QUANTIFYING THE AGRICULTURAL LANDSCAPE AND ASSESSING SPATIOTEMPORAL PATTERNS OF PRECIPITATION AND GROUNDWATER USE

Quantitative agricultural landscape indices are useful to describe fun ctional relationships among climatic conditions, groundwater dynamics, soil properties and agricultural land use for mathematical models. We applied methods of regression statistics, variance component estimati on and a Geographical Information System (GIS) to construct indices de scribing crops and soils and to establish functional relationships amo ng these variables. This paper describes the development of indices an d the partitioning of the spatial and temporal variation in groundwate r models using the data from Tulare County, California, which was sele cted as the study area. Indices of ground surface elevation, total cro p water demand, soil water infiltration rate, and soil production inde x explain 91% of the variation in average spring groundwater level. Af ter relating spatial patterns of groundwater use to indices of crop an d soil properties, we found that mean groundwater use is positively re lated to total crop water demand and soil water infiltration rate whil e the variation in groundwater use was negatively correlated with the crop water demand and soil water infiltration rate and positively rela ted to soil water holding capacity. The spatial variation in groundwat er use was largely influenced by crops and soil types while the tempor al variation was not. We also found that groundwater use increased exp onentially with decreasing annual precipitation for most townships. Ba sed on these associations, groundwater use in each township can be for ecast from relative precipitation under current methods of agricultura l production. Although groundwater table depth is strongly affected by topography, the statistically significant indices observed in the mod el clearly show that agricultural land use influences groundwater tabl e 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 sh ortages.