Performance of different drought indices for agriculture drought in the North China Plain

The Palmer drought severity index （PDSI）, standardized precipitation index （SPI）, and standardized precipitation evapotranspiration index （SPEI） are used worldwide for drought assessment and monitoring. However, substantial differences exist in the performance for agricultural drought among these indices and among regions. Here, we performed statistical assessments to compare the strengths of different drought indices for agricultural drought in the North China Plain. Small differences were detected in the comparative performances of SPI and SPEI that were smaller at the long-term scale than those at the short-term scale. The correlation between SPI/SPEI and PDSI considerably increased from 1- to 12-month lags, and a slight decreasing trend was exhibited during 12- and 24-month lags, indicating a 12-month scale in the PDSI, whereas the SPI was strongly correlated with the SPEI at 1- to 24-month lags. Interestingly, the correlation between the trend of temperature and the mean absolute error and its correlation coefficient both suggested stronger relationships between SPI and the SPEI in areas of rapid climate warming. In addition, the yield-drought correlations tended to be higher for the SPI and SPEI than that for the PDSI at the station scale, whereas small differences were detected between the SPI and SPEI in the performance on agricultural systems. However, large differences in the influence of drought conditions on the yields of winter wheat and summer maize were evident among various indices during the crop-growing season. Our findings suggested that multi-indices in drought monitoring are needed in order to acquire robust conclusions.

Spatio-Temporal Agricultural Drought Quantification in a Rainfed Agriculture, Athi-Galana-Sabaki River Basin

This study employs a quantitative approach to comprehensively investigate the full propagation process of agricultural drought, focusing on pigeon peas (the most grown crop in the AGS Basin) planting seasonal variations. The study modelled seasonal variabilities in the seasonal Standardized Precipitation Index (SPI) and Standardized Agricultural Drought Index (SADI). To necessitate comparison, SADI and SPI were Normalized (from −1 to 1) as they had different ranges and hence could not be compared. From the seasonal indices, the pigeon peas planting season (July to September) was singled out as the most important season to study agricultural droughts. The planting season analysis selected all years with severe conditions (2008, 2009, 2010, 2011, 2017 and 2022) for spatial analysis. Spatial analysis revealed that most areas in the upstream part of the Basin and Coastal region in the lowlands experienced severe to extreme agricultural droughts in highlighted drought years. The modelled agricultural drought results were validated using yield data from two stations in the Basin. The results show that the model performed well with a Pearson Coefficient of 0.87 and a Root Mean Square Error of 0.29. This proactive approach aims to ensure food security, especially in scenarios where the Basin anticipates significantly reduced precipitation affecting water available for agriculture, enabling policymakers, water resource managers and agricultural sector stakeholders to equitably allocate resources and mitigate the effects of droughts in the most affected areas to significantly reduce the socioeconomic drought that is amplified by agricultural drought in rainfed agriculture river basins.

Global Change in Agricultural Flash Drought over the 21st Century

Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project(CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upperlevel and root-zone flash drought is projected to more than double in the mid-and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.

Influence of varied drought types on soil conservation service within the framework of climate change:insights from the Jinghe River Basin,China

Severe soil erosion and drought are the two main factors affecting the ecological security of the Loess Plateau,China.Investigating the influence of drought on soil conservation service is of great importance to regional environmental protection and sustainable development.However,there is little research on the coupling relationship between them.In this study,focusing on the Jinghe River Basin,China as a case study,we conducted a quantitative evaluation on meteorological,hydrological,and agricultural droughts(represented by the Standardized Precipitation Index(SPI),Standardized Runoff Index(SRI),and Standardized Soil Moisture Index(SSMI),respectively)using the Variable Infiltration Capacity(VIC)model,and quantified the soil conservation service using the Revised Universal Soil Loss Equation(RUSLE)in the historical period(2000-2019)and future period(2026-2060)under two Representative Concentration Pathways(RCPs)(RCP4.5 and RCP8.5).We further examined the influence of the three types of drought on soil conservation service at annual and seasonal scales.The NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP)dataset was used to predict and model the hydrometeorological elements in the future period under the RCP4.5 and RCP8.5 scenarios.The results showed that in the historical period,annual-scale meteorological drought exhibited the highest intensity,while seasonal-scale drought was generally weakest in autumn and most severe in summer.Drought intensity of all three types of drought will increase over the next 40 years,with a greater increase under the RCP4.5 scenario than under the RCP8.5 scenario.Furthermore,the intra-annual variation in the drought intensity of the three types of drought becomes smaller under the two future scenarios relative to the historical period(2000-2019).Soil conservation service exhibits a distribution pattern characterized by high levels in the southwest and southeast and lower levels in the north,and this pattern has remained consistent both in the historical and future periods.Over the past 20 years,the intra-annual variation indicated peak soil conservation service in summer and lowest level in winter;the total soil conservation of the Jinghe River Basin displayed an upward trend,with the total soil conservation in 2019 being 1.14 times higher than that in 2000.The most substantial impact on soil conservation service arises from annual-scale meteorological drought,which remains consistent both in the historical and future periods.Additionally,at the seasonal scale,meteorological drought exerts the highest influence on soil conservation service in winter and autumn,particularly under the RCP4.5 and RCP8.5 scenarios.Compared to the historical period,the soil conservation service in the Jinghe River Basin will be significantly more affected by drought in the future period in terms of both the affected area and the magnitude of impact.This study conducted beneficial attempts to evaluate and predict the dynamic characteristics of watershed drought and soil conservation service,as well as the response of soil conservation service to different types of drought.Clarifying the interrelationship between the two is the foundation for achieving sustainable development in a relatively arid and severely eroded area such as the Jinghe River Basin.

