Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements

Integrating geospatial data and cropping system simulation within a geographic information system... The development of sensors that provide geospatial information on crop and soil conditions has been a primary success for precision agriculture. However, further developments are needed to integrate geospatial data into computer algorithms that spatially optimize crop production while considering potential environmental impacts and resource limitations. The objective of this research was to combine several information technologies, including remote sensing, a cropping system model, and a geographic information system (GIS), to synthesize and interpret geospatial data collected during two irrigation scheduling experiments conducted in 2009 and 2011 in a 5-ha cotton field in central Arizona. The Geospatial Simulation (GeoSim) plug-in for Quantum GIS was used to manage geospatial data and conduct site-specific simulations with the CSM-CROPGRO-Cotton model. Simulated annealing optimization was used to adjust five model parameters to simulate site-specific conditions in 320 zones across the field. Using input parameters for GeoSim, a multiple criteria objective function was developed to incorporate measured and simulated leaf area index (LAI), crop canopy height, seed cotton yield, and evapotranspiration (ET) for site-specific optimization of CSM-CROPGRO-Cotton. Parameter identifiability and equifinality issues associated with model inversion were investigated. The optimized model was used for post hoc analysis of irrigation rates that maximized site-specific irrigation water use efficiency. With spatial optimization, the model was able to simulate LAI with root mean squared errors (RMSE) of 15 and 8 % in the 2009 and 2011 experiments, respectively. The RMSEs between measured and simulated canopy height, seed cotton yield, and ET were 5 % or less in both seasons. Some parameters were more identifiable than others during model inversions. Multiple temporal estimates of LAI were effective for constraining the model’s specific leaf area parameter (SLAVR, cm2 g−1), but lack of information on root growth reduce identifiability of a parameter related to that process (SRGF0). Post-hoc simulation analysis of irrigation management options showed that irrigation schedules based on remotely sensed vegetation indices increased irrigation water use efficiency as compared to traditional scheduling methods, particularly in the 2009 growing season. In 2011, the analysis showed that all scheduling methods resulted in excess irrigation application, and higher deep seepage rates were simulated in that season. Taken together, the results demonstrate that well-designed software tools and algorithms for data processing and interpretation can be potentially transformative for integrating multiple geospatial data sets to compute optimum scenarios for precision irrigation management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements

Loading next page...
 
/lp/springer_journal/integrating-geospatial-data-and-cropping-system-simulation-within-a-a3WgH1bo0K
Publisher
Springer US
Copyright
Copyright © 2015 by Springer Science+Business Media New York (outside the USA)
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-015-9393-x
Publisher site
See Article on Publisher Site

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial