Management Of River Systems Research Articles

Turbulent anisotropy and coherent structures in flow through a symmetric compound channel with emergent floodplain vegetation

This experimental study advances understanding of the impact of homogeneous grass (HG), homogeneous shrub, and mixed (heterogeneous) vegetation (MV) on floodplains (FPs) and the flow dynamics within a symmetric compound channel. Velocity measurements were conducted using an Acoustic Doppler Vectrino Profiler in the main channel (MC), slope region (SR), and FP to compute depth-averaged mean streamwise velocity, Reynolds stress anisotropy tensors, and coherent structures. The analysis revealed a 54% increase in depth-averaged velocity at the MC centerline with MV compared to the no vegetation (NV) case, marking the highest increase observed among all vegetation scenarios. Reynolds stress anisotropy showed that streamwise turbulence anisotropy dominated in both the MC and SR, particularly with MV, reflecting enhanced momentum exchange due to vegetation. The anisotropic invariant map demonstrated a shift from one-dimensional to two-dimensional (2D) turbulence states and the formation of cigar-shaped turbulence structures, especially in the SR. This shift was attributed to increased momentum exchange and resistance. Quadrant analysis revealed that vegetation on the FP intensified bursting events, enhancing sediment transport in the near-bed region compared to the NV case. At the free surface, outward interactions were more frequent than inward interactions, indicating upward water movement. Higher vortex frequency and energy dissipation observed in the SR with vegetated FP confirmed the presence of quasi-2D coherent structures, facilitating the breakdown of larger vortices into smaller ones. These findings provide critical insights for river system management, emphasizing vegetation's role in altering flow dynamics and enhancing sediment transport.

Economic assessment of ecosystem services with a novel concept of elevation: An application of the discrete choice experiment method

AbstractThis research was conducted in the Hei River Basin of China to understand respondents' willingness to pay (WTP) for ecological services towards sustainable river system management. A discrete choice experiment is used to gauge respondents' preferences. In addition, elevation was introduced as a novel spatial attribute to account for heterogeneity. Primary data from 1680 respondents were collected across the Hei River Basin. The elevation of the river was categorized into five ad hoc elevation ranges to analyze the potential effects of elevation on environmental attributes. These samples were stratified as 1000–1600 m, 1601–2200 m, 2201–2800 m, 2801–3400 m, and 3401–4000 m. Pooled data results showed that the maximum WTP was for water quality, that is, 142.05 RMB, without considering the effect of elevation. However, when the interaction with elevation was included, the amount decreased to 133.52 RMB. Likewise, elevation‐based group estimates showed a varied pattern of spatial preference, with different preferences for each distinguishing attribute. Group A prioritized water quality (92.81 RMB) and the East Juyan area (4.12 RMB). In contrast, Group B preferred the guaranteed rate of irrigation of farmland (3.50 RMB) and reduced sandstorm frequency (17.90 RMB). Leisure and entertainment conditions had the lowest WTP across all groups (0.09–0.50 RMB). These findings highlight the importance of incorporating respondents' preferences in restoring and maintaining river systems. Additionally, it emphasized the need to consider respondents' socioeconomic characteristics when developing sustainable management policies.

Passage efficiency through fishways of species of the family Cyprinidae and their management implications for fragmented rivers

The contemporary management of fragmented river systems is in a trade-off between the societal benefits of instream barriers (e.g. hydropower, flood risk management) and the ecological harms of their adverse impacts on fish populations. The consequent fragmentation can be mitigated through fishway construction, with mitigation performance measured using species-specific passage rates and efficiencies. There is, however, a bias in passage efficiency studies towards diadromous fishes and, although fish of the Cyprinidae family play a significant role in the fish assemblages of rivers worldwide, their passage efficiencies are poorly understood. Here, systematic review and meta-analyses assessed the passage efficiencies of cyprinid fishes through fishways that have been measured using telemetry methods. Passive integrated transponder (PIT) telemetry was the most common evaluation method of passage efficiency due to their high read rates and relatively low costs versus alternative telemetry methods. These methods revealed cyprinid passage efficiencies were highest through vertical slot fishways and lowest through nature-like constructions, with overall passage rates comparing favourably to anadromous salmonid fishes. Fish were most active during spring and summer, with passage and associated movements often related to spawning. Passage rates of non-native fishes were also higher than for native fishes. Despite the growing acknowledgment of how fishways influence potamodromous fish dispersal and distribution in rivers, passage data remain scarce, preventing managers and policy-makers from making informed decisions on optimal passage solutions for multiple fish species in highly fragmented rivers.

