Drought Patterns Research Articles

Integrated Drought Monitoring and Evaluation through Multi-Sensor Satellite-Based Statistical Simulation

To proactively respond to changes in droughts, technologies are needed to properly diagnose and predict the magnitude of droughts. Drought monitoring using satellite data is essential when local hydrogeological information is not available. The characteristics of meteorological, agricultural, and hydrological droughts can be monitored with an accurate spatial resolution. In this study, a remote sensing-based integrated drought index was extracted from 849 sub-basins in Korea’s five major river basins using multi-sensor collaborative approaches and multivariate dimensional reduction models that were calculated using monthly satellite data from 2001 to 2019. Droughts that occurred in 2001 and 2014, which are representative years of severe drought since the 2000s, were evaluated using the integrated drought index. The Bayesian principal component analysis (BPCA)-based integrated drought index proposed in this study was analyzed to reflect the timing, severity, and evolutionary pattern of meteorological, agricultural, and hydrological droughts, thereby enabling a comprehensive delivery of drought information.

Assessment of agricultural drought in Morocco based on a composite of the Vegetation Health Index (VHI) and Standardized Precipitation Evapotranspiration Index (SPEI)

According to IPCC, Morocco is a highly vulnerable country to extreme climate events, especially droughts; this will affect different socioeconomic sectors, mainly the agriculture sector. Droughts are controlled by the variability of precipitation and evapotranspiration but also not neglecting the effect of land surface conditions such as land surface temperature. In this present study, the remote sense observations MODIS Normalized Difference Vegetation Index (NDVI) and CMSAF Land Surface Temperature (LST) were used for calculating the Vegetation Health Index (VHI). The main advantage of remote sensing products is that they are reasonably efficient in terms of temporal and spatial coverage, and they are useful for the monitoring and assessment of drought in the near real-time. Furthermore, ERA5 Reanalysis-based SPEI is calculated. The goal of this study is to assess the spatial and temporal patterns of drought, this study offers the composite of SPEI and VHI drought monitoring obtained by plotting maps and graphs to show the monthly and annual variability of drought for the period 2000–2015 over the whole of Morocco. This monitoring can be used as a near real-time warning system in a changing climate.

Trend analysis of hydrological and water quality variables to detect anthropogenic effects and climate variability on a river basin scale: A case study of Iran

In recent years, climate changeability, hydrologic regime conditions, and human interventions have become crucial issues to be assessed. In this research, two annually recorded datasets were collected to analyse the change in the trend. The first set is comprised of precipitation, streamflow, and water quality variables including Total Dissolved Solids (TDS), pH, cation, and anion and the second one contains the mean groundwater level and agricultural water demand of four main stations of Shahpour River basin in the south of Iran. To recognize the fluctuating patterns, the Mann-Kendall Trend Test (MKTT), KPSS Stationary Test, and Pettit Homogeneity Test (PHT) of statistical methods were utilized at a 5% significance level. The Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) were subsequently employed to detect the hydrological drought patterns. According to the statistical analysis, the streamflow and water quality depicted intensive varying trends, while there were slight decreasing trends for the precipitation series. Afterward, the abrupt changing points were identified in the first and second datasets between the years 2004 to 2007. The results of this study clarified that human activity effects (as a major factor) and climate variability (as a minor factor) have been affecting the Shahpour River basin. These effects disrupt the water chemical balance (the relationship between cations and anions) and hydrological regimes (increasing drought drivers) and consequently menace the health of the watershed.

Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events

In recent decades, droughts, deforestation and wildfires have become recurring phenomena that have heavily affected both human activities and natural ecosystems in Amazonia. The time needed for an ecosystem to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, little is known about the impacts of these disturbances, alone and synergistically, on forest recovery time and the resulting spatiotemporal patterns at the regional scale. In this study, we combined the 3-PG forest growth model, remote sensing and field derived equations, to map the Amazonia-wide (3 km of spatial resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our results indicate that AGB decreases by 4%, 19% and 46% in forests affected by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: (1) the recovery time of the forests takes longer in the southeastern part of the basin, and, (2) as droughts and wildfires become more frequent—since the intervals between the disturbances are getting shorter than the rate of forest regeneration—the long lasting damage they cause potentially results in a permanent and increasing carbon losses from these fragile ecosystems.

