Evapotranspiration Deficit Index Research Articles

Severe drought events inducing large decrease of net primary productivity in mainland China during 1982–2015

The analysis of the impact of drought events on terrestrial net primary productivity (NPP) is significant to understand the effects of droughts on regional/global carbon cycling. During the past three decades, terrestrial ecosystems in mainland China have been frequently impacted by drought events. However, quantitative analyses of the variation of NPP induced by droughts are still not enough. Therefore, this study explored the response of NPP to drought events from 1982 to 2015 based on the standardized evapotranspiration deficit index (SEDI) and an NPP dataset obtained from the Carnegie–Ames–Stanford Approach model. We first identified drought events and analyzed the characteristics of drought events using a three-dimensional clustering algorithm. Subsequently, we determined the NPP variations in the drought-affected areas during the droughts and explored the correlation between the NPP variation and the drought characteristics. The results showed that 152 persistent drought events lasting at least 3 months were identified. Most events had durations between 3 and 5 months, and 19 events lasted >9 months. A negative NPP was detected in >60% of the drought-affected areas during long-term (>6 months) and severe (>4 × 106 km2 month) drought events and the total NPP showed a clear decrease during these events. In general, strong drought events reduced the total NPP by >30 TgC in the Northern Region, South Region, Southwest Region, and Northeast Region. The substantial decrease was mainly caused by the NPP anomaly from April to September. The NPP responses to drought events exhibited differences due to different drought characteristics. Although a high proportion of the drought-affected areas experienced a decrease in NPP during most short-term (<5 months) and less severe droughts (<2 × 106 km2 month), the total NPP did not exhibit a large change during these events.

A national-scale drought assessment in Uganda based on evapotranspiration deficits from the Bouchet hypothesis

For effective management of drought risks, a process-specific indicator needs to be employed rather than depending only on precipitation anomalies. In this study, we performed an evapotranspiration-based (ET-based) assessment of agricultural droughts in Uganda where drought has usually been assessed with precipitation deficiency. The land-surface ET and evaporative demand were estimated with a state-of-the-art complementary principle across the country under poor ET data availability. Using the ET estimates, the Standardized Evapotranspiration Deficit Index (SEDI) was quantified to assess agricultural droughts for 1984–2017. The ET-based drought assessment was compared with conventional precipitation-based analyses using the Standardized Precipitation Index (SPI) in respect of severity, areal extent, and temporal trends. Results showed that the complementary principle provided acceptable performance in reproducing interpolated latent flux observations. SPI and SEDI were strongly correlated, and thus yielded identical temporal variations of mean drought severity and areal extent. The trend maps of SPI and SEDI also tended to agree, and indicate that central and northwestern Uganda would face increasing drought risks in the future. The declining precipitation in Uganda has been attributed to rising surface temperatures of the Indian Ocean, and is expected to persist up to the next decade. This study suggests that droughts in major croplands could be often accompanied by high heat-wave temperatures in Uganda due to strong land-atmosphere coupling, and thus mortality risks in ecosystems could increase together with water stress.

Historical Drought Assessment Over the Contiguous United States Using the Generalized Complementary Principle of Evapotranspiration

AbstractAs drought involves diverse natural and human‐made processes in hydrologic cycles, it is necessary to track a process‐specific variable for efficient drought risk management. In this study, we employed a state‐of‐the‐art formulation of the generalized complementary relationship (GCR) to estimate terrestrial evapotranspiration (ET). The GCR ET estimates were used to assess historical droughts over the contiguous United States (CONUS) in relation to long‐term natural fluctuations. Results showed that the GCR provided strong performance in reproducing water balance ET estimates and correlations to the El Niño–Southern Oscillation, when compared to observation‐driven estimates and land surface models. For 1982‐2011, the GCR yielded better performance than land surface models even with estimated radiation inputs and no wind speed variations. The Standardized Evapotranspiration Deficit Index (SEDI) based on the GCR provided a consistent drought assessment with precipitation‐based drought identification and remotely sensed vegetation conditions. The SEDI seems to capture the heat wave‐driven flash drought together with water deficit‐driven droughts. In the CONUS, the La Niña‐like conditions were likely to trigger extensive vegetation droughts with extreme severity. This study found the three long‐term environmental factors that affect the general trend of ET deficits over the CONUS, which are the Atlantic Multidecadal Oscillation, the mean air temperature, and the Pacific Decadal Oscillation. Especially, the Atlantic Oscillation seems to be the most significant predictor that could explain the long‐term variation of vegetation droughts over the CONUS. This study highlights that the GCR‐based SEDI could be useful for monitoring and assessment of drought risks at a continental scale.

