Application of sediment rating curves to evaluate efficiency of EPM and MPSIAC using RS and GIS

Mirakhorlo, Mohammad Saeid; Rahimzadegan, Majid

doi:10.1007/s12665-018-7908-2

Cited by 12 publications

(2 citation statements)

References 21 publications

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“…Subsequently, modified models have widely and successfully investigated watersheds around the world. By developing and integrating this model into ArcGIS and RS (Daneshvar and Bagherzadeh, 2012;Noori et al, 2018), some attempts were made to investigate and assess this integrated model for the evaluation of sediment yields and soil erosion in the Iranian watersheds (Mirakhorlo and Rahimzadegan, 2018;Shojaei et al, 2019). On the other hand, some studies have been conducted to compare different models such as EPM, PSIAC, and MPSIAC to estimate the sedimentation yield (Mirakholro and Rahimzadegan, 2018;Zarei et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Investigating Anzali Wetland Sediment Estimation Using the MPSIAC Model

2022

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The adverse effects of upland erosion impact the Anzali Wetland in Iran. The Modified Pacific South-west Inter Agency Committee model (MPSIAC) was used to estimate the sediment yield in the watershed. The watershed was divided into twelve sub-watersheds based on the geomorphologic features and waterway orientations (Sw0-Sw11). To investigate the effect of different factors on erosion and sedimentation, data were digitized using ArcGIS software. The effective factor weights were determined using the MPSIAC model, and the total sediment yield was calculated for each sub-watershed. Results showed that the amount of particulate sediment in the critical sub-watersheds Sw6 and Sw9 was 777.9 and 730.2 t km−2. yr−1, respectively. Based on erosion and sedimentation results, the sub-watershed erosion was prioritized as Sw6> Sw9> Sw4> Sw1> Sw0> Sw5> Sw2> Sw8> Sw3> Sw11 > Sw7> Sw10. Both model inputs (precipitation) and outputs (sediment) at different parts of the watershed were assessed via point observations data. Comparison of correlation values reveals that the correlation between the simulated and sampling values was strong in sub-watershed 1 (R2 < 0.8). EF, RMSE, nRMSE, CRM, and MAE were 0.23, 16.74 tons per year, 5.05%, 0.55, and −3.6, respectively, which indicates the model’s high performance in Sw0. Areas with insufficient cover and bare soil showed a high correlation with the final erosion model. Thus, land-use classes, such as dense vegetation and good pastures, correspond to areas with low erosion. Conversely, bare soils and poor pastures were located on the eroded flats.

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Section: Introductionmentioning

confidence: 99%

Investigating Anzali Wetland Sediment Estimation Using the MPSIAC Model

2022

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“…For example, the sediment rating curve based on the empirical relationship between suspended sediment load and streamflow discharge is traditionally used to infill missing sediment data since continuous discharge records are available in most river basins [10]. Several recent studies [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] have proposed various techniques or adopted various variables to estimate or predict suspended sediment loads. Ben Aissia et al [3] indicated that the copula-based method is one of the recent methods and provides probabilistic characteristics of the missing data.…”

Section: Introductionmentioning

confidence: 99%

Copula-Based Infilling Methods for Daily Suspended Sediment Loads

Shiau

Lien

2021

Water

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Less-frequent and inadequate sampling of sediment data has negatively impacted the long and continuous records required for the design and operation of hydraulic facilities. This data-scarcity problem is often found in most river basins of Taiwan. This study aims to propose a parsimonious probabilistic model based on copulas to infill daily suspended sediment loads using streamflow discharge. A copula-based bivariate distribution model of sediment and discharge of the paired recorded data is constructed first. The conditional distribution of sediment load given observed discharge is used to provide probabilistic estimation of sediment loads. In addition, four different methods based on the derived conditional distribution of sediment load are used to give single-value estimations. The obtained outcomes of these methods associated with the results of the traditional sediment rating curve are compared with recorded data and evaluated in terms of root mean square error (RMSE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE), and modified Nash-Sutcliffe efficiency (MNSE). The proposed approach is applied to the Janshou station located in eastern Taiwan with recorded daily data for the period of 1960–2019. The results indicate that the infilled sediments by the sediment rating curve exhibit better performance in RMSE and NSE, while the copula-based methods outperform in MAPE and MNSE. Additionally, the infilled sediments by the copula-based methods preserve scattered characteristics of observed sediment-discharge relationships and exhibit similar frequency distributions to that of recorded sediment data.

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重力恢复和气候试验(grace)方法在监测伊朗局部尺度地下水位变化方面的效果

Rahimzadegan

Entezari

2019

Hydrogeol J

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Application of sediment rating curves to evaluate efficiency of EPM and MPSIAC using RS and GIS

Cited by 12 publications

References 21 publications

Investigating Anzali Wetland Sediment Estimation Using the MPSIAC Model

Investigating Anzali Wetland Sediment Estimation Using the MPSIAC Model

Copula-Based Infilling Methods for Daily Suspended Sediment Loads

重力恢复和气候试验(grace)方法在监测伊朗局部尺度地下水位变化方面的效果

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