Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.     

Spatial autocorrelation analysis of extreme precipitation in Iran

Spatial variations in extreme precipitation events make hydrological, climatological, social, environmental and agricultural effects on a country. This study presents the spatiotemporal autocorrelation analysis of extreme precipitation events over Iran using gridded data on daily precipitation for the period 1961–2010. The 95th percentile is considered as extreme precipitation factor. The spatial autocorrelation of extreme precipitation is examined by three commonly used spatial autocorrelation statistics, the G _i statistic index, Moran’s I global index, and Local Moran’s I (LISA) index, at the 95 and 99% significant confidence level. The results showed a strong significant spatial autocorrelation for extreme precipitation events with the highest Moran’s I value in January. The positive significant autocorrelation of extreme precipitation is observed over the southern parts of the Caspian Sea and Zagros Mountains ranges, while the negative significant autocorrelation is observed over the central and eastern parts of country. In spring and summer the positive autocorrelation cores displace from the Zagros Mountains ranges to the northwestern and southeastern parts.     

Streamflow drought severity analysis by percent of normal index (PNI) in northwest Iran

The streamflow drought is the most important type of drought due to the high dependence of many activities on surface water resources. The streamflow drought severity was identified by the percent of normal index (PNI) in the western basins of the Lake Urmia located in northwest Iran. The streamflow records were obtained from 14 hydrometric stations for the period October 1975–September 2009. The temporal trends of the streamflow drought severity were detected by the parametric Student’s t test and the nonparametric Mann–Kendall and Sen’s tests. The worst streamflow droughts at almost all the stations occurred in 1999–2000 and 2000–2001. The streamflow drought severity based on the PNI increased during the last 34 years. The results also indicated that the temporal dependency of time series had a dominant role in detecting trend by the parametric Student’s t test.     

Streamflow trends and climate linkages in the Zagros Mountains,Iran

This paper examines trends in streamflow and their links with local climate in the Karkheh River and its major tributaries, which originate from the Zagros Mountains, Iran. Streamflow records from five mainstream stations for the period 1961–2001 were used to examine trends in a number of streamflow variables. The studied variables were mean annual and monthly flows, 1 and 7 days maximum and minimum flows, timing of the 1-day maxima and minima, and the number and duration of high and low flow pulses. Similarly, the precipitation and temperature data from seven climate stations for the period from 1950s to 2003 were used to examine trends in climatic variables and their correlation with the streamflow. The Spearman Rank test was used for the detection of trends and the correlation analysis was based on the Pearson method. The results reveal a number of significant trends in streamflow variables both increasing (e.g. December flows) and decreasing (e.g. May flows) for all stations. However, some trends were not spatially uniform. For example, decline in low flow characteristics were more significant in the upper parts of the basin, whereas increasing trends in floods and winter flows were noteworthy in the middle parts of the basin. Most of these trends could be attributed to precipitation changes. The results show that the decline in April and May precipitation causes the decline in the low flows while the increase in winter (particularly March) precipitation coupled with temperature changes lead to increase in the flood regime. The observed trends at the Jelogir station on the Karkheh River reflect the combined effect of the upstream catchments. The significant trends observed in a number of streamflow variables at Jelogir, 1-day maximum, December flow and low pulse count and duration, point to the changes in hydrological regime of the entire Karkheh River system and are attributed to the changes in climatic variables.     

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value?>?0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value?>?0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, ?0.4, and 0.4 mm year^?1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year^?1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.     

Watershed-wide trend analysis of temperature characteristics in Karun-Dez watershed, southwestern Iran

Trend estimation of climatic characteristics for a watershed is required to determine developing compatible strategies related to design, development, and management of water resources. In this study, the trends of the annual maximum (T _max), minimum (T _min), and mean (T _mean) air temperature; temperature anomaly (T _anomaly); and diurnal temperature range (DTR) time series at 13 meteorological stations located in the Karun-Dez watershed were analyzed using the Mann–Kendall and linear regression trend tests. The pre-whitening method was used to eliminate the influence of serial correlation on the Mann–Kendall test. The result showed increasing trends in the T _min, T _mean, and T _anomaly series at the majority of stations and decreasing trend in the T _max and DTR series. A geographical analysis of the trends revealed a broad warming trend in most of the watershed, and the cooling trends were observed only in the southern parts. Furthermore, the geographical pattern of the trends in the T _mean and T _anomaly series was similar, and the T _max data did not show any dominant trend for the whole watershed. This study provides temperature change scenarios that may be used for the design of future water resource projects in the watershed.     

