Drought Assessment Using GIS and Remote Sensing in Amman-Zarqa Basin, Jordan

This study aims at assessing drought for Amman-Zarqa basin, north Jordan. This basin is one of the important basins in Jordan where most of the agricultural and hydrological activates are located. During the last decades, Amman-Zarqa basin had faced a high variability of the rainy season which starts every year in October and ends in April. The main objective of this research is to find out if this basin is currently facing drought conditions. Two different drought indices were used in this study; these are the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) to evaluate drought using rainfall data and satellite images. Geographical information systems (GIS) software were used in this study to; 1) Create spatial digital database to hold meteorological information for the study area, 2) Generate thematic layers representing spatial distribution of drought for both SPI and NDVI and 3) Delineate areas with high drought risk using SPI and NDVI and compare the results of both models . The results obtained from this study show that Amman-Zarqa basin is currently facing drought conditions. Furthermore, it was concluded that the combination of various indices offer better understanding and better monitoring of drought conditions for semi-arid basins like Amman-Zarqa Basin

Integrated Approach for Groundwater Exploration in Wadi Araba Using Remote Sensing and GIS

Jordan has been recently classified as the fourth poorest country of water resources. Natural and human factors are affecting and increasing the stresses on these resources. Jordan had suffered from the continuous drought periods over the time. Furthermore, unbalanced demand vs. supply is always present as a result of high population growth rate. This study aims at the exploration of new water resources through the investigation of hydrogeological and groundwater resources in Wadi Araba Basin (Northern and Southern Wadi Araba Basins). The integration of Geographic Information Systems (GIS) and data extracted from earth observation satellites with additional collateral data, coupled with selected field investigations and the geological knowledge of the area under investigation, provides a powerful tool in groundwater exploration. Weighted overlay modeling technique was used to develop a groundwater potential model with six weighted and scored parameters. The results of this model were calibrated against observed data collected from the existing wells’ information. The results obtained from this model show that about 40% of the study area was classified as having a good potential for groundwater exploration. The spatial distribution of these areas is highly correlated with the location of the existing groundwater wells. The generated groundwater potential map shows that there is a lot of unexplored areas that have a good potential for groundwater exploration

Hydrological modeling of ungauged wadis in arid environments using GIS: a case study of Wadi Madoneh in Jordan

Runoff is one of the most important hydrological variables used in most of the water resources applications. Reliable prediction of runoff from land surface into streams and rivers is diffi cult and time consuming to obtain for ungauged basins. However, Remote Sensing (RS) and Geographic Information System (GIS) technologies can augment to a great extent the conventional methods used in rainfall-runoff studies. These techniques can be used to estimate the spatial variation of the hydrological parameters, which are useful as input to the rainfall-runoff models. The main objective of this study was to model the rainfall-runoff process in a selected ungauged basin for the purpose of groundwater artifi cial recharge. This model simulation was carried out using an hydrological modeling system assisted by GIS. Two model runs were carried out using precipitation data of the Intensity-Duration-Frequency (IDF) curves at Zarqa rainfall station for 10 years and 50 years return periods. With the fi rst model run, the total direct runoff volume and the peak discharge for the 10 years return period were estimated to be 151,000 m3 and 5.43m3/s, respectively. For the 50 years return period, the total direct runoff volume and the peak discharge were estimated to be 280,000 m3 and 12.77m3/s, respectively. The model was optimized against observed runoff data, measured during a storm event that occurred between the 2nd and the 4th of April, 2006. The fl ow comparison graph indicates that the calibrated model fi ts well with the observed runoff data, with a peak-weighted root mean square error (RMS) of less than 2%. This calibration was performed by applying different curve numbers in the simulated model. It was possible to obtain a reasonable match between the simulated and the observed hydrographs.El escurrimiento es una de las variables hidrológicas más importantes que se emplea en la mayoría de los usos de los recursos de agua. La obtención de una predicción confi able del escurrimiento superfi cial hacia corrientes y ríos en cuencas sin datos de aforo es un proceso difícil que consume mucho tiempo. Sin embargo, las tecnologías de percepción remota y los Sistemas de Información Geográfi ca (SIG) pueden complementar en gran medida a los métodos convencionales en estudios de lluvia-escurrimiento. Estas técnicas pueden ser aplicadas para estimar la variación espacial de los parámetros hidrológicos que se emplean en modelos de lluvia-escurrimiento. El objetivo principal de este estudio fue modelar el proceso de lluvia-escurrimiento en una cuenca sin datos de aforo con el propósito de evaluar su potencial para la recarga artifi cial del agua subterránea. Este modelo de simulación se realizó usando un sistema de modelado hidrológico apoyado por SIG. Se obtuvieron dos modelos usando datos de precipitación de las curvas de Intensidad-Duración-Frecuencia (IDF) de la estación de Zarqa para períodos de retorno de 10 años y de 50 años. Con el primer modelo, el volumen directo total del escurrimiento y la descarga máxima, o pico, para el período de retorno de 10 años fueron estimados en 151,000 m3 y 5.43m3/s, respectivamente. Para un período de retorno de 50 años, se estimó un volumen directo total del escurrimiento de 280,000 m3 y una descarga máxima de 12.77m3/s. El modelo fue optimizado contra datos observados de escurrimiento, medidos durante una tormenta que ocurrió entre el 2 y el 4 de abril de 2006. El gráfi co de comparación del fl ujo indica que el modelo calibrado presenta un buen ajuste con los datos observados de escurrimiento, puesto que el error estándar ponderado (peak weighted root mean square error) es menor que 2%. Esta calibración se realizó aplicando diversos números de curvas en la simulación. Fue posible obtener un ajuste razonable entre los hidrogramas simulados y los observados

Hydrological Modeling of Ungauged Wadis in Arid Environments Using GIS: A Case Study of

ABSTRACT Runoff is one of the most important hydrological variables used in most of the water resources applications. Reliable prediction of runoff from land surface into streams and rivers is diffi cult and time consuming to obtain for ungauged basins. However, Remote Sensing (RS) and Geographic Information System (GIS) technologies can augment to a great extent the conventional methods used in rainfall

Vulnerability Hotspots Mapping for Enhancing Sanitation Services Provision: A Case Study of Jordan

Enhancing sanitation services is a major challenge for sustainable development and plans. This work aims at developing a vulnerability hotspot mapping for improving sanitation services provision in Jordan based on a multi-weighted criteria model. Multiple spatial, physical, demographic, social, economic, and sanitation data were collected and compiled using GIS. We also considered experts’ and stakeholders’ opinions to determine the necessary indicators needed to develop Sanitation Hotspot Index (SHI). We used the Analytic Hierarchy Process (AHP) analysis to assign the relative weights of ten criteria. We also checked the consistency of AHP results. We found that the sanitation and population density got the highest relative weights, while soil hydraulic conductivity got the lowest. Based on the results of AHP, we developed two SHI mapping for two administrative levels: district and neighborhood levels. The maps classified the sanitation vulnerability into five classes ranging from most vulnerable to least vulnerable. The developed SHI maps can be used as a decision support tool for decision-makers and planners to allocate the necessary funds and orient the aids from donors and international agencies to enhance sanitation services in the country’s most vulnerable areas