Percent Of Normal Precipitation Research Articles

Comparative assessment of drought indices for evaluating drought patterns in Peninsular Malaysia

Abstract Drought has been the main environmental issue in Peninsular Malaysia. Hence, this study undertook a thorough evaluation of drought assessment methodologies and focused on the temporal analysis of multiple drought indices, namely, the standardised precipitation index (SPI), deciles index (DI), percent of normal precipitation index (PNPI), rainfall anomaly index (RAI) and Z-score index (ZSI) – across timescales of one-, six- and 12-month durations. This assessment incorporates the average moving range (AMR), Mann–Kendall (MK) test and Sen's slope estimator in temporal analysis and the results showed that shorter timescales lead to higher fluctuation in AMR values, indicating short-term droughts are best assessed using drought indices of shorter timescale. It was found that most drought indices exhibited a similar trend and trend magnitude in all timescales. SPI is utilised as the standard model for the accuracy evaluation of drought indices using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The results showed that ZSI has the highest accuracy of all indices. The novelty of this study lies in evaluating the accuracy and temporal characteristics of precipitation-based drought indices in tropical areas, particularly in Peninsular Malaysia.

Effect of Various Types of ENSO Events on Moisture Conditions in the Humid and Subhumid Tropics

Moisture anomaly conditions within humid and subhumid tropics that are associated with different types of El Niño and La Niña phenomena are described and analyzed with a focus on their spatial distribution and seasonal variability. Five dryness indices (Keetch–Byram Drought Index, Weighted Anomaly Standardized Precipitation Index, Standardized Precipitation Index, Palmer Drought Severity Index, and Percent of Normal Precipitation) were derived from ECMWF (European Centre for Medium-Range Weather Forecasts) fifth generation reanalysis (ERA5) reanalysis and University Corporation for Atmospheric Research (UCAR) datasets for the period from 1979 to 2019. Cross-correlation analysis was used to evaluate the relationships between the El Niño Southern Oscillation (ENSO) and selected dryness indices. To describe the seasonal variability of the ENSO–surface moisture relationships, the composite maps of dryness indices in different seasons were analyzed. The results showed a significant heterogeneity of the ENSO-induced moisture anomaly conditions both within and across various geographical regions. Four main areas in humid and subhumid tropics with the maximum effects of El Niño/La Niña events on the surface moisture conditions were found: Southeast Asia and Australia, Eastern and South Africa, Northeastern and Eastern South America, and Central America. It was shown that the effects of La Niña were usually opposite to those of El Niño, while the responses to the two types of El Niño differed mostly in the moisture anomaly intensity and its spatial patterns.

Quantification of drought severity change in Ethiopia during 1952–2017

Drought is considered as a frequent environmental disaster that persists long enough to adversely influence economic and social development for the last few decades, particularly in Ethiopia. Here, we examined the occurrence of drought severity change in Ethiopia using standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), China Z Index (CZI) and percent of normal precipitation (PNP). Mann Kendal and Sen’s method tests also used to compute trends and magnitudes of drought occurrences. The years 1953, 1961–1964, 1972–1976, 1984–1987, 2002–2004 and 2011–2014 were recorded as the most intense drought episodes ranging from − 1.58 to − 4.31. With some exceptions, the years 1984, 1986, 2002 and 2014/15 were the direst extreme drought occurrence across all locations. The interpolated spatial extent of drought frequency was highest in central, north and southern regions of the country, respectively. More extreme and severe droughts are identified from SPI and SPEI time series than CZI and PNP at many stations across the domain. In 3-month time scales, severe/extreme drought incidences are intra-annual and 12- and 24-month time scales are inter-annual. SPI and SPEI have stronger correlation than SPI and CZI at all timescales. This kind of inventory drought characterization can be used as a basis to quantitatively prioritize specific intervention at the regional level in responding to drought impacts due to climate change with available resources. By large, it will help to foster a vital shift in the way drought is perceived and coped in the region, taking into account the country’s economic, social and environmental context.

