Atmosphere (Dec 2023)

Quantifying Landscape Pattern–Hydrological Process Linkage in Northwest Iran

  • Ali Rasoulzadeh,
  • Raoof Mostafazadeh,
  • Javanshir Azizi Mobaser,
  • Nazila Alaei,
  • Zeinab Hazbavi,
  • Ozgur Kisi

DOI
https://doi.org/10.3390/atmos14121814
Journal volume & issue
Vol. 14, no. 12
p. 1814

Abstract

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The enormous heterogeneity and complexity of landscape patterns and their linkage with the hydrological responses have rarely been quantified and cataloged, especially in ungauged regions. This research therefore linked the landscape characteristics to hydrological processes using a newly developed runoff landscape index (RLI) at the watershed scale in Ardabil Province, northwest Iran. First, 11 common landscape metrics were calculated using Fragstats 4.2.1 software. Then, a runoff landscape index (RLI) was developed based on land cover (λC), soil (λK), and topography (λS) factors in 28 watersheds. Correlation and regression analyses were also conducted to determine the relationship between RLI, commonly used landscape metrics, and mean base flow. The spatial variations of all meaningful landscape metrics and RLI were considerable throughout the study watersheds. The mean values of λC, λK, and λS were found to be 2.78 ± 1.08, 0.50 ± 0.10, and 1.22 ± 0.30, respectively. The mean RLI varied from 0.00009 in the Lay Watershed with an area of 19.09 km2 to 0.28 in the Boran Watershed with 10,268.95 km2. The correlation coefficient (r > 0.42; p-value 2 of 0.97 and 0.67, respectively, in calibration and validation steps was established between river base flow as the dependent variable and main waterway length, LPI, LSI, SPLIT, modified Simpson’s diversity index (MSIDI), and λS as independent variables. The result confirms the significant interdependence of RLI and landscape characteristics, which can be used to interpret the landscape’s dynamic and its effects on hydrological processes.

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