scholarly journals Simulation of Soil Temperature Dynamics with Models Using Different Concepts

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Renáta Sándor ◽  
Nándor Fodor
Keyword(s):  
Soil Temperature ◽  
Leaf Area ◽  
Meteorological Parameters ◽  
Test Site ◽  
Temperature Oscillation ◽  
Winter Period ◽  
1D Model ◽  
Different Depths ◽  
Insulation Effect ◽  
Hydrus 1D

This paper presents two soil temperature models with empirical and mechanistic concepts. At the test site (calcaric arenosol), meteorological parameters as well as soil moisture content and temperature at 5 different depths were measured in an experiment with 8 parcels realizing the combinations of the fertilized, nonfertilized, irrigated, nonirrigated treatments in two replicates. Leaf area dynamics was also monitored. Soil temperature was calculated with the original and a modified version of CERES as well as with the HYDRUS-1D model. The simulated soil temperature values were compared to the observed ones. The vegetation reduced both the average soil temperature and its diurnal amplitude; therefore, considering the leaf area dynamics is important in modeling. The models underestimated the actual soil temperature and overestimated the temperature oscillation within the winter period. All models failed to account for the insulation effect of snow cover. The modified CERES provided explicitly more accurate soil temperature values than the original one. Though HYDRUS-1D provided more accurate soil temperature estimations, its superiority to CERES is not unequivocal as it requires more detailed inputs.

scholarly journals Response characteristics of soil moisture to rainfall for a single grass vegetation in the urban area A case of regional grassland in Yangzhou City

2021 ◽  
Author(s):  
Jinbai Huang ◽  
Jiawei Wen ◽  
Chaofan Zhu ◽  
Diwen Luo
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Infiltration Depth ◽  
Rainfall Events ◽  
Response Characteristics ◽  
Increase Rate ◽  
1D Model ◽  
Different Depths ◽  
Hydrus 1D

A regional grassland with Bermudagrass in Yangzhou City of China was adopted as the study location. Based on the analysis of the different rainfall events and soil water content data in the same periods, the response characteristics of infiltration to rainfall were revealed in a certain degree. The surface resistance parameters (rs) are calibrated according to the soil water content at the depths of a range for 0-30 cm and of the root layer (0-10 cm). Penman-Monteith (P-M) equation was adopted to estimated the hourly evapotranspiration (ET) over the Bermudagrass lawn of the soil layers for the depths of 0-30 cm (ET30) and 0-10 cm (ET10), respectively. Applicability of HYDRUS-1D model for simulating soil water content at different depths was validated. The results indicated that the infiltration depth generally varies with the rainfall event grade, and on the whole, the infiltration depth increases with the improvement of amount of rainfall; the response time for the soil water content in root layer is much shorter with the less soil water content in the topsoil (0-5.5 cm); the increase rate of soil water content raised with increasing of rainfall intensity in the state of unsaturation; ET10 accounts for about 78% of ET30, which demonstrates the water consumed by ET is mainly provided by the soil water in the root layer. the rationality of the results of different rainfall events and infiltration depth achieved by the analysis of the observed data were verified via numerical simulation using Hydrus-1D.

scholarly journals Quality control of 10-min soil temperatures data at RMI

2015 ◽  
Vol 12 (1) ◽  
pp. 23-30 ◽  
Author(s):  
C. Bertrand ◽  
L. González Sotelino ◽  
M. Journée
Keyword(s):  
Quality Control ◽  
Soil Temperature ◽  
Bare Soil ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Temperature Observation ◽  
Soil Temperatures ◽  
Different Depths ◽  
Temperature Records ◽  
Energy Processes

Abstract. Soil temperatures at various depths are unique parameters useful to describe both the surface energy processes and regional environmental and climate conditions. To provide soil temperature observation in different regions across Belgium for agricultural management as well as for climate research, soil temperatures are recorded in 13 of the 20 automated weather stations operated by the Royal Meteorological Institute (RMI) of Belgium. At each station, soil temperature can be measured at up to 5 different depths (from 5 to 100 cm) in addition to the bare soil and grass temperature records. Although many methods have been developed to identify erroneous air temperatures, little attention has been paid to quality control of soil temperature data. This contribution describes the newly developed semi-automatic quality control of 10-min soil temperatures data at RMI.

