Dynamics of hourly sea level at Hillarys Boat Harbour,Western Australia: a chaos theory perspective

Water level forecasting using recorded time series can provide a local modelling capability to facilitate local proactive management practices. To this end, hourly sea water level time series are investigated. The records collected at the Hillarys Boat Harbour, Western Australia, are investigated over the period of 2000 and 2002. Two modelling techniques are employed: low-dimensional dynamic model, known as the deterministic chaos theory, and genetic programming, GP. The phase space, which describes the evolution of the behaviour of a nonlinear system in time, was reconstructed using the delay-embedding theorem suggested by Takens. The presence of chaotic signals in the data was identified by the phase space reconstruction and correlation dimension methods, and also the predictability into the future was calculated by the largest Lyapunov exponent to be 437 h or 18 days into the future. The intercomparison of results of the local prediction and GP models shows that for this site-specific dataset, the local prediction model has a slight edge over GP. However, rather than recommending one technique over another, the paper promotes a pluralistic modelling culture, whereby different techniques should be tested to gain a specific insight from each of the models. This would enable a consensus to be drawn from a set of results rather than ignoring the individual insights provided by each model.     

Seismic hazard assessment for Mymensingh,Bangladesh

Mymensingh municipality lies in one of the most earthquake-prone areas of Bangladesh. The town was completely destroyed during the Great Indian Earthquake of 12 June 1897, for which the surface-wave magnitude was 8.1. In this study the 1897 Great Indian Earthquake was used as a scenario event for developing seismic microzonation maps for Mymensingh. For microzonation purposes SPT data from 87 boreholes were collected from different relevant organizations. To verify those data ten boreholes of depth up to 30 m were drilled. Intensity values obtained for different events were calibrated against attenuation laws to check applicability to the study area. Vibration characteristics at diverse points of the study area were estimated by employing the one-dimensional wave-propagation software SHAKE. SHAKE discretizes the soil profile into several layers and uses an iterative technique to represent the non-linear behavior of the soil by adjusting the material properties at each iteration step. The required input information includes depth, shear wave velocity, damping factor, and unit weight of each soil layer. The liquefaction resistance factor and the resulting liquefaction potential were estimated to quantify the severity of liquefaction. Quantification of secondary site effects and the weighting scheme for combining the various seismic hazards were heuristic, based on judgment and expert opinion.     

Impact of Southern Oscillation on the Frequency of Monsoon Depressions in the Bay of Bengal

The impact of Southern Oscillation on thecyclogenesis over the Bay of Bengal duringthe summer monsoon has been investigated.The analysis of correlation coefficients(CCs) between the frequency of monsoondepressions and the Southern OscillationIndex (SOI) reveals that more depressionsform during July and August of El Niñoyears. Due to this, the seasonal frequencyof monsoon depressions remains little higherduring El Niño epochs even though thecorrelations for June and September are notsignificant. The CCs for July and August aresignificant at the 99% level.The El Niño-Southern Oscillation (ENSO)is known to affect Indian MonsoonRainfall (IMR) adversely. The enhancedcyclogenesis over the Bay of Bengal duringJuly and August is an impact of ENSO whichneeds to be examined closely. Increasedcyclogenesis over the Bay of Bengal may bereducing the deficiency in IMR duringEl Niño years by producing more rainfallover the eastern parts of India duringJuly and August. Thus there is a considerablespatial variation in the impact of ENSOon the monsoon rainfall over India and El Niñoneed not necessarily imply a monsoonfailure everywhere in India.The area of formation of monsoon depressionsshifts eastward during El Niño years.Warmer sea surface temperature (SST) anomaliesprevail over northwest and adjoiningwestcentral Bay of Bengal during premonsoon andmonsoon seasons of El Niño years.May minus March SOI can provide useful predictionsof monsoon depression frequencyduring July and August.     

Environmental isotopic and hydrochemical study of water in the karst aquifer and submarine springs of the Syrian coast

The groundwater of major karst systems and submarine springs in the coastal limestone aquifer of Syria has been investigated using chemical and isotopic techniques. The δ¹⁸O values of groundwater range from ?6.8 to ?5.05‰, while those for submarine springs vary from ?6.34 to +1.08‰ (eastern Mediterranean seawater samples have a mean of +1.7‰). Groundwater originates from the direct infiltration of atmospheric water. Stable isotopes show that the elevation of the recharge zones feeding the Banyas area (400–600 m a.s.l.) is higher than that feeding the Amrit area (100–300 m a.s.l.). The ¹⁸O_extracted (¹⁸O content of the seawater contribution) for the major submarine springs suggests a mean recharge area elevation of 600–700 m a.s.l., and lower than 400 m a.s.l. for the spring close to Amrit. Based on the measured velocity and the percentage of fresh water at the submarine springs outlet, the estimated discharge rate is 350 million m³/year. The tritium concentrations in groundwater (1.6–5.9 TU) are low and very close to the current rainfall values (2.9–5.6 TU). Adopting a model with exponential time distribution, the mean turnover time of groundwater in the Al-sen spring was evaluated to be 60 years. A value of about 3.7 billion m³ was obtained for the maximum groundwater reservoir size.     

