Timothy C. Strickland

Evaluation of SWAT Manual Calibration and Input Parameter Sensitivity in the Little River Watershed

The watershed-scale effects of agricultural conservation practices are not well understood. A baseline calibration and an input parameter sensitivity analysis were conducted for simulation of watershed-scale hydrology in the Little River Experimental Watershed (LREW) in the Coastal Plain near Tifton, Georgia. The Soil and Water Assessment Tool (SWAT) was manually calibrated to simulate the hydrologic budget components measured for the 16.9 km2 subwatershed K of the LREW from 1995 to 2004. A local sensitivity analysis was performed on 16 input variables. The sum of squares of the differences between observed and simulated annual averages for baseflow, stormflow, evapotranspiration, and deep percolation was 19 mm2; average annual precipitation was 1136 mm. The monthly Nash-Sutcliffe model efficiency (NSE) for total water yield (TWYLD) was 0.79 for the ten-year period. Daily NSE for TWYLD was 0.42. The monthly NSE for three years with above-average rainfall was 0.89, while monthly NSE was 0.59 for seven years with below annual average rainfall, indicating that SWATs predictive capabilities are less well-suited for drier conditions. Monthly average TWYLD for the high-flow winter to early spring season was underpredicted, while the low-flow late summer to autumn TWYLD was overpredicted. Results were negatively influenced when seasonal tropical storms occurred during a dry year. The most sensitive parameters for TWYLD were curve number for crop land (CN2(crop)), soil available water content (SOL_AWC), and soil evaporation compensation factor (ESCO). The most sensitive parameters for stormflow were CN2(crop), curve number for forested land (CN2(forest)), soil bulk density (SOL_BD), and SOL_AWC. The most sensitive parameters for baseflow were CN2(crop), CN2(forest), ESCO, and SOL_AWC. Identification of the sensitive SWAT parameters in the LREW provides modelers in the Coastal Plain physiographic region with focus for SWAT calibration.

Effect of Spatial Distribution of Rainfall on Temporal and Spatial Uncertainty of SWAT Output

Accurate rainfall data are critical for accurate representation of temporal and spatial uncertainties of simulated watershed-scale hydrology and water quality from models. In addition, the methods used to incorporate the rainfall data into the simulation model can significantly impact the results. The objectives of this study were to (1) assess the hydrologic impacts of different methods for incorporating spatially variable rainfall input into the Soil and Water Assessment Tool (SWAT) in conjunction with subwatershed delineation level and (2) assess seasonal and spatial uncertainty in hydrologic and water quality simulations of SWAT with respect to rain gauge density. The study uses three different methods to incorporate spatially variable rainfall into the SWAT model and three levels of subwatershed delineation. The impacts of ten different gauge-density scenarios on hydrology and water quality were subsequently evaluated by using the highest gauge-density scenario as a baseline for comparison. Through the centroid method, which is currently used by the AVSWAT-X interface, variations in the representation of measured annual rainfall as model input and corresponding simulated streamflow increased as subwatershed delineation level decreased from high-density to low-density. The rainfall input by the Thiessen averaging method for each subwatershed (Thiessen method) and the inverse-distance-weighted averaging method for the entire watershed (average method) were not sensitive to subwatershed delineation. The impacts of delineation on streamflow were also less with these two methods. The Thiessen method is recommended for SWAT simulation of a watershed with high spatial variability of rainfall. The currently used AVSWAT-X centroid method will also accurately represent spatially variable rainfall if a subwatershed delineation is used that sufficiently incorporates the density of observed rainfall stations. As the number of rain gauges used for the simulation decreased, the uncertainty in the hydrologic and water quality model output increased exponentially. Total phosphorus was most sensitive to the changes in rain gauge density, with an average coefficient of variation of root mean square difference (CVRMSD) of 0.30 from three watersheds, followed by sediment, total nitrogen, and streamflow, showing CVRMSD values of 0.24, 0.18, and 0.17, respectively. Seasonal variations in simulated streamflow and water quality were higher during summer and fall seasons compared to spring and winter seasons. These seasonal and temporal variations can be attributed to the rainfall patterns within the watershed.

SURFACE RUNOFF AND LATERAL SUBSURFACE FLOW AS A RESPONSE TO CONSERVATION TILLAGE AND SOIL-WATER CONDITIONS

Conservation tillage has significant potential as a water management tool for cotton production on sandy, drought-prone soils. Plant residue remaining at the soil surface from prior crops serves as a vapor barrier against water loss, reduces raindrop impact energy, slows surface runoff, and often increases infiltration. By increasing infiltration, the potential for greater plant-available water can be enhanced and irrigation requirements reduced. Five years of data were collected to quantify the hydrologic differences between strip till and conventional till production systems. Surface runoff and lateral subsurface flow were measured on six 0.2 ha plots in South Georgia in order to quantify the water-related effects of conservation tillage. Significant differences in surface and subsurface water losses were observed between the conventional and strip tilled plots. Surface runoff from the conventionally tilled plots exceeded that from the strip tilled plots, while subsurface losses were reversed. Surface runoff losses from the conventionally tilled plots exceeded those from the strip tilled plots by 81% (129 mm/year). Shallow lateral subsurface losses from the strip tilled plots exceeded those from the conventionally tilled plots by 73% (69 mm/year). Overall, a net annual gain of 60 mm of water was observed for the strip tilled plots.

