River parametrisation of the JULES land surface model for improved runoff routing at the global scale.

2021 ◽  
Author(s):  
Aristeidis Koutroulis ◽  
Manolis Grillakis ◽  
Camilla Mathison ◽  
Eleanor Burke
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
Flow Simulation ◽  
Surface Model ◽  
Routing Scheme ◽  
Basin Scale ◽  
River Flow Simulation ◽  
River Routing

<p>The JULES land surface model has a wide ranging application in studying different processes of the earth system including hydrological modeling [1]. Our aim is to tune the existing configuration of the global river routing scheme at 0.5<sup>o</sup> spatial resolution [2] and improve river flow simulation performance at finer temporal scales. To do so, we develop a factorial experiment of varying effective river velocity and meander coefficient, components of the Total Runoff Integrating Pathways (TRIP) river routing scheme. We test and adjust best performing configurations at the basin scale based on observations from GRDC 230 stations that exhibiting a variety of hydroclimatic and physiographic conditions. The analysis was focused on watersheds of near-natural conditions [3] to avoid potential influences of human management on river flow. The HydroATLAS database [4] was employed to identify basin scale descriptive hydro-environmental indicators that could be associated with the components of the TRIP. These indicators summarize hydrologic and physiographic characteristics of the drainage area of each flow gauge. For each basin we select the best performing set of TRIP parameters per basin resulting to the optimal efficiency of river flow simulation based on the Nash–Sutcliffe and Kling–Gupta efficiency metrics. We find that better performance is driven predominantly by characteristics related to the stream gradient and terrain slope. These indicators can serve as descriptors for extrapolating the adjustment of TRIP parameters for global land configurations at 0.5<sup>o</sup> spatial resolution using regression models.</p><p> </p><p>[1] Papadimitriou et al 2017, Hydrol. Earth Syst. Sci., 21, 4379–4401</p><p>[2] Falloon et al 2007. Hadley Centre Tech. Note 72, 42 pp.</p><p>[3] Fang Zhao et al 2017 Environ. Res. Lett. 12 075003</p><p>[4] Linke et al 2019, Scientific Data 6: 283.</p>

scholarly journals ORCHIDEE-ROUTING: A new river routing scheme using a high resolution hydrological database

2018 ◽  
Author(s):  
Trung Nguyen-Quang ◽  
Jan Polcher ◽  
Agnès Ducharne ◽  
Thomas Arsouze ◽  
Xudong Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
River Flow ◽  
Anthropogenic Impacts ◽  
Computational Cost ◽  
Land Surface Model ◽  
Surface Model ◽  
Routing Scheme ◽  
Wide Range ◽  
River Routing

Abstract. This study presents a revised river routing scheme (RRS) for the Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model. The revision is carried out to benefit from the high resolution topography provided the Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS), processed to a resolution of approximately 1 kilometer. The RRS scheme of the ORCHIDEE uses a unit-to-unit routing concept which allows to preserve as much of the hydrological information of the HydroSHEDS as the user requires. The evaluation focuses on 12 rivers of contrasted size and climate which contribute freshwater to the Mediterranean Sea. First, the numerical aspect of the new RRS is investigated, to identify the practical configuration offering the best trade-off between computational cost and simulation quality for ensuing validations. Second, the performance of the revised scheme is evaluated against observations at both monthly and daily timescales. The new RRS captures satisfactorily the seasonal variability of river discharges, although important biases come from the water budget simulated by the ORCHIDEE model. The results highlight that realistic streamflow simulations require accurate precipitation forcing data and a precise river catchment description over a wide range of scales, as permitted by the new RRS. Detailed analyses at the daily timescale show promising performances of this high resolution RRS for replicating river flow variation at various frequencies. Eventually, this RRS is well adapted for further developments in the ORCHIDEE land surface model to assess anthropogenic impacts on river processes (e.g. damming for irrigation operation).

scholarly journals ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological database

2018 ◽  
Vol 11 (12) ◽  
pp. 4965-4985 ◽  
Author(s):  
Trung Nguyen-Quang ◽  
Jan Polcher ◽  
Agnès Ducharne ◽  
Thomas Arsouze ◽  
Xudong Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
River Flow ◽  
Anthropogenic Impacts ◽  
Computational Cost ◽  
Land Surface Model ◽  
Surface Model ◽  
Routing Scheme ◽  
Wide Range ◽  
River Routing

