Variations In Drought Conditions Research Articles

Remote sensing-based agricultural drought mapping in Northern Jordan using Landsat and MODIS data

Monitoring agricultural drought in a semi-arid environment is critical, especially during the growing season, as it negatively impacts vegetation health and crop yield. This study aimed to monitor the spatiotemporal variation of agricultural drought in Northern Jordan using Landsat-8 and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The Spatio-Temporal Image Fusion Model (STI-FM) was used to produce synthetic Landsat images with a high spatiotemporal resolution (30 m / 8 days) by utilizing a pair of successive MODIS images at two points in time (time-1 and time-2) and one Landsat-8 image at time-1. Agricultural drought was mapped and monitored using spectral indices namely, Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). Additionally, the Standard Precipitation Index (SPI) -based meteorological rainfall data was used to validate the accuracy of the drought maps. The results revealed significant spatiotemporal variations in drought conditions, with April 2020 showing the least dry conditions, while 2019 was identified as the driest year. Validation through SPI indicated high accuracy, with kappa values ranging from 0.70 to 0.85 and overall accuracy ranging from 80 % to 92 %. Furthermore, the STI-FM data fusion algorithm effectively generated high-resolution Landsat-8 images, demonstrating a strong correlation between original and synthetic images for the red and NIR spectral bands (0.93 and 0.84, respectively). These findings highlight the effectiveness of integrating STI-FM with spectral indices and SPI for accurate and high-resolution agricultural drought monitoring, which can support improved water resource management and agricultural planning in semi-arid regions.

Temporal variation characteristics in the association between climate and vegetation in Northwest China

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Research on Drought Monitoring Based on Deep Learning: A Case Study of the Huang-Huai-Hai Region in China

As climate change intensifies, drought has become a major global engineering and environmental challenge. In critical areas such as agricultural production, accurate drought monitoring is vital for the sustainable development of regional agriculture. Currently, despite extensive use of traditional meteorological stations and remote sensing methods, these approaches have proven to be inadequate in capturing the full extent of drought information and adequately reflecting spatial characteristics. Therefore, to improve the accuracy of drought forecasts and achieve predictions across extensive areas, this paper employs deep learning models, specifically introducing an attention-weighted long short-term memory network model (AW-LSTM), constructs a composite drought monitoring index (CDMI) and validates the model. Results show that: (1) The AW-LSTM model significantly outperforms traditional long short-term memory (LSTM), support vector machine (SVM) and artificial neural network (ANN) models in drought monitoring, offering not only better applicability in meteorological and agricultural drought monitoring but also the ability to accurately predict drought events one month in advance compared to machine learning models, providing a new method for precise and comprehensive regional drought assessment. (2) The Huang-Huai-Hai Plain has shown significant regional variations in drought conditions across different years and months, with the drought situation gradually worsening in the northern part of Hebei Province, Beijing, Tianjin, the southern part of Huai North and the central part of Henan Province from 2001 to 2022, while drought conditions in the northern part of Huai North, southern Shandong Province, western Henan Province and southwestern Hebei Province have been alleviated. (3) During the sowing (June) and harvesting (September) periods for summer maize, the likelihood of drought occurrences is higher, necessitating flexible adjustments to agricultural production strategies to adapt to varying drought conditions.

Is this land for sale? The effects of drought on land ownership in Uganda

This study examines the impact of drought on the land ownership rights of smallholder farmers in Uganda. Three waves of the Uganda National Panel Survey are combined with an indicator for drought, the Standardized Precipitation Evapotranspiration Index. Using a household fixed effects approach, we exploit spatial and temporal variation in drought conditions to identify its effect on households’ self-reported willingness to acquire land ownership rights, both at the extensive and intensive margins. Results show that exposure to drought lowers households’ intentions to purchase land and substantially reduces the price households are willing to pay for land. The effects persist over time and are robust to different specifications. Our findings suggest that drought exposure limits the operating space for farmers wishing to purchase land.

