Location of Areas Prone to Flood Spreading Using GIS (Ilam Province,Iran)

Water Resources - The present study aimed to locate the areas prone to flood spreading in order to manage surface water resources. Therefore, the information layers of slope, land capability,...     

Seismic reliability assessment and the nonergodicity in the modelling parameter uncertainties

Modelling uncertainty can significantly affect the structural seismic reliability assessment. However, the limit state excursion due to this type of uncertainty may not be described by a Poisson process as it lacks renewal properties with the occurrence of each earthquake event. Furthermore, considering uncertainties related to ground motion representation by employing recorded ground motions together with modelling uncertainties is not a trivial task. Robust fragility assessment, proposed previously by the authors, employs the structural response to recorded ground motion as data in order to update prescribed seismic fragility models. Robust fragility can be extremely efficient for considering also the structural modelling uncertainties by creating a dataset of one-to-one assignments of structural model realizations and as-recorded ground motions. This can reduce the computational effort by more than 1 order of magnitude. However, it should be kept in mind that the fragility concept itself is based on the underlying assumption of Poisson-type renewal. Using the concept of updated robust reliability, considering both the uncertainty in ground motion representation based on as-recorded ground motion and non ergodic modelling uncertainties, the error introduced through structural reliability assessment by using the robust fragility is quantified. It is shown through specific application to an existing RC frame that this error is quite small when the product of the time interval and the standard deviation of failure rate is small and is on the conservative side.     

Assessment of geomorphological bank evolution of the alluvial threshold rivers based on entropy concept parameters

The complex stream bank profiles in alluvial channels and rivers that are formed after reaching equilibrium has been a popular topic of research for many geomorphologists and river engineers. The entropy theory has recently been successfully applied to this problem. However, the existing methods restrict the further application of the entropy parameter to determine the cross-section slope of the river banks. To solve this limitation, we introduce a novel approach in the extraction of the equation based on the calculation of the entropy parameter (λ) and the transverse slope of the bank profile at threshold channel conditions. The effects of different hydraulic and geometric parameters are evaluated on a variation of the entropy parameter. Sensitivity analysis on the parameters affecting the entropy parameter shows that the most effective parameter on the λ-slope multiplier is the maximum slope of the bank profile and the dimensionless lateral distance of the river banks.     

Factors associated with unnecessary requests for an ambulance by non-traumatic patients after the acute earthquake responding phase: a qualitative content analysis

The pre-hospital emergency staff played a key role in transferring the injured patients to health centers. Usually, they reported changes in their decisions on the transfer of non-traumatic patients to hospitals. So, this study was aimed to explore the reasons for unnecessarily requesting an ambulance by non-traumatic patients after the acute responding-to-earthquake phase. This study was a qualitative study that data were analyzed by content analysis approach. Participants were eleven pre-hospital emergency technicians. Data were collected by three sessions of focus group discussion. Data analysis was led to emergence of a main theme: “feeling urgency due to turmoil and uncertainty.” This theme illustrates the basic approach of the inhabitants of the earthquake-stricken region when unnecessarily requesting an ambulance. This theme was derived from two main categories of “turbulent and uncertain conditions” and “psychological turmoil.” The category of “turbulent and uncertain conditions” was comprised of three subcategories: “unreliable care,” “inadequate facilities” and “turbulent living conditions.” The category of “psychological turmoil” was comprised of three subcategories: “psychological turmoil in survivors,” “healthcare providers deciding under pressure” and “turmoil in providing psychological and psychiatric services.” Ambulance dispatch may be unnecessarily performed owing to turbulent and unsure conditions and psychological turmoil in earthquake-stricken people and pre-hospital emergency staff. Providing earthquake-stricken people with psycho-medical services in their place of residence can significantly reduce the workload of pre-hospital emergency staff and consequently that of hospital staff and therefore save time and treatment costs and increase the quality of health services provided for the injured.

     

A nine-step approach for developing and implementing an “agricultural drought risk management plan”; case study: Alamut River basin in Qazvin,Iran

Occurrence of drought, as an inevitable natural climate feature, cannot be ceased while happening. However, costs of the consequences could be alleviated using mature scientific integrated approaches. To reduce the amount of damage, it is required to provide “Contingency” and “Mitigation” action plans. For this reason, development of efficient operating instructions for various regions based on weather conditions and field studies is needed as well as having a sophisticated understanding of socioeconomic situations. This paper describes an approach to provide the first national agricultural drought risk management plan for a river basin in Iran country as a pilot. The study lasted for 3 years as a national technical research project for the “soil conservation and watershed management research institute.” To reach the objectives, besides holding workshops and specialized think-tank meetings, field researches were done. Based on the socioeconomic data sources in the basin and the results of meetings by participation of local managers and residents, the final plan was developed. Moreover, in order to carry out this research, different climatic, agricultural and local information were collected in the watershed. In the next steps, potential risks and vulnerabilities of various agricultural sectors due to the hazard were evaluated. In this study, a nine-step approach to develop an agricultural drought risk management plan proposing different scientific–managerial phases based on the latest experts’ opinions, released international scientific best practices, and existing conditions governing the region was followed. With respect to the average income of US$ one million from agriculture and animal husbandry in the river basin, total drought loss varies from US$ 86,000 to US$ 258,000 for a range of light to very intense drought conditions, respectively. The setup of these nine executive phases defined monitoring, forecasting, and warning steps in working teams and managed the subprograms in partnership with stakeholders and decision-makers to mitigate the rate of drought damage from 30 to 47% (depending on the severity of the drought condition).

