Assessment of an Evapotranspiration Deficit Drought Index in Relation to Impacts on Ecosystems

Ecosystems have increasingly been subject to the challenge of heavy drought under global warming. To quantitatively evaluate the impacts of drought on ecosystems, it is necessary to develop a drought index that can sensitively depict the response of vegetation to drought evolution at a biological time scale. For the ability of direct connection between climate and ecosystem by deficit of evapotranspiration, in the present study, a drought index was defined based on standardized evapotranspiration deficit (SEDI), according to the difference between actual and potential evapotranspiration, to meet the need for highlighting drought impacts on ecological processes. Comparisons with traditional indices show that SEDI can reasonably detect droughts and climatic dry and wet transitions, especially at a monthly time scale, and can also regenerate long-term trends. Moreover, SEDI can more sensitively capture the biological changes of ecosystems in response to the dynamics of drought intensity, compared with the indices of precipitation and temperature. SEDI is more practical than the precipitation and temperature indices to highlight signals of biological effects in climate droughts. Hence, it has potential for use in assessments of climate change and its impact on ecosystems.

Spatial and temporal variation of drought index in a typical steep alpine terrain in Hengduan Mountains

This study describes the spatial and temporal variation of a drought index and makes inferences regarding the environmental factors that influence this variability in the Hengduan Mountains. A drought index is typically used to determine the moisture conditions and the magnitude of water deficiency in a given area. Based on data from 26 meteorological stations over the period 1960-2012, the spatial and temporal variations of the drought index were analyzed using a thin plate smoothing splines method that considered elevation as a covariate. The drought index was estimated based on the potential evapotranspiration(E0) as defined by the Penman Monteith model modified by FAO(1998). The results of the reported analysis showed that the drought index in the Hengduan Mountains has been decreasing since 1960 at a rate of-0.008/a. This represented a progressive shift from the "sub-humid" class, which typified the wider area in the Hengduan Mountains, toward the "humid" class, which appeared in the Hengduan Mountains areas. The drought index was relatively high in the north and low in the south and the variation of the drought index varied with seasons. The drought index showed increasing trends in summer and autumn and it is greater in autumn than in summer, while it showed a decreasing trend in spring and winter. Drought index is inversely proportional to the soil relative humidity and Normalized Difference Vegetation Index(NDVI).

Introducing a drought index to a crop model can help to reduce the gap between the simulated and statistical yield

农田作物生产模型是一个用于评估众多环境和人为因子影响下作物产量变化的重要工具。然而,将所有与作物生长相关的环境因子考虑进模型中是不现实的。因此,模型往往会在一些极端环境条件发生时高估作物的产量。在本文中,我们试图将一个干旱指数(SPEI)应用到一个农田生态系统过程模型(Agro-C)。同时,对比了模型是否考虑干旱指数的情况下与统计产量之间的差距;用于对比的统计产量是黄淮海平原各县近20年来的小麦和玉米统计数据。研究结果显示:在干旱发生的年份里,模型确实部分高估了作物产量;而在模型中加入干旱指数,则能够一定程度提高模型模拟干旱年份粮食作物的精度。

Annual growth of Fagus orientalis is limited by spring drought conditions in Iran’s Golestan Province

Due to the lack of a uniform and accurate defi-nition of‘drought’,several indicators have been introduced based on different variables and methods,and the efficiency of each of these is determined according to their relationship with drought.The relationship between two drought indices,SPI(standardized precipitation index)and SPEI(standard-ized precipitation-evapotranspiration index)in different sea-sons was investigated using annual rings of 15 tree samples to determine the effect of drought on the growth of oriental beech(Fagus orientalis Lipsky)in the Hyrcanian forests of northern Iran.The different evapotranspiration calcula-tion methods were evaluated on SPEI efficiency based on Hargreaves-Samani,Thornthwaite,and Penman-Monteith methods using the step-by-step M5 decision tree regression method.The results show that SPEI based on the Penman-Monteith in a three-month time scale(spring)had similar temporal changes and a better relationship with annual tree rings(R^(2)=0.81)at a 0.05 significant level.Abrupt change and a decreasing trend in the time series of annual tree rings are similar to the variation in the SPEI based on the Penman-Monteith method.Factors affecting evapotranspiration,temperature,wind speed,and sunshine hours(used in the Penman-Monteith method),increased but precipitation decreased.Using non-linear modeling methods,SPEI based on Penman-Monteith best illustrated climate changes affecting tree growth.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

