A case study for the assessment of the suitability of gridded reanalysis weather data for hydrological simulation in Beas river basin of North Western Himalaya

Bhattacharya, Tanmoyee; Khare, Deepak; Arora, Manohar

doi:10.1007/s13201-019-0993-x

Cited by 22 publications

(13 citation statements)

References 27 publications

(27 reference statements)

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“…It is noteworthy that the goal of this study is not to estimate the intrinsic quality of the meteorological forcing (i.e. precipitation and temperature) but rather to understand the impact of the propagation of associated uncertainties on the simulation of hydrological processes (Bhuiyan et al, 2019;Falck et al, 2015;Marthews et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Dembélé

Schaefli

Giesen

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. This study evaluates the ability of different gridded rainfall datasets to plausibly represent the spatio-temporal patterns of multiple hydrological processes (i.e. streamflow, actual evaporation, soil moisture and terrestrial water storage) for large-scale hydrological modelling in the predominantly semi-arid Volta River basin (VRB) in West Africa. Seventeen precipitation products based essentially on gauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP, PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5, PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared as input for the fully distributed mesoscale Hydrologic Model (mHM). To assess the model sensitivity to meteorological forcing during rainfall partitioning into evaporation and runoff, six different temperature reanalysis datasets are used in combination with the precipitation datasets, which results in evaluating 102 combinations of rainfall–temperature input data. The model is recalibrated for each of the 102 input combinations, and the model responses are evaluated by using in situ streamflow data and satellite remote-sensing datasets from GLEAM evaporation, ESA CCI soil moisture and GRACE terrestrial water storage. A bias-insensitive metric is used to assess the impact of meteorological forcing on the simulation of the spatial patterns of hydrological processes. The results of the process-based evaluation show that the rainfall datasets have contrasting performances across the four climatic zones present in the VRB. The top three best-performing rainfall datasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE and CMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC and PGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC for the spatial patterns of soil moisture; ARC, RFE and GSMaP-std for the temporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for the spatial patterns of actual evaporation. No single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes. A dataset that is best in reproducing the temporal dynamics is not necessarily the best for the spatial patterns. In addition, the results suggest that there is more uncertainty in representing the spatial patterns of hydrological processes than their temporal dynamics. Finally, some region-tailored datasets outperform the global datasets, thereby stressing the necessity and importance of regional evaluation studies for satellite and reanalysis meteorological datasets, which are increasingly becoming an alternative to in situ measurements in data-scarce regions.

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Section: Introductionmentioning

confidence: 99%

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Dembélé

Schaefli

Giesen

et al. 2020

Hydrol. Earth Syst. Sci.

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“…This proves that ERA-Interim reanalysis better represents kinetic precipitation of the Beas river basin. Bhattacharya et al (2019) also found that the rainfall gradient of ERA-Interim is linearly correlated with altitude. The reason may be the ERA-Interim reanalysis product uses a four-dimensional variational (4D-var) analysis model.…”

Section: Discussionmentioning

confidence: 76%

“…Therefore it is necessary to evaluate the precipitation estimates to understand the spatio-temporal distribution of mountain precipitation. Several studies (Bhattacharya et al 2019;Tiwari et al 2018) have reported the advantage of using reanalysis temperature products for snowmelt modeling and simulation of streamflow in high altitude rugged terrain where observation networks are inaccessible. A comparison of various reanalysis temperature estimates with observation is needed to understand the variability of temperature with altitude and to estimate suitable gridded temperature data as a proxy of observation stations for data-limited mountain regions.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of reanalysis and global meteorological products in Beas river basin of North-Western Himalaya

