DownscaleConcept 2.3 User Manual. Downscaled, Spatially Distributed Soil Moisture Calculator

2011 ◽  
Author(s):  
M. L. Coleman ◽  
A. Q. Dozier ◽  
C. M. Fields ◽  
J. D. Niemann
Keyword(s):  
Soil Moisture ◽  
Spatially Distributed

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 Evaluation of Soil Water Index of distributed Tank Model in a small basin with field data

2020 ◽  
Author(s):  
Sofia Melo Vasconcellos ◽  
Masato Kobiyama ◽  
Aline de Almeida Mota
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Retention Curve ◽  
Topographic Wetness Index ◽  
Tank Model ◽  
Water Index ◽  
Soil Water Tension ◽  
Spatially Distributed ◽  
Reliable Performance ◽  
Water Tension

Abstract. The objective of the present study was to determine the spatial behaviour of the Soil Water Index (SWI) by applying a distributed version of the Tank Model (D-Tank Model) to the Araponga river basin (5.26 ha) in southern Brazil and to verify its reliability through the comparison to soil moisture estimated with the measured water-tension values and the water retention curve. The study area has a monitoring system for rainfall, discharge (5-min interval), and soil-water tension (10-min interval). The simulation results showed that the D-Tank Model has a reliable performance. The correlation between SWI and HAND was reasonable (r = 0.6) meanwhile that between SWI and the Topographic Wetness Index was high (r = 0.88). The comparison between the spatially distributed values of the SWI and soil moisture confirmed the high potential of the SWI derived from the D-Tank Model to be applied for predictions related to hydrological and environmental sciences.

scholarly journals Validation of SMAP L2 passive-only soil moisture products using <i>in situ</i> measurements collected in Twente, The Netherlands

2019 ◽  
Author(s):  
Rogier van der Velde ◽  
Andreas Colliander ◽  
Michiel Pezij ◽  
Harm-Jan F. Benninga ◽  
Rajat Bindlish ◽  
...  
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Mean Squared Error ◽  
Single Channel ◽  
Soil Depth ◽  
Soil Freezing ◽  
Horizontal Polarization ◽  
Dual Channel ◽  
Spatially Distributed

Abstract. The Twente region in the east of the Netherlands has a network with twenty soil monitoring stations that has been utilized for validation of the Soil Moisture Active/Passive (SMAP) passive-only soil moisture products. Over the period from April 2015 until December 2018, seven stations covered by the SMAP reference pixels have fairly complete data records. Spatially distributed soil moisture simulations with the Dutch national hydrological model have been utilized for the development of upscaling functions to translate the spatial mean of point measurements to the domain of the SMAP reference pixels. The native and upscaled spatial soil moisture means have been adopted as in situ references to assess the performance of the SMAP i) Single Channel Algorithm at Horizontal Polarization (SCA-H), ii) Single Channel Algorithm at Vertical Polarization (SCA-V), and iii) Dual Channel Algorithm (DCA) soil moisture estimates. In the case of the Twente network it was found that the SCA-V soil moisture retrieved SMAP observations collected in the afternoon had the best agreement with the in situ references leading to an unbiased Root Mean Squared Error (uRMSE) of 0.059 m3 m−3. This is larger than the mission target accuracy of 0.04 m3 m−3, which can be attributed to large over- and underestimation errors (> 0.08 m3 m−3) in particular at the end of dry spells and during freezing, respectively. The strong vertical dielectric gradients associated with rapid soil freezing and wetting causes the disparity in soil depth characterized by SMAP and in situ that leads to the large mismatches. Once filtered for frozen conditions and antecedent rainfall the uRMSE improves to 0.043 m3 m−3.

Microwave Observations of Soil Hydrology

1999 ◽  
Author(s):  
T. J. Jackson ◽  
E. T. Engman
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Soil ◽  
Radiant Energy ◽  
Microwave Remote Sensing ◽  
Heat Fluxes ◽  
Soil Parameters ◽  
Soil Hydrology ◽  
Surface Soil Moisture ◽  
Spatially Distributed

