Impact of Soil Moisture on Regional Spectral Model Simulations for South America

Abstract. By providing continuous high-resolution simulations of soil moisture fields, distributed hydrologic models could be powerful tools to advance the scientific community's understanding of the space-time variability and scaling characteristics of soil moisture fields. However, in order to use the soil moisture simulations from hydrologic models with confidence, it is important to understand whether the models are able to represent in a reliable way the processes regulating soil moisture variability. In this study, a comparison of the scaling characteristics of spatial soil moisture fields derived from a set of microwave radiometer observations from the Southern Great Plains 1997 experiment and corresponding simulations using the distributed hydrologic model GEOtop is performed through the use of generalized variograms. Microwave observations and model simulations are in agreement with respect to suggesting the existence of a scale-invariance property in the variograms of spatial soil moisture fields, and indicating that the scaling characteristics vary with changes in the spatial average soil water content. However, observations and simulations give contradictory results regarding the relationship between the scaling parameters (i.e. spatial organization) and average soil water content. The drying process increased the spatial correlation of the microwave observations at both short and long separation distances while increasing the rate of decay of correlation with distance. The effect of drying on the spatial correlation of the model simulations was more complex, depending on the storm and the simulation examined, but for the largest storm in the simulation most similar to the observations, drying increased the long-range correlation but decreased the short-range. This is an indication that model simulations, while reproducing correctly the total streamflow at the outlet of the watershed, may not accurately reproduce the runoff production mechanisms. Consideration of the scaling characteristics of spatial soil moisture fields can therefore serve as a more intensive means for validating distributed hydrologic models, compared to the traditional approach of only comparing the streamflow hydrographs.

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IPCC global coupled model simulations of the South America monsoon system

Climate Dynamics ◽

10.1007/s00382-008-0488-1 ◽

2008 ◽

Vol 33 (7-8) ◽

pp. 893-916 ◽

Cited By ~ 51

Author(s):

Rodrigo J. Bombardi ◽

Leila M. V. Carvalho

Keyword(s):

South America ◽

Coupled Model ◽

The South ◽

Model Simulations ◽

Monsoon System ◽

Global Coupled Model

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High-resolution pan-European multi-model simulations of hydrologic states and fluxes

10.5194/egusphere-egu2020-10652 ◽

2020 ◽

Author(s):

Bibi S Naz ◽

Wendy Sharples ◽

Klaus Goergen ◽

Stefan Kollet

Keyword(s):

Soil Moisture ◽

High Resolution ◽

Groundwater Flow ◽

Hydrologic Model ◽

Hydrological Processes ◽

Model Parameters ◽

Time Step ◽

European Continent ◽

Model Simulations ◽

Community Land Model

High-resolution large-scale predictions of hydrologic states and fluxes are important for many regional-scale applications and water resource management. However, because of uncertainties related to forcing data, model structural errors arising from simplified representations of hydrological processes or uncertain model parameters, model simulations remain uncertain. To quantify this uncertainty, multi-model simulations were performed at 3km resolution over the European continent using the Community Land Model (CLM3.5) and the ParFlow hydrologic model. While Parflow uses a similar approach as CLM in simulating the snow, vegetation and land-atmosphere exchange processes, it simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a two-dimensional kinematic wave approximation. The CLM3.5 uses a simple groundwater model to account for groundwater recharge and discharge processes. Both models were driven with the COSMO-REA6 reanalysis dataset at 6km resolution for the time period from 2000 to 2006 at an hourly time step, and both used the same datasets for the static input variables (such as topography, vegetation and soil properties). The performance of both models was analyzed through comparisons with independent observations including satellite-derived and in-situ soil moisture, evapotranspiration, river discharge, water table depth and total water storage datasets. Overall, both models capture the interannual variability in the hydrologic states and fluxes well, however differences in performance between models showed the uncertainty associated with the representation of hydrological processes, such as groundwater flow and soil moisture and its control on latent and sensible heat fluxes at the surface.

