Using Remote Sensing and Geographic Information Systems to Study the Change Detection in Temperature and Surface Area of Hamrin Lake

: This study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44 º 53ʹ 26.16 '- 45º 07 ʹ 28.03 ʺ and 34º 04ʹ 24.75 ʺ ــ 34º 19ʹ 12.74 ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km 2 for October and the lowest surface area 140.202 km 2 for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on bands 10 (Thermal Infrared 1) and 11 (Thermal Infrared 2) that are sensitive to thermal radiation, as the highest surface temperature reached in June 45.49°C degrees Celsius due to the high temperatures for this month and the lowest in February 3.09°C degrees Celsius, which is one of the months in which temperatures drop to the lowest level. The utilization of remote sensing and GIS innovations has helped a lot in checking changes, whether in surface area or temperature, which saves effort, time and cost. The results of this study put decision makers in taking the necessary precautions for the seasons of water scarcity and drought to meet the community’s water needs in the areas of multiple human consumptions and at the same time take advantage of rainy seasons and water abundance to develop long-term strategic plans to maintain a sustainable water balance.


Introduction:
Water bodies are among the important phenomena on the earth's surface in that studies and measurements can be made through remote sensing techniques and geographic information systems 1 . Lakes act as basic components of the hydrological cycle and local ecosystems, and provide for human needs such as tourism, attractions, fishing, agricultural purposes, sources of freshwater and electric power generation. Changes in the lake area are highly sensitive to both climate change and human activities, spatial analysis techniques can help to estimate, and manage water 2 , there is great importance in mapping lakes and accurately estimating their area changes because they contribute not only to understanding the significance of lake changes, but also the use and protection of lake water resources 3,4 .
The most important factor affecting the water balance of lakes is the temperature, as the high temperature leads to an increase in evaporation from the lakes and is accompanied by the scarcity and scarcity of sources for their regeneration, especially in dry and semi-arid regions characterized by high temperatures that lead to an increase in evaporation rates as is the case in the study area. An assessment of the water temperature in the lakes is essential to understanding their function and environmental condition. Additionally, LST is a proxy for analyzing water quality conditions and the impact of climate change on these systems. Although satellite-derived water temperature is a description of LST only in the upper layer (that is, about 100 meters upper, called "skin temperature"), it may provide important information about patterns of changes in water temperature in lakes, and it may be used in many studies, such as analysis of temperature patterns and heat balance, the spatial distribution of water quality variables, estimation of evaporation, spatial gradients LSWT, temporal variation, LST patterns, and climate change over lakes 5,6 .
Land surface temperature (LST) is an important biophysical parameter in surface energy processes and water balance at the regional level and global scales 7 , and is one of the most important switches in hydrology, meteorology, and surface energy balance 8 , It is one of the most important environmental criteria used to determine the exchange of energy and matter between the Earth's surface and lower atmosphere. LST is widely used to determine soil moisture content, to assess daily temperature change, to calculate surface long wave radiation to account for different types of evaporation 9,10 .
An enormous number of studies present various calculations and techniques for LST recovery from Landsat, a portion of these calculations have likewise been applied in programming devices, for instance, there is a module for open source programming GIS. LST processes from Landsat 5, 7, and 8. Instruments like the ERDAS program have been created. Nonetheless, these instruments require programming establishment and, in particular, they require crude establishment satellite information downloads, which can be amazingly tedious 11,12 .
Conventional strategies for estimating (field estimations) of lake water quality guarantee the ID of elements influencing the quality (Such as pollution by heavy metals, organic compounds, salinity...etc.), yet they are tedious and costly, or more everything, they don't give a spatial picture to help evaluation and observing of lake water quality. This issue was settled because of the simultaneous utilization of conventional field estimations and current far off detecting techniques, the last guides with the assortment of fast, transient and total information on water bodies and the execution of a spatial guide and fleeting evaluation of oceanic biological systems 13,14 . Because of the absence of far off observing of lake water levels, remote sensing addresses a helpful and powerful option technique. Remote sensing data have been progressively used to screen and assess constant unique changes in enormous waterways inside dry grounds and can give valuable evaluations of the lake's water balance just as yearly rates for water misfortune 15 . The utilization of remote sensing methods plans to see the elements of changes in height and surface space of water in lakes, which is a successful method to furnish data spatially and with high exactness 16,17 . Calculating LST from remote sensing images is important because it illustrates most of Earth's physical, chemical, and biological processes 18 . There is a developing mindfulness among ecological researchers that remote sensing can and should assume a part in giving information important to evaluate the states of environments and change in them 19 . Remote sensing is an important way to follow in surface waters. It has the benefit that it tends to be applicable in relation to other direct estimates, and gives images of continuous cycles, yet it can also capture the temporal and spatial changes of surface waters. 20 .
Hamrin Lake is a lake located in Diyala province, eastern Iraq. The lake follows the Hamrin Dam, which is located on the Alwand River in Diyala Governorate, which was inaugurated in June 1981 with the aim of protecting Diyala River Basin cities from seasonal floods. Hamrin Lake is located to the east of Saadia and is the strategic reservoir of water in Diyala 21 . The lake currently supplies more than 70% of Diyala regions with drinking and irrigation water.
The aim of the research is to assess the spatial and temporal differences of temperature and surface area in Lake Hamrin using Landsat 8 OLI / TIRS multi-spectral satellite images, and to know the extent of the ability of the NDWI to estimate the surface area of Lake Hamrin and compare it to the actual water level Work Material and Methods:

