tofigh saadi

A comprehensive examination of natural hazards in Iran highlights the country's susceptibility to extensive damage from various natural crises. Iran's unique spatial structure has made it one of the world's most vulnerable regions to environmental hazards. This research reviews the application of “resilience” in studies of natural hazards, including floods, drought, and land degradation (single-hazard studies) as well as studies that combine these hazards (combined studies) across different regions of Iran.

This study utilized a conceptual research methodology, performing a systematic review of related research documents published in Iran, such as journal articles, dissertations, and theses. The databases used included the "Scientific Information Center of Academic Jihad (SID)", "Iran’s Research Institute of Science and Information Technology (Irandoc)", "Information Bank of Iran's Publications (Magiran)", "Knowledge Reference (Civilica)", and "Google Scholar". While previous studies have often examined resilience within an established analytical framework (concept analysis), this study employed a conceptual methodology aimed at representing knowledge and analyzing data from multiple disciplines. This approach helps clarify meanings and expand operational definitions. The data were analyzed thematically, enabling a more objective examination of resilience across various scientific fields.

The first study on resilience in Iran was conducted in 1988 in a dissertation at Tarbiat Modares University, and the concept appeared in articles in "Hakim Research Journal" in 2005. However, resilience studies focusing on natural hazards, especially in rural areas of Iran, are relatively recent, mostly emerging since the early 2010s. Based on the search criteria, 1,742 scientific documents were identified, with 57 relevant articles included in the review. Most documents were found in "Google Scholar," while the fewest were retrieved from "SID." The highest number of studies was conducted in 2017 (12 studies), and the lowest in 2012, 2021, and 2022 (one study each). Data from most studies were analyzed using statistical tests with SPSS, PLS, and AMOS software, while ArcGIS was commonly used for spatial data display and zoning to prioritize study areas. Most resilience studies focused on drought (36.8%), while the fewest focused on land degradation (10.5%).

The results show that, in flood-related research, the social dimension (29.4%) received the most attention, whereas the institutional dimension (20.6%) received the least. In drought research, the economic dimension (35.4%) received the most attention, while the institutional dimension (16.7%) received the least. In land degradation studies, the physical dimension (33.4%) was the most frequently examined, with other dimensions receiving 22.2% of the focus. Overall, the physical dimension (30.8%) and social dimension (20.5%) received the most attention. By identifying key resilience components, these findings can improve crisis management, reduce damages, and support the planning of development and educational projects in Iran.

A sharp drop in groundwater level as a result of indiscriminate extraction over a long period of time leads to the drying up of groundwater flows, which is called the phenomenon of groundwater drought. In this regard, this research aims to investigate the process of change and reduction of groundwater level, which is characterised by the phenomenon of groundwater drought. Based on this, the Groundwater Resource Index (GRI) was used to evaluate the drought condition of groundwater and analyse its spatial and temporal patterns based on groundwater level data of 21 observation wells between 1993 and 2019. ArcGIS software was used to create zone maps. The results of the research show that certain areas of the study area have experienced moderate to severe drought since 2001. In addition, the GRI zonation maps show that the southern and south-eastern regions of the aquifer have been more sensitive to drought than other parts of the aquifer during the defined period. The spatio-temporal pattern of groundwater drought in the aquifer shows that after a period of moderate drought from 2001 to 2003, the condition of the aquifer improved slightly, and generally stable conditions were established from 2001 to 2010, but since 2011, the occurrence of drought has intensified and the aquifer has been in severe to very severe drought conditions. These conditions highlight the need for careful attention and implementation of management measures. One of the study's recommendations is to use satellite data on groundwater levels to assess the progress of the drought, and compare it with the findings of this study.

