Ayman G. Awadallah

Identifying Homogeneous Water Quality Regions in the Nile River Using Multivariate Statistical Analysis

Detecting homogeneous regions in the Nile River is essential in carrying mathematical modelling. The aim of this paper is to indentify homogenous regions with respect to water quality. Eight years data were subjected to principal components analysis (PCA) to define the parameters responsible for the variability in water quality. The PCA produced three variates (or principal components). For the Nile stem, variates are related to bacterial pollution, organic pollution and then agricultural/nutrients. As for the Nile branches, variables group as coming from bacterial and organic sources, while the agricultural/nutrients stamp is more visible in summer. Then, cluster analysis (CA) was performed to verify whether the observations could be grouped into spatially coherent patterns. CA grouped sampling sites into three homogenous regions: upper, middle and lower Nile stem. To interpret the subdivision, CA was performed on municipal and demographic data coming from Nile governorates, such as potable water consumption, sewage collection, cultivated areas and population data. The cultivated areas group similarly to nutrients water quality data and the percentages of uncollected sewage group similarly to bacterial data. The consecutive use of PCA and CA enabled to determine the main sources of pollution and to identify homogeneous regions with respect to water quality variables.

Reliability assessment of water structures subject to data scarcity using the SCS-CN model

ABSTRACT When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall–runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall–runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (Tc). However, in data-scarce areas, the calibration of CN and Tc from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and Tc in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method. EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis

Harold Edwin Hurst: The Nile and Egypt, past and future

ABSTRACT H.E. Hurst spent some 60 years studying the Nile for the Egyptian government, and laid the foundation for a monumental set of hydrological records and investigations. His studies of the size of over-year reservoirs needed to maintain a given yield from Nile flows showed that this was greater than that based on random series. This finding, known as the Hurst phenomenon, was confirmed by other natural series and led to important advances in practical and theoretical statistics. His work led to the design of the Aswan High Dam and to continued research in Egypt. Editor D. Koutsoyiannis; Guest editor E. Eris

Evolution of the Nile River drought risk based on the streamflow record at Aswan station, Egypt

The drought in Ethiopian Highlands, source of the Nile flood, has been in the news off and on since the early 1970s, to such an extent that it can be inquired if the Nile basin users are exposed to a drought risk increasing in time. Based on a methodology developed by the author and previously used for flood risk assessment, this article aims to study the progressive modification of the likelihood of occurrence of a certain drought event in the Nile River, based on the annual record available at the Aswan station, Egypt. The record is thoroughly studied to detect possible trends and seasonalities. It is then divided into subsamples, on which frequency analyses were performed using the linear moments (L-moments) method. L-moments perform well with short records and are less sensitive to extremes. The 10-, 25-, 50- and 100-year droughts are estimated based on every subsample, then the temporal evolutions of these estimates are investigated. The results show a cyclic pattern of the drought risk, confirming the previously suggested non-stationarity of the flow series as one of the possible interpretation of the Hurst phenomenon.

Optimal selection of rainfall gauges for safe extreme events estimation using a geostatistical approach

This paper’s objective is to present a method for optimizing rain gauge network aiming to determine the optimal number of stations and their locations, to achieve an acceptable error in extreme rainfall estimation. The optimization is based on the comparison between the maximum daily rainfall depths at high return periods deduced using the entire rain gauges networks and that was deduced using an “optimal” number of rain gauges. A latin hypercube sampling (LHS) method is used to generate samples of stations. Each generated sample is analyzed to obtain the optimum set of gauges locations. The optimal number and locations of rain gauges are obtained in two cases: the first one using a regional frequency analysis technique and the second using an at-site frequency analysis technique. The methodology is applied to the existing rain gauges network of the Walnut Gulch Experimental Watershed (WGEW), AZ, USA. The results showed that, a lower number of rain gauges is required based on the regional frequency analysis technique compared to the at-site frequency analysis technique to achieve the same relative error at the high return periods. The study also suggests optimum locations for the rain gauges.