Monitoring and Assessment System of Agricultural Drought Based on GIS Technology

[Objective] The research aimed to simplify the operating process of agricultural drought monitoring and assessment product,and improve fine level of monitoring and assessment map.[Method] By comprehensively using GIS and mathematics,meteorology,management science,computer science,the monitoring and assessment of drought were as the core,the monitoring and assessment system of agricultural drought based on GIS technology was studied.[Result] The drought in Guangxi on November 4,2006 was monitored by using the system,and the actual situation was used to test.The result proved that the good monitoring effect was obtained.[Conclusion] The monitoring and assessment system of agricultural drought based on GIS realized the organic combination of GIS and professional monitoring,assessment model.The flexible HCI interface and visualization expression were provided.The monitoring and assessment function of agricultural drought was realized.It had the good practicality and advancement.

Assessment on Agricultural Drought Risk Based on Variable Fuzzy Sets Model

Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was estab-lished according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respec-tively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combi-nation weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the as-sessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.

Comparison between TVDI and CWSI for drought monitoring in the Guanzhong Plain,China

Temperature vegetation dryness index （TVDI） and crop water stress index （CWSI） are two commonly used remote sens- ing-based agricultural drought indicators. This study explored the applicability of monthly moderate resolution imaging spectroradiometer （MODIS） normalized difference vegetation index （NDVI） and land surface temperature （LST） data for agricultural drought monitoring in the Guanzhong Plain, China in 2003. The data were processed using TVDI, calculated by parameterizing the relationship between the MODIS NDVI and LST data. We compared the effectiveness of TVDI against CWSI, derived from the MOD16 products, for drought monitoring. In addition, the surface soil moisture and monthly pre- cipitation were collected and used for verification of the results. Results from the study showed that： （1） drought conditions measured by TVDI and CWSI had a number of similarities, which indicated that both CWSI and TVDI can be used for drought monitoring, although they had some discrepancies in the spatiotemporal characteristics of drought intensity of this region; and （2） both standardized precipitation index （SPI） and SM contents at the depth of 10 and 20 cm had better correlations to CWSI than to TVDI, indicating that there were more statistically significant relationships between CWSI and SPI/SM, and that CWSI is a more reliable indicator for assessing and monitoring droughts in this region.

Influence Factors and Assessment of Risk Perception for Agricultural Drought Based on Household-scale

This paper describes the basic connotation of risk perception, the influence factors of the risk perception for agricultural drought and the mainstream assess- ment model. Additionally, it summarizes the latest developments of research meth- ods for risk perception for the agricultural drought, and the research status of the risk perception for agricultural drought, and put forward the trends of risk perception for the agricultural drought. Finally, it proposes the research areas of the risk per- ception for agricultural drought should be improved in future.

Assessment of global meteorological,hydrological and agricultural drought under future warming based on CMIP6

Quantifying the changes and propagation of drought is of great importance for regional eco-environmental safety and water-related disaster management under global warming.In this study,phase 6 of the Coupled Model Intercomparison Project was employed to examine future meteorological(Standardized Precipitation Index,SPI,and Standardized Precipitation-Evapotranspiration Index,SPEI),hydrological(Standardized Runoff Index,SRI),and agricultural(Standardized Soil moisture Index,SSI) drought under two warming scenarios(SSP2-4.5 and SSP5-8.5).The results show that,across the globe,different types of drought events generally exhibit a larger spatial extent,longer duration,and greater severity from 1901 to 2100,with SPEI drought experiencing the greatest increases.Although SRI and SSI drought are expected to be more intensifying than SPI drought,the models show higher consistency in projections of SPI changes.Regions with robust drying trends include the southwestern United States,Amazon Basin,Mediterranean,southern Africa,southern Asia,and Australia.It is also found that meteorological drought shows a higher correlation with hydrological drought than with agricultural drought,especially in warm and humid regions.Additionally,the maximum correlation between meteorological and hydrological drought tends to be achieved at a short time scale.These findings have important implications for drought monitoring and policy interventions for water resource management under a changing climate.

