An integrated SVR and crop model to estimate the impacts of irrigation on daily groundwater levels

An integrated SVR and crop model to estimate the impacts of irrigation on daily groundwater levels As groundwater resources are used more intensively, the need to define appropriate strategies to plan and manage irrigation systems under diverse climatic conditions becomes increasingly important. To promote more efficient irrigation practices, accurate and optimal information regarding the interaction between crop water use and groundwater sustainability is needed. In this study, we outlined a modeling approach that combines the features of a crop growth model and a support vector regression (SVR) model for the comprehensive assessment of groundwater variability under different soybean (Glycine max [L.] Merr) irrigation thresholds throughout the growing season. The 20%, 40%, 50% and 60% thresholds of available water were calibrated using the CROPGRO-Soybean model to simulate daily irrigation requirements of soybeans grown in the Mississippi Delta Region (MDR). The daily crop water requirements along with precipitation and previous daily groundwater levels were used as inputs in the SVR to evaluate the predicted response of daily groundwater levels to different irrigation demands. We examined the performance of the SVR model based on the Mean Squared Error (MSE) and its ability to capture the seasonal variability in groundwater levels under different scenarios. Results demonstrate that higher groundwater irrigation volumes significantly affect the daily availability of groundwater. However, more volume does not represent significantly higher soybean yields. We conclude that the hybrid crop-SVR model is able to assess the subsurface water response to multiple scenarios of groundwater available for irrigation and provide useful information for the decision making. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural Systems Elsevier

An integrated SVR and crop model to estimate the impacts of irrigation on daily groundwater levels

Loading next page...
 
/lp/elsevier/an-integrated-svr-and-crop-model-to-estimate-the-impacts-of-irrigation-q1E6XPljJT
Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0308-521x
D.O.I.
10.1016/j.agsy.2017.01.017
Publisher site
See Article on Publisher Site

Abstract

As groundwater resources are used more intensively, the need to define appropriate strategies to plan and manage irrigation systems under diverse climatic conditions becomes increasingly important. To promote more efficient irrigation practices, accurate and optimal information regarding the interaction between crop water use and groundwater sustainability is needed. In this study, we outlined a modeling approach that combines the features of a crop growth model and a support vector regression (SVR) model for the comprehensive assessment of groundwater variability under different soybean (Glycine max [L.] Merr) irrigation thresholds throughout the growing season. The 20%, 40%, 50% and 60% thresholds of available water were calibrated using the CROPGRO-Soybean model to simulate daily irrigation requirements of soybeans grown in the Mississippi Delta Region (MDR). The daily crop water requirements along with precipitation and previous daily groundwater levels were used as inputs in the SVR to evaluate the predicted response of daily groundwater levels to different irrigation demands. We examined the performance of the SVR model based on the Mean Squared Error (MSE) and its ability to capture the seasonal variability in groundwater levels under different scenarios. Results demonstrate that higher groundwater irrigation volumes significantly affect the daily availability of groundwater. However, more volume does not represent significantly higher soybean yields. We conclude that the hybrid crop-SVR model is able to assess the subsurface water response to multiple scenarios of groundwater available for irrigation and provide useful information for the decision making.

Journal

Agricultural SystemsElsevier

Published: Jan 1, 2018

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 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

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

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off