Water-efficient sensing method for soil profiling in the paddy field

Zhenran Gao, Jun Ni, Yan Zhu, Qi Jiang, Weixing Cao

Abstract


The comprehensive and reliable perception of moisture in a soil profile is essential to irrigation. To establish an efficient method for sensing soil moisture, field trials were conducted to analyze the spatial and temporal variations of moisture in a paddy soil profile by using coefficients of variation. The results showed that soil layers at shallow depths undergo more extensive changes in the coefficients of variation. Moisture perception is most sensitive within a depth range of 0-60 cm in the vertical soil profile of a paddy field. By using the clustering algorithm of Euclidean distance, the paddy soil profile was divided into three categories based on soil depth. The first category includes depths ranging from 10-20 cm, the second is from 30-40 cm, and the third is from 50-100 cm. Path analysis indicated that the most sensitive depths for moisture sensing in a paddy soil profile were 20 cm, 30 cm, and 50 cm, whereas the most sensitive depths for moisture sensing by time stability analysis were 20 cm, 40 cm, and 60 cm. Based on the multiple regression of sensitive depths, the results of quantitative inversion indicated that the time stability analysis results were 0.962 when the of path analysis was 0.980, and the time stability analysis was 0.61 when the root mean square error (RMSE) of path analysis was 0.40. The relative error range between the measured and predicted values of path analysis was less than that of time stability analysis. These findings suggest that it is feasible to effectively sense the moisture of the entire vertical soil profile based on the sensitive depth. The present study has also determined that path analysis is superior to time stability analysis.
Keywords: paddy field, profile soil, moisture perception, clustering algorithm, path analysis
DOI: 10.25165/j.ijabe.20181104.3593

Citation: Gao Z R, Ni J, Zhu Y, Jiang Q, Cao W X. Water-efficient sensing method for soil profiling in the paddy field. Int J Agric & Biol Eng, 2018; 11(4): 207-216.

Keywords


paddy field, profile soil, moisture perception, clustering algorithm, path analysis

Full Text:

PDF

References


Coelho E F, Or D. Flow and uptake patterns affecting soil water sensor

placement for drip irrigation management. Trans of the ASAE, 1996; 39(6): 2007–2016.

Aljoumani B, Sànchez-Espigares J A, Cañameras N, Josa R, Monserrat J. Time series outlier and intervention analysis: irrigation management influences on soil water content in silty loam soil. Agricultural Water Management, 2012; 111(4): 105–114.

Starks P J, Heathman G C, Ahuja L R, Ma L W. Use of limited soil property data and modeling to estimate root zone soil water content. Journal of Hydrology, 2003; 272(1-4): 131–147.

Han Y G, Wu H F, Yang P L, Wang Y Q, Li B, Kong Q H. Optimal burial depth of soil moisture sensors for tomato-plangting field. Bulletin of Soil & Water Conservation, 2013; 33(4): 260–263. (in Chinese)

Shen X, Sun J, Zhang J, Wang J, Li S, Yang G. Study on the placement of sensors for moisture content in soil profile for cotton under mulched drip irrigation condition. Agricultural Research in the Arid Areas, 2012; 30(3): 90–95. (in Chinese)

Wang F, Huang L, Wu S, Li K, Li J, Gao Y, Cao Y. Design of multi-channel data acquisition and processing model and optimization of moisture sensor burying position. Transactions of the CSAE, 2015; 31(21): 148–153. (in Chinese)

Qualls R J, Scott J M, Deoreo W B. Soil moisture sensors for urban landscape irrigation: Effectivenss and reliability. Journal of the American Water Resources Association, 2001; 37(3): 547–559.

Wang X, Liu F, Han X. Influence of soil physical and chemical properties on performance of soil profile moisture sensor. Transactions of the CSAM, 2012; 43(11): 97–101.

Zhang X, Li R, Jiao M, Zhang Q, Wang Y, Li J. Development of soil moisture monitor and forecast system. Transactions of the CSAE, 2016; 32(18): 140–146. (in Chinese)

Yang T, Gong H, Li X, Zhao W, Meng D. Progress of soil moisture monitoring by remote sensing. Acta Ecologica Sinica, 2010; 22: 6264–6277.

