Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

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Gravitational and capillary soil moisture dynamics for distributed hydrologic models

Hydrology and Earth System Sciences ◽

10.5194/hess-19-1857-2015 ◽

2015 ◽

Vol 19 (4) ◽

pp. 1857-1869 ◽

Cited By ~ 9

Author(s):

A. Castillo ◽

F. Castelli ◽

D. Entekhabi

Keyword(s):

Soil Moisture ◽

Unsaturated Soils ◽

Soil Layer ◽

Hydrologic Model ◽

Local Scale ◽

Distributed Model ◽

Limiting Factor ◽

Soil Physics ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

Abstract. Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101–103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10−3–10−1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-pixel version of a distributed catchment hydrologic model and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

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Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

Hydrology and Earth System Sciences ◽

10.5194/hess-17-3371-2013 ◽

2013 ◽

Vol 17 (9) ◽

pp. 3371-3387 ◽

Cited By ~ 40

Author(s):

C. Lepore ◽

E. Arnone ◽

L. V. Noto ◽

G. Sivandran ◽

R. L. Bras

Keyword(s):

Soil Moisture ◽

Soil Column ◽

Hydrologic Model ◽

Richards Equation ◽

Landslide Risk ◽

Modeling Framework ◽

Soil Moisture Dynamics ◽

Physically Based ◽

Spatially Distributed ◽

Moisture Dynamics

Abstract. This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

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Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo Forest, Puerto Rico

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-1333-2013 ◽

2013 ◽

Vol 10 (1) ◽

pp. 1333-1373 ◽

Cited By ~ 1

Author(s):

C. Lepore ◽

E. Arnone ◽

L. V. Noto ◽

G. Sivandran ◽

R. L. Bras

Keyword(s):

Soil Moisture ◽

Soil Column ◽

Hydrologic Model ◽

Richards Equation ◽

Landslide Risk ◽

Modeling Framework ◽

Soil Moisture Dynamics ◽

Physically Based ◽

Spatially Distributed ◽

Moisture Dynamics

Abstract. This paper presents the development of a rainfall-triggered landslide module within a physically based spatially distributed ecohydrologic model. The model, Triangulated Irregular Networks Real-time Integrated Basin Simulator and VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics is resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the Luquillo Forest (the study area). The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards equation to better represent the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the Factor of Safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the Infinite Slope model creating a powerful tool for the assessment of landslide risk.

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Gravitational and capillary soil moisture dynamics for hillslope-resolving models

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-7133-2014 ◽

2014 ◽

Vol 11 (6) ◽

pp. 7133-7168 ◽

Cited By ~ 1

Author(s):

A. Castillo ◽

F. Castelli ◽

D. Entekhabi

Keyword(s):

Soil Moisture ◽

Unsaturated Soils ◽

Soil Layer ◽

Hydrologic Model ◽

Local Scale ◽

Distributed Model ◽

Limiting Factor ◽

Soil Physics ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

Abstract. Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into plan computational elements at resolutions of 101–103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local scale processes are modeled using one-dimensional soil columns that are discretized into layers that are usually 10−3–10−1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-D version of a distributed catchment hydrologic model; and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure, and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

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Stochastic rainfall-runoff model with explicit soil moisture dynamics

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2015.0389 ◽

2015 ◽

Vol 471 (2183) ◽

pp. 20150389 ◽

Cited By ~ 11

Author(s):

M. S. Bartlett ◽

E. Daly ◽

J. J. McDonnell ◽

A. J. Parolari ◽

A. Porporato

Keyword(s):

Soil Moisture ◽

Joint Probability ◽

Rainfall Runoff ◽

Soil Moisture Dynamics ◽

Rainfall Occurrence ◽

State Dependent ◽

Rainfall Runoff Model ◽

Runoff Model ◽

Soil Moisture Status ◽

Moisture Dynamics

Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.

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