Measurement of spatial average of field soil water content by the long heat probe method

1994 ◽  
Vol 40 (4) ◽  
pp. 565-571 ◽  
Author(s):  
Tatsuaki Kasubuchi ◽  
Shuichi Hasegawa
2009 ◽  
Vol 16 (1) ◽  
pp. 141-150 ◽  
Author(s):  
M. Gebremichael ◽  
R. Rigon ◽  
G. Bertoldi ◽  
T. M. Over

Abstract. By providing continuous high-resolution simulations of soil moisture fields, distributed hydrologic models could be powerful tools to advance the scientific community's understanding of the space-time variability and scaling characteristics of soil moisture fields. However, in order to use the soil moisture simulations from hydrologic models with confidence, it is important to understand whether the models are able to represent in a reliable way the processes regulating soil moisture variability. In this study, a comparison of the scaling characteristics of spatial soil moisture fields derived from a set of microwave radiometer observations from the Southern Great Plains 1997 experiment and corresponding simulations using the distributed hydrologic model GEOtop is performed through the use of generalized variograms. Microwave observations and model simulations are in agreement with respect to suggesting the existence of a scale-invariance property in the variograms of spatial soil moisture fields, and indicating that the scaling characteristics vary with changes in the spatial average soil water content. However, observations and simulations give contradictory results regarding the relationship between the scaling parameters (i.e. spatial organization) and average soil water content. The drying process increased the spatial correlation of the microwave observations at both short and long separation distances while increasing the rate of decay of correlation with distance. The effect of drying on the spatial correlation of the model simulations was more complex, depending on the storm and the simulation examined, but for the largest storm in the simulation most similar to the observations, drying increased the long-range correlation but decreased the short-range. This is an indication that model simulations, while reproducing correctly the total streamflow at the outlet of the watershed, may not accurately reproduce the runoff production mechanisms. Consideration of the scaling characteristics of spatial soil moisture fields can therefore serve as a more intensive means for validating distributed hydrologic models, compared to the traditional approach of only comparing the streamflow hydrographs.


2010 ◽  
Vol 12 (1) ◽  
pp. 9
Author(s):  
Dwi Putro Tejo Baskoro

A study about the effect of humic substance and green manure on soil physical characteristics and cassava production was conducted on a Sandy loam soil in Sukadana-East Lampung. Humic substance was obtained from Proper Humic, whereas green manure was obtained from crop residue and weed surrounding the experimental site. Humic substance applied was 15 liters ha-1 and green manure applied was 2 tons ha-1. The result of the experiment indicated that in general, humic substance and green manure applied had no significant effect on soil physical characteristics. However, there was a tendency that water content at field capacity (pF 2.54) and water available capacity increased as humic substance and green manure were applied. Similar tendency was also observed for water retained in soil where field soil water content at 7 consecutive no-raindays was slightly higher at soil with humic substance and green manure. With the application of humic substance and green manure, soil could hold water in a longer time. The effect of green manure on field soil water content was, however, slightly better than that of humic substance. Nevertheless, application of humic substance 15 l ha-1 increased significantly cassava growth and production and the effect was better than those from green manure with the dosage of 2 ton ha-1. Key words: cassava production, humic substance, water retention


2017 ◽  
pp. 143-148
Author(s):  
Mahama Salifu

Maize (Zea mays L.) is the most important consuming cereal crop in the world after rice and wheat. This requires an understanding of various management practices as well as conditions that affect maize crop performance. Water deficit stress during crop production is one of the most serious threats to crop production in most parts of the world and drought stress or water deficit is an inevitable and recurring feature of global agriculture and it is against this background that field study of crops response to water deficit is very important to crop producer and researchers to maximize yield and improve crop production in this era of unpredicted climatic changes the world over.A pot experiment was carried out to determine the effects of water deficit on growth and yield formation of maize. Two maize cultivars were used Xundan20 and Zhongdan5485. Three levels of soil water content were used in two stages of water control levels at two stages of the maize plant development1. The JOINTING STAGE: A. CONTROL (CK) soil water content: from 70% to 80% of soil water holding capacity at the field, soil water content: from 55% to 65% of soil water holding capacity at the field, soil water content: from 40% to 50% of the Soil water holding capacity at the field.2. The BIG FLARE PERIOD: A. CONTROL (CK) soil water content: from 75% to 85% of soil water holding capacity at the field, soil water content: from 58% to 68% of soil water holding capacity at the field, soil water content: from 45% to 55% of the soil water holding capacity at the field.This research mainly studied the effects of water deficit on physiological, morphology and the agronomical characteristics of the maize plant at the different water stress levels.The importance of these results in this experiment will enable plant producers to focus and have a fair idea as to which stage of the maize plant’s development that much attention must be given to in terms of water supply.


2021 ◽  
Vol 57 (2) ◽  
Author(s):  
Feike J. Leij ◽  
Jacob H. Dane ◽  
Antonella Sciortino

2016 ◽  
Author(s):  
William Alexander Avery ◽  
Catherine Finkenbiner ◽  
Trenton E. Franz ◽  
Tiejun Wang ◽  
Anthony L. Nguy-Robertson ◽  
...  

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