A comprehensive approach to evaluating watershed models for predicting river flow regimes critical to downstream ecosystem services

Selection of strategies that help reduce riverine inputs requires numerical models that accurately quantify hydrologic processes. While numerous models exist, information on how to evaluate and select the most robust models is limited. Toward this end, we developed a comprehensive approach that helps evaluate watershed models in their ability to simulate flow regimes critical to downstream ecosystem services. We demonstrated the method using the Soil and Water Assessment Tool (SWAT), the Hydrological Simulation Program–FORTRAN (HSPF) model, and Distributed Large Basin Runoff Model (DLBRM) applied to the Maumee River Basin (USA). The approach helped in identifying that each model simulated flows within acceptable ranges. However, each was limited in its ability to simulate flows triggered by extreme weather events, owing to algorithms not being optimized for such events and mismatched physiographic watershed conditions. Ultimately, we found HSPF to best predict river flow, whereas SWAT offered the most flexibility for evaluating agricultural management practices.     

The simulation of land-cover change using a distributed computing environment

Computer models are used in landscape ecology to simulate the effects of human land-use decisions on the environment. Many socioeconomic as well as ecological factors must be considered, requiring the integration of spatially explicit multidisciplinary data. The Land-Use Change Analysis System or LUCAS has been developed to study the effects of land-use on landscape structure in such areas as the Little Tennessee river basin in western North Carolina and the Olympic Peninsula of Washington state. These effects include land-cover change and species habitat suitability. The map layers used by LUCAS are derived from remotely sensed images, census and ownership maps, topological maps and output from econometric models. A public-domain geographic information system (GIS) is used to store, display and analyze these map layers. A parallel version of LUCAS (pLUCAS) was developed using the parallel virtual machine (PVM) on a network of workstations giving a speedup factor of 10.77 with 20 nodes. A parallel model is necessary for simulations on larger domains or for maps with a much higher resolution.     

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.     

Vision‐based Localization and Robot‐centric Mapping in Riverine Environments

This paper presents a vision‐based localization and mapping algorithm developed for an unmanned aerial vehicle (UAV) that can operate in a riverine environment. Our algorithm estimates the three‐dimensional positions of point features along a river and the pose of the UAV. By detecting features surrounding a river and the corresponding reflections on the water's surface, we can exploit multiple‐view geometry to enhance the observability of the estimation system. We use a robot‐centric mapping framework to further improve the observability of the estimation system while reducing the computational burden. We analyze the performance of the proposed algorithm with numerical simulations and demonstrate its effectiveness through experiments with data from Crystal Lake Park in Urbana, Illinois. We also draw a comparison to existing approaches. Our experimental platform is equipped with a lightweight monocular camera, an inertial measurement unit, a magnetometer, an altimeter, and an onboard computer. To our knowledge, this is the first result that exploits the reflections of features in a riverine environment for localization and mapping.     

Development and application of an integrated ecological modelling framework to analyze the impact of wastewater discharges on the ecological water quality of rivers

Modelling is an effective tool to investigate the ecological state of water resources. In developing countries, the impact of sanitation infrastructures (e.g. wastewater treatment plants) is typically assessed considering the achievement of legal physicochemical quality standards, but ignoring the ecological water quality (EWQ) of the receiving river. In this paper, we developed a generic integrated ecological modelling framework quantifying the impact of wastewater discharges on the EWQ of the Cauca river (Colombia). The framework is flexible enough to be used in conjunction with different approaches/models and integrates a hydraulic and physicochemical water quality model with aquatic ecological models. Two types of ecological models were developed, habitat suitability models for selected macroinvertebrate groups and ecological assessment models based on a macroinvertebrate biotic index. Four pollution control scenarios were tested. It was found that the foreseen investments in sanitation infrastructure will lead to modest improvements of the EWQ, with an increase lower than six units of the ecological index BMWP-Colombia. Advanced investments, such as the collection and treatment of all wastewater produced by the cities of Cali, Yumbo and Palmira and upgrading of the treatment systems should be considered to achieve a good EWQ. The results show that the integration of ecological models in hydraulic and physicochemical water quality models (e.g. MIKE 11) has an added value for decision support in river management and water policy. The integration of models is a key aspect for the success in environmental decision making. The main limitation of this approach is the availability of physicochemical, hydraulic and biological data that are collected simultaneously. Therefore, a change in the river monitoring strategy towards collection of data which include simultaneous measurements of these variables is required.     

