Daily Precipitation Extremes in Iran: Decadal Anomalies and Possible Drivers

This study focuses on the empirical statistical analysis of the anomalies in daily precipitation extremes by applying the quantile perturbation method (QPM) to data from 31 Iranian weather stations during the period between 1961 and 2005. The possible causes behind the anomalies in precipitation extremes are identified by analyzing their relationship with the anomalies in eight atmospheric indices (i.e., NAO, SOI, PDO, AMO, NCP, DMI, WeMO, SSN). In terms of decadal oscillations, the country was generally wet in the 1960s and 1970s with most stations exhibiting periods of higher quantile perturbations, whereas lower quantile perturbations were dominant in the 1980s and 1990s. The highest perturbation in extreme precipitation quantiles prevails in Central Iran during the early 1980s, in which the quantiles are about 50% higher than the ones based on the full time series. The frequency of significant precipitation anomalies for winter season was greater than that for spring and autumn seasons. For the summer season, the humid region in North Iran demonstrates strong positive anomalies. The results highlight the noticeable role of large‐scale climatic factors in the anomalous behavior of precipitation extremes in Iran. The atmospheric drivers of the quantile anomalies in extreme precipitation were found to differ from one season to another.     

Streamflow Changes in the South Atlantic,United States During the Mid‐ and Late 20th Century1

Abstract: Repeated severe droughts over the last decade in the South Atlantic have raised concern that streamflow may be systematically decreasing, possibly due to climate variability. We examined the monthly and annual trends of streamflow, precipitation, and temperature in the South Atlantic for the time periods: 1934‐2005, 1934‐1969, and 1970‐2005. Streamflow and climate (temperature and precipitation) trends transitioned ca. 1970. From 1934 to 1969, streamflow and precipitation increased in southern regions and decreased in northern regions; temperature decreased throughout the South Atlantic. From 1970 to 2005, streamflow decreased, precipitation decreased, and temperature increased throughout the South Atlantic. It is unclear whether these will be continuing trends or simply part of a long‐term climatic oscillation. Whether these streamflow trends have been driven by climatic or anthropogenic changes, water resources management faces challenging prospects to adapt to decadal‐scale persistently wet and dry hydrologic conditions.     

ACCEPTING THE STANDARDIZED PRECIPITATION INDEX: A CALCULATION ALGORITHM1

ABSTRACT: The Palmer Drought Severity Index (PDSI) has been calculated for about 30 years as a means of providing a single measure of meteorological drought severity. It was intended to retrospectively look at wet and dry conditions using water balance techniques. The Standardized Precipitation Index (SPI) is a probability index that was developed to give a better representation of abnormal wetness and dryness than the Palmer indices. Before the user community will accept the SPI as an alternative to the Palmer indices, a standard method must be developed for computing the index. Standardization is necessary so that all users of the index will have a common basis for both spatial and temporal comparison of index values. If different probability distributions and models are used to describe an observed series of precipitation, then different SPI values may be obtained. This article describes the effect on the SPI values computed from different probability models as well as the effects on dry event characteristics. It is concluded that the Pearson Type III distribution is the “best” universal model, and that the reliability of the SPI is sample size dependent. It is also concluded that because of data limitations, SPIs with time scales longer than 24 months may be unreliable. An internet link is provided that will allow users to access Fortran 77 source code for calculating the SPI.     

A STATISTICAL SIMULATION TECHNIQUE FOR NORTHERN NEW JERSEY MONTHLY PRECIPITATION1

A 30-year record of monthly precipitation for Northern New Jersey was analyzed for its statistical components. With a weak annual periodicity eliminated, the series was found to be random. The data for each month were fit with a gamma distribution using Thom's suggested best estimates of the distribution parameters. A one-thousand-year simulated monthly precipitation series was generated using random values from the twelve gamma distributions. The statistical properties of the simulated and sample time series agreed well. Numerous anomalous precipitation regimes were observed in the simulated data.     

SPATIAL COMPARABILITY OF THE PALMER DROUGHT SEVERITY INDEX1

ABSTRACT: The Palmer Drought Severity Index, which is intended to be of reasonable comparable local significance both in space and time, has been extensively used as a measure of drought for both agricultural and water resource management. This study examines the spatial comparability of Palmer's (1965) definition of severe and extreme drought. Index values have been computed for 1035 sites with at least 60 years of record that are scattered across the contiguous United States, and quantile values corresponding to a specified index value were calculated for given months and then mapped. The analyses show that severe or extreme droughts, as defined by Palmer (1965), are not spatially comparable in terms of identifying rare events. The wide variation across the country in the frequency of occurrence of Palmer's (1965) extreme droughts reflects the differences in the variability of precipitation, as well as the average amount of precipitation. It is recommended first, that a drought index be developed which considers both variability and averages; and second, that water resource managers and planners define a drought in terms of an index value that corresponds to the expected quantile (return period) of the event.     

