Managing irrigation water as a function of its quality

Water scarcity and the need for increased agricultural production have led to greater utilization of non-conventional, marginal- to low-quality, sources of water for irrigation. These water sources mainly recycled municipal waste water and brackish groundwater, are typically characterized by high concentrations of contaminants including salts.

Agronomic success when irrigating with water high in salts is contingent upon water management in which salts are disallowed from accumulating in crop root zones. Salinity management most often entails application of excess water for leaching and drainage collection and disposal. Addition of salt to agricultural systems causes degradation of soils and negative effects to crops. Leaching of salts leads to contamination of deep soils and groundwater or to drainage waters requiring treatment and disposal solutions.

An additional aspect of water-source and quality specific management is found in plant nutrition-fertilization practices. Interactions between salts and nutrient minerals in soils and plants require rethinking of traditional fertilization methods and regimes.

The recent addition of desalinated water to address chronic water shortages in dry regions including Israel, may coincidentally provide opportunity for a more sustainable solution for agriculture. Desalination can supply very high-quality water to irrigate high-value, salt- sensitive crops and leads to reduction of salinity of recycled wastewater. While allowing less leaching and therefore more sustainable irrigation, the utilization of desalinated water comes with its own set of challenges including cost, unpredictable actual contents of minerals when mixed with other water sources in distribution systems, and requirements for provision of minerals, removed in desalination processes but needed in agricultural applications.

Recent research has provided understanding and tools for optimizing water and nutrient use efficiency as a function of water quality. These include models for crops response which recently have been coupled with economic data to offer tools for decision making for planners and growers.