scholarly journals Establishment and characteristics analysis of a crop–drought vulnerability curve: a case study of European winter wheat

2021 ◽  
Vol 21 (4) ◽  
pp. 1209-1228
Author(s):  
Yanshen Wu ◽  
Hao Guo ◽  
Anyu Zhang ◽  
Jing'ai Wang
Keyword(s):  
Winter Wheat ◽  
Drought Index ◽  
Loss Rate ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Vulnerability ◽  
Initial Development ◽  
Vulnerability Curve ◽  
European Winter Wheat ◽  
The Impact

Abstract. As an essential component of drought risk, crop–drought vulnerability refers to the degree of the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying drought vulnerability and then identifying its spatial characteristics will help understand vulnerability and develop risk-reduction strategies. We select the European winter wheat growing area as the study area and 0.5∘ × 0.5∘ grids as the basic assessment units. Winter wheat drought vulnerability curves are established based on the erosion–productivity impact calculator model simulation. Their loss change and loss extent characteristics are quantitatively analysed by the key points and cumulative loss rate, respectively, and are then synthetically identified via K-means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index reaches 0.66. (2) In contrast to the Pod Plain, the stage transitions of the vulnerability curve lags behind in the southern mountain area, indicating a stronger tolerance to drought. (3) According to the loss characteristics during the initial, development, and attenuation stages, the vulnerability curves can be divided into five clusters, namely low-low-low, low-low-medium, medium-medium-medium, high-high-high, and low-medium-high loss types, corresponding to the spatial distribution from low latitude to high latitude and from mountain to plain. The paper provides ideas for the study of the impact of environment on vulnerability and for the possible application of vulnerability curve in the context of climate change.

scholarly journals Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

2019 ◽  
Author(s):  
Yanshen Wu ◽  
Hao Guo ◽  
Anyu Zhang ◽  
Jing'ai Wang
Keyword(s):  
Spatial Distribution ◽  
Winter Wheat ◽  
Drought Index ◽  
Loss Rate ◽  
Drought Risk ◽  
Drought Vulnerability ◽  
Initial Development ◽  
Vulnerability Curve ◽  
High Loss ◽  
European Winter Wheat

Abstract. As an essential component of drought risk, crop-drought vulnerability refers to the degree of the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying the drought vulnerability and then identifying its spatial distribution pattern will contribute to understanding vulnerability and the development of risk-reduction strategies. We select the European winter wheat growing area as the study area and a 0.5° × 0.5° grid as the basic assessment unit. Winter wheat drought vulnerability curves are established based on the Erosion-Productivity Impact Calculator model simulation. Their loss transmutation and loss extent characteristics are quantitatively analyzed by the key points and cumulative loss rate, respectively, and are then synthetically identified VIA K-means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index reaches 0.66. (2) The stage transitions of the vulnerability curve lag in the southern mountain area, indicating a stronger tolerance to drought in the system, in contrast to the Pod Plain. (3) According to the loss characteristics during the initial, development and attenuation stages, the vulnerability curves can be divided into five clusters, namely, Low-Low-Low, Low-Low-Medium, Medium-Medium-Medium, High-High-High and Low-Medium-High loss types, corresponding to the spatial distribution from low latitude to high latitude and from mountain to plain. It is recommended to improve the integrated mitigation capability in the Medium-Medium-Medium-loss and High-High-High -loss areas and to develop the ability to mitigate droughts in the 0.3–0.6 intensity range, as non-engineering measures for the droughts greater than 0.6 intensity in low-medium-high areas are needed.

scholarly journals ANALISIS RISIKO KEKERINGAN DI KABUPATEN BANTUL PROVINSI D.I. YOGYAKARTA

2021 ◽  
Vol 18 (2) ◽  
pp. 143
Author(s):  
Annisa Mu'awanah Sukmawati ◽  
Puji Utomo
Keyword(s):  
Risk Analysis ◽  
Rural Areas ◽  
Hazard Analysis ◽  
Drought Risk ◽  
Drought Event ◽  
Quantitative Research Methods ◽  
Risk Areas ◽  
High Level ◽  
The Impact ◽  
Very High

Bantul Regency is a district in Yogyakarta Province which has geographic, geological, hydrological, and demographic characteristics that are likely to cause drought. Drought event in Bantul Regency may have significant impacts on various aspects in line with the characteristics of drought impacts which are complex and cross-sectoral. This study addresses to analyze the level of risk of drought with observation units in 75 villages in the Bantul Regency. The risk analysis was carried out by comparing the time period of the 10 years, i.e. 2008 and 2018 to observe the shift of risk areas of drought in Bantul Regency. The research was conducted using quantitative research methods with quantitative descriptive and mapping analysis. The analysis steps are drought hazard analysis, vulnerability analysis, and drought risk analysis. The analysis shows that during the last 10 years, Kabupaten Bantul has been experiencing an increasing number of villages classified as high risk of drought, both in urban and rural areas. In 2008 there were 15 villages (20%) and increased to 21 villages (28%) in 2018 that were classified as very very high level. Meanwhile, in 2008 there were 30 villages (40%) in 2008 and increased to 32 villages (42.7%) in 2018 that were classified as very high level. It caused by the increasing probability of drought as well as vulnerability. The analysis results can be used as input for stakeholders to take mitigation and anticipation actions to reduce the impact of drought based on the spatial characteristics of the risk areas.

