Design and assessment of weirs for fish passage under drowned conditions

In aquatic systems, in-stream structures such as dams, weirs and road crossings can act as barriers to fish movement along waterways. There is a growing array of technological fish-pass solutions for the movement of fish across large structures such as weirs and dams. However, most existing weir structures lack dedicated fishways, and fish often have to rely on drowned conditions to move upstream. In order to assess the adequacy of a given or proposed weir for upstream fish passage under drowned conditions, it is necessary to determine, firstly, the hydraulic properties of the drowned weir with respect to the requirements of the fish community and, secondly, the duration and timing of drowning flows with respect to the hydrograph for the site and the likely timing of fish movements. This paper primarily addresses the first issue. A computer program has been developed and incorporated in a simple-to-operate spreadsheet for the determination of the hydraulic characteristics of a drowned weir which are important to fish movement. The program is based on a theoretical analysis of drowned weirs and subsequent extensive verification in laboratory experiments. Inputs to the program include site information comprising channel cross-section data, channel slope, and channel roughness, and weir information comprising weir height and the required minimum drowned depth over the weir for migrating fish passage. The program then calculates the flow rate at which the required level of drowning occurs, the velocity characteristics above the weir (including transverse distributions), and flow depths and velocities upstream and downstream of the weir. The paper discusses (briefly) the theoretical background of the program and its experimental verification. A case study is then presented that illustrates the use of the program in the field to assess fish passage opportunities at an existing weir and to develop a case for retrofitting a fishway. Some discussion is also provided on the contribution of a modelled drownout volume to the assessment of how significant a barrier a weir is to fish passage. It is shown that the program is an important new additional tool in the assessment of the adequacy of weir structures in providing for fish movement and informing associated fish passage solutions. (C) 2011 Elsevier B.V. All rights reserved.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.