Variability of Indian summer monsoon droughts in CMIP5 climate models

Variability of Indian summer monsoon droughts is investigated by computing all-India drought indices namely Percent of Normal Precipitation, Standardized Precipitation Index and percentage area of India under moderate and severe drought conditions. Observations for recent decades, post 1960, exhibit declining trend in monsoon rainfall with frequent occurrence and intensification of droughts along with an increase in percentage of area under moderate and severe drought conditions, in association with variations in sea surface temperature (SST). Historical simulations from CMIP5 models suggest that two models, ACCESS1.0 and INMCM4, could well simulate monsoon rainfall variability, particularly the frequent occurrence of droughts and spatial variability of rainfall during drought years in recent historical period (1961–2005). Future projections of all-India drought indices from these two models indicate frequent droughts during near and mid future (2010–2069) with respect to the recent historical period. Intensification of severe droughts for near and mid future are suggested to be more pronounced over north-central India. The reduction in rainfall in the near and mid future is dynamically consistent with a westward shift in large-scale monsoon circulation, particularly the monsoon trough over South Asia. Interestingly, future projections of monsoon teleconnections indicate a weakening (strengthening) of in-phase (out-of-phase) relationship of all-India drought intensity with the equatorial eastern Pacific and the Indian Ocean (western Pacific) SST. Whereas, a strengthening of in-phase relationship between percentage of area under drought conditions and the equatorial eastern Pacific SST is projected for near and mid future with respect to the recent historical period. These drought features are consistent in both the models.

Development of an annual drought classification system based on drought severity indexes.

In order to characterize the occurrence and intensity of droughts in the Doce River Basin, as well as to develop a system for its classification, four different drought indexes were evaluated: Percent of Normal Precipitation (PNP), Deciles Method (DM), Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI). The indices were calculated annually, based on precipitation data from 89 rainfall stations of the Brazilian National Water Agency (ANA). Nine analysis units (AUs) were determined in the basin and the Thiessen Polygons method was used to obtain the average precipitation in the respective drainage areas. The indices were calculated for each AU and then related to the drought intensity classes. An overall classification of the indices was proposed for the drought classification system for a 30-year base period, from 1985 to 2015. The most critical hydrological years of the Doce River Basin in relation to the drought were 1994/1995, 2000/2001 and 2014/2015, the latter being the most critical of the last 30 years. The results show that the annual drought classification system proved to be efficient in the identification of events, allowing to verify that the Doce River Basin presents a severe climatic drought condition, on average, every seven years.

Searching for the optimal drought index and timescale combination to detect drought: a case study from the lower Jinsha River basin, China

Abstract. Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, the comparison of index-identified events with droughts at different levels of the complete system, including soil humidity or river discharges, relies typically on model simulations of the latter, entailing potentially significant uncertainties. The present study explores the potential of using precipitation-based indices to reproduce observed droughts in the lower part of the Jinsha River basin (JRB), proposing an innovative approach for a catchment-wide drought detection and characterization. Two indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Indicator (ODI), have been defined. These indicators aim at identifying and characterizing drought events on the basin scale, using results from four meteorological drought indices (standardized precipitation index, SPI; rainfall anomaly index, RAI; percent of normal precipitation, PN; deciles, DEC) calculated at different locations of the basin and for different timescales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River basin in China, a region prone to frequent and severe droughts. Historical drought events that occurred from 1960 to 2014 have been compiled and cataloged from different sources, in a challenging process. The analysis of the indicators shows a good agreement with the recorded historical drought events on the basin scale. It has been found that the timescale that best reproduces observed events across all the indices is the 6-month timescale.

Spatial and temporal drought analysis in the Krishna river basin of Maharashtra, India

AbstractDroughts can be distinguished by three vital characteristics—spatial coverage, intensity, and duration. The objective of the present study was to study the temporal and spatial variation of drought incidences by using the Standardized Precipitation Index (SPI) and Percent of Normal Precipitation (PNP) at multiple time scales; computed using monthly precipitation data (1960–2012) in the study area of 59 rain gauge stations. Drought climatology based on these drought indices (PNP and SPI) has been studied for finding out their suitability for drought monitoring over Krishna basin in Maharashtra. Study results indicate that at dry and wet conditions, the SPI performs better than PNP in monitoring drought at multiple time scales. However, SPI-1 fails to recognize drought conditions in pre-monsoon and post-monsoon months. The spatially interpolated droughts maps are prepared which displays the variation of drought severity across the study area. The ranking of stations has been done as per drought seve...