2020

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It is a great challenge to obtain reliable gridded meteorological data in some data-scarce and complex territories like the Himalaya region. Less dense observed raingauge data are unable to represent rainfall variability in the Beas river basin of North-Western Himalaya. In this study four reanalyses (MERRA, ERA-Interim, JRA-55 and CFSR) and one global meteorological forcing data WFDEI have been used to evaluate the potential of the products to represent orographic rainfall pattern of Beas river basin using hydrology model. The modeled climate data have compared with observed climate data for a long term basis. A comparison of various rainfall and temperature products helps to determine uniformity and disparity between various estimates. Results show that all temperature data have a good agreement with gridded observed data. ERA-Interim temperature data is better in terms of bias, RMSE (Root Mean Square Error), and correlation compared to other data. On the other hand, MERRA, ERA-Interim and JRA-55 models have overestimated rainfall values, but CFSR and WFDEI models have underestimated rainfall values to the measured values. Variable Infiltration Capacity (VIC), a macroscale distributed hydrology model has been successfully applied to indirectly estimate the performance of five gridded meteorological data to represent Beas river basin rainfall pattern. The simulation result of the VIC hydrology model forced by these data reveals that the discharge of ERA-Interim has a good agreement with observed streamflow. In contrast there is an overestimated streamflow observed for MERRA reanalysis estimate. JRA-55, WFDEI, and CFSR data underestimate the streamflow. The reanalysis products are also poor in capturing the seasonal hydrograph pattern. The ERA-Interim product better represents orographic rainfall for the Beas river basin. The reason may be the ERA-Interim uses a four-dimensional variational analysis model during assimilation. The major drawback of MERRA is the non-inclusion of observed precipitation data during assimilation and modeling error. The poor performance of JRA-55, CFSR and WFDEI is due to the gauge rainfall data assimilation error. This research finding will help for broader research on hydrology and meteorology of the Himalayan region.

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“…The main advantages of reanalysis products are their spatial and temporal resolution consistency over three or more decades, the large quantity of variables available, and the continuous improvements of their model resolution and biases (Schubert et al 2008;Dee et al 2016). This is why reanalysis products are among the most-used datasets in the study of weather and climate (Fuka et al 2014;Essou et al 2017;Bhattacharya et al 2019;Uniyal et al 2019;Luo et al 2020). However, few studies compared ETo computed using reanalysis data with observed ETo data (Yao et al 2014;Martins et al 2017;Tian et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Impacts of climate change and rising atmospheric CO2 on future projected reference evapotranspiration in Emilia-Romagna (Italy)

Hamouda

Tomozeiu

Pavan

et al. 2021

Theor Appl Climatol

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The continuous increase of atmospheric CO2 content mainly due to anthropogenic CO2 emissions is causing a rise in temperature on earth, altering the hydrological and meteorological processes and affecting crop physiology. Evapotranspiration is an important component of the hydrological cycle. Thus, understanding the change in evapotranspiration due to global warming is essential for better water resources planning and management and agricultural production. In this study, the effect of climate change with a focus on the combined effect of temperature and elevated CO2 concentrations on reference evapotranspiration (ETo) was evaluated using the Penman–Monteith equation. A EURO-CORDEX regional climate model (RCM) ensemble was used to estimate ETo in five locations in the Emilia-Romagna region (Northern Italy) during the period 2021–2050. Then, its projected changes in response to different CO2 concentrations (i.e., 372 ppm and 550 ppm) under two Representative Concentration Pathways (RCP) scenarios (i.e., RCP4.5 and RCP8.5) were analyzed. Simulation results with both scenarios, without increasing CO2 levels (372 ppm), showed that the annual and summertime ETo for all locations increased by an average of 4 to 5.4% with regard to the reference period 1981–2005, for an increase of air temperature by 1 to 1.5 °C. When the effect of elevated CO2 levels (550 ppm) was also considered in combination with projected changes in temperature, changes in both annual and summer ETo demand for all locations varied from − 1.1 to 2.2% during the 2021–2050 period with regard to the reference period 1981–2005. This shows that higher CO2 levels moderated the increase in ETo that accompanies an increase in air temperature.

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A case study for the assessment of the suitability of gridded reanalysis weather data for hydrological simulation in Beas river basin of North Western Himalaya

Cited by 22 publications

References 27 publications

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Evaluation of reanalysis and global meteorological products in Beas river basin of North-Western Himalaya

Impacts of climate change and rising atmospheric CO2 on future projected reference evapotranspiration in Emilia-Romagna (Italy)

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