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Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based on an analysis of the seven heaviest rainfall events in recent decades. Climate change appears to be a significant contributing factor to destructive floods. Thus, this paper aims to assess the susceptibility of this area to flash floods in case of heavy downpours.

This paper uses a variety of computational approaches. Following the collection of data, spatial analyses have been conducted and validated. The layers of information are then weighted, and a final risk map is created. Fuzzy analytical hierarchy process, geographic information system and frequency ratio have been used for data analysis. In the final step, a flood risk map is prepared and discussed.

Due to the complex interaction between thermal fluctuations and precipitation, the situation in the area is further complicated by climate change and the variations in its patterns and intensities. According to the study results, coastal areas of the Caspian Sea, the Gorganrood Basin and the southern regions of the province are predicted to experience flash floods in the future. The research criteria are generalizable and can be used for decision-making in areas exposed to flash flood risk.

The unique feature of this paper is that it evaluates flash flood risks and predicts flood-prone areas in the northern part of Iran. Furthermore, some interventions (e.g. remapping land use and urban zoning) are provided based on the socioeconomic characteristics of the region to reduce flood risk. Based on the generated risk map, a practical suggestion would be to install and operate an integrated rapid flood warning system in high-risk zones.

Man has always faced natural hazards and thus attempted to reduce their financial and loss-of-life damages. Assuring sustainable development in the post-disaster reconstruction of areas requires predictive measurements (i.e. vulnerability assessment). This study aims to assess the outcomes of relocating villages after the 2005 flood in the east of Golestan Province in Iran through sustainable development.

This study is an applied research combining qualitative content analysis and quantitative cross-sectional surveys. The statistical population comprises the inhabitants of Faraghi New Town (formed by aggregating 11 villages) and the villagers returning to their former rural settlement. The independent samples t-test was used to compare the outcomes of reconstruction for the samples. Data were collected using a questionnaire and in-depth interviews with the residents. The gathered data were analyzed by content analysis.

The results indicate that building new settlements – while reducing physical vulnerability – cannot be classified as a step toward sustainable development in economic and social aspects because the increasing trend of migration to urban areas, return to former villages, tribal disparities, reduced production, increased bank debts and increased urban insecurity are among the primary adverse social and economic consequences of rural relocations. This finding helps to assist planners and post-disaster designers to reconstruct more sustainable societies.

This study tries to investigate the effects of post-disaster reconstruction in rural settlement in Iran through sustainable development aspects for the first time. It would benefit for policymaking and urban planners and designers to make more resilient societies after disasters.

As a flood-prone region in Iran, Golestan province has encountered various disasters in its history. The last one occurred in March 2019, affected Aq-Qala County and caused irreparable physical, economic, social and environmental problems. The purpose of this study is to investigate the process of providing shelter in emergency, rehabilitation and reconstruction phases after the floods in the villages of Aq-Qala.

A research method is a hybrid approach. The collection of data involved a combination of qualitative and quantitative approaches in addition to reviewing the documented texts in resources to collect the required data using observations, field survey activities, questionnaires and in-depth interviews. From April 2019 to December 2019, nine separate visits have occurred to collect the needed information.

This paper shows dissatisfaction with providing shelter and attempts to identify the factors which caused the challenges. The findings revealed issues such as hygienic problems in collective camps, lack of thermal resistance in temporary accommodations and rising material prices. These findings lead to a contributive list of suggestions avoiding the recurrence of the harms in the future.

This study proposes solutions and approaches to improve the post-flood settlement process for possible floods in the future such as equipped camps, proper temporary housing, monitoring the reconstruction and the price of the materials. If these approaches are used by authorities and people in similar rural areas, the long-term effects of inadequate post-flood shelter can be reduced.

One of the largest floods in Iran happened in Nowruz in 2019, during which torrents of rain, flooding of rivers, landslides and the destruction of dams caused floods and led to financial losses and loss of life in 25 provinces of Iran. During and after the flood, 39 public libraries were closed, three libraries were evacuated and one was completely destroyed.

Despite the damage that occurred in the libraries, the preventive measures had been taken by many of them to reduce the whole damage. In addition, after the flood, responsible organizations including Iran Public Libraries Institution, the Institute for the Intellectual Development of Children and Young Adults and the Cultural and Art Organization of Municipality and the Mosques and Cultural Center, as well as other relief and social teams, and even people performed activities to reduce the negative impacts caused by the flood.

This article reviews these activities and their effectiveness. In the end, “the development of a plan for public libraries in natural and social crises” is proposed and the reasons for its necessity are discussed.

This article reviews these activities and their effectiveness. In the end, “the development of a plan for public libraries in natural and social crises” is proposed and the reasons for its necessity are discussed.

Post-disaster housing reconstruction (PDHR) demands a considerable percentage of global property investment, yet the post-disaster environment presents intricate challenges to reconstruction financing for governments and at the same time, revenue uncertainty for private investors. The purpose of this study is to develop a methodology for tackling land shortage and the financial challenges of PDHR in the aftermath of a disaster.

This study developed a methodology based on a combined minimum revenue guarantee and maximum revenue cap model using a well-established real options analysis (ROA) for revenue risk sharing in PDHR projects and land readjustment (LR) for finance. The applicability of the purported model is demonstrated through an illustrative example.

The results show that flexibility in the options could increase the PDHR contractor’s risk profile by increasing the expected value of the contractor investment and reducing the probability of investment loss. On the other side, a cap on the contractor revenue stream would allow the government to benefit from any excess in revenue and would counterbalance the value of the option.

The framework proposed in this study could serve as a practical risk-revenue sharing in PDHR projects. Governments and policymakers could use the findings to enable the successful delivery of PDHR projects and consequently bring the quality of life of affected people to pre-disaster conditions.

This study can be considered as a first attempt toward the use of the Australian barrier style options structure, and the trinomial lattice valuation model in PDHR projects, which incorporates LR, public-private partnerships, governmental guarantees and PDHR concepts in one ROA-based framework.

Accessing adequate healthcare to all people is one of the main goals of the health sector. The purpose of this paper is to investigate healthcare services access development of the provinces in Iran during 2007 and 2013.

This is a descriptive cross-sectional study. The study population included all the provinces in Iran. The data for 13 variables, including physical and human health resources, was collected from the Ministry of Health and Medical Education and the Statistics Center of Iran. Taxonomy technique was used to determine the degree of healthcare services access development in the provinces.

The findings show that Semnan was the province with the most developed healthcare services access with development score of 0.342 while Sistan Balocehstan province was the least developed with development score of one in 2007. In the year 2013, Chahar-Mahal Bakhtiari and Sistan Baluchestan were the least and most developed provinces with scores of 0.551 and 0.989, respectively. The mean and standard deviation of the development scores in access to healthcare services in 2007 and 2013 were 0.7463±0.1268 and 0.7766±0.1058, respectively.

Most previous studies that examined disparities in access to healthcare resources in Iran only considered one resource. This study applied a taxonomy technique to investigate the disparity and changes in access using 13 main healthcare resources. This approach helped the authors to investigate whether the decisions of the policy makers were intended to eliminate the disparities.

This research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.

A three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.

Rice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCI_min and VCI_min are found to be the most proper indices to predict rice yield.

The results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.

This study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.