Extent Of Drought Research Articles

Temporal and spatial analysis of meteorological drought characteristics in the upper Blue Nile river region

Drought is a costly natural hazard affecting socio-economic activity and agricultural livelihoods, as well as adversely impacting public health and threatening the sustainability of many natural environments. This study was carried out to characterize the temporal and spatial characteristics of meteorological drought in the upper Blue Nile basin to provide a framework for sustainable water resources management. Analysis of historical droughts was undertaken by converting observed monthly precipitation records (1960–2008), for 22 meteorological stations, to the standardized precipitation index (SPI). The SPI was computed at multiple time steps and the Mann–Kendall test was applied on monthly SPI time series for trend detection, and finally severity areal extent frequency (SAF) curves were developed to assess the recurrence pattern of drought severity. Several drought events were observed during the long rainy season and also the short rainy season, and the drought extent and influence were very severe in 1965 and the 1980s. Trend analysis showed statistically insignificant trends in SPI time series, and SAF curves indicated that droughts with a short return period and high degree will cover only small areas of the basin, while only a near-normal drought with a long return period may spread over the whole region.

Spatio-temporal variation in terminal drought over western India using dryness index derived from long-term MODIS data

Drought has always been one of the major hazards in semi-arid and arid regions of the world. This study was undertaken to investigate spatial trends in terminal drought over western India composed of the states of Rajasthan and Gujarat, which are characterized by semi-arid to arid climate. These two states have always been vulnerable to drought since they receive highly variable moderate to scanty rainfall. Leaf area index (LAI)-based temperature vegetation dryness index (TVDI) for the period 2002–2012 was computed using 8-day composites of Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and LAI datasets with 1-km spatial resolution. TVDI maps were prepared for all days of the year (DOY) for the months of September and October, which facilitated our understanding of the spatial extent of drought during different 8-day periods. Based on the analysis, it was found that the LAI-based TVDI could capture drought conditions over space and time. Temporal evolution of the observed crop moisture index (CMI) against TVDI reveals that the TVDI exhibited an increasing trend as the CMI decreased or became negative during the 2002 drought year. A significant and negative relationship (R2=0.23) with TVDI and CMI indicates more sensitivity of TVDI to soil moisture in sparse vegetation canopies under drought conditions. Spatial trends in terminal drought intensity were analyzed using linear regression and Mann–Kendall trend test. It was revealed that a majority of the northern part of the study area witnessed an increase in terminal drought intensity and the southern portion registered negative trends. With 80% confidence, it can be stated that the terminal drought intensity increased at scattered locations over southwestern and central Gujarat. However, over central and southwestern Rajasthan, decreasing trends were registered.

The Mesothalassia Bike‐Tour: (Re)Discovering Water by Riding With Scientists

The Mesothalassia Bike‐Tour: (Re)Discovering Water by Riding With Scientists

Identification of Agricultural Drought Extent Based on Vegetation Health Indices of Landsat Data: Case of Subang and Karawang, Indonesia

Agricultural drought monitoring is paramount in order to maintain food security in Indonesia, particularly in Subang and Karawang as the national rice production centers. In this paper, satellite-borne remote sensing data are tested for monitoring drought extent in about 184.486ha of both regencies. Vegetation Health Index (VHI), a vegetative drought indices based on remote sensing data, is studied in this case using long term sequence of 2000, 2005, 2010, and 2015 dry season Landsat data. VHI collates overall vegetation health, which in turn suitable to indicate agricultural drought extent. It measures either moisture vegetation/vegetation condition (VCI) or thermal condition of vegetation (TCI). Both indices were derived from Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) data respectively. The results revealed that VHI decreased more than 50 percent, from 30.86 in 2000 to 14.66 in 2015. This figure indicated drought extent intensified in research area, from mild drought to severe drought. The severity was mainly triggered by the rising LST from 27°C in 2000 to 40°C in 2015. In addition, there was a decreasing tendency of NDVI values in recent years, leading agricultural fields more susceptible to drought.

