Application of Generalized Likelihood Uncertainty Estimation (GLUE) at different temporal scales to reduce the uncertainty level in modelled river flows

ABSTRACT

In this study, the distributed catchment-scale model, DiCaSM, was applied on five catchments across the UK. Given its importance, river flow was selected to study the uncertainty in streamflow prediction using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology at different timescales (daily, monthly, seasonal and annual). The uncertainty analysis showed that the observed river flows were within the predicted bounds/envelope of 5% and 95% percentiles. These predicted river flow bounds contained most of the observed river flows, as expressed by the high containment ratio, CR. In addition to CR, other uncertainty indices – bandwidth B, relative bandwidth RB, degrees of asymmetry S and T, deviation amplitude D, relative deviation amplitude RD and the R factor – also indicated that the predicted river flows have acceptable uncertainty levels. The results show lower uncertainty in predicted river flows when increasing the timescale from daily to monthly to seasonal, with the lowest uncertainty associated with annual flows.     

Observation of azimuthal anisotropy from the seismic reflectivity of a Tertiary turbidite sand

P‐wave data from a time‐lapse 3D OBC survey have been analysed to estimate and interpret azimuthal seismic anisotropy. This is achieved by careful processing to preserve the azimuthal signature. The survey images a major reservoir body in a channelized turbidite field in the Gulf of Mexico. Three distinct and significant anisotropy anomalies are discovered on or around this particular ‘4500‐ft sand’, all of which change intensity but not orientation with hydrocarbon production. These anomalies are distributed along the highest concentration of cumulative sand thickness, with their symmetry axes aligned with the main channel axis. We suspect that this time‐lapse anisotropy could be caused by the alignment of the depositional grain fabric. Theoretical calculation predicts that this mechanism, when combined with fluid‐saturation changes, can generate the observed pattern of behaviour. If further supported by other researchers, this result would indicate that appropriately designed seismic surveys could be a useful tool for palaeo‐direction studies in clastic reservoirs and also a useful constraint for directional permeability in the reservoir flow simulation model.     

Toward an Ecological Explanation of Agricultural Unemployment in Bangladesh

Cultural ecology theoretical framework was found suitable to explain unemployment in agriculture in three villages in Bangladesh. Path analysis and multiple regression statistics were used to examine the direct, indirect, and total effects of eight independent human, social, environmental, and technology variables as well as their aggregate contribution on agricultural unemployment. The multiple regression model explains 86.2% of the total variation in unemployment in agriculture; they were followed by environmental constraints and labor saving technology variables.     

Variation of δ18O, δD and 3H in karst springs of south Kashmir,western Himalayas (India)

Water samples were collected from cold and warm karst springs for stable isotopes (δ¹⁸O and δD) and ³H from SE of Kashmir valley (western Himalayas) to distinguish the sources of recharge and infer their recharge areas. The spring water samples were most depleted in heavier isotopes in May (average δ¹⁸O: ?8.87‰ and δD: ?50.3‰) and enriched in September (average δ¹⁸O: ?7.58‰ and δD: ?48.1‰). The depleted ¹⁸O and ²H of spring waters bear the signatures of winter precipitation while as the enriched ¹⁸O and ²H of spring waters bear the signature of summer rainfall. D‐excess and ³H corroborate with the stable isotope results that the spring flow in spring season (May) and autumn (September) is dominantly controlled by the melting of winter snowmelt and summer rainfall, respectively. The results showed that unlike δD, the δ¹⁸O value in the karst spring waters decreases in January suggesting δ¹⁸O shift. The spring water samples also fall above the Local Meteoric Water Line and Global Meteoric Water Line indicating the δ¹⁸O shift due to interaction of groundwater with the host carbonate rocks during its traverse. The mean elevation of the recharge areas of the springs using δ¹⁸O and δD tracers was also estimated. Copyright © 2014 John Wiley & Sons, Ltd.     