Soil moisture‐based drought monitoring at different time scales: a case study for the U.S. Great Plains

Short‐term agricultural drought and longer term hydrological drought have important ecological and socioeconomic impacts. Soil moisture monitoring networks have potential to assist in the quantification of drought conditions because soil moisture changes are mostly due to precipitation and evapotranspiration, the two dominant water balance components in most areas. In this study, the Palmer approach to calculating a drought index was combined with a soil water content‐based moisture anomaly calculation. A drought lag time parameter was introduced to quantify the time between the start of a moisture anomaly and the onset of drought. The methodology was applied to four shortgrass prairie sites along a North‐South transect in the U.S. Great Plains with an 18‐year soil moisture record. Short time lags led to high periodicity of the resulting drought index, appropriate for assessing short‐term drought conditions at the field scale (agricultural drought). Conversely, long time lags led to low periodicity of the drought index, being more indicative of long‐term drought conditions at the watershed or basin scale (hydrological drought). The influence of daily, weekly, and monthly time steps on the drought index was examined and found to be marginal. The drought index calculated with a short drought lag time showed evidence of being normally distributed. A longer data record is needed to assess the statistical distribution of the drought index for longer drought lag times.     

PRIESTLEY‐TAYLOR ALPHA COEFFICIENT: VARIABILITY AND RELATIONSHIP TO NDVI IN ARCTIC TUNDRA LANDSCAPES1

ABSTRACT: Average daily values of the Priestley‐Taylor coefficient (a) were calculated for two eddy covariance (flux) tower sites with contrasting vegetation, soil moisture, and temperature characteristics on the North Slope of Alaska over the 1994 and 1995 growing seasons. Because variations in a have been shown to be associated with changes in vegetation, soil moisture, and meteorological conditions in Arctic ecosystems, we hypothesized that a values would be significantly different between sites. Since variations in the normalized difference vegetation index (NDVI) follow patterns of vegetation community composition and state that are largely controlled by moisture and temperature gradients on the North Slope of Alaska, we hypothesized that temporal variations in a respond to these same conditions and thus co‐vary with NDVI. Significant differences in a values were found between the two sites in 1994 under average precipitation conditions. However, in 1995, when precipitation conditions were above average, no significant difference was found. Overall, the variations in a over the two growing seasons showed little relationship to the seasonal progression of the regional NDVI. The only significant relationship was found at the drier, upland study site.     

IMPACTS OF CLIMATE CHANGE ON WATER YIELD IN THE UPPER WIND RIVER BASIN1

ABSTRACT: The potential impacts of climate change on water yield are examined in the Upper Wind River Basin. This is a high‐elevation, mountain basin with a snowfall/snowmelt dominated stream‐flow hydrograph. A variety of physiographic conditions are represented in the rangeland, coniferous forests, and high‐elevation alpine regions. The Soil Water Assessment Tool (SWAT) is used to model the baseline input time series data and climate change scenarios. Five hydroclimatic variables (temperature, precipitation, CO₂, radiation, and humidity) are examined using sensitivity tests of individual and coupled variables with a constant change and coupled variables with a monthly change. Results indicate that the most influential variable on annual water yield is precipitation; and, the most influential variable on the timing of streamflow is temperature. Carbon dioxide, radiation, and humidity each noticeably impact water yield, but less significantly. The coupled variable analyses represent a more realistic climate change regime and reflect the combined response of the basin to each variable; for example, increased temperature offsets the effects of increased precipitation and magnifies the effects of decreased precipitation. This paper shows that the hydrologic response to climate change depends largely on the hydroclimatic variables examined and that each variable has a unique effect (e.g., magnitude, timing) on water yield.     

EFFECTS OF CLIMATIC CHANGE ON THE THORNTHWAITE MOISTURE INDEX1

ABSTRACT: The Thornthwaite moisture index is a useful indicator of the supply of water (precipitation) in an area relative to the demand for water under prevailing climatic conditions (potential evapotranspiration). This study examines the effects of changes in climate (temperature and precipitation) on the Thornthwaite moisture index in the conterminous United States. Estimates of changes in mean annual temperature and precipitation for doubled-atmospheric CO₂ conditions derived from three general circulation models (GCMs) are used to study the response of the moisture index under steady-state doubled-CO₂ conditions. Results indicate that temperature and precipitation changes under doubled-CO₂ conditions generally will cause the Thornthwaite moisture index to decrease, implying a drier climate for most of the United States. The pattern of expected decrease is consistent among the three GCMs, although the amount of decrease depends on which GCM climatic-change scenario is used. Results also suggest that changes in the moisture index are related mainly to changes in the mean annual potential evapotranspiration as a result of changes in the mean annual temperature, rather than to changes in the mean annual precipitation.     