Wavelet neural networks and gene expression programming models to predict short-term soil temperature at different depths

2018 ◽  
Vol 175 ◽  
pp. 37-50 ◽  
Author(s):  
Saeed Samadianfard ◽  
Esmaeil Asadi ◽  
Salar Jarhan ◽  
Honeyeh Kazemi ◽  
Salar Kheshtgar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Networks ◽  
Soil Temperature ◽  
Gene Expression Programming ◽  
Programming Models ◽  
Wavelet Neural Networks ◽  
Short Term ◽  
Different Depths

scholarly journals Soil Temperature Estimation with Meteorological Parameters by Using Tree-Based Hybrid Data Mining Models

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1407
Author(s):  
Mohammad Taghi Sattari ◽  
Anca Avram ◽  
Halit Apaydin ◽  
Oliviu Matei
Keyword(s):  
Soil Temperature ◽  
Soil Depth ◽  
Sunshine Duration ◽  
Evaluation Criteria ◽  
Nonlinear Problems ◽  
Soil Temperatures ◽  
Different Depths ◽  
Windowing Technique ◽  
Using Data ◽  
Research Decision

The temperature of the soil at different depths is one of the most important factors used in different disciplines, such as hydrology, soil science, civil engineering, construction, geotechnology, ecology, meteorology, agriculture, and environmental studies. In addition to physical and spatial variables, meteorological elements are also effective in changing soil temperatures at different depths. The use of machine-learning models is increasing day by day in many complex and nonlinear branches of science. These data-driven models seek solutions to complex and nonlinear problems using data observed in the past. In this research, decision tree (DT), gradient boosted trees (GBT), and hybrid DT–GBT models were used to estimate soil temperature. The soil temperatures at 5, 10, and 20 cm depths were estimated using the daily minimum, maximum, and mean temperature; sunshine intensity and duration, and precipitation data measured between 1993 and 2018 at Divrigi station in Sivas province in Turkey. To predict the soil temperature at different depths, the time windowing technique was used on the input data. According to the results, hybrid DT–GBT, GBT, and DT methods estimated the soil temperature at 5 cm depth the most successfully, respectively. However, the best estimate was obtained with the DT model at soil depths of 10 and 20 cm. According to the results of the research, the accuracy rate of the models has also increased with increasing soil depth. In the prediction of soil temperature, sunshine duration and air temperature were determined as the most important factors and precipitation was the most insignificant meteorological variable. According to the evaluation criteria, such as Nash-Sutcliffe coefficient, R, MAE, RMSE, and Taylor diagrams used, it is recommended that all three (DT, GBT, and hybrid DT–GBT) data-based models can be used for predicting soil temperature.

scholarly journals Response of Soil Temperature, Moisture, and Spring Maize (Zea mays L.) Root/Shoot Growth to Different Mulching Materials in Semi-Arid Areas of Northwest China

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 453
Author(s):  
Haidong Lu ◽  
Zhenqing Xia ◽  
Yafang Fu ◽  
Qi Wang ◽  
Jiquan Xue ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Soil Water ◽  
Leaf Area ◽  
Growth Period ◽  
Soil Water Storage ◽  
Shoot Biomass ◽  
Growth Stages ◽  
Plastic Film ◽  
Area Index ◽  
Spring Maize

Adaptive highly efficient mulching technologies for use on dryland agricultural ecosystems are crucial to improving crop productivity and water-use efficiency (WUE) under climate change. Little information is available on the effect of using different types of mulch on soil water thermal conditions, or on root/shoot trait, leaf area index (LAI), leaf area duration (LAD), yield, and WUE of spring maize. Hence, in this study, white transparent plastic film (WF), black plastic film (BF), and maize straw (MS) was used, and the results were compared with a non-mulched control (CK). The results showed that the mean soil temperature throughout the whole growth period of maize at the 5–15 cm depth under WF and BF was higher than under MS and CK, but under BF, it was 0.6 °C lower than WF. Compared with CK, the average soil water storage (0–200 cm) over the whole growth period of maize was significantly increased under WF, BF, and MS. WF and BF increased the soil water and temperature during the early growth stages of maize and significantly increased root/shoot biomass, root volume, LAI, LAD, and yield compared with MS. Higher soil temperatures under WF obviously reduced the duration of maize reproductive growth and accelerated root and leaf senescence, leading to small root/shoot biomass accumulation post-tasseling and to losses in yield compared with BF

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