Abstract. The river routing scheme (RRS) in the Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model is a valuable tool for closing the water cycle in a coupled environment and for validating the model performance. This study presents a revision of the RRS of the ORCHIDEE model that aims to benefit from the high-resolution topography provided by the Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS), which is processed to a resolution of approximately 1 km. Adapting a new algorithm to construct river networks, the new RRS in ORCHIDEE allows for the preservation of as much of the hydrological information from HydroSHEDS as the user requires. The evaluation focuses on 12 rivers of contrasting size and climate which contribute freshwater to the Mediterranean Sea. First, the numerical aspect of the new RRS is investigated, in order to identify the practical configuration offering the best trade-off between computational cost and simulation quality for ensuing validations. Second, the performance of the new scheme is evaluated against observations at both monthly and daily timescales. The new RRS satisfactorily captures the seasonal variability of river discharge, although important biases stem from the water budget simulated by the ORCHIDEE model. The results highlight that realistic streamflow simulations require accurate precipitation forcing data and a precise river catchment description over a wide range of scales, as permitted by the new RRS. Detailed analyses at the daily timescale show the promising performance of this high-resolution RRS with respect to replicating river flow variation at various frequencies. Furthermore, this RRS may also eventually be well adapted for further developments in the ORCHIDEE land surface model to assess anthropogenic impacts on river processes (e.g. damming for irrigation operation).

scholarly journals Evaluating LSM-Based Water Budgets over a West African Basin Assisted with a River Routing Scheme

2014 ◽  
Vol 15 (6) ◽  
pp. 2331-2346 ◽  
Author(s):  
Augusto C. V. Getirana ◽  
Aaron Boone ◽  
Christophe Peugeot
Keyword(s):  
Deep Water ◽  
Land Surface ◽  
Land Surface Model ◽  
Base Flow ◽  
Water Infiltration ◽  
Surface Model ◽  
Daily Streamflow ◽  
Routing Scheme ◽  
Multidisciplinary Analysis ◽  
River Routing

Abstract Within the framework of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project phase 2 (ALMIP-2), this study evaluates the water balance simulated by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) over the upper Ouémé River basin, in Benin, using a mesoscale river routing scheme (RRS). The RRS is based on the nonlinear Muskingum–Cunge method coupled with two linear reservoirs that simulate the time delay of both surface runoff and base flow that are produced by land surface models. On the basis of the evidence of a deep water-table recharge in that region, a reservoir representing the deep-water infiltration (DWI) is introduced. The hydrological processes of the basin are simulated for the 2005–08 AMMA field campaign period during which rainfall and streamflow data were intensively collected over the study area. Optimal RRS parameter sets were determined for three optimization experiments that were performed using daily streamflow at five gauges within the basin. Results demonstrate that the RRS simulates streamflow at all gauges with relative errors varying from −20% to 3% and Nash–Sutcliffe coefficients varying from 0.62 to 0.90. DWI varies from 24% to 67% of the base flow as a function of the subbasin. The relatively simple reservoir DWI approach is quite robust, and further improvements would likely necessitate more complex solutions (e.g., considering seasonality and soil type in ISBA); thus, such modifications are recommended for future studies. Although the evaluation shows that the simulated streamflows are generally satisfactory, further field investigations are necessary to confirm some of the model assumptions.

Rethinking large scale river routing by leveraging a field-scale resolving land surface model

2020 ◽  
Author(s):  
Nathaniel Chaney ◽  
Noemi Vergopolan ◽  
Colby Fisher
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Land Surface Model ◽  
Added Value ◽  
Surface Model ◽  
Earth System ◽  
Field Scale ◽  
Routing Scheme ◽  
Earth System Models ◽  
River Routing