Meteorological Drought Detection and Forecast Using Standardized Precipitation Index and Univariate Distribution Models: Case Study of Bamako, Mali

As an extended period of unusually dry weather conditions without sufficient rain, drought poses enormous risk on societies. Characterized by the absence of precipitation for long periods of time, often resulting in water scarcity, droughts are increasingly posing significant environmental challenges. Drought is therefore considered an important element in the management of water resources, especially groundwater resources during drought. This study therefore sought to investigate the rainfall variability and the frequency of drought for the period 1991 to 2020 in Bamako based on monthly rainfall data from Bamako-Senou gauge station. The standardized precipitation index (SPI) for 12-month, 6-month and 3-month timescales and the SPI for annual totals were used to characterized drought in the study area (Bamako). Univariate parametric probability distributions such as Normal, Log-normal, Gumbel type I and Pearson type III (P3) distributions were fitted with drought variables (severity and duration) for future planning and management. Non-parametric test such as Mann-Kendall trend test was also used to detect trend in annual rainfall data. The results showed that based on 12-month SPI, Bamako experienced two (02) extreme droughts one in July 2002 (SPI = -2.2165) and another in June 2015 (SPI = -2.0598 QUOTE SPI=-2.0598 ). Drought years represented 46.67% for the overall periods according to the SPI for annual totals. The result further indicated that based on the goodness of fit test, the P3 distribution represents the best fitted distribution to both drought severity and duration over Bamako. Bamako is expected to experience several severe severities with higher and shorter duration in the future. Severities with 1, 2, 6, and 10-month duration had return periods ranged from 2.4 to 3.8 years, while 5, 10, 20, 25, 50, and 100-year return periods had 18.51, 26.08, 33.25, 35.50, 42.38, and 49.14 severities, respectively, and durations associated to these severities were 19.8, 26.9, 33.5, 35.6, 42, and 48.2 months, respectively.

Index-based assessment of agricultural drought in a semi-arid region of Inner Mongolia, China

Agricultural drought is a type of natural disaster that seriously impacts food security.Because the relationships among short-term rainfall,soil moisture,and crop growth are complex,accurate identification of a drought situation is difficult.In this study,using a conceptual model based on the relationship between water deficit and crop yield reduction,we evaluated the drought process in a typical rainfed agricultural region,Hailar county in Inner Mongolia autonomous region,China.To quantify drought,we used the precipitation-based Standardized Precipitation Index(SPI),the soil moisture-based Crop Moisture Index(CMI),as well as the Normalized Difference Vegetation Index(NDVI).Correlation analysis was conducted to examine the relationships between dekad-scale drought indices during the growing season(May–September)and final yield,according to data collection from 2000 to 2010.The results show that crop yield has positive relationships with CMI from mid-June to mid-July and with the NDVI anomaly throughout July,but no correlation with SPI.Further analysis of the relationship between the two drought indices shows that the NDVI anomaly responds to CMI with a lag of 1 dekad,particularly in July.To examine the feasibility of employing these indices for monitoring the drought process at a dekad time scale,a detailed drought assessment was carried out for selected drought years.The results confirm that the soil moisture-based vegetation indices in the late vegetative to early reproductive growth stages can be used to detect agricultural drought in the study area.Therefore,the framework of the conceptual model developed for drought monitoring can be employed to support drought mitigation in the rainfed agricultural region of Northern China.

