Detecting seasonal and cyclical trends in agricultural runoff water quality-hypothesis tests and block bootstrap power analysis.

Seasonal and cyclic trends in nutrient concentrations at four agricultural drainage ditches were assessed using a dataset generated from a multivariate, multiscale, multiyear water quality monitoring effort in the agriculturally dominant Lower Rio Grande Valley (LRGV) River Watershed in South Texas. An innovative bootstrap sampling-based power analysis procedure was developed to evaluate the ability of Mann-Whitney and Noether tests to discern trends and to guide future monitoring efforts. The Mann-Whitney U test was able to detect significant changes between summer and winter nutrient concentrations at sites with lower depths and unimpeded flows. Pollutant dilution, non-agricultural loadings, and in-channel flow structures (weirs) masked the effects of seasonality. The detection of cyclical trends using the Noether test was highest in the presence of vegetation mainly for total phosphorus and oxidized nitrogen (nitrite + nitrate) compared to dissolved phosphorus and reduced nitrogen (total Kjeldahl nitrogen-TKN). Prospective power analysis indicated that while increased monitoring can lead to higher statistical power, the effect size (i.e., the total number of trend sequences within a time-series) had a greater influence on the Noether test. Both Mann-Whitney and Noether tests provide complementary information on seasonal and cyclic behavior of pollutant concentrations and are affected by different processes. The results from these statistical tests when evaluated in the context of flow, vegetation, and in-channel hydraulic alterations can help guide future data collection and monitoring efforts. The study highlights the need for long-term monitoring of agricultural drainage ditches to properly discern seasonal and cyclical trends.

Assessing an intermittently operated household scale slow sand filter paired with household bleach for the removal of endocrine disrupting compounds.

Endocrine disrupting compounds (EDCs) are a contaminant of emerging concern throughout the world, including developing countries where centralized water and wastewater treatment plants are not common. In developing countries, household scale water treatment technologies such as the biosand filter (BSF) are used to improve drinking water quality. No studies currently exist on the ability of the BSF to remove EDCs. In this experiment, the BSF was evaluated for the removal of three EDCs, estrone (E1), estriol (E3), and 17α-ethinyl estradiol (EE2). Removal results were compared to the slow sand filter (SSF) from the literature, which is similar to the BSF in principal but comparisons have revealed differences in removal of other water quality parameters between SSF and BSF. In general, the BSF minimally removed the compounds from spiked lake water as removal was less than 15% for all three compounds, though mass removal much higher than other studies in which the SSF was used. Household bleach was added to the rate was BSF effluent as suggested in order to achieve different Cl- concentrations (0.67, 2.0, 5.0, and 10.0 mg/L) and subsequent removal of EDCs by oxidation was examined. Concentrations were reduced > 98% for all compounds when the Cl- concentration was greater than 5 mg/L. Removal efficiency was > 50% at the 0.67 mg/L Cl- concentration, while almost 70% removal was observed for all compounds at the 2.0 mg/L Cl- concentration.

Vulnerability assessment of agricultural production systems to drought stresses using robustness measures.

Intensification of droughts in agricultural areas threaten global food security. The impacts of drought stresses vary widely across a region, not only due to climate variability but also due to heterogeneous soil and groundwater buffering capacities which protect against droughts. An innovative drought vulnerability index was developed by reconciling the negative effects of drought stresses against the robustness offered by hydrologic buffers. Indicators for climate stresses, soil and groundwater buffering capacities were defined using physical principles and integrated using a multi-criteria decision making (MCDM) framework. The framework was applied to delineate drought vulnerability of agricultural production systems and evaluate current cropping choices across the High Plains region of the US that is underlain by the Ogallala Aquifer. Current crop growth choices appeared to be compatible with the intrinsic drought vulnerabilities with cotton and sorghum grown in higher vulnerability areas and corn and soybean produced in areas with lower vulnerability. Nearly 50% of the aquifer region fell in the transition zone exhibiting medium to high vulnerabilities warranting the need for better water management to adapt to a changing climate.