Development and field-installation of a mathematical simulation model in support of irrigation canal management

Mathematical models / Simulation models / Flow / Hydraulics / Irrigation canals / Decision making / Research / Sri Lanka / Kirindi Oya

Hydraulic mangement of filamentous algae in open-channel networks : case study in Southern France

International audiencePeriphyton constitutes the benthic compartment of aquatic environments such as artificial channels which are specific eco-systems for many reasons. Firstly, they have to fulfill hydraulic performance and water quality objectives. These objectives may be affected by filling problems due to algal developments and sanitary risks linked to toxins secreted by Cyanobacteria. Second, compared to natural streams, artificial channels have a relatively simple geometry and their hydraulic variables are easier to monitor. Also, cross regulators allow the managers to control discharges and water elevations. Periphyton dynamics depend on several factors and hydrodynamic is one of the most crucial one. In this article we analyze an original strategy for algal control currently used in a branch of the Canal de Provence (South of France). The management strategy consists of regular flushes causing increases of the bed shear stress from upstream to downstream and consequently algal filament cutting. This is achieved by increasing the discharge at the upstream end of the branch. We first show that turbidity can be used as an indicator for algal detachment. Then, a detachment model is proposed and coupled with the hydrodynamic simulation of the system. It can be fitted very satisfactorily on the turbidity measurements and can be used to improve the management strategy, such as reducing the discharge released

Optimal Operation of the Multireservoir System in the Seine River Basin Using Deterministic and Ensemble Forecasts

International audienceThis article investigates the improvement of the operation of a four-reservoir system in the Seine River basin, France, by use of deterministic and ensemble weather forecasts and real-time control. In the current management, each reservoir is operated independently from the others and following prescribed rule-curves, designed to reduce floods and sustain low flows under the historical hydrological conditions. However, this management system is inefficient when inflows are significantly different from their seasonal average and may become even more inadequate to cope with the predicted increase in extreme events induced by climate change. In this work, a centralized real-time control system is developed to improve reservoirs operation by exploiting numerical weather forecasts that are becoming increasingly available. The proposed management system implements a well-established optimization technique, model predictive control (MPC), and its recently modified version that can incorporate uncertainties, tree-based model predictive control (TB-MPC), to account for deterministic and ensemble forecasts respectively. The management system is assessed by simulation over historical events and compared to the no-forecasts strategy based on rule-curves. Simulation results show that the proposed real-time control system largely outperforms the no-forecasts management strategy, and that explicitly considering forecast uncertainty through ensembles can compensate for the loss in performance due to forecast inaccuracy

Exploring the Factors Controlling the Error Characteristics of the Surface Water and Ocean Topography Mission Discharge Estimates

The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50–100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g., friction coefficient and bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy

Heterogeneity of Microglial Activation in the Innate Immune Response in the Brain

The immune response in the brain has been widely investigated and while many studies have focused on the proinflammatory cytotoxic response, the brain’s innate immune system demonstrates significant heterogeneity. Microglia, like other tissue macrophages, participate in repair and resolution processes after infection or injury to restore normal tissue homeostasis. This review examines the mechanisms that lead to reduction of self-toxicity and to repair and restructuring of the damaged extracellular matrix in the brain. Part of the resolution process involves switching macrophage functional activation to include reduction of proinflammatory mediators, increased production and release of anti-inflammatory cytokines, and production of cytoactive factors involved in repair and reconstruction of the damaged brain. Two partially overlapping and complimentary functional macrophage states have been identified and are called alternative activation and acquired deactivation. The immunosuppressive and repair processes of each of these states and how alternative activation and acquired deactivation participate in chronic neuroinflammation in the brain are discussed