A daily drought index based on evapotranspiration and its application in regional drought analyses

With climate warming, frequent drought events have occurred in recent decades, causing huge losses to industrial and agricultural production, and affecting people’s daily lives. The monitoring and forecasting of drought events has drawn increasing attention. However, compared with the various monthly drought indices and their wide application in drought research,daily drought indices, which would be much more suitable for drought monitoring and forecasting, are still scarce. The development of a daily drought index would improve the accuracy of drought monitoring and forecasting, and facilitate the evaluation of existing indices. In this study, we constructed a new daily drought index, the daily evapotranspiration deficit index(DEDI), based on actual and potential evapotranspiration data from the high-resolution ERA5 reanalysis dataset of the European Center for Medium-Range Weather Forecasts. This new index was then applied to analyze the spatial and temporal evolution characteristics of four drought events that occurred in southwest, north, northeast, and eastern northwest China in the spring and summer of 2019. Comparisons with the operationally used Meteorological Drought Composite Index and another commonly used index, the Standardized Precipitation Evapotranspiration Index, indicated that DEDI characterized the spatiotemporal evolution of the four drought events reasonably well and was superior in depicting the onset and cessation of the drought events,as well as multiple drought intensity peaks. Additionally, DEDI considers land surface conditions, such as vegetation coverage,which enables its potential application not only for meteorological purposes but also for agricultural drought warning and monitoring.

A drought resistance index to select drought resistant plant species based on leaf water potential measurements

The water deficit in arid and semi-arid regions is the primary limiting factor for the development of urban greenery and forestation. In addition, planting the species that consume low levels of water is useful in arid and semi-arid regions that have poor water management measures. Leaf water potential(Ψ) is a physiological parameter that can be used to identify drought resistance in various species. Indeed, Ψ is one of the most important properties of a plant that can be measured using a pressure chamber. Drought avoiding or drought resistant species have a lower Ψ than plants that use normal or high levels of water. To determine drought resistance of species that are suitable for afforestation in arid urban regions, we evaluated twenty woody species in the Isfahan City, central Iran. The experimental design was random split-split plots with five replications. The species were planted outdoor in plastic pots and then subjected to treatments that consisted of two soil types and five drip irrigation regimes. To evaluate the resistance of each species to drought, we used the Ψ and the number of survived plants to obtain the drought resistance index(DRI). Then, cluster analysis, dendrogram, and similarity index were used to group the species using DRI. Result indicates that the evaluated species were classified into five groups:(1) high water consuming species(DRI>–60 MPa);(2) above normal water consuming species(–60 MPa≥DRI>–90 MPa);(3) normal water consuming species(–90 MPa≥DRI>–120 MPa);(4) semi-drought resistant species(–120 MPa≥DRI>–150 MPa);and(5) drought resistant species(DRI≤–150 MPa). According to the DRI, Salix babylonica L., Populus alba L., and P. nigra L. are high water consuming species, Platanus orientalis L. and Albizia julibrissin Benth are normal water consuming species, and Quercus infectoria Oliv. and Olea europaea L. can be considered as drought resistant species.

Projected Changes of Palmer Drought Severity Index under an RCP8.5 Scenario

The potential change of drought measured by the Palmer Drought Severity Index(PDSI)is projected by using a coupled climate system model under a Representative Pathway 8.5(RCP8.5)scenario.The PDSI changes calculated by two potential evapotranspiration algorithms are compared.The algorithm of Thornthwaite equation overestimates the impact of surface temperature on evaporation and leads to an unrealistic increasing of drought frequency.The PM algorithm based on the Penman-Monteith equation is physically reasonably and necessary for climate change projections.The Flexible Global Ocean-Atmosphere-Land System model,Spectral Version 2(FGOALS-s2)projects an increasing trend of drought during 2051–2100 in tropical and subtropical areas of North and South America,North Africa,South Europe,Southeast Asia,and the Australian continent.Both the moderate drought(PDSI<–2)and extreme drought(PDSI<–4)areas show statistically significant increasing trends under an RCP8.5 scenario.The uncertainty in the model projection is also discussed.

