Standardized Precipitation Evapotranspiration Research Articles

Early crop yield prediction for agricultural drought monitoring using drought indices, remote sensing, and machine learning techniques

Abstract The unpredictability of crop yield due to severe weather events such as drought and extreme heat continues to be a key worry. The present study evaluated six meteorological and three Landsat satellite-based vegetation drought indices from 1986 to 2019 in the drought-prone-semi-arid Saurashtra region of Gujarat (India). Cotton and groundnut crop yield prediction models were developed using multiple linear regression (MLR), artificial neural network with MLP, and random forest (RF). The models performed crop yield estimation at two timescales, i.e., 75 days after sowing and 105 days after sowing. The standardized precipitation evapotranspiration index/reconnaissance drought index among meteorological drought indices, normalized difference vegetation anomaly index/vegetation condition index, and normalized difference water index anomaly were chosen as best highest correlations with crop yields. The RF-based models were found most efficient in predicting the cotton and groundnut yield of Saurashtra with R2 ranging from 0.77 to 0.92, Nash–Sutcliffe efficiency ranging from 71 to 90%, and root-mean-square error ranging from 80 to 133 kg/ha for cotton and 299 to 453 kg/ha for groundnut. This study demonstrated the method for making several decisions based on early crop yield prediction including timely drought mitigation measures.

Assessing Vulnerability and Population Exposed to Drought in Various Climatic Regions of Northeastern Iran

Abstract The motivations of this research are the continuation and intensification of drought effects on various socioeconomic sectors and the observation of few studies and no coordinated efforts to provide a compatible framework for drought risk management in different economic sectors and population groups of the study region. Present research was carried out to assess the vulnerability and population exposed to drought in Khorasan Razavi Province. Meteorological datasets for the years 1950–2020; drought indices including self-calibrating Palmer (scPDSI), standardized precipitation (SPI), and standardized precipitation evapotranspiration (SPEI); population and livestock density indicators; agricultural lands; water stress; and socioeconomic and infrastructural factors have been used. Results indicate that dry and wet periods were estimated to be more intense by SPEI in all studied stations; also, a significant difference was observed between the results of the SPI and SPEI indices in determining the long dry and wet periods. The highest variation between the occurrence of dry and wet periods was estimated using SPEI, which could be related to seasonal fluctuations of temperature and computational evapotranspiration. Although no significant correlation was observed between used indices to identify the number of wet months, a significant positive correlation exists between the numbers of dry months estimated by those. Drought risk analysis demonstrated that the central and southern parts of the province are exposed to very severe drought while the northern and northeastern parts of the area are more inclined to severe drought. The highest class of drought exposure is observed in the southern, central, and eastern regions of the province, so they represent the high-risk category of drought.

Influencia de ENSO en sequía agrícola identificada por evaluación SPEI en los Andes tropicales peruanos, valle del Mantaro

Agricultural drought is a serious threat for those locations where one of the most important economic activities is crop production, which occurrence has been rising due to climate change. In addition, different kinds of phenomena could exacerbate agricultural drought frequency, duration, and severity. For example, El Niño Southern Oscillation (ENSO), which mostly occurs in the tropical western and central pacific, directly affects the Peruvian territory. This study aims to understand ENSO's influence on agricultural drought in the Mantaro Valley, Peru since it is one of the most important agricultural lands in the country without clear scientific information linked to drought and ENSO events. For drought assessment using the Standardized Precipitation Evapotranspiration (SPEI) index and for ENSO events through a documentary and numerical analysis under Oceanic Niño Index (ONI) with information from several scientific recent papers to integrate information and formulate a clear event influence understanding. The results show that within Mantaro Valley along its four provinces and their six meteorological stations, 70% of agricultural drought events occurred when ENSO was present between 1990-2021. Also, the severity straight correlation percentage between both, ENSO and SPEI events is quite variable between 9.09%-70%. It is important to keep analyzing those stations with few data since it can provide a new scenario deportment and track new ENSO forecasting methods to rise adaptive capacity and guarantee national and international food security which has as an important supplier to the Mantaro Valley, Peru.