Investigating the drivers of urban cover-collapse sinkholes in shanghai: analyzing dominant factors and proposing mitigation strategies

Urban cover-collapse sinkholes pose a significant global challenge due to their destructive impacts. Previous studies have identified groundwater fluctuations, subsurface soil conditions, pipeline leakage, precipitation, and subterranean construction activities as key contributors to these phenomena. However, unique geological settings across different urban environments lead to variations in the primary factors influencing sinkhole formation. This study focuses on Shanghai, a city notable for its extensive urbanization and rich historical context, to explore the dynamics of sinkholes within urbanized areas worldwide. We employ spatial analysis and statistical methods to examine data on sinkholes recorded in the past two decades in Shanghai, correlating these events with the city’s shallow sand layer, ground elevation, and proximity to surface water. Our goal is to identify the dominant factors governing sinkhole occurrence in Shanghai and to lay the groundwork for their effective scientific management and prevention. Key findings indicate that most sinkholes in the area are associated with a thin shallow sand layer, low to moderate ground elevations, and the absence of nearby rivers. Additionally, many sinkholes correlate with subterranean voids within the confined aquifer beneath the cohesive soil layer. The lack of historical river channels, obscured by urban development, also indirectly contributes to sinkhole formation. We recommend enhancing urban river management and drainage systems to mitigate potential damage from water accumulation.

Optimization of Manning's roughness coefficient using 1-dimensional hydrodynamic modelling in the perennial river system: A case of lower Narmada Basin, India.

This research bears significant implications for river management, flood forecasting, and ecosystem preservation in the Lower Narmada Basin. A more precise estimation of Manning's Roughness Coefficeint (n) will enhance the accuracy of hydraulic models and facilitate informed decision-making regarding flood risk management, water resource allocation, and environmental conservation efforts. Ultimately, this study aspires to contribute to the sustainable management of perennial river systems in India and beyond by offering a robust methodology for optimizing Manning's n tailored to the complex hydrological dynamics of the Lower Narmada Basin. Through a synthesis of empirical evidence and computational modelling, it seeks to empower stakeholders with actionable insights toward preserving and enhancing these invaluable natural resources. Using the new HEC-RAS v 6.0, a one-dimensional hydrodynamic model was developed to predict overbank discharge at different points along the basin. The study analyzes water levels, stream discharges, and river stage, optimizing Manning's n and required flood risk management. The model predicted a strong output agreement with R2, NSE, and RMSE for the 2020 eventas 0.83, 0.81, and 0.36, respectively, with an optimum Manning's n of 0.03. The lower Narmada Basin part near the coastal zone (validation point) appears inundated frequently. The paper aims to provide insights into optimizing Manning's coefficient, which can ultimately lead to better water flow predictions and more efficient water management in the region.

Spatial distribution of physicochemical parameters and drinking and irrigation water quality indices in the Jhelum River, Pakistan.

Sustainable management of river systems is a serious concern, requiring vigilant monitoring of water contamination levels that could potentially threaten the ecological community. This study focused on the evaluation of water quality in the Jhelum River (JR), Azad Jammu and Kashmir, and northern Punjab, Pakistan. To achieve this, 60 water samples were collected from various points within the JR Basin (JRB) and subjected to a comprehensive analysis of their physicochemical parameters. The study findings indicated that the concentrations of physicochemical parameters in the JRB water remained within safety thresholds for both drinking and irrigation water, as established by the World Health Organization and Pakistan Environmental Protection Agency. These physicochemical parameters refer to various chemical and physical characteristics of the water that can have implications for both human health (drinking water) and agricultural practices (irrigation water). The spatial variations throughout the river course distinguished between the upstream, midstream, and downstream sections. Specifically, the downstream section exhibited significantly higher values for physicochemical parameters and a broader range, highlighting a substantial decline in its quality. Significant disparities in mean values and ranges were evident, particularly in the case of nitrates and total dissolved solids, when the downstream section was compared with its upstream and midstream counterparts. These variations indicated a deteriorating downstream water quality profile, which is likely attributable to a combination of geological and anthropogenic influences. Despite the observed deterioration in the downstream water quality, this study underscores that the JRB within the upper Indus Basin remains safe and suitable for domestic and agricultural purposes. The JRB was evaluated for various irrigation water quality indices. The principal component analysis conducted in this study revealed distinct covariance patterns among water quality variables, with the first five components explaining approximately 79% of the total variance. Recommending the continued utilization of the JRB for irrigation, we advocate for the preservation and enhancement of water quality in the downstream regions.

