Emerging hotspots of agricultural drought under climate change

Southern China is the nation’s major grain-producing areas. In recent years, under the background of global climate change, regional drought disasters have been increased, and caused serious agricultural drought loss and obvious anomaly characteristics. However, the variation characteristics of agricultural drought loss and drought hazard mechanism are still unclear in south China, which seriously affects the in-depth understanding of southern agriculture drought and its assessments. Therefore, based on agricultural drought disaster conditions, crop acreage, meteorological drought monitoring index and conventional meteorological factors and other related data, systematical and comprehensive agricultural drought loss rate variation and its relationship with climate-formative factors have been analyzed in recent 50 years. Agricultural drought comprehensive loss rate is used as an agricultural drought disaster or risk characteristics loss severity index. Agricultural drought comprehensive loss rate is an integrated index that can reflect severity of loss caused by agricultural drought disaster and established by drought-affected crop planting area at different levels and planting area. The results showed that comprehensive agricultural drought loss rate increased obviously and with a rate of about 2.5%, the relative increased rate reached to as high as 80%. Agricultural drought disasters loss has been increased seriously and doughty disasters risk also has been increased more higher than before, southwest is more apparently than south and southeast. With respect to spatial distribution, probability of climate tendency rate for comprehensive loss rate in south China ranges from 0.1%/10 a to 1.8%/ 10 a. In addition, increase in climate tendency rate in the southwest is more obvious than that in the south and southeast. And, as a result of crop growth stages on the climate elements in dependence on different season and climate factors of non-uniform distribution characteristics, agricultural drought loss rate is mainly affected by key period meteorological drought and the effects of climate change, mainly precipitation and temperature. As for precipitation, 6 months including April, May, June, July, August and October serve as key impacting periods. As for temperature, 5 months including January, June, July, August and October serve as key impacting periods. As for MCI, only two months including July and August serve as key impacting periods. But other climatic factors change is not obvious influence on agricultural drought loss rate. In south China, key impacting periods of MCI coincide with key growth phases of most crops; common key impacting periods of temperature and precipitation coincide with major growth phases of most crops in south China; key impacting periods of precipitation coincide with major or key growth phases of some crops; while key impacting periods of temperature coincide with key periods for overwintering of winter wheat. As a result, the fitting relationship between the south agricultural drought loss rate and the critical period climate factor is much better than its relationship with throughout annual climate, and more key climate factors has more obvious advantages in fitting relationship compared with single factor. Such multi-factor relationship can not only describe the disaster-causing effect of meteorological drought, but also reflect the roles played by severe evapotranspiration and soaking rain processes on drought disaster-causing process. Meanwhile, the agricultural drought loss assessment model with multiple factor relationship had been done for cross validation method, correlation, error level and reliability are the relevance of the ideal, which indicated that the model is an optional reliable and objective model for evaluating the impact of drought disasters on agricultural yield in south China or estimation on risks of agricultural drought disasters in future climate scenarios. The study results have important scientific reference significance for the development of south China agriculture dry drought damage assessment method.

Sub-Saharan Africa is the only region in the world that has become poorer in the last generation. The climate change is expected to add significantly to the development challenges of ensuring food security and poverty reduction. The majority of these countries are dependent on rain-fed agriculture (96 %) for their subsistence, thereby making them highly vulnerable to recent climatic change. Adaptation to climate change in the crop production sector is therefore very imperative in providing food security and protecting the livelihood of rural poor smallholder farmers and communities. This study used both the top-down and the bottom-up approach in analysing the sensitivity and vulnerability of subsistence farmers in the Sudano-Sahel of Cameroon on climatic change. Analyses of agricultural droughts using the Standard Precipitation Index (SPI) and statistical models were used in investigating the impacts of recent climatic changes on two staple crops, millet Pennisetum glaucum L. and sorghum Sorghum bicolor L. (Moench). Household questionnaires and interviews were also conducted and subsistence farmers’ perceptions on climatic change were then analyzed. The findings showed that local subsistence farming communities perceived changes in rainfall and its frequency and rise in temperature. The results indicated that climatic trends appear to be responsible for between 12 and 24 % of the yield variation for both millet and sorghum, with maximum temperature at the growing season being the dominant influence. The droughts were observed in up to about 9 % of the years analyzed. Pertaining to climatic variability and change adaptation, subsistence farmers have changed their planting dates, crop varieties as well as switched from crops to livestock and off-farming activities among many others. The result further highlighted the lack of money, poor access to climate information, the encroachment of the desert and the shortage of man power as some of the factors hindering subsistence farmers’ ability to climate change adaptation.

The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021–2050), with respect to baseline (1981–2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. ‘Once in a Decade’ agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.

