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"Navigation Iraq"
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Improving the Accuracy of Local Gravimetric Geoid Modelling Using Simulated Terrestrial Gravity Data
Geodetic observations in any country or region require a precise local geoid model. Hence, this study has improved the geoid modelling using simulated terrestrial gravity data. However, the sparse and limited number of terrestrial gravity data is the primary reason for the inability to develop an accurate gravimetric geoid model in Iraq, including within the Sulaymaniyah Province selected as the case study in this research work. The ability to use the global navigation satellite system (GNSS) to determine orthometric height has been restricted due to the lack of precise geoid models within the region. Hence, 3327 gravity points from several international and local datasets were applied, 160 of which were collected via gravity survey, to simulate and model the gravity in the Sulaymaniyah Province. A stepwise multiple linear regression with a correlation coefficient (r) of 0.997 and a determination coefficient of (R2) of 0.993 (both very close to 1) was deployed to extract the geographical coordinates and the orthometric height of the points to formulate a cutting-edge gravity model. Next, 120 local gravimetric models were generated using software from KTH (a university in Sweden) with two conditions: (1) the simulated gravity data were composed of a variety of grid and cap sizes, and (2) both the interpolated gravity data and the terrestrial data were combined with the downloaded World Gravity Map 2012 (WGM2012) data. Next, ITU_GRACE16 and IGGT_R1 global geoid models (GGMs) were used to support the cap size area. As the quadratic model fit the 11 available global positioning system (GPS)-levelling points, the simulated gravity data revealed the lowest root mean square error (RMSE) result of ± 17 cm when using IGGT_R1 GGM, in comparison to the other two datasets. Meanwhile, EGM2008 scored an RMSE of ± 31 cm. In conclusion, this new data entry method improves the accuracy of local geoid models by mathematically simulating the gravity data instead of interpolating them.
Journal Article
Estimation the Physical Variables of Rainwater Harvesting System Using Integrated GIS-Based Remote Sensing Approach
Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.
Journal Article
Groundwater potential mapping at northeastern Wasit and Missan governorates, Iraq using a data-driven weights of evidence technique in framework of GIS
In this study, a data-driven weights of evidence (WOE) technique was used to demarcate groundwater potential zones at northeastern Missan and Wasit governorates, Iraq using geographic information system (GIS) platform. In the first step, borehole location inventory map consisting of 143 with relatively high yield (>8 L/s) was prepared. Then, eight influencing groundwater factors, namely altitude, slope, geology, land use/land cover, distance to roads, distance to faults, aquifer type, and depth of wells were prepared and integrated into spatial database. The spatial association between borehole locations and each influencing groundwater factors were analyzed and discussed. For the analysis of groundwater productivity, the studentised contrast C/S(C) of each groundwater factors were spatially overlaid and weighted summed to produce groundwater potential index (GWPI) map. The resulting map was classified into four categories: low, moderate, high, and very high according to natural break classification scheme. The low GWPI zone covers 30 % (2,215 km²). The moderate, high, and very high cover 32 % (2,349 km²), 23 % (1,649 km²), and 15 % (1,075 km²) of the total study area, respectively. The high and very high zones cover approximately 40 % of the study area indicating moderate productivity of the aquifer system in the study area. The results of the analysis were validated using receiver operating characteristic (ROC) technique. The areas under the ROC curve (AUC) for success and prediction rates were 0.81 and 0.80, respectively, indicating the high capability of WOE for modeling groundwater potentiality in the study area. Result of this study could be used as guide to manage aquifers in these areas and serve as indicator for sustainable management of aquifer systems.
Journal Article
Identification of suitable sites for groundwater recharge in Awaspi watershed using GIS and remote sensing techniques
Groundwater is a valuable natural resource for drinking, domestic, livestock use, and irrigation, especially in arid and semi-arid regions like the Garmiyan belt in Kurdistan region. The Awaspi watershed is located 50 km east of Kirkuk city, south Kurdistan, Iraq; and covers an area of 2146 km2. The paper presents result of a study aimed at: (1) mapping and preparing thematic layers of factors that control groundwater recharge areas, and (2) determination of sites suitable for groundwater recharge. We used available data such as geological map, groundwater depth map, digital elevation model (DEM), Landsat 8 imagery, and tropical rainfall measuring mission (TRMM) data for this study. These data, supplemented by slope features, lithology, land use land cover, rainfall, groundwater depth, drainage density, landform, lineament density, elevation and topographic position index, were utilized to create thematic maps to identify suitable areas of groundwater recharge, using GIS and remote sensing techniques. Analytic hierarchy process (AHP) was applied to weight, rank, and reclassify these maps in the ArcGIS 10.3 environment, to determine the suitable sites for groundwater recharge within the Awaspi watershed. Fifty-five percent of the total area of the watershed was found to be suitable for groundwater recharge; whereas 45% of the area was determined to have poor suitability for groundwater recharge, but can be used for surface water harvesting.
