scholarly journals The effect on river discharge estimation by considering an interaction between land surface process and river routing process

2015 ◽  
Vol 369 ◽  
pp. 81-86 ◽  
Author(s):  
K. Yorozu ◽  
Y. Tachikawa
Keyword(s):  
Soil Water ◽  
Land Surface ◽  
River Discharge ◽  
Hydrologic Model ◽  
Flow Routing ◽  
Hydrologic Process ◽  
Daily Discharge ◽  
Subsurface Runoff ◽  
Discharge Estimation ◽  
River Routing

Abstract. There is much research assessing the impact of climate change on the hydrologic cycle. However, it has often focused on a specific hydrologic process, without considering the interaction among hydrologic processes. In this study, a distributed hydrologic model considering the interaction between flow routing and land surface processes was developed, and its effect on river discharge estimation was investigated. The model enables consideration of flow routing, irrigation withdrawal from rivers at paddy fields, crop growth depending on water and energy status, and evapotranspiration based on meteorological, soil water and vegetation status. To examine the effects of hydrologic process interaction on river discharge estimation, a developed model was applied to the Chao Phraya river basin using near surface meteorological data collected by the Japanese Meteorological Research Institute's Atmospheric General Circulation Model (MRI-AGCM3.2S) with TL959 spatial resolution as forcing data. Also, a flow routing model, which was part of the developed model, was applied independently, using surface and subsurface runoff data from the same GCM. In the results, the developed model tended to estimate a smaller river discharge than was estimated by the river routing model, because of the irrigation effect. In contrast, the annual maximum daily discharge calculated by the developed model was 24% greater than that by the flow routing model. It is assumed that surface runoff in the developed model was greater than that in the flow routing model because the soil water content was maintained at a high level through irrigation withdrawal. As for drought discharge, which is defined as the 355th largest daily discharge, the developed model gave a discharge 2.7-fold greater than the flow routing model. It seems that subsurface runoff in the developed model was greater than that in the flow routing model. The results of this study suggest that considering hydrologic interaction in a numerical model could affect both flood and drought estimation.

scholarly journals Evaluation of the JULES land surface model in simulating catchment hydrology in Southern Africa

2013 ◽  
Vol 10 (8) ◽  
pp. 11093-11128 ◽  
Author(s):  
N. C. MacKellar ◽  
S. J. Dadson ◽  
M. New ◽  
P. Wolski
Keyword(s):  
Southern Africa ◽  
Land Surface ◽  
River Discharge ◽  
Water Resource Management ◽  
River Flow ◽  
Land Surface Model ◽  
Dry Season ◽  
Surface Model ◽  
Runoff Generation ◽  
Subsurface Runoff

Abstract. Land surface models (LSMs) are advanced tools which can be used to estimate energy, water and biogeochemical exchanges at regional scales. The inclusion of a river flow routing module in an LSM allows for the simulation of river discharge from a catchment and offers an approach to evaluate the response of the system to variations in climate and land-use, which can provide useful information for regional water resource management. This study offers insight into some of the pragmatic considerations of applying an LSM over a regional domain in Southern Africa. The objectives are to identify key parameter sensitivities and investigate differences between two runoff production schemes in physically contrasted catchments. The Joint UK Land Environment Simulator (JULES) LSM was configured for a domain covering Southern Africa at a 0.5° resolution. The model was forced with meteorological input from the WATCH Forcing Data for the period 1981–2001 and sensitivity to various model configurations and parameter settings were tested. Both the PDM and TOPMODEL sub-grid scale runoff generation schemes were tested for parameter sensitivities, with the evaluation focussing on simulated river discharge in sub-catchments of the Orange, Okavango and Zambezi rivers. It was found that three catchments respond differently to the model configurations and there is no single runoff parameterization scheme or parameter values that yield optimal results across all catchments. The PDM scheme performs well in the upper Orange catchment, but poorly in the Okavango and Zambezi, whereas TOPMODEL grossly underestimates discharge in the upper Orange and shows marked improvement over PDM for the Okavango and Zambezi. A major shortcoming of PDM is that it does not realistically represent subsurface runoff in the deep, porous soils typical of the Okavango and Zambezi headwaters. The dry-season discharge in these catchments is therefore not replicated by PDM. TOPMODEL, however, simulates a more realistic seasonal cycle of subsurface runoff and hence improved dry-season flow.

scholarly journals Recent changes to Arctic river discharge

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dongmei Feng ◽  
Colin J. Gleason ◽  
Peirong Lin ◽  
Xiao Yang ◽  
Ming Pan ◽  
...  
Keyword(s):  
Land Surface ◽  
River Discharge ◽  
Global Climate ◽  
Hydrologic Model ◽  
The Arctic ◽  
Small Rivers ◽  
Total Water ◽  
Daily Streamflow ◽  
Spring Freshet ◽  
Arctic Rivers

