Station Discharge Research Articles

Shallow groundwater and river baseflow: Interconnection evidences and integrated water management strategies. Case study in the upper Descoberto watershed, Federal District, Brazil

Aquifer discharge in the form of baseflow is intimate related to river replenishment. In this manner, it is reasonable that water management practices consider an integrated approach including surface and groundwater. Effective regulatory measures, however, require the understanding of the mechanisms and the degree of such interconnection. In the Federal District, capital of Brazil, research focused on this theme are scarce, despite the relevance addressed by some authors. In the present study, shallow groundwater of Upper Descoberto Watershed was monitored for four years (2019–2023). The area responds to 60% of local population public water supply and has been facing land use conflicts and water crisis. Data were collected with 2-h resolution and compared to fluviometric stations discharge and water height records. Graphical analyses demonstrate that river baseflow is highly dependent on shallow aquifer discharge. The decrease of the phreatic aquifer water level results, in a short period, in streams flow reduction. This result is contrasting to the former agreement that considered the connection would take more time to be established. Statistical correlation coefficients are as high as 0.920 for the entire monitoring range and 0.998 for the dry season. The results evidence that soils have important reservoir and regulatory functions, even though they might not be relevant for high water demand activities. In this way, water grant process should account for correlated components, such as territory planning, estimation of total extraction by sensitive areas and properly characterization of insignificant uses, alternative and independent water sources evaluation, and definition of environmental constraints. The mitigation practices of hydric problems must include the implementation of artificial recharge devices, use of sustainable farming methods and control of rainwater overland flow. It is desirable the maintenance and enlargement of the current monitoring net so that former patterns that culminated in water crisis can be early identified and mitigated.

Above and below-ground bacterial communities shift in seagrass beds with warmer temperatures

Current rates of ocean warming are predicted to exacerbate ongoing declines in seagrass populations. Above-ground responses of seagrass to increasing temperatures have been studied from a direct physiological perspective while indirect effects, including changes to microbially-mediated below-ground processes, remain poorly understood. To test potential effects of increased temperature on seagrass growth and associated microbial communities, we sampled seagrass beds experiencing ambient and elevated water temperatures at Lake Macquarie, Australia. Sites with warmer water were associated with a plume from a power station discharge channel with temperatures analogous to conditions predicted by 2100 under current rates of ocean warming (+3°C). The microbial community composition in both sediments and leaf tissues varied significantly between warm and ambient water temperatures with higher relative abundances of putative sulphate-reducing bacteria such as Desulfocapsaceae, Desulfobulbaceae and Desulfosarcinaceae in sedimentary communities in warm water. Above-ground biomass and seagrass growth rates were greater at warm sites while below-ground biomass and detrital decomposition rates showed no difference suggesting potential buffering of temperature effects below-ground. These findings suggest a 3°C rise in temperate regions is unlikely to induce mortality in seagrass however, it may shift microbial communities towards more homogenous structure and composition.

Glass eel migration in an urbanized catchment: an integral bottleneck assessment using mark-recapture

Diadromous fish such as the European eel (Anguilla anguilla L.) are hampered by a high density of barriers in estuaries and freshwater systems. Modified and fragmented waterbodies lack tidal flows, and habitat may be less accessible and underutilized compared to free-flowing rivers and estuaries. With rising sea levels and increased occurrence of droughts, the number of barriers may further increase, implying that the need to study migration in such areas may even become more urgent worldwide. To study glass eel migration and behaviour in such highly modified water systems, a mark-recapture study was carried out in the North Sea Canal (NSC) basin, which drains into the North Sea via a large sluice complex. In total, eight uniquely tagged groups (3,797 glass eels) were released near the sluice complex, and 11 groups (2,663 glass eels) were released at inland barriers upstream over a 28 km long stretch in the NSC in spring 2018. The sluice complex attracted 10.3 million glass eel and did not block or delay their immigration. The large and diurnally intensively used coastal ship locks and allowings some saltwater intrusion, efficiently facilitated glass eel migration. Once in the NSC, water outlets from adjacent polders attracted glass eels relative proportional to the discharge of pumping stations. In the NSC, average migration speeds of 0.7 km/day (max. 1.8 km/day) were measured, and this increased with higher temperatures. Redistribution of glass eel from accumulations at inland barriers to other outlet locations was observed in both upstream and downstream directions in the NSC. Passage success and residence time (‘delays’ of 4.1–13.7 days) varied between the different inland barriers. Most of the glass eel, however, appears to settle in the easily accessible habitats within the brackish NSC catchment. This study combined an integral assessment of successive bottlenecks in a modified inland water system.