Construction and Application of a Seasonal River Health Evaluation System in Arid and Semi-Arid Areas

Addressing the inadequacy of theoretical frameworks and evaluation indicators for assessing the health of seasonal rivers in arid and semi-arid regions, this study aims to enrich the theoretical foundation for the management and ecological restoration of seasonal river systems. By selecting seven indicators from three aspects: hydrology, habitat, and social services, a seasonal river health assessment indicator system was constructed for the Tabu River basin. The weights of the indicators were determined using the analytic hierarchy process and entropy weight method, and a classification standard for seasonal river health was established. The health status of the Tabu River in 2021 was evaluated accordingly. The results revealed that the upstream, midstream, and downstream reaches of the Tabu River were categorized as healthy, sub-healthy, and diseased, respectively, with poor hydrological conditions being the primary concern. The satisfaction level of ecological flow within the basin was low, accompanied by deep groundwater levels and water scarcity issues, aligning with the actual situation. This indicator system effectively reflects the true state of seasonal river ecosystems. Based on the evaluation results, measures such as establishing ecological water storage projects and adjusting agricultural planting structures were proposed to alleviate the impacts caused by water scarcity. Additionally, implementing river and lake management systems, water resource protection measures, and water-saving technologies can directly regulate the pressures imposed on rivers by human socio-economic activities, thus alleviating regional water resource shortages and promoting the health of rivers and regional water resources. These findings provide scientific decision-making support for the management of seasonal river basins and the maintenance of river health.

Precipitation-dependent sensitivity of suspended sediment concentration to turbidity in a mountainous river in southwestern China

Suspended sediment concentration (SSC) has been used as a key indicator in various environmental studies concerning, for example, ecological integrity, river morphology, aquatic and riverine biota, and the management of river and reservoir systems. River turbidity has been widely used as a proxy indicator of SSC. However, the relationship between the two parameters varies considerably under different conditions. The present study investigated the relationships between SSC and turbidity under different rainfall conditions in the Baisha River, a mountainous river located in southwestern China. Data were continuously collected on site from 2015 to 2021. The results showed a significant positive correlation between SSC and turbidity, with the median slope model exhibiting the best linear fit. In addition, the linear regression slopes varied significantly between different seasons and rainfall intensities in the following descending orders: dry season (1.05) > rainy season (0.97), no rainfall (1.14) > non-erosive rainfall (0.99) > erosive rainfall (0.95), and mild rainfall (1.05) > moderate rainfall (0.97) > heavy rainfall (0.93) > rainstorm (0.89). Overall, during the rainy season and under higher rainfall intensities, the regression slope was gentler. This study discussed the mechanisms through which rainfall conditions affected the SSC-turbidity relationship. It was shown that such a relationship was generally influenced by sediment transport in the runoff and river water flow flux, and the number of suspended particles as well as their size were considered as main factors. The results of this study revealed the impact of rainfall conditions on the SSC-turbidity relationship and provided a reference for the rapid assessment of the suspended sediment load in mountain river basins at high altitudes. In addition, based on the results obtained, it is expected that a new method for predicting event-based soil erosion can be applied in similar high-altitude mountain valleys.

An improved Back Propagation Neural Network framework and its application in the automatic calibration of Storm Water Management Model for an urban river watershed

The use of the Storm Water Management Model (SWMM) to simulate flows in urban river watersheds necessitates the proper calibration of the various parameters involved in the process. Back Propagation Neural Network (BPNN) is often used to establish relationship between two sets of multivariate variables, such as parameters and simulation results of SWMM. The aim of this study is to establish an improved BPNN to calibrate SWMM. It was found that when using gauged flow data obtained from the urban river management system as calibration data, only using BPNN was not sufficient. An improved BPNN framework was proposed with integrating Principal Component Analysis (PCA) and Genetic Algorithm (GA) process, abbreviated as PCA-GA-BPNN. It was proved to be effective for calibration. The BPNN combined with GA process made 90 % of the predicted parameters within reasonable range, which was only 8 % using BPNN alone. The PCA process reduced the training time up to 64 %. Using a hydrograph of 196 h, compared with the nondominated sorting genetic algorithm (NSGA), PCA-GA-BPNN training time can be reduced from 18,142 s down to 4.5 s. Nash efficiency coefficients (NSE) of hydrographs fitting was 0.75. Including more rainfall events data in calibration achieved better fitting than including more gauging station data.

