An index to quantifying the impacts of agricultural drought and its application in China

2020 ◽  
Author(s):  
huaiwei sun ◽  
Jianing Chen
Keyword(s):  
Natural Disasters ◽  
Crop Yield ◽  
Drought Index ◽  
Crop Yields ◽  
Meta Analysis ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Yield Reduction ◽  
Climatic Data ◽  
Simple Index

<p>As one of the major weather-driven natural disasters, droughts exhibit as the most frequent and widespread natural disasters in China. It is reported that the agriculture losses show continuously grown by following the increasingly severe droughts for the whole country. In order to investigate the impacts of drought on agricultural, we rechecked the functional relationship between the crop yield and climatic variables. Based on the meta-analysis from previous literature, we found a more stable statistical relationship between the yield and the precipitation and evapotranspiration. These results introduce a new drought index, indicated as Crop Water-Related Index for Drought (CWRID), which can be used as a reference index to approximate the drought impact on the loss of yield. Based on the climatic data in China during 1982-2015, several other drought indices (SPI, SPEI, CI, and SEDI) were compared with CWRID to identify the most appropriate agricultural drought index. The data of historical drought damaged area and drought damaged crop yield reduction were used to validate the performances of different indices. The CWRID reasonably predicted the drought damaged area as well as the drought damaged yield reduction during the past 30 years in China. As a contrast, the SEDI is proved to be no suit for quantifying drought. Also, the calculated values are stored in the dataset and can be shared with researchers by request. As a simple index, results indicated that CWRID can be used to quantify the impacts of drought on agricultural as it can reflect the variation of crop yields.</p>

scholarly journals The impact of drought on the productivity of two rainfed crops in Spain

2019 ◽  
Vol 19 (6) ◽  
pp. 1215-1234 ◽  
Author(s):  
Marina Peña-Gallardo ◽  
Sergio Martín Vicente-Serrano ◽  
Fernando Domínguez-Castro ◽  
Santiago Beguería
Keyword(s):  
Crop Yield ◽  
Drought Index ◽  
Crop Yields ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Yield Response ◽  
Drought Indices ◽  
Drought Severity ◽  
Yield Data ◽  
The Impact

Abstract. Drought events are of great importance in most Mediterranean climate regions because of the diverse and costly impacts they have in various economic sectors and on the environment. The effects of this natural hazard on rainfed crops are particularly evident. In this study the impacts of drought on two representative rainfed crops in Spain (wheat and barley) were assessed. As the agriculture sector is vulnerable to climate, it is especially important to identify the most appropriate tools for monitoring the impact of the weather on crops, and particularly the impact of drought. Drought indices are the most effective tool for that purpose. Various drought indices have been used to assess the influence of drought on crop yields in Spain, including the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI), the Palmer drought indices (Palmer Drought Severity Index, PDSI; Palmer Z Index, Z Index; Palmer Hydrological Drought Index, PHDI; Palmer Modified Drought Index, PMDI), and the Standardized Palmer Drought Index (SPDI). Two sets of crop yield data at different spatial scales and temporal periods were used in the analysis. The results showed that drought indices calculated at different timescales (SPI, SPEI) most closely correlated with crop yield. The results also suggested that different patterns of yield response to drought occurred depending on the region, period of the year, and the drought timescale. The differing responses across the country were related to season and the magnitude of various climate variables.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

2021 ◽  
Author(s):  
Dimmie Hendriks ◽  
Pieter Hazenberg ◽  
Jonas Gotte ◽  
Patricia Trambauer ◽  
Arjen Haag ◽  
...  
Keyword(s):  
Drought Index ◽  
Agricultural Drought ◽  
Data Sources ◽  
Drought Indices ◽  
Next Generation ◽  
Hazard Indices ◽  
Local Data ◽  
Drought Impacts ◽  
Drought Hazard ◽  
Impact Data

<p>An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.</p><p>Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.</p><p>The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.</p><p>We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.</p>

Using Estimates of Weed Pressure to Establish Crop Yield Loss Equations

1994 ◽  
Vol 8 (1) ◽  
pp. 114-118 ◽  
Author(s):  
R. Gordon Harvey ◽  
Clark R. Wagner
Keyword(s):  
Linear Regression ◽  
Crop Yield ◽  
Yield Loss ◽  
Sweet Corn ◽  
Crop Yields ◽  
Yield Reduction ◽  
Weed Species ◽  
Field Corn ◽  
Efficacy Trials ◽  
Total Crop

Herbicide efficacy trials in field corn, sweet corn, and soybean were conducted at three locations in Wisconsin over a 6-yr period. Percent weed pressure (WP) was determined by visually estimating the contribution of all weed species present to the total crop and weed volume in each plot. Crop yields in each plot were measured. Percent crop yield reduction (YLDRED) was calculated by comparing mean yields of individual treatments with those of the highest yielding treatment in each trial. Linear regression analyses of YLDRED and WP data from 1640 field corn and 138 sweet corn treatments were significant. Nonlinear regression analysis of YLDRED and WP data from all 1374 soybean treatments was significant; however, a linear regression of those 1154 soybean treatments with WP ratings of 30 or less produced a more easily interpreted regression equation.