Study of Shellfish Growing Area During Normal Harvesting Periods and Following Wastewater Overflows in an Urban Estuary With Complex Hydrography

Viral testing combined with hydrographic studies is considered standard good practice in determining microbiological impacts on shellfish growing areas following wastewater overflows. In this study, norovirus genogroup I and II, indicators of viral contamination (F-RNA bacteriophage genogroup II (F-RNA GII), crAssphage, pepper mild mottle virus) and Escherichia coli were monitored during periods of normal harvesting and following overflows in two commercial shellfish growing areas in Otago Harbour (Aotearoa New Zealand). Dye tracing, drogue tracking and analysis of particle tracking modelling were also undertaken to assess the dispersion, dilution and time of travel of wastewater discharged from a pump station discharge that impacts the growing areas. Norovirus was not detected in any of the 218 shellfish samples tested. PMMoV and crAssphage were more prevalent than F-RNA GII as determined by RT-qPCR. The dye study indicated long residence time of the waters (≥5 days) in the embayment impacted by the discharge. No relationships were found between the concentrations of viral indicators or E. coli and wastewater dilution, distance between the discharge and the growing areas or time since the last overflow. For the three spills studied (≤327 m3), there was little evidence of microbiological impact on the growing areas. This was likely associated with a deep shipping channel that enhances water flushing in the harbour and reduces contaminant transport to the growing areas. We recommend flexibility in the approach for closure/reopening growing areas impacted by spills, particularly for small duration/volume spills and when norovirus is not present in the community.

Demonstrating the application of batch anaerobic digestion recirculating slurry inoculation of food waste engineering from a microbiological perspective

In this study, the food waste recycled slurry was mixed inoculated with the discharge of the biogas station, and the effect of inoculation ratio and circulating batch on the performance of the system was studied for 2 t/d food waste anaerobic digestion to demonstrate engineering applications. The results showed that a proper proportion of the digestion slurry cycle can promote dehydrogenase activity in the system, and the activity of methanogens and the content of coenzyme F420 gradually increase with the increase of the cycle batch. Under the optimal mixing ratio (50% slurry volume ratio, R50), the time for anaerobic digestion of food waste to reach 90% of the total cumulative methane output can be shortened to 13 days, and the cumulative biogas output is as high as 16.96 L. The value of the kinetic constant k increases with the number of refluxes, and finally reaches 0.114 d−1. The microbial community gradually succeeds in an appropriate direction. The VFA and alkalinity content in the system together affects the composition of Firmicutes, Bacteroides, and Chloroflexus in the system. These results will help increase the utilization rate of biogas slurry, reduce its external discharge, and improve the performance of batch anaerobic digestion engineering applications.

Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard

Abstract. The Arctic is undergoing increased warming compared to the global mean, which has major implications for freshwater runoff into the oceans from seasonal snow and glaciers. Here, we present high-resolution (2.5 km) simulations of glacier mass balance, runoff, and snow conditions on Svalbard from 1991–2022, one of the fastest warming regions in the world. The simulations are created using the CryoGrid community model forced by Copernicus Arctic Regional ReAnalysis (CARRA) (1991–2021) and AROME-ARCTIC forecasts (2016–2022). Updates to the water percolation and runoff schemes are implemented in the CryoGrid model for the simulations. In situ observations available for Svalbard, including automatic weather station data, stake measurements, and discharge observations, are used to carefully evaluate the quality of the simulations and model forcing. We find a slightly negative climatic mass balance (CMB) over the simulation period of −0.08 mw.e.yr-1 but with no statistically significant trend. The most negative annual CMB is found for Nordenskiöldland (−0.73 mw.e.yr-1), with a significant negative trend of −0.27 mw.e. per decade for the region. Although there is no trend in the annual CMB, we do find a significant increasing trend in the runoff from glaciers of 0.14 mw.e. per decade. The average runoff was found to be 0.8 mw.e.yr-1. We also find a significant negative trend in the refreezing of −0.13 mw.e. per decade. Using AROME-ARCTIC forcing, we find that 2021/22 has the most negative CMB and highest runoff over the 1991–2022 simulation period investigated in this study. We find the simulated climatic mass balance and runoff using CARRA and AROME-ARCTIC forcing are similar and differ by only 0.1 mw.e.yr-1 in climatic mass balance and by 0.2 mw.e.yr-1 in glacier runoff when averaged over all of Svalbard. There is, however, a clear difference over Nordenskiöldland, where AROME-ARCTIC simulates significantly higher mass balance and significantly lower runoff. This indicates that AROME-ARCTIC may provide similar high-quality predictions of the total mass balance of Svalbard as CARRA, but regional uncertainties should be taken into consideration. The simulations produced for this study are made publicly available at a daily and monthly resolution, and these high-resolution simulations may be re-used in a wide range of applications including studies on glacial runoff, ocean currents, and ecosystems.

