Muhammad A. Al-Zahrani

An algorithm for designing a precipitation network in the south-western region of Saudi Arabia

Abstract The planning and design of a water resources project demands accurate hydrological information. Accurate and reliable regional hydrological information not only reduces the changes of project failure but also minimizes the economic risk. Therefore, it is imperative that a hydrological network be planned and designed scientifically. The criterion for hydrological network design should be the optimum number of stations and their respective locations by which hydrological information can be maximized. In this paper, a hydrological network design method, based on Shannons Information Measure, was applied to the existing hydrological network in hydrological Area III, located in the south-western region of the Kingdom of Saudi Arabia, to examine their suitability towards providing maximum hydrological information. The study shows that the existing seventy rainfall stations can be reduced to approximately 45 including stations at new sites.

Performance evaluation of slow sand filters using fuzzy rule-based modelling

The main objective of this study is to evaluate and predict the performance of slow sand filters used for wastewater treatment. The uncertainties in the control parameters and processes require fuzzy sets to be used when modelling system performance. Fuzzy logic if–then rules were used to build a model for the removal efficiency (total coliforms) of slow sand filters. The data were collected from three pilot-scale slow sand filters at the Alkhobar (Saudi Arabia) wastewater treatment plant. The removal efficiency of filters was modelled using three input control parameters—filtration rate, sand bed depth and grain size. Based on available data, fuzzy logic if–then rules were established. The fuzzy rule-based model was validated using experimental data of three case studies reported in the literature. The results were also compared with a multiple regression model. A possibilistic risk analysis was performed using optimal removal efficiency of the slow sand filters. The risk is estimated with respect to non-compliance of unrestricted agricultural reuse standards (100 total coliform/100 ml). In addition to slow sand filters, post- or pre-chlorination of wastewater is recommended to improve wastewater quality for conforming agricultural reuse standards.

Urban Residential Water Demand Prediction Based on Artificial Neural Networks and Time Series Models

Water demand prediction is essential in any short or long-term management plans. For short-term prediction of water demand, climatic factors play an important role since they have direct influence on water consumption. In this paper, prediction of future daily water demand for Al-Khobar city in the Kingdom of Saudi Arabia is investigated. For this purpose, the combined technique of Artificial Neural Networks (ANNs) and time series models was constructed based on the available daily water consumption and climatic data. The paper covers the following: forecast daily water demand for Al-Khobar city, compare the performance of the ANNs [General Regression Neural Network (GRNN) model] technique to time series models in predicting water consumption, and study the ability of the combined technique (GRNN and time series) to forecast water consumption compared to the time series technique alone. Results indicate that combining time series models with ANNs model will give better prediction compared to the use of ANNs or time series models alone.

Stochastic Goal Programming Model for Optimal Blending of Desalinated Water with Groundwater

A stochastic goal programming (GP) model is developed in orderto determine the daily production of desalination plants to meet the requirements of water blending stations (WBS) for major cities in the Eastern Province of the Kingdom of SaudiArabia. The WBS is assumed to be a control point in the systemwhere water is blended to satisfy the desired water quality, downstream of the control point. The desalinated water is blended with brackish groundwater extracted from several groundwater wells. The objective of the model is to minimize the goal deviations from the following priority levels: demand for blended water, control of salinity levels, depletion of groundwater and maximize the use of brackish water, demand forbrackish water at WBS, and production of desalinated water. Anessential element of the model is the input data; unfortunately,available data are not accurate due to the inherent uncertaintyassociated with it. This uncertainty will generate uncertainty in the model output, which affects reliability and confidence associated with the decisions. Thus, reliable planning should consider uncertainties associated with model input parameters.The developed stochastic model shows how Goal Programming (GP)modeling can be used to plan the water resources in the EasternProvince of Saudi Arabia, assuming that both supply and demandare uncertain.

Multi-objective optimization model for water resource management: a case study for Riyadh, Saudi Arabia

A multi-objective goal programming model was developed for water distribution from multiple sources to multiple users. The model was applied in Riyadh, Saudi Arabia, for the period of 2015–2050. In Riyadh, water sources are groundwater (GW), desalinated water (DW) and treated wastewater (TWW), while the users are domestic, agricultural and industrial sectors. The model was applied to: (1) satisfy water demands and quality; (2) maximize TWW reuse and GW conservation; and (3) minimize overproduction of DW and overall cost. In 2015, the required allocations of GW, DW and TWW are 3286, 662 and 609 MCM, respectively, which are projected to be 4345, 1554 and 1305 MCM in 2050, respectively. GW source is likely to satisfy the predicted withdrawal of GW till 2035, while probabilities of non-satisfaction of full demands of GW in 2040, 2045 and 2050 were 0.04, 0.23 and 0.51, respectively. Supply of DW and reuse of TWW are needed to be increased to satisfy the predicted quantities during 2015–2050.