Drought Forecasting Using SPI and EDI under RCP-8.5 Climate Change Scenarios for Langat River Basin, Malaysia

In Malaysia, droughts often lead to water deficit and overcoming a lack of fresh water has become one of the important challenges in the country. Climate change have brought about a big environmental impact globally, such as the rise in sea levels, unavailability of fresh portal water and more extreme drought and flood events occurring and Malaysia is no different and not spared all this calamities. The Langat River Basin is located in a fast growing region in Peninsular Malaysia, the Greater Kuala Lumpur Valley and hence the implementation of the drought index in this basin is vital important and necessary. Normally drought characteristics can be determined or identified using the drought indices. The two drought indices were used in this study, namely the SPI (Standardized Precipitation Index) and the EDI (Effective Drought Index) to assess the severity, duration and extend of drought event. The CanESM2 outputs under Representative Concentration Pathway (RCP) 8.5 emission scenario of IPCC Fifth Assessment Report (AR5) were utilized to produce regionalized precipitation and temperature data. The GCM outputs were statistically downscaled using the Statistical Downscaling Model (SDSM) version 4.2.9. Next, the SPI for time scale period of 1-month, 6-months and 12-months (SPI-1, SPI-6 and SPI-12) and EDI were calculated for both the observed and statistically downscaled climate data to investigate and analyze the severity and extent of drought. Both indices were compared to get a more operational index between SPI-1, SPI-6, SPI-12 and EDI outlook for representing Malaysia drought events.

Assessing the Added Value of Dynamical Downscaling Using the Standardized Precipitation Index

In this study, the Standardized Precipitation Index (SPI) is used to ascertain the added value of dynamical downscaling over the contiguous United States. WRF is used as a regional climate model (RCM) to dynamically downscale reanalysis fields to compare values of SPI over drought timescales that have implications for agriculture and water resources planning. The regional climate generated by WRF has the largest improvement over reanalysis for SPI correlation with observations as the drought timescale increases. This suggests that dynamically downscaled fields may be more reliable than larger-scale fields for water resource applications (e.g., water storage within reservoirs). WRF improves the timing and intensity of moderate to extreme wet and dry periods, even in regions with homogenous terrain. This study also examines changes in SPI from the extreme drought of 1988 and three “drought busting” tropical storms. Each of those events illustrates the importance of using downscaling to resolve the spatial extent of droughts. The analysis of the “drought busting” tropical storms demonstrates that while the impact of these storms on ending prolonged droughts is improved by the RCM relative to the reanalysis, it remains underestimated. These results illustrate the importance and some limitations of using RCMs to project drought.

On the role of soil moisture in the generation of heavy rainfall during the Oder flood event in July 1997

Soil moisture–atmosphere feedbacks play an important role in the regional climate over many regions worldwide, not only for the mean climate but also for extreme events. Several studies have shown that the extent and severity of droughts and heat waves can be significantly impacted by dry or wet soil moisture conditions. To date, the impact of soil moisture on heavy rainfall events has been less frequently investigated. Thus, we consider the role of soil moisture in the formation of heavy rainfall using the Oder flood event in July 1997 as an example. Here, we used the regional climate model CCLM as an uncoupled standalone model and the coupled COSTRICE system, where CCLM is coupled with an ocean and a sea ice model over the Baltic and North Sea regions. The results from climate simulations over Europe show that the coupled model can capture the second phase (18–20 July) of heavy rainfall that led to the Oder flood, while the uncoupled model does not. Sensitivity experiments demonstrate that the better performance of the coupled model can be attributed to the simulated soil moisture conditions in July 1997 in Central Europe, which were wetter for the coupled model than for the uncoupled model. This finding indicates that the soil moisture preceding the event significantly impacted the generation of heavy rainfall in this second phase. The better simulation in the coupled model also implies the added value that the atmosphere–ocean coupling has on the simulation of this specific extreme event. As none of the model versions captured the first phase (4–8 July), despite the differences in soil moisture, it can be concluded that the importance of soil moisture for the generation of heavy rainfall events strongly depends on the event and the general circulation pattern associated with it.

Temporal-Spatial Variation of Drought Indicated by SPI and SPEI in Ningxia Hui Autonomous Region, China

The Ningxia Hui Autonomous Region of China (Ningxia) is an important food production area in northwest China severely affected by drought. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were calculated based on monthly meteorological data to explore climate change and variation in drought intensity, duration, frequency, and spatial extent in Ningxia during 1972–2011. Results show that the SPEI is more applicable than the SPI for exploring climate change and drought variation in Ningxia. The Ningxia climate experienced a significant drying tendency. Annual SPEI decreased about 0.37 decade−1 during 1972–2011. Drought was exacerbated by this drying tendency. Regional average duration, maximum duration, intensity, and frequency of drought identified by the SPEI increased by one month, three months, 0.15%, and 36.1%, respectively, during 1992–2011 compared to the period of 1972–1991. The spatial extent of drought identified by the SPEI increased about 14.4% decade−1 in the spring during 1972–2011. Spatially, drought frequency increased from north to south. Average intensity (maximum duration) of drought calculated by the SPEI increased (decreased) northward and southward from the central arid area.