Zhou Q, Jun S. Temporal stability of the spatial distribution pattern of soil water. Acta Pedologica Sinica, 2003; 40(5): 683–690.

Yang S, Wang Y, Sun K. Soil Moisture Content Sensors Placement Based on the Vertical Variety Law. Transactions of the CSAM, 2008; 39(5): 104–107. (in Chinese)

Gao Y, Liu Z, Duan A, Liu Z, Zhang J, Sun J. Laying depth of soil moisture probe in soil profile and date processing technology. Journal of Irrigation and Drainage, 2011; 30(5): 28–32. (in Chinese)

Liu Z, Gao Y, Duan A, Cheng J. Study on the soil moisture probe laying place of farmland in Shangqiu District of Henan Province. Water Saving Irrigation, 2008; 8: 19–22, 25. (in Chinese)

Shi Y, Li F, Sun K, Wang Z, Dong C. Study on the Moisture Sensor Laying Place in Watching and Forecasting Soil Moisture Content. Journal of Laiyang Agricultural College, 2006; 23(3): 179–184. (in Chinese)

Ragab R. Towards a continuous operational system to estimate the root-zone soil moisture from intermittent remotely sensed surface moisture. Journal of Hydrology, 1995; 173(14): 1–25.

Zang Y, Ou-yang Z, Guo J, Li Y, Cheng B, Liu E. Research on the best measurement depth for determining the dynamic soil moisture content of root layer soil moisture. China Rural Water and Hydropower, 2010; 9: 102–104. (in Chinese)

Zheng L, Ma J, Guo F, Ren R, Guo X, Sun X. Monitoring location of soil water content in water storage pit irrigated dwarfed apple tree orchard. Transactions of the CSAM, 2015; 46(10): 160–166. (in Chinese)

Wang X, Jia Y. Sampling depth analysis of farmland soil moisture forecast. Water Resources Science and Technology of Shandong, 1997; 4: 6–8. (in Chinese)

Kachanoski R G, Jong E. Scale dependence and the temporal persistence of spatial patterns of soil water storage. Water Resources Research, 1988; 24(1): 85–91.

De J C. The contribution of condensation to the water cycle under high-mountain conditions. Hydrological Processes, 2010; 19(12): 2419–2435.

Grayson R B, Western A W. Towards areal estimation of soil water content from point measurements: time and space stability of mean response. Journal of Hydrology, 1998; 207(1-2): 68–82.

Martínez-Fernández J, Ceballos A. Mean soil moisture estimation using temporal stability analysis. Journal of Hydrology, 2005; 312(1): 28–38.

Vachaud G, Silans A P D, Balabanis P, Vauclin M. Temporal stability of

spatially measured soil water probability density function. Soil Science Society of America Journal, 1985; 49(4): 822–828.

Shae J B, Steele D D, Gregor B L. Irrigation scheduling methods for popcorn in the northern great plains. Transactions of the ASAE, 1999; 42(2): 351–360.

Shock C C, Feibert E B G, Saunders L D. Irrigation criteria for drip-irrigated onions. Hortscience: A Publication of the American Society for Horticultural Science, 2000; 35(1): 63–66.

Souza C F, Folegatti M V, Or D. Distribution and storage characterization of soil solution for drip irrigation. Irrigation Science,

; 27(4): 277–288.

Liu J, Ma X, Zhang Z. Spatial variability of soil water retention curve in different soil layers and its affecting factors. Transactions of the CSAM, 2010; 41(1): 46–52.

Zhang Y, Qin H, Huang M, Li Z, Yang C, Wang N, et al. Mathematical simulation of rice root spatial distribution and its application. Journal of South China Agricultural University, 2013; 34(3): 304–308. (in Chinese)

Cai K, Luo S, Duan S. The relationship between spatial distribution of rice root system and yield. Journal of South China Agricultural University, 2003; 24(3): 1–4. (in Chinese)




Copyright (c) 2018



2023-2026 Copyright IJABE Editing and Publishing Office