Rainfall is the most important input parameter for water resource planning and hydrological studies because flood risk assessment, rainfall harvesting and runoff estimation depend on the rainfall distribution within a region. Due to practical and economic factors, it is not possible to site rainfall stations everywhere, so representative rainfall stations are sited at specific locations. Rainfall distribution is then estimated from such stations. In this study, rainfall distribution in the southwestern region of Saudi Arabia was estimated using kriging, co-kriging and inverse distance weighted (IDW) methods. Historical records of rainfall from 47 stations for the period 1965-2010 and the altitude of these stations were used. The study shows that co-kriging is a better interpolator than the kriging and IDW methods, with a better correlation between actual and estimated monthly average rainfall for the region.Key words rainfall; kriging; co-kriging; inverse distance weighted method; Saudi Arabia Estimation de la distribution des précipitations de la région Sud-Ouest de l'Arabie saoudite Résumé La pluie est la variable d'entrée la plus importante pour la planification des ressources en eau et les études hydrologiques, car l'évaluation des risques d'inondation, la conception de la récolte des pluies et l'estimation des débits dépendent de la répartition des pluies dans une région. En raison de facteurs économiques et pratiques, il n'est pas possible d'installer partout des stations pluviométriques et on implante donc des stations pluviométriques représentatives en des endroits particuliers. La distribution des précipitations est alors estimée à partir de ces stations. Dans cette étude, la répartition des précipitations de la région du SudOuest de l'Arabie saoudite a été estimée à l'aide des méthodes de krigeage, de co-krigeage et de pondération par l'inverse des distances (PID). On a utilisé l'altitude et les données historiques de précipitations de 47 stations pour la période 1965-2010. L'étude montre que le co-krigeage est un meilleur interpolateur que le krigeage et la PID, avec une meilleure corrélation entre les précipitations moyennes mensuelles réelles et estimées pour la région.
Delivering water in sufficient quantity and acceptable quality is the main objective of water distribution networks (WDN) and at the same time is the main challenge. Many factors affect the delivery of water through distribution networks. Some of these factors are relevant to water quality, quantity and the condition of the infrastructure itself. The deterioration of water quality in the WDN leads to failure at the water quality level, which can be critical because it is closest to the point of delivery and there are virtually no safety barriers before consumption. Accordingly, developing a powerful monitoring system that takes into consideration water demand distribution, the vulnerability of the distribution system and the sensitivity of the population to the deterioration of water quality can be very beneficial and, more importantly, could save lives if there was any deterioration of water quality due to operational failure or cross-contamination events. In this paper, a framework for a water quality monitoring system that considers water demand distribution, the vulnerability of the system and the sensitivity of the population using fuzzy synthetic evaluation and optimization algorithms is developed. The proposed approach has been applied to develop a monitoring system for a real WDN in Saudi Arabia.
This study investigated the rainfall patterns, spatial variability, surface runoff generation and dam requirements in the southwestern region of Saudi Arabia. The region was divided into four areas Asir,
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