Water quality effects of simulated conservation practice scenarios in the Little River Experimental watershed

The goal of this study was to evaluate the water quality effects of alternative conservation practice scenarios using the SWAT (Soil and Water Assessment Tool) model in the Little River Experimental watershed, a representative coastal plain watershed located in southern Georgia. We simulated the water quality effect of two suites of upland conservation practices (CPs)—one targeting erosion and the other targeting nutrients. We also simulated the impact of riparian forest buffers. Finally, we evaluated three different management scenarios for implementing the upland CPs: using a random approach, using subwatershed stream order as a prioritization criterion, and using subwatershed nonpoint source pollutant load as a prioritization criterion. The study showed that using subwatershed nonpoint source pollutant load as a prioritization criterion resulted in the most rapid water quality improvements. This improvement in water quality was nonlinear, while the other implementation schemes yield linear returns. Full implementation of the suite of CPs targeting erosion resulted in the greatest reductions of sediment (54.7%) and total phosphorus (55.9%) loads from upland crop areas. Full implementation of the suite of CPs targeting nutrient reduction resulted in the greatest total nitrogen load reduction (10.3%). Overall, an intact riparian forest buffer offered the most comprehensive reduction of nonpoint source pollutant loads—20.5% for sediment, 19.5% for total phosphorus, and 7.0% for total nitrogen. Simulation results indicate that at the current time, the single greatest contributor to nonpoint source pollutant reduction in the Little River Experimental watershed may be the current level of riparian forest cover.

Herbicide incorporation by irrigation and tillage impact on runoff loss.

Runoff from farm fields is a common source of herbicide residues in surface waters. Incorporation by irrigation has the potential to reduce herbicide runoff risks. To assess impacts, rainfall was simulated on plots located in a peanut (Arachis hypogaea L.) field in Georgias Atlantic Coastal Plain region after pre-emergence application of metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-[(1S)-2-methoxy-1-methylethyl]-acetamide) and pendimethalin (N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitro-benzenamine). Runoff, sediment, and herbicide loss as function of strip tillage (ST) versus conventional tillage (CT) were compared with and without irrigation (12.5 mm) after application of an herbicide tank mixture. For the CT system, metolachlor runoff was reduced 2x and pendimethalin 1.2x when compared with the non-irrigated treatment. The difference in irrigated and non-irrigated metolachlor means was significant (P = 0.05). Irrigation reduced metolachlor runoff by 1.3x in the ST system, but there was a 1.4x increase for pendimethalin. Overall results indicated that irrigation incorporation reduces herbicide runoff with the greatest impact when CT is practiced and products like metolachlor, which have relatively low K(oc) and high water solubility, are used. The lower ST system response was likely due to a combination of spray interception and retention by the ST system cover crop mulch and higher ST soil organic carbon content and less total runoff. During the study, the measured K(oc) of both herbicides on runoff sediment was found to vary with tillage and irrigation after herbicide application. Generally, K(oc) was higher for ST sediment and when irrigation incorporation was used with the CT system. These results have significant implications for simulation model parametization.

Satellite mapping of conservation tillage adoption in the Little River experimental watershed, Georgia

Conservation tillage is a commonly adopted best management practice for improving soil quality and reducing erosion. However, there are currently no methods in place to monitor conservation tillage adoption at the watershed scale. The primary objective of this study was to evaluate the usefulness of Landsat TM data as a tool to depict conservation tillage in a small Coastal Plain watershed. Satellite imagery was used to calculate four commonly used indices: Normalized Difference Vegetation Index, Crop Residue Cover Index, Normalized Difference Tillage Index, and the Simple Tillage Index. Ground truth data consisted of a windshield survey, assigning each site a tillage regime (conventional or conservation tillage) at 138 locations throughout the watershed and surrounding areas. A logistical regression approach was used on two subsets of the data set (n = 20 or n = 44) to determine the influence of the number of ground control points on the success of modeling the occurrence of conservation tillage. The most accurate model was re-applied to the satellite image and evaluated using an independent sample of 94 survey sites. Results indicate that the normalized difference tillage and simple tillage indices performed best, with an overall accuracy of 71% and 78% for models developed using n = 20 and n = 44 sample locations, respectively. Errors were typically in the form of commission. Results are encouraging and suggest that currently available satellite imagery can be used for rapid assessment of conservation tillage adoption using minimal a priori information.

