Magnetic polarity stratigraphy of the Upper Siwalik deposits,Pabbi Hills,Pakistan

Over 1000 m of fluvial molasse, exhibiting a stable detrital remanent magnetization, is exposed in a mammal-bearing sequence in the Upper Siwalik Group of the Pabbi Hills, Pakistan. The magnetic polarity chronology reveals that the sequence records a time period of 2.6 m.y., extending from the early Gauss Normal Epoch into the Brunhes Normal Epoch. During this period, sedimentation rates increased upward in time from 0.25 m/1000 yr to 0.45 m/1000 yr. The sudden disappearance of red beds and a change in the lithoclastic composition of basal channel sands suggests that about 800,000 years ago the primary source area began shifting from the metamorphic terrane of the Himalayan Orogen to a more local sedimentary terrane on the folded margins of the Himalayan foredeep. About 500,000 years ago the anticlinal Pabbi Hills attained surface expression. Uplift continued at a minimum rate of 1 m/1000 yr.A local Pliocene/Pleistocene boundary based on the Olduvai Normal Event is clearly recognized. Local fossil finds reveal thatEquus, diagnostic element of the Pinjor faunal zone, appeared locally about 1.8 m.y. ago and thatHipparion, a faunal element of the Tatrot and earlier faunal zones, persisted locally until at least 3.0 m.y. ago.     

A proposed spatial index to prioritize damaged buildings for allocating USAR operations

A spatial index using fuzzy hierarchical analysis (FAHP) is proposed in this study for prioritizing damaged buildings in the allocation of search and rescue operations after the earthquake disaster. The relevant prioritization criteria have been identified through literature review and interviews with 22 relief managers; the relative importance of these criteria and sub criteria has been computed using the FAHP method. The GIS layers equivalent to the selected criteria were prepared and integrated with one another after normalization in the GIS platform. The proposed method to prioritize the damaged buildings was implemented in the city of Varzeghan in the East Azerbaijan province of Iran. The obtained priority map, with five prioritization classes, is presented. Single-parameter sensitivity analysis method identifies the criteria ‘hazardous facilities’, ‘degree of building blockage’ and ‘chance of survival’ as the most effective criteria for prioritizing damaged buildings.     

A New Framework for Solving the Spatial Network Problems Based on Line Graphs

In this article we define inverse line graphs of directed graphs as a new framework for solving some classical network analysis problems. The extraction method and theories of inverse line graphs are explained in this article. It is shown that by changing the analysis space from the original directed graph to the inverse line graph, complex problems can be changed into simpler problems. We show the usefulness of the proposed framework in two particular applications: shortest path computations and the more general route planning. Considering the implementation result, we expect that this framework could be used in many more network analysis problems.     

The Kings River Experimental Watersheds: Infrastructure and data

The Kings River Experimental Watersheds (KREW) were established in 2002 to expand our knowledge of catchment physical, chemical, and biological processes in Sierra Nevada headwater forests, and to better understand the impacts of prescribed burning and forest thinning on these processes. Two elevation strata (high and low) were selected for the KREW sites, with four independent catchments and one nested catchment within each stratum. Both high and low elevation study areas were instrumented for continuous measurements of meteorology, streamflow, and turbidity. Atmospheric and stream chemistry, suspended sediment concentration, and bedload sediment delivery were measured on a regular schedule. Soil chemical and physical properties and vegetation were systematically sampled before and after the initial thinning and prescribed burning treatments, which were implemented between 2012 and 2016. Post-treatment data collection continues today as we explore opportunities for the second round of possible treatments. The critical research infrastructure and long-term baseline data collection has been instrumental in building partnerships with downstream managers, end users, non-governmental organizations, academic researchers, and national research programmes. Contributions to date include fundamental understanding of magnitude and variability of nutrient deposition; carbon, nutrient, and major ion dynamics in headwater streams; aquatic algae and macroinvertebrate populations; vegetation composition and structure; and streamflow responses to precipitation in the two elevation strata. Data from the experimental watersheds also support calibration and validation of diverse hydrologic models used for water resources planning.     