South African droughts and decadal variability

We explore the historical occurrence of extensive droughts over South Africa within the context of decadal climate variability. A Standardized Precipitation Index dataset is developed and used to assess the spatial extent of droughts in South Africa for the period 1920–2014. The most extensive droughts over the period at various time scales are identified and discussed. Results of a wavelet analysis are also presented towards identifying statistically significant regional climate variation with which the occurrence of droughts is associated. The occurrence of drought with respect to the El Nino Southern Oscillation and decadal climate variability is also considered. Significant associations between short-term droughts and decadal variability are pointed out. An overview of global sea surface temperature and Southern Hemisphere sea-level pressure associations with three prominent scales of multi-year climate variability is given. Dry epochs at the most prominent time scales are shown to be significantly negatively related to the Southern Annular Mode and associated sea surface temperature anomalies in the mid-to-high southern latitudes. Relations with the Pacific Decadal Oscillation, Inter-Decadal Pacific Oscillation and ENSO, which are all associated with a Southern Annular Mode of opposite sign, are also highlighted.

Use of the Standardized Precipitation Evapotranspiration Index (SPEI) to Characterize the Drying Trend in Southwest China from 1982–2012

In this study, the Standardized Precipitation Evaporation Index (SPEI) was applied to characterize the drought conditions in Southwest China from 1982–2012. The SPEI was calculated by precipitation and temperature data for various accumulation periods. Based on the SPEI, the multi-scale patterns, the trend, and the spatio-temporal extent of drought were evaluated, respectively. The results explicitly showed a drying trend of Southwest China. The mean SPEI values at five time scales all decreased significantly. Some moderate and severe droughts were captured after 2005 and the droughts were even getting aggravated. By examining the spatio-temporal extent, the aggravating condition of drought was further revealed. To investigate the performance of SPEI, correlation analysis was conducted between SPEI and two remotely sensed drought indices: Soil Moisture Condition Index (SMCI) and Vegetation Condition Index (VCI). The comparison was also conducted with the Standardized Precipitation Index (SPI). The results showed that for both SMCI and VCI, the SPI and SPEI had approximate correlations with them. The SPEI could better monitor the soil moisture than the SPI in months with significant increase of temperature. The correlations between the VCI and SPI/SPEI were lower; nevertheless, the SPEI was slightly superior to the SPI.

Drought risk during the early growing season in Sahelian Sudan

The African countries are known to be the most vulnerable to climate change and variability and food insecurity. An effort is devoted in this study to assess the year-by-year drought risk to sorghum and millet during the onset of the growing season in the Sudanese Sahel. A recently developed drought risk index (DRI) is used for this purpose. The DRI is a multiplicative formula of six variables, namely frequency, duration, severity and spatial extent of drought, production level and coping capacity through irrigation. A significant finding is that drought at the early stage of the growing season can pose a dramatic risk to crop yield. Analysis and results for 12 provincial states of the region reveal a strong relationship between the probabilistic DRI and yield of these major crops. This relationship offers vital information of a considerable potential risk to crop yield if the drought occurs as early as June and July. Significant proportion of the variations in the crop yield can be explained by the DRI. June DRI expresses up to 68 and 90 % of the variations in sorghum and millet yields, respectively. Up to 84 and 68 % of the respective yields can be explained by June–July DRI. Based on the regional analysis, the median area under drought risk for the entire data period (1970–2006) is 43 % for sorghum and 40 % for millet. From the frequency analysis, the occurrence probabilities of these medians are 41 and 34 %, respectively. Evidence is presented that the agricultural drought risk in this part of the African Sahel is still high during the period 1991 onwards when annual rainfall is said to have been recovering. The present results provide useful information for drought forecasters and decision making in crop and disaster planning and management, especially in view of projected drier and warmer climate conditions during this part of the growing season. Also, the DRI proves to be robust spatially and temporally for agricultural monitoring under situations of limited meteorological data and could be tested for other regions in the African Sahel.

