for adult and children in Site 2; 1.22 and 2.91 for adult and children in Site 3 and 1.36 for children in Site 4) could be of serious concern. This calls for caution for both adults and children exposed to the water through ingestion and the dire need for enforcement of water resource management regulations by the concerned authorities.

Integrating the flow regime and water quality effects into a niche-based metacommunity dynamics model for river ecosystems

Aquatic community dynamics are closely dominated by flow regime and water quality conditions, which are increasingly threatened by dam regulation, water diversion, and nutrition pollution. However, further understanding of the ecological impacts of flow regime and water quality conditions on aquatic multi-population dynamics has rarely been integrated into existing ecological models. To address this issue, a new niche-based metacommunity dynamics model (MDM) is proposed. The MDM aims to simulate the coevolution processes of multiple populations under changing abiotic environments, pioneeringly applied to the mid-lower Han River, China. The quantile regression method was used for the first time to derive ecological niches and competition coefficients of the MDM, which are demonstrated to be reasonable by comparing them with the empirical evidence. Simulation results show that the Nash efficiency coefficients for fish, zooplankton, zoobenthos, and macrophytes are more than 0.64, while the Pearson correlation coefficients for them are no less than 0.71. Overall, the MDM performs effectively in simulating metacommunity dynamics. For all river stations, the average contributions of biological interaction, flow regime effects, and water quality effects to multi-population dynamics are 64%, 21%, and 15%, respectively, suggesting that the population dynamics are dominated by biological interaction. For upstream stations, the fish population is 8%–22% more responsive to flow regime alteration than other populations, while other populations are 9%–26% more responsive to changes in water quality conditions than fish. For downstream stations, flow regime effects on each population account for less than 1% due to more stable hydrological conditions. The innovative contribution of this study lies in proposing a multi-population model to quantify the effects of flow regime and water quality on aquatic community dynamics by incorporating multiple indicators of water quantity, water quality, and biomass. This work has potential for the ecological restoration of rivers at the ecosystem level. This study also highlights the importance of considering threshold and tipping point issues when analyzing the “water quantity-water quality-aquatic ecology” nexus in future works.

A study on the forecast model of winter precipitation type in Liaocheng based on physical parameters

AbstractIn this study, 46 physical parameters are first calculated by using the hourly ground observational data of Liaocheng Airport station and the daily sounding data of Xingtai station and Zhangqiu station in the winters of 2016–2020. After the significance test of the correlation coefficients between the physical parameters and the precipitation types, six physical parameters that could be used in the operational weather forecast at Zhangqiu station and Xingtai station are selected by the methods of box‐plot and skill score based on the distribution characteristics of physical parameters under different precipitation types. Moreover, the judgment criteria for the winter precipitation forecast in Liaocheng are obtained by analyzing the indication effect and thresholds of each physical parameter in different precipitation types. In addition, a forecast model of winter precipitation type in Liaocheng is established by using the extended membership function transformation method with the sounding data from the nearest upstream and downstream stations. The verification with observations shows that the forecast accuracy is above 85% and the model performs quite well. We hope this study can provide a good reference for related operational forecasts in the areas without local sounding data or numerical forecast product receiving.

Multi-Array Design for Hydrokinetic Turbines in Hydropower Canals

The design of hydrokinetic plants in hydropower canals involves the choice of the array layout, rotor geometry, turbine spacing, and array spacing, and necessitates the control of the resultant backwater to avoid upstream flooding hazards. Several works in the literature have shown that array power optimization is feasible with small spacings between the arrays, disregarding the limitation in the power output induced by backwater upstream. In this study, a 1-D channel model with a Double Multiple Streamtube code and wake sub-models are integrated to predict an array layout that will maximize the array power. The outputs of the conducted sensitivity analysis confirm that this design enabled improved power conversion with closely spaced turbines and largely spaced arrays, thus allowing for a partial recovery of the total head variation for a new array deployed upstream. In addition to the quantitative assessment of the mechanical power converted, the tool enables depth control from the downstream undisturbed flow station to the backwater exhaustion far upstream, thereby increasing its flexibility. Furthermore, it overcomes the limitations of actuator disc models by considering rotor’s fluid dynamic losses. The results show that power output linearly scales for a limited number of arrays (≤5), whilst the variation in water depth variation follows a power law from the most downstream array towards upstream, regardless of the plant size. Finally, the maximum upstream inflow depth is demonstrated to become asymptotic for large multi-array plants under ideal conditions.

Effects of cascading reservoirs on streamflow and sediment load with machine learning reconstructed time series in the upper Yellow River basin

Large reservoirs are widely built along rivers for flood control, hydropower generation, water supply for industry and agricultural production, and recreation. Many large reservoirs/dams built to provide multiple functions for local people are strongly influenced by the downstream flow and sediment discharge in the upstream of the Yellow River, China. In this study, we assessed the changes in the river flow and sediment discharge in responses to the construction of cascade reservoirs/dams by using continuously hydrological time series observed at six stations during 1956–2018. The temporal change in the streamflow was insignificant, but the sediment load decreased dramatically due to the trapping effects of the cascade reservoirs. The change points were detected in 1969 and 1986, which were consistent with the timing of the construction of gigantic reservoirs. We then applied the abrupt changing points to divide the whole time series into a reference period (1956–1968) and two changing periods (1969–1986 and 1987–2018). The linear regression and three machine learning models were employed to reconstruct the natural streamflow and sediment load at the downstream station, before quantifying their responses to cascade reservoirs. The annual mean streamflow and sediment load decreased by 21% and 84%, respectively, after constructing the Longyangxia and Liujiaxia reservoirs. Cascade reservoirs contributed 85.39% and 94.91% to the decreases in the streamflow and sediment discharge, respectively. Hydrological regimes have been greatly altered by the 13 cascade reservoirs, with seasonal redistribution of the streamflow and flood peak reduction because their high trapping efficiencies exceed 95%. These findings indicate that large and medium sized reservoirs have drastically altered the streamflow and sediment load, thereby intensely influencing the fluvial processes in the upstream of the Yellow River.

