Introduction

Drought is one of the most important climate hazards that has widespread impacts on water resources, agriculture and ecosystems. Monitoring and assessing this phenomenon requires the use of valid indicators and reliable data. Preventive measures and planning against drought are of great importance in reducing its effects, which requires the use of sufficient knowledge in drought forecasting. Recently, remote sensing and techniques developed based on satellite images have been able to provide appropriate estimates of drought on a regional scale. Currently, satellite images are regularly obtained from the Earth's surface with high spatial resolution and can provide valuable spatial data. The advantages of using remote sensing over meteorological methods include increased sampling points, wider coverage area, higher temporal resolution and lower cost.

Using drought indices based on remote sensing data, it is possible to examine spatial patterns of drought. However, these indices are geographically or temporally specific and their accuracy decreases when used in other regions and times. In this regard, the main objective of this study is to investigate the spatial and temporal distribution patterns of drought and determine the performance of remote sensing indices in the spring and summer seasons in Chaharmahal and Bakhtiari province.

Material and Methods

Chaharmahal and Bakhtiari Province plays a key role in providing the country's water resources, as it is the headwaters of the Karun and Zayandeh Rood rivers. This makes accurate and timely monitoring of drought in the province essential. This study, along with validating satellite image precipitation data, examines the correlation of each satellite index with the Standardized Precipitation Index (SPI), a global standard index for drought assessment. In this study, a set of indices based on remote sensing data, including the Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Plant Health Index (VHI), was used to assess the drought situation in Chaharmahal and Bakhtiari Province. These indices were calculated using MODIS sensor images on a seasonal scale and for the period 2000 to 2023 for 33 stations. In addition, evaluated IMERG satellite precipitation data were also used. The IMERG data is a satellite precipitation dataset with a spatial resolution of 0.1°, produced by combining data from the TRMM and GPM satellites

Results and Discussion

The results of the assessment of the accuracy of IMERG precipitation data showed that the correlation of these data is high, between 0.83 and 0.96. These results indicate that IMERG precipitation satellite data can be used as an acceptable source for drought monitoring. The results also showed that, based on the spring VCI index, which is highly sensitive to changes in vegetation cover, the year 2000 was the driest year, with about 78 percent of the province's area affected by drought, while in 2020, about 88 percent of the province was without drought. The TCI index, which mainly reflects temperature conditions and heat stress, showed that in years with adequate precipitation, the index value increased due to a decrease in land surface temperature (such as 2019). In contrast, in dry years such as 2008 and 2021, TCI values decreased, indicating an intensification of the effect of drought through increased heat stress.The quarterly SPI index in spring showed the highest significant correlation with the TCI, VHI and VCI indices (0.85, 0.81 and 0.65, respectively), indicating the effect of temperature and short-term precipitation in determining the health and greenness of vegetation in spring. In summer, the highest correlation was related to the twelve-month and six-month SPI with the VCI index because the effect of precipitation on vegetation appears with a time lag. Therefore, TCI and VHI indices in spring and VCI in summer can provide a more accurate and complete picture of the vegetation response to spring precipitation in the province.

Conclusion

One of the important findings of this study is that the northern and eastern regions of the province are more vulnerable to drought. This finding can help provincial decision-makers prioritize areas of the province in terms of allocating financial resources to implement drought adaptation methods or preparing to manage farmers' protests. These areas can also be prioritized for water resource allocation or intra-provincial water transfer projects. In addition, these areas can be prioritized for drought resilience projects, such as planning for appropriate crop timing, changing cropping patterns, selecting drought-resistant species and modifying or replacing irrigation methods.