scholarly journals Model Comparisons Between Canonical Vine Copulas and Meta-Gaussian for Agricultural Drought Forecasting over China

2021 ◽  
Author(s):  
Haijiang Wu ◽  
Xiaoling Su ◽  
Vijay P. Singh ◽  
Te Zhang ◽  
Jixia Qi
Keyword(s):  
Performance Metrics ◽  
Reference Model ◽  
Predictive Ability ◽  
Meteorological Drought ◽  
Three Dimensions ◽  
Agricultural Drought ◽  
Drought Forecasting ◽  
Drought Mitigation ◽  
Drought Early Warning ◽  
Vine Copulas

Abstract. Agricultural drought is caused by reduced soil moisture and precipitation and affects the growth of crops and vegetation, and in turn agricultural production and food security. For developing measures for drought mitigation, reliable agricultural drought forecasting is essential. In this study, we developed an agricultural drought forecasting model based on canonical vine copulas under three-dimensions (3C-vine model), in which the antecedent meteorological drought and agricultural drought persistence were utilized as predictors. Besides, the meta-Gaussian (MG) model was selected as a reference model to evaluate the forecast skill. The agricultural drought in August of 2018 was selected as a case study, and the spatial patterns of 1–3-month lead forecasts of agricultural drought utilizing the 3C-vine model resembled the corresponding observations, indicating the predictive ability of the model. The performance metrics (NSE, R2, and RMSE) showed that the 3C-vine model outperformed the MG model for August under diverse lead times. Also, the 3C-vine model exhibited excellent forecast skills in capturing the extreme agricultural drought over different selected typical regions. This study may help with drought early warning, drought mitigation, and water resources scheduling.

scholarly journals Potential of Pan-European Seasonal Hydrometeorological Drought Forecasts Obtained from a Multihazard Early Warning System

2020 ◽  
Vol 101 (4) ◽  
pp. E368-E393 ◽  
Author(s):  
Samuel Jonson Sutanto ◽  
Henny A. J. Van Lanen ◽  
Fredrik Wetterhall ◽  
Xavier Llort
Keyword(s):  
Soil Moisture ◽  
Early Warning ◽  
Water Cycle ◽  
Warning System ◽  
Meteorological Drought ◽  
Early Warning Systems ◽  
Drought Indices ◽  
Drought Forecasting ◽  
Wide Range ◽  
Drought Early Warning

Abstract Drought early warning systems (DEWS) have been developed in several countries in response to high socioeconomic losses caused by droughts. In Europe, the European Drought Observatory (EDO) monitors the ongoing drought and forecasts soil moisture anomalies up to 7 days ahead and meteorological drought up to 3 months ahead. However, end users managing water resources often require hydrological drought warning several months in advance. To answer this challenge, a seasonal pan-European DEWS has been developed and has been running in a preoperational mode since mid-2018 under the EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) project. The ANYWHERE DEWS (AD-EWS) is different than other operational DEWS in the sense that the AD-EWS provides a wide range of seasonal hydrometeorological drought forecasting products in addition to meteorological drought, that is, a broad suite of drought indices that covers all water cycle components (drought in precipitation, soil moisture, runoff, discharge, and groundwater). The ability of the AD-EWS to provide seasonal drought predictions in high spatial resolution (5 km × 5 km) and its diverse products mark the AD-EWS as a preoperational drought forecasting system that can serve a broad range of different users’ needs in Europe. This paper introduces the AD-EWS and shows some examples of different drought forecasting products, the drought forecast score, and some examples of a user-driven assessment of forecast trust levels.

Drought Analysis Based on the Information Diffusion and Fractal Technology: A Case Study of Winter Wheat in China

2020 ◽  
Vol 36 (6) ◽  
pp. 869-877
Author(s):  
Jian-bin Yao ◽  
Jian-hua Liu ◽  
Hui-jie Ma ◽  
Hong-wei Pan
Keyword(s):  
Winter Wheat ◽  
Information Diffusion ◽  
Fractal Theory ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Data Series ◽  
List Type ◽  
Drought Forecasting ◽  
Study Region ◽  
Drought Prediction

HighlightsThere is no good correlation between meteorological drought and crop drought.The data series of meteorological drought and crop drought at the same time have fractal characteristics.Fractal theory can be used to predict the next drought year.Abstract.Drought is one of the natural disasters of global concern. Drought forecasting is an important tool for drought management. Uncertainty is a major challenge in drought forecasting. In order to provide a short-term effective drought prediction, this study provides a new point into drought prediction from the timing-prediction perspective. The key part of this essay lies in its fractal theoretical framework guided by the self-similarity principle, which fully considers the complexity, disorder and regularity of agricultural drought. At the same time, information diffusion theory is used to polish the raw data, especially some data about winter wheat in Zhengzhou in China. The results as follows: 1) the change trend of drought in the study region is consistent with the past; 2) the time of meteorological drought, summer maize does not necessarily lead to drought, but most timing prediction work is consistent, they have shared the similar cyclical changing-laws; and 3) the occurring time of the next drought calculated is consistent with the actual observation results. Therefore, the method established in this study is effective, and it can provide some reference for the prediction of agricultural drought outbreak time. Keywords: Crop drought, Fractal theory, Information diffusion, Meteorological drought, Winter wheat.

