Advances in Environmental and Engineering Research (AEER) is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. This periodical is devoted to publishing high-quality peer-reviewed papers that describe the most significant and cutting-edge research in all areas of environmental science and engineering. Work at any scale, from molecular biology through to ecology, is welcomed.

Main research areas include (but are not limited to):

  • Atmospheric pollutants
  • Air pollution control engineering
  • Climate change
  • Ecological and human risk assessment
  • Environmental management and policy
  • Environmental impact and risk assessment
  • Environmental microbiology
  • Ecosystem services, biodiversity and natural capital
  • Environmental economics
  • Control and monitoring of pollutants
  • Remediation of polluted soils and water
  • Fate and transport of contaminants
  • Water and wastewater treatment engineering
  • Solid waste treatment

Advances in Environmental and Engineering Research publishes a range of papers (original research, review, communication, opinion, study protocol, comment, conference report, technical note, book review, etc.). We encourage authors to be succinct; however, authors should present their results in as much detail as necessary. Reviewers are expected to emphasize scientific rigor and reproducibility.


Archiving: full-text archived in CLOCKSS.

Rapid publication: manuscripts are undertaken in 12 days from acceptance to publication (median values for papers published in this journal in 2021, 1-2 days of FREE language polishing time is also included in this period). 

Current Issue: 2023  Archive: 2022 2021 2020
Open Access Research Article

Surface Water Changes and Water Depletion of Lake Hamrin, Eastern Iraq, Using Sentinel-2 Images and Geographic Information Systems

Huda Jamal Jumaah 1,†, Mohammed Hashim Ameen 2,†, Bahareh Kalantar 3,†,*

  1. Department of Environment and Pollution Engineering, Technical Engineering College of Kirkuk, Northern Technical University, Kirkuk 36001, Iraq

  2. Department of Environmental Engineering, Engineering College, Tikrit University, Tikrit, Iraq

  3. RIKEN Center for Advanced Intelligence Project, Goal-Oriented Technology Research Group, Disaster Resilience Science Team, Tokyo, Japan

  4. † These authors contributed equally to this work.

Correspondence: Bahareh Kalantar

Academic Editor: Chao Chen

Special Issue: Remote Sensing Applications in Coastal Environments

Received: August 31, 2022 | Accepted: January 09, 2023 | Published: January 12, 2023

Adv Environ Eng Res 2023, Volume 4, Issue 1, doi:10.21926/aeer.2301006

Recommended citation: Jumaah HJ, Ameen MH, Kalantar B. Surface Water Changes and Water Depletion of Lake Hamrin, Eastern Iraq, Using Sentinel-2 Images and Geographic Information Systems. Adv Environ Eng Res 2023; 4(1): 006; doi:10.21926/aeer.2301006.

© 2023 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.


Iraq’s lakes and rivers are currently exposed to drought because of climatic and political conditions. This study uses satellite images and geographic information systems to display the water depletion and the change in the surface water area of Hamrin Lake. Sentinel-2 imagery of 2018 and 2022 was used to analyze the surface water area changes and water depletion. A comparison was made by studying the changes that happened between 2018 and 2022 respectively. Moreover, a supervised classification technique was implemented using the Support Vector Machine algorithm (SVM). Besides the shrinkage of Hamrin Lake was determined based on 2017 to 2022 Sentinel-2 images and the Normal Difference Water Index (NDWI). Findings showed an extreme change occurred in the surface water area of the lake, which had decreased by 73% in study years and changed to land in 2022. Based on the resultant maps clear alteration is notable in the shape of the lake from north to southeast where the maximum retraction occurred. The surface water area was 144 km2 in 2018 which decreased to 39 km2 in 2022 and was concentrated in the western part of the lake. Besides, the lake's capacity has become 234 million cubic meters, and the amount of water in it is very little while its capacity is more than two billion cubic meters. This sharp drop in the water level in the lake indicates that what is flowing to the lake is less than what is released from it, especially due to the lack of rain. In addition to the drought, the neighboring countries have taken measures to change courses, cut off some rivers, and build dams, all of which are additional influential factors that impose quick intervention and action to prevent the lake from drying out completely.

