Flood in the South-West of Iran in 2019; Causes, Problems, Actions and Lesson Learned

A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine

Water resources are vital to the survival of living organisms and contribute substantially to the development of various sectors. Climatic diversity, topographic conditions, and uneven distribution of surface water flows have made reservoirs one of the primary water supply resources in Iran. This study used Landsat 5, 7, and 8 data in Google Earth Engine (GEE) for supervised monitoring of surface water dynamics in the reservoir of eight Iranian dams (Karkheh, Karun-1, Karun-3, Karun-4, Dez, UpperGotvand, Zayanderud, and Golpayegan). A novel automated method was proposed for providing training samples based on an iterative K-means refinement procedure. The proposed method used the Function of the Mask (Fmask) initial water map to generate final training samples. Then, Support Vector Machines (SVM) and Random Forest (RF) models were trained with the generated samples and used for water mapping. Results demonstrated the satisfactory performance of the trained RF model with the samples of the proposed refinement procedure (with overall accuracies of 95.13%) in comparison to the trained RF with direct samples of Fmask initial water map (with overall accuracies of 78.91%), indicating the proposed approach’s success in producing training samples. The performance of three feature sets was also evaluated. Tasseled-Cap (TC) achieved higher overall accuracies than Spectral Indices (SI) and Principal Component Transformation of Image Bands (PCA). However, simultaneous use of all features (TC, SI, and PCA) boosted classification overall accuracy. Moreover, long-term surface water changes showed a downward trend in five study sites. Comparing the latest year’s water surface area (2021) with the maximum long-term extent showed that all study sites experienced a significant reduction (16–62%). Analysis of climate factors’ impacts also revealed that precipitation (0.51 ≤ R2 ≤ 0.79) was more correlated than the temperature (0.22 ≤ R2 ≤ 0.39) with water surface area changes.

Identifying the Potential Dam Sites to Avert the Risk of Catastrophic Floods in the Jhelum Basin, Kashmir, NW Himalaya, India

In September 2014, Kashmir witnessed a catastrophic flood resulting in a significant loss of lives and property. Such massive losses could have been avoided if any structural support such as dams were constructed in the Jhelum basin, which has a history of devastating floods. The GIS-based multicriteria analysis (MCA) model provided three suitability zones for dam locations. The final suitable dam sites were identified within the highest suitability zone based on topography (cross-sections), stream order, high suitable zone, minimum dam site interval, distance from roads, and protected area distance to the dam site. It was discovered that 10.98% of the total 4347.74 km2 area evaluated falls in the high suitability zone, 28.88% of the area falls in the medium suitability zone, and 60.14% of the area falls in the low suitability zone. Within the study area, four viable reservoir sites with a holding capacity of 4,489,367.55 m3 were revealed.

How much the Iranian government spent on disasters in the last 100 years? A critical policy analysis

Background

During the past 20 years, Iran has been experiencing a significant increase in the occurrence of disasters mainly due to the emergence of anthropogenic climate change. This paper aims at analyzing the trend of national budget allocation in Iran over the last 100 years to evaluate the focus of the Iranian state on the four phases of Preparedness, Mitigation, Response, and Recovery and propose modifications.

Methods

It is used a critical policy analysis with what’s the problem represented approach. In this approach is focused on problematization and policy gaps. The most important policy statement in any government is the budget. During the first screening, 1028 regulations and laws were found from 1910 to 2020. After full text screening, 494 regulations and laws related to budget allocation to disasters were analyzed.

Results

The Iranian government has spent around 29 billion USD on disasters during the last 100 years. Droughts, earthquake and flood have costs the government more than other disasters, accounting for more than 14, 6.9, and 6.1 billion USD, respectively, in the allocated budget. Most of the Iranian government expenditure during the last 100 years on various disasters such as drought, flood, earthquake, and COVID-19 has been spent on involuntary costs including Response and Recovery. Mitigation and Preparedness are the two critical disaster management phases with very small shares of national budgeting.

Conclusions

From policy audit and policy gaps it is concluded that Iranian governments during last 100 years, problematized the issue of “disasters strike” and not “disasters’ risks”. In time of disasters, governments tried to solve the issues or impacts of disasters with budgeting to response and recovery. Nevertheless, disasters’ prevention or mitigation or preparedness was not a problem for Iranian governments from 1920 to 2020.