中美半干旱区长期地表通量序列的构建及检验

基于中美半干旱区8个野外试验站点2003—2008年的观测数据,选择最小二乘法线性拟合、多项式拟合、以及双重回归拟合等方法,对NCEP再分析数据集的地表通量数据进行了系统的检验和订正。结果表明,对于日平均值,拟合订正效果相对较差,仅部分站点的土壤含水量以及地表感热和潜热通量可以使用曲线拟合的方法得以改进。对月平均值,3种方案都有不同程度的订正改进效果,订正的序列还原了数据的季节变化趋势。在此基础上,综合线性回归和曲线拟合两种方法的优势,最大程度地还原资料的线性趋势,并减小因截断误差造成的信息损失,构建了中美半干旱区长期的地表通量数据序列。所构建的半干旱区长期地表通量序列也为深入认识中美半干旱区陆气相互作用的基本特征以及模式结果验证,提供了宝贵的基础数据。     

Analyzing long-term spatial variability of blue and green water footprints in a semi-arid mountainous basin with MIROC-ESM model (case study: Kashafrood River Basin,Iran)

Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO₂ concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009–2011) and one configuration applied to predict SO₂ concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO₂ concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model’s performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model’s performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO₂ concentrations were assessed by the model with IOA varied from 0.37 to 0.57, mostly dependent on the grid/monitoring station of the simulated domain. The present study can be used, with relevant adaptations, as a user guideline for future conducting simulations in mountainous complex terrain.     

Spatiotemporal trends of aridity index in arid and semi-arid regions of Iran

The spatiotemporal trends of aridity index in the arid and semi-arid regions of Iran in 1966–2005 were investigated using the Mann–Kendall test and Theil–Sen’s slope estimator. The results of the analysis showed negative trends in annual aridity index at 55 % of the stations, while just one site had a statistically significant (α?=?0.1) negative trend. Furthermore, the positive trends in the annual aridity index series were significant at the 95 % confidence level at Bushehr and Isfahan stations. The significant negative trend in the annual aridity index was obtained over Mashhad at the rate of ?0.004. In the seasonal series, the negative trends in the spring and winter aridity index were larger compared with those in the other seasonal series. A noticeable decrease in the winter aridity index series was observed mostly in the southeast of the study area. In the summer and autumn aridity index, two significant positive trends were found.     

Synoptic and dynamic analysis of a flash flood-inducing heavy rainfall event in arid and semi-arid central-northern Iran and its simulation using the WRF model

The synoptic and dynamic aspects of heavy rainfall occurred on 5th May 2017 and caused flash flooding in arid and semi-arid central-northern Iran is analyzed by the Weather Research and Forecasting (WRF) model. This system synoptically is attributed to a surface low-pressure centered over southern Iran extended to the central parts, linking to a mid-tropospheric tilted-trough over western Iran, and advecting significant moisture from the Mediterranean Sea and the Red Sea to the studied area. The dynamical analysis revealed that the penetration of the upper-tropospheric potential vorticity streamer up to 300 hPa level was not related to such heavy rainfall. Contrarily, the low-level factors such as extensive moisture advection, mid-tropospheric diabatic processes such as the latent heat release, daytime deep convection, and topographical impact of Zagros Mountains were found as the key factors leading to this system. This study also examines 11 different convection schemes simulated by the WRF model and verified against rainfall observation. The forecast skills of the output simulations suggest the Grell-Devenyi scheme as the superior configuration in simulating observed precipitation of the event over the area.     

Probabilistic analysis of extreme regional meteorological droughts by L-moments in a semi-arid environment

Regional extreme value analyses of drought characteristics provide information on probabilistic nature of drought occurrence, viewed as an essential tool in drought mitigation and planning. In this paper, L-moments are used to investigate the regional characteristics and probabilistic behavior of drought severity levels, represented by the Standardized Precipitation Index (SPI) annual minima (the minimum monthly SPI value). Rainfall data of 3, 6, 12, and 24 month time scales are investigated. A regional watershed in southwestern Iran is used as a case study area. The semi-arid nature of the study area requires appropriate selection of rainfall data. The boxplot approach is used to select those months with adequate data time series for the SPI analysis. Appropriateness of the suggested data time series is discussed in the context of the research by Wu et al. (2007). Based on the results, all of the suggested time scales are found appropriate for SPI investigations. For each time scale of interest regional homogeneity is evaluated and the best regional/sub-regional probability distribution function is selected. Regional quantiles are estimated for different time scales and their variability with respect to return period is discussed.     

