Satellite-based rainfall estimates evaluation using a parsimonious hydrological model in the complex climate and topography of the Nile River Catchments

2021 ◽  
pp. 105939
Author(s):  
Tesfay G. Gebremicael ◽  
Matthew J. Deitch ◽  
Haley N. Gancel ◽  
Amanda C. Croteau ◽  
Gebremedhin G. Haile ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Nile River ◽  
River Catchments ◽  
Rainfall Estimates

Use of Radar Quantitative Precipitation Estimates (QPEs) for Improved Hydrological Model Calibration and Flood Forecasting

2021 ◽  
Author(s):  
Dayal Wijayarathne ◽  
Paulin Coulibaly ◽  
Sudesh Boodoo ◽  
David Sills
Keyword(s):  
Real Time ◽  
Model Calibration ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Hydrological Models ◽  
Radar Rainfall ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates ◽  
Streamflow Simulation ◽  
Rainfall Estimates

AbstractFlood forecasting is essential to minimize the impacts and costs of floods, especially in urbanized watersheds. Radar rainfall estimates are becoming increasingly popular in flood forecasting because they provide the much-needed real-time spatially distributed precipitation information. The current study evaluates the use of radar Quantitative Precipitation Estimates (QPEs) in hydrological model calibration for streamflow simulation and flood mapping in an urban setting. Firstly, S-band and C-band radar QPEs were integrated into event-based hydrological models to improve the calibration of model parameters. Then, rain gauge and radar precipitation estimates’ performances were compared for hydrological modeling in an urban watershed to assess radar QPE's effects on streamflow simulation accuracy. Finally, flood extent maps were produced using coupled hydrological-hydraulic models integrated within the Hydrologic Engineering Center- Real-Time Simulation (HEC-RTS) framework. It is shown that the bias correction of radar QPEs can enhance the hydrological model calibration. The radar-gauge merging obtained a KGE, MPFC, NSE, and VE improvement of about + 0.42, + 0.12, + 0.78, and − 0.23, respectively for S-band and + 0.64, + 0.36, + 1.12, and − 0.34, respectively for C-band radar QPEs. Merged radar QPEs are also helpful in running hydrological models calibrated using gauge data. The HEC-RTS framework can be used to produce flood forecast maps using the bias-corrected radar QPEs. Therefore, radar rainfall estimates could be efficiently used to forecast floods in urbanized areas for effective flood management and mitigation. Canadian flood forecasting systems could be efficiently updated by integrating bias-corrected radar QPEs to simulate streamflow and produce flood inundation maps.

scholarly journals Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

2013 ◽  
Vol 10 (8) ◽  
pp. 10495-10534
Author(s):  
D. Zhu ◽  
Y. Xuan ◽  
I. Cluckie
Keyword(s):  
Hydrological Model ◽  
Scale Effects ◽  
Model Performance ◽  
Extreme Rainfall ◽  
Distributed Model ◽  
Catchment Scale ◽  
Radar Rainfall ◽  
Rainfall Events ◽  
The Impact ◽  
Rainfall Estimates

Abstract. Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the Upper Medway catchment of Southeast England using the UK NIMROD radar rainfall estimates using three hydrological models based upon three very different structures, e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF. We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar-rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

Evaluation of satellite rainfall estimates over the Lake Tana basin at the source region of the Blue Nile River

2018 ◽  
Vol 212 ◽  
pp. 43-53 ◽  
Author(s):  
Ayele Almaw Fenta ◽  
Hiroshi Yasuda ◽  
Katsuyuki Shimizu ◽  
Yasuomi Ibaraki ◽  
Nigussie Haregeweyn ◽  
...  
Keyword(s):  
Source Region ◽  
Nile River ◽  
Lake Tana ◽  
Blue Nile ◽  
Satellite Rainfall ◽  
Rainfall Estimates ◽  
Lake Tana Basin

Implications of radar rainfall estimates uncertainty on distributed hydrological model predictions

2011 ◽  
Vol 100 (2-3) ◽  
pp. 237-245 ◽  
Author(s):  
Kai Schröter ◽  
Xavier Llort ◽  
Carlos Velasco-Forero ◽  
Manfred Ostrowski ◽  
Daniel Sempere-Torres
Keyword(s):  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Radar Rainfall ◽  
Model Predictions ◽  
Rainfall Estimates

scholarly journals Bridging glacier and river catchment scales: an efficient representation of glacier dynamics in a hydrological model

2016 ◽  
Author(s):  
Michel Wortmann ◽  
Tobias Bolch ◽  
Valentina Krysanova ◽  
Su Buda
Keyword(s):  
Water Resource Management ◽  
Hydrological Model ◽  
Snow Accumulation ◽  
Data Availability ◽  
Glacier Mass Balance ◽  
Full Account ◽  
Fully Integrated ◽  
Mountainous Catchments ◽  
Glacier Dynamics ◽  
River Catchments

Abstract. Glacierised river catchments have been shown to be highly sensitive to climate change, while large populations depend on the water resources originating from them. Hydrological models are used to aid water resource management, yet their treatment of glacier processes is either rudimentary in large applications or linked to fully distributed glacier models that prevent larger model domains. Also, data scarcity in mountainous catchments has hampered the implementation of physically based approaches over entire river catchments. A fully integrated glacier dynamics module was developed for the eco-hydrological model SWIM (SWIM-G) that takes full account of the spatial heterogeneity of mountainous catchments but keeps in line with the semi-distributed disaggregation of the hydrological model. The glacierised part of the catchment is disaggregated into glaciological response units that are based on subbasin, elevation zone and aspect classes. They seamlessly integrate into the hydrological response units of the hydrological model SWIM. Robust and simple approaches to ice flow, avalanching, snow accumulation and metamorphism as well as glacier ablation under consideration of aspect, debris cover and sublimation are implemented in the model, balancing process complexity and data availability. The fully integrated is also capable of simulating a range of other hydrological processes that are common for larger mountainous catchments such as reservoirs, irrigation agriculture and runoff from a diverse soil and vegetation cover. SWIM-G is initialised and calibrated to initial glacier hypsometry, glacier mass balance and river discharge. While the model is intended to be used in medium to large river basins with data-scarce and glacierised headwaters, it is here validated in the data-abundant catchment of the Upper Rhone River, Switzerland and the data-scarce catchment of the Upper Aksu River, Kyrgyzstan/NW China.

scholarly journals Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

2014 ◽  
Vol 18 (1) ◽  
pp. 257-272 ◽  
Author(s):  
D. Zhu ◽  
Y. Xuan ◽  
I. Cluckie
Keyword(s):  
Hydrological Model ◽  
Scale Effects ◽  
Model Performance ◽  
Extreme Rainfall ◽  
Distributed Model ◽  
Catchment Scale ◽  
Radar Rainfall ◽  
Rainfall Events ◽  
The Impact ◽  
Rainfall Estimates

Abstract. Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

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