Space–time variability in soil moisture droughts in the Himalayan region

Abstract. Soil water is a major requirement for biomass production and, therefore, one of the most important factors for agriculture productivity. As agricultural droughts are related to declining soil moisture, this paper examines soil moisture drought in the transboundary Koshi River basin (KRB) in the central Himalayan region. By applying the J2000 hydrological model, daily spatially distributed soil moisture is derived for the entire basin over a 28-year period (1980–2007). A multi-site and multi-variable approach – streamflow data at one station and evapotranspiration data at three stations – was used for the calibration and validation of the J2000 model. In order to identify drought conditions based on the simulated soil moisture, the soil moisture deficit index (SMDI) was then calculated, considering the derivation of actual soil moisture from long-term soil moisture on a weekly timescale. To spatially subdivide the variations in soil moisture, the river basin is partitioned into three distinct geographical regions, namely trans-Himalaya, the mountains, and the plains. Further, the SMDI is aggregated temporally to four seasons – winter, pre-monsoon, monsoon, and post-monsoon – based on wetness and dryness patterns observed in the study area. This has enabled us to look at the magnitude, extent, and duration of soil moisture drought. The results indicated that the J2000 model can simulate the hydrological processes of the basin with good accuracy. Considerable variation in soil moisture was observed in the three physiographic regions and across the four seasons due to high variation in precipitation and temperature conditions. The year 1992 was the driest year and 1998 was the wettest at the basin scale in both magnitude and duration. Similarly, the year 1992 also has the highest number of weeks under drought. Comparing the SMDI with the standardised precipitation index (SPI) suggested that SMDI can reflect a higher variation in drought conditions than SPI. Our results suggested that both the occurrence and severity of droughts have increased in the Koshi River basin over the last 3 decades, especially in the winter and pre-monsoon seasons. The insights provided into the frequency, spatial coverage, and severity of drought conditions can provide valuable contributions towards an improved management of water resources and greater agricultural productivity in the region.

Production and turnover of mycorrhizal soil mycelium relate to variation in drought conditions in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests.

In forests, ectomycorrhizal mycelium is pivotal for driving soil carbon and nutrient cycles, but how ectomycorrhizal mycelial dynamics vary in ecosystems with drought periods is unknown. We quantified the production and turnover of mycorrhizal mycelium in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests and related the estimates to standardised precipitation index (SPI), to study how mycelial dynamics relates to tree species and drought-moisture conditions. Production and turnover of mycelium was estimated between July and February, by quantifying the fungal biomass (ergosterol) in ingrowth mesh bags and using statistical modelling. SPI for time scales of 1-3months was calculated from precipitation records and precipitation data over the study period. Forests dominated by Pinus trees displayed higher biomass but were seasonally more variable, as opposed to Q.ilex forests where the mycelial biomass remained lower and stable over the season. Production and turnover, respectively, varied between 1.4-5.9kgha-1 d-1 and 7.2-9.9 times yr-1 over the different forest types and were positively correlated with 2-month and 3-month SPI over the study period. Our results demonstrated that mycorrhizal mycelial biomass varied with season and tree species and we speculate that production and turnover are related to physiology and plant host performance during drought.

A remote sensing study of spatiotemporal variations in drought conditions in northern Asir, Saudi Arabia.

Changes in vegetation land cover are influenced by, and therefore an indicator of, climatic conditions. The aim of this study is to investigate the relationship between vegetation cover changes and drought events in a small-scale area. Six Landsat images during 1987-2019 were used to extract information about the vegetation land cover changes using the normalized difference vegetation index (NDVI) and the fractional vegetation cover (FVC) in Balqarn Governorate in the northern mountains of Asir, Saudi Arabia. Two climatic parameters, temperature and precipitation, were used as time series for the same period and were decomposed to investigate the seasonal and trend changes for each parameter. The two parameters were also used to calculate the standardized precipitation evapotranspiration index (SPEI) to conduct an in-depth analysis of the drought events influencing vegetation cover. The results showed that the state of the vegetation coverage of the study area remained at a medium level with an average NDVI value, but the FVC values showed evidence of dynamic variability associated with drought and moisture events. The SPEI showed that the study area has been undergoing a long-duration drought event since 2004, ranging from light to severe drought, which was consistent with the time series decomposition results. This investigation has revealed that drought drives changes in vegetation cover and is expressed on small geographic scales as changes in the vegetation cover structure. The framework described here is simple and can be used to evaluate and manage drought risks.