On the mechanism of X-ray production by dart leaders of lightning flashes

Radiation with energies up to about 250 keV associated with the dart leader phase of rocket-triggered lightning were reported by Dwyer et al. (2004). The mechanism of X-ray generation by dart leaders, however, is unknown at present. Recently, Cooray et al., in pressPlease provide complete bibliographic details for Ref. cooray e al., in press and Saleh et al., in press if available., Cooray et al., 2009a developed physical concepts and mathematical techniques necessary to calculate the electric field associated with the tip of dart leaders. We have utilized the results of these calculations together with the energy dependent frictional force on electrons, as presented by Moss et al. (2006), to evaluate the maximum energy an electron will receive in accelerating in the dart-leader-tip electric field. The main assumptions made in performing the calculations are: (a) the dart leader channel is straight and vertical; (b) the path of the electrons are straight inside the channel; and (c) the decay of the channel temperature is uniform along the length of the dart leader. In the calculation, we have taken into account the fact that the electric field is changing both in space and time and that the gas in the defunct return stroke channel is at atmospheric pressure and at elevated temperature (i.e. reduced gas density). The results of the calculation show that for a given dart leader current there is a critical defunct-return-stroke-channel temperature above which the cold electron runaway becomes feasible. For a typical dart leader, this temperature is around 2500 K. This critical temperature decreases with increase in dart leader current. Since the temperature of the defunct return stroke channel may lie in the range of 2000–4000 K, the results show that the electric field at the tip of dart leaders is capable of accelerating electrons to MeV energy levels.     

Yield Forecasting of Spring Maize Using Remote Sensing and Crop Modeling in Faisalabad-Punjab Pakistan

Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha^?1, while remote sensing showed the RMSE of 397 kg ha^?1. Overall strength of relationship between estimated and actual grain yields were good with R² of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.     

Effectiveness of Mg–Al-layered double hydroxide for heavy metal removal from mine wastewater and sludge volume reduction

Health hazards from heavy metal pollution in water systems are a global environmental problem. Of similar concern is sludge that results from wastewater treatment due to unsatisfactory sludge management technology. Therefore, the effectiveness of using Mg–Al-layered double hydroxide in the removal of heavy metals from mine wastewater was tested and compared with that of calcium hydroxide [Ca(OH)₂], which is a common treatment method for heavy metal removal. Initially, the mine wastewater contained cations of the heavy metals iron (Fe), zinc (Zn), copper (Cu), and lead (Pb). The Mg–Al-layered double hydroxides were able to remove 371, 7.2, 121, and 0.4 mg/L of these pollutants, respectively, using the co-precipitation method. The removal of these metals is most effective using 0.5 g Mg–Al-layered double hydroxide (Mg/Al molar ratio 4) and 20 min of shaking. Zn was removed by the formation of Zn(NO₃)(OH)·H₂O and Zn₅(NO₃)₂(OH)₈ when LDH, Mg/Al molar ratios of 4 and 2, respectively, were used. Similarly, Fe, Cu, and Pb were removed by the formation of Fe–Al-layered double hydroxide, Cu₂(OH)₃·NO₃ and Pb₄(OH)₄(NO₃)₄, respectively. While Ca(OH)₂ is also capable of reducing the heavy metal concentrations below the Japanese recommended values, this analysis shows that using 0.5 g Mg–Al-layered double hydroxide is a better treatment condition for mine wastewater, because it generates lower sludge volumes than 0.1 g of Ca(OH)₂. The measured sludge volume was 1.5 mL for Mg–Al-layered double hydroxide and 2.5 mL for Ca(OH)₂, a nearly twofold further reduction.     

Transforming local natural resource conflicts to cooperation in a changing climate: Bangladesh and Nepal lessons

ABSTRACT

Since the 1990s, climate change impact discourse has highlighted potential for large scale violent conflicts. However, the role of climate stresses on local conflicts over natural resources, the role of policies and adaptation in these conflicts, and opportunities to enhance cooperation have been neglected. These gaps are addressed in this paper using evidence from participatory action research on 79 cases of local collective action over natural resources that experience conflicts in Bangladesh and Nepal. Climate trends and stresses contributed to just under half of these conflict cases. Nine factors that enable greater cooperation and transformation of conflict are identified. Participatory dialogue and negotiation processes, while not sufficient, changed understanding, attitudes and positions of actors. Many of the communities innovated physical measures to overcome natural resource constraints, underlying conflict, and/or institutional reforms. These changes were informed by improving understanding of resource limitations and indigenous knowledge. Learning networks among community organizations encouraged collective action by sharing successes and creating peer pressure. Incentives for cooperation were important. For example, when community organizations formally permitted excluded traditional resource users to access resources, those actors complied with rules and paid towards management costs. However, elites were able to use policy gaps to capture resources with changed characteristics due to climate change. In most of the cases where conflict persisted, power, policy and institutional barriers prevented community-based organizations from taking up potential adaptations and innovations. Policy frameworks recognizing collective action and supporting flexible innovation in governance and adaptation would enable wider transformation of natural resource conflicts into cooperation.

Key policy insights

• Climate stresses, policy gaps and interventions can all worsen local natural resource conflicts.

• Sectoral knowledge and technical approaches to adaptation are open to elite capture and can foster conflicts.

• Many local natural resource conflicts can be resolved but this requires an enabling environment for participatory dialogue, external facilitation, flexible responses to context, and recognition of disadvantaged stakeholder interests.

• Transforming conflict to greater cooperation mostly involves social and institutional changes, so adaptation policies should focus less on physical works and more on enabling factors such as negotiation, local institutions, knowledge, and incentives.