Papua New Guinea is blessed with a plethora of enviable natural resources, but at the same time it is also cursed by quite a few natural disasters like volcanic eruptions, earthquakes, landslide, floods, droughts etc. Floods happen to be a natural process of maintaining the health of the rivers and depth of its thalweg; it saves the river from becoming morbid while toning up the fertility of the riverine landscape. At the same time, from human perspective, all these ecological goodies are nullified when flood is construed overwhelmingly as one of the most devastating events in respect to social and economic consequences. The present investigation was tailored to assess the use of multi-criteria decision approach (MCDA) in inland flood risk analysis. Categorization of possible flood risk zones was accomplished using geospatial data sets, like elevation, slope, distance to river, and land use/land cover, which were derived from digital elevation model (DEM) and satellite image, respectively. A pilot study area was selected in the lower part of Markham River in Morobe Province, Papua New Guinea. The study area is bounded by 146˝31 1 to 146˝58 1 east and 6˝33 1 to 6˝46 1 south; covers an area of 758.30 km 2 . The validation of a flood hazard risk map was carried out using past flood records in the study area. This result suggests that MCDA within GIS techniques is very useful in accurate and reliable flood risk analysis and mapping. This approach is convenient for the assessment of flood in any region, specifically in no-data regions, and can be useful for researchers and planners in flood mitigation strategies.

This research established an empirical methodology to estimate potential soil erosion rate based on revised universal soil loss equation (RUSLE) and E 30 model. The study was conducted on a highly precipitated, rugged, tropical forested with steep slope watershed during 1992 to 2009. The fourth (4th) largest river of Papua New Guinea, and its catchment area was considered for this research. Lots of commercial mining and logging activities are the ongoing processes in the upper catchment area without proper conservation measures. Digital elevation model (DEM), landsat satellite images, average annual rainfall, soil texture data base were used to derived mandatory input factors into the RUSLE and E 30 model. Raster calculator of ArcGIS spatial analyst was used to generate all input factors and final pixel-by-pixel based computation of soil loss pattern. The average potential soil erosion rate were calculated in the range of 20.34 mm/year to 23.70 mm/year through RSULE model and in the other hand the rate varies from 21.07 mm/year to 26.78 mm/year through E 30 model during 1992 to 2009 respectively. The erosion rate through both model indicates extremely severe rate of erosion in the upper catchment area are required immediate attention of soil conservation practices.

This research drew from social learning and international development literature. The purpose of this community research was to trace the spread and impact of sweetpotato flour in two rural communities in Papua New Guinea. Research strategy was participatory learning and action utilizing participatory mapping. The paper mapping process was documented using a video recorder and field notes. Geographic Information Systems technology was then used to incorporate local spatial knowledge on scale maps to show spread of knowledge. The main finding was the identification of social networks through tracking of sweetpotato knowledge: identifying who used the knowledge and whether there were any modifications, the location of those who used the knowledge and whether this was shared and with whom. Most significant was the enabling factors that strengthened existing and potential future networks. Community leadership styles determine success of development projects. Rural communities are diverse needing participatory multi-layered methodologies that are people oriented for agricultural technologies to be learnt and utilized for improved livelihood.