Meteorological droughts are projected to worsen in Central America’s dry corridor throughout the 21st century

Understanding past and projected drought patterns across Central America’s ‘Dry Corridor’ (CADC) is crucial for adaptation planning and impact mitigation, especially in small-scale agricultural communities. We analyzed historical and predicted drought patterns in the CADC by calculating Standardized Precipitation Index (SPI) values from local rain gauge records, reanalysis data and a 20-member ensemble of bias-corrected, downscaled CMIP-5 GCMs at both seasonal (3 month) and annual (12 month) scales. Trends in drought frequency, duration, intensity were assessed for three, 30 year future periods compared to historical values. Our results suggest a decrease in mean annual rainfall of 8%–14% in the CADC under moderate to high emissions scenarios, respectively, by end-of-century (2071–2100) relative to a historical baseline (1950–2005). However, projected changes to drought characteristics under these scenarios are more pronounced, with seasonal-scale droughts projected to lengthen by 12%–30%, intensify by 17%–42% and increase in frequency by 21%–24% by end-of-century. Annual-scale, longer-term droughts are projected to lengthen by 68% under moderate emissions, potentially triple in length under high emissions and to intensify by 27%–74%. These results were similar yet slightly more pronounced for some drought metrics when just considering rainy/cropping season months (May–Oct). End-of-century changes to rainfall reliability and drought occurrence such as these would severely impact millions of vulnerable inhabitants in the CADC and should be considered in adaptation policymaking efforts.

Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach

Drought is one of the extreme climatic events that has a severe impact on crop production and food supply. Our main goal is to test the suitability of remote sensing-based indices to detect drought impacts on crop production from a global to regional scale. Moderate resolution imaging spectroradiometer (MODIS) based imagery, spanning from 2001 to 2017 was used for this task. This includes the normalized difference vegetation index (NDVI), land surface temperature (LST), and the evaporative stress index (ESI), which is based on the ratio of actual to potential evapotranspiration. These indices were used as indicators of drought-induced vegetation conditions for three main crops: maize, wheat, and soybean. The start and end of the growing season, as observed at 500 m resolution, were used to exclude the time steps that are outside of the growing season. Based on the three indicators, monthly standardized anomalies were estimated, which were used for both analyses of spatiotemporal patterns of drought and the relationship with yield anomalies. Anomalies in the ESI had higher correlations with maize and wheat yield anomalies than other indices, indicating that prolonged periods of low ESI during the growing season are highly correlated with reduced crop yields. All indices could identify past drought events, such as the drought in the USA in 2012, Eastern Africa in 2016–2017, and South Africa in 2015–2016. The results of this study highlight the potential of the use of moderate resolution remote sensing-based indicators combined with phenometrics for drought-induced crop impact monitoring. For several regions, droughts identified using the ESI and LST were more intense than the NDVI-based results. We showed that these indices are relevant for agricultural drought monitoring at both global and regional scales. They can be integrated into drought early warning systems, process-based crop models, as well as can be used for risk assessment and included in advanced decision-support frameworks.

Spatiotemporal investigation of drought pattern in Iran via statistical analysis and GIS technique

Drought monitoring is very important for water resource planning due to the impact of climate change on the frequency of drought events. The objective of this study was to evaluate the spatiotemporal characteristics of drought in Iran. Spatial and temporal distributions of drought severity were assessed using the well-accepted standardized reconnaissance drought index (RDIst) in seasonal and annual scales in 40 synoptic meteorological stations of Iran during the years 1967–2014. Parametric and nonparametric statistical tests were further used for trend assessments. According to the results of RDIst on an annual time scale, the trends of drought were positive in 87.5% of the stations. The results of seasonal RDIst also indicated that the trends of drought in winter (92.5%), spring (82.5%), summer (37.5%), and fall (67.5%) were upward. In sequence series of all seasons, 90% of all stations had a negative trend in the value of their calculated RDIst over time, which means an upward trend in drought over time. Our findings demonstrated an upward trend in drought over the study period. In 45% of the studied stations, winter had the most significant positive trend at all time scales. The results also showed that a moderate drought covered the highest portion of the study area. Generally, a positive trend was observed in coverage of extreme, severe, and moderate drought. However, a negative trend was evident in the coverage of extreme, severe, and moderate wet conditions during the time. It is suggested that the spatiotemporal distribution of the RDIst trend can be used to identify drought and mitigate its impacts in Iran.

Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data

Studying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study aims to bring out the drought fluctuations within various types of Land Cover (LC) (Grasslands, Croplands, Savannas, and Forest) in North and West Africa regions. The drought characteristics were evaluated by analyzing the monthly Self-Calibrating Palmer Drought Severity Index (scPDSI) in different timescale from 2002 to 2018. Then, the frequency of droughts was examined over the same period. The results have revealed two groups of years (dry years and normal years), based on drought intensity. The selected years were used to compare the shifting between vegetation and desert. The Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), the Precipitation Condition Index (PCI), and the Soil Moisture Condition Index (SMCI) were also used to investigate the spatiotemporal variation of drought and to determine which LC class was more vulnerable to drought risk. Our results revealed that Grasslands and Croplands in the West region, and Grasslands, Croplands, and Savannas in the North region are more sensitive to drought. A higher correlation was observed among the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Tropical Rainfall Measuring Mission (TRMM), and Soil Moisture (SM). Our findings suggested that NDVI, TRMM, and SM are more suitable for monitoring drought over the study area and have a reliable accuracy (R2 > 0.70) concerning drought prediction. The outcomes of the current research could, explicitly, contribute progressively towards improving specific drought mitigation strategies and disaster risk reduction at regional and national levels.

Analysis of Long-Term Variations of Drought Characteristics Using Standardized Precipitation Index over Zambia

This study examines long-term spatial and temporal trends of drought characteristics based on the Standardized Precipitation Index at three different time scales (3, 6, and 12 months) over Zambia from 1981 to 2017. Drought characteristic conditions such as duration, severity, and intensity at monthly, seasonal, and annual levels were analyzed to investigate the drought patterns over Zambia. The results show a significant increase in drought events over the southwestern regions and a decrease over the northeastern regions. It is in this regard that two stations from different locations (southwest and northeast) were analyzed. The results show increasing trends of drought over Sesheke (southwest) and decreasing trends over Kasama (northeast). More drought impacts are felt over southern compared to northern areas, which poses a serious concern to both agriculture and hydrological industries over the drought-prone areas of Southern Zambia. However, the analysis further shows that droughts were more intense, persistent, and severe over the southwest, while moderate droughts were found in some few areas of Northeast Zambia. The Mann–Kendall test trend and slope indicated that both annual and seasonal drought have increased. However, drought increment at an annual level shows a low magnitude as compared to the seasonal level. This suggested the importance of evaluating drought at an interannual and seasonal time scale over Zambia. Specifically, the drought increased determinedly before 2010 and became erratic between 2010 and 2017 with considerable regional variation. Zambia experienced moderate to severe droughts during 1991–1992, 1994–1995, 2006–2005, and 2015–2016, which resulted in serious damages to the environment and society. According to the findings of this study, it is suggested that the implications of drought can be managed by creating strategies and adaptation measures.

Aerobic Rice with or without Strategic Irrigation in the Subtropics

Modern rice varieties adapted to aerobic (dryland) conditions have expanded to new rice growing systems thanks to their plasticity in adapting to rainfed and irrigated conditions. This is important because, as water becomes scarce in paddy rice regions (as it is already in Australia), there will be a move towards tropical to subtropical dryland rainfed rice with attendant problems of drought and low temperature. To assess rice adaptability in the wet season of the semi-arid subtropical conditions of coastal central Queensland, field experiments were established for a late season (in January) planting in 2014 and early season planting in November 2015 with 13 varieties developed by Australian Agriculture Technologies (AAT) Ltd were seeded in a vertisol soil. This was to assess their adaptation to rainfed conditions and their response to strategic irrigation. Water scarcity and low temperature prior to and at flowering were important factors constraining yield. Early flowering varieties in the late season planting escaped the otherwise cold and drought stress during the reproductive stage and had higher yields. In the second year, earlier planting made possible with strategic irrigation avoided the low temperature constraint on yield, but without follow-up strategic irrigation, yields were still low. The average yield of varieties increased from 1.5 times (AAT 4) to 16.3 times (AAT 15) with strategic irrigation compared with rainfed yields averaged across years. The increase in yield with strategic irrigation was associated with a greater leaf area index, spikelet fertility, and instantaneous water use efficiency during flowering. Strategic irrigation concentrated roots in the top 15 cm, but differences in yield between varieties under rainfed conditions were not related to root properties. It is important to consider variations in flowering time, yield potential, and drought patterns when developing rice varieties for rainfed semi-arid tropical conditions, as well as when quantifying the benefits of strategic irrigation.

