Drought is one natural disaster with the greatest impact worldwide. Southern Africa (SA) is susceptible and vulnerable to drought due to its type of climate. In the last four decades, droughts have ...occurred more frequently, with increasing intensity and impacts on ecosystems, agriculture, and health. The work consists of a systematic literature review on the drought regime’s characteristics in the SA under current and future climatic conditions, conducted on the Web of Science and Scopus platforms, using the PRISMA2020 methodology, with usual and appropriate inclusion and exclusion criteria to minimize/eliminate the risk of bias, which lead to 53 documents published after the year 1987. The number of publications on the drought regime in SA is still very small. The country with the most drought situations studied is South Africa, and the countries with fewer studies are Angola and Namibia. The analysis revealed that the main driver of drought in SA is the ocean–atmosphere interactions, including the El Niño Southern Oscillation. The documents used drought indices, evaluating drought descriptors for some regions, but it was not possible to identify one publication that reports the complete study of the drought regime, including the spatial and temporal distribution of all drought descriptors in SA.
Dehydration affects the photosynthetic apparatus. The impact of dehydration on photosynthesis was assessed in twelve Mediterranean species representing different growth forms. Rapid and slow ...dehydration experiments were conducted to (1) compare the impact of water stress among species and growth forms, (2) rank species according to their drought tolerance. Rapid dehydration reduced the electron transport up to PSI, the reduction being linearly related to leaf relative water content (RWC), except for the deciduous species. Specific energy fluxes per reaction center and maximum photochemical activity of PSII remained relatively stable until 10-30% RWC. The modification pattern of the studied parameters was similar for all the growth forms. Slow rehydration increased specific energy fluxes and decreased quantum yields. The dehydration pattern was similar among growth forms, while the recovery pattern was species-specific. Drought tolerance ranking through drought factor index was relatively modified with the integrated biomarker response method.
The main objective of this study was to evaluate the effects of drought and re-watering on 10 varieties of barley (
Hordeum vulgare L.) originating from Morocco. Five varieties obtained from the ...National Institute of Agricultural Research (INRA) of Morocco and five landraces (local varieties defined by high stress tolerance, high yield stability, an intermediate yield and low-input demand) collected at five localities in the south of Morocco were used in the present study. After 2 weeks of growth, drought stress was initiated by withholding water for 2 weeks followed by 1 week of re-watering. The polyphasic OJIP fluorescence transient was used to evaluate photosystem II (PSII) criteria at the end of the first week of drought stress (moderate drought), at the end of the second week (severe drought) and the end of the recovery phase. Drought and re-watering had little effect on the maximum quantum yield of primary photochemistry
φ
Po(=
F
V/
F
M). The photosynthetic performance index (PI) is the product of an antenna, reaction center and electron transport dependent parameter. It revealed differences between varieties as a function of drought and re-watering. For the screening for drought stress tolerance, changes in the PI during a 2-week drought stress treatment were analysed and a new parameter was defined: the drought factor index (DFI)
=
log(PI
week
1
/PI
control)
+
2
log(PI
week
2
/PI
control). The DFI of the tested varieties correlated with their drought tolerance. Another parameter that was analysed was the relative water content. It decreased during the drought stress treatment varying between 61% and 78.2% at the end of the drought period. During the subsequent recovery period, it increased in a species-dependent manner (65.1–94.1%). A third parameter studied were changes in the initial fluorescence rise. The fluorescence rise during the first 300
μs (L-band) can give information on the energetic connectivity between PSII units whereas changes in the rise during the first 2
ms (K-band) offer information on developing limitations on the donor side of PSII. Changes in respectively the L and K-bands of the fluorescence transients OJIP were shown to have predictive value with respect to the vitality of leaves and the tolerance of the varieties to drought stress.
► We screened 20 induced mutants of sesame (Sesamum indicum L.) for drought tolerance. ► Chlorophyll a fluorescence, leaf temperature and stomatal conductance were evaluated. ► The performance index ...was more sensitive to drought stress than the quantum yield of photochemistry. ► Drought factor index (DFI) is proposed in this work to screen for improved drought tolerance.
Drought is one of the major constraints limiting crop productivity in African Sahel. The aim of this study was to select mutant sesame (Sesamum indicum L.) lines with improved levels of drought resistance. Twenty-one M4-M5 sesame lines of unknown drought tolerance, and their three parental sources with well-known and contrasting drought tolerance levels were evaluated at the vegetative stage in a factorial pot experiment, using a completely randomized design with three replicates. After 2 weeks of growth, water was withheld for 16 days as drought stress treatment. Chlorophyll a fluorescence data, as well as stomatal conductance and flag leaf temperature were recorded during the stress period. Recorded chlorophyll a fluorescence transients were analyzed by the JIP-test to translate stress-induced damage in these transients to changes in biophysical parameters allowing quantification of the energy flow through the photosynthetic apparatus. Large genotypic differences in the extent to which drought stress affected chlorophyll a fluorescence transients were observed. Drought stress reduced the performance index and stomatal conductance, and increased flag leaf temperature but had little effect on maximum quantum yield of primary photochemistry. A drought factor index is proposed in this work to screen for improved drought tolerance in twenty-one M4-M5 sesame lines. Mutant lines shi165, lc162, mc112, lc164, icn115, icn141, mt169, dwf172 and cc102 exhibited drought factor index values superior to those of the known drought tolerant cultivars Birkan and 38-1-7. A significant and negative relationship was found between the drought factor index and the leaf temperature index. Finally, we succeeded in obtaining drought tolerant lines with good secondary traits by using mutagenesis and chlorophyll fluorescence technique.
