RESERVOIR WATER QUALITY SAMPLING DESIGN1

ABSTRACT: The design of monitoring programs often serves as one of the major sources of error or uncertainty in water quality data. Properly designed programs should minimize uncertainty or at least provide a means by which variability can be partitioned into recognizable components. While the design of sampling programs has received recent attention, commonly employed strategies for limnological sampling of lakes may not be completely appropriate for many reservoirs. Based on NES data, reservoirs are generally larger, deeper, and morphologically more complex than natural lakes. Reservoirs also receive a majority of their inflow from a single tributary located a considerable distance from the point of outflow. The result is the establishment of marked physical, biological, and chemical gradients from headwater to dam. The existence of horizontal as well as vertical gradients, and their importance in water quality sampling design were the subject of intensive transect sampling efforts at DeGray Lake, a U.S. Army Corps of Engineers reservoir in southern Arkansas. Data collected were used to partition Variance, identify areas of similarity, and demonstrate how an equitable sampling program might be designed.     

Effect of the C:N:P ratio on the denitrifying dephosphatation in a sequencing batch biofilm reactor (SBBR)

A series of investigations were conducted using sequencing batch biofilm reactor(SBBR) to explore the influence of C:N:P ratio on biological dephosphatation including the denitrifying dephosphatation and the denitrification process.Biomass in the reactor occurred mainly in the form of a biofilm attached to completely submerged disks.Acetic acid was used as the source of organic carbon.C:N:P ratios have had a significant effect on the profiles of phosphate release and phosphate uptake and nitrogen removal.The highest rates of phosphate release and phosphate uptake were recorded at the C:N:P ratio of 140:70:7.The C:N ratio of 2.5:1 ensured complete denitrification.The highest rate of denitrification was achieved at the C:N:P ratio of 140:35:7.The increase of nitrogen load caused an increase in phosphates removal until a ratio C:N:P of 140:140:7.Bacteria of the biofilm exposed to alternate conditions of mixing and aeration exhibited enhanced intracellular accumulation of polyphosphates.Also,the structure of the biofilm encouraged anaerobic–aerobic as well as anoxic–anaerobic and absolutely anaerobic conditions in a SBBR.These heterogeneous conditions in the presence of nitrates may be a significant factor determining the promotion of denitrifying polyphosphate accumulating organism(DNPAO) development.     

DAYCENT national-scale simulations of nitrous oxide emissions from cropped soils in the United States

Until recently, Intergovernmental Panel on Climate Change (IPCC) emission factor methodology, based on simple empirical relationships, has been used to estimate carbon (C) and nitrogen (N) fluxes for regional and national inventories. However, the 2005 USEPA greenhouse gas inventory includes estimates of N2O emissions from cultivated soils derived from simulations using DAYCENT, a process-based biogeochemical model. DAYCENT simulated major U.S. crops at county-level resolution and IPCC emission factor methodology was used to estimate emissions for the approximately 14% of cropped land not simulated by DAYCENT. The methodology used to combine DAYCENT simulations and IPCC methodology to estimate direct and indirect N2O emissions is described in detail. Nitrous oxide emissions from simulations of presettlement native vegetation were subtracted from cropped soil N2O to isolate anthropogenic emissions. Meteorological data required to drive DAYCENT were acquired from DAYMET, an algorithm that uses weather station data and accounts for topography to predict daily temperature and precipitation at 1-km2 resolution. Soils data were acquired from the State Soil Geographic Database (STATSGO). Weather data and dominant soil texture class that lie closest to the geographical center of the largest cluster of cropped land in each county were used to drive DAYCENT. Land management information was implemented at the agricultural-economic region level, as defined by the Agricultural Sector Model. Maps of model-simulated county-level crop yields were compared with yields estimated by the USDA for quality control. Combining results from DAYCENT simulations of major crops and IPCC methodology for remaining cropland yielded estimates of approximately 109 and approximately 70 Tg CO2 equivalents for direct and indirect, respectively, mean annual anthropogenic N2O emissions for 1990-2003.     

Resilience and adaptation to extremes in a changing Himalayan environment

Human communities inhabiting remote and geomorphically fragile high-altitude regions are particularly vulnerable to climate change-related glacial hazards and hydrometeorological extremes. This study presents a strategy for enhancing adaptation and resilience of communities living immediately downstream of two potentially hazardous glacial lakes in the Upper Chenab Basin of the Western Himalaya in India. It uses an interdisciplinary investigative framework, involving ground surveys, participatory mapping, comparison of local perceptions of environmental change and hazards with scientific data, identification of assets and livelihood resources at risk, assessment of existing community-level adaptive capacity and resilience and a brief review of governance issues. In addition to recommending specific actions for securing lives and livelihoods in the study area, the study demonstrates the crucial role of regional ground-level, community-centric assessments in evolving an integrated approach to disaster risk reduction and climate change adaptation for high-altitude environments, particularly in the developing world.