The Impact of Spatiotemporal Changes in Land Development (1984–2019) on the Increase in the Runo ﬀ Coe ﬃ cient in Erbil, Kurdistan Region of Iraq

: Nowadays, geospatial techniques are a popular approach for estimating urban ﬂash ﬂoods by considering spatiotemporal changes in urban development. In this study, we investigated the impact of Land Use / Land Cover (LULC) changes on the hydrological response of the Erbil basin in the Kurdistan Region of Iraq (KRI). In the studied area, the LULC changes were calculated for 1984, 1994, 2004, 2014 and 2019 using the Digital Elevation Model (DEM) and satellite images. The analysis of LULC changes showed that the change between 1984 and 2004 was slower than that between 2004 and 2019. The LULC analysis revealed a 444.4% growth in built-up areas, with a 60.4% decrease in agricultural land between 1984 and 2019. The inﬂuence of LULC on urban ﬂoods caused by di ﬀ erent urbanization scenarios was ascertained using the HEC-GeoHMS and HEC-HMS models. Over 35 years, there was a 15% increase in the peak discharge of outﬂow, from 392.2 m 3 / s in 1984 to 450 m 3 / s in 2014, as well as the runo ﬀ volume for a precipitation probability distribution of 10%, which increased from 27.4 mm in 1984 to 30.9 mm in 2014. Overall, the probability of ﬂash ﬂoods increased in the center of the city due to the large expansion of built-up areas.


Introduction
Since the last decades of the twentieth century, Remote Sensing (RS) has become a popular approach for detecting LULC changes. RS imagery has been universally applied in urban expansion and environmental analysis, with a large number of functional and sophisticated strategies being developed [1]. LULC classification plays an essential role in research on the physical and social sciences concerning urbanization and soil mapping [2]. LULC is an essential parameter for detecting human activities and natural changes due to climate change. LULC change detection is valuable for a broad variety of subjects, such as urban development, coastal dynamics, deforestation monitoring, shoreline changes and river transportation using multitemporal satellite images [3][4][5]. LULC changes are affected by human beings seeking to meet different needs, for instance, residential, agricultural, industrial, mining and other infrastructural facilities, and as such are main concerns connected with the economic and sustainable development of a region [6,7]. The timely and precise detection and identification of changes in the Earth's surface provide a foundation for a deeper understanding of human-nature interactions and correlations [8][9][10][11][12][13]. Formerly, in situ data had been used for studying LULC, although such kinds of data are inadequate in a spatial and temporal extent. It is also hard, if not impossible, to collect data from unreachable areas. Thus, data collection is drawn-out and often expensive. Therefore, such data are not dependable for effective planning and decision-making [14,15].
in the different parts of the city to assist in any possible land development planning, flood control and resource management. Assessing, identifying and classifying LULC changes in Erbil Province, and particularly how rapid urban development affects the center of the city, would contribute to managing the hydro-structures effectively and monitoring environmental changes. Additionally, it would help authorities in Erbil municipality and the General Directorate of Water and Sewerage to identify priorities, as well as helping them in making the right decisions. In this paper, we examined changes in LULC in the studied area in five phases. The time-steps started in 1984,1994,2004,2014 and 2019. The studied area is located in Erbil-KRI (North of Iraq). We attempted to find answers to the four research questions concerning LULC changes and their influence on the runoff coefficient (the runoff coefficient is a unitless determinant that is used to convert the amounts of rainfall to runoff, or the ratio of the peak runoff rate to the rainfall intensity [46]) in the studied area from 1984 to 2019: (1) How was the LULC changed during this period, after every ten years? (2) How did the economic, social and political situation affect the LULC changes?
(3) How did this transformation affect the hydrological response in the studied area? (4) Is the probability of urban flash floods increasing?

Study Area
Erbil is a province located in the north of Iraq, and it is the capital city of the KRI. Erbil Province is considered to be the fourth biggest city in Iraq after Baghdad, Basra and Mosul. It lies approximately 350 km (220 miles) from Baghdad, the capital of Iraq. The total area of Erbil Province is 14,873.68 km 2 ; however, the area considered as the studied area in this work is 508.074 km 2 ( Figure 1). The studied area is delineated based on the hydrological situation, using HEC-GeoHMS in ArcGIS 10.5.1, which affects the center of the city in terms of runoff during precipitation events. Due to the location of Erbil Province, it has a semi-arid continental climate and is characterized by hot and dry summers and cold and wet winters. The mean annual precipitation in the central district of Erbil Province from 1980 to 2018 was 419.2 mm. Moreover, the maximum annual rainfall in 1992 reached 866.3 mm, and the minimum in 1999 was 225.8 mm [47].