Future Drought in the Dry Lands of Asia Under the 1.5 and 2.0 °C Warming Scenarios

AbstractDrought has become a major threat to local sustainable development in dryland Asia, one of the largest grassland ecosystems in the world. However, empirical‐ and science‐based evidence regarding the extent of drought changes and the future trends of these changes in dryland Asia is variable and incomplete. Here, we first investigate the historical variations in drought conditions in dryland Asia, as measured by the drought intensity and arid area, using three widely used drought indices (the Palmer Drought Severity Index, the Standardized Precipitation Index, and the Standardized Precipitation Evapotranspiration Index). Then, we use Bayesian model averaging to reproduce the future drought conditions under two representative concentration pathways (RCP2.6 and RCP4.5) from the Coupled Model Intercomparison Project Phase 5 Earth system models. The Palmer Drought Severity Index, Standardized Precipitation Index, and Standardized Precipitation Evapotranspiration Index illustrate that dryland Asia has experienced an overall drying trend and an expansion of arid areas over the past 100 years (1901–2016). Both temperature and precipitation are projected to increase under both the 1.5 and 2.0 °C warming scenarios compared with the values from the reference period (1986–2005). The projected drought conditions in the 1.5 and 2.0 °C warming scenarios will worsen, especially across Kazakhstan and Northwest China. We found that the drought conditions under the 2.0 °C warming conditions will not be as severe as those under the 1.5 °C warming conditions due to the mitigating effect of the projected precipitation increase under RCP4.5. These results call for short‐term and long‐term mitigation and adaptation measurements for drought events in dryland Asia.

Factors influencing nesting ecology of lesser prairie‐chickens

ABSTRACTLesser prairie‐chicken (Tympanuchus pallidicinctus) populations have declined since the 1980s. Understanding factors influencing nest‐site selection and nest survival are important for conservation and management of lesser prairie‐chicken populations. However, >75% of the extant population is in the northern extent of the range where data on breeding season ecology are lacking. We tested factors influencing fine‐scale and regional nest‐site selection and nest survival across the northern portion of the lesser prairie‐chicken range. We trapped and affixed satellite global positioning system and very high frequency transmitters to female lesser prairie‐chickens (n = 307) in south‐central and western Kansas and eastern Colorado, USA. We located and monitored 257 lesser prairie‐chicken nests from 2013 to 2016. We evaluated nest‐site selection and nest survival in comparison to vegetation composition and structure. Overall, nest‐site selection in relation to vegetation characteristics was similar across our study area. Lesser prairie‐chickens selected nest microsites with 75% visual obstruction 2.0–3.5 dm tall and 95.7% of all nests were in habitat with ≥1 dm and ≤4 dm visual obstruction. Nests were located in areas with 6–8% bare ground, on average, avoiding areas with greater percent cover of bare ground. The type of vegetation present was less important than cover of adequate height. Nest survival was maximized when 75% visual obstruction was 2.0–4.0 dm. Nest survival did not vary spatially or among years and generally increased as intensity of drought decreased throughout the study although not significantly. To provide nesting cover considering yearly variation in drought conditions, it is important to maintain residual cover by managing for structural heterogeneity of vegetation. Managing for structural heterogeneity could be accomplished by maintaining or strategically applying practices of the Conservation Reserve Program, using appropriate fire and grazing disturbances in native working grasslands, and establishing site‐specific monitoring of vegetation composition and structure. © 2018 The Wildlife Society.

The Use of SPEI and TVDI to Assess Temporal-Spatial Variations in Drought Conditions in the Middle and Lower Reaches of the Yangtze River Basin, China

Droughts represent the most complex and damaging type of natural disaster, and they have taken place with increased frequency in China in recent years. Values of the standardized precipitation evapotranspiration index (SPEI) calculated using station-based meteorological data collected from 1961 to 2013 in the middle and lower reaches of the Yangtze River Basin (MLRYRB) are used to monitor droughts. In addition, the SPEI is determined for different timescales (1, 3, 6, and 12 months) to characterize dry or wet conditions in this study area. Moreover, remote sensing methods can cover large areas, and multispectral and temporal observations are provided by satellite sensors. The temperature vegetation dryness index (TVDI) is selected to permit assessment of drought conditions. In addition, the correlation between the SPEI and TVDI values is calculated. The results show that the SPEI values over different timescales reflect complex variations in drought conditions and have been well applied in the MLRYRB. Droughts occurred on an annual basis in 1963, 1966, 1971, 1978, 1979, 1986, 2001, 2011, and 2013, particularly 2011. In addition, the regional average drought frequency in the study area during 1961–2013 is 30%, as determined using the SPEI. An analysis of the correlation between the monthly values of the TVDI and the SPEI-3 shows that a negative relationship exists between the SPEI-3 and the TVDI. That is, smaller TVDI values are associated with greater SPEI-3 values and reduced drought conditions, whereas larger TVDI values are associated with smaller SPEI-3 values and enhanced drought conditions. Therefore, this study of the relationship between the SPEI and the TVDI can provide a basis for government to mitigate the effects of drought.

