Field Pilot-Testing of Self-Adaptive Brackish Water Desalination System for Agricultural Drainage Water Desalination

Considerable progress has been made since the early days of Reverse Osmosis (RO) water treatment/desalination in reducing energy consumption through the development of more efficient membranes, effective process configurations and energy recovery devices. There have also been effective developments of low fouling membranes, high performance water treatment chemicals (e.g., antiscalants and coagulants) and feed pretreatment processes to mitigate membrane mineral scaling and fouling. Given the growing interest in inland desalination, there is a growing need for effective management of geographically distributed desalination plants. Such plants must effectively handle temporal variability of water quality and production demand. Reducing membrane fouling and mineral scaling, reducing energy consumption, decreasing plant footprint, and reducing operational costs are all critical elements to future development of inland membrane-based water treatment and desalination for increasing local water portfolios. In order to address the above, a multi-pronged approach was undertaken to assess the prospects for effective autonomous and self-adaptive operation of reverse-osmosis desalination that includes a series of feed water pretreatment units. Translation of theoretical and laboratory studies to pilot field demonstration was included: (a) optimization of process operating conditions as aided by a new class of membrane monitoring approaches for early detection of fouling/mineral scaling and its integration with plant control, (b) self-adaptive operation of two-stage RO that optimizes system operation so as to minimize the energy consumption for a given plant productivity, and (c) deployment of machine-learning tools for plant fault detection and isolation. Field results from a small mobile 60,000 gallons/day RO plant designed for self-adaptive operation will be presented to demonstrate improved operational efficiency through advanced monitoring and control strategies toward a path to high recovery (toward zero liquid discharge) and handling the variability of feed water quality.