Workflow
The methodology applied in this study is illustrated in Figure 2. The expected outcomes are the LULC scenarios for 1984,1994,2004,2014 and 2019. Furthermore, their influence on the hydrological response. To reach these targets, several steps were taken. First, we collected the required data for the study, such as remote sensing data, rainfall datasets and soil maps. Second, we started with image analyses using supervised classification; we used the maximum likelihood classification to extract LULC maps from Landsat images. In the third step, unifying both the LULC maps and soil maps in ArcMap using the HEC-GeoHMS tool, a CN grid was prepared. Moreover, we calculated the basin characteristics and basin slope using DEMs. Lastly, we simulated the hydrological model in HEC- Erbil is going through essential changes because of the impact of political, economic, global, cultural and demographic transformations. The independent management of resources and revenues Remote Sens. 2020, 12, 1302 4 of 21 hand-in-hand with economic prosperity allowed the city to speed up its reconstruction and development, with the benefit of more stability and a safer environment compared to other cities in the center and south of Iraq [48,49]. After several political upheavals and demographic changes in the region, Erbil Province stands as a durable model of exponential urban development, for instance, recently, following the ISIS attack on Syria and Iraq, from 2013 to 2019. In Iraq, the attack targeted the Sunnis zones in the center and mid-west of Iraq as well as the Yazidis area in the Sinjar district, forcing thousands of civilians to flee their homes to the KRI, especially Erbil and Duhok. At that time, the international community, Internal Displaced People (IDP) and refugee organizations built shelters and temporary camps for those people who relocated from their homelands. This demographic change is one of the tens of political upheavals in the region.

Workflow
The methodology applied in this study is illustrated in Figure 2. The expected outcomes are the LULC scenarios for 1984,1994,2004,2014 and 2019. Furthermore, their influence on the hydrological response. To reach these targets, several steps were taken. First, we collected the required data for the study, such as remote sensing data, rainfall datasets and soil maps. Second, we started with image analyses using supervised classification; we used the maximum likelihood classification to extract LULC maps from Landsat images. In the third step, unifying both the LULC maps and soil maps in ArcMap using the HEC-GeoHMS tool, a CN grid was prepared. Moreover, we calculated the basin characteristics and basin slope using DEMs. Lastly, we simulated the hydrological model in HEC-HMS, in order to compare different scenarios and assess the transformation and development in the studied area. In the following sub-sections, the methodology is described in detail.

Remote Sensing Data Acquisition
To examine the LULC changes in the center of Erbil Province, different LULC cover types were prepared from remotely sensed data. Satellite images from Landsat 4-5 TM (1982-2011), Landsat 7 ETM+ (1999-present) and Landsat 8 OLI (2013-present) were downloaded from the LandsatLook viewer (https://landsatlook.usgs.gov/viewer.html). The images were taken by the satellite on

Remote Sensing Data Acquisition
To examine the LULC changes in the center of Erbil Province, different LULC cover types were prepared from remotely sensed data. Satellite images from Landsat 4-5 TM (1982, Landsat 7 ETM+ (1999-present) and Landsat 8 OLI (2013-present) were downloaded from the LandsatLook viewer (https://landsatlook.usgs.gov/viewer.html). The images were taken by the satellite on different dates, as listed in Table 1. The images were selected based on quality, especially those images which were free of cloud or had a limited rate. Moreover, images were selected nearly in the same season, between June and August, in order to have a similar seasonal variation of LULC. In addition, the DEM of the Shuttle Radar Topography Mission (SRTM) (http://dwtkns.com/srtm30m/) was acquired at 1 arc-second (30 m) resolution, to delineate the watershed boundary of the studied area. Furthermore, higher spatial resolution true-color satellite and aerial imagery were retrieved from Google Maps and HERE WeGo (wego.here.com). A soil map of the studied area was extracted using a basin boundary from the prepared digital soil map of Iraq by the Food and Agriculture Organization (FAO) (Figure 3).

