Drainage Water Reuse: State of Control and Process Capability Evaluation

Abstract

The dynamic behavior of water quality and quantity in the Egyptian drains is often viewed as a disruption to the normal operation and performance of the process of water reuse in irrigation. The control of such behavior has been challenging and often elusive in practice. Therefore, this paper presents a framework to advance the understanding and opportunities for improving the reuse process by developing a multivariate process control model. The model starts with preliminary analysis for water quality data that are collected at the reuse site on the examined drain. This phase comprises investigating data distribution and dependency. Then, univariate control charts are used to investigate the state of control for the independent and normally distributed variables. For dependent variables, principal components analysis is used as a method of synthesizing the variables information. In this case, principal component scores are displayed using multivariate control charts. If in-control case existed, process capability index is used to provide a numerical measure of whether or not the reuse process is capable of producing water that satisfies the irrigation quality standards. Since the model will only detect assignable causes if out-ofcontrol or in-capable case existed, management, operational, and/or engineering action will usually be necessary to sustain the reuse process. In these cases, an action plan in response to the model signals will be vital. The main function of the proposed model is to safely manage the reuse practice using statistical quality control techniques. The model was demonstrated using water quality data collected during the period from January 2006 to July 2011 from Hanut (EH02) and El-Salam 3 (ESL03) pump stations along Hadus drain, Eastern Nile Delta-Egypt. The recommended model is automatic, algorithmic, self-tuning, and computerizable.

Statistical Control of the Process Applied to the Monitoring of the Water Quality Index

“…However, this study demonstrates that these control tools are statistical methods applicable to monitoring water quality. Other studies in the environmental area also demonstrate the efficiency of quality tools, for example, Shaban (2014) considers that the process capability index is a versatile tool when studying a way to develop a management model to help with water reuse and the elimination of possible health risks to the population.…”

Photocatalytic reactor for organic compound removal using photocatalytic mechanism

“…The treated water was continuously removed from the top of the reactor after a hydraulic retention time of 5 h. The time of retention was maintained at 5 h based on previous results by the authors [11] that suggested that complete MB degradation occurred within 4 h. During the long-term operation for 50 days, 13 g of TiO 2 was added each week to the reactor, expect for the last 2 weeks (days 35-50). Thus the loading of TiO 2 was fixed at 1 g l −1 throughout the operation and this was based on prior reported work [12][13][14]. Furthermore, the performance at lower TiO 2 loadings was investigated in the last 2 weeks.…”

A comprehensive management model to maximize the benefits of agriculture drainage water reuse

“…Accordingly, before starting the new ADWR scheme, the drainage water quality has to be carefully investigated to verify whether it is sustainable in compliance with the Egyptian water quality standards (Law No 48 of 1982and its amendment 2013and 2018. Typically, these investigations are carried out using statistical quality control models (SQCM) that aim to analyze, control, and improve the quality of the process under study (Shaban, 2014). In this discipline, control charts (CCHs) and process capability indices (PCIs) are the most commonly used and they provide numerical measures of whether the process can produce items that satisfy the quality standards (Zahid & Sultana, 2008).…”

“…In this context, Shaban (2014) used several SPC tools to develop a quality control model that detects changes accompanied by the ADWR process for irrigation. The model was tested using discharge and water quality data (WQD) collected from the Hanut and El-Salam three pump stations within the Hadus drain basin in the Eastern Nile Delta region but the model had some shortcomings because it was limited to dealing only with normally distributed data and cannot handle other data distribution functions.…”