Journal of Environmental Sciences Juniper Publishers

  Abstract The objective of this paper is to determine the impact of wetlands on the characteristics (magnitude, frequency, duration, timing and variability flow) of daily maximum and minimum extreme flows in summer-fall season (July to November) over the 1945-2019 period in Petite Nation watershed. Three relatively close watersheds [Matawin River (1,390km²), Petite Nation River (1,330km²) and L’Assomption River (1,340km²)], which are differentiated mainly by the types of land use (wetland and agricultural areas), were studied. In the Petite Nation River watershed, which has the largest wetland surface area (15%), the frequency of flood occurrence significantly decreased, resulting in a decrease in the magnitude and duration of seasonally daily maximum flows and their early occurrence during the season. In contrast, the interannual rate change flow in the timing and duration of these flows is greater than that observed in the other two watersheds. The “sponge effect”

  Abstract As the water issue relates the carbon issue in peatland, carbon and water interrelation has been studying for long term (more than 10 years) in peatland of Central Kalimantan, Indonesia. The Soil Moisture Content (SMC) and Ground Water Table (GWT) in long term have been monitoring by auto-monitoring system called SESAME, developed by our team, and Net Ecosystem Exchange (NEE) has been measured by Eddy Covariance on the tower. By these long-term monitoring, it is found that a) positive correlation with SMC and GWT, b) negative correlation with NEE and GWT. On the other hand, as global soil moisture data has been provided daily from European Center for Medium-Range Weather Forecasts (ECMWF), we developed mapping model on GWT and NEE, applying correlation coefficient of SMC-GWT and NEE-GWT. The NEE mapping in peatland corresponds with Tier 2 and 3 level of Intergovernmental Panel on Climate Change (IPCC) guideline.    Read More about this Article: https:/

  Abstract Mapping and monitoring of forest area suffering from deforestation and forest degradation using satellite images and remote sensing has been an achievable activity for the sustainable forest management and conservation. Mapping of disturbance and degradation of forest is gaining momentum through Remote Sensing despite, major challenges still exist. The present study was conducted to quantify the forest area of deforestation and degradation within the Maya Devi collaborative forest of Terai region located at Kapilvastu district of Nepal. This study based on the optical satellite data (Landsat 7 ETM of 2000 and Landsat 8 OLI/TIRS of 2016) and spectral un-mixing of these datasets which produced fractional cover (proportion of vegetation, non-photosynthetic vegetation and bare soil). Under the environment of CLASlite tools, mapping of damaged canopy, exposed soil and dead vegetation were produced. With the gap of 15 years two Landsat Image of 2000 and 2016 were p