Predicting River Discharge in the Niger River Basin: A Deep Learning Approach

Across West Africa, the River Niger is a major source of freshwater. In addition, the river system also provides services such as aquaculture, transportation, and hydropower. The river network plays a critical role in the hydropolitics and hydroeconomics of the region. Therefore, River Niger is integral to the development of West Africa, hence, there is a need to ensure that the river’s ecosystem is a healthy one. In light of the changing climate and its associated threats such as droughts and floods, constant monitoring and measurements of the the river’s flow system cannot be overemphasized. This study investigates temporal variations in annual river discharge characteristics at eight stations (Koulikoro, Dioila, Kirango, Douna, Mopti, Dire, Ansongo, and Niamey) in the Niger River basin, presenting detailed quantitative findings. Analyzing discharge data of River Niger from 1950 to 1990, the minimum discharge measures (minimum and 10th percentile) exhibit a consistent decreasing trend post-1960, persisting into the 1990s at several stations. Central tendency measures (mean and 50th percentile) also consistently reduced since 1950, with near-zero median values observed in Diola and Douna. Recovery in mean discharge is evident in Ansongo after 1980. Extreme values (maximum and 90th percentile) show decreasing trends across all stations, with some locations exhibiting a slight recovery after 1980. The decreasing trend in annual minimum, mean, and maximum values has implications for water resources, affecting hydroelectric generation, fish farming, and dry season irrigation. Machine learning algorithms (MLAs) are deployed to predict the prediction of monthly river discharge, with LSTM identified as the best-performing model overall. However, model performance varies across locations, with TCN excelling in Diola but underperforming in Koulikoro. This study emphasizes the chaotic nature of time series data and external drivers limiting the long-term predictive capabilities of MLAs. Quantitative evaluation of MLA performance reveals specific strengths and weaknesses at each station. This study underscores the importance of predicting the 10th percentile of annual river discharge for water resource planning. Models exhibit diverse performance across basins, emphasizing the need for tailored approaches. Further analysis considers measures of central tendencies, predicting the 50th percentile (Q50) and mean discharge values. TCN emerges as the best model for Q50 prediction, showcasing superior performance over other models. Additionally, the study delves into predicting high and low extreme discharges, crucial for understanding potential flood events and preparing for meteorological and hydrological droughts. This study concludes by emphasizing the necessity for location-specific studies in the River Niger basin to facilitate an enhanced integrated river management system.

How much do bacterial growth properties and biodegradable dissolved organic matter control water quality at low flow?

Abstract. The development of accurate water quality modeling tools is necessary for integrated water quality management of river systems. Even though some water quality models can simulate dissolved oxygen (DO) concentrations accurately during high-flow periods and phytoplankton blooms in rivers, significant discrepancies remain during low-flow periods, when the dilution capacity of the rivers is reduced. We use the C-RIVE biogeochemical model to evaluate the influence of controlling parameters on DO simulations at low flow. Based on a coarse model pre-analysis, three sensitivity analyses (SAs) are carried out using the Sobol method. The parameters studied are related to bacterial community (e.g., bacterial growth rate), organic matter (OM; partitioning and degradation of OM into constituent fractions), and physical factors (e.g., reoxygenation of the river due to navigation and wind). Bacterial growth and mortality rates are found to be by far the two most influential parameters, followed by bacterial growth yield. More refined SA results indicate that the biodegradable fraction of dissolved organic matter (BDOM) and the bacterial growth yield are the most influential parameters under conditions of a high net bacterial growth rate (= growth rate − mortality rate), while bacterial growth yield is independently dominant in low net growth situations. Based on the results of this study, proposals are made for in situ measurement of BDOM under an urban area water quality monitoring network that provides high-frequency data. The results also indicate the need for bacterial community monitoring in order to detect potential bacterial community shifts after transient events such as combined sewer overflows and modifications in internal processes of treatment plants. Furthermore, we discuss the inclusion of BDOM in statistical water quality modeling software for improvement in the estimation of organic matter inflow from boundary conditions.

