Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin

Snowmelt and water infiltration are two important processes of the hydrological cycle in alpine basins where snowmelt water is a main contributor of streamflow. In insufficiently gauged basins, hydrologic modeling is a useful approach to understand the runoff formation process and to simulate streamflow. In this study, an existing hydrologic model based on the principles of system dynamics was modified by using the effective cumulative temperature (>0 °C) to calculate snowmelt rate, and the soil temperature to adjust the influence of the soil’s physical state on water infiltration. This modified model was used to simulate streamflows in the Kaidu River basin from 1982 to 2002, including normal, high, and low flows categorized by the Z index. Sensitivity analyses, visual inspection, and statistical measures were employed to evaluate the capability of the model to simulate various components of the streamflow. Results showed that the modified model was robust, and able to simulate the three categories of flows well. The model’s ability to reproduce streamflow in low-flow and normal-flow years was better than that in high-flow years. The model was also able to simulate the baseflow. Further, its ability to simulate spring-peak flow was much better than its ability to simulate the summer-peak flow. This study could provide useful information for water managers in determining water allocations as well as in managing water resources.     

Numerical modelling of multiphase immiscible flow in double‐porosity featured groundwater systems

A numerical model describing the flow of multiphase, immiscible fluids in a deformable, double‐porosity featured soil has been developed. The model is focused on the modelling of the secondary porosity features in soil, which is more relevant to groundwater contamination problems. The non‐linear saturation and relative permeabilities were expressed as functions of the capillary pressures. The governing partial differential equations in terms of soil displacement and fluid pressures were solved numerically. Galerkin's weighted‐residual finite element method was employed to obtain the spatial discretization whereas temporal discretization was achieved using a fully implicit scheme. The model was verified against established, peer‐reviewed works, and the assumption that the immiscible fluids (non‐aqueous phase liquids) will flow preferentially through the secondary porosity features in soil was validated. Copyright © 2011 John Wiley & Sons, Ltd.     

Groundwater vulnerability assessment and evaluation of human activity impact (HAI) within the Dead Sea groundwater basin,Jordan

Groundwater vulnerability to contamination was determined within the Dead Sea groundwater basin, Jordan, using the DRASTIC model and evaluation of human activity impact (HAI). DRASTIC is an index model composed of several hydrogeological parameters and, in this study, the recharge parameter component was calculated as a function of rainfall, soil permeability, slope percentage, fault system, and the intersection locations between the fault system and the drainage system, based on the hydrogeologic characteristics of hard-rock terrain in an arid region. To evaluate the HAI index, a land use/cover map was produced using an ASTER VNIR image, acquired for September 2004, and combined with the resultant DRASTIC model. By comparing the DRASTIC and HAI indices, it is found that human activity is affecting the groundwater quality and increasing its pollution risk. The land use/cover map was verified using the average nitrate concentrations in groundwater associated with land in each class. A sensitivity analysis was carried out in order to study the model sensitivity. The analyses showed that the depth to water table and hydraulic conductivity parameters have no significant impact on the model, whereas the impact of vadose zone, aquifer media, and recharge parameters have a significant impact on the DRASTIC model.     

Dynamics of energy sector and GHG emissions in Saudi Arabia

The energy sector is the main contributor to GHG emissions in Saudi Arabia. The tremendous growth of GHG emissions poses serious challenges for the Kingdom in terms of their reduction targets, and also the mitigation of the associated climate changes. The rising trend of population and urbanization affects the energy demand, which results in a faster rate of increase in GHG emissions. The major energy sector sources that contribute to GHG emissions include the electricity generation, road transport, desalination plants, petroleum refining, petrochemical, cement, iron and steel, and fertilizer industries. In recent years, the energy sector has become the major source, accounting for more than 90% of national CO₂ emissions. Although a substantial amount of research has been conducted on renewable energy resources, a sustainable shift from petroleum resources is yet to be achieved. Public awareness, access to energy-efficient technology, and the development and implementation of a legislative framework, energy pricing policies, and renewable and alternative energy policies are not mature enough to ensure a significant reduction in GHG emissions from the energy sector. An innovative and integrated solution that best serves the Kingdom's long-term needs and exploits potential indigenous, renewable, and alternative energy resources while maintaining its sustainable development stride is essential.