Trend Analysis of Drought Events Over Upper Krishna Basin in Maharashtra

Drought is a significant natural disaster which leads to food, fodder and water shortages along with destruction of vital ecological system. Drought is acknowledged as a phenomenon associated with scarcity of water due to reduction in the amount of precipitation over an extended period of time, usually a season, a year or more in length. Droughts are frequently occurring in Upper Krishna basin in Maharashtra where about 80 percent of agriculture land is rain fed. Also this region is witnessing rapid urbanization due to industrial growth where thirst for water for drinking as well as industrial use is demanding. The study of drought trends is extremely important as it is related with food security and management of scarce water resource, which becomes critical in case of drought events. In this work, the drought trend of Standardized precipitation index (SPI) at 1-, 6-, 12-, 24- and 48- month time scales, Percent of Normal Precipitation (PNP) at Annual and Water-Year time scales and Seasonal rainfall (winter, pre-monsoon, monsoon and post monsoon time scales) are computed using long time series (1960-2012) of monthly precipitation data at 59 stations in the study area. The statistical significance at 95% confidence level as per Mann-Kendall and Sen's slope estimator are used for drought trend analysis over the Upper Krishna basin in Maharashtra. The PNP drought trend analysis at both annual and water-year time scale is able to detect significant trend at only 5 stations out of all rain gauge stations, SPI based drought trend analysis is found to be more sensitive to multiple time scales. As the SPI-1 time scale is able to detect significant trend at only 4 stations, number of stations having significant trend increases as the SPI time scale increases up to SPI-48 at 50 stations. Drought trend of Seasonal rainfall time series vary as per the classes. Pre-monsoon time scale detects significant negative trend at 41 stations with no significant positive trend at any of the stations. Monsoon time scale detects only 2 positive and 1 negative significant trends at total stations. Post-monsoon time scale is not able to detect any significant trend at all stations. The results indicate that, there is negative trend of pre-monsoon rainfall at over 63 percent of area. SPI- 48 time scale is able to detect significant trend at over 84 percent of area. This analysis may help to solve problems associated with floods, droughts and allocation of water for agriculture, industry, hydro-power generation, domestic and industrial use.

Usporedba različitih metoda za ocjenu suše na području kontinentalne Hrvatske

Drought is an extreme hydrological event that causes great economic and environmental damage. Various methods are used for the identification and quantification of drought. The analysis of five drought identification methods was conducted for continental Croatia on 15 weather stations in the period from 1981 to 2011: standardised precipitation index, deciles index, percent of normal precipitation, rainfall anomaly index, and threshold level method. Results have revealed that each of these methods has its specific features but that all are applicable for the area under study. There is a significant correlation between the standard precipitation index and the deciles index, rainfall anomaly index, and percent of normal.

Spatial Patterns and Temporal Variability of Drought in Beijing-Tianjin-Hebei Metropolitan Areas in China

Drought identification and assessment are essential for regional water resources management. In this paper, the spatiotemporal characteristics of drought were evaluated based on monthly precipitation data from 33 synoptic stations during the period of 1960–2010. The percent of normal precipitation was applied to illustrate the driest years in Beijing-Tianjin-Hebei metropolitan areas (BTHMA) (1965, 1997, and 2002). The modified Reconnaissance Drought Index (RDI) was applied to capture the drought patterns and to estimate the drought severity at 33 meteorological stations. Agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) were used to identify three different drought subregions R1, R2, and R3 based on the monthly precipitation values in BTHMA, which is located in southeast, north, and south of BTHMA, respectively. The year 1965 was the driest and 1964 was the wettest during the observed period. The characteristics of drought were analyzed in terms of the temporal evolution of the RDI-12 values and the frequency of drought for the three identified regions. The percentage of years characterized by drought was 13.73% for R1, 16.50% for R2, and 15.53% for R3. 66.91% of drought belongs to the near normal drought category. The obtained results can aid to improve water resources management in the area.

Spatiotemporal characteristics of drought in Serbia

Summary The evaluation of spatiotemporal characteristics of drought was based on monthly precipitation data from 29 synoptic stations for the period of 1948–2012. The percent of normal precipitation was applied to illustrate the driest years in Serbia (1990, 2000, and 2011). The Standardized Precipitation Index (SPI) and S-mode principal component analysis (PCA) were used to capture the drought patterns. Agglomerative hierarchical cluster analysis was applied to identify three different drought sub-regions: (1) region R1 includes the north and the northeast part of Serbia; (2) region R2 includes the western part of Central Serbia and southwestern part of Serbia; and (3) region R3 includes central, east, south and southeast part of Serbia. The R2 had the monthly precipitation values above average, while R1 and R3 had the precipitation values under average of Serbia. The year 2000 was the driest and 1955 was the wettest during the observed period. The characteristics of drought were analyzed in terms of the temporal evolution of the SPI-12 values and the frequency of drought for the three identified regions. The percentage of years characterized by drought was 44.62% for R1, 50.77% for R2 and 46.15% for R3. Approximately 70% of the frequency of drought belongs to the near normal drought category.

