scholarly journals Analysis of aggregation and disaggregation effects for grid-based hydrological models and the development of improved precipitation disaggregation procedures for GCMs

1999 ◽  
Vol 3 (1) ◽  
pp. 95-108 ◽  
Author(s):  
H. S. Wheater ◽  
T. J. Jolley ◽  
C. Onof ◽  
N. Mackay ◽  
R. E. Chandler
Keyword(s):  
Soil Moisture ◽  
Time Scale ◽  
Scale Dependence ◽  
Moisture Distribution ◽  
Image Processing Technique ◽  
Simple Extension ◽  
Hydrological Models ◽  
Radar Rainfall ◽  
Spatial Coverage ◽  
Grid Based

Abstract. Appropriate representation of hydrological processes within atmospheric General Circulation Models (GCMs) is important with respect to internal model dynamics (e.g. surface feedback effects on atmospheric fluxes, continental runoff production) and to simulation of terrestrial impacts of climate change. However, at the scale of a GCM grid-square, several methodological problems arise. Spatial disaggregation of grid-square average climatological parameters is required in particular to produce appropriate point intensities from average precipitation. Conversely, aggregation of land surface heterogeneity is necessary for grid-scale or catchment scale application. The performance of grid-based hydrological models is evaluated for two large (104km2) UK catchments. Simple schemes, using sub-grid average of individual land use at 40 km scale and with no calibration, perform well at the annual time-scale and, with the addition of a (calibrated) routing component, at the daily and monthly time-scale. Decoupling of hillslope and channel routing does not necessarily improve performance or identifiability. Scale dependence is investigated through application of distribution functions for rainfall and soil moisture at 100 km scale. The results depend on climate, but show interdependence of the representation of sub-grid rainfall and soil moisture distribution. Rainfall distribution is analysed directly using radar rainfall data from the UK and the Arkansas Red River, USA. Among other properties, the scale dependence of spatial coverage upon radar pixel resolution and GCM grid-scale, as well as the serial correlation of coverages are investigated. This leads to a revised methodology for GCM application, as a simple extension of current procedures. A new location-based approach using an image processing technique is then presented, to allow for the preservation of the spatial memory of the process.

Soil moisture distribution mapping in topsoil and its effect on maize yield

Biologia ◽  
2017 ◽  
Vol 72 (8) ◽  
Author(s):  
Gábor Milics ◽  
Attila J. Kovács ◽  
Attila Pörneczi ◽  
Anikó Nyéki ◽  
Zoltán Varga ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Management Practices ◽  
Soil Moisture Content ◽  
Cost Effective ◽  
Maize Yield ◽  
Moisture Distribution ◽  
Field Soil ◽  
Spatial Coverage ◽  
Distribution Mapping

AbstractSoil moisture content directly influences yield. Mapping within field soil moisture content differences provides information for agricultural management practices.In this study we aimed to find a cost-effective method for mapping within field soil moisture content differences. Spatial coverage of the field sampling or TDR method is still not dense enough for site-specific soil management. Soil moisture content can be calculated by measuring the apparent soil electrical conductivity (Soil moisture map was also compared to yield map showing correlation (

Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Aslanidou ◽  
P. Smiris
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Moisture Distribution ◽  
Taxus Baccata ◽  
Mixed Stands ◽  
Potential Growth ◽  
North East ◽  
Soil Moisture Distribution

This  study deals with the soil moisture distribution and its effect on the  potential growth and    adaptation of the over-story species in north-east Chalkidiki. These  species are: Quercus    dalechampii Ten, Quercus  conferta Kit, Quercus  pubescens Willd, Castanea  sativa Mill, Fagus    moesiaca Maly-Domin and also Taxus baccata L. in mixed stands  with Fagus moesiaca.    Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content  of each sample    was measured in order to determine soil moisture distribution and its  contribution to the growth    of the forest species. The most important results are: i) available water  is influenced by the soil    depth. During the summer, at a soil depth of 10 cm a significant  restriction was observed. ii) the    large duration of the dry period in the deep soil layers has less adverse  effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out    at a soil depth of 40 cm iii) in the beginning of the growing season, the  soil moisture content is    greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew  stands, is 10-15 % in    the Q. pubescens  stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii    stands.