Temporal and Spatial Variability of Dryness Conditions in Kazakhstan during 1979–2021 Based on Reanalysis Data

The spatial and temporal variability of dryness conditions in the territory of Kazakhstan during the period 1979–2021 was investigated using monthly and hourly ERA5 reanalysis data on air temperature and precipitation as well as various aridity indices. A large part of the territory is characterized by the air temperature increase in summer and spring, as well as precipitation reduction, especially during the summer months. It was shown that the end of the 20th century (1979–2000) and the beginning of the 21st century (2001–2021) are characterized by different trends in air temperature and precipitation. All applied indices, i.e., the Palmer Drought Severity Index (PDSI), the Keetch–Byram Drought Index (KBDI), Standardized Precipitation (SPI) and Standardized Precipitation Evapotranspiration (SPEI), showed increased dryness in most parts of the territory of Kazakhstan. KBDI indicated an increased risk of wildfires, especially in the southwestern and northwestern regions. The hottest and driest areas are situated in the regions that are simultaneously affected by rising temperatures and reduced precipitation in spring and summer. The strongest increase in aridity and fire risk in the southwest and northwest is mainly due to reduced precipitation in the summer. Minimal risks of droughts occur in the northern and central regions, where conditions in the early 21st century became even less favorable for drought formation compared to the late 20th century (increased precipitation in both spring and summer and lower summer temperatures).

Projected dry/wet regimes in China using SPEI under four SSP‐RCPs based on statistically downscaled CMIP6 data

AbstractDry/wet conditions are one of the key constituents of climate change. The understanding of dry/wet variability is vital for production and water resources management. In this research, the temporal variations of 12‐month timescale standardized precipitation evapotranspiration (SPEI) over 2021–2100 under the SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5 scenarios in seven subregions and China's mainland were investigated over the baseline period of 1961–2000. The run theory was used to project the variations of dry/wet frequency, duration and severity at different levels during 1961–2000, 2021–2060 and 2061–2100 based on the estimated SPEI. The results showed that dry tendency would occur in northwest China. The linear trend for SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5 were −0.056, −0.031, 0.009 and −0.072 per decade, respectively. While wet tendency would occur in the other regions over 2021–2100. The mild, moderate and severe dry/wet duration and severity over 2021–2060 and 2061–2100 would gradually decrease. Except for northwest China and Qinghai‐Tibetan Plateau, the extreme drought duration and severity would increase in the other subregions, while the extreme wet duration and severity would increase in most regions of China. The drought frequency in north China would range from 0 to 14 times and be smaller than the other regions over 2021–2060 and 2060–2100. However, the wet frequency in south China would be larger than that in the other regions. The dry/wet frequency duration and severity for the SSP5‐8.5 scenario would be the largest among the four scenarios. The projected dry/wet conditions can provide useful information for future water resources management.

Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models

Droughts may inflict significant damage to agricultural and water supplies, resulting in substantial financial losses as well as the death of people and livestock. This study intends to anticipate droughts by studying the changes of an acceptable index using appropriate climatic factors. This study was divided into three phases, first being the determination of the Standardized Precipitation Evapotranspiration (SPEI) index for the Cholistan, Punjab, Pakistan area based on a dataset spanning 1980 to 2020. The indices are calculated at different monthly intervals which could to predict short-term periods for the Cholistan in Pakistan, we selected two distinctive time periods of one month (SPEI–1) and three months (SPEI–3). The second phase involved dividing the data into three sample sizes, which were used for training data from 1980 to 2010, testing data from 2011 to 2015 and validation data from 2016 to 2020. The utilization of the random forest (RF) algorithm to train and evaluate the data using a variety of climate variables e.g. potential evapotranspiration, rainfall, vapor pressure cloud cover, and mean, minimum and maximum, temperature. The final phase was to analyze the performance of the model based on statistical metrics and drought classes. Based on these considerations, statistical measures, such as the Coefficient of Determination (R2) and the Root Mean Square Error (RMSE) approach, were used to evaluate the performance of the test group throughout the testing period. The model's performance revealed the satisfactory results with R2 values of 0.80 and 0.78, for SPEI–1 and SPEI–3 situations, respectively. Following the data analysis, it was discovered that the validation period had a receiving operating curve and area under the Curve (ROC-AUC) of 0.87 for the SPEI–1 case and 0.85 for the SPEI–3 case. In this context, the results indicate that the SPEI may be useful as a prediction tool for drought prediction and the performances the RF model was suitable for both timescales. However, a more rigorous analysis with a larger dataset or a combination of datasets from different areas might be more beneficial for generalization over more extended time periods provide additional insights.

