Estimating the Effect of Urban Growth on Annual Runoff Volume Using GIS in the Erbil Sub-Basin of the Kurdistan Region of Iraq

Hameed, Hasan Mohammed

doi:10.3390/hydrology4010012

Cited by 31 publications

(19 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Therefore, the cities with higher increasing rates of SUHII should pay more attention to protect the terrestrial ecosystems. In this study, the continuous and rapid urbanization of the 10 cities was similar with other cities according to previous studies [56][57][58][59]. Future studies will focus on UEs on environment at regional or global scales.…”

Section: The Relationships Between Suhii and ∆Evimentioning

confidence: 51%

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

et al. 2017

View full text Add to dashboard Cite

Abstract:In the context of rapid urbanization, systematic research about temporal trends of urbanization effects (UEs) on urban environment is needed. In this study, MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature (LST) data and enhanced vegetation index (EVI) data were used to analyze the temporal trends of UEs on vegetation and surface urban heat islands (SUHIs) at 10 big cities in Yangtze River Basin (YRB), China during 2001-2016. The urban and rural areas in each city were derived from MODIS land cover data and nighttime light data. It was found that the UEs on vegetation and SUHIs were increasingly significant in YRB, China. The ∆EVI (the UEs on vegetation, urban EVI minus rural EVI) decreased significantly (p < 0.05) in 9, 7 and 5 out of 10 cities for annual, summer and winter, respectively. The annual daytime and nighttime SUHI intensity (SUHII; urban LST minus rural LST) increased significantly (p < 0.05) in 10 and 4 out of 10 cities, respectively. The increasing rate of daytime SUHII and the decreasing rate of ∆EVI in old urban areas were much less than the whole urban area (0.034 • C/year vs. 0.077 • C/year for annual daytime SUHII; 0.00209/year vs. 0.00329/year for ∆EVI). The correlation analyses indicated that the annual and summer daytime SUHII were significantly negatively correlated with ∆EVI in most cities. The decreasing ∆EVI may also contribute to the increasing nighttime SUHII. In addition, the significant negative correlations (r < −0.5, p < 0.1) between inter-annual linear slope of ∆EVI and SUHII were observed, which suggested that the cities with higher decreasing rates of ∆EVI may show higher increasing rates of SUHII.

show abstract

Section: The Relationships Between Suhii and ∆Evimentioning

confidence: 51%

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The United State Department of Agriculture (USDA) identifies four main soil groups based on texture, infiltration characteristics and permeability [42][43][44]. Typically, higher CN values indicate higher surface runoff whereas lower CN values refer to reduced runoff [45,46].…”

Section: Methodsmentioning

confidence: 99%

“…The SCS-CN method is essentially based on the water balance equation and on two fundamental hypotheses. The first hypothesis is that the ratio and runoff to effective rainfall corresponds to the ratio of actual potential retention to potential retention; [44][45][46].…”

Section: Methodsmentioning

confidence: 99%

Integrating System Dynamics and Remote Sensing to Estimate Future Water Usage and Average Surface Runoff in Lagos, Nigeria

2018

View full text Add to dashboard Cite

The goal of this study was twofold; first analyze the patterns of water consumption in Lagos, Nigeria and use them in a System Dynamics (SD) model to make projections about future demand. The second part used remote sensing to quantify the contribution of extensive land use/cover change to urban flooding. Land use/cover dynamics over the past decade was analyzed using satellite imagery provided by Landsat Thematic Mapping (TM). Unsupervised classification was performed with false color composite using the Iterative Self-Organizing Data Analysis (ISODATA) technique in a Geographic Information Systems (GIS). The study area was divided into four different land use types during image classification: bare land, built-up area, water bodies, and vegetation. For water demand, two different scenarios of population growth including 5.5% and 2.75 % annual increase were considered. The results showed that water demand dropped by 67% of its current value when losses in distribution were reduced by 20% and population annual growth rate kept at 2.75% over the study period. Bare land and water bodies lost 1.31% and 1.61% of their current area respectively while built-up area grew by 1.11%. These changes in land use/cover changes led to a 64% increase in average surface runoff, mostly attributable to increasing surface imperviousness and the absence of an adequate urban drainage system.

show abstract

“…Interestingly, beyond its original scope, it has also been extended to several other scientific areas such as flood design for hydraulic structure [19][20], water balance calculation, sediment yield modelling [21][22][23][24][25], sediment transport [26], water quality [27][28], irrigation [29], soil moisture modelling [30], long-term hydrologic simulation [31][32][33][34][35][36][37][38], prediction of infiltration and rainfallexcess rates [39][40][41][42][43], rainwater harvesting [44][45][46][47], urban hydrology [48][49], hydrograph simulation [50], e-flow assessment [51], partitioning of heavy metals [52][53], transport of pollutants [50]. Moreover, many research efforts have also investigated the utility of the SCS-CN method in quantifying the runoff response due to land use/cover changes [54][55][56][57], and effect of forest fires on hydrological response and the associated hydrological risks [58][59][60]…”

Section: Introductionmentioning

confidence: 99%

Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

Rk¹,

Verma²,

Sharma³

et al. 2021

Preprint

View full text Add to dashboard Cite

The need of incorporating storm intensity or duration in Soil Conservation Service Curve Number (SCS-CN) methodology for improved direct surface runoff estimation for a watershed has been highlighted by many engineers and hydrologists since long and despite this fact, it is still poorly explored. Therefore, this study aims to present storm duration-based improved SCS-CN models for estimating more accurate direct surface runoff from rainfall events. The accuracy and consistency of improved models are tested on a large rainfall-runoff dataset (18,660 rainfall events) derived from 39 watersheds in the USDA-ARS. Furthermore, the quantitative model’s performance is also evaluated employing six widely accepted statistical measures viz. root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), observations standard deviation ratio (RSR), and several grading criteria. These models are compared with the original SCS-CN model (M1) and its simple form (M2) with traditionally fixed initial abstraction ratio (λ) as 0.2. The resulting lowest values of RMSE, NRMSE, MAE, NSE, PBIAS and highest values of RSR and ranking grading system (RGS) for the proposed models (M3-M5) reveal that their performance is better than M1 and M2 models. The proposed M5 model incorporating both storm duration and varying initial abstraction (Ia) as a certain percentage of rainfall, performed the best followed by M3 incorporating only storm duration. According to RGS, M5 also ranked first with the highest marks (195) followed by M3 (140). Due to high accuracy in predicted runoff, M5 can be recommended for both small and large watersheds as it overcomes the following issues: fixed λ (=0.2), assumption of constant rainfall intensity (time-independent), fixation of Ia at 2% of rainfall and applicability to only small watersheds, restricting the application of original SCS-CN and its modified versions.

show abstract

Estimating the Effect of Urban Growth on Annual Runoff Volume Using GIS in the Erbil Sub-Basin of the Kurdistan Region of Iraq

Cited by 31 publications

References 33 publications

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

Integrating System Dynamics and Remote Sensing to Estimate Future Water Usage and Average Surface Runoff in Lagos, Nigeria

Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

Contact Info

Product

Resources

About