A simulation tool for managing environmental flows in regulated rivers

Environmental flows provide river flow regimes to restore and conserve aquatic ecosystems, creating considerably different demands compared to conventional water extraction. With increasing incorporation of environmental flows in water planning worldwide, governments require decision support tools to manage these flows in regulated rivers. We developed the Environmental Water Allocation Simulator with Hydrology (eWASH), a fast, flexible and user-friendly scenario-based hydrological modelling tool, supporting environmental flow management decisions for single- or multi-reservoir systems. Environmental flow demands and management rules are easily specified via the graphical user interface, and batch processing functions aid in uncertainty assessment. eWASH modelled main processes of complex regulated rivers and the tool is widely applicable. We calibrated eWASH for the Gwydir and Macquarie Rivers of Australia's Murray–Darling Basin. Modelled monthly environmental flow allocations exhibited Nash–Sutcliffe efficiencies of 0.55 for the Gwydir and 0.72 for the Macquarie catchments respectively when validated.     

Development of an environmental flows decision support system

The Murray–Darling Basin in Australia is severely environmentally degraded as a result of a range of anthropogenic changes, most notably the regulation and extraction of surface water resources for irrigated agriculture. Environmental problems include eutrophication of rivers and storages, elevated salinity levels, widespread blooms of toxic blue–green algae, decline of native fish and bird populations, and reduction of area of riverine wetlands. Both the community and the government are committed to improving the state of the environment in the Basin, both for it's intrinsic ecological values, and to ensure the sustainability of production in what is Australia's most economically important agricultural region. To facilitate the on-going trade-off process between competing users of this resource, a decision support system (DSS) is being developed which will enable explicit prediction of the likely response of key features of the riverine environment to proposed flow management scenarios. The DSS is being developed using the RAISON shell (Lam, D.C.L., Mayfield, C.I., Swayne, D.A., Hopkins, K., 1994. A prototype information system for watershed management and planning. Journal of Biological Systems 2 (4), 499–517), and will integrate a range of simple models of riverine ecology which are being developed. These models will include qualitative and quantitative models representing the response of different aspects of the instream and floodplain ecology dependent upon the river flow regime. The DSS will not include a detailed model of river hydrology or hydraulics, but rather, will use the output from the range of such models currently in use in the Basin as inputs to the ecological models. The DSS will also provide a range of tools to allow user-defined evaluation of scenario results, as well as explanations and supporting information to elucidate the ecological modelling.     

Accounting for surface–groundwater interactions and their uncertainty in river and groundwater models: A case study in the Namoi River,Australia

Surface–groundwater (SW–GW) interactions constitute a critical proportion of the surface and groundwater balance especially during dry conditions. Conjunctive management of surface and groundwater requires an explicit account of the exchange flux between surface and groundwater when modelling the two systems. This paper presents a case study in the predominantly gaining Boggabri–Narrabri reach of the Namoi River located in eastern Australia. The first component of the study uses the Upper Namoi numerical groundwater model to demonstrate the importance of incorporating SW–GW interactions into river management models. The second component demonstrates the advantages of incorporating groundwater processes in the Namoi River model.Results of the numerical groundwater modelling component highlighted the contrasting groundwater dynamics close to, and away from the Namoi River where lower declines were noted in a near-field well due to water replenishment sourced from river depletion. The contribution of pumping activities to river depletion was highlighted in the results of the uncertainty analysis, which showed that the SW–GW exchange flux is the most sensitive to pumping rate during dry conditions. The uncertainty analysis also showed that after a drought period, the 95% prediction interval becomes larger than the simulated flux, which implies an increasing probability of losing river conditions. The future prospect of a gaining Boggabri–Narrabri reach turning into losing was confirmed with a hypothetical extended drought scenario during which persistent expansion of groundwater pumping was assumed. The river modelling component showed that accounting for SW–GW interactions improved the predictions of low flows, and resulted in a more realistic calibration of the Namoi River model.Incorporating SW–GW interactions into river models allows explicit representation of groundwater processes that provides a mechanism to account for the impacts of additional aquifer stresses that may be introduced beyond the calibration period of the river model. Conventional river models that neglect the effects of such future stresses suffer from the phenomenon of non-stationarity and hence have inferior low flow predictions past the calibration period of the river model. The collective knowledge acquired from the two modelling exercises conducted in this study leads to a better understanding of SW–GW interactions in the Namoi River thus leading to improved water management especially during low flow conditions.     

