MASS LOAD ESTIMATION ERRORS UTILIZING GRAB SAMPLING STRATEGIES IN A KARST WATERSHED¹

Abstract

Developing a mass load estimation method appropriate for a given stream and constituent is difficult due to inconsistencies in hydrologic and constituent characteristics. The difficulty may be increased in flashy flow conditions such as karst. Many projects undertaken are constrained by budget and manpower and do not have the luxury of sophisticated sampling strategies. The objectives of this study were to: (1) examine two grab sampling strategies with varying sampling intervals and determine the error in mass load estimates, and (2) determine the error that can be expected when a grab sample is collected at a time of day when the diurnal variation is most divergent from the daily mean. Results show grab sampling with continuous flow to be a viable data collection method for estimating mass load in the study watershed. Comparing weekly, biweekly, and monthly grab sampling, monthly sampling produces the best results with this method. However, the time of day the sample is collected is important. Failure to account for diurnal variability when collecting a grab sample may produce unacceptable error in mass load estimates. The best time to collect a sample is when the diurnal cycle is nearest the daily mean.

Long‐term assessment of nutrient flow pathway dynamics and in‐stream fate in a temperate karst agroecosystem watershed

“…Tobacco received both N and P inorganic fertilizer sources whereas the other row crops (e.g., maize) were side‐dressed with inorganic N. Surrounding landscapes were predominantly horse pasture with some sparse residential development. The streams at the ARC are shallow, flow over limestone bedrock with limited sediment deposits, and are generally unshaded with some riparian vegetation (Fogle et al, ). Sediment storage in the streambed is low with most of the bedrock exposed.…”

“…Regarding in‐stream fate, agroecosystem streambeds often consist of exposed bedrock or thin surficial sediment deposits starkly contrasting the deep alluvial beds found in systems with predominant hyporheic zones (Fogle, Taraba, & Dinger, ; Ford & Fox, ; Husic, Fox, Agouridis, et al, ; Mellander et al, ). Recent studies have highlighted the impact of the surficial fine‐grained laminae, in both surface and phreatic conduit streambeds, on nutrient attenuation and transient storage (Ford & Fox, , ; Ford, Fox, & Pollock, ; Husic, Fox, Ford, et al, ; Husic, Fox, Agouridis, et al, ).…”

Using High‐Resolution Data to Assess Land Use Impact on Nitrate Dynamics in East African Tropical Montane Catchments

“…In the case of NO 3 -N, such high-frequency data have been used in temperate regions to improve load estimates (Ferrant et al, 2013;Fogle et al, 2003;Pellerin et al, 2014;Rozemeijer et al, 2010), to identify NO 3 -N 2,932 m on top of the Mau Escarpment to 1,715 m at the outlet. The landscape is characterized by three main land use types: natural forest (NF), smallholder agriculture (SHA) and commercial tea and tree plantations (TTP).…”

Reach-Scale Model of Aquatic Vegetation Quantifies N Fate in a Bedrock-Controlled Karst Agroecosystem Stream

“…The Camden Creek watershed (drainage area of 10.69 km 2 ; Figure 2) is characterized by broad, shallow sinkholes, low relief, broad valleys and ridges, sparse rock outcrops, and thick, fertile, limestone and shale residual soils over phosphatic Ordovician limestone [55]. Camden Creek and surface tributaries in the watershed are shallow, emanate from springs, flow over limestone bedrock, and are generally unshaded through grazed pasture with some riparian vegetation [56], with low streambed sediment storage on exposed bedrock [11]. As a result of spatial variability in land use, nutrient concentrations varied across spring inputs to the stream channel.…”