The impact of water resources development projects on water vapor pressure trends in a semi-arid region, Turkey

The aim of this study was to investigate long-term seasonal trends and decadal change patterns of monthly mean water vapor pressure (WVP) observation series at 16 meteorological stations scattered point-wisely over the Southeastern Anatolian Project (GAP) area in Turkey, where large-scale soil and water development projects have been put into practice since the 1970s. The record length of WVP observation series of each station varied between 31- and 41-years between 1962 and 2002. The monthly mean WVP observation series of each station was rearranged on seasonal basis. Sequential Mann–Kendall trend test, Sen’s slope estimator, and Spearman’s rank–order correlation tests were employed for detection of likely trends, and Kruskall–Wallis test was used to detect decadal variations in WVP series of each observation station. A possible area of representation for each meteorological station was determined by using the Thiessen polygons technique in a geographical information systems media. It was found that 15 seasonal WVP series have a positive trend covering 97% of the GAP area in the summer season; although one WVP series has a negative trend direction. However, in the spring season, 33% of the area had a positive trend, and a negative trend did not appear in any stations. WVP records in the winter season showed an increasing trend over 19% of the GAP area, whereas a decreasing trend prevailed in 9% of the area. The study results led us to conclude that the substantial increase of WVP observations in summer season could be attributed to both the shift from rain-fed agriculture to irrigated agriculture being made increasingly spacious year by year and building large water reservoirs in the GAP located in a semi-arid region. The results also indirectly suggested that the historical trends in the WVP parameters might be related to global climate change phenomenon.     

Spatial and temporal analysis of the drought vulnerability and risks over eight decades in a semi-arid region (Tensift basin: Morocco)

Theoretical and Applied Climatology - The multiple downscaled scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future...     

Single and dual crop coefficients and crop evapotranspiration for wheat and maize in a semi-arid region

In this study, weighing lysimeters were used to investigate the daily crop coefficient and evapotranspiration of wheat and maize in the Fars province, Iran. The locally calibrated Food and Agriculture Organization (FAO) Penman–Monteith equation was used to calculate the reference crop evapotranspiration (ET_o). Micro-lysimetry was used to measure soil evaporation (E). Transpiration (T) was estimated by the difference between crop evapotranspiration (ET_c) and E. The single crop coefficient (K _c) was calculated by the ratio of ET_c to ET_o. Furthermore, the dual crop coefficient is composed of the soil evaporation coefficient (K _e) and the basal crop coefficients (K _cb) calculated from the ratio of E and T to ET_o, respectively. The maximum measured evapotranspiration rate for wheat was 9.9 mm?day^?1 and for maize was 10 mm?day^?1. The total evaporation from the soil surface was about 30 % of the total wheat ET_c and 29.8 % of total maize ET_c. The single crop coefficient (K _c) values for the initial, mid-, and end-season growth stages of maize were 0.48, 1.40, and 0.31 and those of wheat were 0.77, 1.35, and 0.26, respectively. The measured K _c values for the initial and mid-season stages were different from the FAO recommended values. Therefore, the FAO standard equation for K _c-_mid was calibrated locally for wheat and maize. The K _cb values for the initial, mid-, and end-season growth stages were 0.23, 1.14, and 0.13 for wheat and 0.10, 1.07, and 0.06 for maize, respectively. Furthermore, the FAO procedure for single crop coefficient showed better predictions on a daily basis, although the dual crop coefficient method was more accurate on seasonal scale.     

Spatiotemporal reference evapotranspiration changes in humid and semi-arid regions of Iran: past trends and future projections

Theoretical and Applied Climatology - This study was undertaken to investigate the reference evapotranspiration (ET0) changes in semi-arid and humid regions of Iran during the past...     

Rain gauge network evaluation and optimal design using spatial correlation approach in arid and semi-arid regions of Iran

Theoretical and Applied Climatology - The present study is aimed at evaluation of a rain gauge network in order to optimize a network design. In this regard, point rainfall estimations were...     