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part II assessment results and management implications

The 781,000km2 (193million acre) United States National Forests and Grasslands system (NF) provides important ecosystem services such as clean water supply, timber production, wildlife habitat, and recreation opportunities to the American public. Quantifying the historical impacts of climate change and drought on ecosystem functions at the national scale is essential to develop sound forest management and watershed restoration plans under a changing climate. This study applied the previously validated Water Supply and Stress Index model (WaSSI) to 170 NFs in the conterminous U.S. (CONUS) to examine how historical extreme droughts have affected forest water yield (Q) and gross primary productivity (GPP). For each NF, we focused on the five years with the lowest annual SPI3 (Standardized Precipitation Index on a 3-month time scale) during 1962–2012. The extent of extreme droughts as measured by the number of NFs and total area affected by droughts has increased during the last decade. Across all lands in CONUS, the most extreme drought during the past decade occurred in 2002, resulting in a mean reduction of Q by 32% and GPP by 20%. For the 170 individual NFs, on average, the top-five droughts represented a reduction in precipitation by 145mmyr−1 (or 22%), causing reductions in evapotranspiration by 29mmyr−1 (or 8%), Q by 110mmyr−1 (or 37%) and GPP by 65gCm−2yr−1 (or 9%). The responses of the forest hydrology and productivity to the top-five droughts varied spatially due to different land-surface characteristics (e.g., climatology and vegetation) and drought severity at each NF. This study provides a comprehensive benchmark assessment of likely drought impacts on the hydrology and productivity in NFs using consistent methods and datasets across the conterminous U.S. The study results are useful to the forestry decision makers for developing appropriate strategies to restore and protect ecosystem services in anticipating potential future droughts and climate change.

Paleoprecipitation Reconstruction in the Indus and Ganges Basins by Inverse Modeling of Tree-Ring-Based PDSI

Abstract The South Asian monsoon is critically important for agricultural production in the region that includes the vast, fertile Indus and Ganges basins. However, the behavior of the South Asian monsoon is not well understood because of its complex nature, and existing instrumental climate records are insufficient for investigating the risks of the low-frequency but high-impact megadroughts that have historically occurred. This paper develops an inverse Palmer drought severity index (PDSI) model to retrieve paleoprecipitation for the region during the time period of 1300–1899, using available data of the water-holding capacity of soil, temperature, and reconstructed PDSI based on the tree-ring analysis of Cook et al.. Temperature data are reconstructed by a regression analysis utilizing an existing temperature reconstruction in an adjacent region and the Pacific decadal oscillation. Based on the retrieved paleoprecipitation, several megadroughts are identified during the reconstruction period. The drought frequency in the Indus basin is higher than that in the Ganges basin. The intensity, frequency, and spatial extent of severe droughts increased from 1300–1899 to 1900–2010. As a signal of climate change, increasing intensity and frequency of severe drought in the Indus and Ganges River basins needs adaptation strategies and drought preparedness measures to secure the food production in this area.

Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI)

Owing to its severe effect on productivity of rain-fed crops and indirect effect on employment as well as per capita income, agricultural drought has become a prime concern worldwide. The occurrence of drought is mainly a climatic phenomenon which cannot be eliminated. However, its effects can be reduced if actual spatio-temporal information related to crop status is available to the decision makers. The present study attempts to assess the efficiency of remote sensing and GIS techniques for monitoring the spatio-temporal extent of agricultural drought. In the present study, NOAA-AVHRR NDVI data were used for monitoring agricultural drought through NDVI based Vegetation Condition Index. VCI was calculated for whole Rajasthan using the long term NDVI images which reveals the occurrence of drought related crop stress during the year 2002. The VCI values of normal (2003) and drought (2002) year were compared with meteorological based Standardized Precipitation Index (SPI), Rainfall Anomaly Index and Yield Anomaly Index and a good agreement was found among them. The correlation coefficient between VCI and yield of major rain-fed crops (r>0.75) also supports the efficiency of this remote sensing derived index for assessing agricultural drought.

