River basin hydrology in a global off-line land-surface model

The use of numerical weather prediction (NWP) model to dynamically downscale coarse climate reanalysis data allows for the capture of processes that are influenced by land cover and topographic features. Climate reanalysis downscaling is useful for hydrology modeling, where catchment processes happen on a spatial scale that is not represented in reanalysis models. Selecting proper parameterization in the NWP for downscaling is crucial to downscale the climate variables of interest. In this work, we are interested in identifying at least one combination of physics in the Weather Research Forecast (WRF) model that performs well in our area of study that covers the Baker River Basin and the Northern Patagonian Icecap (NPI) in the south of Chile. We used ERA-Interim reanalysis data to run WRF in twenty-four different combinations of physics for three years in a nested domain of 22.5 and 4.5 km with 34 vertical levels. From more to less confident, we found that, for the planetary boundary layer (PBL), the best option is to use YSU; for the land surface model (LSM), the best option is the five-Layer Thermal, RRTM for longwave, Dudhia for short wave radiation, and Thompson for the microphysics. In general, the model did well for temperature (average, minimum, maximum) for most of the observation points and configurations. Precipitation was good, but just a few configurations stood out (i.e., conf-9 and conf-10). Surface pressure and Relative Humidity results were not good or bad, and it depends on the statistics with which we evaluate the time series (i.e., KGE or NSE). The results for wind speed were inferior; there was a warm bias in all of the stations. Once we identify the best configuration in our experiment, we run WRF for one year using ERA5 and FNL0832 climate reanalysis. Our results indicate that Era-interim provided better results for precipitation. In the case of temperature, FNL0832 gave better results; however, all of the models’ performances were good. Therefore, working with ERA-Interim seems the best option in this region with the physics selected. We did not experiment with changes in resolution, which may have improved results with ERA5 that has a better spatial and temporal resolution.

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Variations in terrestrial water storage in the Lancang-Mekong river basin from GRACE solutions and land surface model

Journal of Hydrology ◽

10.1016/j.jhydrol.2019.124258 ◽

2020 ◽

Vol 580 ◽

pp. 124258 ◽

Cited By ~ 4

Author(s):

Wenlong Jing ◽

Xiaodan Zhao ◽

Ling Yao ◽

Hao Jiang ◽

Jianhui Xu ◽

...

Keyword(s):

River Basin ◽

Land Surface ◽

Water Storage ◽

Land Surface Model ◽

Mekong River ◽

Surface Model ◽

Terrestrial Water Storage ◽

Mekong River Basin ◽

Terrestrial Water

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Simulating Flash Floods Using Geostationary Satellite-Based Rainfall Estimation Coupled with a Land Surface Model

Hydrology ◽

10.3390/hydrology7010009 ◽

2020 ◽

Vol 7 (1) ◽

pp. 9 ◽

Cited By ~ 3

Author(s):

Dwi Prabowo Yuga Suseno ◽

Tomohito J. Yamada

Keyword(s):

Spatial Distribution ◽

River Basin ◽

Land Surface ◽

River Flow ◽

Flash Flood ◽

Land Surface Model ◽

Flash Floods ◽

Flood Mitigation ◽

Surface Model ◽

Flow Simulations

Clarifying hydrologic behavior, especially behavior related to extreme events such as flash floods, is vital for flood mitigation and management. However, discharge and rainfall measurement data are scarce, which is a major obstacle to flood mitigation. This study: (i) simulated flash floods on a regional scale using three types of rainfall forcing implemented in a land surface model; and (ii) evaluated and compared simulated flash floods with the observed discharge. The three types of rainfall forcing were those observed by the Automated Meteorological Data Acquisition System (AMeDAS) (Simulation I), the observed rainfall from the Ministry of Land, Infrastructure and Transportation (MLIT) (Simulation II), and the estimated rainfall from the Multi-purpose Transport Satellite (MTSAT), which was downscaled by AMeDAS rainfall (Simulation III). MLIT rainfall observations have a denser station network over the Ishikari River basin (spacing of approximately 10 km) compared with AMeDAS (spacing of approximately 20 km), so they are expected to capture the rainfall spatial distribution more accurately. A land surface model, the Minimal Advance Treatments of Surface Interaction and Runoff (MATSIRO), was implemented for the flash flood simulation. The river flow simulations were run over the Ishikari river basin at a 1-km grid resolution and a 1-h temporal resolution during August 2010. The statistical performance of the river flow simulations during a flash flood event on 23 and 24 August 2010 demonstrated that Simulation I was reasonable compared with Simulation III. The findings also suggest that the advantages of the MTSAT-based estimated rainfall (i.e., good spatial distribution) can be coupled with the benefit of direct AMeDAS observations (i.e., representation of the true rainfall).

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Parameter sensitivity analysis and optimization of Noah land surface model with field measurements from Huaihe River Basin, China

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-015-1033-5 ◽

2015 ◽

Vol 29 (5) ◽

pp. 1383-1401 ◽

Cited By ~ 7

Author(s):

Ting Hou ◽

Yonghua Zhu ◽

Haishen Lü ◽

Edward Sudicky ◽

Zhongbo Yu ◽

...

Keyword(s):

Sensitivity Analysis ◽

River Basin ◽

Land Surface ◽

Land Surface Model ◽

Field Measurements ◽

Surface Model ◽

Huaihe River Basin ◽

Parameter Sensitivity Analysis ◽

Huaihe River ◽

Noah Land Surface Model

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Regional Parameter Estimation of the VIC Land Surface Model: Methodology and Application to River Basins in China

Journal of Hydrometeorology ◽

10.1175/jhm568.1 ◽

2007 ◽

Vol 8 (3) ◽

pp. 447-468 ◽

Cited By ~ 100

Author(s):

Zhenghui Xie ◽

Fei Yuan ◽

Qingyun Duan ◽

Jing Zheng ◽

Miaoling Liang ◽

...