The concept and statistical method of drought resistance index in crops

There is evindence showing that stress susceptibility index(SSI)(1一Yd/Yp)/(1—(?)d/(?)p)used as a measure of drought resistance of crop on the field is an altered form of droughtresistance coefficient(DRC)(Yd/Yp).The correlative coefficient SSI and DRC is r=-1.Therefore,the SSI doesn’t improve the defect of the DRC.After two years experiments per-formed by using thirty winter wheat varieties as trial materials,the concept of drought resistanceindex in crops was put forward.Its expressing equation is:the yield in drylan×drought resis-tance coefficient/average yield in dryland.It makes the drought resistance coefficient(physicalindex)correlate well with the yield in dryland(agronomy index)and is suitable for breeder.

Using leaf area index(LAI) to assess vegetation response to drought in Yunnan province of China

Climatic extremes such as drought have becoming a severe climate-related problem in many regions all over the world that can induce anomalies in vegetation condition. Growth and CO2 uptake by plants are constrained to a large extent by drought.Therefore, it is important to understand the spatial and temporal responses of vegetation to drought across the various land cover types and different regions. Leaf area index(LAI) derived from Global Land Surface Satellite(GLASS) data was used to evaluate the response of vegetation to drought occurrence across Yunnan Province, China(2001-2010). The meteorological drought was assessed based on Standardized Precipitation Index(SPI)values. Pearson's correlation coefficients between LAI and SPI were examined across several timescales within six sub-regions of the Yunnan. Further, the drought-prone area was identified based on LAI anomaly values. Lag and cumulative effects of lack of precipitation on vegetation were evident, with significant correlations found using 3-, 6-, 9-and 12-month timescale. We found 9-month timescale has higher correlations compared to another timescale.Approximately 29.4% of Yunnan's area was classified as drought-prone area, based on the LAI anomaly values. Most of this drought-prone area was distributed in the mountainous region of Yunnan.From the research, it is evident that GLASS LAI can be effectively used as an indicator for assessing drought conditions and it provide valuable information for drought risk defense and preparedness.

Spatial and Temporal Characteristics of Drought and Flood in Quanzhou Based on Standardized Precipitation Index (SPI) in Recent 55 Years

To analyze the characteristics of drought and flood variations in Quanzhou during recent 55 years, the standardized precipitation index (SPI) and Empirical Orthogonal Function (EOF) and Rotated Empirical Orthogonal Function (REOF) were calculated by using the monthly precipitation data from 6 meteorological bureaus across Quanzhou for 1960-2014. Results showed that: 1) During 1960-2014, the drought and flood showed Periodic variation characteristics in Quanzhou, the specific period of frequent drought was 1963-1972, 1977-1986 and 2009-2011, and the specific period of frequent flood was 1961-1962, 1972-1975, 1990-1992 and 1997-2007;the drought and flood did not have significant tendency of variation in Spring and Summer, and the drought and flood showed a non-significant downward trend in Autumn and Winter. 2) The drought and flood variation had relatively consistent trend in Quanzhou, but there was a big difference on the northwest mountainous area, the middle semi-mountainous area and the southeast coast area in some periods. 3) The precipitation cell and distribution in every season were Nan’an and Anxi, but there was a big difference in rainfall less area: it was Yongchun and Dehua in Spring, Chongwu and Jinjiang in Summer, Chongwu in Autumn, Dehua and Chongwu in Winter.

Evaluation of Spatial-Temporal Variability of Drought Events in Iran Using Palmer Drought Severity Index and Its Principal Factors (through 1951-2005)

Intensity and variability of droughts are considered inIranduring the period 1951 to 2005. Four variables are considered: the Palmer Drought Severity Index (PDSI), the soil moisture, the temperature and the precipitation (products used for the analysis are downloaded from the NCAR website). Link with the climatic indexLa Ninais also considered (NOAA downloadable products is used). The analysis is based on basic statistical approaches (correlation, linear regressions and Principal Component Analysis). The analysis shows that PDSI is highly correlated to the soil moisture and poorly correlated to the other variables—although the temperature in the warm season shows high correlation to the PDSI and that a severe drought was experienced during 1999-2002 inthe country.

