Abstract

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 different 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 m3/s in 1984 to 450 m3/s in 2014, as well as the runoff 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.

Highlights

  • Since the last decades of the twentieth century, Remote Sensing (RS) has become a popular approach for detecting LULC changes

  • This study investigated both the dynamic changes in LULC and evolution in the hydrological response in the center of Erbil Province, Kurdistan Region of Iraq (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%

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Summary

Introduction

Since the last decades of the twentieth century, Remote Sensing (RS) has become a popular approach for detecting LULC changes. 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]. In situ data had been used for studying LULC, such kinds of data are inadequate in a spatial and temporal extent. It is hard, if not impossible, to collect data from unreachable areas. Such data are not dependable for effective planning and decision-making [14,15]

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