Influence of the Atlantic Multidecadal Oscillation on drought in northern Daxing’an Mountains, Northeast China

The northern Daxing’an Mountains (DM) of China has experienced many serious drought disasters, which caused great losses of agricultural production and people’s lives. However, the temporal and spatial limitations of instrument data have seriously hindered our understanding of drought change and its impact on human culture and natural ecosystems. Here, we analyze the process, patterns and driving mechanism of drought in the northern DM based on a 294-year (CE 1722–2015) tree-ring-based Palmer Drought Severity Index (PDSI) drought reconstruction. Drought in the northern DM is consistent with other drought records in the central DM and the eastern and central Mongolian Plateau (MP). In the past 294 years, most of the extreme dry or wet years or periods occurred in the 18th and 20th centuries. There were 2 years and 78.7 years significant (p < 0.01) periodic peaks of drought in northern DM. After the rapid warming in the 1980s, the central and northern DM experienced a wet trend, while the eastern and western MP experienced a drying trend. The Atlantic Multidecadal Oscillation (AMO) plays a key role in influencing the drought in the northern DM by modulating the oceanic-atmospheric-land surfaces interaction process and other large-scale circulations. Compared with the effect of AMO on drought patterns in North America, Europe and western MP, the cold phase of AMO is more favorable to drought in northern DM.

Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha−1 year−1, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.

Stochastic time-series models for drought assessment in the Gaza Strip (Palestine)

Abstract The Eastern Mediterranean region of the Middle East and North Africa (MENA) is experiencing patterns of major drought due to the effects of rising temperatures and falling precipitation levels. The multiscale drought evaluation Standardized Precipitation Evapotranspiration Index (SPEI) reveals evolving and severe drought from North Africa and the Sinai desert toward the Middle East. While there has been a period without drought between 1970 and 1990, the severity and frequency of drought increased considerably after 1990. Current drought conditions in the Eastern Mediterranean region of MENA are moderate to severe with a 60–100% likelihood of occurrence, according to time parameters. The Gaza Strip is especially vulnerable to the consequences of increasing drought because it is situated in the vicinity of the Sinai Desert; therefore, a downscaled study of drought in the region is essential to implement mitigation measures for the sustainable management and planning of coastal aquifer and agricultural activities in the Gaza Strip. Considerable availability of precipitation time series from various meteorological stations helped provide a local drought study for the Gaza Strip, in accordance with the Standardized Precipitation Index (SPI). The stochastic time-series model of (4,0,1) (5,1,1)12 shows a robust simulator for modeling and forecasting the future trend of precipitation at the nine meteorological stations. In terms of correlation accuracy, the model achieves a correlation (r) of approximately 93–97% in the calibration range and a correlation (r) of about 92–99% in the validation range. In terms of measuring the difference between the values, the root mean squared error (RMSE) of the model results shows that the RMSE was between 7–21 in the calibration range and 11–21 in the validation range. The model reveals a slightly stable trend in precipitation patterns at the northern meteorological stations of Beit Hanon, Beit Lahia, Shati, and Remal. However, declining precipitation tendency was recorded at the southern meteorological stations of Mughraka, Nussirat, Beir Al-Balah, Khanyounis, and Rafah. The SPI-based drought assessment implies that the precipitation annual threshold levels at SPI = 0 drop territorially from 474 mm in the north to about 250 mm in the south of the Gaza Strip. In this study, a representative 12-month local scale SPI12 at an annual precipitation threshold level of 370 mm was formulated to address the drought conditions in the Gaza Strip. Standing on the outputs of the local SPI12 scale might signify that the region of the Gaza Strip risks drought status with an incidence likelihood varying from 8% in the north to 100% in the south. Regular drought is prevalent in the northern governorates, but the hazards of extreme and severe drought are high in the southern areas with an incidence risk of about 83%. Sequentially, southern governorates of Rafah and Khanyounis experience chronic annual drought, while the return period of drought is reported to be every 9–12 years in the northern governorates of the Gaza Strip. The rain-fed years of 1998 and 2010 reported the worst periods of drought, while the period of 2016 showed a good droughtless water balance. Overall, the no-drought status might define the prospective conditions in the governorates of North Gaza, Gaza, and central Gaza over the next 20 years, while Rafah and Khanyounis are anticipated to be under normal to severe drought conditions.