An integrated modelling framework for regulated river systems

Management of regulated water systems has become increasingly complex due to rapid socio-economic growth and environmental changes in river basins over recent decades. This paper introduces the Source Integrated Modelling System (IMS), and describes the individual modelling components and how they are integrated within it. It also describes the methods employed for tracking and assessment of uncertainties, as well as presenting outcomes of two case study applications.Traditionally, the mathematical tools for water resources planning and management were generally designed for sectoral applications with, for example, groundwater being modelled separately from surface water. With the increasing complexity of water resources management in the 21st century those tools are becoming outmoded. Water management organisations are increasingly looking for new generation tools that allow integration across domains to assist their decision making processes for short-term operations and long-term planning; not only to meet current needs, but those of the future as well.In response to the need for an integrated tool in the water industry in Australia, the eWater Cooperative Research Centre (CRC) has developed a new generation software package called the Source IMS. The Source IMS is an integrated modelling environment containing algorithms and approaches that allow defensible predictions of water flow and constituents from catchment sources to river outlets at the sea. It is designed and developed to provide a transparent, robust and repeatable approach to underpin a wide range of water planning and management purposes. It can be used to develop water sharing plans and underpin daily river operations, as well as be used for assessments on water quantity and quality due to changes in: i) land-use and climate; ii) demands (irrigation, urban, ecological); iii) infrastructure, such as weirs and reservoirs; iv) management rules that might be associated with these; and v) the impacts of all of the above on various ecological indices. The Source IMS integrates the existing knowledge and modelling capabilities used by different state and federal water agencies across Australia and has additional functionality required for the river system models that will underpin the next round of water sharing plans in the country. It is built in a flexible modelling environment to allow stakeholders to incorporate new scientific knowledge and modelling methods as they evolve, and is designed as a generic tool suitable for use across different jurisdictions. Due to its structure, the platform can be extended/customised for use in other countries and basins, particularly where there are boundary issues.     

DEM-based modification of pixel-swapping algorithm for enhancing floodplain inundation mapping

Floodplain inundation plays a key role in riparian ecosystems. Remote sensing provides an advanced technology for detecting floodplain inundation, but the trade-off between the spatial and temporal resolutions of remotely sensed imagery is a well-known issue. Sub-pixel mapping is an effective way to mitigate the trade-off by improving the spatial resolution of image classification results while keeping their temporal resolution. It is therefore useful for improving the mapping of highly dynamic flood inundation using coarse-resolution images. However, traditional sub-pixel mapping algorithms have limitations on delineating the extent of floodplain inundation that reveals linear and complex characteristics. A modified pixel-swapping (DMPS) algorithm which is based on a digital elevation model (DEM) is thus developed in this study. It is built on the widely accepted pixel-swapping (PS) algorithm and one of its derivatives, the linearized pixel-swapping (LPS) algorithm. A Landsat image recording a significant flood inundation event in the Chowilla Floodplain of the Murray–Darling Basin in Australia was used as a case study. The results show that the DMPS algorithm outperformed the original PS and LPS algorithms both in accuracy and rationality of the resultant map. It improves the accuracy and the kappa coefficient by about 5% and 0.1, respectively, in comparison with the PS algorithm. The spatial pattern of inundation derived from the DMPS algorithm reveals fewer breakpoints and errors along the river channels. Moreover, it is observed that the DMPS algorithm is less sensitive to some critical parameters compared with the PS and LPS algorithms. It is hoped that the proposed DMPS algorithm will broaden the application of coarse-resolution sensors in floodplain inundation detection, which would thereby benefit the ecological studies in floodplains.     