Propagation characteristics from meteorological drought to agricultural drought over the Heihe River Basin, Northwest China

In the context of global warming,drought events occur frequently.In order to better understanding the process and mechanism of drought occurrence and evolution,scholars have dedicated much attention on drought propagation,mainly focusing on drought propagation time and propagation probability.However,there are relatively few studies on the sensitivities of drought propagation to seasons and drought levels.Therefore,we took the Heihe River Basin(HRB)of Northwest China as the case study area to quantify the propagation time and propagation probability from meteorological drought to agricultural drought during the period of 1981–2020,and subsequently explore their sensitivities to seasons(irrigation and non-irrigation seasons)and drought levels.The correlation coefficient method and Copula-based interval conditional probability model were employed to determine the drought propagation time and propagation probability.The results determined the average drought propagation time as 8 months in the whole basin,which was reduced by 2 months(i.e.,6 months)on average during the irrigation season and prolonged by 2 months(i.e.,10 months)during the non-irrigation season.Propagation probability was sensitive to both seasons and drought levels,and the sensitivities had noticeable spatial differences in the whole basin.The propagation probability of agricultural drought at different levels generally increased with the meteorological drought levels for the upstream,midstream,and southern downstream regions of the HRB.Lesser agricultural droughts were more likely to be triggered during the irrigation season,while severer agricultural droughts were occurred mostly during the non-irrigation season.The research results are helpful to understand the characteristics of drought propagation and provide a scientific basis for the prevention and control of droughts.This study is of great significance for the rational planning of local water resources and maintaining good ecological environment in the HRB.

Modeling Spatio-temporal Drought Events Based on Multi-temporal,Multi-source Remote Sensing Data Calibrated by Soil Humidity

Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue.The resulting model,the‘Humidity calibrated Drought Condition Index’(HcDCI)was applied for the years 2001 to 2019 in form of a case study to Weihai County,Shandong Province in East China.Design and development are based on a linear combination of the Vegetation Condition Index(VCI),the Temperature Condition Index(TCI),and the Rainfall Condition Index(RCI)using multi-source satellite data to create a basic Drought Condition Index(DCI).VCI and TCI were derived from MODIS(Moderate Resolution Imaging Spectroradiometer)data,while precipitation is taken from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station data)data.For reasons of accuracy,the decisive coefficients were determined by the relative humidity of soils at depth of 10-20 cm of particular areas collected by an agrometeorological ground station.The correlation between DCI and soil humidity was optimized with the factors of 0.53,0.33,and 0.14 for VCI,TCI,and RCI,respectively.The model revealed,light agricultural droughts from 2003 to 2013 and in 2018,while more severe droughts occurred in 2001 and 2002,2014-2017,and 2019.The droughts were most severe in January,March,and December,and our findings coincide with historical records.The average temperature during 2012-2019 is 1℃ higher than that during the period 2001-2011 and the average precipitation during 2014-2019 is 192.77 mm less than that during 2008-2013.The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities.The model thus,demonstrates its capability to reveal drought periods in detail,its transferability to other regions and its usefulness to take future measures.

Agricultural Drought Resisting and Hydrological-Ecological Changes Taking Hebei Province in North China as an Example

Drought is usually supposed to be a rainfall deficiency problem. Most studies and practices to mitigate drought disaster are focusing on water development and irrigation, while neglecting that the agriculture system is a compounded human-natural system. Drought situation and tendency is also driven by human coping strategies. This paper takes Hebei Province in north China as an example, studing the spirally interact process of drought resisting and hydrological ecological feedback. The result shows that large scale water projects construction facilitated irrigation. With improved irrigation, farmers enhanced multiple crop index and land-use intensity greatly and increased the sowing area of water consuming crop, winter wheat. At the same time, both crop yield and gross output are raising steadily. Water demand and depletion in agricultural system increase year by year. This gradually leads to highly dependent on over exploitation of water resources, especially overdraw of groundwater. The process deteriorated the stability of hydrological-ecological system and made the ecological environment drying up. Drying up environment is breeding greater vulnerability and risk of drought in the long term. For sustainable development, integrated drought risk management should be based on the balance between sustainable water supply and water demand. The key is to improve agricultural system＇s adaptive and resilient capacity to drought.

