Ireland’s Rural Environment: Research Highlights from Johnstown Castle

ReportThis booklet gives a flavour of the current research in Teagasc Johnstown Castle Research Centre and introduces you to the staff involved. It covers the areas of Nutrient Efficiency, Gaseous emissions, Agricultural Ecology, Soils and Water quality

Assessment Erosion 3D Hazard with USLE and Surfer Tool: a Case Study of Sumani Watershed in West Sumatra Indonesia

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia.  The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed.  Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%).  Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated  as having very less to moderate.  On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah.  The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81

Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia.  The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed.  Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%).  Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated  as having very less to moderate.  On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah.  The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81

Water quality modeling using geographic information system (GIS) data

Protection of the environment and natural resources at the Kennedy Space Center (KSC) is of great concern. The potential for surface and ground water quality problems resulting from non-point sources of pollution was examined using models. Since spatial variation of parameters required was important, geographic information systems (GIS) and their data were used. The potential for groundwater contamination was examined using the SEEPAGE (System for Early Evaluation of the Pollution Potential of Agricultural Groundwater Environments) model. A watershed near the VAB was selected to examine potential for surface water pollution and erosion using the AGNPS (Agricultural Non-Point Source Pollution) model

The onset of grasses in the Amazon drainage basin, evidence from the fossil record

Poaceae (the grass family) originated in the Cretaceous, but first dominate the palynological records of the Amazon drainage basin (ADB) in the Neogene (23 to 2.5 million years ago (Ma)). However, the ecological role of grasses in the landscape during this time remains to be resolved. In this paper, we summarise the global significance of grasses and the relevance of the fossil record, and evaluate the history of the grasses in the ADB. We present a 3-stage model of the changing role of grasses, which we based on a revision of Neogene depositional environments, the palynological record, and modern grass distribution in the Neotropics. Our model comprises the following hypotheses: (H1) assumes that from c. 23 to 9 Ma western Amazonia was dominated by a megawetland (the ‘Pebas system’) that harboured large amounts of (aquatic?) grasses. In (H2) we propose that from c. 9 Ma Andean uplift prompted megafans (extremely large alluvial fans) that extended from the Andes into the lowlands. Meanwhile, the ‘Pebas’ megawetland gradually transformed into a fluvial system. In this scenario, grasses would have had a competitive advantage and were able to colonise the newly formed megafan and fluvial landscapes. Finally, in (H3) we suggest that landscape dynamics and climatic change intensified from c. 3.5 Ma, allowing for a renewed expansion of the grasses. In addition, both the fossil and molecular records suggest that from c. 5 Ma grasses were firmly established in the tropical alpine vegetation (páramo), the tropical lowland floodplains (várzeas), and savannas (cerrado). Although further study will have to confirm the precise nature of the ADB grass history, we anticipate that abiotic processes during the Neogene and Quaternary left a strong imprint in the grass phytogeography of northern South America