Assessing Drought Vulnerability of Bulgarian Agriculture through Model Simulations

This study assesses vulnerability of agriculture to drought, using WINISAREG model and seasonal SPI2-index for eight climate regions （1951-2004）. Results relative to Plovdiv show that in soils of large TAW （total available water） net irrigation requirements NIRs range from 0 to 380 mm. In soils of small TAW, NIRs reach 440 mm in the very dry year. NIRs in Sofia/Silistra are about 100 mm smaller than in Plovdiv while in Sandanski they are 30-110 mm larger. Rainfed maize is associated with great yield variability （29% 〈 Cv 〈 72%）. Considering an economical RYD （relative yield decrease） threshold, 32% of years are risky when TA Wis large in Plovdiv that is double than in Sofia and half than in Sandanski. In North Bulgaria the risky years are 10% in Pleven/Silistra that is half than in Lom. In Plovdiv region reliable relationships （R2 〉 91%） were found relating the SPI2 ＂July-Aug.＂ with simulated RYD of rainfed maize while remaining relationships were less accurate （73% 〈 R2 〈 86%）. Economical losses are produced when High Peak Season SPI2 〈 ＋ 0.20 in Sandanski, SPI2 〈 - 0.50 in Plovdiv and SPI2 〈 - 0.90 in Sofia. In North Bulgaria the SPI2 threshold ranges from - 0.75 to - 1.50. Derived reliable relationships and SPl-thresholds are used for drought vulnerability mapping.

Assessment of Agricultural Drought Vulnerability Based on Crop Growth Stages:A Case Study of Huaibei Plain,China

Climate change can lead to and intensify drought disasters.Quantifying the vulnerability of disaster-affected elements is significant for understanding the mechanisms that transform drought intensity into eventual loss.This study proposed a growth-stage-based drought vulnerability index(GDVI)of soybean using meteorological,groundwater,land use,and field experiment data and crop growth model simulation.The CROPGRO-Soybean model was used to simulate crop growth and water deficit.Four growth stages were considered since the sensitivity of soybean to drought is strictly related to the growth stage.The GDVI was applied to the Huaibei Plain,Anhui Province,China,with the goal of quantifying the spatiotemporal characteristics of soybean drought vulnerability in typical years and growth stages.The results show that:(1)The sensitivity of leaf-related parameters exceeded that of other parameters during the vegetative growth stage,whereas the top weight and grain yield showed a higher sensitivity in the reproductive growth stage;(2)A semi-logarithmic law can describe the relationship between the drought sensitivity indicators and the GDVI during the four growth stages.The pod-filling phase is the most vulnerable stage for water deficit and with the highest loss upper limit(over 70%);(3)The 2001 and 2002 seasons were the driest time during 1997-2006.Fuyang and Huainan Cities were more vulnerable to drought than other regions on the Huaibei Plain in 2001,while Huaibei and Suzhou Cities were the most susceptible areas in 2002.The results could provide effective decision support for the categorization of areas vulnerable to droughts.

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil,groundwater and agricultural yield.It has been recognized as one of the most pervasive global change drivers to affect the soil.Soil being a weakly renewable resource takes a long time to form,but it takes no time to degrade.However,the response of soil to drought conditions as soil loss is not manifested in the existing literature.Thus,this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India.MODIS remote sensing data was utilized for driving drought indices during 2000-2019.Firstly,we constricted Temperature condition index(TCI)and Vegetation Condition Index(VCI)from Land Surface Temperature(LST)and Enhanced Vegetation Index(EVI)derived from MODIS data.TCI and VCI were then integrated to determine the Vegetation Health Index(VHI).Revised Universal Soil Loss Equation(RUSLE)was utilized for estimating soil loss.The relationship between drought condition and vegetation was ascertained using the Pearson correlation.Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during2000-2019.The mean frequency of the drought occurrence was 7.95 months.The average soil erosion in the sub-basin was estimated to be 9.88 t ha^(-1)year^(-1).A positive relationship was observed between drought indices and soil erosion values(r value being 0.35).However,wide variations were observed in the distribution of spatial correlation.Among various factors,the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin.Thus,the study calls for policy measures to lessen the impact of drought and soil erosion.