Graphical abstract

Click to view original image


Hamrin Lake; support vector machine; sentinel-2 images; water depletion; remote sensing

1. Introduction

The water issue is one of the necessary components for keeping the environmental structure balanced to provide all the human needs, particularly in countries characterized by dry and semi-dry weather such as Iraq, as water is a consequential resource in controlling the population distribution and economic activity, mainly in agriculture, thus it has an essential role in providing people with a needed food supply [1]. Satellite remote sensing images can greatly help monitor water surface dynamics of lakes and water bodies worldwide [2,3]. Iraq experienced severe drought in the past years and lost a large water capacity, as rainfall rates decreased by 40% from the normal level. In the same period, the water flow from the rivers decreased significantly due to Turkey’s project to build dams in the catchment of the Tigris River and irrigation projects and dams that are under construction in the sources of the Iranian Tigris River, which reduced the flow of rivers to Iraq in the future [4]. Using remote sensing data, studies were conducted on Iraq lakes, and the result was human and natural activities that made drastic alterations to the lakes' surface areas over the past years. These sudden changes recorded mainly were associated with policies of water management related to political events; on the other hand, the water level is low due to the lack of rain [5,6]. For example, based on six satellite images, the surface water area changes of Al-Razzazah lake were evaluated and mapped from 1989 until 2020, where the total surface area has turned out to be one-sixth of the previous area of 1989 [7]. While a study found a correlation between the rainfall rates and their effect on the water surface area of Hamrin Lake from 1990 to 2019, which showed the scarcity of rainfall is the most important factor affecting the water capacity [8]. Based on Hussein [1], used satellite images and area calculations and concluded that there is a discrepancy in the entire Hamrin lake area from year to year, with a clear increase in the water level being recorded in some years while a significant decrease was recorded in other years. Furthermore, Titolo [5], used the Normal Difference Water Index (NDWI) besides Sentinel-2 data for distinguishing the surface area to investigate the receding of lake Hamrin and deduced dramatic changes in the lake's shape. Updated data and accurate information are necessary to evaluate the results of changes [9]. For land cover detections, pixel-based classification algorithms have been developed [10]. The distinguished one involves Maximum Likelihood Classification, Support Vector Machine (SVM), and Decision Tree [11]. The classification type and training data attributes influence classification performance; these conditions must be carefully considered [12]. SVM classification reliability of hyper-spectral images has been approved in many papers [11,13].

Nowadays, Iraq suffers from a hot climate and scarcity of r; besides, the policy of neighboring to build dams and cut water sources from Iraq, all these negatively affect the water capacity of the lakes. In this study, we used remote sensing and GIS applications. We employed the SVM classifier to extract and calculate the surface water area and determine water levels in Hamrin Lake. It is important to conduct detailed research on the capacities of lakes over different years using modern systems that reveal the extent of change in surface area and volume of residual water to put control policies and avoid lake drying out.

2. Materials and Methods

2.1 Study Area

The study area is Hamrin Lake, a man-made lake known as Diyala dam, which lies in Diyala province, about 50 km northeast of Baquba [1]. Figure 1 represents the study area of the Hamrin Lake location. The capacity of Hamrin Lake is almost 3.95 billion m3, with a 445 km2 area [14]. It was constructed in 1981 and extends along the Diyala river, one of the Tigris tributaries which bonded between (34°22′ N, 44°49′ E) to (34°2′ N, 45°12′ E). Hamrin is subject to various changes in the surface area, occasionally affecting its actual shape. The most consecutive retraction of surface water area was recorded in 2008, when it decreased by 80%, because of damming of the Lund River by the neighboring country [5], and it reached 21.23 km2 as a surface area. In contrast, the maximum rate recorded in 1988 and the surface water area was 358.38 km2 [1].

Click to view original image

Figure 1 The study area Hamrin Lake location.

The lake is the source of irrigation for the city and agricultural lands, as eighty percent of the population depends on agriculture. The water scarcity crisis has caused the cancellation of agricultural plans and the collapse of the agricultural sector throughout the province, in addition to severe damage to livestock. The lake is considered the primary and main water source in Diyala Governorate, so it was important to conduct research and investigate the state of the lake with the advancing years to display the current status of the lake, which suffers from drought.