Evaluation of the potential stranding risk for aquatic organisms according to long-term morphological changes and grain size in alpine rivers impacted by hydropeaking

Hydropeaking is one of the major hydropower-related disturbances of natural processes in river systems. The artificial flow fluctuations that are caused by the on-demand production of electricity are known for their severe impacts on aquatic ecosystems. These particularly affect those species and life stages that are not able to adjust their habitat selection to rapid up- and downramping rates. To date, the stranding risk has both experimentally and numerically mainly been investigated with variable hydropeaking graphs over stable river bathymetries. There is a lack of knowledge on how single, discrete peaking events vary concerning their impact on the stranding risk when the river morphology changes in the long-term perspective. The present study precisely addresses this knowledge gap by investigating morphological changes on the reach scale over a period of 20 years and the related variability of the lateral ramping velocity as a proxy for stranding risk. Two alpine gravel bed rivers impacted by hydropeaking over decades were tested by applying a one-dimensional and two-dimensional unsteady modelling approach. Both the Bregenzerach River and the Inn River exhibit alternating gravel bars on the reach scale. The results of the morphological development, however, showed different developments in the period 1995–2015. The Bregenzerach River displayed continuous aggradation (uplift of river bed) over the various selected submonitoring periods. In contrast, the Inn River showed continuous incision (erosion of river bed). The stranding risk exhibited high variability on a single cross-sectional basis. However, on the reach scale, no significant changes in stranding risk were calculated for either river reach. In addition, the impacts of river incision on the substrate composition were investigated. Here, in line with preceding studies, the results show that the coarsening of substrate increases the stranding risk and that especially the d90 (90 % finer of the grain size distribution) must be considered. The present study reveals that the quantified stranding risk of aquatic organisms is a function of the general morphological (bar) characteristics of the impacted river and both the morphological and grain size development have an impact on the potential stranding risk of aquatic organisms and should be considered in the revision of licences in the management of multi-stressed river systems.

Climate change increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan

As a direct consequence of extreme monsoon rainfall throughout the summer 2022 season Pakistan experienced the worst flooding in its history. We employ a probabilistic event attribution methodology as well as a detailed assessment of the dynamics to understand the role of climate change in this event. Many of the available state-of-the-art climate models struggle to simulate these rainfall characteristics. Those that pass our evaluation test generally show a much smaller change in likelihood and intensity of extreme rainfall than the trend we found in the observations. This discrepancy suggests that long-term variability, or processes that our evaluation may not capture, can play an important role, rendering it infeasible to quantify the overall role of human-induced climate change. However, the majority of models and observations we have analysed show that intense rainfall has become heavier as Pakistan has warmed. Some of these models suggest climate change could have increased the rainfall intensity up to 50%. The devastating impacts were also driven by the proximity of human settlements, infrastructure (homes, buildings, bridges), and agricultural land to flood plains, inadequate infrastructure, limited ex-ante risk reduction capacity, an outdated river management system, underlying vulnerabilities driven by high poverty rates and socioeconomic factors (e.g. gender, age, income, and education), and ongoing political and economic instability. Both current conditions and the potential further increase in extreme peaks in rainfall over Pakistan in light of anthropogenic climate change, highlight the urgent need to reduce vulnerability to extreme weather in Pakistan.

Cooperative adaptive management of the Nile River with climate and socio-economic uncertainties

The uncertainties around the hydrological and socio-economic implications of climate change pose a challenge for Nile River system management, especially with rapidly rising demands for river-system-related services and political tensions between the riparian countries. Cooperative adaptive management of the Nile can help alleviate some of these stressors and tensions. Here we present a planning framework for adaptive management of the Nile infrastructure system, combining climate projections; hydrological, river system and economy-wide simulators; and artificial intelligence multi-objective design and machine learning algorithms. We demonstrate the utility of the framework by designing a cooperative adaptive management policy for the Grand Ethiopian Renaissance Dam that balances the transboundary economic and biophysical interests of Ethiopia, Sudan and Egypt. This shows that if the three countries compromise cooperatively and adaptively in managing the dam, the national-level economic and resilience benefits are substantial, especially under climate projections with the most extreme streamflow changes.