scholarly journals A new agricultural drought index considering the irrigation water demand and water supply availability

2020 ◽  
Vol 104 (3) ◽  
pp. 2409-2429
Author(s):  
Zikang Xing ◽  
Miaomiao Ma ◽  
Yongqiang Wei ◽  
Xuejun Zhang ◽  
Zhongbo Yu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Irrigation Water ◽  
Water Demand ◽  
Drought Index ◽  
Agricultural Drought ◽  
Drought Event ◽  
Moisture Condition ◽  
Irrigation Water Demand ◽  
Moisture Variation ◽  
The Impact

Abstract Agricultural drought has a tremendous impact on crop yields and economic development under the context of global climate change. As an essential component of water balance in irrigated areas, artificial irrigation, which is not widely incorporated into agricultural drought indices in previous studies. Therefore, an irrigation water deficit index (IWDI) based on the estimation of irrigation water demand and supply is proposed. The performance of the new index was compared with the Soil Moisture Anomaly Percentage Index (SMAPI) over the upstream of the Zi River basin (UZRB). The results indicated the IWDI is highly correlated with precipitation, runoff, and potential evapotranspiration, combined with a more comprehensive moisture condition than the previous agricultural drought index. Due to the consideration of crop growth process and farmland spatial distribution, the proposed index showed a significant advantage in stressing drought conditions of agricultural concentration area and eliminating the impact of invalid soil moisture drought of non-growing seasons. Furthermore, the drought condition identified by the new index presented a good agreement with the historical drought event that occurred in 2013.7–8, which accurately reproduced the soil moisture variation and vegetation growth dynamics.

scholarly journals Meteorological Drought and its Relationship with Southern Oscillation Index (SOI)

2020 ◽  
Vol 6 (10) ◽  
pp. 1864-1875 ◽  
Author(s):  
Donny Harisuseno
Keyword(s):  
Southern Oscillation Index ◽  
Drought Index ◽  
Southern Oscillation ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Risk ◽  
Drought Event ◽  
Association Analyses ◽  
The Standardized Precipitation Index

Drought monitoring, including its severity, spatial, and duration is essential to enhance resilience towards drought, particularly for overcoming drought risk management and mitigation plan. The present study has an objective to examine the suitability of the Standardized Precipitation Index (SPI) and Percent of Normal Index (PN) on assessing drought event by analyzing their relationship with the Southern Oscillation Index (SOI). The monthly rainfall data over twenty years of the observation period were used as a basis for data input in the drought index calculation. The statistical association analyses, included the Pearson Correlation (r), Kendal tau (τ), and Spearman rho (rs) used to assess the relationship between the monthly drought indexes and SOI. The present study confirmed that the SPI showed a more consistent and regular pattern relationship with SOI basis which was indicated by a moderately high determination coefficient (R2) of 0.74 and the magnitude of r, τ, and rs that were of 0.861, 0.736, and 0.896, respectively. Accordingly, the SPI showed better compatibility than the PN for estimating drought characteristics. The study also revealed that the SOI data could be used as a variable to determine the reliability of drought index results.

scholarly journals Analysis of Agricultural Drought Risk Based on Information Distribution and Diffusion Methods in the Main Grain Production Areas of China

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 764 ◽  
Author(s):  
Kaijie Niu ◽  
Qingfang Hu ◽  
Lu Zhao ◽  
Shouzheng Jiang ◽  
Haiying Yu ◽  
...  
Keyword(s):  
Agricultural Drought ◽  
Diffusion Method ◽  
Drought Risk ◽  
Grain Production ◽  
Information Distribution ◽  
Drought Vulnerability ◽  
Vulnerability Curve ◽  
Agricultural Drought Risk ◽  
Production Areas ◽  
Drought Damage