Effects of the southern oscillation on the probability for climatic categories of monthly rainfall, in a semi-arid region in the southern mid-latitudes

In many regions of the world, planning agricultural and water management activities is usually done based on probabilities for monthly rainfall, taking on values on specified intervals of values. These intervals of monthly rainfall amounts are commonly grouped into three categories: drought, normal rainfall, and abundant rainfall. Changes in the probabilities for occurrence of monthly rainfall amounts within these climatic rainfall categories will influence the decisions farmers and water managers will take (for example, crops to cultivate, flood preparedness, and operations of water reservoirs). This research explores the changes produced by the SO (Southern Oscillation) on the probability that the areal average of monthly rainfall (AAvMR) takes on values belonging to specified climatic rainfall categories. The semi-arid region under study is a major agricultural region in central Argentina; weather effects on agriculture in this region influence the world market of several crops. The evolution of the Southern Oscillation was divided into three phases: LSOI (low Southern Oscillation index phase, that includes ENSO events), NSOI (neutral SOI phase), and HSOI (high SOI phase that includes La Niña–SO events). The following are the criteria defining the three phases of the SO: (1) low SOI (ENSO), where the five-month moving average of the SO index, SOI, is less than −0.5 standard deviation during at least five consecutive months, and is equal to or less than −1 standard deviation during at least one month; (2) high SOI (La Niña–SO), where the SOI is greater than 0.5 standard deviation during at least five consecutive months, and is equal to or greater than 1 standard deviation during at least one month; and (3) neutral SOI (transition between extremes), where the SOI does not correspond to low SOI nor to high SOI. It was found that the Southern Oscillation influences the probability distribution of monthly rainfall only in four months of the year. Findings show that monthly rainfall has a complex response to the evolution of the SO. The response is not restricted to higher probability for occurrence of abundant rainfall or drought categories during low SOI (ENSO) or high SOI (La Niña–SO) episodes, respectively. The LSOI (ENSO) phase influences the AAvMR in several ways: depending on the month, it increases or decreases the probability of the abundant rainfall category. LSOI (ENSO) also increases or decreases, depending on the month, the probability of the normal rainfall category. It also decreases the probability that AAvMR takes on values in the drought category. A similar kind of complex response of monthly rainfall amounts occurs when the active phase is the HSOI (La Niña–SO). The responses are: (1) the probability of the category `drought' increases only in three months of the year, (2) increase or decrease of the probability of the normal rainfall category, depending on the month, and (3) decrease of the probability of the abundant rainfall category. Finally, the effects of NSOI (neutral phase of the SO) are not negligible. Depending on the month, NSOI episodes increase or decrease the probability of drought, or abundant rainfall, or normal rainfall categories.     

准后向散射对单点声雷达测量温度结构系数的影响

本文从湍流大气对声波散射方程出发,推导出静止大气和有水平运动两种情况下,有限接收面积上的平均准后向散射截面公式。从而分析了影响平均准后向散射截面的因子,同时还计算讨论了不同天线口径、风速和值的平均准后向散射截面。 计算结果表明:在一般情况下,边界层内用声雷达测得的温度结构系数[C_T~2(θ)]要比理论上纯后向温度结构系数[C_T~2(180°)]大些;C_T~2(θ)与C_T~2(180°)比值以及C_T~2(θ)随高度的变化都与天线口径、风速分布和m值等密切相关。因此对用不同声雷达在不同大气条件作对比测量,得到某些不一致的现象,可给予一定的解释。     

Preparation of frost atlas using different interpolation methods in a semiarid region of south of Iran

In this research, suitability of different kriging and inverse distance weighted (IDW) methods in estimating occurrence date of frost was evaluated. Data included minimum daily air temperature values from 27 meteorological stations of Fars province in southern Iran from 18 to 45 years. Data ranges of 0 to ?1.5, ?1.5 to ?3 and below ?3°C were considered as mild, moderate and severe frost intensities, respectively. Starting with the first day of autumn, iso-occurrence days for the frost intensities and occurrence probabilities (25%, 50%, 75% and 90%) were estimated using ordinary kriging, cokriging, residual kriging type 1 (RK1), residual kriging type 2 (RK2), universal kriging and IDW methods. In these models, the errors of estimated frost intensities at different probabilities were lowest in the RK2 model, but lack of establishment of spatial structure due to long distance between stations caused the predictions not to be acceptable in some cases. In a proposed method (modified inverse distance weighted, MIDW), the trend between the first and last days of frost occurrence with earth elevation was removed, and the reminder values were estimated by (IDW) method. Although, the errors for estimated frost dates by MIDW and RK2 methods were the same, but the MIDW method did not have the spatial establishment shortcoming. Furthermore, the simplicity and practicality of the MIDW method makes it a reasonable selection.