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We examined total Kjeldahl nitrogen (TKN) loading to a small forested stream during storm events. We hypothesized that upper soil and litter layers in riparian area are primary source of higher TKN concentrations during storm. A storm water sampling program was carried out to gather requisite flow and water quality data to calibrate and validate water and nutrient components of the Riparian Ecosystem Management Model for TKN. Water quality and storm flow data collected from January 2000 to December 2003 were used to simulate the hydrology and nitrogen transport over a second-order watershed within the Fort Benning Military Installation, Georgia. Intensive sampling conducted from October 2002 to May 2003 provided the necessary data to characterize the rising limb, peak, and recession limb of six major storm events. Simulated runoff and storm TKN loads were compared with their corresponding observed or calculated values. Hydrology and nitrogen data collected from February 21, 2003 to December 31, 2003 were used for the model validation. The hydrology component of the model showed a Nash-Sutcliffe efficiency of 87% for the validation period. The average absolute difference between simulated and calculated TKN loads was 25%. Even though the monthly water budget indicated the dominance of subsurface flow, TKN contribution from direct runoff was significantly greater than that from subsurface flow. On an average, 73% of the observed total TKN load at the watershed outlet was contributed by surface runoff during storm events. The results suggested that the surface runoff during the storm events washed off the nitrogen from the forest floor and transported to the stream.

In order to investigate the effects of canopy-dependent processes on throughfall chemistry, comparative studies on the chemical composition of throughfall were carried out in five characteristic forest types of the southeastern United States within Fort Benning Military Installation from January 2002 to August 2003. The concentrations and fluxes of and total organic carbon (TOC), total Kjeldahl nitrogen (TKN), and total phosphorus (TP) were determined in rainfall and throughfall. Seasonal variations in chemical fluxes were also evaluated. Throughfall concentrations of TOC, TKN, and TP in matured pine stand were higher than in rainfall and other forest stands. Throughfall nutrient concentrations in wetland were lowest as compared to rainfall as well as hardwood, mixed, plantation, and pine stands. The average TOC, TKN, and TP concentrations in the matured pine stand were 17.2, 0.74, and 0.057 mg/L, respectively. In wetland stands, average concentrations of TOC, TKN, and TP were 4.0, 0.54, and 0.034 mg/L, respectively. Hardwood stand had the lowest TKN concentration of 0.53 mg/L. Nutrient fluxes were generally higher during the dormant season (November-April) as compared to the growing season (May-October). The highest and lowest TOC fluxes during dormant season were contributed from pine stand (801.7 g/ha) and wetland stand (186.2 g/ha), respectively. Rainfall was the major contributor of TKN fluxes in growing season (32.3 g/ha) as well as in dormant season (34.1 g/ha). Similarly, highest TP flux was produced in mixed stand (2.7 g/ha) during the dormant season. Enrichment ratios of nutrients reveal that, in general, forest stands used up nutrients during growing season and washed off during the dormant season.

A geostatistical method was applied to optimize an existing groundwater-level monitoring network in the Upper Floridan aquifer for the South Florida Water Management District in the southeastern United States. Analyses were performed to determine suitable numbers and locations of monitoring wells that will provide equivalent or better quality groundwater-level data compared to an existing monitoring network. Ambient, unadjusted groundwater heads were expressed as salinity-adjusted heads based on the density of freshwater, well screen elevations, and temperature-dependent saline groundwater density. The optimization of the numbers and locations of monitoring wells is based on a pre-defined groundwater-level prediction error. The newly developed network combines an existing network with the addition of new wells that will result in a spatial distribution of groundwater monitoring wells that better defines the regional potentiometric surface of the Upper Floridan aquifer in the study area. The network yields groundwater-level predictions that differ significantly from those produced using the existing network. The newly designed network will reduce the mean prediction standard error by 43% compared to the existing network. The adoption of a hexagonal grid network for the South Florida Water Management District is recommended to achieve both a uniform level of information about groundwater levels and the minimum required accuracy. It is customary to install more monitoring wells for observing groundwater levels and groundwater quality as groundwater development progresses. However, budget constraints often force water managers to implement cost-effective monitoring networks. In this regard, this study provides guidelines to water managers concerned with groundwater planning and monitoring.