<p>Over the past decade there has been important progress towards modeling the water, energy, and carbon cycles at field scales (10-100 meter) over continental extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid hydrologic response units (HRUs); these HRUs are defined via cluster analysis of available field-scale environmental datasets (e.g., elevation). However, until now, there has yet to be complementary advances in river routing schemes that are able to fully harness HydroBlocks’ approach to sub-grid heterogeneity, thus limiting the added value of field-scale resolving land surface models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). In this presentation, we will introduce a novel large scale river routing scheme that leverages the modeled field-scale heterogeneity in HydroBlocks through more realistic sub-grid stream network topologies, reach-based river routing, and the simulation of floodplain dynamics.</p><p>The primary features of the novel river routing scheme include: 1) each macroscale grid cell is assigned its own river network delineated from field-scale DEMs; 2) similar sub-grid reaches (e.g., Shreve order) are grouped/clustered to ensure computational tractability; 3) the fine-scale inlet/outlet reaches of the macroscale grid cells are linked to assemble the continental river networks; 4) river dynamics are solved at the reach-level via an implicit solution of the Kinematic wave with floodplain dynamics; 5) two way connectivity is established between each cell’s sub-grid HRUs and the river network. The resulting routing scheme is able to effectively represent sub-100 meter-delineated stream networks within Earth system models with relatively minor increases in computation with respect to existing approaches. To illustrate the scheme’s novelty when coupled to the HydroBlocks land surface model, we will present simulation results over the Yellowstone river in the United States between 2002 and 2018. We will show the added value of the scheme when compared to existing approaches with regards to floodplain dynamics, water management, and riparian corridors. Furthermore, we will present results regarding the scheme’s computational tractability to ensure the feasibility of its use within Earth system models. Finally, we will discuss the potential of this approach to enhance flood and drought monitoring tools, numerical weather prediction, and climate models.</p>

scholarly journals River Network Routing on the NHDPlus Dataset

2011 ◽  
Vol 12 (5) ◽  
pp. 913-934 ◽  
Author(s):  
Cédric H. David ◽  
David R. Maidment ◽  
Guo-Yue Niu ◽  
Zong-Liang Yang ◽  
Florence Habets ◽  
...  
Keyword(s):  
Information System ◽  
Mississippi River ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
River Basins ◽  
Network Routing ◽  
River Network ◽  
Surface Model ◽  
Muskingum Method

Abstract The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to automatically optimize the Muskingum parameters and to assess river flow computations, hence allowing the diagnosis of runoff computations provided by land surface models. RAPID is applied to the Guadalupe and San Antonio River basins in Texas, where flow wave celerities are estimated at multiple locations using 15-min data and can be reproduced reasonably with RAPID. This river model can be adapted for parallel computing and although the matrix method initially adds a large overhead, river flow results can be obtained faster than with the traditional Muskingum method when using a few processing cores, as demonstrated in a synthetic study using the upper Mississippi River basin.

scholarly journals Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data

2012 ◽  
Vol 5 (4) ◽  
pp. 941-962 ◽  
Author(s):  
B. Ringeval ◽  
B. Decharme ◽  
S. L. Piao ◽  
P. Ciais ◽  
F. Papa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
River Flow ◽  
Spatial Scales ◽  
Remote Sensing Data ◽  
Surface Model ◽  
Global Evaluation ◽  
Good Opportunity ◽  
Sensing Data ◽  
Basin Scale

Abstract. The quality of the global hydrological simulations performed by land surface models (LSMs) strongly depends on processes that occur at unresolved spatial scales. Approaches such as TOPMODEL have been developed, which allow soil moisture redistribution within each grid-cell, based upon sub-grid scale topography. Moreover, the coupling between TOPMODEL and a LSM appears as a potential way to simulate wetland extent dynamic and its sensitivity to climate, a recently identified research problem for biogeochemical modelling, including methane emissions. Global evaluation of the coupling between TOPMODEL and an LSM is difficult, and prior attempts have been indirect, based on the evaluation of the simulated river flow. This study presents a new way to evaluate this coupling, within the ORCHIDEE LSM, using remote sensing data of inundated areas. Because of differences in nature between the satellite derived information – inundation extent – and the variable diagnosed by TOPMODEL/ORCHIDEE – area at maximum soil water content, the evaluation focuses on the spatial distribution of these two quantities as well as on their temporal variation. Despite some difficulties in exactly matching observed localized inundated events, we obtain a rather good agreement in the distribution of these two quantities at a global scale. Floodplains are not accounted for in the model, and this is a major limitation. The difficulty of reproducing the year-to-year variability of the observed inundated area (for instance, the decreasing trend by the end of 90s) is also underlined. Classical indirect evaluation based on comparison between simulated and observed river flow is also performed and underlines difficulties to simulate river flow after coupling with TOPMODEL. The relationship between inundation and river flow at the basin scale in the model is analyzed, using both methods (evaluation against remote sensing data and river flow). Finally, we discuss the potential of the TOPMODEL/LSM coupling to simulate wetland areas. A major limitation of the coupling for this purpose is linked to its ability to simulate a global wetland coverage consistent with the commonly used datasets. However, it seems to be a good opportunity to account for the wetland areas sensitivity to the climate and thus to simulate its temporal variability.