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Simulation of streamflow in two Mediterranean catchments using a process-based model and remote sensing products

10.5194/egusphere-egu2020-10378 ◽

2020 ◽

Author(s):

Tiago Ramos ◽

Lucian Simionesei ◽

Marta Basso ◽

Vivien Stefan ◽

Ana Oliveira ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Catchment Area ◽

Vegetation Index ◽

Crop Growth ◽

Assessment Tools ◽

Landsat 8 ◽

Network Computing ◽

Area Index ◽

Model Simulations

Watershed modelling is one of the most important assessment tools in watershed planning and management. Nonetheless, the classic calibration of watershed models, in which a few discharge gauges near the outlet of a catchment are used to compare measured and simulated streamflow, is often criticized by not assuring that relevant processes such as evapotranspiration, soil moisture, crop growth, and groundwater recharge are well represented in the catchment area. This study aimed to simulate streamflow in two Mediterranean catchments, Orba (778km2) in Italy and Segre (1286km2) in Spain, using the physically-based, fully distributed MOHID-Land model. Model calibration/validation of streamflow was first performed following a classical approach. Different products derived from remote sensing platforms were then used to evaluate the adequacy of model simulations of crop growth and soil moisture in the catchment area.The MOHID-Land model considers four compartments or mediums (atmosphere, porous media, soil surface and river network), computing water dynamics through the different mediums using mass and momentum conservation equations. The model was implemented in the two simulated catchments with a resolution of 1 km. Data inputs included the Digital Elevation Model over Europe (EU-DEM) with a resolution of 30 m; the soil hydraulic properties map from EU-SoilHydroGrids ver1.0 with a resolution of 250 m; the CORINE land cover map from 2012 with a resolution of 100 m; the hourly weather data (precipitation, wind velocity, relative air humidity, solar radiation and surface air temperature) from local weather stations; and the reservoir discharge data from governmental and/or regional agencies. Simulations were run from 2006-2014 for Orba and from 2008-2018 for Segre, and included a model warm-up, a calibration, and a validation period. Comparison between simulated and measured flows were performed in 2 and 10 hydrometric stations located in the Orba and Segre catchments, respectively. Four statistical parameters (R2, RMSE, PBIAS and NSE) were used to evaluate model performance, confirming the good fitting of model simulations to measured data.Model simulations of leaf area index (LAI) were then compared with LAI maps at 30 m resolution derived from ATCOR and Landsat 8 imagery data using the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). Furthermore, model simulation of soil moisture were also compared at the surface depth (0-5 cm) with soil moisture maps at 1 km resolution created with the DISaggregation based on a Physical And Theoretical scale CHange (DISPATCH) algorithm for the downscaling of the 40 km SMOS (Soil Moisture and Ocean Salinity) soil moisture data using land surface temperature (LST) and NDVI data. Results showed the fundamental differences between the MOHID-Land and remote sensing outputs, with major differences being analyzed by soil units and land use classes.

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Connection between Spring Conditions and Peak Summer Monsoon Rainfall in South America: Role of Soil Moisture, Surface Temperature, and Topography in Eastern Brazil

Journal of Climate ◽

10.1175/2007jcli1684.1 ◽

2007 ◽

Vol 20 (24) ◽

pp. 5929-5945 ◽

Cited By ~ 84

Author(s):

Alice M. Grimm ◽

Jeremy S. Pal ◽

Filippo Giorgi

Keyword(s):

Soil Moisture ◽

South America ◽

Surface Temperature ◽

Summer Monsoon ◽

Monsoon Rainfall ◽

Summer Monsoon Rainfall ◽

Spring Precipitation ◽

Southeast Brazil ◽

Peak Summer

Abstract A link between peak summer monsoon rainfall in central-east Brazil, composing part of the South American monsoon core region, and antecedent conditions in spring is disclosed. Rainfall in this region during part of spring holds a significant inverse correlation with rainfall in peak summer, especially during ENSO years. A surface–atmosphere feedback hypothesis is proposed to explain this relationship: low spring precipitation leads to low spring soil moisture and high late spring surface temperature; this induces a topographically enhanced low-level anomalous convergence and cyclonic circulation over southeast Brazil that enhances the moisture flux from northern and central South America into central-east Brazil, setting up favorable conditions for excess rainfall. Antecedent wet conditions in spring lead to opposite anomalies. The main links in this hypothesis are confirmed through correlation analysis of observed data: spring precipitation is negatively correlated to late spring surface temperature in central-east Brazil, and surface temperature in southeast Brazil is positively correlated with peak summer monsoon precipitation in central-east Brazil. The intermediary links of the surface–atmosphere feedback are tested in sensitivity experiments with the regional climate model version 3 (RegCM3). These experiments confirm that the proposed links are possible: the reduced soil moisture in central-east Brazil is shown to increase the surface temperature and produce a cyclonic anomaly over southeast Brazil, as well as increased precipitation in central-east Brazil. A crucial role of the mountains of southeast Brazil in anchoring the patterns of intraseasonal variability, and sustaining the “dipolelike” precipitation mode observed over South America, is suggested. The low predictability of monsoon rainfall anomalies in central-east Brazil during the austral summer might be partially ascribed to the fact that the models do not well reproduce the topographical features and the land–atmosphere interactions that are important for the variability in that region.

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