Study area:
The study area was determined through field visits, using the GPS tool and with the help of Google Earth, as Hamrin Lake is located in Diyala Governorate, eastern Iraq, between latitudes 44 º 53ʹ 26.16 '-45º 07 ʹ 28.03 ʺ and 34º 04ʹ 24.75 ʺ ‫ــ‬ 34º 19ʹ 12.74 ʺ . Fig. 1 shows the location of Lake Hamrin. The satellite images of the study area were used for the period from October 2019 to September 2020 (a water year), which amounted to 12 images (for band 10 and 11) of the Landsat 8 multi-spectral satellite, at an average of one image per month of the study period, as shown in

Spectral indices utilized in the study: "Normalized Differences Water Index (NDWI)"
The reflectivity of water is high in the green frequency (0.52-0.60) μm and very little in the close to infrared frequency range (0.76-0.90) μm. The high reflectivity of the plant and soil in the infrared frequency range makes the NDWI esteems positive for water regions are thus enlightened and have positive qualities in NDWI when green and building regions seem dim and dark with negative or zero qualities (3) . The NDWI was calculated using the following equation 22  The surface area of the lake was calculated from each satellite image based on NDWI, which made it easy to determine and extract the outer limits of the lake water, and to draw the water body for it using ArcMap 10.8. Table. 2 shows the statistical measures of the NDWI for the lake and for each month, the numbers and statistical measures in table were calculated in the ArcMap 10.8 program.

"Normalized Difference Vegetation Index (NDVI)":
It is quite possible that most notable unearthly and plant indices are utilized in the investigation of vegetation. It has been utilized widely in the investigation of worldly and spatial and temporal elements of vegetation cover. The NDVI record depends on the unearthly qualities of vegetation, contrasted with sans vegetation regions. Red strongly absorbs and reflects infrared rays. This is caused by the chlorophyll found in green leaves. Thus, areas with dense vegetation cover their horrific properties in the infrared, and areas with less thicker vegetation or devoid of vegetation. The NDVI profile is selected based on the discrimination in the measurement of radiation reflected in the closure by the red channels and the infrared channels divided by the amount of appearance in the two channels. "The value of the NDVI index is between -1 and + 1, the value of which is close to 1 (0.

Calculation of LST from satellite images:
At first, the Geometric and Radiometric remedy and Enhancement measures for the satellite data utilized in the examination were performed utilizing the Erdas Imagine 2015 program, depending on the two thermal bands B10 and B11 from each satellite image. The surface temperature of the lake water was calculated during the study period and as follows: 1-The numerical values of DN of each pixel in the image for the two thermal bands were converted to the values of DN to Radiance using the following equation 25 : where Lλ= is radiative reflection (m 2 * sr * m), ML = is Standardization factor specific to each package, Qcal = The numeric value of the pixel, AL = Correction factor 2-The temperature was calculated at the satellite TOA (Top of Atmospheric brightness highest temperature) Utilizing the following equation 26  Pv=square ((NDVI-NDVI min )/(NDVI max -NDVI min )). .... 6 Where: NDVI min It is the lowest value of 0.2 NDVI for soil exposed pixels and NDVI max It is the highest value of NDVI 0.5 for a healthy vegetable pixel, Pv = The percentage of vegetation cover 4-The surface temperature was calculated using the following equation 25 : LST=TB / (1+ (L *TB/P) *Ln(e)) .... 7 Where LST = Land Surface Temperature, P= (14380) Fixed value, e = 0.004 * Pv + 0.986 The emission correction factor is a constant value 5-The above calculations were made for bands 10 and 11 of each image, and then the average was taken from them, and thus the surface temperature of Lake Hamrin was extracted 27,28 .

Results and Discussion:
In this study, the NDWI index was adopted in determining the water body of Lake Hamrin and its area in each image, as shown in Figs. 2, 3 and 4.  Table. 3 shows the area of the lake calculated from the satellite images and the height of the water level inside the lake with the date of taking each image, as these levels were obtained from official departments. It is noted from Table 3  To extract the surface temperature of the lake from each spatial image and for each month of the study period (from the beginning of October 2019 until the month of September 2020) we used ArcMap 10.8 for this purpose, as in Figs. 5, 6 7, and Table 3.   It is noticed from Fig. 3 and Table. 4 that the temperature varies, as the temperatures at the edges of the lake are higher than the middle, due to the change in depth.

Conclusions:
The conclusion drawn from this study is there is change in the surface area and temperature of Lake Hamrin water throughout the year and is related to the seasons of the year and the rise and fall of the temperature, as the highest surface temperature reached in June 45.49 degrees Celsius due to the high temperatures for this month and the lowest in February 3.09 degrees Celsius, which is one of the months in which temperatures drop to the lowest level. The availability of rain that increases the surface area, and the consumption of lake water for various human activities leads to a decrease in the surface area, as it reached the highest surface area 264.617 km 2 for the month of October and the lowest surface area 140,202 km 2 for the month of September. The utilization of remote sensing and GIS innovations has helped a lot in checking changes, whether in surface area or temperature, which saves effort, time and cost. The results of this study put decision makers in taking the necessary precautions for the seasons of water scarcity and drought to meet the community's water needs in the areas of multiple human consumptions and at the same time take advantage of rainy seasons and water abundance and develop long-term strategic plans to maintain a sustainable water balance. The study recommends expanding the use of geospatial technologies to study the aquatic environment and follow-up the annual changes that occur in the surface area and temperature of Hamrin Lake, which helps decision makers to take the necessary measures to maintain water sustainability.