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In research on monitoring drought events, analysis is often carried out using a single period as a reference. On the other hand, changing this default period in drought calculations causes the drought index values obtained from research to differ. As a gap in the literature, this point highlights the necessity of investigating the effect of various time periods on drought characteristics. It underscores the need to propose a new concept and methodology to address this gap effectively. This research aims to analyze critical drought characteristics through dynamic time period scenarios. For the first time in the literature, drought indices and potential and critical characteristics were analyzed for various (dynamic) time periods. Drought analysis was carried out for 13 time period scenarios with 10-year intervals from a meteorological station in Durham (1872–2021) by changing the initial time condition using the Standardized Precipitation Index (SPI). The results showed that in addition to the similarities, there are significant differences between drought characteristics. For example, in some time period scenarios, a drought event was recorded during a specific period, while in other scenarios (S5–S7, S10–S13), no drought was detected during the same period, like in SPI 1. Additionally, for SPI 12, the drought duration varied significantly, lasting between 20 and 29 months, and for SPI 6, the drought duration varied between 3 and 13 months. Regarding the intensity, SPI 1 ranged between −0.89 and −1.33, indicating a 33% difference, and the SPI 3 intensity ranged between −1.08 and −1.91, indicating a 50% increase in intensity. This research significantly contributes to the field by providing a novel approach using dynamic time period scenarios to determine critical drought characteristics, offering valuable insights for water resource management, drought mitigation planning, and design purposes. [ABSTRACT FROM AUTHOR]

Evaluating drought is paramount in water resources management and drought mitigation plans. Drought indices are essential tools in this evaluation, which mainly depends on the time period of the original datasets. Investigating the effects of time periods is critical for a comprehensive understanding and evaluation of drought. Also, It holds particular significance for regions facing data availability challenges. The existing literature reveals a gap in drought assessment and comparison analysis using conventional methods based on drought indices only. This research proposes an innovative drought classification matrix to compare drought indices and spatial and temporal scenarios; the proposed matrix depends on any drought classification for comparison procedure. Furthermore, it aims to investigate the differences between several time period scenarios based on the proposed matrix and several statistical metrics (R2, CC, RMSE, HH, and RB) and determine the acceptable/minimum time period. The application of the proposed matrix and selection of an acceptable/minimum time period is presented to three different climates: Durham station in the United Kingdom, Florya station in Türkiye, and Karapinar station in Türkiye. The results show that the time period scenarios are able to catch the reference time period (RTP) scenario reasonably, with strong correlation and negative relative bias. The 10-year time period is sufficient as an acceptable/minimum time period for short timescales, such as meteorological drought. Conversely, for longer timescales, such as hydrological drought, a 20-year time period is the acceptable/minimum time period. The proposed matrix demonstrates a robust and powerful framework for comparison, making it applicable to various drought assessment scenarios globally. [ABSTRACT FROM AUTHOR]

In research on monitoring drought events, analysis is often carried out using a single period as a reference. On the other hand, changing this default period in drought calculations causes the drought index values obtained from research to differ. As a gap in the literature, this point highlights the necessity of investigating the effect of various time periods on drought characteristics. It underscores the need to propose a new concept and methodology to address this gap effectively. This research aims to analyze critical drought characteristics through dynamic time period scenarios. For the first time in the literature, drought indices and potential and critical characteristics were analyzed for various (dynamic) time periods. Drought analysis was carried out for 13 time period scenarios with 10-year intervals from a meteorological station in Durham (1872–2021) by changing the initial time condition using the Standardized Precipitation Index (SPI). The results showed that in addition to the similarities, there are significant differences between drought characteristics. For example, in some time period scenarios, a drought event was recorded during a specific period, while in other scenarios (S5–S7, S10–S13), no drought was detected during the same period, like in SPI 1. Additionally, for SPI 12, the drought duration varied significantly, lasting between 20 and 29 months, and for SPI 6, the drought duration varied between 3 and 13 months. Regarding the intensity, SPI 1 ranged between −0.89 and −1.33, indicating a 33% difference, and the SPI 3 intensity ranged between −1.08 and −1.91, indicating a 50% increase in intensity. This research significantly contributes to the field by providing a novel approach using dynamic time period scenarios to determine critical drought characteristics, offering valuable insights for water resource management, drought mitigation planning, and design purposes.

The study presents a daily water balance model with a focus on quantifying drought intensity and duration in different forest stands within the Level II monitoring sites in Saxony. The model requires climatic data input and various site and stand parameters, which mostly have physical meaning and can be measured. We estimated the van Genuchten soil parameters of the model by different pedotransfer functions. Water stress is assumed to occur when the relative extractable soil water (REW) or the ratio of real transpiration and potential transpiration or pressure head drops below a certain threshold. The model was not calibrated to test the robustness of physically based parameters but was validated with available soil moisture measurements at forest climate stations (grass vegetation) and inventory locations in various vegetation and climatic conditions with Kling-Gupta efficiencies > 0.5 at most of the sites. The model captures the dynamics of soil water depletion and recharge in a study period well. Day-to-day estimates of water balance components allow us to calculate the duration and intensity of drought events and derive stress indices. A dendro-ecological application is presented: a retrospective analysis of the effects of drought on radial tree growth. Some limitations and potential of applications of the model are discussed.

