We tested here a simple, hydrologically based, multi-year daily crop model called PolyCrop (PC), and tested it for the purpose of reproducing the dynamics of maize (Zea Mais L.) within two case study areas in the Po valley of Italy, namely Persico Dosimo (Cremona province), and Livraga (Lodi province), and to subsequently calculate water use therein, in the form of water footprint indicators. The model uses daily information of weather drivers given by temperature, precipitation, and solar radiation to simulate soil water budget, crop growth and crop yield, providing daily estimates of soil moisture, evapotranspiration, leaf area index LAI, and biomass. We simulated maize growth in Persico Dosimo using the PC, and the reference model from the literature Cropsyst (CS), and we validated our simulations against crop productivity data during 2001-2010. We then simulated maize growth in Livraga for 3years (2010-2012), and we compared (i) actual evapotranspiration, and soil moisture against daily field measurements taken by an eddy covariance tower, and TDR probes, (ii) biomass against results from simulations with CS, and (iii) LAI against estimates from MODIS satellite images at 1km resolution with eight-day frequency of acquisition. We then calculated water footprint (green water footprint, WFG, and blue water footprint, WFB) of maize in the area, defined as the absolute and specific (per kg yield) amount of water evapotranspired during the growing season, and we use PC and CS models to assess WFG, and WFB, under the present irrigation scheme. We benchmarked our WF estimates against available estimates in the reference literature. The PC model performs comparably well in depicting daily dynamics of maize growth, soil moisture, and LAI, and water footprint of the crop system, and therefore we are confident that it may be useful for crop growth simulation, as necessary to tackle a number of issues, including e.g. (i) assessment of crop productivity under current climate and management, (ii) short to medium term forecast of yield and soil moisture for a sustainable irrigation management, (iii) assessment of water usage of cropping systems, and (iv) modified crop and water footprint conditions under prospective climate change, using climate forcing from GCMs and other climate models. Future developments may regard inclusion of nutrient dynamics, which is not a limiting factor nowadays for growth in the Po valley, but may concern use of or crop model elsewhere, or here in the future. © 2014 Elsevier Ltd.

A model for crop yield and water footprint assessment: Study of maize in the Po valley

NANA, ESTER;CORBARI, CHIARA;BOCCHIOLA, DANIELE
2014-01-01

Abstract

We tested here a simple, hydrologically based, multi-year daily crop model called PolyCrop (PC), and tested it for the purpose of reproducing the dynamics of maize (Zea Mais L.) within two case study areas in the Po valley of Italy, namely Persico Dosimo (Cremona province), and Livraga (Lodi province), and to subsequently calculate water use therein, in the form of water footprint indicators. The model uses daily information of weather drivers given by temperature, precipitation, and solar radiation to simulate soil water budget, crop growth and crop yield, providing daily estimates of soil moisture, evapotranspiration, leaf area index LAI, and biomass. We simulated maize growth in Persico Dosimo using the PC, and the reference model from the literature Cropsyst (CS), and we validated our simulations against crop productivity data during 2001-2010. We then simulated maize growth in Livraga for 3years (2010-2012), and we compared (i) actual evapotranspiration, and soil moisture against daily field measurements taken by an eddy covariance tower, and TDR probes, (ii) biomass against results from simulations with CS, and (iii) LAI against estimates from MODIS satellite images at 1km resolution with eight-day frequency of acquisition. We then calculated water footprint (green water footprint, WFG, and blue water footprint, WFB) of maize in the area, defined as the absolute and specific (per kg yield) amount of water evapotranspired during the growing season, and we use PC and CS models to assess WFG, and WFB, under the present irrigation scheme. We benchmarked our WF estimates against available estimates in the reference literature. The PC model performs comparably well in depicting daily dynamics of maize growth, soil moisture, and LAI, and water footprint of the crop system, and therefore we are confident that it may be useful for crop growth simulation, as necessary to tackle a number of issues, including e.g. (i) assessment of crop productivity under current climate and management, (ii) short to medium term forecast of yield and soil moisture for a sustainable irrigation management, (iii) assessment of water usage of cropping systems, and (iv) modified crop and water footprint conditions under prospective climate change, using climate forcing from GCMs and other climate models. Future developments may regard inclusion of nutrient dynamics, which is not a limiting factor nowadays for growth in the Po valley, but may concern use of or crop model elsewhere, or here in the future. © 2014 Elsevier Ltd.
2014
Eddy covariance; Remote sensing; Water footprint; Zea Mais L.; Agronomy and Crop Science; Animal Science and Zoology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1013312
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