Policy relevance

The main contributor to GHG emissions in Saudi Arabia is the energy sector that accounts for more than 90% of the national CO₂ emissions. Tremendous growth of GHG emissions poses serious challenges for the Kingdom in their reduction and mitigating the associated climate changes. This study examines the changing patterns of different activities associated with energy sector, the pertinent challenges, and the opportunities that promise reduction of GHG emissions while providing national energy and economic security. The importance of achieving timely, sustained, and increasing reductions in GHG emissions means that a combination of policies may be needed. This study points to the long-term importance of making near- and medium-term policy choices on a well-informed, strategic basis. This analytical paper is expected to provide useful information to the national policy makers and other decision makers. It may also contribute to the GHG emission inventories and the climate change negotiations.     

Asia-Pacific mussel watch: monitoring contamination of persistent organochlorine compounds in coastal waters of Asian countries

Contamination of persistent organochlorines (OCs) such as PCBs (polychlorinated biphenyls), DDT and its metabolites (DDTs), HCH (hexachlorocyclohexane) isomers (HCHs), chlordane compounds (CHLs), and HCB (hexachlorobenzene) were examined in mussels collected from coastal waters of Asian countries such as Cambodia, China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Philippines, Far East Russia, Singapore, and Vietnam in 1994, 1997, 1998, 1999, and 2001 to elucidate the contamination status, distribution and possible pollution sources and to assess the risks on aquatic organisms and human. OCs were detected in all mussels collected from all the sampling sites investigated. Considerable residue levels of p,p(')-DDT and alpha-HCH were found in mussels and the concentrations of DDTs and HCHs found in mussels from Asian developing countries were higher than those in developed nations suggesting present usage of DDTs and HCHs along the coastal waters of Asian developing countries. On the other hand, lower concentrations of PCBs detected in mussels from Asian developing countries than those in developed countries indicate that PCBs contamination in mussels is strongly related to industrial and activities. To our knowledge, this is a first comprehensive report on monitoring OCs pollution in the Asia-Pacific region.     

Artificial neural network application to estimate kinematic soil pile interaction response parameters

Six artificial neural network (ANN) models are developed to predict various response parameters of kinematic soil pile interaction. These responses include (1) kinematic response factors for free and fixed head piles in homogenous soil layer to derive foundation input motion (2) normalized bending moment at fixed head of pile in homogenous soil layer (3) normalized kinematic pile moment at the interface of two soil layers of sharply different soil stiffnesses. These ANN models represent simple solutions that can be implemented in a simple calculator capable of matrix operation and bypass the site response analysis and the complex wave diffraction analysis. The data required for ANN training is generated using beam on dynamic Winkler formulation (BDWF). Fifty percent of the data is used to train the ANN models while remaining 50% is used to test the ANN models. The trained ANN models show good agreement with BDWF results.     

Spatial modeling of Dengue prevalence and kriging prediction of Dengue outbreak in Khyber Pakhtunkhwa (Pakistan) using presence only data

Stochastic Environmental Research and Risk Assessment - During the span of August–October, 2017 a major outbreak of Dengue fever happened in Khyber Pakhtunkhwa province of Pakistan. Cases...     

EFFECTS OF SEASONALITY ON STREAMFLOW AND WATER QUALITY OF THE PINANG RIVER IN PENANG ISLAND, MALAYSIA

For the Pinang River, originating in the western highlands of Penang Island, the nature, sources and extent of pollution were studied. The river water samples collected at five selected sites were analyzed for various physical and chemical parameters, namely temperature, DO, BOD, COD, SS, pH, ammoniac nitrogen (AN), and conductance. Long-term data of rainfall and temperature were analyzed to determine the seasonal variations of the streamflow.The streamflow during the dry season is extremely low compared to the wet season, thus concentrations of contaminants derived from point pollution source increase due to lack of rainfall and runoff events. On the contrary, in the predominantly urban and agricultural catchments, non-point pollution source increases during rainy season through seepage and runoff. Effects of seasonal variations consequently deterrnine the quantity and quality of the water parameters.The Jelutong River, the Dondang River and the Air Itam River carry the seepage from widely urban and residential areas to the main Pinang River systems. Water quality of the Pinang River at different points assessed by the water quality indices was compared. According to the quality indices during the study period, water quality in the upper reaches of the river is medium to good. It dwindled in the plains, due to the seepage from urban areas and discharges from the industrial and agricultural lands.