The yield of winter wheat in Shandong Province is of great significance for ensuring regional and national food security. To reduce the risk of production loss, the WOFOST model was used to simulate the winter wheat growth to obtain the quantitative and dynamic information. Based on the observational data, a moisture control experiment and the trial and error method, the applicability and drought simulation of the WOFOST model were evaluated for winter wheat growth. For the simulation of the seedling period, flowering period, and maturity period of winter wheat in Shandong Province, the R2 were 0.95, 0.69, and 0.68 respectively. The D-index were 0.99, 0.89, and 0.86 respectively. The mean absolute error (mAE) were 1.3, 4.3, and 4.1 respectively. And the nRMSE were 0.65%, 4.3%, and 3.2%, respectively. For the yield simulation, the R2, D-index, mean relative error (mRE), and nRMSE were 0.48, 0.82, 10.5% and 12.8%, respectively. For the yield simulation under drought stress, the R2, D-index, mRE, and nRMSE were 0.77, 0.93, 7.1%, and 7.4%, respectively. An evaluation index system was built through four different degrees of drought treatment between the jointing period and the flowering period. With the aggravation of drought, the growth indicators about the total above ground production (TAGP), maximum leaf area index (MAXLAI), total dry weight of leaves (TWLV), and total dry weight of stems (TWST) decreasing by 13.6–41.0%, 37.8–56.5%, 19.4–42.1%, and 20.3–51.2%, respectively. The results showed that this model could adequately simulate the formation process of yield under both normal and drought conditions.

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Many drought indicators with different difficulties have been applied in numerous climatic zones. The reconnaissance drought index, which is based on precipitation and potential evapotranspiration, is considered a powerful weather drought index in arid and semi-arid zones. The effective reconnaissance drought index, which is a modification of the reconnaissance drought index, is suggested to enhance ability of the reconnaissance drought index to evaluate agricultural drought. The estimation of this index is based on two climatic variables which are the potential evapotranspiration (PET) and effective precipitation. The FAO Penman–Monteith method is considered the reference equation to evaluate the potential evapotranspiration; however, it is difficult to apply in regions with shortage weather data due to the requirement for a large number of climatic variables. Consequently, this research is applied Hargreaves, Blaney–Criddle, and Thornthwaite methods to assess the impact of the effective precipitation and potential evapotranspiration estimation methods, elevation, and climatic conditions on the effective reconnaissance drought index as well as investigating the correlation between the reconnaissance drought index and the effective reconnaissance drought index. Data from 13 weather stations, over the time interval between 1979 and 2014, cover different elevations, and weather environments within the Greater Zab River Basin, North Iraq, has been selected. The obtained results indicated that there is no important effect on drought severity assessment (at 100% of weather stations) were detected by using the considered potential evapotranspiration methods at different elevations for different climate conditions. However, there is a clear effect for different the effective precipitation and potential evapotranspiration techniques at diverse altitudes and climatic conditions on the aridity evaluation that is assessed by effective reconnaissance drought index (at about 50% of the considered stations). Consequently, concern has to be paid to the effective precipitation and potential evapotranspiration evaluation methods, particularly at high elevations; this is because applying a range of approaches may cause errors in the water resources availability predictions. [ABSTRACT FROM AUTHOR]

In order to relieve the water shortage for irrigation in North China, an adaptive real-time irrigation scheduling based on weather forecast and drought evaluation was developed. First, drought degree was evaluated into five ranks in crop growing seasons, and then the irrigation threshold was decided based on the chosen drought evaluation indexes, finally using field water balance principle and soil moisture simulation technology, an adaptive real-time irrigation scheduling was established to adapt to climate changes and actual rainfall based on winter wheat filed experiments from 2011 to 2014 in this study. Results showed that the irrigation water depths in 2013-2014 provided by the traditional irrigation schedule was 266 mm, which was much higher than that provided by adaptive real-time irrigation schedule (177 mm). Though the yield and water productivity provided by adaptive real-time irrigation were not the highest among different irrigation treatments, it is more suitable for the application adaptive real-time irrigation in North China to cope with the limited water resources of the irrigation districts. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that usually occurs in various areas of the northeastern part of Thailand and it has a major impact on agriculture. The main objective of this studywas to apply remote sensing technology and the Standardized Vegetation Index (SVI) for the evaluation of drought in the aforementioned areas. For the implementation, data of the Normalized Difference Vegetation Index (NDVI) from the Terra/MODIS satellite was utilized for the analysis in order to examine the drought areas due to the change of the vegetation conditions by the SVI within a period of three years: 2014, 2015, 2106. According to the study, it was found that the worst drought was in 2016, followed by the years 2014 and 2015, respectively. Furthermore, for the reliability of this technique, the analysis results from the SVI to find the statistical relationship with the rainfall in the target areas was completed. The results of both sets of the data showed a high relationship in all three years (2014, R2 = 0.83; 2015, R2 = 0.88 and 2016, R2 = 0.97). Thus, it could be concluded that examining the drought situation by remote sensing technology and the SVI at different periods in the areas of the Lower Northeastern region of Thailand could identify the forms of drought effectively. [ABSTRACT FROM AUTHOR]

