A model for estimating monthly and annual evaporation of Lake Qaroun was developed using the energy budget concept. The evaporation is estimated from the amount of solar radiation, atmospheric long-wave radiation, back radiation and evaporative energy. A modification is made to the energy equation to allow the calculation of evaporation from saline lakes by analyzing data from four evaporation pans with different salinities.The model simulations were checked against evaporation rates measured by Mankarous WF (1979. Hydrology of Lake Qaroun. MSc thesis, Faculty of Engineering, Cairo University, Cairo, Egypt). The monthly comparison shows that the model gives an acceptable accuracy with a relative error ranging from −12.4 to + 12.9%. The model produces reliable results in terms of annual prediction with a maximum percent error of 3% and the minimum of −2.7%. The standard deviation of differences indicates that there is a good probability of obtaining simulated values within 0.8 mm (in May) to within 22.2 mm (in December) of measured values.

Most geographical spatial analysis requires a continuous data set and this study is designed to create such a surface. Digital model of landscape is an important part within creation of geo-information systems. It is an important tool in applications, which model an Earth’s surface like geomorphology, hydrology, geology, cartography, ecology, etc. Many software products offer different interpolation methods for creation of digital model of landscape. Its accuracy and quality is impacted by selection of an interpolation method and precision input data. Several studies have demonstrated that various spatial interpolation techniques perform differently depending on the type of attribute, geometrical configuration of the samples, spatial resolution, world region, etc. Hence, selecting the best interpolation technique for each particular situation is a key factor. The major objective of this paper is to assess the spatial variability of elevation data in Iraq by comparing different interpolation procedures. The elevation data were interpolated using a deterministic method (Inverse square distance) and geostatistical methods in ArcGIS. Cross-validation is a sample reuse algorithm for quantitative comparison of experimental performance of alternative interpolation methods. Cross validation can help make an informed decision as to which method provides the best results. Two diagnostic statistics are mainly considered in this paper from the results mean error, and root mean square error.

The mapping of global solar radiation is important in designing of solar energy system and renewable energy applications, also the global solar radiation estimation and mapping will facilitate engineers and architect purposes and applications. In present paper measured and estimated global solar radiation data was employed. The estimation of global radiation data can give results with acceptable accuracy to establish solar maps of monthly radiation using Geographic Information Systems (GIS) software. Simple Kriging interpolation was used to derive radiation maps over Iraq.  Different models were employed, namely Spherical, Circular, and Gaussian. Solar radiation data for the years 1985,1990,1995,2000 and 2005 were used for the production of solar radiation maps over Iraq. On average, Iraq receives (5000) kWh/m2 of global solar radiation in year 2005. The highest global solar radiation is estimated at 6790kWh/m2 in September while the lowest is 1660 kWh/m2in December. Cross validation was used to find the best model by comparing the error criteria, namely MPE, RMS, MSPE, RMSS, and ASE. It was found the Spherical model gives best results according to the cross validation error criteria.Mapping Monthly Average Global Solar Radiation over Iraq Using GIS and Heliosat Model

Global environment change has become a worldwide concern in recent years. Rainfall is an important climatologically parameter, and knowledge of its temporal and spatial patterns is useful for researchers working in many disciplines, such as optimal management of agriculture, environment and related activities. Meteorological data coming from stations are the most reliable and used sources to assess the climate condition of an area. Historical records of monthly rainfall data for the time period 2003-2013 were acquired from the Iraqi Meteorological Organization and Seismology (IMOS). The long-term data were collected from 24 weather stations. To obtain optimal maps of rainfall we also used the Tropical Rainfall Measuring Mission (TRMM). In this paper we tried to explain the possibility of vector format KML and its properties for thematic mapping in Google Earth closer, which is used to display the resulting map outputs. Maps alone are compiled by the client using the Web site browser for transferring input variables to the server, where they are processed and map data is subsequently generated according to client requirements.

The design and operation of any solar energy system requires a good knowledge of the solar radiation data in a location. This data finds application in agriculture, climatology, meteorology, etc. Since the solar radiation reaching the earth’s surface varies with climatic conditions of a place, a study of solar radiation under local climatic condition is essential. Global solar radiation is of economic importance as renewable energy alternatives. In this research 14 Iraqi climatic stations radiation data were used for the years 2013 to 2015.  Data have been designed and calculated by using Excel.  ArcGIS 10.2 is used for spatial interpolation and mapping activities. Surface radiation map have been generated by using ordinary kriging interpolation technique. Different models are tested, namely Spherical, Gaussian and Circular model. Creation of digital grid maps makes it possible to obtain climatic information at any point, whether there is a weather station or not. Results show that the spherical model outperforms Gaussian and circular models.