Water Level Forecasting in Tidal Rivers during Typhoon Periods through Ensemble Empirical Mode Decomposition

In this study, a novel model that performs ensemble empirical mode decomposition (EEMD) and stepwise regression was developed to forecast the water level of a tidal river. Unlike more complex hydrological models, the main advantage of the proposed model is that the only required data are water level data. EEMD is used to decompose water level signals from a tidal river into several intrinsic mode functions (IMFs). These IMFs are then used to reconstruct the ocean and stream components that represent the tide and river flow, respectively. The forecasting model is obtained through stepwise regression on these components. The ocean component at a location 1 h ahead can be forecast using the observed ocean components at the downstream gauging stations, and the corresponding stream component can be forecast using the water stages at the upstream gauging stations. Summing these two forecasted components enables the forecasting of the water level at a location in the tidal river. The proposed model is conceptually simple and highly accurate. Water level data collected from gauging stations in the Tanshui River in Taiwan during typhoons were used to assess the feasibility of the proposed model. The water level forecasting model accurately and reliably predicted the water level at the Taipei Bridge gauging station.

Method for quantitatively assessing the impact of an inter-basin water transfer project on ecological environment-power generation in a water supply region

To tackle ever-changing global water problems, inter-basin water transfer (IBWT) projects provide water supply alternatives for water-scarce regions and create potential risks for water-supply regions. To analyze the multiple interrelated impacts of IBWT projects on supply regions, in this study, we establish a cascade multi-objective complementary optimal scheduling model and apply the model to the water supply regions of the west route of China’s South-North Water Transfer Project and the Dadu-Minjiang Water Transfer Project. With the goal of fully utilizing water resources to gain comprehensive benefits, we objectively and quantitatively evaluate the impacts of IBWT projects on the ecology and hydropower generation of water supply regions. To reduce the complexity of solving the model, the model is decomposed into a two-stage optimization model and is solved with particle swarm optimization and fuzzy optimization. The results show that: (1) The multi-objective model that simultaneously considers minimal ecological water shortage degree, maximal power generation, and the maximization of the annual minimum output is more conducive to the full utilization of water resources. (2) The factors affecting the ecological flow, the power generation and its structure in the water supply region, and the annual minimum output are different. (3) To deal with risks, the upstream power station in the water supply region is controlled to meet the ecological needs as the primary goal, and the downstream power station is mainly responsible for the task of compensating and adjusting the output gap during the dry season. This study can provide technical support for the demonstration and decision-making of IBWT projects, and it explores the ideas of water resource planning and management.

Influences of Urban Discharges and Urban Heat Effects on Stream Temperature

Urban areas with dark and impermeable surfaces are known to have a heating effect on air and still water compared to surrounding areas, called the urban heat island effect (UHI). UHI and stormwater discharges’ collective impact on stream temperature, especially regarding seasonal changes, is a less-studied field. In this study, the temperature effect of the urban village Aarslev on Stream Vindinge in Southern Denmark was examined. Loggers (ID A–L) were placed in Stream Vindinge in 2020–2021, measuring temperature (°C) and pressure (kPa). Outlets were analyzed with respect to origin: Direct stormwater outlets (rain ÷ basin), stormwater delayed by ponds (rain + basin), common overflow, and common sewage from WWTP. Data showed the stream temperature rise through Aarslev village in all months (except March) with 0.3–1.9 °C, most notably in the summer months. A one-way ANOVA confirmed that the upstream station A and downstream station K were significantly different (p-values < 0.001). No significant difference in temperatures between the different outlet types was found. An increase in stream temperature was observed in response to rain events, followed by a temperature decrease. This was assumed to be a “first heat flush”. This was speculated to mean less optimal conditions for trout and sensitive macroinvertebrates not because of heat shock, but rather to lower O2 concentrations and higher mineralization. River and lake temperatures are projected to increase, and this effect might become more pronounced. A decrease in stream temperature was observed after the village (station L). Therefore, it was concluded that the rise in temperature through the village was due to UHI.

Taxonomic and functional responses of macroinvertebrate communities to dam construction in a non-wadeable river

Damming and impoundment are among the main flow-related alterations in rivers worldwide. However, compared to the highland river sections where the impacts associated with dams have been largely studied, still scarce evidence is available in scientific literature for large, lowland rivers. In this study, the ecological effects of a hydropower dam in the Po River (Italy) on the taxonomic and functional responses of benthic macroinvertebrates were examined by comparing one station upstream of the dam with one downstream station over a six-year period. Weak and not significant differences were observed for taxon richness, abundance and community composition. By contrast, community-level proportion of macroinvertebrates associated with water velocity increased during medium and high flow condition and decreased during low flow condition in downstream stations. Such differences were also mirrored by the Flow-T index, that is a biomonitoring index recently developed to assess hydraulic conditions in rivers. Results of this study support the adoption of stressor-specific metrics in river biomonitoring.