Hydro-geomorphological regime of the lower Yellow river and delta in response to the water–sediment regulation scheme: Process, mechanism and implication

The water and sediment regulation schemes (WSRS) orientated by dams have profoundly adjusted the hydrological process and geomorphological evolution of the lower Yellow River and delta. Two decades since the implementation of WSRS, the observed multidisciplinary datasets allowed us to systematically evaluate the impacts of this unprecedented engineering effort on the river-coastal system. The sediment fluxes transported to the sea showed a notable rebounded and coarsened process due to the erosion of the riverbed during the WSRS periods. The average median grain size of suspended sediment increased from 17.7 μm in the 1990 s to 26 μm in 2002–2009. The natural rhythm of hydrological process is fundamentally altered by WSRS, about 50% and 30% of annual sediments and water delivered to the sea for only 20 days. The water discharge system is more temporally dynamic and complex with higher dimensionality after the operation of WSRS. The erosion pattern has been a dominant feature in all the channel segments downstream the Xiaolangdi Reservoir, with an average total erosion volume of 1.02 × 108 m3/a after the WSRS. However, the erosion efficiency of the lower river showed a decreased trend, due to the riverbed had formed a coarse armored substrate for the continued scouring since 2002. The YRD has changed from the pattern of erosion to progradation for the increase of sediment supply, and the average growth rate of subaerial delta was about 6.89 km2/a during 2003–2014. The lessons learned from the operation of WSRS may provide a valuable reference for the management of global large river systems.

Hydrogeomorphic advancements in river science for water security in India

Effective management of rivers and the maintenance of the integrity of linked biophysical systems require multidisciplinary approaches. Thus, River Science is a relatively new arena of scientific inquiry that focuses on problems of sustainable management of river systems and it actively integrates multiple scales and various concepts. This paper presents a review of new developments in hydrogeomorphic processes understanding, which are critical to assess water security for Indian river systems.Indian rivers are under the influence of a diverse interplay of climatic, geomorphic, tectonic, and anthropogenic forces, and are broadly classified in terms of Himalayan and Peninsular rivers, which can be further subdivided into 6 major types. The Himalayan rivers have received greater attention in comparison to rivers in peninsular India. Within the backdrop of changing climate, an improved understanding of the interrelationships between hydrological, morphological and ecological processes is the key to quantifying water security for Indian rivers in the near future. Geomorphic threshold, hydrological and sediment connectivity, Groundwater-Surfacewater (GW-SW) interaction and Environmental-flow (E-flow) assessment are the essential elements to understand the hydrology-morphological-ecological processes. Such studies have been initiated in Indian river systems, however, these are still limited in number. Stream power distribution based approaches are frequently employed to understand hydrological controls on morphological processes and form in regulated and unregulated rivers. As a majority of the Himalayan rivers are hydrologically and morphologically disconnected due to large dams or barrages, the result is a discontinuum of channel processes. Peninsular rivers are dominantly bedrock and highly regulated river systems, which show significant short- to long-term flow variability and have tributaries which are not perennial. Disconnectivity due to extensive flow regulation and water withdrawals impose great stress on the flow processes and sediment transport, and result in the progressive decline in channel morphology, habitat, and ecosystem flow needs. A critical research question in highly regulated river systems is regarding how the flow regime at the reach scale and the associated hydrogeomorphic variability can be systematically characterized. Identification of geomorphic thresholds at different scales and quantification of (a) hydrological and sediment connectivity in river systems, (b) surface–groundwater interaction, and (c) E-flow assessment for different reaches in each river basin are the major gaps in River Science studies specific to Indian river systems. Especially, E-flow assessment for different river basins using a holistic approach must be the leading area of River Science research to aid management and policy making with the goal of enhancing water security. Relatively less studied peninsular rivers need more quantitative process-based hydrogeomorphic studies and their application for E-flow assessment.

