Obtaining soil hydraulic parameters from soil water content data assimilation under different climatic/soil conditions

CATENA ◽  
2018 ◽  
Vol 163 ◽  
pp. 311-320 ◽  
Author(s):  
Javier Valdes-Abellan ◽  
Yakov Pachepsky ◽  
Gonzalo Martinez
Keyword(s):  
Data Assimilation ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Conditions ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

scholarly journals Bayesian inverse modelling of in situ soil water dynamics: using prior information about the soil hydraulic properties

2011 ◽  
Vol 8 (1) ◽  
pp. 2019-2063 ◽  
Author(s):  
B. Scharnagl ◽  
J. A. Vrugt ◽  
H. Vereecken ◽  
M. Herbst
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Vadose Zone ◽  
Hydraulic Properties ◽  
Prior Information ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

Abstract. In situ observations of soil water state variables under natural boundary conditions are often used to estimate field-scale soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to reliably estimate all the soil hydraulic parameters. In this case study, we tested whether prior information about the soil hydraulic properties could help improve the identifiability of the van Genuchten-Mualem (VGM) parameters. Three different prior distributions with increasing complexity were formulated using the ROSETTA pedotransfer function (PTF) with input data that constitutes basic soil information and is readily available in most vadose zone studies. The inverse problem was posed in a formal Bayesian framework and solved using Markov chain Monte Carlo (MCMC) simulation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Synthetic and real-world soil water content data were used to illustrate our approach. The results of this study corroborate and explicate findings previously reported in the literature. Indeed, soil water content data alone contained insufficient information to reasonably constrain all VGM parameters. The identifiability of these soil hydraulic parameters was substantially improved when an informative prior distribution was used with detailed knowledge of the correlation structure among the respective VGM parameters. A biased prior did not distort the results, which inspires confidence in the robustness and effectiveness of the presented method. The Bayesian framework presented in this study can be applied to a wide range of vadose zone studies and provides a blueprint for the use of prior information in inverse modelling of soil hydraulic properties at various spatial scales.

Data Assimilation with Soil Water Content Sensors and Pedotransfer Functions in Soil Water Flow Modeling

2012 ◽  
Vol 76 (3) ◽  
pp. 829-844 ◽  
Author(s):  
Feng Pan ◽  
Yakov Pachepsky ◽  
Diederik Jacques ◽  
Andrey Guber ◽  
Robert L. Hill
Keyword(s):  
Data Assimilation ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Flow ◽  
Pedotransfer Functions ◽  
Flow Modeling ◽  
Soil Water Flow

Exploring hydrological processes at a small agricultural catchment in the Czech Republic

2021 ◽  
Author(s):  
Tailin Li ◽  
Nina Noreika ◽  
Jakub Jeřábek ◽  
Tomáš Dostál ◽  
David Zumr
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Hydrological Processes ◽  
Hydraulic Parameters ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
Mike She ◽  
Stream Discharge ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

<p>A better understanding of hydrological processes in agricultural catchments is not only crucial to hydrologists but also helpful for local farmers. Therefore, we have built the freely-available web-based WALNUD dataset (Water in Agricultural Landscape – NUčice Database) for our experimental catchment Nučice (0.53 km<sup>2</sup>), the Czech Republic. We have included observed precipitation, air temperature, stream discharge, and soil moisture in the dataset. Furthermore, we have applied numerical modelling techniques to investigate the hydrological processes (e.g. soil moisture variability, water balance) at the experimental catchment using the dataset.</p><p>The Nučice catchment, established in 2011, serves for the observation of rainfall-runoff processes, soil erosion and water balance of the cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9 %, and the climate is humid continental (mean annual temperature 7.9 °C, average annual precipitation 630 mm). The catchment consists of three fields covering over 95 % of the area. There is a narrow stream which begins as a subsurface drainage pipe in the uppermost field draining the water at catchment. The typical crops are winter wheat, rapeseed, mustard and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed in the area of the basin, and an H flume to monitor the stream discharge, water turbidity and basic water quality indicators. The soil water content (at point scale) and groundwater level are also recorded. Recently, we have installed two cosmic-ray soil moisture sensors (StyX Neutronica) to estimate large-scale topsoil water content at the catchment.</p><p>Even though the soil management and soil properties in the fields of Nučice seem to be nearly homogeneous, we have observed variability in the topsoil moisture pattern. The method for the explanation of the soil water regime was the combination of the connectivity indices and numerical modelling. The soil moisture profiles from the point-scale sensors were processed in a 1-D physically-based soil water model (HYDRUS-1D) to optimize the soil hydraulic parameters. Further, the soil hydraulic parameters were used as input into a 3D spatially-distributed model, MIKE-SHE. The MIKE-SHE simulation has been mainly calibrated with rainfall-runoff observations. Meanwhile, the spatial patterns of the soil moisture were assessed from the simulation for both dry and wet catchment conditions. From the MIKE-SHE simulation, the optimized soil hydraulic parameters have improved the estimation of soil moisture dynamics and runoff generation. Also, the correlation between the observed and simulated soil moisture spatial patterns showed different behaviors during the dry and wet catchment conditions.</p><p>This study has been supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS20/156/OHK1/3T/11 and the Project SHui which is co-funded by the European Union Project: 773903 and the Chinese MOST.</p>