Application of multilayer perceptron (MLP) method for streamflow forecasting (case study: Upper Citarum River, Indonesia)

Flood forecasting is a critical component of flood early warning. The discharge that occurs is one of the parameters that can be used as a reference for predicting flooding. Various discharge forecasting models based on physically based models or data-driven models have been developed. One of the flood forecasting methods that can be considered for forecasting discharge on watersheds with limited physical data is the Artificial Neural Network (ANN). Furthermore, the ANN method allows the analysis process to be completed in less time and with fewer resources. One of the ANN models employed in this work is the multilayer perceptron (MLP). The MLP model was developed in this study to predict streamflow at the Citarum river, particularly at the Dayeuhkolot hydrological station at 2, 4, 6, 8, 10, 12, and 24 hours ahead. Two data input scenarios were used in the modeling scene. First, input data in the form of station rainfall data and discharge data. The second is regional rainfall and discharge data. Before predicting the discharge in the coming hours, the hyperparameters model is optimized using the GridSearchCV method. The model’s performance is assessed using the RMSE, NSE, and R2 values. The MLP method produced satisfactory results for both scenarios when predicting discharge in less than 4 hours with the NSE and R2 value higher than 0.9. Scenario 2 input data produces a slightly better prediction model than scenario 1. Based on NSE and R2 values, discharge prediction with a prediction time of more than 6 hours produces less accurate results.

Adaptively monitoring streamflow using a stereo computer vision system

Abstract. The gauging of free surface flows in waterways provides the foundation for monitoring and managing the water resources of built and natural environments. A significant body of literature exists around the techniques and benefits of optical surface velocimetry methods to estimate flows in waterways without intrusive instruments or structures. However, to date, the operational application of these surface velocimetry methods has been limited by site configuration and inherent challenging optical variability across different natural and constructed waterway environments. This work demonstrates a significant advancement in the operationalisation of non-contact stream discharge gauging applied in the computer vision stream gauging (CVSG) system through the use of methods for remotely estimating water levels and adaptively learning discharge ratings over time. A cost-effective stereo camera-based stream gauging device (CVSG device) has been developed for streamlined site deployments and automated data collection. Evaluations between reference state-of-the-art discharge measurement technologies using DischargeLab (using surface structure image velocimetry), Hydro-STIV (using space–time image velocimetry), acoustic Doppler current profilers (ADCPs), and gauging station discharge ratings demonstrated that the optical surface velocimetry methods were capable of estimating discharge within a 5 %–15 % range between these best available measurement approaches. Furthermore, results indicated model machine learning approaches leveraging data to improve performance over a period of months at the study sites produced a marked 5 %–10 % improvement in discharge estimates, despite underlying noise in stereophotogrammetry water level or optical flow measurements. The operationalisation of optical surface velocimetry technology, such as CVSG, offers substantial advantages towards not only improving the overall density and availability of data used in stream gauging, but also providing a safe and non-contact approach for effectively measuring high-flow rates while providing an adaptive solution for gauging streams with non-stationary characteristics.

