MEASURING DROUGHT IMPACTS: THE ILLINOIS CASE1

ABSTRACT: Drought is an interaction between physical processes and human activities. This study quantified the impacts of precipitation deficiencies on streamflow, reservoirs, and shallow ground water supplies. An in-depth analysis of newspaper accounts of droughts between paired cities, one in drought and one not in drought, were used to measure the differences in the types of drought impacts, and in the time of onset of impacts as related to developing precipitation deficiencies. Precipitation deficiencies related to the onset and the magnitude of surface water supply adjustments, and to shallow ground water problems, were established. Thus, monitoring and prediction of the onset and magnitude of drought problems can now be done from readily available data on precipitation deficiencies. Newspapers were found to be reliable indicators for the timing of drought impacts and adjustments as precipitation deficiency develops. A review of local and state adjustments during two recent droughts revealed most decision makers lacked information and experience in dealing with drought.     

SPATIAL VARIATIONS OF WATER LOSS DURING DROUGH A CASE STUDY1

ABSTRACT: A regional water conservation system for drought management involves many uncertain factors. Water received from precipitation may stay on the ground surface, evaporate back into the atmosphere, or infiltrate into the ground. Reliable estimates of the amount of evapotranspiration and infiltration are not available for a large basin, especially during periods of drought. By applying a geographic information system, this study develops procedures to investigate spatial variations of unavailable water for given levels of drought severity. Levels of drought severity are defined by truncated values of monthly precipitation and daily streamflow to reflect levels of water availability. The greater the truncation level, the lower the precipitation or streamflow. Truncation levels of monthly precipitation are recorded in depth of water while those of daily streamflow are converted into monthly equivalent water depths. Truncation levels of precipitation and streamflow treated as regionalized variables are spatially interpolated by the unbiased minimum variance estimation. The interpolated results are vector values of precipitation and streamflow at a grid of points covering the studied basin. They are then converted into raster‐based values and expressed graphically. The image subtraction operation is used to subtract the image of streamflow from that of precipitation at their corresponding level of drought severity. It is done on a cell‐by‐cell basis resulting in new attribute values to form the spatial image representing a spatial distribution of potential water loss at a given level of drought severity.     

COMPARING THE PALMER DROUGHT INDEX AND THE STANDARDIZED PRECIPITATION INDEX1

ABSTRACT: The Palmer Drought Index (PDI) is used as an indicator of drought severity, and a particular index value is often the signal to begin or discontinue elements of a drought contingency plan. The Standardized Precipitation Index (SPI) was recently developed to quantify a precipitation deficit for different time scales. It was designed to be an indicator of drought that recognizes the importance of time scales in the analysis of water availability and water use. This study compares historical time series of the PDI with time series of the corresponding SPI through spectral analysis. Results show that the spectral characteristics of the PDI vary from site to site throughout the U.S., while those of the SPI do not vary from site to site. They also show that the PDI has a complex structure with an exceptionally long memory, while the SPI is an easily interpreted, simple moving average process.     

秦皇岛地区气候干旱与人工增雨的探索

气候分析表明:随着气候变化及环境城市化,秦皇岛市区域年平均气温指数呈上升趋势,特别是近10年出现了连续偏高的异常变化;年降水指数呈明显减小趋势,出现了连年干旱,高温少雨不仅使生态环境不断恶化,而且使农田干旱、水库蓄水严重不足,因此人工增雨变得更加迫切。目前,秦皇岛市人工增雨工作已进入常态化、业务化轨道。总结1999—2008年火箭人工增雨经验,人工增雨操作的技术关键:一是分析局地降水气候规律;二是利用碘化银进行人工增雨需要适当的温度条件,即所谓进行冷云催化。在增雨时应充分考虑这一物理机制,选择好合适的发射高度,把催化剂送到可催化的温度环境中,以保证作业成功率。     

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.     