Evaluation of a High-Resolution SPI for Monitoring Local Drought Severity

AbstractA standardized precipitation index (SPI) that uses high-resolution, daily estimates of precipitation from the National Weather Service over the contiguous United States has been developed and is referred to as HRD SPI. There are two different historical distributions computed in the HRD SPI dataset, each with a different combination of normals period (1971–2000 or 1981–2010) and clustering solution of gauge stations. For each historical distribution, the SPI is computed using the NCEP Stage IV and Advanced Hydrologic Prediction Service (AHPS) gridded precipitation datasets for a total of four different HRD SPI products. HRD SPIs are found to correlate strongly with independently produced SPIs over the 10-yr period from 2005 to 2015. The drought-monitoring utility of the HRD SPIs is assessed with case studies of drought in the central and southern United States during 2012 and over the Carolinas during 2007–08. A monthly comparison between HRD SPIs and independently produced SPIs reveals generally strong agreement during both events but weak agreement in areas where radar coverage is poor. For both study regions, HRD SPI is compared with the U.S. Drought Monitor (USDM) to assess the best combination of precipitation input, normals period, and station clustering solution. SPI generated with AHPS precipitation and the 1981–2010 PRISM normals and associated cluster solution is found to best capture the spatial extent and severity of drought conditions indicated by the USDM. This SPI is also able to resolve local variations in drought conditions that are not shown by either the USDM or comparison SPI datasets.

Research on the joint probability distribution of rainfall and reference crop evapotranspiration

The relationship between rainfall and reference crop evapotranspiration (ET0) can be complex in an irrigation district. To reveal such complex and possibly a nonlinear relationship, rainfall and ET0 data were collected at the Xinxiang irrigation experiment station from the years 1961 to 2010. Marginal distributions of the two variables derived from fitting the Pearson Type III distribution were incorporated for the development of the joint probability distribution using a copula model. Subsequently, the joint probability as well as the return period of given specific rainfall and ET0 values can be computed. For the analysis of the variations in drought conditions over the 50 years, the copula-based joint probability is further decomposed into several subcomponents using the empirical mode decomposition method. The variations under distinct frequencies and over different time periods were observed. Our results showed that the joint probability distribution of rainfall and ET0 can facilitate the planning for drought resistance in an irrigation district.

Comparison of drought projections using two UK weather generators

Possible changes in drought under future climate scenarios may pose unprecedented challenges for water resources, as well as other environmental and societal issues, and need assessment to quantify their associated risk. Two weather generators, based upon (a) the Neyman-Scott Rectangular Pulses (NSRP) model as implemented by the United Kingdom Climate Projections 09 (UKCP09) study, and (b) the generalized linear model (GLM) approach, are used to investigate potential variations in drought conditions for six catchments in the UK under climate projections. The results show that both weather generators provide rainfall simulations having satisfactory monthly statistics. However, the rainfall series from the UKCP09 weather generators lack inter-annual variability, whereas the GLM simulations, which include non-stationary global circulation model (GCM) outputs as driving variables, seem to have a more appropriate representation of the observed drought conditions. For drought projections in the 2080s, the UKCP09 simulations provide repetitive patterns without much temporal variation, similar to the results in the control period. This study suggests that for the drought index considered here (a 3-month drought severity index) the GLM approach appears to be a more appropriate model for drought study on inter-annual scales in comparison with the UKCP09 weather generator. Editor D. Koutsoyiannis Citation Chun, K.P., Wheater, H.S., and Onof, C., 2013. Comparison of drought projections using two UK weather generators. Hydrological Sciences Journal, 58 (2), 295–309.

