Current Issue : October - December Volume : 2012 Issue Number : 4 Articles : 4 Articles
A study evaluated corn (Zea mays L.) hybrids (Asgrow785, DKC61-73, DKC63-42, LG2642, and Kruger2114) and water\r\nmanagement systems (nondrained, nonirrigated (NDNI); drained, nonirrigated (DNI) with subsurface drain tiles 6.1 and 12.2m\r\napart; drained plus subirrigated (DSI) with tiles 6.1 and 12.2m apart; nondrained, overhead irrigated (NDOHI)) on yields, plant\r\npopulation, and grain quality from2008 to 2010. Precipitation during this study was 36 to 283mmabove the past decade. Planting\r\ndate was delayed 18 d in the nondrained control in 2009, and additional delayed planting controls were included this year. Grain\r\nyields were similar in the 6.1- and 12.2 m-spaced DNI and DSI systems in 2008 and 2010, but plant population increased 74% and\r\nyields were 3.1Mg ha-1 greater with DSI at a 6.1m spacing compared to 12.2m in 2009. At a 6.1m spacing, DNI or DSI increased\r\nyield 1.1 to 6.6Mg ha-1 (10 to over 50%) compared to NDNI or NDOHI soil. High yielding hybrids achieved similar yields with\r\nDNI, while NDNI DKC63-42 had 1.2Mg ha-1 greater yields compared to DKC61-73. A 6.1m spacing for DNI claypan soils is\r\nrecommended for high yielding corn production....
Simultaneous measurements of soil moisture profiles and water table heads, along a flow path, were used to determine evapotranspiration\r\n(ET) along with other components of the water budget. The study was conducted at a small-scale (~0.8Km2) hydrologic\r\nmonitoring field site in Hillsborough County, Florida, from January 2002 to June 2004. Frequency Domain Reflectometry soil\r\nmoisture probes, installed in close proximity to water table monitoring wells were used to derive changes in the soil water storage.\r\nA one-dimensional transect model was developed; changes in the soil water storage and water table observations served as input to\r\ndetermine all vertical and lateral boundary fluxes along the shallow water table flow plane. Two distinct land cover environments,\r\ngrassland and an alluvial wetland forest, were investigated in this particular study. The analysis provided temporally variable ET\r\nestimates for the two land covers with annual totals averaging 850mm for grassland, to 1100mm for the alluvial wetland forest.\r\nQuantitative estimates of other components of a water budget, for example, infiltration, interception capture, total rainfall excess,\r\nand runoff were also made on a quarterly and annual basis. Novelty of this approach includes ability to resolve ET components\r\nand other water budget fluxes that provide useful parameterization and calibration potential for predictive simulation models...
Monitoring of progress towards the Millennium Development Goal (MDG)\r\ndrinking water target relies on classification of water sources as ââ?¬Å?improvedââ?¬Â or\r\nââ?¬Å?unimprovedââ?¬Â as an indicator for water safety. We adjust the current Joint Monitoring\r\nProgramme (JMP) estimate by accounting for microbial water quality and sanitary risk\r\nusing the only-nationally representative water quality data currently available, that from\r\nthe WHO and UNICEF ââ?¬Å?Rapid Assessment of Drinking Water Qualityââ?¬Â. A principal\r\ncomponents analysis (PCA) of national environmental and development indicators was\r\nused to create models that predicted, for most countries, the proportions of piped and of\r\nother-improved water supplies that are faecally contaminated; and of these sources, the\r\nproportions that lack basic sanitary protection against contamination. We estimate that\r\n1.8 billion people (28% of the global population) used unsafe water in 2010. The 2010\r\nJMP estimate is that 783 million people (11%) use unimproved sources. Our estimates\r\nrevise the 1990 baseline from 23% to 37%, and the target from 12% to 18%, resulting in a\r\nshortfall of 10% of the global population towards the MDG target in 2010. In contrast,\r\nusing the indicator ââ?¬Å?use of an improved sourceââ?¬Â suggests that the MDG target for drinkingwater\r\nhas already been achieved. We estimate that an additional 1.2 billion (18%) use\r\nwater from sources or systems with significant sanitary risks. While our estimate is\r\nimprecise, the magnitude of the estimate and the health and development implications\r\nsuggest that greater attention is needed to better understand and manage drinking\r\nwater safety....
Jakara River, northwestern, Nigeria has been found to be polluted by\r\nvarious sources of pollution associated with excessive land use. This study attempted\r\nto identify the sources of pollution in the Jakara Basin using principal component\r\nanalysis and factor analysis (PCA/FA). Four different sampling points were designed\r\nalong Jakara River and surface water samples were collected for sixty days. Fifteen\r\nphysico-chemical parameters were analyzed which includes: water temperature,\r\nturbidity, salinity, conductivity, pH, nitrates (NO3-), ammonia-nitrate (NH3-NL), total\r\nsolids (TS), suspended solids (SS), dissolved solids (DS), 5-day biochemical oxygen\r\ndemand (BOD5), chemical oxygen demand (COD), dissolved oxygen (DO),\r\nphosphates (PO43-), and chloride (Cl). PCA/FA extracted five principal components\r\n(PCs) explaining 70.7% of the total variance of the raw data. PCA/FA showed that\r\nJakara River is influenced mostly by organic and nutrients (anthropogenic) pollution\r\nfrom domestic wastewater and little contribution from geology of the area, erosion\r\nand farmland run-off. These results provide fundamental information for the\r\nauthorities to take sound action for developing better water pollution control and\r\neffective management of river water quality in the area....
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