Image Pre-Processing
Extensive pre-processing was done, particularly geo-referencing, layer stacking, extraction and image enhancement. Layers were stacked using Edras Imagine 2014 in order to obtain multicomposite images for further processing, and then from the stacked satellite image, the study area was extracted with "extract by mask" using the Erbil basin boundary prepared in ArcGIS 10.5.1, and again, using Edras Imagine 2014, the resolution of the images was enhanced twice using the convolution function in spatial tools and the subset function in subset and chip tools. The enhancement process was carried out in order to obtain a clear image for the classification and accuracy assessment stage.

Image Pre-Processing
Extensive pre-processing was done, particularly geo-referencing, layer stacking, extraction and image enhancement. Layers were stacked using Edras Imagine 2014 in order to obtain multi-composite images for further processing, and then from the stacked satellite image, the study area was extracted with "extract by mask" using the Erbil basin boundary prepared in ArcGIS 10.5.1, and again, using Edras Imagine 2014, the resolution of the images was enhanced twice using the convolution function in spatial tools and the subset function in subset and chip tools. The enhancement process was carried out in order to obtain a clear image for the classification and accuracy assessment stage.

Image Classification
Image classification and change identification are two of the most common techniques for observing LULC changes in urban areas. The process is complex and requires the consideration of several factors, and it should be done accurately. Concerning the LULC classification, the basin was categorized into five different classes: water (including rivers, tributaries and ponds), built-up (including residential, industrial, commercial, local streets, roads and other urban areas), bare land (uncovered soils, unused areas, rocky mountains and dry river beds), agriculture (including crop fields and fallow areas) and finally vegetation (including forests, orchards, vegetable fields, parks, lawns, shrubs and others). For this study, supervised classification was performed using Edras Imagine 2014. Supervised classification is where the software user creates spectral signatures of known classes, such as urban, water and agriculture, and then the software specifies each pixel in the image to the cover type to which its signature is most comparable [50]. The maximum likelihood classifier (MLC) is one of the most popular adopted parametric classification algorithms [12,[51][52][53][54]. At the beginning of the classification process, three bands were combined as a false-color composite, including band nos. 5, 4 and 3, for each LULC class in each satellite image, 20 training sites were collected. In total, 100 training sites were collected for one image. With this background, 500 training sites have been collected for five satellite images. During this process, Google Maps and HERE WeGo (wego.here.com) were used with the aim of obtaining an accurate definition of the training sites. The training sites were different in pixel size and used as an area of interest to train the images, to be later merged into one signature for a given LULC category and used for the classification.

Image Post-Processing
The LULC maps were noisy as a consequence of the resemblances of the spectral responses of specific land cover classes such as pasture/scrubland and built-up areas. In this process, the classified image was accurately compared to reality, and an accuracy assessment analysis was performed to verify the classification results. The purpose of the accuracy assessment was to quantitatively evaluate how or to what effective degree the pixels were sampled into the LULC categories. The accuracy of the classified images from 1984, 1994, 2004, 2014 and 2019 was evaluated by Edras Imagine 2014 using randomly generated points. Some studies used 500 reference points for accuracy assessment [55,56], however number of reference points depends on the size of the studied area. In this study for each image, 500 reference points were generated (equalized random points per class) and aligned to the boundary of the study area shapefile. This was necessary to assess the accuracy of the classification results and the modification of land cover categories.

Hydrological Modeling Using HEC-HMS
The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) was developed to simulate the precipitation-runoff procedures of dendritic watershed systems [57]. The model consists of multi sub-models to simulate different elements of the runoff formation process with the choice of various infiltrations, unit hydrographs and flood routing methods. Because of its simplicity and the limited number of parameters, HEC-HMS is universally used, which makes calibration relatively uncomplicated [36]. The basin model, meteorological model and control specification are the three main models of simulation in HEC-HMS [32]. The basin model, consisting of the delineation of sub-basins, sub-basin areas, river length, river slope, longest flow path, elevation and basin slope, was developed using HEC-GeoHMS [58], and the said basin model was then converted to the HEC-HMS model ( Figure 4). The Soil Conservation Service (SCS) Curve Number (CN) (today, the Natural Resources Conservation Service (NRCS)) method was applied for precipitation losses. Many studies showed that Remote Sens. 2020, 12, 1302 7 of 21 the CN method could be applied in different environments and, despite its simplicity, can produce practicable results comparable to those of more complicated models [59,60]. The SCS-Unit hydrograph method was applied for transformation, and the Muskingum-Cunge method was used for river routing. Analyzed long-term series of maximum daily rainfall data were used in this study and within them, a probability distribution of 10%, which is equal to 71.16 mm [47].