Effects of Superabsorbent Polymer on Soil Water Content and Sugarcane Germination and Early Growth in Sandy Soil Conditions

Sugar Tech ◽  
2018 ◽  
Vol 21 (3) ◽  
pp. 444-450 ◽  
Author(s):  
Kenta Watanabe ◽  
Samran Saensupo ◽  
Yanischa Na-iam ◽  
Peeraya Klomsa-ard ◽  
Klanarong Sriroth
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Sandy Soil ◽  
Early Growth ◽  
Soil Conditions ◽  
Superabsorbent Polymer

scholarly journals Multimodel assessment of climate change-induced hydrologic impacts for a Mediterranean catchment

2018 ◽  
Vol 22 (7) ◽  
pp. 4125-4143 ◽  
Author(s):  
Enrica Perra ◽  
Monica Piras ◽  
Roberto Deidda ◽  
Claudio Paniconi ◽  
Giuseppe Mascaro ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Climate Models ◽  
Actual Evapotranspiration ◽  
Soil Conditions ◽  
Hydrologic Models ◽  
The Future ◽  
The Mediterranean

Abstract. This work addresses the impact of climate change on the hydrology of a catchment in the Mediterranean, a region that is highly susceptible to variations in rainfall and other components of the water budget. The assessment is based on a comparison of responses obtained from five hydrologic models implemented for the Rio Mannu catchment in southern Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter balance SImulation Model (WASIM) – are all distributed hydrologic models but differ greatly in their representation of terrain features and physical processes and in their numerical complexity. After calibration and validation, the models were forced with bias-corrected, downscaled outputs of four combinations of global and regional climate models in a reference (1971–2000) and future (2041–2070) period under a single emission scenario. Climate forcing variations and the structure of the hydrologic models influence the different components of the catchment response. Three water availability response variables – discharge, soil water content, and actual evapotranspiration – are analyzed. Simulation results from all five hydrologic models show for the future period decreasing mean annual streamflow and soil water content at 1 m depth. Actual evapotranspiration in the future will diminish according to four of the five models due to drier soil conditions. Despite their significant differences, the five hydrologic models responded similarly to the reduced precipitation and increased temperatures predicted by the climate models, and lend strong support to a future scenario of increased water shortages for this region of the Mediterranean basin. The multimodel framework adopted for this study allows estimation of the agreement between the five hydrologic models and between the four climate models. Pairwise comparison of the climate and hydrologic models is shown for the reference and future periods using a recently proposed metric that scales the Pearson correlation coefficient with a factor that accounts for systematic differences between datasets. The results from this analysis reflect the key structural differences between the hydrologic models, such as a representation of both vertical and lateral subsurface flow (CATHY, TOPKAPI, and tRIBS) and a detailed treatment of vegetation processes (SWAT and WASIM).

Root effects on soil water and hydraulic properties

Biologia ◽  
2007 ◽  
Vol 62 (5) ◽  
Author(s):  
Horst Gerke ◽  
Rolf Kuchenbuch
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Content ◽  
Bulk Density ◽  
Soil Water ◽  
Soil Water Content ◽  
Hydraulic Properties ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic ◽  
Root Effects

AbstractPlants can affect soil moisture and the soil hydraulic properties both directly by root water uptake and indirectly by modifying the soil structure. Furthermore, water in plant roots is mostly neglected when studying soil hydraulic properties. In this contribution, we analyze effects of the moisture content inside roots as compared to bulk soil moisture contents and speculate on implications of non-capillary-bound root water for determination of soil moisture and calibration of soil hydraulic properties.In a field crop of maize (Zea mays) of 75 cm row spacing, we sampled the total soil volumes of 0.7 m × 0.4 m and 0.3 m deep plots at the time of tasseling. For each of the 84 soil cubes of 10 cm edge length, root mass and length as well as moisture content and soil bulk density were determined. Roots were separated in 3 size classes for which a mean root porosity of 0.82 was obtained from the relation between root dry mass density and root bulk density using pycnometers. The spatially distributed fractions of root water contents were compared with those of the water in capillary pores of the soil matrix.Water inside roots was mostly below 2–5% of total soil water content; however, locally near the plant rows it was up to 20%. The results suggest that soil moisture in roots should be separately considered. Upon drying, the relation between the soil and root water may change towards water remaining in roots. Relations depend especially on soil water retention properties, growth stages, and root distributions. Gravimetric soil water content measurement could be misleading and TDR probes providing an integrated signal are difficult to interpret. Root effects should be more intensively studied for improved field soil water balance calculations.

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