Fuzzy synthetic evaluation of treated wastewater reuse for agriculture

Reuse of treated wastewater (TWW) for agriculture is in practice in many countries. TWW reuse requires wastewater collection, treatment and recycling, which is associated with cost as well as risk to human and ecological systems. In contrast, it can increase agricultural production and reduce environmental risks by reducing wastewater discharge into the natural environment. In Saudi Arabia, where available water resources are extremely limited, TWW reuse can save significant amount of non-renewable groundwater used in agricultural development, which is a strategic goal for the country. In this paper, a multicriteria decision-making approach was developed where cost, risk, benefits and social acceptance of TWW reuse were considered to be the main criteria. A multistage hierarchy risk management model was constructed for this evaluation. Fuzzy synthetic evaluation technique was incorporated where fuzzy triangular membership functions were developed to capture uncertainties of the basic criteria. The analytic hierarchy process was used to determine the relative importance of various criteria at different hierarchy levels. This study indicated that TWW reuse could have positive impact on agriculture, risk reduction and groundwater conservation.

Estimating urban flooding potential near the outlet of an arid catchment in Saudi Arabia

ABSTRACT The aim of this study is to build a flood simulation model for the city of Hafr Al-Batin catchment area. The model consists of a hydrologic model, a hydraulic model and pre- and post-processing tools. A geographic information system-based modelling interface was used to pre-process the terrain and rainfall data and generate input files for hydrologic and hydraulic models. Soil map data, land cover map, land use map and digital elevation model was used to delineate the physical watersheds characteristics. The runoff estimation was based on the widely known Soil Conservation Service curve number approach. The hydrologic/hydraulic model simulations simulated the runoff hydrograph corresponding to different design storms and helped to delineate the resulting flood inundation maps. The results indicate good agreement between the delineated inundation map and the hazard map developed by the municipality. They also show that the location of the city complicates the runoff response for small storms creating two distinct peaks. The results of this study can be utilized for planning purposes and in the design of flood control structures as the study has estimated the runoff corresponding to different design storms and used hydraulics and geospatial data in delineating the flood zones.

Optimization of chlorination boosters in drinking water distribution network for Al-Khobar City in Saudi Arabia

Water quality management in distribution networks is directly related to spatial distribution of chlorine boosters and its dosages. Water chlorination is essential to reduce the effects of bacterial and other microbiological contaminants. A higher dosage of chlorine generates harmful by-products in addition to changes in drinking water’s taste and odor. The optimization of chlorine dosage is necessary to decrease the microbial contaminants that affect water quality. Once the chlorine threshold is determined for microbial contaminant, it will help decision makers suggest optimal values. These decisions can rely on the estimated water quality index (WQI). WQI is an index to evaluate water quality and can be linked to adequate residual chlorine with optimal booster dosage, numbers, and locations in water distribution network (WDN). The city of Al-Khobar, Saudi Arabia’s WDN was selected to validate the application of this study. Based on geographic location, the city Al-Khobar water network was divided into five zones. The initial temporal and spatial analysis pointed out poor water quality zones. EPANET, a modeling and simulating software, was applied to evaluate the WQI. Those EPANET results were then integrated with an optimization model. The optimization model suggested new chlorine booster locations to improve water quality in the city of Al-Khobar water distribution network.

Assessing the impacts of rainfall intensity and urbanization on storm runoff in an arid catchment

In the past few decades, rapid urbanization has occurred in many regions of the Kingdom of Saudi Arabia due to increasing population and urban development. Additionally, the effects of global warming on rainfall characteristics have been observed. This rapid change in urbanization and climate change has cause significant changes in the nature of land surfaces and rainfall patterns, which affect the runoff process and the amount of surface runoff during floods. This study investigated the effect of urbanization and rainfall intensity for Hafr Al-Batin watershed located in Saudi Arabia. For this purpose, a hydrologic model, HEC-HMS, was adopted to simulate the flow of different rainfall intesities and urbanization levels. Simulated results showed that for a 100-year storm, a 24-h duration, and an urbanization level of 80%, the peak flow was 213% higher than the estimated current peak and the runoff volume was 112% higher than the current runoff volume. These results show a strong linear correlation between the level of urbanization and both peak discharge and runoff volume. Furthermore, the results indicate that for short return periods, the peak flow is more sensitive to the level of urbanization compared to long periods.