Open Journal of Soil Science

Volume 3, Issue 4 (August 2013)

ISSN Print: 2162-5360   ISSN Online: 2162-5379

Google-based Impact Factor: 1.36  Citations  

Evaluation of the Precision Agricultural Landscape Modeling System (PALMS) in the Semiarid Texas Southern High Plains

HTML  Download Download as PDF (Size: 2655KB)  PP. 169-181  
DOI: 10.4236/ojss.2013.34020    4,681 Downloads   7,895 Views  Citations

ABSTRACT

Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Landscape Modeling System (PALMS) model to simulate soil water content throughout the growing season for several years and for three major soil series of the semiarid Texas Southern High Plains (SHP). Accuracy of the model was evaluated by comparing measured and calculated values of soil water content and using root mean squared difference (RMSD), squared bias (SB), squared difference between standard deviations (SDSD), and lack of correlation weighted by the standard deviation (LCS). Different versions of the model were obtained by modifying soil hydraulic properties, including saturated hydraulic conductivity (Ks) and residual (θr) and saturated (θs) soil volumetric water content, which were calculated using Rosetta pedotransfer functions. These modifications were combined with updated routines of the soil water solver in PALMS to account for rapid infiltration into dry soils that often occur in the SHP. Field studies were conducted across a wide range of soil and water conditions in the SHP. Soil water content was measured by neutron attenuation and gravimetrically throughout the growing seasons at each location to compare absolute values and the spatial distribution of soil water with PALMS calculated values. Use of Rosetta calculated soil hydraulic properties improved PALMS soil water calculation from 1% - 13% of measured soil volumetric water content (θv) depending on soil type. Large-scale models such as PALMS have the potential to more realistically represent management effects on soil water availability in agricultural fields. Improvements in PALMS soil water calculations indicated that the model may be useful to assess long-term implications of management practices designed to conserve irrigation water and maximize the profitability of dryland and irrigated cropping systems in the SHP.

Share and Cite:

J. Nelson, R. Lascano, J. Booker, R. Zartman and T. Goebel, "Evaluation of the Precision Agricultural Landscape Modeling System (PALMS) in the Semiarid Texas Southern High Plains," Open Journal of Soil Science, Vol. 3 No. 4, 2013, pp. 169-181. doi: 10.4236/ojss.2013.34020.

Cited by

[1] Precision Agriculture: Water and Nutrient Management
2020
[2] Simulation of efficient irrigation management strategies for grain sorghum production over different climate variability classes
2019
[3] Drivers of Potential Recharge from Irrigated Agroecosystems in the Wisconsin Central Sands
Vadose Zone Journal?, 2017
[4] Improvement of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (USA) High Plains
Sensors, 2015
[5] Temporal and spatial simulation of production-scale irrigated cotton systems
Precision Agriculture, 2015
[6] PALMScot: a cotton landscape model for a precision agriculture scale
Precision agriculture, 2015
[7] Evaluation of a Landscape-Scale Approach to Cotton Modeling
Agronomy Journal, 2014
[8] Threshold Dynamics in Soil Carbon Storage for Bioenergy Crops
Environmental science & technology, 2014
[9] Circular planting to enhance rainfall capture in dryland cropping systems at a landscape scale: Measurement and simulation
Practical Applications of Agricultural System Models to Optimize the Use of Limited Water, 2014
[10] Evaluation of a landscape‐scale approach to cotton modeling
2014
[11] Modeling Landscape-Scale Water Balance in Irrigated Cotton Systems
2013

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.