Due to the water crisis, drought, population increase, and lack of conventional water resources, the use of new technologies to use unconventional water and manage consumption in different sectors is highly needed. In the present study, the factors affecting the success and failure of technological research in the water industry in Iran were analyzed with the aim of identifying the reasons for not applying of the country's water technological projects, inventions, and research. To provide effective solutions to strengthen the success and prevent the failure of water technologies, 15 questionnaires based on the Analytical Hierarchy Process (AHP) were completed by experts, experienced, knowledgeable, and proficient in the subject in the autumn and winter of 2022 and the results analyzed in the spring of 2023. According to the purpose of the study, the hierarchical structure included four technical, economic, social, and environmental criteria, each of which had four sub-criteria. After completing the questionnaires, the weights of criteria and sub-criteria were determined using Expert Choice software. To measure the accuracy of completed questionnaires, the inconsistency rate was calculated and equaled 0.09, which was less than the limit (0.1). The examination of the final weight of each of the sub-criteria showed that the first to third rank among all the investigated factors in the four main criteria, respectively, the ease of repair sub-criteria (S1) of the technical criteria with a final weight of 0.243, useful life (S4) from the technical criteria with a weight of 0.158 and the operation and maintenance cost (W4) from the economic criteria with a weight of 0.120. In general, the first two factors in the technical criteria and the superior factor in the economic criteria play a role as the most effective factors in the effectiveness of strengthening the success and preventing the failure of water technologies.

Water budget evaluations are important research topics in various regions of the world, as they aim to determine one or more components of the water balance. To estimate these components accurately, it is necessary to have adequate knowledge and methods. Therefore, reviewing the common methods used in international models can help to improve the estimation of water resources budget. The present study seeks to identify the challenges of groundwater budget estimation and to propose solutions for enhancing the accuracy of calculations, based on a critical analysis of previous studies conducted in Hashtgerd from 1987 to 2022. A three-level analysis was performed at the technical, institutional-structural, and infrastructural levels. The technical analysis of water budget components indicates that in the recent periods, the total output and input of groundwater were 257 and 245 MCM, respectively. Moreover, the average storage deficit was estimated at 18 MCM, which showed an increasing trend. This research suggests several measures to address the challenges, such as: equipping the study area with hardware facilities (lysimeters and data loggers); revising and updating the monitoring network of observation wells in the region; using remote sensing techniques to estimate evapotranspiration and other water budget components; updating the hydrodynamic information of the aquifer; measuring the withdrawal amount from exploitation wells and Qanats at a frequency of less than five years with more accurate methods; and establishing facilities for recording and displaying online components of the water budget in Hashtgerd at different scales. In this regard, the need for conducting water resources budget studies is emphasized, considering the uncertainties associated with the estimation of inputs and outputs.

Investigations show that the developed technologies and inventions developed in different sectors of water (drinking, industry, and agriculture) are not used in the implementation position as they should be. Therefore, it is necessary to scrutinize the existing problems and provide remedial solutions for the introduction of new technologies in the water industry. For this purpose, 10 of the most important technologies, innovations, inventions, projects, and practical ideas for the country's water sector were identified from among the 70 selected technologies. Then, this questionnaire was completed by 15 people who are experts, experienced, knowledgeable and proficient in the subject in the spring and summer of 2022. Cronbach's alpha test was used to measure the reliability of the questionnaires and its value for different parts of the questionnaire (strength, weakness, opportunity, and threat) was between 0.85-1, which is approved. Then the internal and external analysis of each technology was done using the SWOT analytical tool and the best strategy for each technology was introduced. The classification of the top and most frequent factors in each of the four sections based on the results of the 10 discussed technologies indicated that the option of increasing efficiency and significant water saving (S1) from the strengths section, became the most important option with ranked first 7 times. The high cost of design, construction, or execution (W1) from the weak points with 7, Changing the approach of the country's macro policies and adopting new technology (O3), and water storage, the ability to develop and sustain the country's water and food security (O4) from the opportunity points with 3, and as well as the short-term impact of technology and future problems related to it (T1), administrative bureaucracy and the lack of acceleration of the process of patenting and technology use (T2), and low economic-technical efficiency and exit from the application cycle (T5) from the threat points with 3 times placing in the first place, were the most important choices of each section. Also, the pathology of the factors of success and failure of technologies showed that the strong point of localization of technology and inventions of the water industry and the production of reliable data (S5), the weak point of problems related to the lack of ease of use (W3), the opportunity point of developing technical knowledge and transferring science to other countries (O1), and the threat point of low economic-technical efficiency and exit from the application cycle (T5) were identified as the least important factors with 4, 4, 4 and 5 times placing in the fifth place, respectively.