AbstractArctic rivers drain ~15% of the global land surface and significantly influence local communities and economies, freshwater and marine ecosystems, and global climate. However, trusted and public knowledge of pan-Arctic rivers is inadequate, especially for small rivers and across Eurasia, inhibiting understanding of the Arctic response to climate change. Here, we calculate daily streamflow in 486,493 pan-Arctic river reaches from 1984-2018 by assimilating 9.18 million river discharge estimates made from 155,710 satellite images into hydrologic model simulations. We reveal larger and more heterogenous total water export (3-17% greater) and water export acceleration (factor of 1.2-3.3 larger) than previously reported, with substantial differences across basins, ecoregions, stream orders, human regulation, and permafrost regimes. We also find significant changes in the spring freshet and summer stream intermittency. Ultimately, our results represent an updated, publicly available, and more accurate daily understanding of Arctic rivers uniquely enabled by recent advances in hydrologic modeling and remote sensing.

Complementing ERA5 and E-OBS20 with high resolution river discharge

2020 ◽  
Author(s):  
Stefan Hagemann ◽  
Tobias Stacke
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Land Surface ◽  
River Discharge ◽  
River Mouth ◽  
Water Model ◽  
Model Intercomparison ◽  
Station Data ◽  
Intercomparison Project ◽  
Subsurface Runoff

<p>The 0.5° resolution of many global observational datasets is not sufficient for the requirements of current state-of-the-art regional climate model (RCM) simulations over Europe. Here, the ERA5 reanalysis of the ECMWF (C3S 2017) and E-OBS data (Cornes et al. 2018) are frequently used as reference datasets when RCM results are evaluated on resolutions higher than 0.5°. In addition, ERA5 data are also commonly used to force regional ocean models. As ERA data do not comprise river discharges, the lateral forcing of freshwater inflow from land is taken from other data sources, such as station data, runoff climatologies, etc. However, these data are not necessarily consistent with the ERA5 forcing over the ocean surface. If such data are derived from station data, they are only available for specific rivers and not spatially homogeneously distributed for all coastal areas. In addition, they might not be representative for the river mouth if the respective station location is too far away from the river mouth, which is often the case.</p><p>In order to allow a consistent forcing of river discharges and evaluation of simulated hydrological fluxes, we extended ERA5 and E-OBS v20.0e with high resolution river discharge. This also allows a consistent assessment of hydrological changes from these two datasets. The discharge was simulated with the recently developed 5 Min. version of the Hydrological discharge (HD) model (Hagemann et al., submitted). Note that for the development of this HD model version, no river specific parameter adjustments were conducted so that the HD model is generally applicable for climate change studies and over ungauged catchments.</p><p>The HD model requires gridded fields of surface and subsurface runoff as input with a daily temporal resolution or higher. As no large-scale observations of these variables exist, they need to be calculated by a land surface scheme or hydrology model using observed or re-analyzed meteorological data. Here, we used the HydroPy global hydrological model, which is the successor of the MPI-HM model (Stacke and Hagemann 2012). The latter has contributed to the WATCH Water Model Intercomparison Project (WaterMIP; Haddeland et al. 2011) and the inter-sectoral impact model intercomparison project (ISIMIP; Warszawski et al. 2014). Note that ERA5 also comprises archived fields of surface and subsurface runoff, but it turned out that its separation of total runoff is not suitable to generate adequate river discharges with the HD model. In our presentation, we evaluate the simulated discharge using various metrics and consider significant discharge trends over Europe.</p><p><strong>References</strong></p><p>C3S (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS)</p><p>Cornes, R., et al. (2018) J. Geophys. Res. Atmos. 123, doi:10.1029/2017JD028200</p><p>Haddeland, I., et al. (2011). J. Hydrometeorol. 12, doi: 10.1175/2011jhm1324.1</p><p>Hagemann, S., T. Stacke and H. Ho-Hagemann, High resolution discharge simulations over Europe and the Baltic Sea catchment. Frontiers in Earth Sci., submitted.</p><p>Stacke, T. and Hagemann, S. (2012). Hydrol. Earth Syst. Sci. 16, doi: 10.5194/hess-16-2915-2012</p><p>Warszawski, L., et al. (2014) Proc. Natl. Acad. Sci. USA 111, doi: 10.1073/pnas.1312330110</p>

scholarly journals Assimilation of wide-swath altimetry observations to correct large-scale river routing model parameters

2019 ◽  
Author(s):  
Charlotte M. Emery ◽  
Sylvain Biancamaria ◽  
Aaron Boone ◽  
Sophie Ricci ◽  
Mélanie C. Rochoux ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Global Scale ◽  
Hydrologic Model ◽  
Model Parameters ◽  
True Value ◽  
Input Parameters ◽  
River Routing