LULC Accuracy Assessment
The classification accuracy of the prepared LULC change maps was evaluated. The producer's accuracy is the number of correctly classified reference points of a particular class divided by the total number of reference points for that category. It is an indicator of the error of omission [61]. The user's accuracy is an alternative measure for individual category accuracy. It is the number of correctly classified reference points of a specific class divided by the total number of points being classified as that category. It measures the error of commission [62]. The accuracy assessment for the results of five images showed an overall classification accuracy of 85.60%. While each image was analyzed and assessed independently, as in this study, different satellite images were used ( Table 2). The accuracy rate depends on the quality of RS data such as the resolution, available bands and the quality of the image. In this study, there is a limitation to examine the accuracy of classified maps because of the nature of LULC changes, which alter according to different regional conditions, and also due to the lack of availability of ground values.

LULC Accuracy Assessment
The classification accuracy of the prepared LULC change maps was evaluated. The producer's accuracy is the number of correctly classified reference points of a particular class divided by the total number of reference points for that category. It is an indicator of the error of omission [61]. The user's accuracy is an alternative measure for individual category accuracy. It is the number of correctly classified reference points of a specific class divided by the total number of points being classified as that category. It measures the error of commission [62]. The accuracy assessment for the results of five images showed an overall classification accuracy of 85.60%. While each image was analyzed and assessed independently, as in this study, different satellite images were used ( Table 2). The accuracy rate depends on the quality of RS data such as the resolution, available bands and the quality of the image. In this study, there is a limitation to examine the accuracy of classified maps because of the nature of LULC changes, which alter according to different regional conditions, and also due to the lack of availability of ground values.

LULC Results and Change Detection
The resulting LULC maps generated for the studied area for 1984,1994,2004,2014 and 2019 are shown in Figure 5a-e, respectively.

LULC Results and Change Detection
The resulting LULC maps generated for the studied area for 1984,1994,2004,2014 and 2019 are shown in Figure 5a-e, respectively.
The water class was only about 0.50% in 1984 and 1994, and after this period surface waters disappeared in the basin. Nevertheless, surface waters flow in seasonal streams if there is enough precipitation in the year. For example, in 2018, annual precipitation reached 721.3 mm, and this amount was not recorded in Erbil city center from 1992. As a consequence of this, some seasonal streams appeared again.  (Table 3).   (Table 3).

