scholarly journals What is Missing from the Prescription of Hydrology for Land Surface Schemes?

2016 ◽  
Vol 17 (7) ◽  
pp. 2013-2039 ◽  
Author(s):  
Bruce Davison ◽  
Alain Pietroniro ◽  
Vincent Fortin ◽  
Robert Leconte ◽  
Moges Mamo ◽  
...  
Keyword(s):  
Land Surface ◽  
River Flow ◽  
Surface Heterogeneity ◽  
Heat Fluxes ◽  
Hydrologic Models ◽  
Land Surface Water ◽  
Weather And Climate ◽  
Central Canada ◽  
Parameter Values

Abstract Land surface schemes (LSSs) are of potential interest both to hydrologists looking for innovative ways to simulate river flow and the land surface water balance and to atmospheric scientists looking to improve weather and climate predictions. This paper discusses three ideas, which are grounded in hydrological science, to improve LSS predictions of streamflow and latent heat fluxes. These three possibilities are 1) improved representation of lateral flow processes, 2) the appropriate representation of surface heterogeneity, and 3) calibration to streamflow as a way to account for parameter uncertainty. The current understanding of lateral hydrological processes is described along with their representation of a selected group of LSSs. Issues around spatial heterogeneity are discussed, and calibration in hydrologic models and LSSs is examined. A case study of an evapotranspiration-dominated basin with over 10 years of extensive observations in central Canada is presented. The results indicate that in this particular basin, calibration of streamflow presents atmospheric modelers with a unique opportunity to improve upon the current practice of using lookup tables to define parameter values. More studies are needed to determine if model calibration to streamflow is an appropriate method for generally improving LSS-modeled heat fluxes around the globe.

Irrigation in JULES Land-Only Simulations over South and East Asia

2021 ◽  
Author(s):  
Markus Todt ◽  
Pier Luigi Vidale ◽  
Patrick C. McGuire ◽  
Omar V. Müller
Keyword(s):  
Soil Moisture ◽  
East Asia ◽  
Land Surface ◽  
River Flow ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Irrigated Agriculture ◽  
Irrigation Season ◽  
Irrigation Scheme ◽  
The Impact

<p>Capturing soil moisture-atmosphere feedbacks in a weather or climate model requires realistic simulation of various land surface processes. However, irrigation and other water management methods are still missing in most global climate models today, despite irrigated agriculture being the dominant land use in parts of Asia. In this study, we test the irrigation scheme available in the land model JULES (Joint UK Land Environment Simulator) by running land-only simulations over South and East Asia driven by WFDEI (WATCH Forcing Data ERA-Interim) forcing data. Irrigation in JULES is applied on a daily basis by replenishing soil moisture in the upper soil layers to field capacity, and we use a version of the irrigation scheme that extracts water for irrigation from groundwater and rivers, which physically limits the amount of irrigation that can be applied. We prescribe irrigation for C3 grasses in order to simulate the effects of agriculture, albeit retaining the simpler, widely used 5-PFT (plant functional type) configuration in JULES. Irrigation generally increases soil moisture and evapotranspiration, which results in increasing latent heat fluxes and decreasing sensible heat fluxes. Comparison with combined observational/machine-learning products for turbulent fluxes shows that while irrigation can reduce biases, other biases in JULES, unrelated to irrigation, are larger than improvements due to the inclusion of irrigation. Irrigation also affects water fluxes within the soil, e.g. runoff and drainage into the groundwater level, as well as soil moisture outside of the irrigation season. We find that the irrigation scheme, at least in the uncoupled land-atmosphere setting, can rapidly deplete groundwater to the point that river flow becomes the main source of irrigation (over the North China Plain and the Indus region) and can have the counterintuitive effect of decreasing annual average soil moisture (over the Ganges plain). Subsequently, we will explore the impact of irrigation on regional climate by conducting coupled land-atmosphere simulations.</p>

scholarly journals Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data

2016 ◽  
Vol 373 ◽  
pp. 167-173
Author(s):  
Fabio Castelli ◽  
Giulia Ercolani
Keyword(s):  
Land Surface ◽  
River Flow ◽  
Central Italy ◽  
Flood Forecasting ◽  
Hydrologic Model ◽  
Flow Data ◽  
Hydrologic Models ◽  
Operational Forecasting ◽  
Abstract Data ◽  
Data Error