Abstract. Land surface models combined with river routing models are widely used to study the continental part of the water cycle. They give global estimates of water flows and storages but not without non-negligible uncertainties; among which inexact input parameters have a significant part. The incoming Surface Water and Ocean Topography (SWOT) satellite mission, with a launch schedule for 2021, will be dedicated to measure water surface elevations, widths and surface slopes of rivers larger than 100 meters at global scale. SWOT will provide a significant amount of new data for river hydrology and they could be combined, through data assimilation, to global-scale models in order to correct their input parameters and reduce their associated uncertainty. The objective of this study is to present a data assimilation platform based on the asynchronous ensemble Kalman filter (AEnKF) that assimilates synthetical SWOT observations of water elevations to correct the input parameters of a large scale hydrologic model over a 21-day time window. The study is applied on the ISBA-CTRIP model over the Amazon basin and focuses on correcting the spatial distribution of the river Manning coefficients. The data assimilation algorithm, tested through a set of Observing System Simulation Experiments (OSSE), is able to retrieve the true value of the Manning coefficients within one assimilation cycle most of the time and shows perspectives in tracking the Manning coefficient temporal variations. Ultimately, in order to deal with potential bias between the observed and the model bathymetry, the assimilation of water elevation anomalies was also tested and showed promising results.

scholarly journals The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km

2019 ◽  
Vol 12 (6) ◽  
pp. 2501-2521 ◽  
Author(s):  
Stephan Thober ◽  
Matthias Cuntz ◽  
Matthias Kelbling ◽  
Rohini Kumar ◽  
Juliane Mai ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Land Surface ◽  
Hydrologic Model ◽  
River Network ◽  
Time Stepping ◽  
Danube Catchment ◽  
Adaptive Time ◽  
Adaptive Time Stepping ◽  
River Routing

Abstract. Routing streamflow through a river network is a fundamental requirement to verify lateral water fluxes simulated by hydrologic and land surface models. River routing is performed at diverse resolutions ranging from few kilometres to 1∘. The presented multiscale routing model mRM calculates streamflow at diverse spatial and temporal resolutions. mRM solves the kinematic wave equation using a finite difference scheme. An adaptive time stepping scheme fulfilling a numerical stability criterion is introduced in this study and compared against the original parameterisation of mRM that has been developed within the mesoscale hydrologic model (mHM). mRM requires a high-resolution river network, which is upscaled internally to the desired spatial resolution. The user can change the spatial resolution by simply changing a single number in the configuration file without any further adjustments of the input data. The performance of mRM is investigated on two datasets: a high-resolution German dataset and a slightly lower resolved European dataset. The adaptive time stepping scheme within mRM shows a remarkable scalability compared to its predecessor. Median Kling–Gupta efficiencies change less than 3 % when the model parameterisation is transferred from 3 to 48 km resolution. mRM also exhibits seamless scalability in time, providing similar results when forced with hourly and daily runoff. The streamflow calculated over the Danube catchment by the regional climate model REMO coupled to mRM reveals that the 50 km simulation shows a smaller bias with respect to observations than the simulation at 12 km resolution. The mRM source code is freely available and highly modular, facilitating easy internal coupling in existing Earth system models.

scholarly journals On the Suitability of GCM Runoff Fields for River Discharge Modeling: A Case Study Using Model Output from HadGEM2 and ECHAM5

2012 ◽  
Vol 13 (1) ◽  
pp. 140-154 ◽  
Author(s):  
F. C. Sperna Weiland ◽  
L. P. H. van Beek ◽  
J. C. J. Kwadijk ◽  
M. F. P. Bierkens
Keyword(s):  
Land Surface ◽  
River Discharge ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Subsurface Runoff ◽  
Discharge Modeling ◽  
Annual Discharge

Abstract The representation of hydrological processes in land surface schemes (LSSs) has recently been improved. In this study, the usability of GCM runoff for river discharge modeling is evaluated by validating the mean, timing, and amplitude of the modeled annual discharge cycles against observations. River discharge was calculated for six large rivers using runoff, precipitation, and actual evaporation from the GCMs ECHAM5 and Hadley Centre Global Environmental Model version 2 (HadGEM2). Four methods were applied: 1) accumulation of GCM runoff, 2) routing of GCM runoff, 3) routing of GCM runoff combined with temporal storage of subsurface runoff, and 4) offline hydrological modeling with the global distributed hydrological model PCRaster Global Water Balance (PCR-GLOBWB) using meteorological data from the GCMs as forcing. The quality of discharge generated by all four methods is highly influenced by the quality of the GCM data. In small catchments, the methods that include runoff routing perform equally well, although offline modeling with PRC-GLOBWB outperforms the other methods for ECHAM5 data. For larger catchments, routing introduces realistic travel times, decreased day-to-day variability, and it reduces extremes. Complexity of the LSS of both GCMs is comparable to the complexity of the hydrological model. However, in HadGEM2 the absence of subgrid variability for saturated hydraulic conductivity results in a large subsurface runoff flux and a low seasonal variability in the annual discharge cycle. The analysis of these two GCMs shows that when LSSs are tuned to reproduce realistic water partitioning at the grid scale and a routing scheme is also included, discharge variability and change derived from GCM runoff could be as useful as changes derived from runoff obtained from offline simulations using large-scale hydrological models.

