Establishing the water resources implications for closing the land and water productivity gaps using remote sensing – A case study of sugarcane

Abstract

Context

Two of the key limitations for sustainably increasing agricultural production are the scarcity of land and fresh water resources. Establishing land and water productivity gaps is, therefore, essential for measuring how efficiently these resources are being utilised and assessing the scope for increasing feed and food production. Monitoring the productivity gaps at large scales or over time using field data is challenging and expensive. Remote sensing offers an alternative data source to reveal spatial and temporal variations in productivity.

Objective

This paper presents a framework that integrates remote sensing derived data and field data to assess (1) land and water productivity gaps, (2) bright spots – fields exhibiting land- and water productivity equal to or higher than the target, and (3) net irrigation water demand for increasing production.

Methods

The framework is developed and applied to the Xinavane sugarcane estate in Mozambique, demonstrating its practical application through systematic evaluation on a 6637 ha section of the estate divided by different irrigation application methods.

Results

The results reveal that the productivity gap is the highest on fields irrigated by furrow (13.1 tonnes (ton) per ha), followed by sprinkler (12.6 ton/ha) and centre pivot (9.4 ton/ha). Bridging the productivity gap on the same cropland results in an increased sugarcane production of 12.5 % requiring 8.5 % additional irrigation water, whereas achieving the same production increase through irrigation expansion requires more blue water.

Conclusions

The analyses show that remote sensing provides a viable source of information to diagnose the productivity constraints and how bright spots can provide insights into the best field management practices to overcome them. The framework demonstrates its usefulness for policy makers and stakeholders to make informed decisions on the scarce blue water allocation for enhancing agricultural production.