Coupling real-time control and socio-economic issues in participatory river basin planning

In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.     

A remote sensing approach to determine environmental flows for wetlands of the Lower Darling River,New South Wales,Australia

A remote sensing approach was adopted to determine environmental flow requirements for wetlands in the Lower Darling River. The regulation of river flows by the Menindee Lakes Storage has altered the natural flow regime in the river and is likely to be affecting the health of both the river and its wetlands. Landsat Thematic Mapper (TM) images corresponding to four flood events (1989, 1990 and two in 1996) were analysed and a relationship between river flow heights and wetland inundation was established. Wetlands were classified according to broad commence-to-flow river discharges. The study concluded that 13 000 Ml d^-1 (megalitres per day) at Weir 32 would inundate approximately 50% of the wetlands along the Lower Darling River, this figure being 10 000 Ml d^-1 less than estimated in a previous study.     

Approximating the tail of the Anderson–Darling distribution

The Anderson–Darling distribution plays an important role in the statistical testing of uniformity. However, it is difficult to evaluate, especially in its tail. We consider a new Monte Carlo approach to approximate the tail probabilities of the Anderson–Darling distribution. The estimates are compared with existing tables and recent numerical approximations, obtained via numerical inversion and naive Monte Carlo. Our results demonstrate improved accuracy over existing tables and approximating functions for small tail probabilities. We also present an approximating function for tail probabilities of less than 3×10⁻².     

Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

This study presents monthly estimates of groundwater anomalies in a large river basin dominated by extensive floodplains, the Negro River Basin, based on the synergistic analysis using multisatellite observations and hydrological models. For the period 2003-2004, changes in water stored in the aquifer is isolated from the total water storage measured by GRACE by removing contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by WGHM and LaD hydrological models. The groundwater anomalies show a realistic spatial pattern compared with the hydrogeological map of the basin, and similar temporal variations to local in situ groundwater observations and altimetry-derived level height measurements. Results highlight the potential of combining multiple satellite techniques with hydrological modeling to estimate the evolution of groundwater storage.     

Prediction of sediment,particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model

A Generalised Additive Modelling (GAM) approach is applied to prediction of both particulate and dissolved nutrient concentrations in a wet-tropical river (the Fitzroy River, Queensland, Australia). In addition to covariant terms considered in previous work (i.e. flow, discounted flow and a rising-falling limb term), we considered several new potential covariates: meteorological and hydrological variables that are routinely monitored, available in near-real time, and were considered to have potential predictive power. Of the additional terms considered, only flows from three tributaries of the Fitzroy River (namely, the Nogoa, Comet and Isaac Rivers) were found to significantly improve the model. Inclusion of one or more of these additional flow terms greatly improved results for dissolved nitrogen and dissolved phosphorus concentrations, which were not otherwise amenable to prediction. In particular, the Nogoa sub-catchment, dominated by pasture for cattle, was found to be important in determining dissolved inorganic nitrogen and phosphorus concentrations reaching the river mouth. This insight may direct further research, including future refinement of processed-based catchment models. The GAMs described here are used to provide near real-time river boundary conditions for a complex coupled hydrodynamic and biogeochemical model of the Great Barrier Reef Lagoon, and can be coupled with a forecasting hydrological model to allow integrated forecasting simulations of the catchment to coast system.     

A non-linear optimization model for water treatment planning of a river basin

The primary objective of this study is to develop a long-range planning model for water treatment management of a river basin.

In order to satisfy environmental standards concerning river water pollution, it is fundamentally necessary to construct area-wide sewerages and sewage treatment plants. Hero, an optimal planning problem to construct these public sewage treatment systems is formulated as a non-linear optimization one. In addition the water supply planning problem is taken into consideration by assuming that waste water treated by public tertiary treatment plants can be roused for industrial purposes. The objective function adopted in this model is the total cost of both construction and operation necessary for public sewage treatment systems, and the optimal solution which minimizes this objective function is determined using the generalized reduced gradient (GRG) algorithm.