2.2 Methodology

The methods applied in the research are shown in Figure 2. Moreover, the dataset attributes of the used images are reported in Table 1.

Click to view original image

Figure 2 The methods applied in the research.

Table 1 The dataset attributes of the used images.

In this study, two Sentinel-2 images; of the years 2018, and the year 2022 were used, with (10 m) resolution and low cloud cover.

The spatial reference of the images was WGS_1984_UTM_zone_38N. The used Sentinel-2 Images in the study are shown in Figure 3.

Click to view original image

Figure 3 Sentinel-2 Images of Hamrin Lake of; (a) the year 2018, and (b) the year 2022.

Based on ARC-GIS version 10.3, a supervised SVM classification was applied. The principle of this method is to separate hyperplane creation from the trained data.

GIS includes useful tools and applications that facilitate the process of analysis and evaluation in addition to creating models [15,16,17,18,19,20] and detecting changes [7,11]. The classification process by SVM included creating training samples and then classifying the raster using the Esri classifier definition file (ecd.). This file involves the information necessary to establish a certain type of Esri-supported classification. To perform the classification, the input raster must match the same input raster used to create this ecd. file. The resulting land cover maps are then used for extracting areas for each year separately so the comparison can be applied usefully. The final step involved calculating water levels based on lake depth and extracted areas. The equation of SVM can be written as [11]:

\[ f(x)= {sign}\left(\sum_{i}^{r} \propto_{i} y_{i} x_{i}+b\right) \tag{1} \]

\[ f(x)= {sign}\left(\sum_{i}^{r} \propto_{i} y_{i} k\left(x, x_{i}\right)+b\right) \tag{2} \]

where a vector (xi) is of each r training case, it represents a spectral response composed of a description of the class item (yi) ∝i (i = 1, ..., r) are multipliers of Lagrange,k(x,xi) is the task of the kernel while b refers to hyperplane space from starting point [11].

Moreover, NDWI was used to compare changes based on Sentinel-2 Images from 2017 to 2022. This Index is used to monitor changes in water content for water bodies. Because bodies of water strongly absorb light in the visible to the infrared electromagnetic spectrum, NDWI adopts green and NIR near-infrared bands to shade water bodies. NDWI is sensitive to buildings and can result in the overestimation of water bodies. The NDWI function of Sentinel-2 can be written as follows:

\[ { Sentinel }-2_{N D W I}=(B 03-B 08) /(B 03+B 08) \tag{3} \]

For Sentinel-2 (B03) Band 3 represents green, and (B08) Band 8 represents NIR [21].

3. Results and Discussion

Based on NDWI, Figure 4 represents Hamrin Lake shrinkage from 2017 to 2022. Hamrin Lake's land cover map and differences between the two years 2018 and 2022 are shown in Figure 5. The surface area in 2018 was equal to 144 km2. It will became 39 km2 in 2022. The decrease can be seen on the maps.

Click to view original image

Figure 4 Hamrin Lake shrinkage from 2017 to 2022.

Click to view original image

Figure 5 Hamrin change map of; (a) year 2018, (b) year 2022, (c) Retraction rate.

The surface water area change map of Hamrin Lake in the years 2018 and 2022 has been shown in Figure 5(c). The area changes can be seen visually on the map, where substantial changes in the surface area happened in the year 2022. Figure 5(c) shows the retraction of the lake area from the north to the southeast. The area was retracted by 105 km2. Based on Khalaf [22] used NDWI and satellite images of Hamrin from 2019 to 2020 at the rate of one image per month and concluded that the highest water surface occupied 617.264 km2 in October, and the lowest surface occupied 202,140 km2 in September in September.

Furthermore, the water level was calculated based on obtained surface areas and lake depth. The calculated capacity in 2018 was 864 million cubic meters, while it decreased to 234 million cubic meters in 2022.

