کمی سازی، چالش اولیه ارزیابی و مدیریت ریسک خشکسالی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکترای آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران.

2 استادیاردانشکده جغرافیای دانشگاه تهران، تهران، ایران

3 دانشیار گروه جغرافیای طبیعی، دانشکده جغرافیا، دانشگاه تهران. تهران، ایران.

چکیده

اختلاف در نتایج حاصله از کمّی‌سازی شدت خشکسالی به‌وسیله شاخص‌های متفاوت، می‌تواند برآورد آسیب‌پذیری، ریسک و مدیریت این مخاطره مهم را متأثر کند. با توجه به این، هدف تحقیق حاضر، مقایسه فضایی تفاوت شاخص‌های خشکسالی اقلیمی (RDI, DI, SPI, PNPI, ZSI, CZI, EDI, RDI, SPEI) و اثر این تفاوت‌‌ها در مطالعات ریسک با محاسبه شاخص مخاطره خشکسالی (DHI) بوده است. به‌ این منظور از داده‌های ماهانه و روزانه بارش و دمای بازتحلیل شبکه‌بندی (ERA5) با قدرت تفکیک 25/0×25/0 درجه استفاده شد. ابتدا درصد مساحت شدت شاخص‌ها استخراج و تفاوت توزیع فضایی آنها ترسیم، سپس به منظور بررسی اثر این تفاوت‌‌ها در ورودی محاسبه آسیب‌پذیری و ریسک، شاخص مخاطره خشکسالی براساس نتایج هر 9 شاخص محاسبه گردید. نتایج نشان داد که شاخص‌ها؛ الف) شدت‌های خشکسالی را متفاوت برآورد نموده‌اند. ب) این تفاوت‌ها در نقطه تعادل شاخص (محدوده نرمال) بیشتر و با افزایش شدت،‌ تفاوت‌ها کمتر شده ج) بیشترین ضریب تغییرات، در خشکسالی بسیارشدید و در مرتبه بعد در ترسالی بسیارشدید و خشکسالی شدید یا به عبارتی بی‌هنجاری‌های حدی بارش مشاهده گردید. د) برآورد شرایط حدی انتهایی در شاخص‌های EDI و SPEI مناسب نبود. ه) انحراف‌معیار گستره‌های شدت‌های منفی شاخص بیش از ترسالی بوده است. استفاده از شدت‌‌ها در محاسبه شاخص مخاطره خشکسالی، نتایج متفاوتی به‌دست داد. بنابراین طبق نتایج تحقیق استفاده هر یک از شاخص‌‌ها بدون توجه‌به محدویت‌‌‌ها، دربرآورد آسیب‌پذیری، خسارت و ریسک، منجر‌به نتایج متفاوتی خواهد شد. پیشنهاد می‌گردد شاخص‌ یا شاخص‌های مناسب و استاندارد با درنظر گرفتن شرایط جغرافیایی-اقلیمی کشور تعیین و در دیگر مطالعات مورد استفاده قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Quantification, The first challenge of drought risk assessment and management

نویسندگان [English]

  • Sousan Heidari 1
  • Mostafa Karimi 2
  • Ghasem Azizi 3
  • AliAkbar Shamsipour 3
1 Ph.D Student of Climatology, Department of Physical Geography, Faculty of Geography, University of Tehran, Iran.
2 Department of Physical Geography, Faculty of Geography, University of Tehran, Iran
3 Department of Physical Geography, Faculty of Geography, University of Tehran, Iran
چکیده [English]