ATMOSPHERIC CONTRIBUTIONS TO FOREST NUTRIENT CYCLING1

The atmosphere is a significant source of plant nutrients that partially replenishes losses due to timber harvesting. The relative importance of wet and dry deposition depends upon the specific nutrient and site. Nitrogen in bulk precipitation (wetfall and dryfall) is equivalent to at least 70 percent of the nitrogen incorporated annually in above-ground woody tissues of some temperate hardwood forests. Atmospheric sources of calcium and potassium supply between 20 and 40 percent of the nutrients sequestered in woody increments. Annual nutrient inputs in bulk precipitation can exceed removals associated with sawiog harvest over a rotation period. Atmospheric inputs of nitrogen are only slightly less than hydrologic losses immediately after timber harvesting. The deposition of nutrients is highly variable in both time and space; interpretations of nutrient inputs and forest management impacts require quantification of inputs for a variety of ecosystems over long periods of time.     

秦皇岛湿润生态环境变化

利用线性倾向分析、滑动平均和计算干燥度等方法对秦皇岛市1954-2005年降水、气温、相对湿度、蒸发量、干燥度等变化进行分析研究，结果表明：近50年秦皇岛地区气温逐渐升高，降水减少，气候干燥度普遍增大，生态环境呈干旱化趋势，南部干旱化进程较北部大，90年代后干旱化趋势增大。     

A PROPOSED METHOD FOR DROUGHT MONITORING1

ABSTRACT: Existing definitions of drought have focused on limited hydrologic indicators and are less effective for the purpose of drought monitoring. This study uses historical records of streamflow, precipitation, ground water, temperature, and lake elevation to define drought. Based on the method of truncation, drought durations and conditional probabilities of each indicator were estimated to define the drought severity levels, namely, 70 percent, 80 percent, 90 percent, and 95 percent. A drought monitoring method was developed by a combination of truncation level, duration, and conditional probabilities of five indicators. A six-month period of the 1988 drought in the central Ohio region was used to test the monitoring method. It was found that the developed method could effectively detect an occurrence of drought.     

TOWARDS CHARACTERIZING AND PLANNING FOR DROUGHT IN VERMONT‐PART I: A CLIMATOLOGICAL PERSPECTWE1

ABSTRACT: In the Green Mountain state of Vermont, droughts of one form or another and of varying intensities, seventies, and areal extent are not uncommon occurrences. The 1990s were marked by at least three drought events of which the 1998 to 1999 was the most recent. In spite of this recurrence, ongoing drought monitoring and mitigative planning efforts are not as advanced as they could be and no official drought plan exists for the state. This article is the first of two in this volume. It summarizes the cascade of drought types that impacted the state during the 1998 to 1999 episode. From a number of precipitation statistics and drought indices, fine spatial scales (county or better) were found to best capture the character of drought impacts, while the weekly time step is recommended as the temporal unit around which to base planning and monitoring efforts. The companion article outlines a possible framework for drought planning efforts and highlights key constituencies to be included in the process.     

Recent Ogallala Aquifer Region Drought Conditions as Observed by Terrestrial Water Storage Anomalies from GRACE

Recent severe drought events have occurred over the Ogallala Aquifer region (OAR) during the period 2011–2015, creating significant impacts on water resources and their use in regional environmental and economic systems. The changes in terrestrial water storage (TWS), as indicated by the Gravity Recovery and Climate Experiment (GRACE), reveals a detailed picture of the temporal and spatial evolution of drought events. The observations by GRACE indicate the worst drought conditions occurred in September 2012, with an average TWS deficit of ~8 cm in the northern OAR and ~11 cm in the southern OAR, consistent with precipitation data from the Global Precipitation Climatology Project. Comparing changes in TWS with precipitation shows the TWS changes can be predominantly attributable to variations in precipitation. Power spectrum and squared wavelet coherence analysis indicate a significant correlation between TWS change and the El Nino‐Southern Oscillation, and the influence of equatorial Pacific sea surface temperatures on TWS change is much stronger in the southern OAR than the northern OAR. The results of this study illustrate the value of GRACE in not just the diagnosis of significant drought events, but also in possibly improving the predictive power of remote signals that are impacted by nonregional climatic events (El Nino), ultimately leading to improved water resource management applications on a regional scale. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Prediction of Crop Production using Drought indices at Different Time Scales and Climatic Factors to Manage Drought Risk1

