Agricultural Hydroinformatics: A Blueprint for an Emerging Framework to Foster Water Management-Centric Sustainability Transitions in Farming Systems

Abstract

It is increasingly recognized that water scarcity, rather than a lack of arable land, will be the major constraint to increase agricultural production over the next few decades. Therefore, water represents a unique agricultural asset to drive agricultural sustainability. However, its planning, management and usage are often influenced by a mix of interdependent economic, engineering, social, hydrologic, environmental, and even political factors. Such a complex interdependency suggests that a sociotechnical approach to water resources management, a subject of the field of Hydroinformatics, represents a viable path forward to achieve sustainable agriculture. Thus, this paper presents an overview of the intersection between hydroinformatics and agriculture to introduce a new research field called agricultural hydroinformatics. In addition, it proposes a general conceptual framework taking into account the distinctive features associated with the sociotechnical dimension of hydroinformatics when applied in agriculture. The framework is designed to serve as a stepping-stone to achieve, not only integrated water resources management, but also agricultural sustainability transitions in general. Using examples from agricultural water development to horticultural and livestock farming, the paper highlights facets of the framework applicability as a new paradigm on data flows/sources consideration, and information and simulation models engineering as well as integration for a holistic approach to water resources management in agriculture. Finally, it discusses opportunities and challenges associated with the implementation of agricultural hydroinformatics and the development of new research areas needed to achieve the full potential of this emerging framework. These areas include, for example, sensor deployment and development, signal processing, information modeling and storage, artificial intelligence, and new kind of simulation model development approaches.

Temporal and Local Heterogeneities of Water Table Depth under Different Agricultural Water Management Conditions

“…Of course, more sites and years under adequate subirrigation systems would be needed to further substantiate this recommendation. Automatic infrastructures for water table management and adequate hydroinformatics [1], that is, the combined use of predictive models [8,25] and remotely controlled subirrigation systems [26], represent a promising avenue towards real-time water table management.…”

“…Agricultural water management faces more and more challenges, having to cope with changing climate conditions including more occurrences of extreme droughts and precipitation. One way to adapt is to implement integrated water management through agricultural hydroinformatics [1]. The use of such tools actively relies on developing and incorporating real-time predictive and adaptive models of distribution patterns of water table depth (WTD).…”

Resolving streamflow diel fluctuations in a small agricultural catchment with an integrated surface‐subsurface hydrological model

“…Also, it was evident that irrigation sustained a higher base flow during dry periods as compared to the simulation without irrigation; however, irrigation did not affect, but only superposed to, the occurrence of streamflow diel fluctuations in this catchment. With the outlook of exploiting open monitoring data for improving the realism of catchment-scale hydrological models in human-impacted catchments (Celicourt et al, 2020), it is essential to establish cooperative frameworks between farmers and research institutions for boosting the exchange of crucial hydrological data (Della Chiesa et al, 2019).…”