•The original drought index KBDI needs improvement to cover all geo-climatic settings.•Integrating soil-hydrological properties improves fire danger prediction.•Groundwater table dynamics influence ...topsoil moisture, hence the drought index.•Identification of critical groundwater depth helps forest fire management.
In this paper, we discuss how an existing empirical drought index, i.e. the Keetch–Byram Drought Index (KBDI) that is commonly used for assessing forest fire danger, has been adjusted and modified for improved use in tropical wetland ecosystems. The improvement included: (i) adjustment of the drought factor to the local climate, and (ii) addition of the water table depth as a dynamic factor to control the drought index. We distinguished three different indices, the original Keetch–Byram Drought Index, the adjusted KBDI (KBDIadj) that represents the original drought index, but including local climate information, and the modified KBDI (mKBDI) that considers both local climate information, and soil and hydrological characteristics. The mKBDI was developed and tested in a wetland forest of South Sumatra (Indonesia) from April 2009 to March 2011. During this period, hydrometeorological data were monitored and used to calculate the KBDI, KBDIadj, and mKBDI. First, mKBDI was calibrated using observed soil moisture that was converted to an observed drought index (DIobs). The results indicate that performance of the mKBDI is encouraging based on the following: (i) its pattern followed the dynamics of DIobs, (ii) prediction of frequency of fire danger classes, and (iii) statistically criteria. The mKBDI clearly outperformed KBDI and KBDIadj. Furthermore, we found a critical water table depth when it reaches maximum fire danger (0.85m for the wetland forest of South Sumatra) below which danger does not increase anymore. The mKBDI could be more widely applied, if pedotransfer functions are developed that link easily obtainable soil properties to the parameters of the water table factor. Our findings encourage land use planners, water managers and stakeholders (e.g. forest estate owners) to integrate local climate information, and soil and hydrological characteristics into the Keetch–Byram Drought Index to better predict fire danger, particularly in tropical wetland ecosystems.
Context
Wildfires are common in localities where there is sufficient productivity to allow the accumulation of biomass combined with seasonality that allows this to dry and transition to a flammable ...state. An understanding of the conditions under which vegetated landscapes become flammable is valuable for assessing fire risk and determining how fire regimes may alter with climate change.
Objectives
Weather based metrics of dryness are a standard approach for estimating the potential for fires to occur in the near term. However, such approaches do not consider the contribution of vegetation communities. We aim to evaluate differences in weather-based dryness thresholds for fire occurrence between vegetation communities and test whether these are a function of landscape aridity.
Methods
We analysed dryness thresholds (using Drought Factor) for fire occurrence in six vegetation communities using historic fires events that occurred in South-eastern Australia using logistic regression. These thresholds were compared to the landscape aridity for where the communities persist.
Results
We found that dryness thresholds differed between vegetation communities, and this effect could in part be explained by landscape aridity. Dryness thresholds for fire occurrence were lower in vegetation communities that occur in arid environments. These communities were also exposed to dry conditions for a greater proportion of the year.
Conclusions
Our findings suggest that vegetation driven feedbacks may be an important driver of landscape flammability. Increased consideration of vegetation properties in fire danger indices may provide for better estimates of landscape fire risk and allow changes to fire regimes to be anticipated.
The McArthur Forest Fire Danger Index used in Australia for operational fire warnings has a component representing fuel availability called the Drought Factor (DF). The DF is partly based on soil ...moisture deficit, calculated as either the Keetch‐Byram Drought Index (KBDI) or Mount's Soil Dryness Index (MSDI). The KBDI and MSDI are simplified water balance models driven by observation based daily rainfall and temperature. In this work, gridded KBDI and MSDI analyses are computed at a horizontal resolution of 5 km and are verified against in‐situ soil moisture observations. Also verified is another simple model called the Antecedent Precipitation Index (API). Soil moisture analyses from the Australian Community Climate and Earth System Simulator (ACCESS) global Numerical Weather Prediction (NWP) system as well as remotely sensed soil wetness retrievals from the Advanced Scatterometer (ASCAT) are also verified. The verification shows that the NWP soil wetness analyses have greater skill and smaller biases than the KBDI, MSDI and API analyses. This is despite the NWP system having a coarse horizontal resolution and not using observed precipitation. The average temporal correlations (root mean square difference) between cosmic ray soil moisture monitoring facility observations and modeled or remotely sensed soil wetness are 0.82 (0.15 ±0.02), 0.66 (0.33 ±0.07), 0.77 (0.20 ±0.03), 0.74 (0.22 ±0.03) and 0.83 (0.18 ±0.04) for NWP, KBDI, MSDI, API and ASCAT. The results from this study suggests that analyses of soil moisture can be greatly improved by using physically based land surface models, remote sensing measurements and data assimilation.
Key Points
Simple water balance models have less skill than weather prediction system soil moisture analyses
Weather prediction system soil moisture analyses are unbiased and capture the seasonal variations
The remotely sensed ASCAT soil wetness product is of good quality
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