Medium Term Streamflow Prediction Based on Bayesian Model Averaging Using Multiple Machine Learning Models

Medium-term hydrological streamflow forecasting can guide water dispatching departments to arrange the discharge and output plan of hydropower stations in advance, which is of great significance for improving the utilization of hydropower energy and has been a research hotspot in the field of hydrology. However, the distribution of water resources is uneven in time and space. It is important to predict streamflow in advance for the rational use of water resources. In this study, a Bayesian model average integrated prediction method is proposed, which combines artificial intelligence algorithms, including long-and short-term memory neural network (LSTM), gate recurrent unit neural network (GRU), recurrent neural network (RNN), back propagation (BP) neural network, multiple linear regression (MLR), random forest regression (RFR), AdaBoost regression (ABR) and support vector regression (SVR). In particular, the simulated annealing (SA) algorithm is used to optimize the hyperparameters of the model. The practical application of the proposed model in the ten-day scale inflow prediction of the Three Gorges Reservoir shows that the proposed model has good prediction performance; the Nash–Sutcliffe efficiency NSE is 0.876, and the correlation coefficient r is 0.936, which proves the accuracy of the model.

Analysis and research on the characteristics of pollutants discharged from the separate storm pump station

The separate storm pump station can reduce the overflow pollution in rainy days and reduce the impact on the water environment. However, before or after rainfall, the impact of the discharge of diversion rainwater pump station on the water environment is still prominent, which has become one of the important reasons restricting the improvement of water environment pollution. This paper investigates the diversion rainwater pump stations in Shanghai, analyzes the discharge flow and pollution law of the diversion rainwater pump stations according to the operation data, and studies the characteristics, causes and effects of discharge pollution. Therefore, to provide support for the pollutant discharge control of the diversion rainwater pump station.

Analysis of The Impact of Bone Sugar Factory Waste Water On Quality of Teko River Water

The Bone sugar factory discharges its liquid waste into the Teko River water body. The Teko River is widely used for agricultural and fishery purposes, so it is necessary to maintain the quality of the water to suit its designation. Liquid waste from the Bone sugar factory can affect the water quality of the Teko River. The purpose of this study was to determine the water quality status of the Teko River due to the discharge of waste water from the Bone sugar factory. Observations were made on the water body of the Teko River from the up stream and down stream of the disposal of sugar factory wastewater at 3 stations. Station 1 is the point before the discharge of wastewater, station 2 is the point of discharge of wastewater and station 3 is the point after discharge of wastewater, the recipient of the impact. The results of the research conducted on the Teko river water body showed that the status of water quality at station 1 was the category of lightly polluted, station 2 was in the category of lightly polluted and station 3 was in the category of meeting quality standards. Determination of water quality using the Pollution Index method according to Minister of Environment Decree Number 115 of 2003 using class II river water quality standards according to Government Regulation Number 22 of 2021quality standards according to Government Regulation Number 22 of 2021.

A comprehensive ecological flow calculation for a small hydropower development river: A case study

AbstractSmall hydropower projects play a significant role in supplying clean energy and promoting economic development all around the world. The calculation of a river's ecological flow, that is, not only the quantity but also the quality of flowing water, in the watershed where small hydropower projects are located play an important role in scientifically guiding the discharge of small hydropower stations in the upper reaches of the river. By combining Gini coefficient with hydrological variation diagnosis, this study provided a novel approach to test the randomness of hydrological series and assess the evenness of runoff distribution. Furthermore, this study is the first attempt to calculate ecological flow for two separate periods (flood and low‐water periods), and thus is able to better reflect annual runoff variations. In the meantime, the Tennant method was improved by introducing of monthly runoff coefficient and median substitution, and integrating four other hydrological methods (empirical method, Qp method, annual distribution method and minimum monthly average measured runoff method) into the comprehensive calculation and analysis. The above methods were applied to the ecological base flow calculation for a small hydropower project in Dongjiang River basin of China. Through comprehensive and comparative analysis, better applicability was demonstrated by the improved Tennant method and the annual distribution method. The recommended values of ecological base flow for each month were derived at the range of 407–431 m3/s during the flood period and 179–239 m3/s during the low‐water period. This study demonstrated that the method could meet the ecological flow calculation requirements for river ecosystem and provide scientific basis for the delineation of ecological flow thresholds, and thereby ensure the healthy and sustainable development of small hydropower and the healthy river aquatic ecosystem.