Drought risk assessment in China:Evaluation framework and influencing factors

Global warming and rapid economic development have led to increased levels of disaster risk in China.Previous attempts at assessing drought risk were highly subjective in terms of assessment methods and selection of the assessment indicators and which resulted in appreciable uncertainty in the results of these risk assessments.Based on the assumption that areas with historically high drought losses are more likely to suffer future high drought losses,we develop a new drought risk assessment model that includes historical drought loss data.With this model,we map the regional differentiation of Chinese drought risk.Regions with high(extreme high)drought risk account for 4.3%of China’s area.Five significant high-risk areas have been identified:Northeast China,North China,the east part of Northwest China,the east part of Southwest China and a small part in the west of Northwest China.Areas with high and extreme high drought risk are dominant in the Heilongjiang Province,accounting for 32%of the total area,followed by the Ningxia Hui Autonomous Region,with 26%of total area.The contribution of each influencing factor has been quantified,which indicates that high-exposure and high-vulnerability account for the high-risk of drought.We recommend that measures like strengthening the protection of cultivated land and reducing dependence on the primary industry should be taken to mitigate to drought-induced losses.

Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC（Environmental Policy Integrated Climate） model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was ＆lt;0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.

Global vulnerability to agricultural drought and its spatial characteristics

As an important part of agricultural drought risk, agricultural drought vulnerability helps effectively prevent and alleviate drought impacts by quantifying the vulnerability as well as identifying its spatial distribution characteristics. In this study, global agricultural cultivation regions were chosen as the study area; six main crops(wheat, maize, rice, barley, soybean,sorghum) were selected as the hazard-affected body of agricultural drought. Then, global vulnerability to agricultural drought was assessed at a 0.5° resolution and finally, its distribution characteristics were revealed. The results indicated that the area percentages of different grades of global vulnerability to agricultural drought from low to very high were 38.96%, 28.41%,25.37%, and 7.26%, respectively. This means that the total area percentage of high and very high vulnerability zones exceeded30% of the study area. Although high and very high vulnerability zones were mainly distributed in arid and semi-arid regions,approximately 40% of those above were distributed in humid and semi-humid regions. In addition, only about 15% of the population in this study was located in the high vulnerability regions. Among the vulnerability factors, water deficit during the growing season and the irrigation area ratio are the key factors affecting regional vulnerability. Therefore, the vulnerability could be reduced by adjusting crop planting dates and structures as well as by improving irrigation level and capacity.

Datasets of meteorological drought events and risks for the developing countries in Eurasia

For the area of Eurasia concentrated with developing countries(referred to here by the abbreviation DPEA),mainly located in Asia and Eastern Europe,this work presents datasets of gridded meteorological drought events and country-based drought risk by combining multiple drought indices and socio-economic data.A basic gridded dataset of the drought events during 1950-2015 is extracted from three drought indices:the self-calibrating Palmer Drought Severity Index,the Standardized Precipitation Index,and the Standardized Precipitation Evapotranspiration Index.The three drought indices generally show consistent characteristics of drought events in DPEA.A second-level dataset(a drought risk dataset)is then produced as the product of drought hazard,exposure and vulnerability during 2000-2015.For drought exposure,the indicators of population and livestock density,agricultural land and water stress are chosen,while drought vulnerability composites multiple social,economic and infrastructural factors.Drought hazard tends to concentrate at the southern rim of Eurasia.Relatively large differences in drought exposure exist between different countries,but for drought vulnerability the differences are small.After considering the socio-economic components in risk assessment,most countries in West,South-Central and South Asia have the highest drought risk in DPEA.The datasets of drought events and risks are available at http://www.dx.doi.org/10.11922/sciencedb.898.

蒙古高原植被净初级生产力干旱风险

The increasing frequency of recent droughts has an adverse effect on the ecosystem of the Mongolian Plateau.The growth condition of NPP is considered an indicator of the ecological function.Therefore,identifying the relationship between NPP and drought can assist in the prevention of drought-associated disasters and the conservation of the ecological environment of the Mongolian Plateau.This study used the Carnegie-Ames-Stanford Approach(CASA)model to simulate the NPP capacity of the Mongolian Plateau between 1982 and 2015,as well as drought indicators(drought probability,vulnerability,and risk)to explore the drought risk of NPP.The findings pointed to an overall increase in NPP with regional variances;however,the NPP rate in Inner Mongolia was considerably higher than that in Mongolia.The standardized precipitation evapotranspiration index(SPEI)showed an overall downward trend,with Inner Mongolia experiencing a substantially lower rate of decline than Mongolia.The areas most likely to experience drought were primarily in the center and north while the areas with the highest drought vulnerability were primarily in the northeast,center,and southeast.Mongolia showed a higher probability of drought compared to Inner Mongolia.Drought-prone regions of the Mongolian Plateau increased during the 21st century while drought-vulnerable areas increased and shifted from north to south.Alpine grasslands and coniferous forests were least vulnerable to drought,while other vegetation types experienced temporal variation.In the 21st century,the primary determinants of drought risk shifted from precipitation and the normalized difference vegetation index(NDVI)to temperature and relative humidity.