Development of stochastic dynamic Nash game model for reservoir operation II. The value of players’ information availability and cooperative behaviors

Stochastic dynamic game models can be applied to derive optimal reservoir operation policies by considering interactions among water users and reservoir operator, their preferences, their levels of information availability and cooperative behaviors. The stochastic dynamic game model with perfect information (PSDNG) has been developed by [Ganji A, Khalili D, Karamouz M. Development of stochastic dynamic Nash game model for reservoir operation. I. The symmetric stochastic model with perfect information. Adv Water Resour, this issue]. This paper develops four additional versions of stochastic dynamic game model of water users interactions based on the cooperative behavior and hydrologic information availability of beneficiary sectors of reservoir systems. It is shown that the proposed models are quite capable of providing appropriate reservoir operating policies when compared with alternative operating models, as indicated by several reservoir performance characteristics. Among the proposed models, the selected model by considering cooperative behavior and additional hydrologic information (about the randomness nature of reservoir operation parameters), as exercised by reservoir operator, provides the highest attained level of performance and efficiency. Furthermore, the selected model is more realistic since it also considers actual behavior of water users and reservoir operator in the analysis.     

Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data

The ability of the extreme learning machine (ELM) is investigated in modelling groundwater level (GWL) fluctuations using hydro-climatic data obtained for Hormozgan Province, southern Iran. Monthly precipitation, evaporation and previous GWL data were used as model inputs. Developed ELM models were compared with the artificial neural networks (ANN) and radial basis function (RBF) models. The models were also compared with the autoregressive moving average (ARMA), and evaluated using mean square errors, mean absolute error, Nash-Sutcliffe efficiency and determination coefficient statistics. All the data-driven models had better accuracy than the ARMA, and the ELM model’s performance was superior to that of the ANN and RBF models in modelling 1-, 2- and 3-month-ahead GWL. The RMSE accuracy of the ANN model was increased by 37, 34 and 52% using ELM for the 1-, 2- and 3-month-ahead forecasts, respectively. The accuracy of the ELM models was found to be less sensitive to increasing lead time.     

Pattern recognition of major asperities using local recurrence time in Alborz Mountains, Northern Iran

In this study, seismic data recorded during the period 01/01/1996 to 09/01/2009 has been used to evaluate the seismic hazard potential along the Alborz region, Northern Iran. The technique of mapping local recurrence time, T _L, is used to map major asperities, which are considered as the areas with maximum hazard. We calculated T _L from a and b values which are in turn derived from the frequency–magnitude relation constants within a radius of 30 km about every corner point of a 10-km spacing grid. Since b value is inversely related to applied stress, the areas with lowest b values and/or shortest T _L are interpreted to locate the asperities or the areas of maximum seismic hazard. To test this method, we computed T _L map using seismic catalogues before and after the 2004 Baladeh earthquake of M _w 6.2. The local recurrence time map before the earthquake shows anomalously short T _L in the epicentral region of the Baladeh earthquake a decade before its occurrence. The T _L map after the earthquake indicates that this large event has redistributed the applied stress in the Alborz region. The microseismicity of the region after the Baladeh earthquake, however, suggests that there are two anomalies in T _L map positioned in Alborz. The places where these anomalies are observed can be considered as the areas with maximum seismic hazard for future large earthquake in the Alborz region.     

An assessment of the potential impact of climate change on rice farmers and markets in Bangladesh

Bangladesh, the sixth largest rice producer in the world, has been identified as high risk from the effects of climate change. Many of the adverse impacts of climate change such as land inundation and changes in weather patterns and CO₂ levels will impact the agricultural sector. This study develops a partial-equilibrium multi-regional farm household model of Bangladesh rice and non-rice agricultural markets to quantify the impacts of climate change on consumption, production, prices, and farmers’ welfare. The model is calibrated to the Bangladesh rice market using Household Income and Expenditure Survey data. The model is simulated to analyze the impact of land reduction and productivity decline resulting from climate change. The results show that the decline in production in the coastal and northern regions offsets the production increase in the central and eastern regions, and the simulation predicts that total rice production for Bangladesh falls by about 2%. As total rice consumption falls and imports rise, the net effect leads to a rise in the rice price by 5.71% and a decline in farmers’ welfare. Sensitivity analysis shows that more- (less-) effective abatement technology could play a key role in mitigating (exacerbating) the price and welfare effects. The model predicts that many farmers in regions directly impacted by climate change could leave farming in search of off-farm work. Thus, the government can ease this transition by promoting urban development to provide more job options and technical training for farmers.