Jarbou A. Bahrawi

Soil Erosion Estimation Using Remote Sensing Techniques in Wadi Yalamlam Basin, Saudi Arabia

Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing (RS) and Geographic Information Systems (GIS) techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE) for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating the -factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk (37,740 ha). GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.

A fully distributed spreadsheet modeling as a tool for analyzing groundwater level rise problem in Jeddah city

In this paper, a spreadsheet modeling is introduced as a tool for studying fully distributed real-world engineering problems. The merits of using the spreadsheet are the following: its simplicity, the spreadsheet is very well known to many researchers and engineers; it performs fast calculations; it has a user-friendly graphic interface; and it can also provide animated graphs. These merits provide engineers and scientists with a flexible tool to tackle environmental problems and quickly performing solution scenarios to their problems. A real-world case study has been presented to illustrate the application of such spreadsheet models. The groundwater level rise in Jeddah city is one of the problems that Jeddah city are facing. The reasons of groundwater level rise in Jeddah are the following: the leakage from septic tanks, leakage from freshwater pipe networks, landscape irrigation, annual rainfall, flash floods from eastern wadis, etc. These sources have been complied with a regional groundwater flow model (the general form of the partial differential equation for steady groundwater flow in a heterogeneous, unconfined aquifer with a fully distributed recharge, evaporation and pumping rates, and with a variable aquifer bottom elevation), discritized with a finite difference method, then formulated on a spreadsheet, and solved with the built-in macro-solver on the Excel software. The spreadsheet model has been tested and compared with analytical solution. The model has also been calibrated with observations, and the correlation coefficient was 0.96 for the hydraulic head data. The results have been displayed graphically in one, two, and three dimensions. Various scenarios have been investigated to show solutions of the problem. The results have shown that the spreadsheet modeling is a powerful, flexible, and a user-friendly tool in modeling fully distributed real-world engineering problems. Results can be transferred from spreadsheet to GIS software to present results over satellite images or base maps. Analysis of various solution scenarios can be done efficiently, and one can get quick answers to the decision makers at a preliminary stage of a project before going to a sophisticated modeling approach with specialized software.

Stream network pollution by olive oil wastewater risk assessment in Crete, Greece

Abstract Discharge of olive mill wastewater (OMWW) into rivers system in Crete had led to heavy organic pollution and several drastic environmental impacts. The current research study aims to map and evaluate the environmental hazards initiated by olive mill wastewater pollution discharged into surface stream network of Kolymvari agricultural area located in western Crete, Greece. Implemented methodology is based on locating source points of pollution and determining pollutant surface flow paths under GIS environment. Hydrological features of the area were delineated in the GIS environment using basically elevation data provided by the Ministry of Agriculture. On a microscale, it was proved that the implementation of MCA can quantify the environmental risk to surface water resources caused by OMWW. On a macroscale, risk mapping was implemented by establishing a spatial connection between the source points of pollution and the possible sedimentation areas. Furthermore, mapping of olive mill waste tanks will positively improve the exercised methodology in term of assessing the potential risks of soil and groundwater pollution.

Potential rainwater harvesting improvement using advanced remote sensing applications.

The amount of water on earth is the same and only the distribution and the reallocation of water forms are altered in both time and space. To improve the rainwater harvesting a better understanding of the hydrological cycle is mandatory. Clouds are major component of the hydrological cycle; therefore, clouds distribution is the keystone of better rainwater harvesting. Remote sensing technology has shown robust capabilities in resolving challenges of water resource management in arid environments. Soil moisture content and cloud average distribution are essential remote sensing applications in extracting information of geophysical, geomorphological, and meteorological interest from satellite images. Current research study aimed to map the soil moisture content using recent Landsat 8 images and to map cloud average distribution of the corresponding area using 59 MERIS satellite imageries collected from January 2006 to October 2011. Cloud average distribution map shows specific location in the study area where it is always cloudy all the year and the site corresponding soil moisture content map came in agreement with cloud distribution. The overlay of the two previously mentioned maps over the geological map of the study area shows potential locations for better rainwater harvesting.

Quick Urban Flood Risk Assessment in Arid Environment Using HECRAS and Dam Break Theory: Case Study of Daghbag Dam in Jeddah, Saudi Arabia

Urban flood hazards are becoming a worldwide problem. The change in climatic conditions has caused serious threats to humanity, one of which is the unexpected severe floods.

Application of the random walk theory for simulation of flood hazards: Jeddah flood 25 November 2009

Hydrological and hydraulic modelling are becoming essential in the field of flood hazards. There are many models available in the literature among them HECHMS, MIKESHE, HECRAS, MIKEFLOOD, MIKE11, SWMM, DELFT3D, etc. Each of these models has its own advantages and disadvantages. In general, hydrological models are used to estimate the flood from a rainstorm, while hydraulic models are used to delineate the inundation zones. Solution of the governing equations for flood propagation is cumbersome and takes lots of time and efforts especially in two-dimensional domains in urbanised areas. In this paper, an efficient methodology based on the random walk theory is developed and programmed to delineate the inundation areas from a flood. The method is applied on the flood that happened on November 2009 in Jeddah city using a simplified city configuration. The results are plausible. The method can be further developed to simulate floods in a real city configuration.

Empirical equations for flood analysis in arid zones: the Ari-Zo model

Water resources all over the world are facing several problems such as scarcity, pollution, climate change, and global warming. Arid zones especially suffer from either severe drought or severe floods. Scientific analysis of flood events is difficult because of lacking flood measurement data and rainfall-runoff models that are suited for arid regions. Researchers in the field of hydrology are developing rainfall-runoff models for storm runoff predictions since 1932. However, it is noticeable that most research papers, books, and theses are considering studies in temperate regions, while arid zones are lacking such studies. The main objective of this paper is to derive a mathematical model called Ari-Zo, using regression analysis, to predict flood peaks, time to peak, and time of concentration from rainfall storms in arid zones. The data used in this study relied on storm measurements registered at Allith and Yiba basins and their subcatchments (eight subbasins) located in the southwestern part of Saudi Arabia. The stream flow data method has been used to derive the unit hydrograph in the Ari-Zo model from 36 storms. The study developed several mathematical relationships between the hydrological variables and the regional topography of the basins. The mathematical equations obtained from this study are the discharge peaking factor, time of concentration, and time to peak. The Ari-Zo model results are compared with the results of the National Resources Conservation Service (NRCS) method and showed substantial differences. The peaking factors of NRCS range between 0.0646 and 0.2582, while in Ari-Zo, it ranges between 0.0513 (low flood case) and 1.9465 (very extreme flood case). The ratio between the time to peak and the time of concentration in NRCS is equal to 0.667, while in Ari-Zo, it ranges between 0.05 and 0.5 and on average, it is 0.276. The parameters of time of concentration in Ari-Zo model are different from those of Kirpich equation. The study recommends using the Ari-Zo model for arid zone hydrological studies.