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
It is predicted that drought will be more frequent and sustained in the future, which may affect the decline of rubber tree production. Therefore, it is critical to research some of the variables ...related to the drought-resistance mechanism of the rubber tree. As a result, it can be used to guide the selection of new rubber drought-resistance clones. The goal of this study was to identify drought-resistance mechanisms in rubber clones from the high drought factor index (DFI) group using ecophysiological and biochemical variables. The treatments consist of two factors, namely water deficit and contrasting clones based on the DFI variable. The first factor consisted of three levels, namely normal (fraction of transpirable soil water (FTSW) > 0.75), severe water deficit (0.1 < FTSW < 0.20), and recovery condition (FTSW > 0.75 after rewatering). The second factor consisted of seven clones, namely clones G239, GT1 (low DFI), G127, SP 217, PB 260 (moderate DFI), as well as G206 and RRIM 600 (high DFI). RRIM 600 had the highest DFI among the other clones as a drought-tolerance mechanism characteristic. Furthermore, clones RRIM 600, GT1, and G127 had lower stomatal conductance and transpiration rate than drought-sensitive clone PB 260. As a result, as drought avoidance mechanisms, clones RRIM 600, GT1, and G127 consume less water than clone PB 260. These findings indicated that clone RRIM 600 was a drought-resistant clone with drought tolerance and avoidance mechanisms.
The Austrian pine (Pinus nigra), an introduced conifer in Hungary, forms a highly flammable vegetation type. The fire risk of such stands was examined using McArthur's empirical forest fire danger ...model. Our study focused on the effects of temperature and wind speed on fire behaviour. By keeping the input parameters of the model constant while changing temperature andwind speed within a specified interval the resulting fire danger index (FDI) and fire behaviour were examined. The applied fixed parameters were: 30 °C temperature, 30% relative humidity, 30 km h-1 wind speed, 30 degree of slope and drought factor value 10. The annual trends of the Byram-Keetch drought index (BKDI) and the drought factor were also calculated. Our results show that increasing temperature and wind speed raises the FDI, flame height, rate of fire spread (ROS) and spotting distance. The amount of fuel does not influence the FDI, but increasing the amount promotes the ROS and raises the flame height. Wind speed was the most important factor in the ROS. A serious fire risk of these plantations was determined. The reliability of McArthur's model was proved by comparison of our results with experimental laboratory data based on literature.
Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially ...burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data is needed about the weather. Therefore, we need an algorithm that can predict the dryness factor. So, the most significant fire potential can be predicted during the dry season. Moreover, daily prediction of the dry season is needed each day to conduct the best action then a qualified preventive measure can be carried out. The method used in this study is the backpropagation algorithm which has functions for calculating, testing and training the drought factors. By using empirical data, some data are trained and then tested until it can be concluded that 100% of the data already well recognized. Furthermore, some other data tested without training, then the result is 60% of the data match. In general, this algorithm shows promising results and can be applied more to complete several variables supporters.
Photochemical Response Analysis on Drought Stress for Red Pepper (Capsiumannuum L.) Yoo, S.Y., Hankyong National University, Ansung, Republic of Korea; Lee, Y.H., Hankyong National University, Ansung, Republic of Korea; Park, S.H., Hankyong National University, Ansung, Republic of Korea ...
Korean Journal of Soil Science and Fertilizer,
12/2013, Letnik:
46, Številka:
6
Journal Article
Odprti dostop
The aim of this study is to determine the drought stress index through photochemical analysis in red pepper (Capsiumannuum L.). The photochemical interpretation was performed in the basis of the ...relation between Kautsky effect and Photosystem II (PSII) following the measurement of chlorophyll, pheophytin contents, and CO2 assimilation in drought stressed 5-week-old red pepper plants. The CO2 assimilation rate was severely lowered with almost 77% reduction of chlorophyll and pheophytin contents at four days after non-irrigation. It was clearly observed that the chlorophyll fluorescence intensity rose from a minimum level (the O level), in less than one second, to a maximum level (the P-level) via two intermediate steps labeled J and I (OJIP process). Drought factor index (DFI) was also calculated using measured OJIP parameters. The DFI was -0.22, meaning not only the initial inhibition of PSII but also sequential inhibition of PSI . In real, most of all photochemical parameters such as quantum yield of the electron transport flux from Quinone A (QA) to Quinone B (QB), quantum yield of the electron transport flux until the PSI electron acceptors, quantum yield of the electron transport flux until the PSI electron acceptors, average absorbed photon flux per PSII reaction center, and electron transport flux until PSI acceptors per cross section were profoundly reduced except number of QA reducing reaction centers (RCs) per PSII antenna chlorophyll (RC/ABS). It was illuminated that at least 6 parameters related with quantum yield/efficiency and specific energy fluxes (per active PSII RC) could be applied to be used as the drought stress index. Furthermore, in the combination of parameters, driving forces (DF) for photochemical activity could be deduced from the performance index (PI) for energy conservation from photons absorbed by PSII antenna until the reduction of PSI acceptors. In conclusion, photochemical responses and their related parameters can be used as physiological DFI.
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