城市河流滨岸带生态设计与修复研究

合理设计和修复一直是城市河流滨岸带生态环境保护中的关键科学问题,成为学术界和工程界关注的焦点。随着社会经济发展。人类开发河流流域过程中不科学行为给河流流域造成严重的生态破坏现象。城市河流的整治与其滨岸带重新设计显得尤为重要。文章依托当前我国河流滨岸带整体破坏的实际状况,从景观生态学角度,归纳河流滨岸带合理定位,提出生态修复与设计对策,实现整体生态系统的保护。研究成果可为我国城市河流滨岸带设计和修复提供参考。     

Application of a GIS-based simulation tool to illustrate implications of uncertainties for water management in the Amudarya river delta

River basin management decisions have to be made under uncertainty. Relevant uncertainties especially in external driving forces can often not be sufficiently reduced. Rather than expecting to eliminate them, new management strategies should thus aim at taking them into account. Simulation tools can support a process of reasoning about the implications of uncertainties for the outcome of management policies in a specific river basin management context. Model supported scenario analysis of alternative strategies with authorities, managers and other stakeholders can assist in the development of new strategies. The tools provide factual knowledge on the outcome of policy options proposed as scenarios by the participants to the debate. The GIS-based simulation tool TUGAI has been developed to support assessment of the ecological effects of alternative water management strategies in the degraded Amudarya river delta. It combines a multi-objective water allocation model with simple models of landscape dynamics and a fuzzy based evaluation of habitat suitability for riverine Tugai forests. In this paper an example application of the tool for scenario analysis to illustrate the implications of uncertainty in future water supply to the delta area is demonstrated. Scenario analysis provides an assessment of the range and magnitude of the impact of those uncertainties on the ecological situation in the delta. The potential and limitations of applying simple simulation tools in participative settings for analysis and discussion of the potential impacts of uncertainties and development of cooping strategies are discussed.     

BIM技术在生态河湖工程设计中的应用探索

为解决二维绘图设计信息散碎、跨专业人员理解难度大、效率低及设计周期长等难题,将BIM技术应用到生态河湖工程中。立足生态河湖工程特点,结合以往工程设计经验,对Autodesk和Dassault 2种BIM软件平台进行对比分析,分析优劣及适用性,最终确定Autodesk的Civil 3D和Revit软件更适用于生态河湖治理工程。根据这2款BIM软件的整体架构特点及适用范围,研究出一套适用于生态河湖工程三维设计的解决方案,并应用于沁阳市城区段生态综合治理工程中。实际应用表明：应用基于BIM技术的全流程解决方案,可创建河道和建筑物BIM模型,自动统计工程量及生成图纸,大大提高生产效率,节约人力、物力和成本,提高出手产品质量。     

River mapping from a flying robot: state estimation, river detection, and obstacle mapping

Accurately mapping the course and vegetation along a river is challenging, since overhanging trees block GPS at ground level and occlude the shore line when viewed from higher altitudes. We present a multimodal perception system for the active exploration and mapping of a river from a small rotorcraft. We describe three key components that use computer vision, laser scanning, inertial sensing and intermittant GPS to estimate the motion of the rotorcraft, detect the river without a prior map, and create a 3D map of the riverine environment. Our hardware and software approach is cognizant of the need to perform multi-kilometer missions below tree level with size, weight and power constraints. We present experimental results along a 2?km loop of river using a surrogate perception payload. Overall we can build an accurate 3D obstacle map and a 2D map of the river course and width from light onboard sensing.     

A decision support system for adaptive real-time management of seasonal wetlands in California

This paper describes the development of a comprehensive flow and salinity monitoring system and application of a decision support system (DSS) to improve management of seasonal wetlands in the San Joaquin Valley of California. The Environmental Protection Agency regulates salinity discharges from non-point sources to the San Joaquin River using a procedure known as the total maximum daily load (TMDL) to allocate the assimilative capacity of the river for salt among watershed sources. Management of wetland sources of salt load will require the development of monitoring systems, more integrative management strategies and coordination with other entities. To obtain local cooperation, the Grassland Water District (GWD), whose primary function is to supply surface water to private duck clubs and manage wetlands, needs to communicate to local landowners the likely impacts of salinity regulation on the long-term health and function of wildfowl habitat. The project described in this paper will also provide this information. The models that form the backbone of the DSS, develop salinity balances at both a regional and local scale. The regional scale concentrates on deliveries to and exports from the GWD while the local scale focuses on an individual wetland unit where more intensive monitoring is being conducted. The design of the DSS is constrained to meet the needs of busy wetland managers and is being designed from the bottom up utilizing tools and procedures familiar to these individuals.     

