WATER QUALITY ASSESSMENT WITH AGRO-ENVIRONMENTAL INDEXING OF NON-POINT SOURCES, TRINITY RIVER BASIN

Abstract

A comprehensive water quality assessment was conducted to determine the potential impacts of agriculture on surface and groundwater quality. The EPIC (Environmental Policy Integrated Climate) model was used to simulate cropping systems in the Trinity River Basin in Texas for 12 eight-digit hydrologic unit areas (HUA) using combinations of 29 soil series, 9 crops, and 3 tillage technologies. The study utilizes an indexing method to facilitate communicating the relative impacts of soils, crops, tillage, and management practices on the following agro-environmental indicators of water quality: (1) surface water runoff, (2) soil erosion, (3) nitrate-nitrogen (NO 3 -N) loss in runoff, (4) phosphorus (P) loss in runoff, (5) NO 3 -N loss in sediment, (6) P loss in sediment, and (7) NO 3 -N leaching loss. A frequency analysis was also conducted to provide an overview of the impacts; indicated by averaging broad groupings of precipitation, soil types by percent clay, percent slope, tillage practices, and crop rotations produced. When grouped by soil type, high clay content soils on average minimized NO 3 -N leaching of all soil types. In contrast, clay and loam soils increased runoff over sandy soils. Additionally, clay and loam soils lost more NO 3 -N and P in runoff as well as in sediment than sandy soils. With respect to tillage practice, no-till and reduced tillage generally reduced erosion compared with conventional tillage practices. NO 3 -N and P losses in sediment were reduced using no-till and reduced tillage, but the NO 3 -N and P losses in runoff were not particularly affected, on average, by tillage practice. With regard to crop selection and rotation, the degree of agro-environmental impact from nutrient losses was largely correlated with the applications of N and P. Though the simulation results largely agreed with previous experiences of agricultural researchers, the ultimate implication of this study is that creating indices for a multitude of comparisons of simulated water quality or other environmental impacts in complex agricultural systems can be communicated and summarized with a high degree of specificity. However, indexing simulation results for comparative analyses was less than satisfactory, on occasion, when an index value was very large usually caused by a small value for the baseline crop. In many cases, the impact of the alternative would not be considered as extreme, though the large index value might imply the agro-environmental impact to be severe. The major advantage of indexing is the ease of communicating diverse results in an uncomplicated manner. Thus, indexing provides a means of communicating water quality impacts of complex production elements in agriculture to citizens, policy makers, and other decision-makers not familiar with them.