Through the study of the Yodo river basin in Japan, it is ascertained that various information necessary for planning can be obtained from the model developed in this study.     

Errors in river lengths derived from raster digital elevation models

Length of river reaches is one of the most important characteristics of stream networks when applying hydrological or environmental simulation models. A common method of obtaining estimates of river lengths is based on deriving flow directions, accumulated area and drainage lines from raster digital elevation models (DEM). This method leads to length estimates with variable accuracy, which depends on DEM horizontal resolution, flatness of terrain, DEM vertical accuracy, the algorithm used to obtain flow directions and the way by which distances are calculated over raster structures. We applied an automatic river length extraction method for eight river reaches in the River Uruguay Basin (206 000 km²), in Southern Brazil, and compared its results to the lengths obtained from drainage vector lines digitalized over satellite images. Our results show that relative errors can be higher than 30% in flat regions with relatively low DEM resolution. Preprocessing of DEM by the method known as stream burning greatly improves results, reducing errors to the range 1.9–7.4%. Further improved estimates were obtained by applying optimized values for the length of orthogonal and diagonal steps called distance transforms, reducing the errors to the range ?2.0–3.3%.     

Managing water in complex systems: An integrated water resources model for Saskatchewan,Canada

Using a system dynamics approach, an integrated water resources system model is developed for scenario analysis of the Saskatchewan portion of the transboundary Saskatchewan River Basin in western Canada. The water resources component is constructed by emulating an existing Water Resources Management Model. Enhancements include an irrigation sub-model to estimate dynamic irrigation demand, including alternative potential evapotranspiration estimates, and an economic sub-model to estimate the value of water use for various sectors of the economy. Results reveal that the water resources system in Saskatchewan becomes increasingly sensitive to the selection of evapotranspiration algorithm as the irrigation area increases, due to competition between hydropower and agriculture. Preliminary results suggest that irrigation expansion would decrease hydropower production, but might increase the total direct economic benefits to Saskatchewan. However, indirect costs include reduction in lake levels and river flows.     

Energy-efficient cognitive access approach to convergence communications

This article studies the cognitive access in convergence communications.Convergence communications provide upper-layer applications with uniform communication service,converging different lower-layer networks into a uniform access pattern such as all-IP communications.As an import access in convergence communications,the cognitive access provides users with a flexible and dynamic access to networks.In this article,we do not only take into account the spectrum usage of convergence communication networks,but also consider theirs energy efficiency.An energy-efficient access algorithm is proposed to improve network performance and efficiency.Different from the existing cognitive access,we regard energy efficiency as the optimal objective to turn the energy-efficient cognitive access into an optimal problem.The collision avoidance and sleeping mechanisms are used to reduce energy consumption and raise network throughput.The utility function is proposed to maximize networks’energy efficiency and then achieve the energy-efficient cognitive access.Simulation results show that the proposed approach is effective and feasible,which can significantly improve networks’energy efficiency.     

Characteristics and Sustainability Evaluation of Vegetation Change in Heihe River Basin during 2001 to 2017

Characteristics of vegetation variation play an important role in ecological monitoring and provide the basis for integrated river basin management decisions. In this study, the spatial-temporal trends in vegetation cover change and its sustainability in Heihe river basin during 2001~2017 were characterized, using MODIS-EVI time series data at a spatial resolution of 250 meters in Google Earth Engine(GEE) platform. Combined with temperature, precipitation and river runoff data, the factors affecting vegetation growth in Heihe River Basin were identified. The results show that: Over the last 17 years, the average annual increment of EVI in Heihe river basin was 0.003 9, and the annual expansion of vegetation area was 480.3 km². Vegetation in the upper, middle and lower reaches of Heihe river has changed in varying degrees affected by temperature, precipitation, reclamation of cultivated land, water resources management and related groundwater. Whether the annual maximum EVI value or vegetation area, the increase trend of vegetation in the middle reaches was the most significant, and the oasis area was more obvious than the non-oasis area. This trend is sustainable in the short term, but there is a greater risk for a long time scale. The study provides a demonstration for high-speed monitoring of vegetation changes, reflecting the equal importance of growth and type changes for monitoring vegetation in arid regions. The regional synergy of vegetation changes in river basin puts forward higher requirements for integrated river basin management, such as reasonable water separation and strengthening surface-groundwater collaborative management.     