Satellite Data Based Soil Water Index as a Tool to Monitor Droughts and Agricultural Crisis -An Example of Yavatmal District, Maharashtra, India

2020 ◽  
Vol 4 (1-2) ◽  
pp. 12-18
Author(s):  
Vijendra Boken
Keyword(s):  
Soil Water ◽  
Satellite Data ◽  
Suicide Rate ◽  
Crop Yields ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Coefficient Of Correlation ◽  
Water Index ◽  
Farmer Suicides ◽  
June July

Yavatmal is one of the drought prone districts in Maharashtra state of India and has witnessed an agricultural crisis to the extent that hundreds of its farmers have committed suicides in recent years. Satellite data based products have previously been used globally for monitoring and predicting of drought, but not for monitoring their extreme impacts that may include farmer-suicides. In this study, the performance of the Soil Water Index (SWI) derived from the surface soil moisture estimated by the European Space Agency’s Advanced Scatterometer (ASCAT) is assessed. Using the 2007-2015 data, it was found that the relationship of the SWI anomaly was bit stronger (coefficient. of correlation = 0.59) with the meteorological drought or precipitation than with the agricultural drought or crop yields of major crops (coefficient. of correlation = 0.50).  The farmer-suicide rate was better correlated with the SWI anomaly averaged annually than with the SWI anomaly averaged only for the monsoon months (June, July, August, and September). The correlation between the SWI averaged annually increased to 0.89 when the averages were taken for three years, with the highest correlation occurring between the suicide rate and the SWI anomaly averaged for three years. However, a positive relationship between SWI and the suicide rate indicated that drought was not a major factor responsible for suicide occurrence and other possible factors responsible for suicide occurrence need to examine in detail.

scholarly journals Evaluation of dimensional accuracy of dental bridges manufactured with conventional casting technique and CAD/CAM system with Ceramill Sintron blocks using CMM

2018 ◽  
Vol 12 (4) ◽  
pp. 264-271 ◽  
Author(s):  
Alireza Izadi ◽  
Fariborz Vafaee ◽  
Arash Shishehian ◽  
Ghodratollah Roshanaei ◽  
Behzad Fathi Afkari
Keyword(s):  
Reference Model ◽  
Coordinate Measuring Machine ◽  
Dimensional Accuracy ◽  
Three Dimensions ◽  
Casting Technique ◽  
Dimensional Changes ◽  
Conventional Casting ◽  
Cad Cam ◽  
Milling Method ◽  
Measuring Machine

Background. Recently, non-presintered chromium-cobalt (Cr-Co) blocks with the commercial name of Ceramill Sintron were introduced to the market. However, comprehensive studies on the dimensional accuracy and fit of multi-unit frameworks made of these blocks using the coordinate measuring machine (CMM) are lacking. This study aimed to assess and compare the dimensional changes and fit of conventional casting and milled frameworks using Ceramill Sintron. Methods. A metal model was designed and scanned and 5-unit frameworks were fabricated using two techniques: (I) the conventional casting method (n=20): the wax model was designed, milled in the CAD/CAM machine, flasked and invested; (II) the milling method using Ceramill Sintron blocks (n=20): the wax patterns of group 1 were used; Ceramill Sintron blocks were milled and sintered. Measurements were made on the original reference model and the fabricated frameworks using the CMM in all the three spatial dimensions, and dimensional changes were recorded in a checklist. Data were analyzed with descriptive statistics, and the two groups were compared using one-way ANOVA and Tukey test (α=0.05). Results. The fabricated frameworks in both groups showed significant dimensional changes in all the three dimensions. Comparison of dimensional changes between the two groups revealed no significant differences (P>0.05) except for transverse changes (arch) that were significantly greater in Ceramill Sintron frameworks (P<0.05). Conclusion. The two manufacturing processes were the same regarding dimensional changes and the magnitude of marginal gaps and both processes resulted in significant dimensional changes in frameworks. Ceramill Sintron frameworks showed significantly greater transverse changes than the conventional frameworks.