Focusing on the shortages of moisture estimation and time scale in the self-calibrating Palmer drought severity index (scPDSI), this study proposed a new Palmer variant by introducing the Variable Infiltration Capacity (VIC) model in hydrologic accounting module, and modifying the standardization process to make the index capable for monitoring droughts at short time scales. The performance of the newly generated index was evaluated over the Yellow River Basin (YRB) during 1961⁻2012. For time scale verification, the standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) at a 3-month time scale were employed. Results show that the new Palmer variant is highly correlated with SPI and SPEI, combined with a more stable behavior in drought frequency than original scPDSI. For drought trend detection, this new index is more inclined to reflect comprehensive moisture conditions and reveals a different spatial pattern from SPI and SPEI in winter. Besides, two remote sensing products of soil moisture and vegetation were also employed for comparison. Given their general consistent behaviors in monitoring the spatiotemporal evolution of the 2000 drought, it is suggested that the new Palmer variant is a good indicator for monitoring soil moisture variation and the dynamics of vegetation growth.

The yield of winter wheat in Shandong Province is of great significance for ensuring regional and national food security. To reduce the risk of production loss, the WOFOST model was used to simulate the winter wheat growth to obtain the quantitative and dynamic information. Based on the observational data, a moisture control experiment and the trial and error method, the applicability and drought simulation of the WOFOST model were evaluated for winter wheat growth. For the simulation of the seedling period, flowering period, and maturity period of winter wheat in Shandong Province, the R 2 were 0.95, 0.69, and 0.68 respectively. The D-index were 0.99, 0.89, and 0.86 respectively. The mean absolute error (mAE) were 1.3, 4.3, and 4.1 respectively. And the nRMSE were 0.65%, 4.3%, and 3.2%, respectively. For the yield simulation, the R 2 , D-index, mean relative error (mRE), and nRMSE were 0.48, 0.82, 10.5% and 12.8%, respectively. For the yield simulation under drought stress, the R 2 , D-index, mRE, and nRMSE were 0.77, 0.93, 7.1%, and 7.4%, respectively. An evaluation index system was built through four different degrees of drought treatment between the jointing period and the flowering period. With the aggravation of drought, the growth indicators about the total above ground production (TAGP), maximum leaf area index (MAXLAI), total dry weight of leaves (TWLV), and total dry weight of stems (TWST) decreasing by 13.6-41.0%, 37.8-56.5%, 19.4-42.1%, and 20.3-51.2%, respectively. The results showed that this model could adequately simulate the formation process of yield under both normal and drought conditions., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Drought is one of the main disasters causing agricultural production losses. Accurate and effective agricultural drought monitoring is of great significance to reduce agricultural production losses. In this study, the standardized soil moisture index for agricultural drought evaluation was established by using the historical time series of soil moisture. Based on the index, the temporal and spatial distribution of drought events in the Luanhe River Basin from 2002 to 2019 were analyzed, and the agricultural drought was quantitatively evaluated. The results showed that soil moisture of most grid units in the Luanhe River Basin obeyed normal distribution during the study period, and that the soil moisture of a few grid units obeyed generalized extreme distribution. The changes of drought and flood in each grid unit had good temporal consistency, that is, the changes of drought and flood was consistent. The changes of drought and flood in the middle of the basin was relatively significant, while the agricultural drought generally showed a trend of reduction. The spatial distribution of agricultural drought severity was not obvious. Relatively speaking, the drought characteristics (the frequency, duration and intensity of drought) were higher in the middle and northwest of the basin and lower in the southeast. The results could provide a reference for agricultural drought prediction and the formulation of drought prevention and mitigation measures in the Luanhe River Basin.

Focusing on the shortages of moisture estimation and time scale in the self-calibrating Palmer drought severity index (scPDSI), this study proposed a new Palmer variant by introducing the Variable Infiltration Capacity (VIC) model in hydrologic accounting module, and modifying the standardization process to make the index capable for monitoring droughts at short time scales. The performance of the newly generated index was evaluated over the Yellow River Basin (YRB) during 1961–2012. For time scale verification, the standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) at a 3-month time scale were employed. Results show that the new Palmer variant is highly correlated with SPI and SPEI, combined with a more stable behavior in drought frequency than original scPDSI. For drought trend detection, this new index is more inclined to reflect comprehensive moisture conditions and reveals a different spatial pattern from SPI and SPEI in winter. Besides, two remote sensing products of soil moisture and vegetation were also employed for comparison. Given their general consistent behaviors in monitoring the spatiotemporal evolution of the 2000 drought, it is suggested that the new Palmer variant is a good indicator for monitoring soil moisture variation and the dynamics of vegetation growth. [ABSTRACT FROM AUTHOR]