Usage of soil moisture models in agronomic research

1996 ◽  
Vol 76 (3) ◽  
pp. 285-295 ◽  
Author(s):  
O. O. Akinremi ◽  
S. M. McGinn
Keyword(s):  
Soil Moisture ◽  
Grain Yield ◽  
Water Use ◽  
Crop Yield ◽  
Drought Index ◽  
Regional Scale ◽  
Irrigation Scheduling ◽  
Water Model ◽  
Yield Reduction ◽  
Efficiency Coefficient

Soil moisture controls many important processes in the soil-plant system and the extent of these processes cannot be quantified without knowing moisture status of the root zone. Of agronomic importance these include, seedling emergence, evapotranspiration, mineralization of the soil organic fraction, surface runoff, leaching and crop yield. Many models have been developed to simulate these processes based on algorithms of varying degrees of complexity that describe the dynamic nature of soil moisture at different temporal and spatial scales. This paper reviews the direct applications of soil moisture models in agronomy from the field to regional scale and for daily to seasonal time steps. At every level of detail, the lack of model validation beyond the region where it was developed is the main limitation to the application of soil moisture models in agronomy. At the field scale, models have been used for irrigation scheduling to ensure efficient utilization of irrigation water and maximize crop yields. Models are also used to estimate crop yield based on the growing season water use. The water use of crops is converted to biomass accumulation and grain yield using a water-use efficiency coefficient and a harvest index. Other empirical equations are available that relate cumulative crop water use directly to grain yield. On a regional scale, in a study of drought climatology on the Canadian prairie, we coupled a soil water model, the Versatile Soil Moisture Budget, with the Palmer Drought Index model to improve the modelling of soil moisture. This was found to improve the relationship of the Palmer drought index to wheat yield reduction resulting from drought. Key words: Soil moisture, modelling, water-use, evapotranspiration, aridity index, Canadian prairies

A Study on the Estimation of the Occurrence Frequency of Mega-drought by the Characteristics of Drought Damage

2020 ◽  
Author(s):  
Song Youngseok ◽  
Kim Jinbok ◽  
Park Jongun ◽  
Park Moojong
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Development Program ◽  
Agricultural Drought ◽  
Drought Indices ◽  
The Past ◽  
Short Period ◽  
Recent Climate ◽  
The World ◽  
Drought Damage

<p>Unlike natural disasters such as typhoons, torrential rains and floods, drought is a disaster caused by long-term effects as well as short-term effects. The effect of drought is caused by damage from a short period of weeks to a long period of years, which causes extensive and enormous damage to agriculture, life, society and economy. In addition, the recent climate change has affected the frequency and scale of rainfall in the global temperature, so it is necessary to prepare measures against it.</p><p>The past studies on drought have been conducted using drought indexes such as agricultural, meteorological, and hydrological methods to evaluate drought. The representative drought indexes for each drought are Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Agricultural drought is Crop Moisture Index (CMI), Crop Specific Drought Index (CSDI), Hydrological drought is Surface Drought Water Supply Index (SWSI), Reclamation Drought Index (RDI) and so on are used. However, these drought indices are only used as a method of predicting the depth of drought, and do not give the actual number of drought occurrences.</p><p>In this study, we want to determine the frequency of Mega-drought occurrences in consideration of the drought damage characteristics that occurred worldwide from 1900 to 2018. The drought damages in the world were used by EM-DAT (the Emergency Events Database) which manages disaster data in CRED (Centre for Research on the Epidemiology of Disasters). Drought damages occurred in the world from 1900 to 2018 occurred more than once/years in 146 countries. The duration of drought persistence occurred in the country continuously for at least one to 17 years. The purpose of this study is to propose the criteria for mega drought by using the past victim data in connection with the incidence frequency.</p><p>Acknowledges : This research was supported by a grant(2019-MOIS31-010) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety(MOIS).</p><div> </div>

scholarly journals The Impacts of Climate-Induced Agricultural Drought on Four Cereal Crops: A Case Study in Bako Tibe District, Oromia National Regional State, Ethiopia

