Abstract
Quantitative agricultural landscape indices are useful to describe functional relationships among climatic conditions, groundwater dynamics, soil properties and agricultural land use for mathematical models. We applied methods of regression statistics, variance component estimation and a Geographical Information System (GIS) to construct indices describing crops and soils and to establish functional relationships among these variables. This paper describes the development of indices and the partitioning of the spatial and temporal variation in groundwater models using the data from Tulare County, California, which was selected as the study area. Indices of ground surface elevation, total crop water demand, soil water infiltration rate, and soil production index explain 91% of the variation in average spring groundwater level. After relating spatial patterns of groundwater use to indices of crop and soil properties, we found that mean groundwater use is positively related to total crop water demand and soil water infiltration rate while the variation in groundwater use was negatively correlated with the crop water demand and soil water infiltration rate and positively related to soil water holding capacity. The spatial variation in groundwater use was largely influenced by crops and soil types while the temporal variation was not. We also found that groundwater use increased exponentially with decreasing annual precipitation for most townships. Based on these associations, groundwater use in each township can be forecast from relative precipitation under current methods of agricultural production. Although groundwater table depth is strongly affected by topography, the statistically significant indices observed in the model clearly show that agricultural land use influences groundwater table depth. These simple relationships can be used by agronomists to make water management decisions and to design alternative cropping systems to sustain agricultural production during periods of surface water shortages.
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Zhang, M., Geng, S. & Ustin, S.L. Quantifying the agricultural landscape and assessing spatio-temporal patterns of precipitation and groundwater use. Landscape Ecology 13, 37–54 (1998). https://doi.org/10.1023/A:1007924914662
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DOI: https://doi.org/10.1023/A:1007924914662