Vegetation controls on soil moisture distribution in the Valles Caldera, New Mexico, during the North American monsoon

Ecohydrology ◽  
2008 ◽  
Vol 1 (3) ◽  
pp. 225-238 ◽  
Author(s):  
Enrique R. Vivoni ◽  
Alex J. Rinehart ◽  
Luis A. Méndez-Barroso ◽  
Carlos A. Aragón ◽  
Gautam Bisht ◽  
...  
Keyword(s):  
Soil Moisture ◽  
New Mexico ◽  
North American ◽  
Moisture Distribution ◽  
North American Monsoon ◽  
Valles Caldera ◽  
The North ◽  
Soil Moisture Distribution

A MOISTURE STRESS INDEX FOR WHEAT BY MEANS OF A MODULATED SOIL MOISTURE BUDGET

1968 ◽  
Vol 48 (5) ◽  
pp. 535-544 ◽  
Author(s):  
A. R. Mack ◽  
W. S. Ferguson
Keyword(s):  
Soil Moisture ◽  
Stress Function ◽  
Potential Evapotranspiration ◽  
Moisture Stress ◽  
Moisture Distribution ◽  
Stress Index ◽  
Wheat Crop ◽  
Moisture Budget ◽  
Dough Stage ◽  
Soil Moisture Budget

Actual evapotranspiration (AE), soil moisture distribution, and moisture stress for a wheat crop (PE-AE) were estimated by the modulated soil moisture budget of Holmes and Robertson. The estimated soil moisture was reasonably well correlated with soil moisture measured weekly by means of gypsum blocks. Wheat yields from experimental plots in the corresponding area were related more closely to the moisture stress function (PE-AE: r = − 0.83), than to the seasonal precipitation (r = 0.62), the potential evapotranspiration (PE) or the evapotranspiration ratio (AE/PE). Regression analyses showed that the grain yields were reduced by an average of 156 (±sb = 40) kg/ha per cm of moisture stress from emergence to harvest, or by 311 and 69 kg/ha per cm of stress, from the fifth-leaf to the soft-dough stage and from the soft-dough stage to maturity, respectively. The moisture stress function may be used to characterize the soil–plant–atmosphere environment for the growing season of a crop. Precipitation and evapotranspiration data are presented annually for three standardized growing periods at Brandon from 1921 to 1963.

scholarly journals The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models

2018 ◽  
Vol 22 (9) ◽  
pp. 4649-4665 ◽  
Author(s):  
Anouk I. Gevaert ◽  
Ted I. E. Veldkamp ◽  
Philip J. Ward
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Propagation Time ◽  
Hydrological Models ◽  
Land Surface Models ◽  
Surface Models

Abstract. Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socioeconomic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices (SIs) of soil moisture, runoff, and streamflow from an ensemble of global hydrological models (GHMs) forced by a consistent meteorological dataset. Drought propagation is strongly related to climate types, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models (LSMs) than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 127 in situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 10 % of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.

scholarly journals Modified Richards’ Equation to Improve Estimates of Soil Moisture in Two-Layered Soils after Infiltration

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1174 ◽  
Author(s):  
Honglin Zhu ◽  
Tingxi Liu ◽  
Baolin Xue ◽  
Yinglan A. ◽  
Guoqiang Wang
Keyword(s):  
Soil Moisture ◽  
Overland Flow ◽  
Hydrological Cycle ◽  
Soil Depth ◽  
Controlling Factors ◽  
Moisture Distribution ◽  
Richards Equation ◽  
Infiltration Process ◽  
Soil Moisture Distribution

Soil moisture distribution plays a significant role in soil erosion, evapotranspiration, and overland flow. Infiltration is a main component of the hydrological cycle, and simulations of soil moisture can improve infiltration process modeling. Different environmental factors affect soil moisture distribution in different soil layers. Soil moisture distribution is influenced mainly by soil properties (e.g., porosity) in the upper layer (10 cm), but by gravity-related factors (e.g., slope) in the deeper layer (50 cm). Richards’ equation is a widely used infiltration equation in hydrological models, but its homogeneous assumptions simplify the pattern of soil moisture distribution, leading to overestimates. Here, we present a modified Richards’ equation to predict soil moisture distribution in different layers along vertical infiltration. Two formulae considering different controlling factors were used to estimate soil moisture distribution at a given time and depth. Data for factors including slope, soil depth, porosity, and hydraulic conductivity were obtained from the literature and in situ measurements and used as prior information. Simulations were compared between the modified and the original Richards’ equations and with measurements taken at different times and depths. Comparisons with soil moisture data measured in situ indicated that the modified Richards’ equation still had limitations in terms of reproducing soil moisture in different slope positions and rainfall periods. However, compared with the original Richards’ equation, the modified equation estimated soil moisture with spatial diversity in the infiltration process more accurately. The equation may benefit from further solutions that consider various controlling factors in layers. Our results show that the proposed modified Richards’ equation provides a more effective approach to predict soil moisture in the vertical infiltration process.

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