Development of an assessment framework for the proposed Multi-Scalar Seasonally Amalgamated Regional Standardized Precipitation Evapotranspiration Index (MSARSPEI) for regional drought classifications in global warming context

Drought hazard is one of the main consequences of global warming and climate change. Unlike other natural disasters, drought has complex climatic features. Therefore, accurate drought monitoring is a challenging task. This paper proposes a framework for assessing drought classifications at the regional level. The proposed framework provides a new drought monitoring indicator called Multi-Scalar Seasonally Amalgamated Regional Standardized Precipitation Evapotranspiration Index (MSARSPEI). MSARSPEI is an amalgam of the Standardized Precipitation Evapotranspiration (SPEI) (Vicente-Serrano et al., 2010) and Regionally Improved Weighted Standardized Drought Index (RIWSDI) (Jiang et al., 2020). In the proposed framework, the Boruta algorithm of feature selection is configured to ensemble monthly time series data of evaporation in various meteorological stations located in specific regions. Further, the framework suggests the standardization of the Cumulative Distribution Function (CDF) of K-Component Gaussian (K-CG) mixture distribution function for obtaining MSARSPEI data. The application of the proposed framework is based on seven different regions of Pakistan. For comparative analysis, this paper compared the performance of MSARSPE with SPEI using Pearson correlation. Outcomes associated with this research show that the proposed regional drought index has a strong correlation with the competing indicator in various time scales. In addition, the study assessed the spatial extent of various drought classifications under MSARSPEI. In summation, this research concludes that the choice of the MSARSPEI is rationally valid and more appropriate for the regional assessment of drought under the global warming scenario.

Trends in drought occurrence and severity at mid-latitude European stations (1951\u20132015) estimated using standardized precipitation (SPI) and precipitation and evapotranspiration (SPEI) indices

One of the negative consequences of climate change is the also increase in the severity, frequency and length of droughts appearing in Europe. The effects of meteorological drought are often substantial, not only for the natural environment but also for humans. Hence, the main purpose of this research was to determine the trends in the severity and occurrence of droughts in Europe during the period 1951–2015 using the standardized precipitation index and the standardized precipitation and evapotranspiration index (SPEI). For six European sites located in mid latitudes, the number of dry months was determined and the trend of their occurrence was examined. Moreover, for the summer months in which the indicators fell below 0, the trend related to the severity of the drought was determined for each site. Despite the absence of a statistically significant trend of an increase in the occurrence of dry months in general, an increase in the severity of droughts occurring in summer was observed for the SPEI over a 6-month scale for all the investigated stations. The highest number of dry months since the 1970s appeared during the last 5 years of analysis.

Weather shocks and migration intentions in Western Africa: insights from a multilevel analysis

Abstract We use a multilevel approach to investigate whether a general and robust relationship between weather shocks and (internal and international) migration intentions can be uncovered in Western African countries. We combine individual survey data with measures of localized weather shocks for 13 countries over the 2008–2016 period. A meta-analysis on results from about 51,000 regressions is conducted to identify the specification of weather anomalies that maximizes the goodness of fit of our empirical model. We then use this best specification to document heterogeneous mobility responses to weather shocks. We find that variability in Standardized Precipitation Evapotranspiration Index/rainfall is associated with changing intentions to move locally or internationally in a few countries only. However, the significance, sign and magnitude of the effect are far from being robust and consistent across countries. These differences might be due to imperfections in the data or to differences in long-term climate conditions and adaptation capabilities. They may also suggest that credit constraints are internalized differently in different settings, or that moving internally is not a relevant option as weather conditions are spatially correlated while moving abroad is an option of last resort. Although our multilevel approach allows us to connect migration intentions with the timing and spatial dimension of weather shocks, identifying a common specification that governs weather-driven mobility decisions is a very difficult, if not impossible, task, even for countries belonging to the same region. Our findings also call for extreme caution before generalizing results from specific case studies.