Drought in the Upper Hron Region (Slovakia) between the Years 1984–2014

Climate change causes an increase in the frequency and severity of weather extremes. One of the most relevant severe and damaging phenomena in Europe is drought. However, a difference in the spatial frequency of the occurrence and drought trends is evident between southern and northern Europe. Central Europe and particularly the West Carpathian region form a transitional zone, and drought patterns are complicated because of the geomorphologically complicated landscape. Since almost half of the Slovak state territory is represented by such natural landscape, it is necessary to investigate regional drought specifics. Therefore, we decided to analyze drought occurrence and trends using the SPI (Standardised Precipitation Index) and the SPEI (Standardised Precipitation Evapotranspiration Index) at available climatological stations of the Slovak Hydrometeorological Institute (SHMI) in the upper Hron region within the 1984–2014 period. We found that (1) drought incidence decreased with increasing altitude, (2) increasing air temperature increased the difference in drought trends between lowlands and mountains during the studied period, and (3) abrupt changes in time series of drought indices, that could indicate some signals of changing atmospheric circulation patterns, were not revealed. Finally, we constructed a simplified map of drought risk as an explanation resource for local decision-makers.

Prediction of Droughts in the Mongolian Plateau Based on the CMIP5 Model

Understanding the variations of future drought under climate warming can provide the basis for mitigation efforts. This study utilized the standardized precipitation evapotranspiration index (SPEI), empirical mode decomposition (EMD) and empirical orthogonal function analysis (EOF) to predict the spatiotemporal variation of future drought under the representative concentration pathway RCP4.5 and RCP8.5 scenarios within the Mongolian Plateau over the period 2020–2100. The SPEI was computed using temperature and precipitation data generated by the fifth stage of the Coupled Model Intercomparison Project (CMIP5). The results under both the RCP4.5 and RCP8.5 scenarios showed increasing changes in temperature and precipitation. Both scenarios indicated increases in drought, with those under RCP8.5 much more extreme than that under RCP4.5. Under both scenarios, the climate showed an abrupt change to become drier, with the change occurring in 2041 and 2054 for the RCP4.5 and RCP8.5 scenarios, respectively. The results also indicated future drought to be more extreme in Mongolia than in Inner Mongolia. The simulated drought pattern showed an east–west antiphase and a north–south antiphase distribution based on EOF. The frequency of drought was higher under RCP8.5 compared to that under RCP4.5, with the highest frequencies under both scenarios occurring by the end of the 21st century, followed by the mid-21st century and early 21st century. The findings of this research can provide a solid foundation for the prevention, early warning and mitigation of drought disasters within the context of climate change in the Mongolian Plateau.

Prognostic and diagnostic assessment of hydrological drought using water and energy budget-based indices

Long-term meteorological drought can lead to hydrological drought by restricting water resources required by humans, such as streamflow and reservoir storage. We developed two new indices for monitoring hydrologic drought-based satellite-derived evapotranspiration, a major factor in hydrological drought occurrence. The Water Budget-based Drought Index (WBDI) estimates potential runoff by the differences between precipitation and evapotranspiration using water budget analysis while the Energy-based Water Deficit Index (EWDI) is an index of available water capacity through evapotranspiration and soil moisture based on solar radiation using energy budget analysis. We used these, along with the existing Standardized Precipitation-Evapotranspiration Index (SPEI, based on precipitation, atmospheric temperature, and evapotranspiration), to map the spatiotemporal patterns of drought on the Korean Peninsula from 2001 to 2014. For validation against actual drought conditions, we compared the results with streamflow data from five gauging stations in South Korea. EWDI—the diagnostic approach—performed best when assessing current hydrological drought conditions, while WBDI and SPEI—prognostic approach—best captured drought conditions after 2–3 months of lag time. Our results confirmed that evapotranspiration is a major factor affecting hydrological drought; the new methods demonstrated here make it possible to evaluate drought through diagnostic and prognostic perspectives depending on the situation, thereby improving scientific drought evaluation capacity.

