Relative Importance of Input Parameters in the Modeling of Soil Moisture Dynamics of Small Urban Areas

2012 ◽  
Vol 17 (3) ◽  
pp. 359-367
Author(s):  
Shazia Nishat ◽  
Yiping Guo ◽  
Brian W. Baetz
Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan

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.


2009 ◽  
Vol 17 (2) ◽  
pp. 256-260 ◽  
Author(s):  
Feng WANG ◽  
Shu-Qi WANG ◽  
Xiao-Zeng HAN ◽  
Feng-Xian WANG ◽  
Ke-Qiang ZHANG

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

2018 ◽  
Vol 22 (6) ◽  
pp. 3229-3243 ◽  
Author(s):  
Maoya Bassiouni ◽  
Chad W. Higgins ◽  
Christopher J. Still ◽  
Stephen P. Good

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.


2015 ◽  
Vol 19 (6) ◽  
pp. 2617-2635 ◽  
Author(s):  
M. Sprenger ◽  
T. H. M. Volkmann ◽  
T. Blume ◽  
M. Weiler

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.


2021 ◽  
Author(s):  
Lin Li ◽  
Hu Liu ◽  
Yang Yu ◽  
Wenzhi Zhao

&lt;p&gt;&lt;strong&gt;Abstract: &lt;/strong&gt;Wetlands remaining in the arid inland river landscapes of northwestern China suffer degradation and their resilience and ability to continue functioning under hydrologic and land use changes resulting from climate change may be significantly inhibited. Information on the desert-oasis wetlands, however, is sparse and knowledge of how ecological functioning and resilience may change under climate change and water-resource management is still lacking. Research in oasis wetland areas of the Northwestern China identified linkages between subsurface flow, plant transpiration, and water levels. In this study, we present an ecohydrological analysis of the energy and water balance in the wetland ecosystem. A process-based stochastic soil moisture model developed for groundwater-dependent ecosystems was employed to modelling the interactions between rainfall, water table fluctuations, soil moisture dynamics, and vegetation, and to investigate the ecohydrology of arid inland wetlands system. Field measured groundwater levels, vertical soil moisture profiles, soil water potentials, and root biomass allocation and transpiration of pioneer species in the wetlands were used to calibrate and validate the stochastic model. The parameterized model was then running to simulate the probability distributions of soil moisture and root water uptake, and quantitative descript the vegetation&amp;#8211;water table&amp;#8211;soil moisture interplay in the hypothesized scenarios of future. Our analysis suggested the increasing rates of water extraction and regulation of hydrologic processes, coupled with destruction of natural vegetation, and climate change, are jeopardizing the future persistence of wetlands and the ecological and socio-economic functions they support. To understand how climate change will impact on the ecohydrological functioning of wetlands, both hydrological and land use changes need to be considered in future works.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Wetland ecosystem, groundwater, soil moisture dynamics, water balances, Heihe River Basin&lt;/p&gt;


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