Keyword(s):

Parameter Estimation ◽

River Basin ◽

Land Surface ◽

Land Surface Model ◽

River Basins ◽

Large River ◽

Surface Model ◽

Parameter Estimates ◽

Climatic Zones ◽

Streamflow Simulation

Abstract This paper presents a methodology for regional parameter estimation of the three-layer Variable Infiltration Capacity (VIC-3L) land surface model with the goal of improving the streamflow simulation for river basins in China. This methodology is designed to obtain model parameter estimates from a limited number of calibrated basins and then regionalize them to uncalibrated basins based on climate characteristics and large river basin domains, and ultimately to continental China. Fourteen basins from different climatic zones and large river basins were chosen for model calibration. For each of these basins, seven runoff-related model parameters were calibrated using a systematic manual calibration approach. These calibrated parameters were then transferred within the climate and large river basin zones or climatic zones to the uncalibrated basins. To test the efficiency of the parameter regionalization method, a verification study was conducted on 19 independent river basins in China. Overall, the regionalized parameters, when evaluated against the a priori parameter estimates, were able to reduce the model bias by 0.4%–249.8% and relative root-mean-squared error by 0.2%–119.1% and increase the Nash–Sutcliffe efficiency of the streamflow simulation by 1.9%–31.7% for most of the tested basins. The transferred parameters were then used to perform a hydrological simulation over all of China so as to test the applicability of the regionalized parameters on a continental scale. The continental simulation results agree well with the observations at regional scales, indicating that the tested regionalization method is a promising scheme for parameter estimation for ungauged basins in China.

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Validation of IAP94 land surface model over the Huaihe River basin with HUBEX field experiment data

Advances in Atmospheric Sciences ◽

10.1007/s00376-001-0009-1 ◽

2001 ◽

Vol 18 (1) ◽

pp. 139-154 ◽

Cited By ~ 1

Author(s):

Yang Xiaosong ◽

Lin Zhaohui ◽

Dai Yongjiu ◽

Guo Yufu

Keyword(s):

Field Experiment ◽

River Basin ◽

Land Surface ◽

Land Surface Model ◽

Surface Model ◽

Huaihe River Basin ◽

Huaihe River ◽

Experiment Data ◽

The Huaihe River

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Hydrological recurrence as a measure for large river basin classification and process understanding

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8191-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8191-8238 ◽

Cited By ~ 1

Author(s):

R. Fernandez ◽

T. Sayama

Keyword(s):

River Basin ◽

Land Surface ◽

Fourier Transforms ◽

Land Surface Model ◽

Arctic Region ◽

River Basins ◽

Large River ◽

Global Scale ◽

Surface Model ◽

Monsoon Area

Abstract. Hydrologic functions of river basins are summarized as water collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. In some situations these four variables behave more in a recurrent manner by repeating in a similar range year after year or in other situations they exhibit more randomness with higher variations year by year. The degree of recurrence in runoff is important not only for water resources management but also for hydrologic process understandings, especially in terms of how the other three variables determine the degree of recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to global scale and large basins based on the combinations of recurrence in the four variables. We evaluate it by Lagged Autocorrelation, Fast Fourier Transforms and Colwell's Indices of variables obtained from EU-WATCH dataset composed by eight hydrologic and land surface model outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian Monsoon area and part of higher latitudes with oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and subarctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In humid tropic region, the basins belong to a class with high recurrence in all the variables, while in subtropical region many of the river basins have low recurrence. In temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the subarctic and arctic region, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different datasets to provide useful insights into the understanding of hydrologic regimes based on the classification.

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Simulating Flash Floods Using a Geostationary Satellite-Based Rainfall Estimation Coupled with a Land Surface Model

10.20944/preprints201909.0312.v1 ◽

2019 ◽

Author(s):

Dwi Prabowo Yuga Suseno ◽

Tomohito J Yamada

Keyword(s):

Spatial Distribution ◽

River Basin ◽

Land Surface ◽

River Flow ◽

Land Surface Model ◽

Flash Floods ◽

Flood Mitigation ◽

Rainfall Simulation ◽

Surface Model ◽

Flow Simulations

Clarifying hydrologic behavior, especially behavior related to extreme events such as flash floods, is vital for flood mitigation and management. However, discharge and rainfall measurement data are scarce, which is a major obstacle to flood mitigation. This study (i) simulated flash floods on a regional scale using three types of rainfall forcing implemented in a land surface model and (ii) evaluated and compared simulated flash floods with the observed discharge. The three types of rainfall forcing were those observed by the Automated Meteorological Data Acquisition System (AMeDAS) (Simulation I), the observed rainfall from the Ministry of Land, Infrastructure and Transportation (MLIT) (Simulation II), and the estimated rainfall from the Multi-purpose Transport Satellite (MTSAT), which was downscaled by AMeDAS rainfall (Simulation III). MLIT rainfall observations have a denser station network over the Ishikari River basin (spacing of approximately 10 km) compared with AMeDAS (spacing of approximately 20 km), so they are expected to capture the rainfall spatial distribution more accurately. A land surface model, Minimal Advance Treatments of Surface Interaction and Runoff (MATSIRO), was implemented for the flash flood simulation. The river flow simulations were run over the Ishikari river basin at a 1-km grid resolution and a 1-h temporal resolution during August 2010. The statistical performance of the river flow simulations demonstrated that Simulation I was reasonable compared with Simulation III. The findings also suggest that the advantage of the MTSAT-based estimated rainfall (i.e., good spatial distribution) can be coupled with the benefit of direct AMeDAS observations (i.e., representation of the true rainfall).

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