Multi-scale assessment of eco-hydrological resilience to drought in China over the last three decades

Understanding to what extent can terrestrial ecosystems maintain their structure and functions and recover after being hit by drought is critical for sustainable ecosystem management and drought mitigation practices. This study assesses multi-scale (i.e., at grid, climate type, land use, basin, province scales) eco-hydrological resilience to drought over China during the period of 1982–2015, based on Standard Evapotranspiration Deficit Index as well as satellite-retrieved evapotranspiration (ET) and net primary production (NPP). Over the last three decades, the ecosystem water use efficiency (eWUE) increased in most regions of China (especially in Northeast China and North China Plain) in the context of climate change. The western China showed a significant wetting trend with ascending ET, GPP and eWUE. The SEDI and ET showed significantly increasing tendencies but the ecosystem GPP and eWUE did not exhibit obvious responses to regional wetting in the middle and lower reaches of Yangtze River basin. Most terrestrial ecosystems in China were found overall resilient to drought except for mild temperature-fully humid-warm summer at the climate type scale, water type at the land use scale, Northwest Rivers at the basin scale as well as Ningxia, Qinghai, Shanghai and Hong Kong at the province scale. These findings would facilitate the identification of most drought-vulnerable regions for ecosystem management and taking reasonable adaptation measures (e.g., use of alternative water resources or reuse water, water conservation and smart irrigation) to ensure the sustainability of terrestrial ecosystems during the drought periods over China.

Impacts of Chinese Grain for Green program and climate change on vegetation in the Loess Plateau during 1982–2015

Remote sensing based vegetation index provides a practical method for the monitoring of vegetation dynamics at regional and global scales. Here, using a long-term remotely sensed normalized difference vegetation index (NDVI) dataset, we quantified the vegetation changes in the Loess Plateau (LP) over the last three decades (1982–2015), which includes the period before the Chinese“Grain for Green Program”(GGP) was launched (1982–1999), and the period after the GGP (1999–2015). The correlations between the NDVI and four climate related variables, i.e., precipitation, temperature, root-soil moisture (RSM), and a drought proxy-standardized evapotranspiration deficit index (SEDI), were also examined. The results indicated that, (i) the GGP strongly changed the vegetation in the LP. The growing-season mean NDVI (GSM-NDVI) and the annual mean NDVI (AM-NDVI) decreased slightly before the GGP launched in 1999, with slopes of −3.38×10−3 and−8.00×10−4year−1, respectively. However, they showed slight and significant (p<0.05) increases after the GGP, with slopes of 4.75×10−3 and 2.32×10−3year−1, respectively. (ii) Climate change (i.e., warming and drying) resulted in adverse effects on vegetation in the LP during the period before the GGP. However, the observed changes (i.e., wetting and reduced drought) exerted positive effects on the vegetation during the period after the GGP. (iii) Inter-annual variations of spatially averaged NDVI over the LP were primarily determined by RSM rather than any other climate related variables. In the southeastern LP, the inter-annual variation of GSM-NDVI was mainly determined by precipitation and SEDI, while the inter-annual variation of AM-NDVI was mainly caused by SEDI and RSM. Inter-annual variations of both GSM-NDVI and AM-NDVI were mainly determined by SEDI and RSM in the northwestern LP, and by temperature in the southwestern LP.

Global Assessment of the Standardized Evapotranspiration Deficit Index (SEDI) for Drought Analysis and Monitoring

This article developed and implemented a new methodology for calculating the standardized evapotranspiration deficit index (SEDI) globally based on the log-logistic distribution to fit the evaporation deficit (ED), the difference between actual evapotranspiration (ETa) and atmospheric evaporative demand (AED). Our findings demonstrate that, regardless of the AED dataset used, a log-logistic distribution most optimally fitted the ED time series. As such, in many regions across the terrestrial globe, the SEDI is insensitive to the AED method used for calculation, with the exception of winter months and boreal regions. The SEDI showed significant correlations ( p &lt; 0.05) with the standardized precipitation evapotranspiration index (SPEI) across a wide range of regions, particularly for short (&lt;3 month) SPEI time scales. This work provides a robust approach for calculating spatially and temporally comparable SEDI estimates, regardless of the climate region and land surface conditions, and it assesses the performance and the applicability of the SEDI to quantify drought severity across varying crop and natural vegetation areas.