黑河流域2001~2017年植被变化特征及其可延续性评价

植被的变化特征是流域生态监测的重要内容和流域综合管理决策的基础信息。基于谷歌地球引擎(Google Earth Engine,GEE),利用空间分辨率为250 m的MODIS-EVI(Enhanced Vegetation Index)产品,研究2001~2017年黑河流域植被的时空变化趋势及延续性特征。结合气温、降水与河流径流量观测数据,分析黑河流域上游、中下游绿洲与非绿洲区植被变化的影响因素。结果表明:近17年来黑河流域植被年最大EVI值年均增幅为0.0039,年均新增植被面积为480.3 km^2。受气温、降水、耕地开垦、水资源管理措施及与其密切相关的地下水等因素的不同影响,上中下游表现出不同的变化特征。无论是年最大EVI值还是植被面积,中游的增加趋势最为显著,绿洲区较非绿洲区增加趋势更为明显。这种变化趋势短期内可能延续,但长时间内存在较大风险。研究为快速监测植被变化提供了示范,揭示了干旱区植被监测中长势变化与类型变化的同等重要性,流域植被变化的区域协同性对合理分水、加强地表-地下水协同管理等流域综合管理提出了更高要求。     

数字孪生飞云江流域水利知识平台建设研究

为提高飞云江流域智慧管控风险能力,根据数字孪生流域知识平台建设要求,以知识图谱为技术框架,引入机器深度学习技术,融入流域预报调度业务规则、历史典型场景洪水模式和专家预报经验等知识,通过图模型可视化处理,将知识以图数据模式进行存储,建立流域业务规则库、历史场景库、专家经验库和知识图谱库。利用图计算引擎管理和驱动知识,对流域特点、水利对象关联关系、业务规则等水利知识,进行挖掘提炼、归类组合、智慧管理和集成应用,构建基于水利知识图谱的数字孪生流域知识平台。数字孪生飞云江流域水利知识平台具有智能匹配、智慧推荐、全景推演等特点,可支撑流域防洪“四预”业务,提升流域风险与调度决策全流程数字化、智慧化、精准化水平,为其他水利知识平台建设提供经验借鉴。     

Remote survey of large-scale braided,gravel-bed rivers using digital photogrammetry and image analysis

The use of conventional survey methods to monitor large, gravel river beds has traditionally led to a reliance on repeat measurements of cross-sections which, unless very closely spaced, may give unreliable information about three-dimensional channel morphology and morphological change. Provided certain technological limitations can be overcome, remote survey techniques, such as digital photogrammetry and airborne laser scanning, remove the spatial and temporal constraints typically associated with ground-based surveys, allowing high spatial resolution, distributed, elevation mapping of gravel river beds. This paper develops the use of digital photogrammetry for the survey of a 3.3 km reach of the braided Waimakariri River, New Zealand, which, when combined with image analysis of water colour to infer water depth, provides a Digital Elevation Model (DEM) of the entire river bed. Central to the successful application of this method is DEM post-processing. Errors take two forms: (i) individual point errors associated with incorrect stereo-matching during automated data collection; and (ii) spatially-variable systematic errors that are associated with uncertainties in sensor position and orientation as determined during the bundle adjustment. An automated post-processing procedure is developed to deal with individual point errors and this improves DEM surface quality in terms of accuracy, precision and internal reliability. Systematic errors in the final DEM surface were reduced by applying a simple correction based on surveyed photo-control point elevations.