Runoff prediction of urban stream based on the discharge of pump stations using improved multi-layer perceptron applying new optimizers combined with a harmony search

Prediction using neural networks is applied in various fields, including hydrology and water resource management. In the learning process, an optimizer is used to determine the relationship (weights and biases) between the input and output data to lower the value of the loss function. Existing optimizers rely absolutely on the relationship that are initially generated and have the probability to converge to a local optimum. Additionally, since there is no structure for storing information about the previously generated correlation, there is a probability that the optimal weights and biases could not be found even when learning proceeds. It is necessary to apply a meta-heuristic optimization algorithm that can consider both global/local search and has a structure that can store the previously generated solution. In this study, a new optimizer was combined with a harmony search (HS), to improve existing optimizers. To test the performance of the improved multi-layer perceptron using the new optimizer (IMLP), the runoff of the Dorim stream in Seoul was predicted. The rainfall and the discharge of pump stations were constructed as input data, and data preprocessing was performed by normalization and correlation coefficients. The IMLP showed improved accuracy and could be used to manage urban streams.

Research of Water Consumption Rate Measurement Based on Thermodynamic Method

As an important index which can be used to evaluate the economic operation result for hydropower station, the water consumption rate of hydropower unit can be acquired with hill chart curve of hydraulic turbine, the relationship curve between flow discharge of hydropower station and water level of reservoir. However, considering that the hill chart curve of turbine is calculated and converted by the model test, there are certain errors when used on the prototype machine, which also brings limitations to the applicability. According to the definition of water consumption rate, it can be determined by the unit’s net head and efficiency. The static water head of the unit can be obtained by measuring pressure for spiral case inlet and draft tube outlet. Therefore, the key issue for the measurement of unit water consumption rate is the measurement of turbine flow discharge. Therefore, according to the operating characteristics of high-head turbines, this article adopts thermodynamics to measure the flow discharge of turbine, studies the installation and implementation of high- and low-pressure section test instruments with the site condition of a hydropower project, and analyses of the water consumption rate of units under different conditions such as the multiple-unit’s operation, various water heads, etc. The analysis results show the relationship and trend for the water consumption rate and unit operation condition, which can provide references for the optimal dispatch operation of multi-units’ hydropower stations, achieving the purpose of reducing the water consumption rate of power generation and improving the efficiency of power generation.

Runoff Prediction Based on the Discharge of Pump Stations in an Urban Stream Using a Modified Multi-Layer Perceptron Combined with Meta-Heuristic Optimization

Runoff in urban streams is the most important factor influencing urban inundation. It also affects inundation in other areas as various urban streams and rivers are connected. Current runoff predictions obtained using a multi-layer perceptron (MLP) exhibit limited accuracy. In this study, the runoff of urban streams was predicted by applying an MLP using a harmony search (MLPHS) to overcome the shortcomings of MLPs using existing optimizers and compared with the observed runoff and the runoff predicted by an MLP using a real-coded genetic algorithm (RCGA). Furthermore, the results of the MLPHS were compared with the results of the MLP with existing optimizers such as the stochastic gradient descent, adaptive gradient, and root mean squared propagation. The runoff of urban steams was predicted based on the discharge of each pump station and rainfall information. The results obtained with the MLPHS exhibited the smallest error of 39.804 m3/s when compared to the peak value of the observed runoff. The MLPHS gave more accurate runoff prediction results than the MLP using the RCGA and that using existing optimizers. The accurate prediction of the runoff in an urban stream using an MLPHS based on the discharge of each pump station is possible.

Effects of Total Dissolved Gas Supersaturation on the Survival of Juvenile Procypris rabaudi and Juvenile Myxocyprinus asiaticus at Varying Water Depth in a Natural River.

Total dissolved gas (TDG) supersaturation, which can be caused by flood discharge, results in gas bubble disease (GBD) in fish and threatens their survival downstream of dams. TDG supersaturation has become a serious environmental problem in the Yangtze River. Few studies have evaluated the effect of TDG supersaturation on fish in natural rivers during periods of flood discharge. To estimate fish tolerance to TDG supersaturation under natural conditions, juvenile Myxocyprinus asiaticus and juvenile Procypris rabaudi were exposed to TDG-supersaturated water for 96 h at various depths (0-0.3 m, 0.3-1.3 m, 1.3-2.3 m and 0-2.3 m) during periods of flood discharge of Dagangshan hydropower station. The results showed that juvenile Procypris rabaudi and juvenile Myxocyprinus asiaticus exhibited obvious GBD signs. An increase in exposure time decreased survival probability of the two species. Deeper water depths can increase the tolerance of juvenile Procypris rabaudi to TDG supersaturation in natural rivers during periods of flood discharge while it cannot improve the survival of juvenile Myxocyprinus asiaticus. Compared with juvenile Myxocyprinus asiaticus, juvenile Procypris rabaudi showed weaker tolerance of TDG supersaturation in shallow water, and juvenile Procypris rabaudi were more vulnerable to TDG supersaturation than juvenile Myxocyprinus asiaticus even if the TDG level (116%) was low.

