Environmental Engineering
G.R. Puno; R.A. Marin; R.C.C. Puno; A.G. Toledo-Bruno
Abstract
BACKGROUND AND OBJECTIVES: The study explored the capability of the geographic information system interface for the water erosion prediction project, a process-based model, to predict and visualize the specific location of soil erosion and sediment yield from the agricultural watershed of Taganibong.METHODS: ...
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BACKGROUND AND OBJECTIVES: The study explored the capability of the geographic information system interface for the water erosion prediction project, a process-based model, to predict and visualize the specific location of soil erosion and sediment yield from the agricultural watershed of Taganibong.METHODS: The method involved the preparation of the four input files corresponding to climate, slope, land management, and soil properties. Climate file processing was through the use of a breakpoint climate data generator. The team had calibrated and validated the model using the observed data from the three monitoring sites.FINDINGS: Model evaluation showed a statistically acceptable performance with coefficient of determination values of 0.64 (probability value = 0.042), 0.85 (probability value = 0.000), and 0.69 (probability value = 0.001) at 95% level, for monitoring sites 1, 2, and 3, respectively. A further test revealed a statistically satisfactory model performance with root mean square error-observations standard deviation ratio, Nash-Sutcliffe efficiency, and percent bias of 0.62, 0.61, and 44.30, respectively, for monitoring site 1; 0.65, 0.56, and 25.60, respectively, for monitoring site 2; and 0.60, 0.65, and 27.90, respectively, for monitoring site 3. At a watershed scale, the model predicted the erosion and sediment yield at 89 tons per hectare per year and 22 tons per hectare per year, respectively, which are far beyond the erosion tolerance of 10 tons per hectare per year. The sediment delivery ratio of 0.20 accounts for a total of 126,390 tons of sediments that accumulated downstream in a year.CONCLUSION: The model generated maps that visualize a site-specific hillslope, which is the source of erosion and sedimentation. The study enables the researchers to provide information helpful in the formulation of a sound policy statement for sustainable soil management in the agricultural watershed of Taganibong.
Environmental Management
C.E. Akumu; J. Henry; T. Gala; S. Dennis; C. Reddy; F. Tegegne; S. Haile; R.S. Archer
Abstract
The understanding of inland wetlands’ distribution and their level of vulnerability is important to enhance management and conservation efforts. The aim of the study was to map inland wetlands and assess their distribution pattern and vulnerability to natural and human disturbances such as climate ...
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The understanding of inland wetlands’ distribution and their level of vulnerability is important to enhance management and conservation efforts. The aim of the study was to map inland wetlands and assess their distribution pattern and vulnerability to natural and human disturbances such as climate change (temperature increase) and human activities by the year 2080. Inland wetland types i.e. forested/shrub, emergent and open water bodies were classified and mapped using maximum likelihood standard algorithm. The spatial distribution pattern of inland wetlands was examined using average nearest neighbor analysis. A weighted geospatial vulnerability analysis was developed using variables such as roads, land cover/ land use (developed and agricultural areas) and climate data (temperature) to predict potentially vulnerable inland wetland types. Inland wetlands were successfully classified and mapped with overall accuracy of about 73 percent. Clustered spatial distribution pattern was found among all inland wetland types with varied degree of clustering. The study found about 13 percent of open water bodies, 11 percent of forested/shrub and 7 percent of emergent wetlands potentially most vulnerable to human and natural stressors. This information could be used to improve wetland planning and management by wetland managers and other stakeholders.
