Evaluation of Sentinel-1, SMAP and SMOS surface soil moisture products for distributed eco-hydrological modelling in Mediterranean forest basins

Gomis-Cebolla, José; García-Arias, Alicia; Perpinyà-Vallès, Martí; Francés, Félix

doi:10.1016/j.jhydrol.2022.127569

Cited by 9 publications

(3 citation statements)

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“…As a result, the deep infiltration factor does not play a big role, but the evaporation and drainage factor plays a greater role in maintaining and preventing flooding. The area of the Mashin Basin is 13 times the area of the Kasilian Basin; on the other hand, the average air temperature in the warm areas of the Mashin Basin, which plays a large role in the model results [30], is much higher than the temperature of the Kasilian Basin. Therefore, in the area of the Mashin Basin, the water flow needs more time to reach the outlet.…”

Section: Resultsmentioning

confidence: 94%

“…As can be seen, in all these studies, the values for λ are different, and it is not possible to consider a fixed number for it. Further investigations showed that there is no significant correlation between the values of λ and S max [17,30]. Therefore, it is necessary to examine the values of I and S max separately.…”

Section: Resultsmentioning

confidence: 98%

“…All the values obtained are less than the value recommended by the SCS-CN method. Additionally, based on the previous studies, the value of λ in the Emameh, Kasilian, Darjazin, Khanmirza, and Mashin basins have been reported to be about 0.09, 0.16, 0.2, 0.3 [30], and 0.2 [20], respectively. As can be seen, in all these studies, the values for λ are different, and it is not possible to consider a fixed number for it.…”

Section: Resultsmentioning

confidence: 99%

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Presentation of a Rainfall–Runoff Retention Model (3RM) Based on Antecedent Effective Retention for Estimating Runoff in Seven Basins in Iran

Shamohammadi,

Ghasemi,

Ostad-Ali-Askari

et al. 2023

CivilEng

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This study aims to correct and assess the SCS-CN model. In this research, the 3RM model (written by Shamohammadi) has been modified in such a way that the maximum primary retention (I), maximum secondary retention (Fmax), and basin potential retention (Smax) can be calculated using precipitation (Pa). The purpose of this study is to evaluate the total retention model (St=f(Fmax,Smax,pa)) and the runoff model (Q=f(St,pa)) using the mountain basins of Iran, including Emameh, Kasilian, Navrood, Darjazin, Kardeh, Khanmirza, and Mashin. The results showed that the primary retention, maximum secondary retention, and retention capacity are, respectively, 2.3, 30.4, and 32.7 mm in Imamah, 2.5, 48.6, and 51.1 mm in Kasilian, 2.4, 26.7, and 29.1 mm in Navrood, 3.2, 21.5, and 24.7 mm in Darjazin, 1.7, 15.0, and 16.7 mm in Kardeh, 2.5, 33.2, and 38.1 mm in Khanmirza, and 4.9, 44.5, and 50.6 mm in Mashine. Additionally, the λ (ratio of primary retention to potential retention) values for all basins are less than 0.2 (suggested by SCS) and vary between 0.05 in Kasilian and 0.1 in the Darjazin, Kardeh, and Mashine basins. The results of fitting the model to the rainfall-runoff data showed that the evaluation indices, including the coefficient of determination (R2), Nash–Sutcliffe (NS), and root mean square error (RMSE), for predicting the runoff in the basins varied between 0.78 to 0.96, 0.78 to 0.961, and 0.86 to 2.28, respectively. According to the obtained results, it can be concluded that the model has an acceptable ability to predict runoff for all the studied basins.

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Section: Resultsmentioning

confidence: 94%

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

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