CLIMATOLOGICAL WATERSHED CALIBRATION1

ABSTRACT: This study tests the hypothesis that climatic data can be used to develop a watershed model so that stream flow changes following forest harvest can be determined. Measured independent variables were precipitation, daily maximum and minimum temperature, and concurrent relative humidity. Computed variables were humidity deficit, saturated vapor pressure, and ambient vapor pressure. These climatic variables were combined to compute a monthly evaporation index. Finally, the evaporation index and monthly precipitation were regressed with measured monthly stream flow and the monthly estimates of stream flow were combined for the hydrologic year. A regression of predicted versus measured annual stream flow had a standard error of 1.5 inches (within 6.1 percent of the measured value). When 10, 15, and 20 years of data were used to develop the regression equations, predicted minus measured stream flow for the last 7 years of record (1972–1978) were within 16.8, 11.5, and 9.7 percent of the measured mean, respectively. Although single watershed calibration can be used in special conditions, the paired watershed approach is expected to remain the preferred method for determining the effects of forest management on the water resource.     

Water balance characterization of the early 21st century drought in the western United States

Monthly temperature and precipitation data for 923 United States Geological Survey 8-digit hydrologic units are used as inputs to a monthly water balance model to compute monthly actual evapotranspiration, soil moisture storage, and runoff across the western United States (U.S.) for the period 1900 through 2020. Time series of these water balance variables are examined to characterize and explain the dry conditions across the western U.S. since the year 2000. Results indicate that although precipitation deficits account for most of the changes in actual evapotranspiration and runoff, increases in temperature primarily explain decreases in soil moisture storage. Specifically, temperature has been particularly impactful on the magnitude of negative departures of soil moisture storage during the spring (April through June) and summer (July through September) seasons. These effects on soil moisture may be particularly detrimental to agriculture in regions already stressed by drought such as the western U.S.     

Effects of climate and land use changes on groundwater resources in coastal aquifers

To estimate the freshwater loss in coastal aquifers due to salinisation, a numerical model based on the sharp interface assumption has been introduced. The developed methodology will be useful in areas where limited hydrological data are available. This model will elaborate on the changes in fresh groundwater loss with respect to climate change, land use pattern and hydrologic soil condition. The aridity index has been introduced to represent the variations in precipitation and temperature. The interesting finding is that the deforestation leads to increase groundwater recharge in arid areas, because deforestation leads to reduce evapotranspiration even though it favors runoff. The combined climate and land use scenarios show that when the aridity index is less than 60, the agricultural lands give higher groundwater recharge than other land use patterns for all hydrologic soil conditions. The calculated recharge was then used to estimate the freshwater-saltwater interface and percentage of freshwater loss due to salinity intrusion. We found that in arid areas, the fresh groundwater loss increases as the percentage of forest cover increases. The combined effects of deforestation and aridity index on fresh groundwater loss show that deforestation causes an increase in the recharge and existing fresh groundwater resource in areas having low precipitation and high temperature (arid climates).     

A METHOD FOR ESTIMATING SNOWFALL AMOUNTS1

ABSTRACT: Long-term climatic data from National Weather Service stations in six areas of the United States were utilized to develop regression equations relating a “snowfall index” parameter and air temperature. Nearly 200 stations, representing a wide range in physiographic and climatic conditions, were selected for analysis. Snowfall index is defined as the ratio of snowfall depth to precipitation. Using annual data, regression analysis indicated snowfall index to be significantly (α= 0.01) related to temperature for five of the six areas studied. Differences between equations were attributed to the effects of precipitation and temperature during non-snowfall periods. Mean monthly data were also considered and significant equations (α= 0.011, representing a family of similarly shaped curves, were obtained. The illustrated equations can be used for estimating mean monthly and annual snowfall amounts for stations having only temperature and precipitation measurements.     

MULTIFRACTAL SCALING OF DAILY RUNOFF TIME SERIES IN AGRICULTURAL WATERSHEDS1

Abstract: Multifractal scaling behavior of long-term records of daily runoff time series in 32 subwatersheds covering a wide range of sizes was examined. These subwatersheds were associated with four agricultural watersheds with different climates and topography. The empirical moment scaling curves obtained using the trace moment method showed that the runoff time series exhibited a multifractal behavior, which was valid over a time scale range from one day to about three years. The multi-fractal scaling of the runoff time series was well described by the Universal Multifractal Model. The spectral analysis (β < 1) and the order of fractional integration (H ⋍; 0) indicated that the runoff time series were conservative. The multifractal parameters, α (multifractal index) and C₁ (co-dimension), were reasonably close to each other for subwatersheds within each of the watersheds and were generally similar among the four watersheds. The α values of the four watersheds were 1.10 ± 0.13, 1.61 ± 0.06,1.61 ± 0.24, and 1.63 ± 0.19. The C₁ values of four watersheds were 0.19 ± 0.01, 0.17 ± 0.01, 0.17 ± 0.04, and 0.11 ± 0.02. The multifractal analyses provided useful insight into the runoff time series, especially the occurrence and distribution of extreme events.     

