Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

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Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran. / Jahanshahi, Afshin; Melsen, Lieke; Patil, Sopan et al.
Yn: Journal of Hydrology, Cyfrol 603, Rhif Part C, 127099, 12.2021.

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

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Jahanshahi A, Melsen L, Patil S, Goharian E. Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran. Journal of Hydrology. 2021 Rhag;603(Part C):127099. Epub 2021 Hyd 31. doi: https://doi.org/10.1016/j.jhydrol.2021.127099

Author

Jahanshahi, Afshin ; Melsen, Lieke ; Patil, Sopan et al. / Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran. Yn: Journal of Hydrology. 2021 ; Cyfrol 603, Rhif Part C.

RIS

TY - JOUR

T1 - Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran

AU - Jahanshahi, Afshin

AU - Melsen, Lieke

AU - Patil, Sopan

AU - Goharian, Erfan

PY - 2021/12

Y1 - 2021/12

N2 - Simulating streamflow in ungauged catchments remains a challenging task in hydrology and increases the demand for regionalization studies worldwide. Here, we investigate the effect of three modes of parameter transfer, including temporal (transferring across different periods), spatial (transferring between same calibration periods but different sites), and spatiotemporal (transferring across both different periods and sites) on simulating streamflow using HBV conceptual rainfall-runoff model at 576 unregulated catchments throughout Iran (407,000 Km2). Our main conclusions are: (1) temporal mode shows the best performance, with the lowest decline in performance (median decline of 5.8%) as measured using the NSE efficiency metric, (2) difference between spatial and spatiotemporal options was negligible (median decline of 13.7% and 15.1% respectively), (3) all parameters are associated with some uncertainties and those related to runoff and snow components of the model are associated with the highest and lowest uncertainties, respectively, (4) overall, the model performance in arid regions is not as good as humid regions which confirmed that elevation and climate play a major role in parameter estimation in these areas, and (5) aridity and catchment elevation are two major controls on model transferability at regional (climate classes) and local (the whole country) scales. We also show that the superiority of the temporal mode is maintained with: (i) increasing spatial distance between gauged (donor) and ungauged (target) catchments, (ii) increasing time lag (10 years) between calibration and validation, and (iii) gradually increased time lags between calibration and validation. Our study suggest that spatiotemporal parameter transfer can be a reliable option for PUB studies and climate change-related studies, at least in wetter catchments. However, further research is needed to explore the complicated relationship between temporal and spatial aspects of hydrological variability.

AB - Simulating streamflow in ungauged catchments remains a challenging task in hydrology and increases the demand for regionalization studies worldwide. Here, we investigate the effect of three modes of parameter transfer, including temporal (transferring across different periods), spatial (transferring between same calibration periods but different sites), and spatiotemporal (transferring across both different periods and sites) on simulating streamflow using HBV conceptual rainfall-runoff model at 576 unregulated catchments throughout Iran (407,000 Km2). Our main conclusions are: (1) temporal mode shows the best performance, with the lowest decline in performance (median decline of 5.8%) as measured using the NSE efficiency metric, (2) difference between spatial and spatiotemporal options was negligible (median decline of 13.7% and 15.1% respectively), (3) all parameters are associated with some uncertainties and those related to runoff and snow components of the model are associated with the highest and lowest uncertainties, respectively, (4) overall, the model performance in arid regions is not as good as humid regions which confirmed that elevation and climate play a major role in parameter estimation in these areas, and (5) aridity and catchment elevation are two major controls on model transferability at regional (climate classes) and local (the whole country) scales. We also show that the superiority of the temporal mode is maintained with: (i) increasing spatial distance between gauged (donor) and ungauged (target) catchments, (ii) increasing time lag (10 years) between calibration and validation, and (iii) gradually increased time lags between calibration and validation. Our study suggest that spatiotemporal parameter transfer can be a reliable option for PUB studies and climate change-related studies, at least in wetter catchments. However, further research is needed to explore the complicated relationship between temporal and spatial aspects of hydrological variability.

KW - Aridity Parameter transfer

KW - Rainfall-runoff model

KW - Ungauged catchment

U2 - https://doi.org/10.1016/j.jhydrol.2021.127099

DO - https://doi.org/10.1016/j.jhydrol.2021.127099

M3 - Article

VL - 603

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

IS - Part C

M1 - 127099

ER -