2020 ◽  
Vol 35 (1) ◽  
pp. 135
Author(s):  
Terefa Adunya ◽  
Fedhasa Chalchisa Benti
Keyword(s):  
Crop Yields ◽  
Pearson Correlation ◽  
Agricultural Drought ◽  
Extreme Weather Events ◽  
Coefficient Of Determination ◽  
Cereal Crops ◽  
Drought Indices ◽  
Trend Test ◽  
Small Scale ◽  
The Impact

<p>Increasing temperature and altered precipitation patterns lead to the extreme weather events such as drought and flood, which severely affects the agricultural production. This study was aimed to assess the impact of climate change-induced agricultural drought on four cereal crops in Bako Tibe District. Time-series climate and crop yield data, recorded from 1989 to 2018, were acquired from NASA’s data portal and Bako Research Institute. The changes in temperature and precipitation were analyzed using Mann Kendall trend test. The agricultural drought index was analyzed using R-software. The correlation between the selected yield crops and drought indices were evaluated using Pearson correlation coefficient. The results show that trends of seasonal and annual maximum and minimum temperatures were significantly increased (P&lt;0.05). However, seasonal and annual precipitations were insignificantly decreased (P&gt;0.05). Moderate to severe agricultural drought intensities happened four times in the last three decades. These drought spells spatially covered about 36% of the total area of the district. Crop yields and drought indices were significantly correlated at p-values; 0.0034, 0.043, 0.003 and 0.001 for teff, wheat, barley and maize, respectively. The coefficient of determination (R2) values of crop yields were 28.3%, 30.9%, 28.5% and 34.6% for teff, wheat, barley and maize, correspondingly. The study clearly suggests that the increase in temperature and decrease in precipitation enhanced the frequency and intensity of drought events and these impacted the selected crop yields during the past three decades. The map-based results could be used as guides for governmental and non-governmental organizations concerning on drought impact mitigation activities in the district by encouraging farmers to adopt appropriate agricultural technologies, drought tolerant crop varieties and small scale irrigation.</p>

scholarly journals FORECASTING AND MONITORING AGRICULTURAL DROUGHT IN THE PHILIPPINES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1263-1269
Author(s):  
G. J. Perez ◽  
M. Macapagal ◽  
R. Olivares ◽  
E. M. Macapagal ◽  
J. C. Comiso
Keyword(s):  
Land Surface ◽  
Drought Index ◽  
Vegetation Index ◽  
The Philippines ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Drought Event ◽  
Ancillary Data ◽  
Vulnerability Maps

A monitoring and forecasting sytem is developed to assess the extent and severity of agricultural droughts in the Philippines at various spacial scales and across different time periods. Using Earth observation satellite data, drought index, hazard and vulnerability maps are created. The drought index, called Standardized Vegetation-Temperature Ratio (SVTR), is derived using the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). SVTR is evaluated by correlating its values with existing agricultural drought index, particulary Evaporative Stress Index (ESI). Moreover, the performance of SVTR in detecting drought occurrences was assessed for the 2015-2016 drought event. This period is a strong El Niño year and a large portion of the country was affected by drought at varying degrees, making it a good case study for evaluating drought indices. Satellitederived SVTR was validated through several field visits and surveys across different major agricultural areas in the country, and was found to be 73% accurate. The drought hazard and vulnerability maps are produced by utilizing the evapotranspration product of MODIS, rainfall climatology from the Tropical Rainfall Microwave Mission (TRMM) and ancillary data, including irrigation, water holding capacity and land use. Finally, we used statistical techniques to determine trends in NDVI and LST and generate a sixmonth forecast of drought index. Outputs of this study are being assessed by the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) and the Department of Agriculture Bureau of Soils and Water Management (DABSWM) for future integration in their operations.

scholarly journals Mapping the Spatial and Temporal Variation of Agricultural and Metrological Drought Using Geospatial Techniques, Ethiopia

2020 ◽  
Author(s):  
Abebe Senamaw ◽  
Solomon Addisu ◽  
K.V. Suryabhagavan
Keyword(s):  
Temporal Variation ◽  
Crop Yield ◽  
Meteorological Drought ◽  
Condition Index ◽  
Agricultural Drought ◽  
Spatial And Temporal Variation ◽  
Drought Indices ◽  
Drought Risk ◽  
Drought Condition ◽  
Gis And Remote Sensing

Abstract Background Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The objective of this study was to assess spatial and temporal variation of agricultural and metrological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI). To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as SPI and crop yield anomaly. The results revealed that the year 2009 and 2015 were drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r=0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map. ResultThe result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56%, 35% and 8% of study area were vulnerable to very severe, severe and moderate drought condition respectively. Conclusion In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. Thus besides mapping drought vulnerable areas, integrating socioeconomic data for better understand other vulnerable factors were recommended.

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