NEW ENGLAND DROUGHT AND RELATIONS WITH LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS1

ABSTRACT: To provide a basis for regional hydroclimatic forecasting, New England (NE) precipitation and streamflow are compared with indices for the El Niño/Southern Oscillation, the Pacific North American (PNA) pattern, and the North Atlantic Oscillation (NAO). Significant positive correlations are found between the NAO index and monthly streamflow at western inland locations, with the strongest seasonal correlations occurring in winter. Smoothed records for the winter NAO and winter streamflow are highly correlated at some sites, suggesting that interrelationships are most significant in the low frequency spectrum. However, correlations between the NAO and precipitation are not significant, so further examination of other factors is needed to explain the relationship between the NAO and streamflow. NAO related regional air temperature, sea surface temperature (SST), storm tracking, and snowfall variability are possible mechanisms for the observed teleconnection. Exceptionally cool regional air temperatures, and SSTs, and unique regional storm track patterns characterized NE's climate during the famous 1960s drought, suggesting that concurrent (persistent) negative NAO conditions may have contributed to the severity of that event. Monthly and winter averaged regional streamflow variability are also significantly correlated with the PNA index. This, along with results from previous studies, suggests that tropospheric wave character and associated North Pacific SST anomalies are also related to NE regional drought conditions.     

电子装备南海环境适应性改进设计研究

南海地区环境条件非常严酷,某雷达电子装备服役于我国南海某海岛,在保持主要战技指标不变的前提下,针对南海地区高温高湿高盐雾的环境特点重新对雷达进行了环境适应性改进设计研究,在总体、电讯、结构、工艺和军方等的有效协调配合下,其改进设计得到了有效实施,通过试验验证在南海几年来的使用运行,历经高湿热、强盐雾的影响,防护设计效果满足预期设计要求。     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

ESTIMATED RUNOFF FROM MAN-MADE SNOW1

ABSTRACT: The consumptive loss from man-made snowmaking at six Colorado ski areas is calculated. The focus of the procedures in this investigation is on the consumptive loss that occurs to man-made snow particles during the period they reside on or in the snowpack until spring snowmelt (termed the watershed loss). Calculated watershed losses under a variety of precipitation and temperature conditions at six ski areas varied from 7 to 33 percent. These calculations were made using the calibrated Subalpine Water Balance Simulation Model (Leaf and Brink, 1973a, 1973b). The watershed loss of 7 to 33 percent indicates the range of likely watershed losses that can be expected at Colorado ski areas. A previous paper by the authors (Eisel et al., 1988) provided estimates of the mean consumptive loss during the snowmaking process (termed initial loss) for conditions existing at Colorado ski areas to be 6 percent of water applied. Therefore, based on the mean initial loss, the total consumptive loss from man-made snowmaking under conditions found at Colorado ski areas could be expected to range from 13 to 37 percent. These results demonstrate the range of total consumptive losses that could be expected in various years and for various watershed conditions. These total percentage losses cannot be extrapolated directly to other specific sites because the total consumptive loss is dependent on temperature during actual snowmaking, temperature and precipitation throughout the winter at the specific ski area, and watershed conditions at the ski area. Consumptive losses to man-made snow for a specific ski area should be estimated using the handbook procedures developed especially for this purpose (Colorado Ski Country USA, 1986b).     

STRATIFICATION VARIABILITY IN THREE MORPHOMETRICALLY DIFFERENT LAKES UNDER IDENTICAL METEOROLOGICAL FORCING1

ABSTRACT: Synoptic water temperature measurements were taken in three temperate lakes located within 25 km of one another to study the effects of morphometry (and changes in weather) on seasonal and short-term thermal stratification characteristics. Two of the lakes had nearly the same surface areas and two had nearly identical mean depths; all were exposed to identical weather conditions. The dominance of weather over morphometry on the water surface temperature response was illustrated by the synoptic measurements in two different years. Stratification structure was also found to be dominated by weather for sufficiently deep lakes. Surface area effects were most subtle but explainable as sheltering effects. The onset of stratification was not, as traditionally described, a simple, gradual response of a lake to the annual solar radiation cycle. Rather it depends on a series of alternating heating, cooling, and mixing cycles similar to annual and diel cycles but with a period of approximately five days. These were in direct response to the passage of major weather systems and displayed no apparent time lag. No comparable synoptic water temperature data set could be found in the literature.     

Statistical Models to Predict and Assess Spatial and Temporal Low‐Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.