The upper few centimeters of the soil are extremely important because they are the interface between soil science and land-atmosphere research and are also the region of the greatest amount of organic material and biological activity (Wei, 1995). Passive microwave remote sensing can provide a measurement of the surface soil moisture for a range of cover conditions within reasonable error bounds (Jackson and Schmugge, 1989). Since spatially distributed and multitemporal observations of surface soil moisture are rare, the use of these data in hydrology and other disciplines has not been fully explored or developed. The ability to observe soil moisture frequently over large regions could significantly improve our ability to predict runoff and to partition incoming radiant energy into latent and sensible heat fluxes at a variety of scales up to those used in global circulation models. Temporal observation of surface soil moisture may also provide the information needed to determine key soil parameters, such as saturated conductivity (Ahuja et al., 1993). These sensors provide a spatially integrated measurement that may aid in understanding the upscaling of essential soil parameters from point observations. Some specific issues in soil hydrology that could be addressed with remotely sensed observations as described above include (Wei, 1995): (1) criteria for soil mapping based on spatial and temporal variance structures of state variables, (2) identifying scales of observation, (3) determining soil physical properties within profiles based on surface observations, (4) quantifying correlation lengths of soil moisture in time and space relative to precipitation and evaporation, (5) examining the covariance structure between soil water properties and those associated with water and heat fluxes at the land-atmosphere boundary at various scales, and (6) determining if vertical and horizontal fluxes of energy and matter below the surface can be ascertained from surface soil moisture distributions. In this chapter, the basis of microwave remote sensing of soil moisture will be presented along with the advantages and disadvantages of different techniques. Currently available sensor systems will be described.

scholarly journals Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

2013 ◽  
Vol 14 (6) ◽  
pp. 1773-1790 ◽  
Author(s):  
Rene Orth ◽  
Randal D. Koster ◽  
Sonia I. Seneviratne
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Weather Forecasting ◽  
Water Balance Model ◽  
Balance Model ◽  
Catchment Scale ◽  
Spatially Distributed ◽  
Optimized Model ◽  
Streamflow Data

Abstract Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. The authors investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Their approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

scholarly journals Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
L. Pasolli ◽  
C. Notarnicola ◽  
L. Bruzzone ◽  
G. Bertoldi ◽  
S. Della Chiesa ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Support Vector ◽  
Distributed Data ◽  
Remotely Sensed Data ◽  
Ancillary Data ◽  
Sar Images ◽  
Biophysical Parameter ◽  
Spatially Distributed ◽  
Microwave Signals ◽  
The Alps

Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data.

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

2013 ◽  
Vol 10 (1) ◽  
pp. 1333-1373 ◽  
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.

From the field-scale Aquacrop model to a regional gridded crop model: initial evaluation over Europe

2020 ◽  
Author(s):  
Shannon de Roos ◽  
Gabriëlle de Lannoy ◽  
Dirk Raes
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Cropping Systems ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Crop Model ◽  
Crop Models ◽  
Soil Database ◽  
Aquacrop Model ◽  
Spatially Distributed

&lt;p&gt;The pressure on soil and water resources to support the demand for crop production calls for effective water management at the regional scale and a need for regional crop models.&lt;/p&gt;&lt;p&gt;In our study, the field-based Aquacrop v.6.1 is modified to a gridded crop model that is run spatially over the main part of Europe at 1-km resolution.&lt;/p&gt;&lt;p&gt;The gridded model simulates spatially distributed soil moisture, crop biomass and yield, given spatial input of meteorological forcings extracted from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and 1-km soil texture information from the Harmonized World Soil Database v1.2 (HWSD v1.2). For the first model evaluation, a hypothetical and uniform crop is implemented, and field management and irrigation practices are not included. We will present preliminary results over Europe by comparing the spatial soil moisture and biomass simulations with remote sensing data.&lt;/p&gt;&lt;p&gt;This work is part of the SHui project, a H2020 project that aims at improving stakeholder decision-making for water scarcity management in European and Chinese cropping systems.&lt;/p&gt;

scholarly journals Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

2012 ◽  
Vol 16 (2) ◽  
pp. 357-373 ◽  
Author(s):  
M. Liu ◽  
A. Bárdossy ◽  
J. Li ◽  
Y. Jiang
Keyword(s):  
Soil Moisture ◽  
Model Development ◽  
Topographic Effects ◽  
Runoff Generation ◽  
Humid Region ◽  
Swap Model ◽  
Physically Based ◽  
Spatially Distributed ◽  
Significant Spatial Variation ◽  
Limited Process

Abstract. In this paper, simulations with the Soil Water Atmosphere Plant (SWAP) model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET), and soil moisture content (SMC) caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

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