In management and planning of water resources, hydrological models are suitable tool that can be very effective in simulating hydrological processes such as water balance. Distributed hydrological models simulate each of the water balance parameters by discretization and solving equations in each cell. In the present study, the WetSpass-M distributed model is used to estimate and evaluate the components of the water balance in Hashtgerd study area in Alborz province. The model was implemented in monthly basis and for a 20 year period. In order to calibrate and validate the model, first the monthly flow data of the hydrometric station were used as observational data. The remote sensing approach (SEBAL algorithm) was applied to re-estimate evapotranspiration. Then, the results of the two approaches were evaluated and compared. According to the model results in the Hashtgerd study area, the mean annual values of evapotranspiration and groundwater recharge were estimated to be 347.3 and 272.6 MCM, respectively. Furthermore, the mean annual values of evapotranspiration for plains and mountains were respectively 241 and 106.3 MCM. The mean annual recharge rate in the plains was equal to 197 MCM, while it was estimated to be 75.6 MCM for mountains. The variations analysis of model outputs was performed based on the standard deviation for the water balance parameters in plains and mountains. The results showed that the most variations during the simulation period were observed respectively in the irrigation component, evapotranspiration, recharge, and rainfall.

Drought is one of the natural disasters occurring over a long period of time compared to other natural phenomena which intermittently impedes human societies through the negative impacts on water and agricultural resources and subsequently the economy. One of the methods of drought monitoring is the use of drought indices such as SPI. In this study, SPI index was used to study drought over the period 2001 to 2016. The SPI index is purely based on precipitation, so it is important to select a proper precipitation source to extract the SPI index at different time scales. Synoptic stations, due to lack of proper distribution and high statistical gaps, cannot be a reliable source of precipitation in this type of research, so global precipitation datasets having high spatial and temporal resolution can be used as a viable alternative to ground stations, in this study the Era-interim precipitation product, which is the product of the European Center for Medium range Weather Forecast was used. Initial results indicated that the Era-interim precipitation product could be used as a viable alternative to synoptic stations nationwide. Therefore, this precipitation product was used to assess the drought situation in the country. The study of drought status with respect to SPI indicated that with increasing SPI time scale dry and wet conditions became more severe so that mild dry and wet conditions in most in most month and years turned into severe dry and wet conditions.

One of the most important consequences of Climate Change is the changing of climatic variables and the effects on hydrological variables and water resources. Karaj Dam is one of the important sources of water and electrical energy for Tehran and Alborz province. Thus, diagnosis of affective factors on the water resources of upstream of this catchment and entered runoff to Karaj dam could be vital for planners and policy makers for the future periods. One of the best methods for diagnosing the effects of Climate Change on climatic and hydrological variables is Detection and Attribution with Optimal Fingerprint approach. In this research have been tried to detect and attribute the ALL, GHG and NAT signals by simulations from CanESM-2.0 model. Therefor every signal has been downscaled with MRQNBC method, and then simulated with SWAT calibrated model for selected signals for (1985-2011). At last those entered to optimal fingerprint method. By attention the results, just GHG signal (which shows the globe under the effects of Greenhouse gases without the other forcing has been detected and attributed and its scaling factor (β) got 0.76. While two other signals (ALL, NAT) haven’t been detected and attributed. In other words the changing of entered runoff to Karaj dam was very likely consonant with simulated runoff which affected from GHG signal only.

Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small. Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.
This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI. Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions. The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.
Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.