Long-term stream chemistry trends in the southern Georgia Little River Experimental Watershed

Long-term stream water quality data may provide opportunities to study the effectiveness of conservation practices. The first three decades of data for the Little River in southwestern Georgia were analyzed for trends as part of the Conservation Effects Assessment Project. Concentrations and loads for chloride, ammonium-N, nitrate plus nitrite-N, total Kjeldahl N, total P, and dissolved molybdate reactive phosphorus were determined from 1974 through 2003 for eight nested subwatersheds in the Little River Experimental Watershed. There was a statistically significant downward trend for annual mean total phosphorus concentration in five subwatersheds and an upward trend for chloride in three subwatersheds. The decrease in total phosphorus concentration occurred primarily in winter. Trends in phosphorus and chloride concentrations did not appear to be related to land use. There were no statistical differences in annual streamflow or nutrient loads expressed on a per area basis among the nested subwatersheds. Annual and seasonal flow-weighted mean concentrations were different among the subwatersheds for nitrate-N and chloride. The larger subwatersheds had significantly higher nitrate-N in winter and spring. The nutrient loads and concentrations from these subwatersheds were an order of magnitude less compared to other agricultural watersheds. Conservation practices were implemented on 11% of the watershed area from 1980 to 2003; however, the affects of the practices on watershed water quality was not clear. Earlier short-term studies attributed the low levels of nutrient transport to the presence of extensive riparian forests and the general prevalence of forest in these mixed land use watersheds.

Tillage, cover-crop residue management, and irrigation incorporation impact on fomesafen runoff.

Intensive glyphosate use has contributed to the evolution and occurrence of glyphosate-resistant weeds that threaten production of many crops. Sustained use of this highly valued herbicide requires rotation and/or substitution of herbicides with different modes of action. Cotton growers have shown considerable interest in the protoporphyrinogen oxidase inhibitor, fomesafen. Following registration for cotton in 2008, use has increased rapidly. Environmental fate data in major use areas are needed to appropriately evaluate risks. Field-based rainfall simulation was used to evaluate fomesafen runoff potential with and without irrigation incorporation in a conventional tillage system (CT) and when conservation tillage (CsT) was practiced with and without cover crop residue rolling. Without irrigation incorporation, relatively high runoff, about 5% of applied, was measured from the CT system, indicating that this compound may present a runoff risk. Runoff was reduced by >50% when the herbicide was irrigation incorporated after application or when used with a CsT system. Data indicate that these practices should be implemented whenever possible to reduce fomesafen runoff risk. Results also raised concerns about leaching and potential groundwater contamination and crop injury due to rapid washoff from cover crop residues in CsT systems. Further work is needed to address these concerns.

Curve number estimates for conventional and conservation tillages in the southeastern Coastal Plain

The USDA Natural Resource Conservation Service curve number (CN) method for estimating surface runoff is frequently used in natural resource modeling. Water yield and subsequently water quality estimates depend heavily on CN selection. This study was conducted to estimate CNs for a cotton-peanut rotation under conventional and strip tillage (ST) methods for growing and dormant seasons. A comparison between alternative methods for calculating CN and their applicability was also made. Rainfall-runoff data measured from 1999 to 2005 at a field study site in South Georgia were used to calculate CNs by averaging, lognormal, and data-censoring methods. For conventional and STs, CNs by the averaging method using year-round data were 89 and 84, respectively, and by the lognormal method were 89 and 83, respectively. Results from the data-censoring method were 81 and 75, respectively, which matched standard table values developed from a long-term series of annual maximum runoff. Values were also found to vary by season. Curve numbers by the lognormal method for ST were 83 and 88 for growing and dormant seasons, respectively; however, there was no difference between growing and dormant seasons, 89, for conventional tillage. The corresponding CNs by the data-censoring method for ST were 71 and 79 for growing and dormant seasons, respectively, and for conventional tillage were 82 and 79 for growing and dormant seasons, respectively. Based upon errors of the estimates, runoff estimates showed no improvement when separate CNs for the two seasons were used. The data-censoring method CNs yielded lower runoff estimate errors than CNs obtained by the lognormal method. The data-censoring method is recommended for determining CNs from plot rainfall-runoff data pairs.

Pressurized liquid extraction of soil microbial phospholipid and neutral lipid fatty acids.

Soil microbial lipid biomarkers are indicators of viable microbial biomass and community structure. Pressurized liquid extraction (PLE) of soil phospholipid fatty acids (PLFA) and neutral lipid fatty acids (NLFA) was compared to a conventional extraction method in four soils with differing physical and chemical properties. PLE efficiency was greater than that of the conventional method for about half of the saturated PLFA and for selected other Gram-positive (i16:0) and Gram-negative bacteria (18:1omega7c) PLFA, fungal PLFA (18:2omega6,9c), and eukaryotic NLFA from a coarse-textured soil. Lipids extracted by the two methods did not indicate a significant difference in microbial community structure data. Principle component analysis revealed that PLFA clustered by location, with data indicating that the group of microbes contributing the greatest weight differed among soils. Overall, the PLE method proved to be more efficient at extracting soilborne microbial lipids while not altering microbial community information. These advantages indicate the PLE method is robust and well-suited to soil microbial ecology research.