Standardized Baseflow Drought Index Comparison to SPEI in High Baseflow Streams

Increased use of streamflow, most importantly minimum flow/baseflow data should be incorporated into drought indices, especially in regions where streams have a high baseflow component. Standard departure for streamflow (SDSF) and standard departure for baseflow (SDBF) were compared to the standardized precipitation and evapotranspiration index (SPEI) drought index values for 17 baseflow-dominated watersheds in the northern, central, and southern regions of Wisconsin. For each watershed, comparisons of SDSF, SDBF, and SPEI time series (for 1, 3, and 12-month time scales) were evaluated using correlation, run lengths of negative and positive values, sign congruence, and Mann-Kendall trend test. In general, SDBF performed better than SDSF for longer time scales. Trends of wetness appear to be distinguished earlier in SDBF compared to SDSF and SPEI-1, SPEI-3, and SPEI-12. The results of this study are consistent with regional statewide climate studies on precipitation and changes in precipitation intensity. This study highlights how standardized baseflow data are robust and compare to SPEI 12-month time scales.

A New Approach for Assessing the Drought Risk Management Capacity at the Municipal Level in Brazil

Long-term drought has occurred in all regions of Brazil, and its effects have been more intense in recent decades. Poor management of drought can exacerbate significant consequences, severely compromising water, food, energy, economic security, natural systems, and high fire risk that can affect biomes. It also slowly and indirectly affects the society living on vulnerable geographic space. This article discusses a methodology for assessing the drought risk management capacity at the municipal level in Brazil, and this new approach is statistically based using environmental data provided by the municipalities, from observational networks to data banks and remotely sensed data. It presents a method to indicate the steps of priority actions for the phases of drought management. It also characterized the long-term drought in Brazil (hydrological drought) between 1982 and 2022. The proposed approach provides a better understanding and the use of various drought indices to develop the most appropriate action steps for mitigation and adaptation. The final goal is to increase the resilience for those affected by drought. The work was developed based on the actions defined by the Brazilian Federal Government (Preparation, Prevention, Mitigation, Response, Recovery, and Restoration). This aims to improve the management of risk and disaster typified as drought in Brazil and to contribute with scientific knowledge to legislators regarding adaptation and resilience policies to drought extremes in parts of the country. At the end, we expect to highlight to managers and decision-makers the critical points in the government’s proactive and reactive actions to drought that need to be better managed.

Evaluating Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq: A Case Study

The study evaluated the Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq. It calculated the reference evapotranspiration, actual evapotranspiration, and amount of precipitation with effective rainfall to estimate the droughts indicators which are the Standard Precipitation Index (SPI), the Standard Precipitation and Evaporation Rain Index (SPEI) and Reconnaissance Drought Index RDI. The study indicated that the greatest decrease in river flow occurred from 2019-2021 to 2020-2021 due to increasing temperature in summer and decreasing precipitation in winter. This research evaluated a wet and drought indicating for planning and management of water resources to face changes in climate of future. The research showed the last years were years of drought according to the three indicators. SPI ranged from 0.5 to 1.5 in the rainy years, but it was -0.5 to -1 as moderately dry because in the middle of Iraq while in the south of Iraq was severely dry or extremely dry. SPEI of the study area ranged from -1.5 to -2.5 which means severely dry. The SPEI measures are negative values meaning the months and years were drier. RDi ranged from 0 to -1 was dry and moderately dry while some months and years are positive and will be wet through rainfall for ten years (2014-2023). From indices showed that the region was a drying study area due to the impact of climate change because of the reduction of precipitation and increase in temperature which caused a rise of evapotranspiration during the last few years.

A Contemporary Review on Drought Modeling Using Machine Learning Approaches

Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Itsbeginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughtsin the last few decades. Predicting future droughts is vital for framing drought management plans to sustainnatural resources. The data-driven modelling for forecasting the metrological time series prediction is becomingmore powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques havedemonstrated success in the drought prediction process and are becoming popular to predict the weather, especiallythe minimum temperature using backpropagation algorithms. The favourite ML techniques for weather forecastinginclude support vector machines (SVM), support vector regression, random forest, decision tree, logistic regression,Naive Bayes, linear regression, gradient boosting tree, k-nearest neighbours (KNN), the adaptive neuro-fuzzyinference system, the feed-forward neural networks, Markovian chain, Bayesian network, hidden Markov models,and autoregressive moving averages, evolutionary algorithms, deep learning and many more. This paper presentsa recent review of the literature using ML in drought prediction, the drought indices, dataset, and performancemetrics.

Changes in Germination and Seedling Traits of Sesame under Simulated Drought

Drought is considered one of the leading abiotic constraints to agricultural crop production globally.Present study was conducted to assess the effects of different drought treatments(viz.Control,10%PEG,and 20%PEG)on seed germination,germination indices,seedling traits,and drought tolerance indices of sesame.Our results showed that maximum reduction in the studied parameters was observed at higher PEG concentration(i.e.,20%PEG).As compared to control,the drought treatments viz.10%and 20%PEG decreased the values for germination indices,such as germination percentage,coefficient of variation of germination time,germination index,and seedling vigor index.Similarly,for seedling traits,the values were decreased for root length,shoot length,root shoot ratio,root fresh weight,shoot fresh weight,root dry weight and shoot dry weight under 10%and 20%PEG treatments significantly in comparison with control.Furthermore,relative to control,the values for drought tolerance indices,such as germination drought tolerance index,root length drought tolerance index,shoot length drought tolerance index,total seedling length drought tolerance index,root fresh weight drought tolerance index,shoot fresh weight drought tolerance index,total fresh weight drought tolerance index,root dry weight drought tolerance index,shoot dry weight drought tolerance index and total dry weight drought tolerance index were also reduced under 10%and 20%PEG treatments,respectively.Our results confirms that drought impact on seed germination and seedling traits could be quantified by using different indices which can further help to design drought adaptation and mitigation strategies.Based on these results it can be concluded that germination indices,seedling traits,and drought tolerance indices have great potential to simulate drought stress impacts on different crop traits thus they should be used in all kinds of stress related studies.

Stomatal conductivity, canopy temperature and evapotranspiration of maize (Zea mays L.) to water stress in Northeast China

The Northeast China Plain(NECP)is one of the main maize(Zea mays L.)production regions in China but is now subject to drought because of climate change and a rain-fed cultivation system.A two-year experiment was conducted in a typical maize cultivation region in the NECP to investigate the responses of plant physiological factors and evapotranspiration(ET)to water stresses at different growth stages.Results show that the responses of plant physiological factors to water stress can be divided into three levels based on soil water content(SWC)in the main root zone:when SWC was greater than 0.22 cm^(3)/cm^(3)(equivalent to 62%field capacity(FC)),stomatal conductivity(gs)and ET reached their highest values,and the canopy temperature(Tc)was close to the air temperature;when SWC was within 0.15-0.22 cm^(3)/cm^(3)(43%-62%FC),the gs and ET decreased,and Tc increased as SWC decreased;and when SWC was lower than 0.15 cm^(3)/cm^(3)(<43%FC),gs and ET reached their lowest values and Tc was greater than 1.2 times the air temperature.The ratio of canopy temperature to air temperature(RT),is closely related to stomatal conductivity and soil water content,and especially linearly related to crop water stress index(CWSI),and can be used as an alternative to CWSI for evaluating maize water stress because of easily data achieving and simple calculation processes.In a conclusion,RT of 1.2 can be used as an index to identify a severe water stress status,and maintaining SWC greater than 60%FC at the heading and grain-filling stages is important for supporting maize normal ET and growth in the study region.