Evaluation of Soil Water Index of distributed Tank Model in a small basin with field data

Vasconcellos, Sofia Melo; Kobiyama, Masato; Mota, Aline de Almeida

doi:10.5194/hess-2019-682

Cited by 6 publications

(8 citation statements)

References 39 publications

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“…Having reviewed the literature in terms of using the Tank model (either selected as the main or in combination with other forms to model the water balance of ecosystems), we reach to the below discussed conclusion. As researchers have always been seeking for the platforms that enable them to simulate the hydrological processes with less effort and more performance, many have adapted a series of lumped to distributed forms of Tank to advance the hydrologic predictions based on the local data availability and model flexibility ( Chen and Adams, 2006 ; Basri, 2013 ; Onyutha, 2016 ; Jabbarian Amiri et al., 2016 ; Suryoputro et al., 2017 ; Song et al., 2017 ; Sheikh Goodarzi et al., 2018 , 2020 ; Phuong et al., 2018 ; Jaiswal et al., 2020 ; Vasconcellos et al., 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…Data-wise, evapotranspiration, which is one of the key factors in the rainfall-runoff modeling process, has been calculated by different methods ranging from lysimeter-based field measurements, Penman modified ( Vasconcellos et al., 2020 ) to Hargreaves ( Jabbarian Amiri et al., 2016 ). As for indirect methods we need the actual evapotranspiration to be estimated based on the growing crops.…”

Section: Discussionmentioning

confidence: 99%

“…However, different aims of the clients and developers have led to employing various time steps, namely single events ( Vasconcellos et al., 2020 ), daily ( Song et al., 2017 and current study) or monthly ( Phuong et al., 2018 ). As a matter of defining calibration strategy, researchers have equipped Neural Network ( Chen and Adams, 2006 ), global search optimization methods such as Genetic Algorithms and Shuffled Complex Evaluation ( Sheikh Goodarzi et al., 2018 ; Song et al., 2017 ) and different sets of objective functions (NSE and RMSE) to calibrate their hydrologic platforms.…”

Section: Discussionmentioning

confidence: 99%

“…However, some limitations should be taken into account when applying the Tank model to different spatial scales, particularly to small watersheds ( Sheikh Goodarzi et al., 2020 ). As such, some researchers aimed to post-process the modeling results ( Vasconcellos et al., 2020 and Jabbarian Amiri et al., 2016 validated their outputs with an uncertainty analysis). The MAC test applied in this study can also be recommended to ensure that the modeling outputs are reliable enough or (in case of regionalization) transferable.…”

Section: Discussionmentioning

confidence: 99%

“…In their study, the two storage Tank successfully detected the discharge loss caused by intensive water usage and reservoir constructions in the study areas. Vasconcellos et al. (2020) aimed to explore the reliability of spatially distributed soil water index (SWI) and topographical wetness index (TWI) values in comparison with soil moisture measures.…”

Section: Introductionmentioning

confidence: 99%

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Watershed hydrological modelling in data scarce regions; integrating ecohydrology and regionalization for the southern Caspian Sea basin, Iran

Goodarzi

Amiri

Azarnivand

et al. 2021

Heliyon

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The aim of this study is to evaluate an alternative approach to indicate how hydrological processes behave in a given watershed, and to test whether this approach can replace traditional calibration, particularly under data deficient conditions. Therefore, a regional calibration method (RC) was adapted to characterize “parameter-based hydrologic processes” as a function of watershed ecologic attributes. The methodological process included (1) temporal phase, (2) correlation analysis and (3) spatial phase. The defined methodology was carried out on a 4160 km 2 area containing 21 watersheds laying in the southern coastal line of the Caspian Sea, Iran. By implementing the RC, regional models were specified corresponding to each hydrological process defined in the Tank model. Testing the reliability of the transferring process of hydrological parameters was conducted using multi-level accuracy comparison (MAC) benefiting from descriptive statistics, scatter-plots and T-test. Both temporal and spatial phases have shown acceptable outputs backed by their ecologic significance, but as an alternative approach to traditional calibration, the standalone RC still needs development to achieve a more robust basis covering all the parameters of the hydrologic model. According to the post-processor MAC, the transferability of six out of twelve regional models ( height of lower outlet at the first tank, intermediate flow, deep-percolation, infiltration , surface flow , height of outlet at the second tank ) was accepted with respect to the given tests. As such, our method outperformed the number of transferable parameters by an outstanding regional model predicting the surface flow in comparison with similar studies. Although the RC could not achieve total perfection, nevertheless it could still help users by providing more information about the contribution of ecologic variables in the prediction of the hydrological processes of a certain watershed.

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