Drought Trends in the Polish Carpathian Mts. in the Years 1991–2020

Mountains are highly sensitive to the effects of climate change, including extreme short- and long-term weather phenomena. Therefore, in spite of relatively high annual precipitation totals, mountains might become endangered by droughts. The paper presents drought trends in the Polish Carpathians located in Central Europe. Data from the period 1991–2020 from 12 meteorological stations located in various vertical climate zones of the mountains were used to define drought conditions using the following indices: Standardized Precipitation (SPI), Standardized Precipitation Evapotranspiration (SPEI), Relative Precipitation (RPI) and Sielianinov. Additionally, four forest drought indices were used in order to estimate the impact of drought on beech as a typical Carpathian tree species, i.e., the Ellenberg (EQ), Forestry Aridity (FAI), Mayr Tetratherm (MT) and De Martonne Aridity (AI) indices. Statistically significant but weak trends were obtained for the 6-month SPI for four stations (indicating an increase in seasonal to mid-term precipitation), for the 1-month SPEI for three stations, for the 3-month SPEI for four stations, and for MT for all stations (indicating an increase in drought intensity). The analysis of dry month frequency according to particular indices shows that at most of the stations during the last decade of the study period, the frequency of dry months was much higher than in previous decades, especially in the cold half-year. Two zones of the Polish Carpathians are the most prone to drought occurrence: the peak zone due to the shift in climatic vertical zones triggered by the air temperature increase, and the forelands and foothills, together with basins located about 200–400 m a.s.l., where the mean annual air temperature is the highest in all the vertical profile, the annual sums of precipitation are very diversified, and the conditions for beech are already unfavorable.

Spatial and Statistical Variability Analyses of Satellite-Based Climatic Data in Mereb-Gash Basin

Global reanalysis products are extensively used for hydrologic applications in sparse data regions. The establishment of some inputs for hydrologic modelling from global reanalysis requires prior scrutiny and assessment. Thus, the present study attempts to exploit Climate Forecast System Reanalysis datasets for the Mereb-Gash river basin in Eritrea, with the objective of preparing input data for future hydrological modelling efforts as well as climate characterization. The research activities include statistical analysis of reanalysis datasets, computation of potential evapotranspiration and drought indices using different approaches. Results show that there were predominantly significant monotonic trends in most of the data; precipitation and relative humidity exhibited significant decreasing trends, whereas increasing trends were detected in temperature and potential evapotranspiration. Three potential evapotranspiration estimation methods were employed out of which the Thornthwaite method showed a considerable dependence on elevation of a station. In most cases, Penman-Monteith provides higher estimates than Hargreaves and Thornthwaite equations. Besides, drought indices based on standardized precipitation evapotranspiration and rainfall anomaly demonstrate the presence of persistent dry conditions over the period 2000 to 2013 and predominantly humid conditions from 1979 through the end of 1990s. The findings of this study imply that presence of significant trends in most of the climatic variables and persistent drought conditions in recent years may ultimately be associated to human and climate influences on the environment. Thus, concerted and effective countermeasures should be executed in the study area to reverse the existing ecological imbalances.

Variability analysis of dry spells for improving agribusiness management in Lesotho.

In sub-Saharan Africa, rain-fed agriculture remains one of the major sources of food, employment for low-skilled and rural community members and income for both commercial and subsistence farmers. Understanding problems posed by dry spells variability on agribusinesses is one of the critical challenges of our time. This study characterised dry spells in Lesotho for the improvement of agribusinesses using standardised precipitation (SPI) and standardised precipitation evapotranspiration (SPEI) drought indices. This study was found imperative mainly because Basotho’s livelihood is dependent on rain-fed agriculture and this study further aimed to provide an early warning system that could be used for policymaking against adverse effects of drought events in the area. A 30-year-long rainfall and average monthly temperature data were collected from 10 administrative districts of Lesotho and used to compute SPI and SPEI values. Three dry spell parameters – frequency, duration and intensity – were derived from SPI and SPEI time series. The main findings of this study were that all candidate stations experienced similar dry spell conditions in both duration and frequency and all the selected stations throughout the country experienced extreme drought intensity levels from both SPI and SPEI. Two of the 10 districts showed a statistically significant decrease in Mann Kendal’s trend from both SPI and SPEI time series. This implied that farmers must be encouraged to grow drought-resistant cultivars in order to sustain and support agribusiness in Lesotho. Rangeland policies and legislations must be enforced for livestock production, especially in the periods when extreme dry spell events are expected. The government and all other relevant stakeholders are, therefore, encouraged to devise means to support farmers with irrigation systems to maintain agricultural production, revenue and employees’ employment status.