Exploring the influence of climate change-induced drought propagation on wetlands

Drought is one of the most devastating natural hazards, affecting ecosystems, communities, and their economies worldwide. According to the last IPCC report, is expected, indeed, an increase in severity and frequency of drought under a changing climate, at least over Mediterranean regions. However, is still more uncertain the effect of climate change in other regions in the world. To analyze the effect of this extreme phenomenon, many drought indices have been developed in recent years based on different hydroclimatic variables and depending on the type of drought under study. Among these indices it is worth mentioning, for meteorological droughts, the Standardized Precipitation Index (SPI) or the Standardized Precipitation Evapotranspiration Index (SPEI), agricultural drought indices such as the Standardized Soil moisture Index (SSI), or those that make use of different variables or multivariate indices such as the Multivariate Standardized Drought Index (MSDI) that combines soil moisture and precipitation, and the Standardized Precipitation Evapotranspiration Soil Moisture Index (SPESMI), an adaptation of the MSDI that incorporates the effect of potential evapotranspiration on the water balance. This work aims to analyze from meteorological to agricultural droughts projections over Europe using standardized drought indices. For this, we evaluate drought characteristics (i.e., duration and intensity of drought events) for the different drought indicator at scales from 1 to 48 months using an ensemble of climate change regional projections from EURO-CORDEX under a business-as-usual climate change scenario. Changes for the future were analyzed for global warming corresponding to 1.5º, 2º, 3º and 4ºC of temperature above pre-industrial levels. The results of this analysis could offer useful information for adaptation strategies to climate change. Keywords: standardized drought indices, agricultural droughts, Europe, climate change. projections. Acknowledgments: This research was financed by the project P20_00035 funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, the project “Thematic Center on Mountain Ecosystem & Remote sensing, Deep learning-AIe-Services University of Granada-SierraNevada”(LifeWatch-2019-10-UGR-01), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program2014-2020 (POPE), LifeWatch-ERIC action line, and by the project PID2021-126401OB-I00 funded by MCIN/AEI/ 10.13039/501100011033/FEDER Una manera de hacer Europa.

Abstract. Despite uncertainties in future climates, there is considerable evidence that there will be substantial impacts on the environment and human interests. Climate change will affect the hydrology of a region through changes in the timing, amount, and form of precipitation, evaporation and transpiration rates, and soil moisture, which in turn affect also the drought characteristics in a region. Droughts are long-term phenomena affecting large regions causing significant damages both in human lives and economic losses. The most widely used approach in regional climate impact studies is to combine the output of the General Circulation Models (GCMs) with an impact model. The outputs of Global Circulation Model CGCMa2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. In this study, a statistical downscaling method has been applied for monthly precipitation. The methodology is based on multiple regression of GCM predictant variables with observed precipitation developed in an earlier paper (Loukas et al., 2008) and the application of a stochastic timeseries model for precipitation residuals simulation (white noise). The methodology was developed for historical period (1960–1990) and validated against observed monthly precipitation for period 1990–2002 in Lake Karla watershed, Thessaly, Greece. The validation indicated the accuracy of the methodology and the uncertainties propagated by the downscaling procedure in the estimation of a meteorological drought index the Standardized Precipitation Index (SPI) at multiple timescales. Subsequently, monthly precipitation and SPI were estimated for two future periods 2020–2050 and 2070–2100. The results of the present study indicate the accuracy, reliability and uncertainty of the statistical downscaling method for the assessment of climate change on hydrological, agricultural and water resources droughts. Results show that climate change will have a major impact on droughts but the uncertainty introduced is quite large and is increasing as SPI timescale increases. Larger timescales of SPI, which, are used to monitor hydrological and water resources droughts, are more sensitive to climate change than smaller timescales, which, are used to monitor meteorological and agricultural droughts. Future drought predictions should be handled with caution and their uncertainty should always be evaluated as results demonstrate.

Climate change impacts on water security in global drylands

The objective of this study is to analyze future drought characteristics in meteorological, hydrology, and agricultural droughts under the impact of changing climate in the Kessie watershed, upper Blue Nile Basin, using three drought indices; Reconnaissance Drought Index (RDI), Streamflow Drought Index (SDI) and Agricultural Standardized Precipitation Index (aSPI), respectively. The study used baseline data (1985–2014) and future (2041–2100) downscaled from Coupled Model Intercomparison Project 6 (CMIP-6) based on the three Global Climate Models (GCMs) projections under two scenarios of the Shared Socioeconomic Pathways (SSP) (SSP2-4.5, SSP5-8.5) with well-calibrated Soil and Water Assessment Tool (SWAT) model to simulate future streamflow for two future time horizons 2050s (2041–2070) and 2080s (2071–2100). Based on the yearly time scale, our results indicate that droughts of a high magnitude and rising frequency would affect most of the research area. These droughts will be either meteorological (RDI), agricultural (aSPI), or hydrological (SDI). Short-term agricultural and hydrological droughts are also anticipated to occur more frequently. The projected increases in frequency and trend of agricultural and hydrological droughts in this area are greater due to the anticipated drop in annual rainfall and the larger increase in mean annual temperature in the middle of Kessie. Furthermore, compared to hydrological and agricultural droughts, meteorological drought is less vulnerable to climate change; but, as the accumulation period lengthens, a stronger association develops between hydrological and agricultural droughts. These findings may be useful for water resources management and future planning for mitigation and adaptation to the climate change impact in the study area.