Journal Article
Optimization of area–volume–elevation curve using GIS–SRTM method for rainwater harvesting in arid areas
The major limitation in planning water harvesting is the lack of knowledge in the estimation of surface area and storage volume at any depth of dam reservoir. The area–volume–elevation (AVE) curve of a reservoir plays a key role in estimating the most suitable depth, optimum surface area and highest capacity of reservoir storage. The existing methods to estimate the AVE curve are costly and time-consuming and require laborious work. This study attempts to develop a method to optimize the AVE curve for earth dams, using the digital elevation model generated by the Shuttle Radar Topography Mission (SRTM) data, and integrate it with the geographic information system (GIS), known as the GIS–SRTM. The proposed method was tested using field data in the Western Desert of Iraq, which is an arid environment. Three constructed small earth dams were selected for this study. The AVE curves were extracted for Horan 2 (H2), Al-gara 2 (G2) and Al-gara 4 (G4) earth dams. Comprehensive analyses have been carried out to evaluate the performance of the AVE curves using the proposed GIS–SRTM method and the field data. From the comparison, the proposed GIS–SRTM method was able to produce reliable AVE curves with a relative error less than 20%. Additionally, the proposed method was less time-consuming and the AVE curves can be visualized immediately. The proposed GIS–SRTM method is relatively supportive in analyzing spatial data to select the optimal site for rainwater harvesting and prevent excessive evaporation losses.
Journal Article
Meteorological drought analysis in northern Iraq using SPI and GIS
Droughts are major natural disasters for many parts of the world. Iraq is one of the countries which are recently facing frequent severe drought events, especially the northern region which is considered as the breadbasket of the country. Successful management of water in droughts needs understanding its causes and development. The study aimed to discuss the effects of drought with its features; frequency of occurrence and spatial distribution, to recognize drought covered areas’ distribution and drought impact on the northern region of Iraq. The study utilizes the standardized precipitation index (SPI) at different time scales, i.e., 3, 6, 12, and 24-month, to analyze the meteorological drought. Monthly rainfall data for the period 1937–2010 were utilized from nine meteorological stations scattered in the study area to assess SPI values. Drought distribution within the study area with different time scales was mapped employing the geographic information system. Our results showed that the study area has suffered from frequent severe drought events, which were hitting in nearly every decade, and the most severe drought periods were during the years 1997–2001 and 2006–2010. The results exposed that most of the drought events fall in mild drought category according to the SPI classification. Besides, it has been shown that the eastern part of the study area has experienced many severe droughts considering accumulated deficits and drought period length. However, the severe drought events were much harmful on the western part of the study area due to its low annual rainfall rates.
Journal Article
Fault, Responsibility, and Administrative Law in Late Babylonian Legal Texts
This book presents a reassessment of the governmental systems of the Late Babylonian period—specifically those of the Neo-Babylonian and early Persian empires—and provides evidence demonstrating that these are among the first to have developed an early form of administrative law.
The present study revolves around a particular expression that, in its most common form, reads ḫīṭu ša šarri išaddad and can be translated as “he will be guilty (of an offense) against the king.” The authors analyze ninety-six documents, thirty-two of which have not been previously published, discussing each text in detail, including the syntax of this clause and its legal consequences, which involve the delegation of responsibility in an administrative context. Placing these documents in their historical and institutional contexts, and drawing from the theories of Max Weber and S. N. Eisenstadt, the authors aim to show that the administrative bureaucracy underlying these documents was a more complex, systematized, and rational system than has previously been recognized.
Accompanied by extensive indexes, as well as transcriptions and translations of each text analyzed here, this book breaks new ground in the study of ancient legal systems.
eBook
A novel geographical information system-based Ant Miner algorithm model for delineating groundwater flowing artesian well boundary: a case study from Iraqi southern and western deserts
The Ant Miner algorithm was compared with the bivariate frequency ratio (FR) and boosted regression trees (BRT) algorithms in terms of its capacity to assess groundwater potential. A geospatial dataset was prepared that contains two components: a flowing well inventory map and eleven factors relevant to groundwater conditions. Average nearest neighbor technique was used to investigate the spatial pattern of flowing wells and to find the appropriate distance between flowing and nonflowing points in the study area. A wrapper approach known as
random forest classifier
and a filtering approach known as
information gain ratio
were used to identify the most relevant groundwater factors. The developed models were validated via the area under the operating characteristic curve. Results revealed that the Ant Miner model performed better in terms of both success (0.944) and prediction (0.92) rates compared to FR and BRT. Furthermore, the Ant Miner algorithm derived five simple, easily interpreted rules for predicting groundwater potential that can be used by hydrogeologists for identifying potential groundwater well locations with minimal effort and cost.
Journal Article