Estimation of the longitudinal dispersion coefficient via a fusion of optimized models

Abstract Determination of the longitudinal dispersion coefficient (LDC) is fundamental to the development of strategies for environmental management of river systems. This paper presents an integrated model for an estimation of the longitudinal dispersion coefficient by a fusion of optimized intelligent models (optimized neural network (ONN), optimized fuzzy inference system (OFIS), and optimized support vector regression (OSVR)) via committee machine (CM), with optimization done by the Bat-inspired algorithm (BA). The optimization eliminates the associated loss of accuracy of the intelligent models, which is a direct consequence of an improper adjustment of parameters (weights and biases in the neural network, membership's functions in the fuzzy inference system, and user-defined parameters in support vector regression). Data gathered from literature are employed to validate the proposed integrated model. A comparison between the optimized models and a committee machine, based on statistical parameters, shows that the committee machine model can attain high accuracy. Sensitivity analysis (SA) shows the contribution of each optimized model to the committee machine and ranks the contribution of the optimized models in ascending order as optimized neural network, optimized fuzzy inference system, and optimized support vector regression, each significantly correlated with the accuracy of longitudinal dispersion coefficient prediction.

Characterising the woody vegetation in contrasting habitat types in the lower Fitzroy River, Western Australia

Context Riverine systems consist of distinct habitats along a landscape gradient and characterising the composition and structure of vegetation in these habitats can support environmental water-management decisions. However, in many regions, including northern Australia, there is a paucity of hydro-ecological data. Aims We aimed to characterise the species composition and the structure of riparian and floodplain woody vegetation of the lower Fitzroy River. Methods We surveyed woody vegetation in different habitats within the riparian zone and floodplain. Multivariate analysis was used to assess differences in the composition of riparian woody species among the four habitat types and univariate analysis was used to compare vegetation structure, recruitment, and environmental variables among habitats. Key results The composition and the physical structure of woody species differed among habitat types of the lower Fitzroy River, indicating a zonation of riparian and floodplain vegetation in response to fluvial processes and water availability. The floodplain was characterised by sparsely distributed Eucalyptus microtheca and a sparse (∼30%) canopy cover. In contrast, the riverbank habitat type had very large trees (mean basal area = 0.26 m2), with a dense canopy cover (∼80%) and was dominated by Melaleuca argentea, M. leucadendra and Barringtonia acutangula. Both the top of bank and off-channel wetlands represent a more intermediary environment, characterised by greater species richness and greater seedling recruitment. Conclusions Identifying these habitat types and characterising their physical and biological properties, such as the relationship between flooding and the composition of woody species, provides a framework to assist the management of large floodplain river systems.

A RELATIONAL DATABASE FOR INLAND FISHERIES RESOURCE MANAGEMENT

A relational database, named RRDBMS (River, Reservoir and Wetland Database Management System) has been developed with the objective of systematically storing data on various abiotic (morphological, sediment and water quality) and biotic (plankton, pheriphyton, macrobenthic organisms, macrophytes, gear wise and species specific fish catch) parameters of inland aquatic resources like river, reservoir, wetlands, etc. This software would facilitate in bringing scattered research data under one roof so that researchers and planners can use the inland fishery data at any point of time. The software has been developed in a user-friendly environment with menus and shortcuts, so that any user can operate the system easily. Key words: Database, river, reservoir, wetland, RRDBMS, Visual Basic.

Bedforms evolution in the Vistula River mouth during extreme flood event, southern Baltic Sea

Results of bathymetric surveys conducted to examine changes of sand dunes geometry in the Vistula River mouth before, during and after the extreme flood event are presented. A total of 2076 dunes were analysed based on a series of bed elevation profiles obtained along the centreline of about 3.3 km length. Low-steepness dunes characterized by the mean lee-side slopes milder than β<10° are fully dominant at low flows. In contrast, at high hydrology, nearly 50% of dunes indicate β>10°. Dune height and length are substantially out of phase with progressive changes of water discharge exposing a well-pronounced anti-clockwise hysteresis. Distinct behaviour of dune dimensions reflected in increasing of dune steepness H/λ of about 3-fold and decreasing of about 4-fold were observed during rising and falling discharges, respectively. The bed roughness due to dunes presence showed changes of about 10-fold during the both of limbs and is found to be in range of about kdunes=(1/5÷3/5)Hmean. At the mesoscale region, spectra followed sufficiently by the ‘–3 power law’ for low hydrology, with steeper spectrum slopes close to ‘–4’ during moderate and high water discharges. With the development of the flood, potential of flow separation phenomena was increased of about 9-fold, from 2.2% at the flood beginning phase up to 20% at the flood peak. The obtained results could be used for the improvement of the hydraulic numerical models in sand-bed rivers to predict bedforms evolution, flow resistance and turbulence as well as water levels for proper river system management during flood events.