Index System and Influence of Drought in Northwest China

In this paper, the index systems of the agricultura drought and decrease percentage of grain crop are established. Th trend and influence of drought in the region is analyzed based o the 50 years (1951-2000) statistical data of precipitation and 5 years (1951–2002) agricultural drought of the region, includin five provinces: Shaanxi, Gansu, Ningxia, Qinghai and Xinjiang The result shows that the drought disaster is increasing and th most serious were in the 1970s and 1990s, and main agricultura drought is a great disaster incident. The regression prediction equa tion of drought and flood grades and agricultural drought area grades are set up by the harmonic wave method, and forecastin the drought will lighten during the first ten years of the 21s century.

An improved temperature vegetation dryness index(iTVDI) and its applicability to drought monitoring

Using Moderate Resolution Imaging Spectroradiometer(MODIS) data from the dry season during 2010–2012 over the whole Yunnan Province, an improved temperature vegetation dryness index(iTVDI), in which a parabolic dry-edge equation replaces the traditional linear dry-edge equation, was developed, to reveal the regional drought regime in the dry season. After calculating the correlation coefficient, root-mean-square error, and standard deviation between the iTVDI and observed topsoil moisture at 10 and 20 cm for seven sites, the effectiveness of the new index in depicting topsoil moisture conditions was verified. The drought area indicated by iTVDI mapping was then compared with the drought-affected area reported by the local government. The results indicated that the iTVDI can monitor drought more accurately than the traditional TVDI during the dry season in Yunnan Province. Using iTVDI facilitates drought warning and irrigation scheduling, and the expectation is that this new index can be broadly applied in other areas.

APPLICATION OF VEGETATION INDEX OF METEOROLOGICAL SATELLITE IN DROUGHT ANALYSIS OF NINGXIA

There are five channels in NOAA-N series meteorological satellites. The channel No.1 is exactly located in the absorbtion band of vegetation, the channel No. 2 in the strong re-flection one. Therefore the two channels are suitable for monitoring and analysing vegeta-tion. To make certain mathematical value combination of two channels and specify its val-

Screening of Drought Resistance Identification Indexes for Rice(Oryza sativa L.) Cultivars in Ningxia

The morphological characters, physiological characters, yield traits and yield per plant of total 49 rice cultivars from Ningxia were investigated under conditions of water stress and non-water stress so as to determine the relationship between each trait and yield per plant under water stress and the relationship between each relative character and drought resistance coefficient under water stress and non-water stress. The correlation, grey correlation, stepwise regression and path analyses showed that the tiller number per plant, plant height, grain density, effective panicle number per plant and grain number per panicle, total 5 traits, were significantly correlated with the drought resistance of rice, and they could be used to identify the drought resistance of rice in Ningxia. In addition, the drought resistance of rice was graded qualitatively according to the subordinate function value of corresponding drought resistance coefficient. The results showed that among the 49 rice cultivars from Ningxia,6 rice cultivars were highly drought resistant, and 9 rice cultivars were moderately drought resistant, suggesting that the evaluation method was feasible and effective.

Regional Climate Index for Floods and Droughts Using Canadian Climate Model (CGCM3.1)

The impacts of climate change on the discharge regimes in New Brunswick (Canada) were analyzed, using artificial neural network models. Future climate data were extracted from the Canadian Coupled General Climate Model (CGCM3.1) under the greenhouse gas emission scenarios B1 and A2 defined by the Intergovernmental Panel on Climate Change (IPCC). The climate change fields (temperatures and precipitation) were downscaled using the delta change approach. Using the artificial neural network, future river discharge was predicted for selected hydrometric stations. Then, a frequency analysis was carried out using the Generalized Extreme Value (GEV) distribution function, where the parameters of the distribution were estimated using L-moments method. Depending on the scenario and the time slice used, the increase in low return floods was about 30% and about 15% for higher return floods. Low flows showed increases of about 10% for low return droughts and about 20% for higher return droughts. An important part of the design process using frequency analysis is the estimation of future change in floods or droughts under climate scenarios at a given site and for specific return periods. This was carried out through the development of Regional Climate Index (RCI), linking future floods and droughts to their frequencies under climate scenarios B1 and A2.