Accurate assessment of agricultural drought risk is of strategic significance to ensure future grain production security in the main grain production areas of China. Agricultural drought risk assessment is based on drought vulnerability characteristics. In this study, firstly the drought thresholds were redefined by correlation analysis of drought strength based on the Standardized Precipitation Evapotranspiration Index (SPEI) and drought damage rates, then the information distribution and the two-dimensional normal information diffusion method were employed to establish the vulnerability curve between drought strength and drought damage rates. Finally, provincial drought risks and the conditional probabilities at different drought damage stages were obtained. The results show that the drought vulnerability curve was nonlinear. With the increase of drought strength, drought damage rates increased rapidly at the beginning, and after a small fluctuation locally, they no longer increased significantly and tended to be relative stable. The occurrence probabilities of agricultural drought risk presented great spatial differences, with the characteristics of high in the northern, moderate in the central and southwestern part, and lower in the southeastern provinces in the main grain production areas of China. The analysis of conditional probability showed that Hubei, Henan, and Jiangxi were the provinces most prone to drought-affected risk under the drought-induced condition; while Liaoning, Hunan, and Inner Mongolia were the ones most prone to lost harvest risk under the drought-induced or the drought-affected condition. The results could be used to provide guidance for drought risk management and to formulate appropriate plans by the relevant departments.

scholarly journals A 3D Copula Method for the Impact and Risk Assessment of Drought Disaster and an Example Application

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Hou ◽  
Pengcheng Yan ◽  
Guolin Feng ◽  
Dongdong Zuo
Keyword(s):  
Risk Assessment ◽  
Meteorological Drought ◽  
Theory And Practice ◽  
Agricultural Drought ◽  
Risk Assessments ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Duration ◽  
Drought Intensity ◽  
The Impact

Droughts have more impact on crops than any other natural disaster. Therefore, drought risk assessments, especially quantitative drought risk assessments, are significant in order to understand and reduce the negative impacts associated with droughts, and a quantitative risk assessment includes estimating the probability and consequences of hazards. In order to achieve this goal, we built a model based on the three-dimensional (3D) Copula function for the assessment of the proportion of affected farmland areas (PAFA) based on the idea of internally combining the drought duration, drought intensity, and drought impact. This model achieves the “internal combination” of drought characteristics and drought impacts rather than an “external combination.” The results of this model are not only able to provide the impacts at different levels that a drought event (drought duration and drought intensity) may cause, but are also able to show the occurrence probability of impact at each particular level. We took Huize County and Mengzi County in Yunnan Province as application examples based on the meteorological drought index (SPI), and the results showed that the PAFAs obtained by the method proposed in this paper were basically consistent with the actual PAFAs in the two counties. Moreover, due to the meteorological drought always occurring before an agricultural drought, we can get SPI predictions for the next month or months and can further obtain more abundant information on a drought warning and its impact. Therefore, the method proposed in this paper has values both on theory and practice.

The impact of winter wheat cultivation practices on the quality of soil and grain

2006 ◽  
Vol 34 (1) ◽  
pp. 649-651
Author(s):  
D. Šileikiene ◽  
V. Rutkoviene ◽  
J. Pekarskas
Keyword(s):  
Winter Wheat ◽  
Wheat Cultivation ◽  
Cultivation Practices ◽  
The Impact

scholarly journals Seasonal streamflow forecasting by conditioning climatology with precipitation indices

2017 ◽  
Vol 21 (3) ◽  
pp. 1573-1591 ◽  
Author(s):  
Louise Crochemore ◽  
Maria-Helena Ramos ◽  
Florian Pappenberger ◽  
Charles Perrin
Keyword(s):  
Long Range ◽  
Precipitation Forecast ◽  
Low Flow ◽  
Drought Risk ◽  
Streamflow Forecasting ◽  
Streamflow Forecasts ◽  
Precipitation Indices ◽  
Seasonal Streamflow ◽  
Prediction Approach ◽  
The Impact

Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

scholarly journals Modeling the Impact of Atmospheric Warming on Staple Crop Growth in China in the 1960s and 2000s

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 36
Author(s):  
Qing Zhang ◽  
Wen Zhang ◽  
Yongqiang Yu ◽  
Tingting Li ◽  
Lijun Yu
Keyword(s):  
Winter Wheat ◽  
Climate Warming ◽  
Northeast China ◽  
Cropping Systems ◽  
Crop Growth ◽  
East China ◽  
Frequency Distributions ◽  
Before And After ◽  
The 1960S ◽  
The Impact

Responses of crop growth to climate warming are fundamental to future food security. The response of crops to climate change may be subtly different at their growing stages. Close insights into the differentiated stage-dependent responses of crops are significantly important in making adaptive adjustments of crops’ phenological optimization and cultivar improvement in diverse cropping systems. Using the Agro-C model, we studied the influence of past climate warming on crops in typical cropping systems in China. The results showed that while the temperature had increased distinctly from the 1960s to 2000s, the temperature frequency distributions in the growth season of crops moved to the high-temperature direction. The low temperature days during the crop growth periods that suppress crop growth decreased in the winter wheat area in North and East China, rice and maize areas in Northeast China, and the optimum temperature days increased significantly. As a result, the above ground biomass (AGB) of rice and maize in Northeast China and winter wheat in North and East China increased distinctly, while that of rice in South China had no significant change. A comparison of the key growth periods before and after heading (silking) showed that the warming before heading (silking) made a great contribution to the increase in the AGB, especially for winter wheat.

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