The Agricultural Nonpoint Source Pollution Model (AGNPS) was applied to estimate the loads of nitrogen and phosphorus according to antecedent soil moisture conditions (AMC) using probable rainfall in a stream draining small agricultural watersheds. Calibration and verification of the model were performed using observed data collected from rainfall events in the Imgo watersheds during 1997-1998. Evaluation of model outputs was based on graphical displays contrasting observed and simulated values for each rainfall-runoff event, and standard statistics such as coefficient of efficiency. The coefficient of efficiency of peak flow, total N, and total P in the estimation were 0.97, 0.93, and 0.74, respectively. Probable rainfall of Imgo watersheds was computed for several return periods using the frequency analysis of Gumbel's extreme value distribution. As the probable flood increase, concentrations of total N and total P generally decrease. Loss of N and P was proportional to the preceding soil water content in the same probable rainfall. The excessive fertilization under AMC-III condition can cause relatively higher outflow of N and P from the soil. It can be concluded that surface runoff and sediment transport influence soil quality and the quality of water absorption and AGNPS can provide realistic estimates of nonpoint source nutrient yields.
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http://dx.doi.org/10.1081/ese-120037881 | DOI Listing |
PLoS One
January 2025
UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom.
Surface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data.
View Article and Find Full Text PDFJ Contam Hydrol
January 2025
USDA ARS, National Soil Erosion Research Laboratory, West Lafayette, IN 47907, United States of America.
Agricultural phosphorus (P) losses may result from either recently applied fertilizers or from P accumulated in soil and sediment. While both P sources pose an environmental risk to freshwater systems, differentiating between sources is crucial for identifying and implementing management practices to decrease loss. In this study, laboratory rainfall simulations were completed on runoff boxes and undisturbed soil columns before and after fertilizer application.
View Article and Find Full Text PDFJ Paediatr Child Health
January 2025
Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
Aim: Angiostrongylus cantonensis, the leading cause of eosinophilic meningoencephalitis, is well established in eastern Australia. Prolonged wet weather in Queensland during 2021-2022 coincided with anecdotal reports of increased neuroangiostrongyliasis cases, prompting an evaluation of paediatric cases from 2013 to 2022.
Methods: This retrospective observational study reviewed children (0-16 years) with cerebrospinal fluid (CSF) eosinophilia (≥ 10% of the total CSF leukocyte count) and/or A.
PLoS Negl Trop Dis
January 2025
Institute of Exact and Applied Sciences, University of New Caledonia, Nouméa, Province Sud, New Caledonia.
Background: Leptospirosis is a neglected zoonotic disease prevalent worldwide, particularly in tropical regions experiencing frequent rainfall and severe cyclones, which are further aggravated by climate change. This bacterial zoonosis, caused by the Leptospira genus, can be transmitted through contaminated water and soil. The Pacific islands bear a high burden of leptospirosis, making it crucial to identify key factors influencing its distribution.
View Article and Find Full Text PDFSci Total Environ
January 2025
Institute of Estuarine and Coastal Research, School of Marine Engineering and Technology, Sun Yat-sen University, Guangzhou 510275, China. Electronic address:
With climate change and intensified human activities, disasters such as heavy rainfall, flooding, typhoons, and storm surges are becoming more frequent, posing significant threats to lives, property, and economic development. We propose a method combining extreme value theory and probability distribution to examine the flood severity under the effect of strong human activities. By focusing on the Pearl River Delta (PRD), as one of the most populated areas of China, we quantified changes in the severity of extreme water level for different return levels between 1966 and 1990 and 1991-2016 (with strong human activities), associated with the spatial patterns over the PRD.
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