Land use as possible strategy for managing water table depth in flat basins with shallow groundwater

ABSTRACT

In flat plains groundwater affects agricultural production outcomes and risks. Agricultural land use decisions, however, may strongly impact groundwater levels available for production. This paper explores the scope for managing groundwater levels through land use decisions in a sub-basin of the Salado River in the Argentine Pampas, a very flat area that plays a key role in world agricultural production. A spatially distributed hydrological model implemented with MIKE SHE software was used to establish the impacts of different land uses on groundwater dynamics, and to assess the interdependencies among spatially close decision-makers sharing a water table (WT). Additionally, groundwater level changes in response to climate variability were quantified. We found land use has strong effects on WT levels both for oneself (e.g. pastures can lead to significant decreases (up to 4.5 m) in WT levels) and others, in the form of strong interdependencies that exist between farmers sharing a WT where land use decisions of one farmer effect groundwater level of neighbouring farms and vice versa. However, the effectiveness to control groundwater levels through land use decisions is subject to the rather unpredictable effects of rainfall variability. The results presented in this paper provide key insights in relation to physical and social aspects that should be considered for managing groundwater levels through land use decisions, in order to avoid negative and/or maximize positive effects on agricultural production.

KEYWORDS:

• Land use change
• groundwater dynamics
• interdependencies
• Argentine pampas
• hydrological modelling
• climate variability

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Pablo E. García http://orcid.org/0000-0003-4193-7601

Notes

1 The water table is defined as the top of the water-saturated zone (or phreatic zone) in the soil profile.

Additional information

Funding

This research was supported by the U.S. National Science Foundation (NSF), grants [0709681 and 1211613] (Dynamics of Coupled Natural and Human Systems) and [1049109] (Decadal Regional Climate Prediction using Earth System Models), and by the Inter-American Institute for Global Change Research (IAI) grant [2031]-addendum (Collaborative Research Network 2). The IAI is supported by the NSF.