Monthly and Annual precipitation dataset from NASA/Modern-Era Retrospective Analysis of research and applications MERRA-2 of the dates 01/01/2018 to 12/31/2021 for (Hamrin Lake) was analyzed and studied in this research for location latitude 34.1943 and longitude 44.9975. MERRA-2 is the original long-term international analysis to incorporate meteorological assimilation, integrate space-based observation of aerosols, and designate their relations with other physical progress in the weather system. Figure 6 shows monthly and annual precipitation from NASA/MERRA-2 dataset. From Figure 6, we can see the precipitation lack in the latest years, especially in 2021 and 2020. The low rainfall periods have negative effects on lake continuity.

Click to view original image

Figure 6 Monthly and annual precipitation NASA/MERRA-2 precipitation sum (mm).

Furthermore, Figure 7 represents the trends in the sum annual precipitation of Hamrin Lake for four years (2018 to 2021).

Click to view original image

Figure 7 Trends in the sum annual precipitation of Hamrin Lake during four years.

Based on the NASA/MERRA-2 precipitation sum, the trends of surface water area were reported with a 0.99 R2 coefficient of determination. A high correlation of decreasing area each year imposes rapid intervention to develop appropriate strategies to prevent the drying up of the lake in the coming years. Hadi [8] showed a significant recorded correlation of 0.84 between rainfall and Hamrin lake’s water value. Besides, a study was conducted by Hadi et al., [23] in which they proved precipitation deficiency in a cumulative manner thru study years, and thus its effect on the drying up of rivers and lakes [23]. Moreover, based on Khalaf [22] lake Hamrin experienced a decrease in lake’s surface area, which threatens to dry up the lake, that consistent the current study results.

4. Conclusions

The study's goal was to calculate the surface water area of Hamrin Lake and its residual water level to date. The water cover was extracted using the SVM classification approach. The study concluded an extreme reduction in the lake’s surface area in the year 2022 with a very high retraction in water level. The negative effects of climate and rainfall scarcity during 2021 and 2022 have led to a change in the lake’s surface area with an alteration in the morphological shape of Hamrin Lake with a drop in water level. Besides these influential factors, the lack of water flowing into the lake and mismanagement also affected the lake's drought. In addition to the policies of neighboring countries in cutting the watercourse from the rivers towards Iraq. The water shortage in Hamrin Lake, the province’s first water source, reached 73 percent in the summer of 2022, meaning that a large part of the lake has dried up, negatively affecting agricultural areas due to the water crisis. One of the solutions is to supply the Diyala River which supplies the lake with water from the Tigris to avoid the destruction of agricultural lands so can slightly achieve the water demand requirements.


The authors acknowledge the use of annual and monthly rainfall data from the (NASA) Langley Research Center Forecast of Universal Energy Resource Project.

Author Contributions

Huda J. Jumaah and Mohammed H. Ameen acquired the data as well as conceptualized and performed the analysis; Huda J. Jumaah wrote the manuscript and discussed the analysis; Bahareh Kalantar edited, restructured, and optimized the manuscript.


This study didn’t receive any funding.

Competing Interests

The authors have declared that no competing interests exist.