Influence of Urbanization on the Flash Flood Potential
The present study is focused on both urban development and its impact on the flood peak discharge, as well as the runoff coefficient and the flood hydrograph, using the rainfall-runoff hydrological modeling for a storm rainfall depth with the probability distribution of 10%, which is equal to 71.16 mm, and the land use conditions of 1984, 1994, 2004, 2014 and 2019. The SCS-CN loss method has been applied in the HEC-HMS model for computing the runoff. The soil group, land use and hydrological condition of the land cover are the main factors in calculating the CN. The LULC and soil maps are unified, and the hydrological soil group was set as per the soil cover. The assigned CN, relevant to the hydrological soil group and land use cover, is tabulated in Table 4. The composite CN for each sub-basin was derived and used as the input for the SCS-CN modeling in HEC-HMS (Table 5). The hydrological modeling reveals that flash flooding caused by more frequent rainfall events (with a smaller probability distribution [47,63]) is increased more by urban growth than by large storm events. Erbil is undergoing an observable horizontal expansion. It has been developing in all directions due to its location on flat terrain and the form and height of Erbil Citadel, which have shaped the urban model of the peripheral areas as concentric rings with a radial axis [48]. A large number of land parcels were distributed within the city master plan, but some of these distributed lands lack municipal services and facilities, and have therefore remained undeveloped [48]. Nevertheless, the category of the land has changed, for instance, from agricultural land to residential land, for example, a neighborhood called Hasarok 8, which was distributed more than fifteen years ago. Generally, the residential areas are more concentrated on the east, north-east and south-east of the city. Hence, the mentioned areas are among the most populated. While the other part of the city is more developed regarding architecture and urban design trends. Wealthy quarters and exclusive compounds have been established, along with several office buildings and business centers [48]. Nowadays, Erbil is considered to be the region's most developed city and it is a powerful economy for several reasons, such as: being the capital of the KRI, and the existence of KRG ministries, the parliament, international organizations (UN, UNHCR, UNDP, NRC, AMG, etc.), the airport, diplomatic representatives, international companies and the newly generated and expanded political infrastructure. At present, Erbil has more than ninety different quarters, in comparison to eighty-two in 2012, and in 1950 only eight [64]. This can be noticed more visibly in the upper sub-basins (W330, W350, W360, W380, W390 and W450) ( Table 6), where there is a dramatic increase in built-up areas, especially in W330 which grew by about 2178% between 2004 and 2019. Also, built-up areas in sub-basins such as W350 and W360 grew by 465.14% and 1029.29%, respectively. However, there was also development in the built-up areas in the lower sub-basins (440, 480 and 500, 510, 540, 560, 570, 590 and 620). Generally, a lower sub-basin is considered as a rural agricultural area. Between 1984 and 2004, development in these areas was slow. Then after 2004, development started in these areas but the development could not be compared in size to the upper sub-basins.   As a consequence of the LULC transformation, the runoff coefficient for Erbil basin was also changed. The example results of the hydrological modeling of the outflow for 10% rainfall probability are presented in Figure 6. The hydrological modeling using HEC-HMS showed that in 1984 the runoff coefficient for Erbil basin was only 0.39, in 1994 and 2004 the rate increased to 0. 40   As expected, the runoff volume varied in each sub-basin; for instance, there was a considerable LULC change in the sub-basins (W330, W350, W360, W380, W390 and W450). In sub-basin W330, as a consequence of urban development, which was about 2178% only between 2004 and 2019, the runoff volume increased from 26.58 to 35.42 mm (Table 7). This revealed that there is a significant impact of urbanization on runoff characteristics. Moreover, Figure 7 and Table 7 show that in all those sub-basins where there was significant urban growth, the runoff coefficient increased as well. The hydrological model has not been validated so far due to the lack of outflow measurements in any of As expected, the runoff volume varied in each sub-basin; for instance, there was a considerable LULC change in the sub-basins (W330, W350, W360, W380, W390 and W450). In sub-basin W330, as a consequence of urban development, which was about 2178% only between 2004 and 2019, the runoff volume increased from 26.58 to 35.42 mm (Table 7). This revealed that there is a significant impact of urbanization on runoff characteristics. Moreover, Figure 7 and Table 7 show that in all those sub-basins where there was significant urban growth, the runoff coefficient increased as well. The hydrological model has not been validated so far due to the lack of outflow measurements in any of the sub-basins in the studied area. The model verification is planned in the next stage of research on urban flash flood risk mitigation in Erbil. Table 7. Runoff and runoff coefficient in each sub-basin for p = 10% rainfall (71.16 mm).

Sub-Basins
Runoff ( the sub-basins in the studied area. The model verification is planned in the next stage of research on urban flash flood risk mitigation in Erbil.

Discussion
RS data, by employing the maximum likelihood method for image classification, were used to provide detailed information to describe the LULC dynamics around the central district of Erbil Province. Regarding the percentage of the accuracy assessment of the classified images (85.60%), this could be considered to be an acceptable classification. A Kappa statistics value of between 0 and 1 for the analysis of classified maps has become the standard for the agreement of maps in practice [65]. The Kappa values for the results of our study and the validation of the visual interpretation