Quantifying sensitivity to droughts – an experimental modeling approach

Abstract. Meteorological droughts like those in summer 2003 or spring 2011 in Europe are expected to become more frequent in the future. Although the spatial extent of these drought events was large, not all regions were affected in the same way. Many catchments reacted strongly to the meteorological droughts showing low levels of streamflow and groundwater, while others hardly reacted. Also, the extent of the hydrological drought for specific catchments was different between these two historical events due to different initial conditions and drought propagation processes. This leads to the important question of how to detect and quantify the sensitivity of a catchment to meteorological droughts. To assess this question we designed hydrological model experiments using a conceptual rainfall-runoff model. Two drought scenarios were constructed by selecting precipitation and temperature observations based on certain criteria: one scenario was a modest but constant progression of drying based on sorting the years of observations according to annual precipitation amounts. The other scenario was a more extreme progression of drying based on selecting months from different years, forming a year with the wettest months through to a year with the driest months. Both scenarios retained the observed intra-annual seasonality for the region. We evaluated the sensitivity of 24 Swiss catchments to these scenarios by analyzing the simulated discharge time series and modeled storage. Mean catchment elevation, slope and area were the main controls on the sensitivity of catchment discharge to precipitation. Generally, catchments at higher elevation and with steeper slopes appeared less sensitive to meteorological droughts than catchments at lower elevations with less steep slopes.

Development of an Experimental Near-Real-Time Drought Monitor for India*

Abstract Persistent and widespread drought hampers water resources management and crop production. India has faced frequent droughts over the last few decades. Despite the detrimental impacts of droughts in India, a real-time monitoring system at appropriate spatial and temporal resolution has been lacking. Here, an experimental drought monitor for India is developed that operates daily at a spatial resolution of 0.25° and provides near-real-time information on droughts. The real-time daily precipitation data are obtained from the Tropical Rainfall Measurement Mission (TRMM) while daily temperatures are obtained from the Global Ensemble Forecast System (GEFS), version 2. Near-real-time precipitation and temperatures are bias corrected using the historic precipitation and temperature data from the India Meteorological Department (IMD). Data extending from the past to near present were reconstructed by combining IMD (1969–2010) with real-time, bias-corrected TRMM and GEFS datasets (2010 onward). The experimental drought monitor provides information on meteorological, hydrological, and agricultural droughts using the standardized precipitation index (SPI), standardized runoff index (SRI), and standardized soil moisture index (SSI), respectively. Soil moisture and runoff are simulated using the Variable Infiltration Capacity (VIC) model in near–real time to estimate the severity and areal extent of agricultural and hydrological droughts. The severity and areal extent of droughts from the experimental drought monitor are successfully evaluated against a satellite-based drought severity index. The experimental drought monitor provides high-resolution drought information (district level) that can be valuable for natural resources management and policy making.

Agricultural drought trends and mitigation in Tillaberí, Niger

Whether aggravated agricultural drought in the Sahel is related to a changing climate (meteorological drought, i.e., deficit of rainfall or unfavourable rainfall distribution) or to land use and land degradation (soil-water drought, i.e., decreased water infilitration and water holding capacity) is a much-debated issue. Global climate models and trend analysis show little agreement on how rainfall and meteorological drought are changing in the region, and research has increasingly attributed agricultural drought to an imbalanced rainwater distribution over the root zone caused by human-induced land degradation. This paper investigates the extent of both meteorological and soil-water drought on “laterite” soils in the Tillaberí region of Niger and their effect on millet (Pennisetum glaucum (L.) R. Br.) growth by combining monthly (1905–1996) and daily (1989–2010) rainfall analysis with analysis of the root zone water distribution under different management practices. The treatments include: zaï + manure (Z), demi-lunes + manure (DL), scarification + manure (SCAR), control + manure (CF) and control (C). Our findings suggest that increasing agricultural drought does not originate from a decreasing annual amount of rainfall. However, other daily rainfall parameters more important for crop biomass productivity than total rainfall amount, such as the number of dry spells, do appear to have recently worsened. Dry-spell analysis showed increased drought risks during the vegetative growth phase (0–40 DAS) and the vulnerable grain formation phase (90–110 DAS, Days After Sowing). The extremely low grain yields and values of soil-water storage below the critical value for water stress of the control treatments, moreover, confirm poor root zone water distribution. DL and Z however, show potential, to mitigate both dry spells and soil-water drought, as they induce an important increase of soil-water storage, resulting in higher grain yields. In order to optimize these water and soil conservation (WSC) techniques and to increase their potential for drought mitigation, the underlying features enabling increased soil-water storage, including water balance analysis, soil physical properties, nutrient management and system design, should be tackled in future studies.

