Effect of palm waste on sloping land to fresh fruit bunch production in oil palm plantation

Palm waste is abundant and readily available. It is low cost and commonly used as a fertilizer on oil palm plantations. The effectiveness of oil palm waste on sloping lands in oil palm plantation was investigated. Data was collected from each block with sloping lands, including the type, dose, and timing of fertilizer, record of rainfall, and Fresh Fruit Bunch (FFB) production for each month. There was no significant difference on FFB production between the types of fertilizer: inorganic fertilizer, inorganic substitution with palm waste, and palm waste only. However, a significant difference on FFB production was found between types of sloping land. Optimum FFB production was 15.01 kg palm-1 month-1 for inorganic substitution with palm waste on undulating hilly (IH) areas. Fertilizing with only palm waste gave 15.93 kg palm-1 month-1 of FFB production on a flat gently sloping (FGS) area. It shows that palm waste has comparable potential with inorganic fertilizer, even when applied on sloping land

Short-term variability of Johor River discharge based on wavelet analysis

River discharge provides a direct measure of water quantity and availability of water for specific uses. It also provides the basis for understanding river basin processes and is essential for interpreting and understanding river flow characteristics. This study investigates the temporal variability of river discharge records of Johor River. Wavelet analysis of discharge records for 30 years was carried out to characterize the river flow variability. Our results indicate that Johor River discharge data shows a significant short-term variability of between 0.6 to 2.5 years

Occurrence of natural radioactivity and corresponding health risk in groundwater with an elevated radiation background in Juban District, Yemen

This study aims to investigate the occurrence of natural radiation in groundwater with an elevated background level in Juban District, Yemen, and to assess the corresponding health risk. The mean concentrations of U, Th, and K in groundwater were 11.25, 0.15, and 17.35 mg l-1, respectively. The mean activity concentrations of 226Ra, 228Ra, and 40K were 94, 216, and 3306 mBq l-1, respectively. 65 % of the groundwater samples were above the WHO guidance level for 228Ra in water. The maximum concentrations of 226Ra, Th, and 228Ra were found around the fault zones in the basement aquifer while the concentrations of U increase down-gradient of Juan District. The principal factors controlling the occurrence and concentrations of radionuclides are aquifer type, leaching behaviour, characteristics of fracture systems, salinity, and water flow path. The annual effective doses due to ingestion of the water were estimated for infant and adult groups. The mean annual effective dose for infants was 1.97 mSv year-1 which is almost twenty times the WHO guideline level for drinking water. The ingestion dose deduced for adults and infants is dominated by 228Ra, where the average contribution from 228Ra in infants amounted to 90 % and in adults 76 %

Application of radial basis function neural networks for modeling rainfall-runoff processes: a case study of Semenyih River catchment, Malaysia

The gradual transformation of arable lands into urbanized environments in built-up areas is common in fast developing countries like Malaysia. Such changes have a large effect on hydrologic processes in the catchment area, which eventually results in an increase of both the magnitude and frequency of floods in urban areas. Therefore there is a great need of reliable rainfall-runoff models that are able to accurately estimate the discharge for a catchment. So far various physically-based models have been developed to capture the rainfall-runoff process, but the drawback has been the estimation the several numbers of parameters which is quite difficult and time consuming. Recently, artificial intelligence tools are being used because of their capability of modeling complex nonlinear relationships. These tools have been widely used in hydrological time series modeling and prediction. Radial basis function neural network (RBFNN) is a popular artificial intelligence technique that is well used in hydrological modeling. In this study, 30 extreme rainfall-runoff events were extracted from twelve years of hourly rainfall and runoff data. An input selection method based on correlation analysis and mutual information was developed to identify the proper input combinations of rainfall and discharge antecedents. The results obtained by RBFNN model were then compared with a traditionally used statistical model known as auto-regressive moving average with exogenous inputs (ARMAX), as a bench mark. Results showed that RBFNN performance is superior then the traditional statistical model and has good potential to be used as a reliable rainfall-runoff modeling tool

The activity concentrations of 222Rn and corresponding health risk in groundwater samples from basement and sandstone aquifer, the correlation to physicochemical parameters

This study aims to evaluate the activity concentrations of 222Rn and to assess the corresponding health risk in groundwater samples obtained in Juban District, Ad Dali' Governorate, Yemen. The measurements were performed by RAD 7 radon detector manufactured by DURRIDGE COMPANY Inc. The activity concentrations of 222Rn ranged from 1.0±0.2 Bq l-1 to 896.0±0.8 Bq l-1. 57% of the groundwater samples were above the US Environmental Protection Agency (USEPA) recommended value for Rn in water. Induced coupled plasma mass spectrometry (ICP-MS) was used to determine the concentrations of uranium in groundwater samples. The measured concentration of U ranged from 0.33±0.01 μg l-1 to 24.6±0.6 μg l-1. The results were comparable to internationally recommended values. The highest concentration of U and 222Rn were found to be in the basement aquifer, while the lowest concentrations of both radionuclides were in the sandstone aquifer. High concentrations of Rn are found along fault zones. The relationship between the activity concentration of 222Rn, concentration of U and physicochemical parameters were investigated. The results showed a very strong relationship between activity concentrations of 222Rn with concentrations of U and the salinity of water

Terrestrial gamma dose rate, radioactivity and radiological hazards in the rocks of an elevated radiation background in Juban District, Ad Dali Governorate, Yemen

This study aims to evaluate natural radiation and radioactivity in the rock and to assess the corresponding health risk in a region of elevated background radiation in Juban District, Ad Dali' Governorate, Yemen. The mean external gamma dose rate was 374 nGy h-1 which is approximately six times the world average. The measured results were used to compute annual effective dose equivalent, collective effective dose and excess lifetime cancer risk, which are 2.298 mSv, 61.95 man Sv y-1 and 8.043 × 10-3, respectively. Rocks samples from different geological formations were analyzed for quantitative determination of 226Ra, 232Th and 40K. The specific activity of the rocks samples ranges from 7 ± 1 Bq Kg-1 to 12 513 ± 329 Bq Kg-1 for 232Th, from 6 ± 1 Bq kg-1 to 3089 ± 74 Bq kg-1 for 226Ra and 702 ± 69 Bq kg-1 to 2954 ± 285 Bq kg-1 for 40K. 232Th is the main contributor to gamma dose rate from the rock samples. Indicators of radiological health impact, radium equivalent activity and external hazard index are 3738 Bq kg-1 and 10.10, respectively. The mean external hazard index was ten times unity in the studied locations in Juban District, which is higher than the recommended value