Discussion
RS data, by employing the maximum likelihood method for image classification, were used to provide detailed information to describe the LULC dynamics around the central district of Erbil Province. Regarding the percentage of the accuracy assessment of the classified images (85.60%), this could be considered to be an acceptable classification. A Kappa statistics value of between 0 and 1 for the analysis of classified maps has become the standard for the agreement of maps in practice [65]. The Kappa values for the results of our study and the validation of the visual interpretation classification of five classified images were over 0.79, which means that all maps agree well (a Kappa value between 0.61 and 0.8 is considered to correspond well [66,67]). Urbanization in Erbil city has witnessed both dramatic changes and shifts in different periods. These changes principally corresponded to legislation factors, in parallel with the political situation, and economic and social determinants over four subsequent periods: , , (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003), (2003-present) [68]. Between 1984 and 2003, Iraq generally and the Kurdistan Region, which was established in 1992, were in a period of slow economic growth, due to the number of wars that happened in this area, such as the Iraq-Iran war (22 September 1980-20 August 1988, Gulf War (2 August 1990-28 February 1991, and Kurdish conflict (1994)(1995)(1996)(1997)(1998). However, the Kurdistan Region, and especially Erbil as the capital of the region, witnessed considerable growth and development after 2004. Generally, since 1991, the KRI has been a de facto independent entity making its own regulations and policies, and according to the new constitution, which was prepared in 2005, Iraq is a federal country, with the Kurdistan Region as the only federal state within its borders [69]. Further analysis showed that the increase in built-up areas was about 25 km 2 between 1984 and 2004, which nearly equals 1.25 km 2 per year. Furthermore, only between 2004 and 2014, the increase in built-up areas was about 63 km 2 , which is the equivalent of 6.3 km 2 per year, which can be considered as very high, indicating rapid urban growth in the city with a spatial and temporal change in land use over only ten years. Oil production and real estate investment caused an economic boom. The population of Erbil Province grew from approximately 95,000 inhabitants in 1965 to about 1.3 million in 2010 [70], recently reaching more than 2 million. Figure 8 shows the evolution of built-up areas from 1984 to 2019. The current study, supported by previous research in this area, demonstrates that increasing urban development in flood plain zones will boost peak discharge, reduce the time to peak, and increase the runoff volume [2,29,[71][72][73][74].
Remote Sens. 2020, 12, 1302 16 of 22 classification of five classified images were over 0.79, which means that all maps agree well (a Kappa value between 0.61 and 0.8 is considered to correspond well [66,67]). Urbanization in Erbil city has witnessed both dramatic changes and shifts in different periods. These changes principally corresponded to legislation factors, in parallel with the political situation, and economic and social determinants over four subsequent periods: , , (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003), (2003-present) [68]. Between 1984 and 2003, Iraq generally and the Kurdistan Region, which was established in 1992, were in a period of slow economic growth, due to the number of wars that happened in this area, such as the Iraq-Iran war (September 22, 1980-August 20, 1988, Gulf War ( August 2, 1990-February 28, 1991, and Kurdish conflict (1994)(1995)(1996)(1997)(1998). However, the Kurdistan Region, and especially Erbil as the capital of the region, witnessed considerable growth and development after 2004. Generally, since 1991, the KRI has been a de facto independent entity making its own regulations and policies, and according to the new constitution, which was prepared in 2005, Iraq is a federal country, with the Kurdistan Region as the only federal state within its borders [69]. Further analysis showed that the increase in built-up areas was about 25 km 2 between 1984 and 2004, which nearly equals 1.25 km 2 per year. Furthermore, only between 2004 and 2014, the increase in built-up areas was about 63 km 2 , which is the equivalent of 6.3 km 2 per year, which can be considered as very high, indicating rapid urban growth in the city with a spatial and temporal change in land use over only ten years. Oil production and real estate investment caused an economic boom. The population of Erbil Province grew from approximately 95,000 inhabitants in 1965 to about 1.3 million in 2010 [70], recently reaching more than 2 million. Figure 8 shows the evolution of built-up areas from 1984 to 2019. The current study, supported by previous research in this area, demonstrates that increasing urban development in flood plain zones will boost peak discharge, reduce the time to peak, and increase the runoff volume [2,29,[71][72][73][74]. The findings of this study indicate that urbanization resulted in an increased risk of urban flash floods. Another cause of this risk is also the changing characteristics of precipitation as a result of global climate change [47,63]. Such floods are dangerous to people and destroy the urban infrastructure due to the overflow of the stormwater drainage system [75] and increase erosion of the land surface [76]. Generally, urban development will not only boost peak discharge but will also elevate the runoff volume and the extent of the flooded zone within a catchment. Because Erbil city center is more or less a flat territory, the flooding will last for a longer time compared to steeper areas, as well as due to the circularity of the main roads around Erbil Citadel, such as Barzani circular street, The findings of this study indicate that urbanization resulted in an increased risk of urban flash floods. Another cause of this risk is also the changing characteristics of precipitation as a result of global climate change [47,63]. Such floods are dangerous to people and destroy the urban infrastructure due to the overflow of the stormwater drainage system [75] and increase erosion of the land surface [76]. Generally, urban development will not only boost peak discharge but will also elevate the runoff volume and the extent of the flooded zone within a catchment. Because Erbil city center is more or less a flat territory, the flooding will last for a longer time compared to steeper areas, as well as due to the circularity of the main roads around Erbil Citadel, such as Barzani circular street, Kurdistan circular street, Peshawa circular road, 120 m ring road and the under-construction 150 m ring road. All these mentioned roads cross rivers and streams passing through the city. As a consequence, the routes of most of the rivers and streams have been either blocked or changed to smaller sewer culverts or pipes. This means for urbanized areas, streets, underpasses and low elevation areas, the possibility to be flooded is greater compared to other areas. Erbil center district has suffered from urban flash floods since the 1930s. In the last two decades, the number of flash floods due to heavy rainfalls has increased. Recently, on February 20, 2020, some neighborhoods in the Erbil center district were flooded. According to the meteorological station of the Erbil Directorate of Irrigation, the amount of 24.3 mm rainfall was measured within six hours. Moreover, the highest rainfall intensity recorded in this episode was 9.8 mm/hour in the middle of the event. Water accumulated in the expected areas within a short time. The inundation level was more than 25 cm in some areas, as shown in Figure 9a Kurdistan circular street, Peshawa circular road, 120 m ring road and the under-construction 150 m ring road. All these mentioned roads cross rivers and streams passing through the city. As a consequence, the routes of most of the rivers and streams have been either blocked or changed to smaller sewer culverts or pipes. This means for urbanized areas, streets, underpasses and low elevation areas, the possibility to be flooded is greater compared to other areas. Erbil center district has suffered from urban flash floods since the 1930s. In the last two decades, the number of flash floods due to heavy rainfalls has increased. Recently, on February 20, 2020, some neighborhoods in the Erbil center district were flooded. According to the meteorological station of the Erbil Directorate of Irrigation, the amount of 24.3 mm rainfall was measured within six hours. Moreover, the highest rainfall intensity recorded in this episode was 9.8 mm/hour in the middle of the event. Water accumulated in the expected areas within a short time. The inundation level was more than 25 cm in some areas, as shown in Figure 9a-b.
(a) (b) Figure 9. (a) Difficulty in moving (photo taken by Soran Hassan Jazě). (b) A municipality wheel loader transports officers to a national bank near West Erbil emergency hospital (photo taken from NRT official social media page).

