Inicio  /  Water  /  Vol: 8 Par: 4 (2016)  /  Artículo
ARTÍCULO
TITULO

Geospatial Techniques for Improved Water Management in Jordan

Jawad T. Al-Bakri    
Sari Shawash    
Ali Ghanim and Rania Abdelkhaleq    

Resumen

This research shows a case from Jordan where geospatial techniques were utilized for irrigation water auditing. The work was based on assessing records of groundwater abstraction in relation to irrigated areas and estimated crop water consumption in three water basins: Yarmouk, Amman-Zarqa and Azraq. Mapping of irrigated areas and crop water requirements was carried out using remote sensing data of Landsat 8 and daily weather records. The methodology was based on visual interpretation and the unsupervised classification for remote sensing data, supported by ground surveys. Net (NCWR) and gross (GCWR) crop water requirements were calculated by merging crop evapotranspiration (ETc), calculated from daily weather records, with maps of irrigated crops. Gross water requirements were compared with groundwater abstractions recorded at a farm level to assess the levels of abstraction in relation to groundwater safe yield. Results showed that irrigated area and GCWR were higher than officially recorded cropped area and abstracted groundwater. The over abstraction of groundwater was estimated to range from 144% to 360% of the safe yield in the three basins. Overlaying the maps of irrigation and groundwater wells enabled the Ministry of Water and Irrigation (MWI) to detect and uncover violations and illegal practices of irrigation, in the form of unlicensed wells, incorrect metering of pumped water and water conveyance for long distances. Results from the work were utilized at s high level of decision-making and changes to the water law were made, with remote sensing data being accredited for monitoring water resources in Jordan.

 Artículos similares

       
 
Abdulrahman Mubarark AlAli, Abdelrahim Salih and Abdalhaleem Hassaballa    
This paper aimed to map areas prone to flooding in the Wadi Hanifah drainage basin located in the Riyadh region, and identify the most important factors that contribute to flooding through examining the influence of ten topographical, hydrological, and e... ver más
Revista: Water

 
Cédric Roussel and Klaus Böhm    
Explainable Artificial Intelligence (XAI) has the potential to open up black-box machine learning models. XAI can be used to optimize machine learning models, to search for scientific findings, or to improve the understandability of the AI system for the... ver más

 
Durlov Lahon, Dhrubajyoti Sahariah, Jatan Debnath, Nityaranjan Nath, Gowhar Meraj, Pankaj Kumar, Shizuka Hashimoto and Majid Farooq    
The alteration of land use and land cover caused by human activities on a global scale has had a notable impact on ecosystem services at regional and global levels, which are crucial for the survival and welfare of human beings. Merbil, a small freshwate... ver más

 
Rokaya Eltehewy, Ahmed Abouelfarag and Sherine Nagy Saleh    
Rapid damage identification and classification in disastrous situations and natural disasters are crucial for efficiently directing aid and resources. With the development of deep learning techniques and the availability of imagery content on social medi... ver más

 
Polina Lemenkova and Olivier Debeir    
This paper addresses the issue of the satellite image processing using GRASS GIS in the mangrove forests of the Niger River Delta, southern Nigeria. The estuary of the Niger River Delta in the Gulf of Guinea is an essential hotspot of biodiversity on the... ver más