The behavioural response of European seabass (Dicentrarchus labrax) to chlorinated seawater effluents

Seawater chlorination is widely used for coastal, marine industries for the prevention of fouling. Using a choice chamber system, we investigated the influence of chlorinated seawater at typical concentrations occurring near chlorinated cooling water discharges, on the behaviour of juvenile seabass (Dicentrachus labrax). These studies showed that there was evidence of an effect of chlorination, with models predicting 22% fewer fish present in the chlorine dosed chamber compared to the undosed chamber in all control runs (mean number of fish in the dosed chamber in all control runs was 2.23 in comparison to 1.74 when chlorine was present). These data suggest that when food is available D. labrax will enter areas that are at mean chlorination levels of 0.04 mg l−1, which are typical close to the discharge of power station cooling water but are more likely to move away once the food supply is reduced.

Identification of preferential groundwater run-off belts through correlation between spring discharge and precipitation in Baiquan spring basin

Baiquan spring group is a typical sign of the existence of preferential groundwater run-off belts in Baiquan spring basin. The spring flow is mainly affected by the supply of karst water, and atmospheric precipitation is the most important factor affecting the supply of karst water. By using Pearson correlation coefficient method, the number of months with the maximum Pearson coefficient between the spring discharge and the precipitation at the monthly scale of each hydrological station in the water spring area is analyzed, which is called the best precipitation delay. According to the optimal precipitation lag time, the Pearson correlation coefficients of spring discharge and precipitation of each hydrological station in 2006-2013 are calculated on the three months scale and the daily scale respectively, and the hydrological stations closely related to spring discharge are found out. The results show that: the best precipitation lag time of each station is 6 months; the precipitation change of Wangsheren station, Suncun station and Wenzu station is consistent with the spring flow process, which has a relatively large impact on the spring flow. The 3 stations may be located in the preferential groundwater run-off belts bearing medium in Baiquan spring basin.

Correlation Analysis of Runoff-Electricity Price-Load in Cascade Hydropower Spot Market

Runoff, electricity price, and load are the main random variables in the cascade hydropower spot market. The inter-influence, intertwining and coupling relationship among the three increase the difficulty of power market operation. For this reason, this study first used the system dynamics method to draw the causal circuit diagram of the correlation between power station runoff, discharge price and full network load in the spot market, revealed the correlation mechanism of the three, and analyzed the correlation between the three based on the actual data of the spot market. The results show that there is a significant correlation between the three variables. The price of clearing electricity is positively correlated with the load of the whole network, the correlation coefficient is as high as 0.5238, and the price of clearing electricity is negatively correlated with the reservoir runoff, showing a certain degree of complementarity.

One dimensional hydrodynamic modelling of pamba river for identifying the flood vulnerability

Hydrodynamic modelling is a powerful tool to understand and analyse a river flow and its conditions. The identification of flood vulnerability areas of Pamba river helps to minimize the damages associated with the flood. A hydrodynamic river model was customised and calibrated for the river Pamba in Kerala using MIKE HYDRO River model. The model was calibrated using Manning’s roughness coefficient. In this study, we utilize the time series of daily discharge and water level of different gauging station of Centre Water Commission at Kallooppara, Malakkara, Thumpamon and water level data of Thottappalli spillway. The SRTM DEM was used to generate the flood model for the period June to August 2010. The model performance was assessed by comparing observed and stimulated water level at the upstream and downstream of the river. The correlation coefficient value obtained in the range of 0.53 to 0.94. The outcomes of the study can benefit future modelling effort through the provision of robust tool to predict water levels at various points of the river. This study can help the water resources policy makers for arriving at suitable mitigation measures.