     

An Introduction to MODISI and SCMOD Methods for Correction of the MODIS Snow Assessment Algorithm

Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.     

Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment

The study examines the potential of urban roofs to reduce the urban heat island (UHI) effect by changing their reflectivity and implementing vegetation (green roofs) using the example of the City of Vienna. The urban modelling simulations are performed based on high-resolution orography and land use data, climatological observations, surface albedo values from satellite imagery and registry of the green roof potential in Vienna. The modelling results show that a moderate increase in reflectivity of roofs (up to 0.45) reduces the mean summer temperatures in the densely built-up environment by approximately 0.25 °C. Applying high reflectivity materials (roof albedo up to 0.7) leads to average cooling in densely built-up area of approximately 0.5 °C. The green roofs yield a heat load reduction in similar order of magnitude as the high reflectivity materials. However, only 45 % of roof area in Vienna is suitable for greening and the green roof potential mostly applies to industrial areas in city outskirts and is therefore not sufficient for substantial reduction of the UHI effect, particularly in the city centre which has the highest heat load. The strongest cooling effect can be achieved by combining the green roofs with high reflectivity materials. In this case, using 50 or 100 % of the green roof potential and applying high reflectivity materials on the remaining surfaces have a similar cooling effect.     

A GIS‐based multi‐criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by granular computing. It provides a transparent structure despite the traditional multi‐layer neural networks. It also allows the classifier to be applied on a set of rules for each incoming pattern. Drawbacks of original granular computing (GrC) are covered, where some input patterns remained unclassified. The study was applied to classify seismic vulnerability of the statistical units of the city of Tehran, Iran. Slope, seismic intensity, height and age of the buildings were effective parameters. Experts ranked 150 randomly selected sample statistical units with respect to their degree of seismic physical vulnerability. Inconsistency of the experts' judgments was investigated using the induced ordered weighted averaging (IOWA) operator. Fifty‐five classification rules were extracted on which a neural network was based. An overall accuracy of 88%, κ = 0.85 and R² = 0.89 was achieved. A comparison with previously implemented methodologies proved the proposed method to be the most accurate solution to the seismic physical vulnerability of Tehran.     

Trends in monthly precipitation over the northwest of Iran (NWI)

Increasing global temperatures during the last century have had their own effects on other climatic conditions, particularly on precipitation characteristics. This study was meant to investigate the spatial and temporal monthly trends of precipitation using the least square error (LSE) approach for the northwest of Iran (NWI). To this end, a database was obtained from 250 measuring stations uniformly scattered all over NWI from 1961 to 2010. The spatial average of annual precipitation in NWI during the period of study was approximately 220.9–726.7 mm. The annual precipitation decreased from southwest to northeast, while the large amount of precipitation was concentrated in the south-west and in the mountainous areas. All over NWI, the maximum and minimum precipitation records occurred from March to May and July to September, respectively. The coefficient of variation (CV) is greater than 44 % in all of NWI and may reach over 76 % in many places. The greatest range of CV, for instance, occurred during July. The spatial variability of precipitation was consistent with a tempo-spatial pattern of precipitation trends. There was a considerable difference between the amounts of change during the months, and the negative trends were mainly attributed to areas concentrated in eastern and southern parts of NWI far from the western mountain ranges. Moreover, limited areas with positive precipitation trends can be found in very small and isolated regions. This is observable particularly in the eastern half of NWI, which is mostly located far from Westerlies. On the other hand, seasonal precipitation trends indicated a slight decrease during winter and spring and a slight increase during summer and autumn. Consequently, there were major changes in average precipitation that occurred negatively in the area under study during the observation period. This finding is in agreement with those findings by recent studies which revealed a decreasing trend of around 2 mm/year over NWI during 1966–2005.

     

A Geometric Computational Model for Calculation of Longwall Face Effect on Gate Roadways

In this paper a geometric computational model (GCM) has been developed for calculating the effect of longwall face on the extension of excavation-damaged zone (EDZ) above the gate roadways (main and tail gates), considering the advance longwall mining method. In this model, the stability of gate roadways are investigated based on loading effects due to EDZ and caving zone (CZ) above the longwall face, which can extend the EDZ size. The structure of GCM depends on four important factors: (1) geomechanical properties of hanging wall, (2) dip and thickness of coal seam, (3) CZ characteristics, and (4) pillar width. The investigations demonstrated that the extension of EDZ is a function of pillar width. Considering the effect of pillar width, new mathematical relationships were presented to calculate the face influence coefficient and characteristics of extended EDZ. Furthermore, taking GCM into account, a computational algorithm for stability analysis of gate roadways was suggested. Validation was carried out through instrumentation and monitoring results of a longwall face at Parvade-2 coal mine in Tabas, Iran, demonstrating good agreement between the new model and measured results. Finally, a sensitivity analysis was carried out on the effect of pillar width, bearing capacity of support system and coal seam dip.