A Fast Semi Distributed Rainfall Runoff Model for Engineering Applications in Arid and Semi-Arid Regions

A new GIS based rainfall runoff model is developed for engineering applications, achieving a highly automated watershed analysis process starting from watershed delineation and up to the runoff hydrograph calculation. The model can be classified as a semi-distributed time area model that adopts an improved grid based approach for calculation of watershed response. The model deals with each grid cell in the digital elevation model as an independent hydrologic unit. Travel time through each grid cell is estimated using Manning’s formula and a stream power formula that relates the hydraulic radius at the cell to the characteristics of its upstream watershed area and excess rainfall depth. The watershed response at its outlet is estimated by routing the response of each grid cell using a flow path response function that is defined for that cell. The routed responses of all watershed cells are then convoluted to produce the outflow hydrograph. Model advantages include accuracy improvements due to the incorporation of grid-based routing calculations (both translation and attenuation), fully automated model structure, and fast ability to model many watersheds simultaneously. The combination of these advantages constitutes the novelty of the model that makes it very suitable for engineering design as well as for real-time applications. The model was tested using the data of the experimental watershed, Walnut Gulch, Arizona, USA, gauged by 88 rainfall stations and several discharge recording flumes. The results show that the model can accurately predict the runoff hydrograph where suitable input is available.

Development of design storm hyetographs in hyper-arid and arid regions: case study of Sultanate of Oman

The temporal distribution of the design storm is an important input in hydrological models. This research aims to develop design storm profiles representative of arid and hyper-arid areas based on actual storm recordings. Two hundred thirty-six rainfall storms were collected from seventeen rainfall gauges that cover the coastal zone of Oman for the period from 1993 to 2007. Storms were classified into four categories according to their total durations. Design storm hyetographs were derived from raw rainfall records for all four categories using the Alternating Block Method (ABM) and were also computed by ABM applied on the Intensity-Duration-Frequency (IDF) curves. Both design storm profiles were compared and it was found that the ABM_IDF storm profiles were equivalent to the four ABM_Storms profiles from a practical point of view as they produce similar peak discharges. The storm profiles developed in the current research were also compared to the commonly used Soil Conservation Service (SCS) dimensionless distributions and the UK50 storm profiles. The results showed that the most conservative commonly used SCS type II and the UK50 summer profiles are not safe to be used in design purposes in arid and hyper arid regions, despite their wide utilization in many codes of practice in these regions. The study recommends using the newly developed dimensionless storm profiles derived from the actual records.

A Novel Record-Extension Technique for Water Quality Variables Based on L-Moments

Extension of hydrological or water quality records at short-gauged stations using information from another long-gauged station is termed record extension. The ordinary least squares regression (OLS) is a traditional and commonly used record-extension technique. However, OLS is more appropriate for the substitution of scattered missing values than for record-extension as the OLS provides extended records with underestimated variance. Underestimation of the variance of the extended records leads to underestimation of high percentiles and overestimation of low percentiles given that the data is normally distributed. The Maintenance of Variance Extension techniques (MOVE) have the advantage of maintaining the variance in the extended records. However, the OLS and MOVE techniques are sensitive to the presence of outliers. Two new record-extension techniques with the advantage of being robust in the presence of outliers were recently proposed by the authors: the robust line of organic correlation (RLOC) and modified version of the Kendall-Theil Robust line (KTRL2). In this study a new robust technique is proposed. The new regression technique based on L-moments (LMOM) is a modified version of the RLOC and uses the same intercept as that of RLOC and KTRL2 while the estimated slope is based on the second L-moment. An empirical examination of the preservation of the water quality variable characteristics was carried out using water quality records from the Nile Delta water quality monitoring network in Egypt. A comparison between nine record-extension techniques (OLS, MOVE1 to MOVE4, KTRL, KTRL2, RLOC and LMOM) was performed to examine the extended records for bias and standard error in their statistical moment estimates and over the full range of percentiles. Results showed that the proposed LMOM technique outperforms other techniques by producing extended records that preserve variance as well as extreme percentiles.