Spatial Calculation of the Barley Green Water Footprint in Southeastern Buenos Aires Province

The green water footprint (GWF) quantifies the consumptive water use in rainfed crops, i.e. the water consumed through the evapotranspiration process (ET<inf>green</inf>) that will not be available in the catchment area for a certain period. It represents 80% of the water consumption of agricultural activity. Despite its relevance, few studies in Argentina evaluate these water flows, which support production. Barley is the second most important winter crop in the region and has a significant role in grain exports, however, there is a gap in the GWF reference values. The aim of this study was to estimate the GWF in barley crops in the Tandil county, at 250 m spatial resolution. The methodology suggested by the Water Footprint Network was applied. To extend this methodology to the study area, a method based on satellite data (SDM) was applied to calculate the evaporative fraction (EF) and yield (Y). The performance of this method was compared with the widely used grid method (GM). We used field agroclimatic and crop data, as well as MODIS and LANDSAT products to determine ETgreen and Y. The results showed GWF values in barley from 400 m<sup>3</sup>t<sup>1</sup>to 550 m<sup>3</sup>t<sup>1</sup>in the county plots. The highest values were associated with areas where land use changed from livestock to agriculture. SDM had a better correlation with GWF values measured in the plots (R<sup>2</sup>=0.79), while GM underestimated these volumes in all cases, with no correlation with in situ GWF (R<sup>2</sup>=0.01). The underestimation was mainly related to the low spatial resolution applied, which does not consider the spatial variability of ET<inf>green</inf> and Y. With these results, we intend to contribute to monitor water management in rainfed crops and to improve the adaptability of these systems to climate variability.

Authors

Institutions

Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/argencon62399.2024.10735989
Primary Topic
Latin American rural development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial Calculation of the Barley Green Water Footprint in Southeastern Buenos Aires Province

Mauro Holzman, Paula Olivera Rodríguez, Guadalupe Ares, Francisco Diez et al.
Latin American rural development
article

Spatial Calculation of the Barley Green Water Footprint in Southeastern Buenos Aires Province

Mauro Holzman, Paula Olivera Rodríguez, Guadalupe Ares, Francisco Diez, Cristian Laino Baldini
article en

Abstract

The green water footprint (GWF) quantifies the consumptive water use in rainfed crops, i.e. the water consumed through the evapotranspiration process (ET<inf>green</inf>) that will not be available in the catchment area for a certain period. It represents 80% of the water consumption of agricultural activity. Despite its relevance, few studies in Argentina evaluate these water flows, which support production. Barley is the second most important winter crop in the region and has a significant role in grain exports, however, there is a gap in the GWF reference values. The aim of this study was to estimate the GWF in barley crops in the Tandil county, at 250 m spatial resolution. The methodology suggested by the Water Footprint Network was applied. To extend this methodology to the study area, a method based on satellite data (SDM) was applied to calculate the evaporative fraction (EF) and yield (Y). The performance of this method was compared with the widely used grid method (GM). We used field agroclimatic and crop data, as well as MODIS and LANDSAT products to determine ETgreen and Y. The results showed GWF values in barley from 400 m<sup>3</sup>t<sup>1</sup>to 550 m<sup>3</sup>t<sup>1</sup>in the county plots. The highest values were associated with areas where land use changed from livestock to agriculture. SDM had a better correlation with GWF values measured in the plots (R<sup>2</sup>=0.79), while GM underestimated these volumes in all cases, with no correlation with in situ GWF (R<sup>2</sup>=0.01). The underestimation was mainly related to the low spatial resolution applied, which does not consider the spatial variability of ET<inf>green</inf> and Y. With these results, we intend to contribute to monitor water management in rainfed crops and to improve the adaptability of these systems to climate variability.

Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
Openalex Percentile: Top 65%
Latin American rural development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.