Comparison of the Performance of Six Drought Indices in Characterizing Historical Drought for the Upper Blue Nile Basin, Ethiopia

The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration Deficit Index (ETDI), Soil Moisture Deficit Index (SMDI), Aggregate Drought Index (ADI), and Standardized Runoff-discharge Index (SRI), and evaluates their performance with respect to identifying historic drought events in the UBN basin. The indices were calculated using monthly time series of observed precipitation, average temperature, river discharge, and modeled evapotranspiration and soil moisture from 1970 to 2010. The Pearson’s correlation coefficients between the six drought indices were analyzed. SPI and SPEI at 3-month aggregate period showed high correlation with ETDI and SMDI (r &gt; 0.62), while SPI and SPEI at 12-month aggregate period correlate better with SRI. The performance of the six drought indices in identifying historic droughts: 1973–1974, 1983–1984, 1994–1995, and 2003–2004 was analyzed using data obtained from Emergency Events Database (EM-DAT) and previous studies. When drought onset dates indicated by the six drought indices are compared with that in the EM-DAT. SPI, and SPEI showed early onsets of drought events, except 2003–2004 drought for which the onset date was unavailable in EM-DAT. Similarly, ETDI, SMDI and SRI-3 showed early onset for two drought events and late onsets in one-drought event. In contrast, ADI showed late onsets for two drought events and early onset for one drought event. None of the six drought indices could individually identify the onsets of all the selected historic drought events; however, they may identify the onsets when combined by considering several input variables at different aggregate periods.

A drought index based on actual evapotranspiration from the Bouchet hypothesis

AbstractGlobal drought assessment has mainly depended on precipitation‐based drought indices that may also take into account potential evapotranspiration (ETp). In this study, we combined the actual evapotranspiration (ETa) estimated from the Bouchet hypothesis and the structure of the Standardized Precipitation‐Evapotranspiration Index to develop a fully ET‐based drought index, the Standardized Evapotranspiration Deficit Index (SEDI). We found that SEDI, without using precipitation data, produces results that are consistent with the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) for drought identification in the South‐Central United States. We also found a competitive performance of SEDI through comparisons between the Vegetation Health Index with SEDI, PDSI, and SPI. We suggest the high applicability of the SEDI based on the Bouchet hypothesis as an independent drought index for regions with strong land‐atmosphere coupling or as an alternative drought index to fully precipitation‐dependent indices for assessing agricultural droughts.

Spatio-temporal Analysis of Hydrological Drought at Catchment Scale Using a Spatially-distributed Hydrological Model

Lately, drought is more intense and much more severe around the globe, causing more deaths than other hazards in the past century. Drought can be characterized quantitatively for its spatial extent, intensity and duration by using drought indicators. Several indicators have been developed in order to characterize drought, being the most widespread the Standardized Precipitation Index (SPI). Nevertheless, due to its known limitations, other indicators have been proposed. In this paper, evaporation and runoff simulations of a basin were used to evaluate the variation and performance of different meteorological and hydrological drought indicators in identifying drought. Daily simulations of evaporation and runoff were computed by using a distributed hydrological model of a catchment located in the southeast of Mexico. After calibration of the hydrological model, we calculated at different time steps the drought indicators: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration Deficit Index (ETDI), Standardized Evapotranspiration Deficit Index (SEDI) and Standardized Runoff Index (SRI). Furthermore, the so-called Non-Contiguous Drought Analysis (NCDA) was carried out to compare the skill of each indicator to identify drought. Results show that meteorological drought indicators do not identify all drought events for the time steps of 1 and 3 months. For 3-, 6- and 9-month time steps, meteorological drought indicators tend to identify the onset with a lag. For long-time steps of 12 and 24, the use of agricultural and hydrological droughts indicators is recommended, since these indicators can identify prolonged drought periods. The results suggest that for a better monitoring of drought in a catchment, it is important the joint evaluation and the use of not only meteorological drought indicators but also hydrological and agricultural ones, in order to identify drought events and their spatio-temporal evolution.

Identification and simulation of space–time variability of past hydrological drought events in the Limpopo River basin, southern Africa

Abstract. Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979–2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring

Drought is one of the major natural hazards that bring about billions of dollars in loss to the farming community around the world each year. Drought is most often caused by a departure of precipitation from the normal amount, and agriculture is often the first sector to be affected by the onset of drought due to its dependence on water resources and soil moisture reserves during various stages of crop growth. Currently used drought indices like the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) have coarse spatial (7000–100,000 km 2) and temporal resolution (monthly). Hence, the distributed hydrologic model SWAT was used to simulate soil moisture and evapotranspiration from daily weather data at a high spatial resolution (16 km 2) using GIS. Using this simulated data the drought indices Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were developed based on weekly soil moisture deficit and evapotranspiration deficit, respectively. SMDI was computed at four different levels, using soil water available in the entire soil profile, then soil water available at the top 2 ft. (SMDI-2), 4 ft. (SMDI-4), and 6 ft. (SMDI-6). This was done because the potential of the crop to extract water from depths varies during different stages of the crop growth and also by crop type. ETDI and SMDI-2 had less auto-correlation lag, indicating that they could be used as good indicators of short-term drought. The developed drought indices showed high spatial variability (spatial standard deviation ∼1.00) in the study watersheds, primarily due to high spatial variability of precipitation. The wheat and sorghum crop yields were highly correlated ( r > 0.75) with the ETDI and SMDI's during the weeks of critical crop growth stages, indicating that the developed drought indices can be used for monitoring agricultural drought.