Source Sector Contributions to Aerosol Levels in Pakistan

Urban air pollution in Pakistan is a serious challenge and it causes significant damage to human health and ecosystems. This paper presents a modelling study using the Weather Research and Forecasting Model coupled with Chemistry(WRF-Chem) to simulate the spatial distributions and temporal variations of aerosol concentrations over Pakistan, focusing on contributions of domestic emission sectors(transport, industry, residential, and energy) to mass concentrations of sulfate(SO2–4), nitrate(NO–3), ammonium(NH+4), black carbon(BC), and organic carbon(OC) during the months of January, April, July, and October in 2010. Sensitivity studies indicate that, averaged over January, April, July, and October of 2010, energy and industry sectors have the largest contributions to SO2–4 concentrations, each of which contributes about 10%?20% to SO2– 4over the polluted eastern Pakistan. The contributions from residential and transport sectors to NO–3 concentrations reach 40%?50% in central Pakistan. The residential sector has the highest contribution of 50%–80% to BC and OC loading in northeastern and southern Pakistan. Examination of sector contributions to aerosol levels in Lahore, the most polluted city in Pakistan, suggests that reductions in emissions in the residential sector should be an efficient measure for improving particulate matter air quality in this region.     

A multi-proxy reconstruction of spatial and temporal variations in Asian summer temperatures over the last millennium

To investigate climate variability in Asia during the last millennium, the spatial and temporal evolution of summer (June–July–August; JJA) temperature in eastern and south-central Asia is reconstructed using multi-proxy records and the regularized expectation maximization (RegEM) algorithm with truncated total least squares (TTLS), under a point-by-point regression (PPR) framework. The temperature index reconstructions show that the late 20th century was the warmest period in Asia over the past millennium. The temperature field reconstructions illustrate that temperatures in central, eastern, and southern China during the 11th and 13th centuries, and in western Asia during the 12th century, were significantly higher than those in other regions, and comparable to levels in the 20th century. Except for the most recent warming, all identified warm events showed distinct regional expressions and none were uniform over the entire reconstruction area. The main finding of the study is that spatial temperature patterns have, on centennial time-scales, varied greatly over the last millennium. Moreover, seven climate model simulations, from the Coupled Model Intercomparison Project Phase 5 (CMIP5), over the same region of Asia, are all consistent with the temperature index reconstruction at the 99 % confidence level. Only spatial temperature patterns extracted as the first empirical orthogonal function (EOF) from the GISS-E2-R and MPI-ESM-P model simulations are significant and consistent with the temperature field reconstruction over the past millennium in Asia at the 90 % confidence level. This indicates that both the reconstruction and the simulations depict the temporal climate variability well over the past millennium. However, the spatial simulation or reconstruction capability of climate variability over the past millennium could be still limited. For reconstruction, some grid points do not pass validation tests and reveal the need for more proxies with high temporal resolution, accurate dating, and sensitive temperature signals, especially in central Asia and before AD 1400.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.     

Unnoticed but important: revealing the hidden contribution of community-based religious institution of the mosque in disasters

The role of community-based religious institutions has been largely undocumented, underestimated and overshadowed in the disaster studies literature. This paper explores the role of the mosque, a community-based religious institution, in disaster management by documenting and analysing its role in rural settings in the aftermath of the 2005 earthquake in Pakistan. The study examines the role of the mosque in relation to key actors from the state, civil society and private sector during response, relief, recovery, reconstruction and rehabilitation phases of the Pakistan earthquake. Using qualitative research methods and a case study design, this article analyses primary data collected through 5 months of fieldwork (in 2009 and 2010). The findings demonstrate the multifaceted and distinct contribution of the mosque in cultural, economic, social and political aspects of the lives of the earthquake-affected communities. Possible challenges to engagement with the mosque, both gender inclusiveness and political controversy around its role, are also raised. This research suggests that state, civil society and private sector actors involved in disaster management need to understand complex relationships involving people and their religious institutions, and their impact on the social dimension of recovery. The findings of the study contribute to the scarce knowledge about the role of community-based religious institutions including churches, mosques, synagogues and temples and call for engagement: that is, acknowledging and valuing their role for building a synergy between secular and religious efforts for disaster risk reduction and post-disaster recovery.     

Impact of rangeland enclosure and seasonal grazing on protected and unprotected rangelands in Chakwal region,Pakistan

Scrub rangelands support livestock grazing and provide ecosystem services to their inhabitants.The present study was conducted in Chakwal,an important tract of ...