Conclusions
This study investigated both the dynamic changes in LULC and evolution in the hydrological response in the center of Erbil Province, KRI, from 1984 to 2019 using multispectral satellite data. To sum up our research questions from the introduction section, our outcomes are presented as follows: 1.
The results revealed that between 1984 and 2004, bare land and built-up areas steadily increased, while between 2004 and 2019, built-up areas soared by almost 245% (from just 55.823 to 136.658 km 2 ). Permeable areas like agricultural land and vegetation steadily decreased from 1984 to 2019. Only between 2014 and 2019 did vegetation areas increase, especially in the downstream area of the city. In our opinion, these changes are related to farming types in these areas, and the remote sensing data showed the class as vegetation; 2.
Three factors (economic, social and political) influenced the LULC changes in the studied area. For instance, after 2004, the KRI generally, and especially Erbil, enjoyed a decade of prosperity and development due to many factors such as stable security, local and international investment, and the successful implementation of some of the American free market-based developmental policies; 3.
The influence of urbanization on the flood peak discharge, runoff volume and runoff coefficient were investigated for the depth of storm rainfall at the probability distribution of 10%, which is equal to 71.16 mm under different urbanization scenarios. The simulations showed that urban development could considerably aggravate flooding caused by a given storm due to the hindrance of natural drainage and decreasing permeability; 4.
As it is obvious in the analysis, parallel to urban development, the runoff volume and peak discharge increased as well. Therefore, the probability of more flash floods in the city is increasing likewise. If the authorities do not take steps related to adopting a new strategy in order to stop urban flash floods, such flash floods will target areas that are denser in urban development and population.
The outcome of this study shows how important remote sensing is for the detection of previous, present and future human activities, in a relatively simple, cheap and easy way. Moreover, without using RS data and GIS techniques, the analysis of LULC in third world countries is somehow difficult or impossible. The results achieved from the study indicate that there is an increase in the runoff peak and volume, which is due to the hydrological response related to urbanization in the city. As a consequence of this, the possibility of flash floods is increased and it becomes a risk to life quality in the studied area, especially in the center of the city. The findings of the study are also important for policymakers and local authorities when deciding how to re-adapt the city to the current situation and plan for future development. In addition, the findings and the prepared LULC scenarios of this study will be useful in the research field on the flash floods mitigation in the studied area.