Exploring standardized precipitation evapotranspiration index for drought assessment in Bangladesh.

Drought is a critical issue, and it has a pressing, negative impact on agriculture, ecosystems, livelihoods, food security, and sustainability. The problem has been studied globally, but its regional or even local dimension is sometimes overlooked. Local-level drought assessment is necessary for developing adaptation and mitigation strategies for that particular region. Keeping this in understanding, an attempt was made to create a detailed assessment of drought characteristics at the local scale in Bangladesh. Standardized precipitation evapotranspiration (SPEI) is a new drought index that mainly considers the rainfall and evapotranspiration data set. Globally, SPEI has become a useful drought index, but its local scale application is not common. SPEIbase (0.5° grid data) for 110years (1901-2011) was utilized to overcome the lack of long-term climate data in Bangladesh. Available weather data (1955-2011) from Bangladesh Meteorology Department (BMD) were analyzed to calculate SPEIweather station using the SPEI calculator. The drivers for climate change-induced droughts were characterized by residual temperature and residual rainfall data from different BMD stations. Grid data (SPEIbase) of 26 stations of BMD were used for drought mapping. The findings revealed that the frequency and intensity of drought are higher in the northwestern part of the country which makes it vulnerable to both extreme and severe droughts. Based on the results, the SPEI-based drought intensity and frequency analyses were carried out, emphasizing Rangpur (northwest region) as a hot spot, to get an insight of drought assessment in Bangladesh. The findings of this study revealed that SPEI could be a valuable tool to understand the evolution and evaluation of the drought induced by climate change in the country. The study also justified the immediate need for drought risk reduction strategies that should lead to relevant policy formulations and agricultural innovations for developing drought adaptation, mitigation, and resilience mechanisms in Bangladesh.

Effects of Recent Minimum Temperature and Water Deficit Increases on Pinus pinaster Radial Growth and Wood Density in Southern Portugal

Western Iberia has recently shown increasing frequency of drought conditions coupled with heatwave events, leading to exacerbated limiting climatic conditions for plant growth. It is not clear to what extent wood growth and density of agroforestry species have suffered from such changes or recent extreme climate events. To address this question, tree-ring width and density chronologies were built for a Pinus pinaster stand in southern Portugal and correlated with climate variables, including the minimum, mean and maximum temperatures and the number of cold days. Monthly and maximum daily precipitations were also analyzed as well as dry spells. The drought effect was assessed using the standardized precipitation-evapotranspiration (SPEI) multi-scalar drought index, between 1 to 24-months. The climate-growth/density relationships were evaluated for the period 1958-2011. We show that both wood radial growth and density highly benefit from the strong decay of cold days and the increase of minimum temperature. Yet the benefits are hindered by long-term water deficit, which results in different levels of impact on wood radial growth and density. Despite of the intensification of long-term water deficit, tree-ring width appears to benefit from the minimum temperature increase, whereas the effects of long-term droughts significantly prevail on tree-ring density. Our results further highlight the dependency of the species on deep water sources after the juvenile stage. The impact of climate changes on long-term droughts and their repercussion on the shallow groundwater table and P. pinaster’s vulnerability are also discussed. This work provides relevant information for forest management in the semi-arid area of the Alentejo region of Portugal. It should ease the elaboration of mitigation strategies to assure P. pinaster’s production capacity and quality in response to more arid conditions in the near future in the region.

Erratum for “Assessment of the Drought Hazard in the Tiber River Basin in Central Italy and a Comparison of New and Commonly Used Meteorological Indicators” by Pamela Maccioni, Maggie Kossida, Luca Brocca, and Tommaso Moramarco

During composition, two errors were inadvertently introduced to the final published paper. The corrections are given as follows: 1. In the Abstract, the abbreviation of standardized effective precipitation evapotranspiration index should be SP* ETI, not SPETI. The correct abbreviation, SP* ETI, is used in the rest of the paper. 2. In the section, “Standardized Effective Precipitation Evapotranspiration Index,” the first sentence of the third paragraph should be corrected as, “To estimate P , two different cases are identified (SEI 2001), as follows: (1) EP > ET0; in this case the effective precipitation is enough to satisfy the vegetation water supply, and P 1⁄4 P − ET0; and (2) EP ET0 was provided as P 1⁄4 P − EP; it should be changed to P 1⁄4 P − ET0. ASCE regrets these errors.