scholarly journals The multiscale Routing Model mRM v1.0: simple river routing at resolutions from 1 to 50 km

2019 ◽  
Author(s):  
Stephan Thober ◽  
Matthias Cuntz ◽  
Matthias Kelbling ◽  
Rohini Kumar ◽  
Juliane Mai ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Land Surface ◽  
Climate Model ◽  
Hydrologic Model ◽  
River Network ◽  
Time Step ◽  
Danube Catchment ◽  
Adaptive Time ◽  
River Routing

Abstract. Routing streamflow through a river network is a fundamental requirement to verify lateral water fluxes simulated by hydrologic and land surface models. River routing is performed at diverse resolutions ranging from few kilometers to around 1°. The presented multiscale Routing Model mRM calculates streamflow at diverse spatial and temporal resolutions. mRM solves the kinematic wave equation using a finite difference scheme. An adaptive time stepping scheme fulfilling a numerical stability criteria is introduced in this study and compared against the original parametrization of mRM that has been developed within the mesoscale Hydrologic Model (mHM). mRM requires a high-resolution river network, which is upscaled internally to the desired spatial resolution. The user can change the spatial resolution by simply changing one number in the configuration file without any further adjustments of the input data. The performance of mRM is investigated on two datasets: a high-resolution German dataset and a slightly lower resolution European dataset. The adaptive time step scheme within mRM shows a remarkable scalability compared to its predecessor. Median Kling-Gupta efficiencies change less than 3 percent when the model parametrization is transferred from 3 to 48 km resolution. mRM also exhibits seamless scalability in time, providing identical results when forced with hourly and daily runoff. The streamflow calculated over the Danube catchment by the Regional Climate Model REMO coupled to mRM is comparable at 25 and 50 km resolution. The mRM source code is freely available and highly modular facilitating an easy internal coupling in existing Earth System Models.

scholarly journals Exploring the Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land Surface Model

2017 ◽  
Vol 18 (3) ◽  
pp. 897-915 ◽  
Author(s):  
Jennifer L. Jefferson ◽  
Reed M. Maxwell ◽  
Paul G. Constantine
Keyword(s):  
Land Surface ◽  
Stomatal Resistance ◽  
Hydrologic Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Common Land Model ◽  
Surface Models ◽  
Input Parameters ◽  
Rate Of Photosynthesis ◽  
Quantities Of Interest

Abstract Land surface models, like the Common Land Model component of the ParFlow integrated hydrologic model (PF-CLM), are used to estimate transpiration from vegetated surfaces. Transpiration rates quantify how much water moves from the subsurface through the plant and into the atmosphere. This rate is controlled by the stomatal resistance term in land surface models. The Ball–Berry stomatal resistance parameterization relies, in part, on the rate of photosynthesis, and together these equations require the specification of 20 input parameters. Here, the active subspace method is applied to 2100 year-long PF-CLM simulations, forced by atmospheric data from California, Colorado, and Oklahoma, to identify which input parameters are important and how they relate to three quantities of interest: transpiration, stomatal resistance from the sunlit portion of the canopy, and stomatal resistance from the shaded portion. The slope (mp) and intercept (bp) parameters associated with the Ball–Berry parameterization are consistently important for all locations, along with five parameters associated with ribulose bisphosphate carboxylase/oxygenase (RuBisCO)- and light-limited rates of photosynthesis [CO2 Michaelis–Menten constant at 25°C (kc25), maximum ratio of oxygenation to carboxylation (ocr), quantum efficiency at 25°C (qe25), maximum rate of carboxylation at 25°C (vcmx25), and multiplier in the denominator of the equation used to compute the light-limited rate of photosynthesis (wj1)]. The importance of these input parameters, quantified by the active variable weight, and the relationship between the input parameters and quantities of interest vary seasonally and diurnally. Input parameter values influence transpiration rates most during midday, summertime hours when fluxes are large. This research informs model users about which photosynthesis and stomatal resistance parameters should be more carefully selected. Quantifying sensitivities associated with the stomatal resistance term is necessary to better understand transpiration estimates from land surface models.

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