Monthly drought prediction based on ensemble models

Drought is a natural hazard, which is a result of a prolonged shortage of precipitation, high temperature and change in the weather pattern. Drought harms society, the economy and the natural environment, but it is difficult to identify and characterize. Many areas of Pakistan have suffered severe droughts during the last three decades due to changes in the weather pattern. A drought analysis with the incorporation of climate information has not yet been undertaken in this study region. Here, we propose an ensemble approach for monthly drought prediction and to define and examine wet/dry events. Initially, the drought events were identified by the short term Standardized Precipitation Index (SPI-3). Drought is predicted based on three ensemble models i.e., Equal Ensemble Drought Prediction (EEDP), Weighted Ensemble Drought Prediction (WEDP) and the Conditional Ensemble Drought Prediction (CEDP) model. Besides, two weighting procedures are used for distributing weights in the WEDP model, such as Traditional Weighting (TW) and the Weighted Bootstrap Resampling (WBR) procedure. Four copula families (i.e., Frank, Clayton, Gumbel and Joe) are used to explain the dependency relation between climate indices and precipitation in the CEDP model. Among all four copula families, the Joe copula has been found suitable for most of the times. The CEDP model provides better results in terms of accuracy and uncertainty as compared to other ensemble models for all meteorological stations. The performance of the CEDP model indicates that the climate indices are correlated with a weather pattern of four meteorological stations. Moreover, the percentage occurrence of extreme drought events that have appeared in the Multan, Bahawalpur, Barkhan and Khanpur are 1.44%, 0.57%, 2.59% and 1.71%, respectively, whereas the percentage occurrence of extremely wet events are 2.3%, 1.72%, 0.86% and 2.86%, respectively. The understanding of drought pattern by including climate information can contribute to the knowledge of future agriculture and water resource management.

Farmers’ drought experience, risk perceptions, and behavioural intentions for adaptation: evidence from Ethiopia

ABSTRACT This paper examines farmers' cognitive perceptions of risk and the behavioural intentions to implement specific drought risk reduction measures using the Protection Motivation Theory (PMT) model. We follow an innovative route by extending a PMT model with a drought experience variable, which, we hypothesize, will influence risk perceptions and the take-up of adaptation measures. In order to do so, we investigated detailed historical drought patterns by looking at the spatial and temporal aspects of drought conditions during crop growing season at the village level. In our extended PMT model, drought experience, as represented by a long-term Normalized Difference Vegetation Index (NDVI), plays a significant role in predicting farmers' intention to take up adaptation measures. The result reveals that drier conditions significantly increase farmers' behavioural intention to implement adaptation measures against drought risk, which is the key finding of the study. Moreover, our findings show that perceived vulnerability and severity, self-efficacy, and response efficacy are positively and significantly associated with the number of drought risk reduction measures implemented. The findings of our empirical analysis contribute to the effect of cognitive perceptions through a new lens of farmer's personal experience with drought shocks, represented by the state of vegetation or physical environment.

Drought characteristics and its elevation dependence in the Qinghai\u2013Tibet plateau during the last half-century

Associated with global warming, drought has destructive influences on agriculture and ecosystems, especially in the fragile Qinghai–Tibet Plateau (QTP). This study investigated spatial–temporal patterns of meteorological drought in the QTP and its surrounding areas and made an attempt to explore the relationship between drought conditions and elevation. Robust monitoring data from 274 meteorological stations during 1970–2017 were analyzed using the Sen’s slope method, Mann–Kendall trend test and rescaled range analysis. Results revealed that under the wetting trend in the QTP, Standardized Precipitation Evapotranspiration Index (SPEI) increased of maximum 0.012/year in spring. Moreover, severe drought frequency in winter and future drought risk in summer also showed an increasing trend. Wetter trends were positively correlated with elevation, with a key point being 4,000 m where the change trend above 4,000 m was about 6.3 times of that below 4,000 m in study area. The difference of drought severities between SPEI in the QTP and its surrounding areas has increased from − 0.19 in 1970 to 0.38 in 2017 and kept growing in future.

Spatial-temporal Analysis of Precipitation and Drought in the Poyang Lake Basin during 1957-2012

Xiao, L.Y., 2020. Spatial-temporal analysis of precipitation and drought in the Poyang lake basin during 1957-2012. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 379-382. Coconut Creek (Florida), ISSN 0749-0208.Droughts have presented an increasing trend in the Poyang Lake Basin in the past several decades. To find patterns of meteorological drought, spatiotemporal changes in precipitation and drought were analyzed. Firstly, the Mann-Kendall method was adopted for a trend test. Results show that precipitation trends in the Poyang Lake Basin have clearly temporal and spatial distinctions. For the monthly scale, there were dry trends in May for all of the basin area, while statistically significant wet trends were found in January for nearly all the basin. Secondly, the standard precipitation index (the SPI) was calculated to characterize droughts. Analysis of the standard precipitation index at a 12-month time scale suggested that the statistically significant decreasing trends were found at Xiushui station and Ganxian station, which are located in the north and south. Results of the analysis revealed that the half part of the Poyang Lake Basin became drier during 1957-2012. Morover, we can know the decrease of precipitation in May and October may be the reason of the drought in the Xiushui and Ganxian stations.