EFFECT OF DROUGHT ON AGRICULTURE AND ITS COUNTERMEASURES

ＥＦＦＥＣＴＯＦＤＲＯＵＧＨＴＯＮＡＧＲＩＣＵＬＴＵＲＥＡＮＤＩＴＳＣＯＵＮＴＥＲＭＥＡＳＵＲＥＳＥＦＦＥＣＴＯＦＤＲＯＵＧＨＴＯＮＡＧＲＩＣＵＬＴＵＲＥＡＮＤＩＴＳＣＯＵＮＴＥＲＭＥＡＳＵＲＥＳ￥ＣｈｅｎＹａｎｎｉａｎ（Ｍｅｔｅｏｒｏｌｏｇｉｃａｌ...

Quantitative Assessment and Spatial Characteristics of Agricultural Drought Risk in the Jinghe Watershed, Northwestern China

Though drought is a recurrent phenomenon in the Jinghe watershed, very little attention has been paid to drought mitigation and preparedness. This article presents a method for the spatial assessment of agricultural drought risk in the Jinghe watershed of western China at a 1-km grid scale. A conceptual framework, which emphasizes the combined roles of hazard and vulnerability in defining risk, is used. The Z index method in a GIS environment is used to map the spatial extent of drought hazards. The key social and physical factors that define agricultural drought in the context of the Jinghe watershed are indentified and corresponding thematic maps are prepared. Risk is calculated by the integration of hazard and vulnerability. Results show that the risk gradient follows a north-south and west-east tendency and that agricultural droughts pose the highest risk to northern and northwestern sections of the Jinghe watershed.

Maize drought disaster risk assessment of China based on EPIC model

Digital Agriculture is one of the important applications of Digital Earth.As the global climate changes and food security becomes an increasingly important issue,agriculture drought comes to the focus of attention.China is a typical monsoon climate country as well as an agricultural country with the world’s largest population.The East Asian monsoon has had a tremendous impact upon agricultural production.Therefore,a maize drought disaster risk assessment,in line with the requirements of sustainable development of agriculture,is important for ensuring drought disaster reduction and food security.Meteorology,soil,land use,and agro-meteorological observation information of the research area were collected,and based on the concept framework of‘hazard-inducing factors assessment(hazard)-vulnerability assessment of hazard-affected body(vulner-ability curve)-risk assessment(risk),’importing crop model EPIC(Erosion-Productivity Impact Calculator),using crop model simulation and digital mapping techniques,quantitative assessment of spatio-temporal distribution of maize drought in China was done.The results showed that:in terms of 2,5,10,and 20 year return periods,the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas.With the 20 year return period,high risk value regions(drought loss rate]0.5)concentrate in the irrigated maize region of Northwest china,ecotone between agriculture and animal husbandry in Northern China,Hetao Irrigation Area,and north-central area of North China Plain,accounting for 6.41%of the total maize area.These results can provide a scientific basis for the government’s decision-making in risk management and drought disaster prevention in China.

Agricultural drought monitoring: Progress, challenges, and prospects

In this paper, we compared the concept of agricultural drought and its relationship with other types of droughts and reviewed the progress of research on agricultural drought monitoring indices on the basis of station data and remote sensing. Applicability and limitations of different drought monitoring indices were also compared. Meanwhile, development history and the latest progress in agricultural drought monitoring were evaluated through statistics and document comparison, suggesting a transformation in agricultural drought monitoring from traditional single meteorological monitoring indices to meteorology and remote sensing-integrated monitoring indices. Finally, an analysis of current challenges in ag- ricultural drought monitoring revealed future research prospects for agricultural drought monitoring, such as investigating the mechanism underlying agricultural drought, identifying factors that influence agricultural drought, developing multi-spatiotemporal scales models for agricultural drought monitoring, coupling qualitative and quantitative agricultural drought evaluation models, and improving the application levels of remote sensing data in agricultural drought monitoring.

Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield

Agricultural drought threatens food security.Numerous remote-sensing drought indices have been developed,but their different principles,assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas.Here,we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces,northern China(predominantly rain-fed and irrigated agriculture,respectively):vegetation health index(VHI),temperature vegetation dryness index(TVDI)and drought severity index(DSI).We compared the agreement between these indices and the standardized precipitation index(SPI),soil moisture,winter wheat yield and National Meteorological Drought Monitoring(NMDM)maps.On average,DSI outperformed the other indices,with stronger correlations with SPI and soil moisture.DSI also corresponded better with soil moisture and NMDM maps.The jointing and grain-filling stages of winter wheat are more sensitive to water stress,indicating that winter wheat required more water during these stages.Moreover,the correlations between the drought indices and SPI,soil moisture,and winter wheat yield were generally stronger in Shaanxi province than in Henan province,suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.

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.

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.