Assessing water quality management options in the Upper Litani Basin, Lebanon, using an integrated GIS-based decision support system

The widespread and relentless discharge of untreated wastewater into the Upper Litani Basin (ULB) river system in Lebanon has reached staggering levels rendering its water unfit for most uses especially during the drier times of the year. Despite the call by governmental and non-governmental agencies to develop several wastewater treatment plants and sewage networks in an effort to control this problem, these efforts do not seem to be coordinated or based on comprehensive and integrated assessments of current and projected conditions in the basin.This paper provides an overview of the development and implementation of an integrated decision support system (DSS) designed to help policy makers and other stakeholders have a clearer understanding of the key factors and processes involved in the sewage induced degradation of surface water quality in the ULB, and formulate, assess and evaluate alternative management plans. The DSS is developed based on the WEAP model, which provides a GIS based and visual simulation environment and scenario management and analysis capabilities. The DSS was used to assess two main water quality management plans taking into consideration hydrological, spatial and seasonal variabilities. An incremental cost-effectiveness analysis was conducted to identify best buy plans. The results have confirmed the gravity of this problem and demonstrated the importance of taking immediate action on curbing this onslaught on this valuable and scarce fresh water resource.     

Development of a decision support system for supplier evaluation and order allocation

This study aims to develop models and generate a decision support system (DSS) for the improvement of supplier evaluation and order allocation decisions in a supply chain. Supplier evaluation and order allocation are complex, multi criteria decisions. Initially, an analytic hierarchy process (AHP) model is developed for qualitative and quantitative evaluation of suppliers. Based on these evaluations, a goal programming (GP) model is developed for order allocation among suppliers. The models are integrated into a DSS that provides a dynamic, flexible and fast decision making environment. The DSS environment is tested at the purchasing department of a manufacturer and feedbacks are obtained.     

Assessment of environmental impacts of river basin development on the riverine forests of eastern Kenya using multi-temporal satellite data

The utility of Landsat MSS (Multispectral Scanner) and SPOT XS data in monitoring the impacts of river basin development on a riverine forest located in the lower Tana River Basin of eastern Kenya was evaluated. Land cover change maps derived from Landsat MSS indicated little change in total forest area between 1975 and 1984. Land cover change maps derived from SPOT XS data indicated a 27% decline in forest area between 1989 and 1996. Mean patch size and area-perimeter ratio of the closed riverine forest remained virtually unchanged whereas these parameters for the open forest class decreased by 31% and 4% respectively. In addition, the average extent of the open riverine forest from the river channel declined by about 200 m between 1989 and 1996. This decline was attributed to decreased extent of floods along the floodplain following construction of dams in the upper river basin, and increased exploitation of the forests for fuelwood, especially in the vicinity of the established Bura Irrigation and Settlement Project. The greater lateral movement observed in the location of the river channel for the 1975-1985 period, compared to the 1985-1996 period, was also attributed to construction of dams in the upper river basin.     

A framework for coupling explanation and prediction in hydroecological modelling

Causal explanation and empirical prediction are usually addressed separately when modelling ecological systems. This potentially leads to erroneous conflation of model explanatory and predictive power, to predictive models that lack ecological interpretability, or to limited feedback between predictive modelling and theory development. These are fundamental challenges to appropriate statistical and scientific use of ecological models. To help address such challenges, we propose a novel, integrated modelling framework which couples explanatory modelling for causal understanding and input variable selection with a machine learning approach for empirical prediction. Exemplar datasets from the field of freshwater ecology are used to develop and evaluate the framework, based on 267 stream and river monitoring stations across England, UK. These data describe spatial patterns in benthic macroinvertebrate community indices that are hypothesised to be driven by meso-scale physical and chemical habitat conditions. Whilst explanatory models developed using structural equation modelling performed strongly (r² for two macroinvertebrate indices = 0.64–0.70), predictive models based on extremely randomised trees demonstrated moderate performance (r² for the same indices = 0.50–0.61). However, through coupling explanatory and predictive components, our proposed framework yields ecologically-interpretable predictive models which also maintain the parsimony and accuracy of models based on solely predictive approaches. This significantly enhances the opportunity for feedback among causal theory, empirical data and prediction within environmental modelling.     