District-wide drought climatology of the southwest monsoon season over India based on standardized precipitation index (SPI)

District-wide drought climatology over India for the southwest monsoon season (June–September) has been examined using two simple drought indices; Percent of Normal Precipitation (PNP) and Standardized Precipitation Index (SPI). The season drought indices were computed using long times series (1901–2003) of southwest monsoon season rainfall data of 458 districts over the country. Identification of all India (nation-wide) drought incidences using both PNP and SPI yielded nearly similar results. However, the district-wide climatology based on PNP was biased by the aridity of the region. Whereas district-wide drought climatology based on SPI was not biased by aridity. This study shows that SPI is a better drought index than PNP for the district-wide drought monitoring over the country. SPI is also suitable for examining break and active events in the southwest monsoon rainfall over the country. The trend analysis of district-wide season (June–September) SPI series showed significant negative trends over several districts from Chattisgarh, Bihar, Kerala, Jharkhand, Assam and Meghalaya, Uttaranchal, east Madhya Pradesh, Vidarbha etc., Whereas significant positive trends in the SPI series were observed over several districts from west Uttar Pradesh, west Madhya Pradesh, South & north Interior Karnataka, Konkan and Goa, Madhya Maharashtra, Tamil Nadu, East Uttar Pradesh, Punjab, Gujarat etc.

Assessing indicators of agricultural drought impacts on spring wheat yield and quality on the Canadian prairies

Drought is one of the costliest weather related natural hazards in the world. Traditionally, drought has been monitored using drought indices such as the “ percent of normal precipitation” to provide policy makers with information on drought extent and severity so that timely intervention measures can be taken. This study was conducted to identify drought indices that strongly correlated with spring wheat yield and quality. Detailed crop and weather data were collected from a series of wheat experiments across Saskatchewan and Manitoba, providing a diverse range of wheat growing environments. The data collected from 2003 to 2006 provided 15 site-years of data, which were used to derive drought indices in four categories: (i) water supply, (ii) water demand, (iii) water balance and (iv) water use. The drought indices were accumulated either over selected periods of the crop growing season including 1-month, 2-month, 3-month and 4-month (May–August) and/or specific wheat growth periods i.e., from planting to anthesis, anthesis to maturity and planting to maturity. Drought indices explained from 27% to 74% ( P < 0.05) of the variation in wheat grain yield and four different wheat bread-making quality parameters for two different wheat genotypes (AC Barrie and Superb). The drought index category most highly correlated to the greatest number of wheat characteristics was water demand, followed by water balance, water use and water supply. These results imply that water demand (evapotranspiration, ET) and water balance provide the most accurate assessment of drought impacts on spring wheat yield and quality on the Canadian prairies. Consequently, water demand and water balance indices would be more useful in assessing agricultural drought than the water supply indices frequently used for meteorological drought. The Hargreaves et al. method of estimating ET produced indices with correlation coefficients similar to those of the more complex modified Penman–Monteith method. Drought indices accumulated from planting to anthesis were slightly superior to those accumulated over the entire growing season, but highly superior to those accumulated from anthesis to maturity. Based on these results it would be possible to generate preliminary estimates of drought impacts on spring wheat yield and quality by mid-season with some confidence. This could be very useful in regards to providing policy makers and grain merchants with early warning information to plan and prepare for potential drought conditions.

Developing Objective Operational Definitions for Monitoring Drought

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

A Review of Twentieth-Century Drought Indices Used in the United States

The monitoring and analysis of drought have long suffered from the lack of an adequate definition of the phenomenon. As a result, drought indices have slowly evolved during the last two centuries from simplistic approaches based on some measure of rainfall deficiency, to more complex problem-specific models. Indices developed in the late nineteenth and early twentieth century included such measures as percent of normal precipitation over some interval, consecutive days with rain below a given threshold, formulae involving a combination of temperature and precipitation, and models factoring in precipitation deficits over consecutive days. The incorporation of evapotranspiration as a measure of water demand by Thornthwaite led to the landmark development in 1965 by Palmer of a water budget-based drought index that is still widely used. Drought indices developed since the 1960s include the Surface Water Supply Index, which supplements the Palmer Index by integrating snowpack, reservoir storage, streamflow, a...