1. Introduction

Defining and measuring drought is a difficult concept. Perhaps the most general definition of drought refers to "a specific period of abnormal rainfall in a specific area", in other words, a drought occurs when a significant water shortage is widespread in time and space. But there has long been disagreement over the details. Disputes about the concept of drought and the uncertainty of measuring its characteristics can be an obstacle to research and planning related to drought. This shows that the qualitative and quantitative analysis of drought is a challenging issue. Although several studies have been conducted in connection with the evaluation of drought indices around the world, the somewhat forgotten point in past studies is that drought indices sometimes do not provide the same results in estimating and quantifying the severity of drought. Using the estimates obtained from multiple indicators as input for other similar studies, evaluating and managing the vulnerability and risk caused by this hazard, which is of great interest, and using its results in planning and even allocating budget and insurance coverage, doubles the importance of the issue. Therefore, the present research, focusing on meteorological drought indicators as a basic drought monitoring indicator that requires limited variables (rainfall, and in some cases temperature) but is effective in other types of drought, tries to provide a general presentation (introduction, calculation details, required data) of the main meteorological drought indicators, to address the difference in estimation and quantification of the drought index.

2. Methodology

To evaluate the severity of drought for the period of 1979-2021, precipitation and temperature were used as their main variables on a daily and monthly scale according to the input of the indicators. The studied indicators were carried out in the selected year 2016-2017 when different regions of Iran were affected by drought and wet. It should be noted that the beginning of the annual period is considered from September. After developing the database, the drought indicators studied in the research were used to calculate the severity of the drought on an annual scale. Meteorological drought indices were classified into two categories of drought indices. In the last step, the drought hazard index was calculated, which expresses the severity of the drought event and is used as the first step to calculate the vulnerability and drought hazard index.

3. Results and Discussion

The 12-month SPI drought intensity values are lower than the results of RAI, DI, and ZSI indices, which is a significant point that is considered one of the disadvantages of this index. The estimation results of the ZSI index are almost equal to the RAI index, and the results of the CZI index are almost the same as the 12-month SPI index. The results of the EDI index showed that although this index can show the severity to some extent, it underestimates the severity of the annual drought events. In addition, this index has not exactly corresponded to the actual conditions caused by the drought. But this index is used to identify the length of the period and the start and end of the drought. which is a great advantage for this index. The spatial distribution of the RDI index estimate shows that half of Iran’s area had normal conditions in the year under review. In terms of space pattern, it is similar to the CZI index. The estimation of the SPEI index, similar to SPI and EDI indices, has not estimated the end of extreme conditions (very severe drought and wets).

Among the indicators, the coverage percentage of drought severity in the ZSI, CZI, and RAI indices are almost closer to each other. While the intensity of the EDI index is different from other indices. According to the amount of internal standard deviation, it seems that RAI, DI, and ZSI indices had a more appropriate estimation of drought conditions.

In addition to the mentioned cases, the comparison between the intensities of the investigated indicators also showed that the differences in normal conditions, droughts, and wets weak are greater and as the intensity increases, this difference decreases. The results of the drought hazard index resulting from the drought indices have had significant differences from each other.

4. Conclusion

According to the obtained results, it can be said that although the results of the three indices RAI, DI, and ZSI are closer to each other, the drought indices used (RAI, DI, SPI, PNPI, ZSI, CZI, EDI, RDI, SPEI) in the selected year, the drought intensities have been estimated differently. The difference in drought intensities was more in normal conditions, wet, and weak droughts. The standard deviation of the ranges of negative intensities of the index (drought) is more than that of drought conditions. Calculating the severity of drought hazard (DHI) using the intensity results obtained from the indicators showed a significant and sometimes extreme difference in this estimate. Estimation of drought intensity is used in other important studies such as calculating vulnerability, loss, and risk caused by drought. These differences and as a result the difference in results can affect environmental planning and management and economic considerations such as budget allocation and insurance coverage. Therefore, it is very important to check the accuracy of drought intensities estimation using indicators. Although there have been studies aimed at achieving a suitable index, an index that is approved and accepted in the diverse geographical-climatic area of the Country has not been introduced, which shows the need for a more comprehensive study in this field.

کلیدواژه‌ها [English]

  • Climatic Hazards
  • Drought Indices
  • Drought Severity
  • Iran
  • Precipitation Anomalies
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