Use of environmental sensors and sensor networks to develop water and salinity budgets for seasonal wetland real-time water quality management

Management of river salt loads in a complex and highly regulated river basin such as the San Joaquin River Basin of California presents significant challenges for current Information Technology. Computer-based numerical models are used as a means of simulating hydrologic processes and water quality within the basin and can be useful tools for organizing Basin data in a structured and readily accessible manner. These models can also be used to extend information derived from environmental sensors within existing monitoring networks to areas outside these systems based on similarity factors – since it would be cost prohibitive to collect data for every channel or pollutant source within the Basin. A common feature of all hydrologic and water quality models is the ability to perform mass balances. This paper describes the use of a number of state-of-the-art sensor technologies that have been deployed to obtain water and salinity mass balances for a 60,000 ha tract of seasonally managed wetlands in the San Joaquin River Basin of California. These sensor technologies are being combined with more traditional environmental monitoring techniques to support real-time salinity management (RTSM) in the River Basin. Two of these new technology applications: YSI-Econet (which supports continuous flow and salinity monitoring of surface water deliveries and seasonal wetland drainage); and electromagnetic salinity mapping (a remote sensing technology for mapping soil salinity in the surface soils) – have not previously been reported in the literature. Continuous sensor deployments that experience more widespread use include: weather station sensor arrays – used to estimate wetland pond evaporation and moist soil plant evapotranspiration; high resolution multi-spectral imagery – used to discriminate between and estimate the area of wetland moist soil plant vegetation; and groundwater level sensors – used primarily to estimate seepage losses beneath a wetland pond during flood-up. Important issues associated with quality assurance of continuous data are discussed and the application of a state-of-the-art software product AQUARIUS, which streamlines the process of data error correction and dissemination, is described as an essential element of ensuring successful RTSM implementation in the San Joaquin River Basin.     

The roles of user motivation to perform a task and decision support system (DSS) effectiveness and efficiency in DSS use

The purposes of this study are to: (1) obtain measures of actual decision support system (DSS) use that include the three elements of DSS use proposed by Burton-Jones and Straub (Burton-Jones, A., & Straub, D.W., Jr., (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246), and (2) identify an important psychological construct – a user’s motivation to perform a task – and examine how it interacts with two DSS characteristics – effectiveness and efficiency – to affect actual DSS use. As predicted, the findings indicated that individuals who used a more effective DSS to work on a task that they were motivated in increased usage of the DSS, while DSS use did not differ between individuals who used either a more or less effective DSS to complete a task that they were less motivated in. The results also showed significant difference for two measures of DSS use (i.e., STEP and TIME) and no significant difference for one measure of DSS use (i.e., USE) between individuals who used either a more or less efficient DSS to perform a task that they were more motivated in. As expected, significant differences were found for individuals who used either a more or less efficient DSS to complete a task that they were less motivated in. Finally, the results showed that DSS use increased when perceived ease of use and perceived usefulness of the DSS were high; therefore, these results corroborate the findings of prior research in the context of actual DSS use.     

Optimisation as a process for understanding and managing river ecosystems

Optimisation can assist in the management of riverine ecosystems through the exploration of multiple alternative management strategies, and the evaluation of trade-offs between conflicting objectives. In addition, it can facilitate communication and learning about the system. However, the effectiveness of optimisation in aiding decision making for ecological management is currently limited by four major challenges: identification and quantification of ecosystem objectives; representation of ecosystems in predictive simulation models; specification of objectives and management alternatives in an optimisation framework; and evaluation of model results against actual ecological outcomes. This study evaluates previous literature in ecology, optimisation and decision science, and provides a strategy for addressing the challenges identified. It highlights the need for better recognition and analysis of assumptions in optimisation modelling as part of a process that generates and shares knowledge.     

Ecological effects of cellular computing in microbial populations

Gene regulatory networks allow single cells to adopt a wide range of different phenotypes in response to changes in environmental conditions. The ecological implications of these cellular computations are poorly understood, and they are largely absent from models of microbial community assembly. Here, we highlight a number of examples where ecological interactions are or may be affected by cellular computations. Our review identifies specific opportunities for integrating cellular decision-making into mathematical models of microbe-microbe interactions and community assembly. We argue that incorporating cellular decision-making into microbial ecology will be critical in order to gain a quantitative understanding of microbial biogeography.