Climate change impacts on meteorological, agricultural and hydrological droughts in China

Correlation of climate change and human activities with agricultural drought and its impact on the net primary production of winter wheat

Abstract. Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model’s applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP, last access: 4 April 2024).

Abstract. This study examines future drought propagation (the temporal transition from meteorological to agricultural droughts), persistence (inter-seasonal agricultural droughts), and spatial concurrence (simultaneous occurrence of monsoonal agricultural droughts across regions) under climate change using a multivariate copula approach in monsoon-dominant Asia. The standardised precipitation index (SPI) and standardised soil moisture index (SSI) are used to analyse meteorological and agricultural droughts, respectively. Under the worst-case emission scenario (Shared Socioeconomic Pathway, SSP5-8.5), South Asia (excluding western and peninsular India) and eastern China are projected to experience intensified drought propagation compared to in the historical period (1975–2014). In addition to increased propagation in these regions, the propagated agricultural droughts are expected to persist across seasons in the future. On the hydrologically significant Tibetan Plateau, all-season droughts that were historically rare, with return periods exceeding 50 years, could occur as frequently as once every 5 years in the far-future period (2061–2100). Random forest models indicate that the temperature is a key driver of future agricultural droughts in nearly half of the study area. The increasing non-rainfall-related agricultural droughts in the far future could be attributed to the rise in temperature. Based on bivariate return periods of spatial concurrence, frequent future spatial drought concurrence is anticipated between populous South Asia and East Asia compared to the historical time frame, posing risks to water and food security. Conversely, Southeast Asia is projected to experience reduced spatial drought concurrence with other regions, which could encourage greater regional cooperation. Overall, this comprehensive approach, which integrates three aspects of drought dynamics, offers valuable insights for climate change mitigation, planning, and adaptation.

Chapter 4 - Climate variability and agriculture

The global challenge of Climate change poses a significant threat to humanity, with its impacts already being felt in various parts of the world through unpredictable and severe weather events leading to property damage and loss of life (IPCC, 2014). Community resilience is vital in reducing the losses caused by climate change, and it depends on an understanding of perceived risks, vulnerabilities, and local efforts to mitigate them. The Chittagong Hill Tracts of Bangladesh is one of the regions that is particularly vulnerable to climate change, due to its geography, degradation of forests, sensitivity of livelihoods, and low capacity in comparison to other parts of the country (World bank 2018).Although vulnerability assessments to climate change have been conducted previously, there remains a gap in involving indigenous communities residing in hilly areas of Bangladesh. The recognition of climate change risks as perceived by local communities could serve as a foundation for developing locally-led adaptation plans aimed at building local resilience.The Basonto Mon watershed is located in Rangamati district of Bangladesh, with GPS coordinates of 22˚ 40.218"N 92˚ 16.620" E (GPS coordinates derived from Google Earth) and an elevation of 390 feet above sea level. The area comprises of five villages from varying elevations and is primarily inhabited by the Chakma community. There are 269 households in the region, primarily relying on Jhum cultivation, agriculture on fringe lands, and seasonal labor for their livelihoods, with an average annual household income of BDT 96000 (approximately US$ 1132). About 76% of the community consider themselves under serious threat from the effects of climate change, while 24% have limited understanding of the issue. Approximately 20% of the respondents believe that their livelihoods will be mostly affected by climate change, while 78% identified multiple impacts including health, disaster intensity, family workload, and more. The region is also facing severe soil erosion caused by deforestation, incorrect agricultural practices, and the monoculture of forest species such as teak. The community is at risk from agricultural drought, flash floods, landslides, cyclones, among other things, with the most impacted months being March to August.Climate drivers in the area include erratic rainfall, sudden heavy downpours, increased number of rainless days, and rising temperatures. Acute water scarcity caused by the drying of streams is another major concern for the community and has a widespread impact on women and their families. The most vulnerable sectors identified are the forest and ecosystem, livelihoods, and water security.Approximately 75% of the population is literate and has access to educational institutions and health clinics. However, the environment is fragile. To address this, there are three main priorities: 1) preserving the forests through cooperative efforts, reforestation, and public education, 2) promoting sustainable and climate-resistant agriculture, as well as alternative livelihoods and market access, and 3) improving access to clean water and preserving water sources through community-led management. Key stakeholders, such as the CHT institutions and local government bodies, are crucial in supporting the community in becoming more resilient to the effects of climate change.

Quantitation of meteorological, hydrological and agricultural drought under climate change in the East River basin of south China