Spatial and temporal variation in survival of a rare reptile: a 22-year study of Sonoran desert tortoises

Although many species may be vulnerable to changes in climate, forecasting species-level responses can be challenging given the array of physiological, behavioral, and demographic attributes that might be affected. One strategy to improve forecasts is to evaluate how species responded to climatic variation in the past. We used 22 years of capture-recapture data for Sonoran desert tortoises (Gopherus morafkai) collected from 15 locations across their geographic range in Arizona to evaluate how environmental factors affected spatial and temporal variation in survival. Although rates of annual survival were generally high ([Formula: see text] = 0.92), survival of adults decreased with drought severity, especially in portions of their range that were most arid and nearest to cities. In three locations where large numbers of carcasses from marked tortoises were recovered, survival of adults was markedly lower during periods of severe drought ([Formula: see text] = 0.77-0.81) compared to all other periods ([Formula: see text] = 0.93-0.98). Assuming continued levels of dependency of humans on fossil fuels, survival of adult tortoises is predicted to decrease by an average of 3 % during 2035-2060 relative to survival during 1987-2008 in 14 of the 15 populations we studied. This decrease could reduce persistence of tortoise populations, especially in arid portions of their range. Temporal and spatial variation in drought conditions are important determinants of survival in adult desert tortoises.

Droughts and their social perception in the mass media (southern Spain)

AbstractIn the Mediterranean environment, drought is one of the extreme phenomena that has most direct consequences and complexity. It also has a direct social impact through the mass media, whose analysis, typology and characterization should be a priority in strategies to plan and mitigate effects. The appearance of droughts is slow, their occurrence is often not recognized until human activity and the environment have already been significantly affected, and drought effects persist for a long time after the drought has ended. The spatial distribution of droughts is highly complex, and significant variation in drought conditions is common between different locations. This makes it difficult to identify similar regions, especially in areas of climate transition, where the atmospheric influences are complex. This is the situation in the Iberian Peninsula (particularly the south of the peninsula), which straddles both temperate and sub‐tropical climates and in which precipitation is highly variable and spatial variability is substantial. In this study, we analysed rainfall anomalies (Standardized Precipitation Index, SPI) over the last 50 years at four representative meteorological stations in southern Spain, two on the coast (Málaga and Algarrobo) and two at the headwaters of river basins regulated by dams (Antequera and Periana). The aims of the study were to (1) analyse the types of drought, and their frequency and intensity and (2) establish the dynamics and evolution of the social perception of droughts in the context of global change, brought about by the communications media. The results showed the SPI was a useful tool for identifying dry anomalies that may feature in our field of study of meteorological and hydrological drought, depending on its duration. Meteorological drought impact on the eco‐geomorphological system is common and has had a particular development since the 1980s. Hydrological droughts are those that have had the greatest effect on water reserves, particularly when they occur in the headwaters of the watershed covered by reservoirs. Their importance has increased since the 1980s. Determination of drought periods and its impact mass media could have extraordinary relevance as a mechanism to establish the levels of awareness on sustainable use of resources. For future research, other socioeconomic and demographic variables should be considered to know the link between drought and water deficit. Copyright © 2012 Royal Meteorological Society

Relationships among Vegetation, Surficial Geology and Soil Water Content at the Pocono Mesic Till Barrens

EBERHARDT, R. W. AND R. E. LATHAM (Department of Biology, Swarthmore College, Swarthmore, PA 190811390). Relationships among vegetation, surficial geology and soil water content at the Pocono mesic till barrens. J. Torrey Bot. Soc. 127:115-124. 2000.-We examined relationships among vegetation, surficial geology, and soil water content in the Pocono till barrens, an assemblage of pitch pine-scrub oak-heath communities rich in rare species near Long Pond, Pennsylvania. Soil water content was measured using time domain reflectometry over three time periods in summer 1997 in four vegetation types (forest and three barrens communities) on two parent materials (Illinoian glacial till and upper Devonian sandstone bedrock). Wide variation in drought conditions among the time periods (quantified using the Keetch-Byram drought index) allowed for strong tests of differences in soil water-holding capacity among vegetation and parent material types. Soils of barrens and forests did not differ in water content at any depth or drought condition, which confirmed floristic evidence and earlier research that suggested pitch pine-scrub oak vegetation is not associated with xeric conditions. Disturbance history, and possibly the hypothesis of alternative community states, better explain the distinction between barrens and forests in the study area. Soils derived from till and bedrock had similar water contents at each time period, although bedrock soils may have been slightly wetter in the top 15 cm of the soil profile. This contradicts a presupposed relationship between parent material and soil water content and suggests that pitch pine-scrub oak vegetation might occur more extensively on mesic sites in northeastern Pennsylvania than previously thought. Contrary to expectation, barrens types did not differ in soil water content under any drought condition. These results suggest that rhodora barrens, which include diverse and abundant hydrophytes, are not restricted to sites relatively immune from drought. A testable alternative explanation is offered for the distribution of the rare rhodora barrens vegetation type.