Upscaling Soil Hydraulic Parameters in the Picacho Mountain Region Using Bayesian Neural Networks

2012 ◽  
Vol 55 (2) ◽  
pp. 463-473 ◽  
Author(s):  
R. B. Jana ◽  
B. P. Mohanty ◽  
Z. Sheng
Keyword(s):  
Neural Networks ◽  
Mountain Region ◽  
Hydraulic Parameters ◽  
Bayesian Neural Networks ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

scholarly journals Evaluation and improvement of the default soil hydraulic parameters for the Noah Land Surface Model

Geoderma ◽  
2017 ◽  
Vol 285 ◽  
pp. 247-259 ◽  
Author(s):  
Andrea Sz. Kishné ◽  
Yohannes Tadesse Yimam ◽  
Cristine L.S. Morgan ◽  
Bright C. Dornblaser
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Hydraulic Parameters ◽  
Soil Hydraulic Parameters ◽  
Noah Land Surface Model ◽  
Soil Hydraulic

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>

scholarly journals Joint Distributions of the Unsaturated Soil Hydraulic Parameters and their Effect on Other Variates

2004 ◽  
Vol 3 (4) ◽  
pp. 1492-1492 ◽  
Author(s):  
G. H. de Rooij ◽  
R. T. A. Kasteel ◽  
A. Papritz ◽  
H. Fluhler
Keyword(s):  
Unsaturated Soil ◽  
Hydraulic Parameters ◽  
Joint Distributions ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

scholarly journals Vegetation of the eastern communal conservancies in Namibia: II. Environmental drivers

Koedoe ◽  
2014 ◽  
Vol 56 (1) ◽  
Author(s):  
Ben J. Strohbach ◽  
Josephat T. Kutuahuripa
Keyword(s):  
Soil Texture ◽  
Fire Regime ◽  
Sandy Soils ◽  
Hydraulic Lift ◽  
Environmental Drivers ◽  
Hydraulic Parameters ◽  
Rainfall Gradient ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic ◽  
Grass Sward

The eastern communal conservancies are situated along the western fringe of the Kalahari basin. Under a very short rainfall gradient, the vegetation abruptly changes from microphyllous Acacia-dominated savannas to mesophyll savannas, dominated by Terminalia sericea and Combretum spp. We hypothesise that this is caused by changes in soil moisture availability brought about by changes in soil texture from loamy soils to deep sands (the ‘inverse texture effect’). For this analysis, we used vegetation and soils data derived from a recognisance survey of the natural resources of the study area. As the sites in the soil and vegetation surveys did not overlap, it was decided to use only synoptic data for the plant associations in the analysis. Non-metric multidimesional scaling ordination was utilised as ordination technique of the vegetation data and various environmental parameters, including soil texture, soil hydraulic parameters, climatic and fire regime parameters, were overlaid as biplots onto the resulting graph, as were various plant functional attributes particularly related to climatic conditions. The main environmental gradient identified within the study area is the rainfall gradient. This relatively short gradient, however, does not explain the marked change in vegetation observed within the study area. This change is attributed to the change in soil type, in particular, the soil texture and the associated soil hydraulic parameters of the soil. This gradient is closely correlated to leaf size, explaining the change from microphyll savannas to mesophyll savannas along the change from loamy to sandy soils. One of the lesser understood mechanisms for the survival of these mesophyll plants on sandy soils seems to be a deep root system, which is actively involved in water redistribution within the soil profile – by hydraulic lift, inverse hydraulic lift and stem flow.Conservation implications: Understanding these mechanisms will greatly assist in understanding savanna dynamics. With the threat of global climate change, we postulate that the vegetation will gradually change from the present mesophyll to a microphyll savanna, but that the grass sward will probably not develop very well. Shrub and tree removal (‘bush harvesting’) is likely to speed up the desertification process within this area.

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