Abstract. Data assimilation has the potential to improve flood forecasting. However, it is rarely employed in distributed hydrologic models for operational predictions. In this study, we present variational assimilation of river flow data at multiple locations and of land surface temperature (LST) from satellite in a distributed hydrologic model that is part of the operational forecasting chain for the Arno river, in central Italy. LST is used to estimate initial condition of soil moisture through a coupled surface energy/water balance scheme. We present here several hindcast experiments to assess the performances of the assimilation system. The results show that assimilation can significantly improve flood forecasting, although in the limit of data error and model structure.

scholarly journals Aggregation effects of surface heterogeneity in land surface processes

1999 ◽  
Vol 3 (4) ◽  
pp. 549-563 ◽  
Author(s):  
Z. Su ◽  
H. Pelgrum ◽  
M. Menenti
Keyword(s):  
Land Surface ◽  
Surface Heterogeneity ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Land Surface Processes ◽  
Radiative Fluxes ◽  
Heterogeneous Landscapes ◽  
Observation Scale ◽  
Remote Sensor ◽  
Original Observation

Abstract. In order to investigate the aggregation effects of surface heterogeneity in land surface processes we have adapted a theory of aggregation. Two strategies have been adopted: 1) Aggregation of radiative fluxes. The aggregated radiative fluxes are used to derive input parameters that are then used to calculate the aerodynamic fluxes at different aggregation levels. This is equivalent to observing the same area at different resolutions using a certain remote sensor, and then calculating the aerodynamic fluxes correspondingly. 2) Aggregation of aerodynamic fluxes calculated at the original observation scale to different aggregation levels. A case study has been conducted to identify the effects of aggregation on areal estimates of sensible and latent heat fluxes. The length scales of surface variables in heterogeneous landscapes are estimated by means of wavelet analysis.

Ecosystem modeling of methane and carbon dioxide fluxes for boreal forest sites

2001 ◽  
Vol 31 (2) ◽  
pp. 208-223 ◽  
Author(s):  
Christopher Potter ◽  
Jill Bubier ◽  
Patrick Crill ◽  
Peter Lafleur
Keyword(s):  
Carbon Dioxide ◽  
Boreal Forest ◽  
Land Surface ◽  
Net Primary Production ◽  
Ground Cover ◽  
Methane Flux ◽  
Growing Season ◽  
Ecosystem Model ◽  
Heat Fluxes ◽  
Water Levels

Predicted daily fluxes from an ecosystem model for water, carbon dioxide, and methane were compared with 1994 and 1996 Boreal Ecosystem–Atmosphere Study (BOREAS) field measurements at sites dominated by old black spruce (Picea mariana (Mill.) BSP) (OBS) and boreal fen vegetation near Thompson, Man. Model settings for simulating daily changes in water table depth (WTD) for both sites were designed to match observed water levels, including predictions for two microtopographic positions (hollow and hummock) within the fen study area. Water run-on to the soil profile from neighboring microtopographic units was calibrated on the basis of daily snowmelt and rainfall inputs to reproduce BOREAS site measurements for timing and magnitude of maximum daily WTD for the growing season. Model predictions for daily evapotranspiration rates closely track measured fluxes for stand water loss in patterns consistent with strong controls over latent heat fluxes by soil temperature during nongrowing season months and by variability in relative humidity and air temperature during the growing season. Predicted annual net primary production (NPP) for the OBS site was 158 g C·m–2 during 1994 and 135 g C·m–2 during 1996, with contributions of 75% from overstory canopy production and 25% from ground cover production. Annual NPP for the wetter fen site was 250 g C·m–2 during 1994 and 270 g C·m–2 during 1996. Predicted seasonal patterns for soil CO2 fluxes and net ecosystem production of carbon both match daily average estimates at the two sites. Model results for methane flux, which also closely match average measured flux levels of –0.5 mg CH4·m–2·day–1 for OBS and 2.8 mg CH4·m–2·day–1 for fen sites, suggest that spruce areas are net annual sinks of about –0.12 g CH4·m–2, whereas fen areas generate net annual emissions on the order of 0.3–0.85 g CH4·m–2, depending mainly on seasonal WTD and microtopographic position. Fen hollow areas are predicted to emit almost three times more methane during a given year than fen hummock areas. The validated model is structured for extrapolation to regional simulations of interannual trace gas fluxes over the entire North America boreal forest, with integration of satellite data to characterize properties of the land surface.

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