Modeling Vadose Zone Moisture Dynamics with the Integrated Hydrologic Model (IHM)

2007 ◽  
Author(s):  
Jing Zhang ◽  
Jeffrey Geurink ◽  
Mark A. Ross
Keyword(s):  
Vadose Zone ◽  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
Moisture Dynamics

scholarly journals Gravitational and capillary soil moisture dynamics for distributed hydrologic models

2015 ◽  
Vol 19 (4) ◽  
pp. 1857-1869 ◽  
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.

scholarly journals Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model

2020 ◽  
Vol 580 ◽  
pp. 124358 ◽  
Author(s):  
Fadji Z. Maina ◽  
Erica R. Siirila-Woodburn ◽  
Michelle Newcomer ◽  
Zexuan Xu ◽  
Carl Steefel
Keyword(s):  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

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

2006 ◽  
Vol 10 (3) ◽  
pp. 353-368 ◽  
Author(s):  
J. Parajka ◽  
V. Naeimi ◽  
G. Blöschl ◽  
W. Wagner ◽  
R. Merz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Regional Scale ◽  
Hydrologic Model ◽  
Hydrologic Models ◽  
Ungauged Catchments ◽  
Soil Moisture Dynamics ◽  
Model Efficiency ◽  
The Relationship ◽  
Runoff Model ◽  
Moisture Dynamics

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.

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

2013 ◽  
Vol 17 (9) ◽  
pp. 3371-3387 ◽  
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.

scholarly journals Assessing the impact of model spin-up on surface water-groundwater interactions using an integrated hydrologic model

2014 ◽  
Vol 50 (3) ◽  
pp. 2636-2656 ◽  
Author(s):  
Hoori Ajami ◽  
Matthew F. McCabe ◽  
Jason P. Evans ◽  
Simon Stisen
Keyword(s):  
Surface Water ◽  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

scholarly journals Assessment of the Timing of Daily Peak Streamflow during the Melt Season in a Snow-Dominated Watershed

2016 ◽  
Vol 17 (8) ◽  
pp. 2225-2244 ◽  
Author(s):  
Xing Chen ◽  
Mukesh Kumar ◽  
Rui Wang ◽  
Adam Winstral ◽  
Danny Marks
Keyword(s):  
Water Flux ◽  
Subsurface Flow ◽  
Hydrologic Model ◽  
Daily Streamflow ◽  
Penn State ◽  
Integrated Hydrologic Model ◽  
Interseasonal Variability ◽  
Peak Streamflow ◽  
Surface And Subsurface Flow ◽  
Temporal Shifts

Abstract Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic Model (PIHM). The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season and between wet and dry years. The results could be used for supporting DPTs prediction efforts and for prioritization of observables for DPT determination.

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