scholarly journals Improving Snow Analyses for Hydrological Forecasting at ECCC Using Satellite-Derived Data

2021 ◽  
Vol 13 (24) ◽  
pp. 5022
Author(s):  
Camille Garnaud ◽  
Vincent Vionnet ◽  
Étienne Gaborit ◽  
Vincent Fortin ◽  
Bernard Bilodeau ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Water Conservation ◽  
Land Surface ◽  
River Flow ◽  
Flow Analysis ◽  
Land Surface Model ◽  
Surface Model ◽  
Streamflow Forecasting ◽  
Snow Cover Extent ◽  
Hydrological Services

As part of the National Hydrological Services Transformation Initiative, Environment and Climate Change Canada (ECCC) designed and implemented the National Surface and River Prediction System (NSRPS) in order to provide surface and river flow analysis and forecast products across Canada. Within NSRPS, the Canadian Land Data Assimilation System (CaLDAS) produces snow analyses that are used to initialise the land surface model, which in turn is used to force the river routing component. Originally, CaLDAS was designed to improve atmospheric forecasts with less focus on hydrological processes. When snow data assimilation occurs, the related increments remove/add water from/to the system, which can sometimes be problematic for streamflow forecasting, in particular during the snowmelt period. In this study, a new snow analysis method introduces multiple innovations that respond to the need for higher quality snow analyses for hydrological purposes, including the use of IMS snow cover extent data instead of in situ snow depth observations. The results show that the new snow assimilation methodology brings an overall improvement to snow analyses and substantially enhances water conservation, which is reflected in the generally improved streamflow simulations. This work represents a first step towards a new snow data assimilation process in CaLDAS, with the final objective of producing a reliable snow analysis to initialise and improve NWP as well as environmental predictions, including flood and drought forecasts.

scholarly journals Development and evaluation of 0.05° terrestrial water storage estimates using CABLE land surface model and GRACE data assimilation

2021 ◽  
Author(s):  
Natthachet Tangdamrongsub ◽  
Michael F. Jasinski ◽  
Peter Shellito
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Land Surface ◽  
Water Storage ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Terrestrial Water Storage ◽  
Grace Data ◽  
Terrestrial Water

Abstract. Accurate estimation of terrestrial water storage (TWS) at a meaningful spatiotemporal resolution is important for reliable assessments of regional water resources and climate variability. Individual components of TWS include soil moisture, snow, groundwater, and canopy storage and can be estimated from the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. The spatial resolution of CABLE is currently limited to 0.5° by the resolution of soil and vegetation datasets that underlie model parameterizations, posing a challenge to using CABLE for hydrological applications at a local scale. This study aims to improve the spatial detail (from 0.5° to 0.05°) and timespan (1981–2012) of CABLE TWS estimates using rederived model parameters and high-resolution meteorological forcing. In addition, TWS observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are assimilated into CABLE to improve TWS accuracy. The success of the approach is demonstrated in Australia, where multiple ground observation networks are available for validation. The evaluation process is conducted using four different case studies that employ different model spatial resolutions and include or omit GRACE data assimilation (DA). We find that the CABLE 0.05° developed here improves TWS estimates in terms of accuracy, spatial resolution, and long-term water resource assessment reliability. The inclusion of GRACE DA increases the accuracy of groundwater storage (GWS) estimates and has little impact on surface soil moisture or evapotranspiration. The use of improved model parameters and improved state estimations (via GRACE DA) together is recommended to achieve the best GWS accuracy. The workflow elaborated in this paper relies only on publicly accessible global datasets, allowing reproduction of the 0.05° TWS estimates in any study region.

scholarly journals Assimilating satellite-based soil moisture observations in a land surface model: The effect of spatial resolution

2021 ◽  
Vol 13 ◽  
pp. 100105
Author(s):  
Tasnuva Rouf ◽  
Manuela Girotto ◽  
Paul Houser ◽  
Viviana Maggioni
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model

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.

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