Constraints of VSWI in the Estimation of Drought Extent Using Landsat Data: A Case of Tuban, Indonesia

Existing drought-impacted data are generally rooted from individual reports, which under-represent spatial information. To improve the report, some meteorological satellites have been employed. Nonetheless, due to lacking of spatial resolution, the scale of the data is often excessively coarse. With the availability of long-term Landsat data, estimated extent of drought has been studied. One of the latest methods for this purpose is Vegetation Supply Water Index (VSWI). VSWI is defined as a ratio between vegetation index (in this case NDVI) and land surface temperature (LST, presented in Kelvin). Both data can be derived from remote sensing data containing multispectral reflectance and thermal data, which are available in Landsat data after calibration procedure. In this research, Landsat 7 sensor was applied considering its temporal span. Landsat data were atmospherically corrected to avoid misinterpretation of the results. We found that VSWI can accommodate various state of drought in agricultural fields. Severely affected fields are represented in dark tone, illustrating the absence of vegetation cover when surface temperature rises. Nonetheless, shortcomings of the technique are visually observable. Based on two kinds of rice field (irrigated and rainfed) coupled with two states of field condition (wet and dry), we conclude that dried and waterlogged irrigated rice fields are inseparable due similar value of NDVI. In contrast, vegetated rice field has fairly high VSWI value. The results indicate that further analysis incorporating water index can improve discrimination process.

Temporal and spatial variability of drought in Huang-Huai-Hai River Basin, China

Drought is a kind of extreme hydrological event. With the penetration of climate change impact, severity, areal extent, and frequency of drought are increasing, especially in Huang-Huai-Hai River Basin, which plays a key role in China’s agriculture production. Analyzing the regional temporal and spatial variability in the context of climate change could provide a basis for the evasion of disasters and risk. The maximum number of consecutive dry days was selected as the indicator to analyze the decadal variability of drought severity, areal extent, and spatial variability of drought frequency in different seasons in Huang-Huai-Hai River Basin. Based on these, temporal and spatial variability of two kinds of special extreme events—consecutive drought and heavy rain after drought—were studied. The results showed that: (1) Huang-Huai-Hai River Basin mainly experienced moderate drought and severe drought. Moderate drought mainly occurs in autumn. High-frequency region of moderate drought is located in the plain of Huang-Huai-Hai River Basin, and its area is approximately 22.7 % of Huang-Huai-Hai River Basin. Severe drought often occurs in spring with high-frequency region in the upstream of the Yellow River. The area of this high-frequency region is about 6 % of Huang-Huai-Hai River Basin. (2) During 1961~2011, the areal extent of summer severe drought, autumn severe drought, and extreme drought all showed increasing trend, in which the increasing trend of the autumn severe drought area in the Yellow River has reached the significance level α = 0.05. (3) Consecutive drought of several seasons often took place in Ningxia plain and Hetao plain which lie in the northwest of the Yellow River Basin. In the recent 20 years, consecutive drought from spring to summer and consecutive drought from summer to autumn occurred frequently. Drought-flood abrupt alternation such as heavy rain after drought often occurred in summer temporally and Huaihe River Basin spatially.

Soil Moisture Droughts under the Retrospective and Projected Climate in India*

Abstract Changes in precipitation, air temperature, and model-simulated soil moisture were examined for the observed (1950–2008) and projected (2010–99) climate for the sowing period of Kharif and Rabi [KHARIF_SOW (May–July) and RABI_SOW (October–December)] and the entire Kharif and Rabi [KHARIF (May–October) and RABI (October–April)] crop-growing periods in India. During the KHARIF_SOW and KHARIF periods, precipitation declined significantly in the Gangetic Plain, which in turn resulted in declines in soil moisture. Statistically significant warming trends were noticed as all-India-averaged air temperature increased by 0.40°, 0.90°, and 0.70°C in the KHARIF, RABI_SOW, and RABI periods, respectively, during 1950–2008. Frequency and areal extent of soil moisture–based droughts increased substantially during the latter half (1980–2008) of the observed period. Under the projected climate (2010–99), precipitation, air temperature, and soil moisture are projected to increase in all four crop-growing seasons. In the projected climate, all-India ensemble mean precipitation, air temperature, and soil moisture are projected to increase up to 39% (RABI_SOW period), 2.3°C, and 5.3%, respectively, in the crop-growing periods. While projected changes in air temperature are robust across India, robust increases in precipitation and soil moisture are projected to occur in the end-term (2070–99) climate. Frequency and areal extents of soil moisture–based severe, extreme, and exceptional droughts are projected to increase in the near- (2010–39) and midterm (2040–69) climate in the majority of crop-growing seasons in India. However, frequency and areal extent of droughts during the crop-growing period are projected to decline in the end-term climate in the entire crop-growing period because of projected increases in the monsoon season precipitation.