  1. Husain Y. Monitoring and calculating the surface area of lakes in northern Iraq using satellite images. Appl Res J. 2016; 2: 54-62.
  2. Dastour H, Ghaderpour E, Hassan QK. A combined approach for monitoring monthly surface water/ice dynamics of Lesser Slave Lake via earth observation data. IEEE J Sel Top Appl Earth Obs Remote Sens. 2022; 4: 6402-6417. [CrossRef]
  3. Taheri DA, Valadan ZM, Ghasemi H, Ghaderpour E, Hassan QK. A new clustering method to generate training samples for supervised monitoring of long-term water surface dynamics using Landsat data through Google earth engine. Sustainability. 2022; 30: 8046. [CrossRef]
  4. Jaffar HD. Determination and measuring some of the physical and chemical parameters in the clay of Lake Hamrin, Iraq. Ibn Al-Haitham J Pure Appl Sci. 2017; 30: 34-42.
  5. Titolo A. Use of time-series NDWI to monitor emerging archaeological sites: Case studies from Iraqi artificial reservoirs. Remote Sens. 2021; 13: 786. [CrossRef]
  6. Dawood A, Kalaf Y, Abdulateef N, Falih M. Investigation of surface area of lakes and marshes from satellite images by using remote sensing and geographic information system integration in Iraq. MATEC Web Conf. 2018; 162: 03016. [CrossRef]
  7. Jumaah HJ, Ameen MH, Mohamed GH, Ajaj QM. Monitoring and evaluation Al-Razzaza Lake changes in Iraq using GIS and remote sensing technology. Egypt J Remote Sens Space Sci. 2022; 25: 313-321. [CrossRef]
  8. Hadi AS, Mohammed RS. The effect of change indicators in the amounts of rainfall on the water supply of Lake Hamrin in Diyala Governorate-Iraq-for the period 1990-2019. J Surra Man Raa. 2022; 18: 721-736.
  9. Congalton RG. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ. 1991; 37: 35-46. [CrossRef]
  10. Otukei JR, Blaschke T. Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms. Int J Appl Earth Obs Geoinf. 2010; 125: 527-531. [CrossRef]
  11. Jumaah HJ, Kalantar B, Ueda N, Sani OS, Ajaj QM, Jumaah SJ. The Effect of war on land use dynamics in Mosul Iraq using remote sensing and GIS techniques. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS; 2021 July 11-16; Brussels, Belgium. New York: IEEE. [CrossRef]
  12. Cerra D, Plank S, Lysandrou V, Tian J. Cultural heritage sites in danger-Towards automatic damage detection from space. Remote Sens. 2016; 8: 781. [CrossRef]
  13. Kavzoglu T, Colkesen I. A kernel functions analysis for support vector machines for land cover classification. Int J Appl Earth Obs Geoinf. 2009; 11: 352-359. [CrossRef]
  14. Abdulrazzaq ID, Jalut QH, Abbas JM. Evaluation of dam breach parameters using different approaches for earth-fill dam. In: Geotechnical engineering and sustainable construction. Singapore: Springer; 2022. pp. 135-144. [CrossRef]
  15. Jumaah HJ, Mansor S, Pradhan B, Adam SN. UAV-Based PM2.5 monitoring for small-scale urban areas. Int J Geoinformatics. 2018; 14: 61-69.
  16. Jumaah HJ, Ameen MH, Kalantar B, Rizeei HM, Jumaah SJ. Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, Malaysia. Geomatics Nat Hazards Risk. 2019; 10: 2185-2199. [CrossRef]
  17. Kalantar B, Ameen MH, Jumaah HJ, Jumaah SJ, Halin AA. Zab River (Iraq) sinuosity and meandering analysis based on the remote sensing data. Int Arch Photogramm Remote Sens Spat Inf Sci. 2020; XLIII-B3-2020: 91-95. [CrossRef]
  18. Ameen MH, Jumaah HJ, Kalantar B, Ueda N, Halin AA, Tais AS, et al. Evaluation of PM2.5 particulate matter and noise pollution in Tikrit University based on GIS and statistical modeling. Sustainability. 2021; 13: 9571. [CrossRef]
  19. Hamed HH, Jumaah HJ, Kalantar B, Ueda N, Saeidi V, Mansor S, et al. Predicting PM2.5 levels over the north of Iraq using regression analysis and geographical information system (GIS) techniques. Geomatics Nat Hazards Risk. 2021; 12: 1778-1796. [CrossRef]
  20. Habbeb MG, Sulyman MH, Jumaah HJ. Modeling water quality index using geographic information systems and weighted arithmetic index in Kirkuk, Iraq. Poll Res. 2022; 41: 323-327. [CrossRef]
  21. Kaplan G, Avdan U. Object-based water body extraction model using Sentinel-2 satellite imagery. Eur J Remote Sens. 2017; 50: 137-143. [CrossRef]
  22. Khalaf AB. Using remote sensing and geographic information systems to study the change detection in temperature and surface area of Hamrin Lake. Baghdad Sci J. 2022; 19: 1130.
  23. Hadi AM, Mohammed AK, Jumaah HJ, Ameen MH, Kalantar B, Rizeei HM, et al. GIS-based rainfall analysis using remotely sensed data in Kirkuk Province, Iraq: Rainfall analysis. Tikrit J Eng Sci. 2022; 25: 48-55. [CrossRef]
Download PDF Download Citation
0 0