scholarly journals Different Drought Legacies of Rain-Fed and Irrigated Croplands in a Typical Russian Agricultural Region

2020 ◽  
Vol 12 (11) ◽  
pp. 1700
Author(s):  
Yuanhuizi He ◽  
Fang Chen ◽  
Huicong Jia ◽  
Lei Wang ◽  
Valery G. Bondur
Keyword(s):  
Surface Temperature ◽  
Drought Index ◽  
Growth Period ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Growth Stages ◽  
Drought Conditions ◽  
Irrigated Lands ◽  
Meteorological Droughts

Droughts are one of the primary natural disasters that affect agricultural economies, as well as the fire hazards of territories. Monitoring and researching droughts is of great importance for agricultural disaster prevention and reduction. The research significance of investigating the hysteresis of agricultural to meteorological droughts is to provide an important reference for agricultural drought monitoring and early warnings. Remote sensing drought monitoring indices can be employed for rapid and accurate drought monitoring at regional scales. In this paper, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and the surface temperature product are used as the data sources. Calculating the temperature vegetation drought index (TVDI) and constructing a comprehensive drought disaster index (CDDI) based on the crop growth period allowed drought conditions and spatiotemporal evolution patterns in the Volgograd region in 2010 and 2012 to be effectively monitored. The causes of the drought were then analyzed based on the sensitivity of a drought to meteorological factors in rain-fed and irrigated lands. Finally, the lag time of agricultural to meteorological droughts and the hysteresis in different growth periods were analyzed using statistical analyses. The research shows that (1) the main drought patterns in 2010 were spring droughts from April to May and summer droughts from June to August, and the primary drought patterns in 2012 were spring droughts from April to June, with an affected area that reached 3.33% during the growth period; (2) local drought conditions are dominated by the average surface temperature factor. Rain-fed lands are sensitive to the temperature and are therefore prone to summer droughts. Irrigated lands are more sensitive to water shortages in the spring and less sensitive to extremely high temperature conditions; (3) there is a certain lag between meteorological and agricultural droughts during the different growth stages. The strongest lag relationship was found in the planting stage and the weakest one was found in the dormancy stage. Therefore, the meteorological drought index in the growth period has a better predictive ability for agricultural droughts during the appropriately selected growth stages.

Agricultural Drought Prediction Based on Conditional Distributions of Vine Copulas

2021 ◽  
Author(s):  
Haijiang Wu ◽  
Xiaoling Su ◽  
Vijay P. Singh ◽  
Kai Feng ◽  
Jiping Niu
Keyword(s):  
Agricultural Drought ◽  
Conditional Distributions ◽  
Drought Prediction ◽  
Vine Copulas

scholarly journals Drought Propagation Patterns under Naturalized Condition Using Daily Hydrometeorological Data

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jianzhu Li ◽  
Yuangang Guo ◽  
Yixuan Wang ◽  
Shanlong Lu ◽  
Xu Chen
Keyword(s):  
Early Warning ◽  
Assessment Tool ◽  
Swat Model ◽  
Meteorological Drought ◽  
Threshold Level ◽  
Hydrological Drought ◽  
Propagation Pattern ◽  
Drought Early Warning ◽  
Hydrological Droughts

Drought propagation pattern forms a basis for establishing drought monitoring and early warning. Due to its regional disparity, it is necessary and significant to investigate the pattern of drought propagation in a specific region. With the objective of improving understanding of drought propagation pattern in the Luanhe River basin, we first simulated soil moisture and streamflow in naturalized situation on daily time scale by using the Soil and Water Assessment Tool (SWAT) model. The threshold level method was utilized in identifying drought events and drought characteristics. Compared with meteorological drought, the number of drought events was less and duration was longer for agricultural and hydrological droughts. The results showed that there were 3 types of drought propagation pattern: from meteorological drought to agricultural/hydrological drought (M-A/H), agricultural/hydrological drought without meteorological drought (NM-A/H), and meteorological drought only (M). To explain the drought propagation pattern, possible driven factors were determined, and the relations between agricultural/hydrological drought and the driven factors were built using multiple regression models with the coefficients of determination of 0.4 and 0.656, respectively. These results could provide valuable information for drought early warning and forecast.

Linkage of agricultural drought with meteorological drought in different climates of Iran

2019 ◽  
Vol 138 (1-2) ◽  
pp. 1025-1033 ◽  
Author(s):  
Maliheh Behrang Manesh ◽  
Hassan Khosravi ◽  
Esmail Heydari Alamdarloo ◽  
Mahnaz Saadi Alekasir ◽  
Ahmad Gholami ◽  
...  
Keyword(s):  
Meteorological Drought ◽  
Agricultural Drought ◽  
Different Climates

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

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