Population growth and rising water demand, climate change, severe droughts, and land-use changes are among the top severe issues in Iran. Water management in this country is sectoral and disintegrated. Each authority evaluates water based on its final intention and there is no commonplace indicator for evaluation programs. In this research, we used the Water Poverty Index (WPI) to map the status of water scarcity in a north-eastern province of Iran. Water poverty was measured based on five components of "Resources", "Access", "Capacity", "Use", and "Environment". The scores on each component were then aggregated using the weighted multiplicative function, assuming equal weights for all components. The overall WPI was evaluated to be 41.1, signaling an alarming and serious water poverty in the study area. Based on the results, Azadshahr (29.1) and Gorgan (61.6) districts had the worst and the best conditions among all cases, respectively. To better understand the importance of WPI components, four weighting alternatives were used; however, none of them resulted in a tangible improvement of WPI index. The cross-correlation between the components was also evaluated, with Access and Capacity showing significant results. Leaving out "Capacity", however, reduced WPI by 8.1. In total, "Access", "Capacity", and "Use" had the highest correlation with WPI, implying that any attempt to improve water poverty in the province must firstly tackle these issues. This study showed that WPI is an effective indicator of water scarcity assessment and could be used to make priorities for policy-making and water management.

A changing climate has been posing significant impacts on vegetation growth, especially in the Yellow River Basin (YRB) where agriculture and ecosystems are extremely vulnerable. In this study, the data for normalized difference vegetation index (NDVI) obtained from moderate-resolution imaging spectroradiometer (MODIS) sensors and climate data (precipitation and temperature) derived from the national meteorological stations were employed to examine the spatiotemporal differences in vegetation growth and its reaction to climate changes in the YRB from 2000‒2019, using several sophisticated statistical methods. The results showed that both NDVI and climatic variables exhibited overall increasing trends during this period, and positive correlations at different significant levels were found between temperature/precipitation and NDVI. Furthermore, NDVI in spring had the strongest response to temperature/precipitation, and the correlation coefficient of NDVI with temperature and precipitation was 0.485 and 0.726, respectively. However, an opposite situation was detected in autumn (September to November) since NDVIs exhibited the weakest responses to temperatures/precipitation, and the NDVI’s correlation with both temperature and precipitation was 0.13. This indicated that, compared to other seasons, increasing the temperature and precipitation has the most significant effect on NDVI in spring (March to May). Except for a few places in the northern, southern, and southwestern regions of the YRB, NDVI was positively correlated with precipitation in most areas. There was an inverse relationship between NDVI and temperature in most parts of the central YRB, especially in summer (June to August) and growing season (May to September); however, there was a positive correlation in most areas of the YRB in spring. Finally, continuous attention must be given to the influence of other factors in the YRB.

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