scholarly journals Emerging methods for noninvasive sensing of soil moisture dynamics from field to catchment scale: a review

2015 ◽  
Vol 2 (6) ◽  
pp. 635-647 ◽  
Author(s):  
Heye R. Bogena ◽  
Johan A. Huisman ◽  
Andreas Güntner ◽  
Christof Hübner ◽  
Jürgen Kusche ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Catchment Scale ◽  
Soil Moisture Dynamics ◽  
Noninvasive Sensing ◽  
Moisture Dynamics

scholarly journals A signature-based approach to quantify soil moisture dynamics under contrasting land-uses

2021 ◽  
Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Urban Areas ◽  
Shallow Groundwater ◽  
Land Uses ◽  
Catchment Scale ◽  
Soil Moisture Dynamics ◽  
Land Use Types ◽  
Event Based ◽  
Moisture Dynamics

Soil moisture signatures provide a promising solution to overcome the difficulty of evaluating soil moisture dynamics in hydrologic models. Soil moisture signatures are metrics that quantify the dynamic aspects of soil moisture timeseries and enable process-based model evaluations. To date, soil moisture signatures have been tested only under limited land-use types. In this study, we explore soil moisture signatures’ ability to discriminate different dynamics among contrasting land-uses. We applied a set of nine soil moisture signatures to datasets from six in-situ soil moisture networks worldwide. The dataset covered a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, urban areas, grazed areas, and cropland areas. Our set of signatures characterized soil moisture dynamics at three temporal scales: event, season, and a complete timeseries. Statistical assessment of extracted signatures showed that (1) event-based signatures can distinguish different dynamics for all the land-uses, (2) season-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, and cropped vs. grazed vs. grassland contrasts), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, shallow vs. deep groundwater, wetland vs. non-wetland, and cropped vs. grazed vs. grassland contrasts). Further, we compared signature-based process interpretations against literature knowledge; event-based and timeseries-based signatures generally matched well with previous process understandings from literature, but season-based signatures did not. This study will be a useful guideline for understanding how catchment-scale soil moisture dynamics in various land-uses can be described using a standardized set of hydrologically relevant metrics.

Soil moisture dynamics of different land-cover types in the blacksoil regions of China

2009 ◽  
Vol 17 (2) ◽  
pp. 256-260 ◽  
Author(s):  
Feng WANG ◽  
Shu-Qi WANG ◽  
Xiao-Zeng HAN ◽  
Feng-Xian WANG ◽  
Ke-Qiang ZHANG
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Soil Moisture Dynamics ◽  
Land Cover Types ◽  
Moisture Dynamics

Soil moisture dynamics with hydro-climatological parameters at different soil depths

2016 ◽  
Vol 75 (2) ◽  
Author(s):  
Muhammad Ajmal ◽  
Muhammad Waseem ◽  
Waqas Ahmad ◽  
Tae-Woong Kim
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics

scholarly journals Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

2018 ◽  
Vol 22 (6) ◽  
pp. 3229-3243 ◽  
Author(s):  
Maoya Bassiouni ◽  
Chad W. Higgins ◽  
Christopher J. Still ◽  
Stephen P. Good
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Dry Season ◽  
Soil Water Balance ◽  
Rainfall Pattern ◽  
Site Specific ◽  
Soil Moisture Dynamics ◽  
Soil Saturation ◽  
Moisture Dynamics

Abstract. Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash–Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

scholarly journals Estimating flow and transport parameters in the unsaturated zone with pore water stable isotopes

2015 ◽  
Vol 19 (6) ◽  
pp. 2617-2635 ◽  
Author(s):  
M. Sprenger ◽  
T. H. M. Volkmann ◽  
T. Blume ◽  
M. Weiler
Keyword(s):  
Soil Moisture ◽  
Stable Isotope ◽  
Solute Transport ◽  
Water Flow ◽  
Pore Water ◽  
Pedotransfer Functions ◽  
Transport Parameters ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics ◽  
Water Isotope

Abstract. Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last 2 decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a) pore water isotope concentrations, (b) a combination of pore water isotope concentrations and soil moisture time series, and (c) a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by solving the Richards equation numerically with the finite-element code of HYDRUS-1D. The transport of deuterium was simulated with the advection-dispersion equation, and a modified version of HYDRUS was used, allowing deuterium loss during evaporation. The Mualem–van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a), using only the pore water isotope content, cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b) and (c), using both the isotope profiles and the soil moisture time series, resulted in good simulation results with regard to the Kling–Gupta efficiency and good parameter identifiability. However, approach (b) has the advantage that it considers the isotope data not only for the solute transport parameters but also for water flow and root water uptake, and thus increases parameter realism. Approaches (b) and (c) both outcompeted simulations run with parameters derived from pedotransfer functions, which did not result in an acceptable representation of the soil moisture dynamics and pore water stable isotope composition. Overall, parameters based on this new approach that includes isotope data lead to similar model performances regarding the water balance and soil moisture dynamics and better parameter identifiability than the conventional inverse model approaches limited to hydrometric fitting targets. If only data from isotope profiles in combination with textural information is available, the results are still satisfactory. This method has the additional advantage that it will not only allow us to estimate water balance and response times but also site-specific time variant transit times or solute breakthrough within the soil profile.

Sign in / Sign up

Export Citation Format

Share Document