Sadat Noori, S.M., A.M. Liaghat, and K. Ebrahimi, 2011. Prediction of Crop Production Using Drought Indices at Different Time Scales and Climatic Factors to Manage Drought Risk. Journal of the American Water Resources Association (JAWRA) 48(1): 1‐9. DOI: 10.1111/j.1752‐1688.2011.00586.x Abstract: Drought causes great damage to rainfed and irrigated farming. Therefore, prediction of crop production during the drought period is essential in order to manage drought risk. Thus, proceeding to agricultural drought risk management can be very useful. This study shows the results of early crop prediction using the combination of climate factors and drought indices at different time scales. The study region was Hamadan, a semiarid region in Iran. The methodology demonstrated here has allowed the prediction of production several months before harvest. Moreover, the predictive models constructed have explained 89% of the temporal variability of wheat production. This method could be very efficient for managing crop production. Moreover, having clear prediction, decision makers can plan better for overcoming drought impacts to reduce crop uncertainty for farmers in insurance companies.     

Water Management Applications for Satellite Precipitation Products: Synthesis and Recommendations

This article is an assessment of the current state of the art and relative utility of satellite precipitation products (SPPs) for hydrologic applications to support water management decisions. We present a review of SPPs, their accuracy in diverse settings including the influence of geography, topography, and weather systems, as well as the pros and cons of their use for different water management applications. At the end of this broad synthesizing effort, recommendations are proposed for: (1) SPP developers to improve the quality, usability, and relevance of precipitation products; and (2) SPP users to improve the reliability of their predictions and hydrologic applications to better support water management.     

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.     

PREDICTIVE MODELS FOR GREAT LAKES HYDROLOGY1

ABSTRACT: The individual hydrologic components are assumed to be normally distributed for each month and linear regression equations are estimated for predicting the value of the individual monthly hydrologic components. It is shown that some of the hydrologic components for downwind (in this case downstream) lakes are dependent upon hydrologic events for the upwind lakes. This is particularly so for precipitation in the downwind lake basins which appears to be dependent upon evaporation values for upwind lakes.     

USE OF CLIMATE PREDICTIONS TO DECIDE A WATER MANAGEMENT PROBLEM1

ABSTRACT: Seasonal precipitation predictions were utilized in a water management decision with major economic, societal, and political ramifications. A summer (1984) drought had created a situation calling for possible fall season use of state waters from two major multipurpose reservoirs with an ensuing effect on water price negotiations. Choices facing management and use of water from the reservoirs were to invoke expensive water restrictions with a 33 percent chance of being right, do nothing (66 percent chance of wrong outcome), or use the precipitation predictors (for above normal fall rain) having a 50 percent chance of error. Hydrologists chose to follow the precipitation predictions, which proved to be accurate for the fall of 1984, helping to reveal the long-term value of using well understood climate predictions in water management.     

Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

ON PRECIPITATION SENSOR NETWORK DENSITIES FOR EVALUATING WINTERTIME OROGRAPHIC CLOUD SEEDING EXPERIMENTS1

Principal component analysis is used to investigate density requirements of wintertime orographic cloud seeding experiment precipitation sensor networks. Three passes in the vicinity of Climax, Colorado are studied. The eighteen or more evenly spaced precipitation sensors of each pass are almost completely described by three principal components. These three principal components appear to represent (i) mean precipitation, (ii) slope orientation to storm systems, and (iii) elevation. Evaluation of these principal components is implemented with two distribution-free tests, a proportionality test and the runs test. The results of this study suggest that the loss of experimental information caused by low density precipitation sensor networks may be of little consequence.     

Evaluating and Extending CLIGEN Precipitation Generation for the Loess Plateau of China1

Abstract: Climate generator (CLIGEN) is widely used in the United States to generate long‐term climate scenarios for use with agricultural systems models. Its applicability needs to be evaluated for use in a new region or climate. The objectives were to: (1) evaluate the reproducibility of the latest version of CLIGEN v5.22564 in generating daily, monthly, and yearly precipitation depths at 12 stations, as well as storm patterns including storm duration (D), relative peak intensity (ip), and peak intensity (rp) at 10 stations dispersed across the Loess Plateau and (2) test whether an exponential distribution for generating D and a distribution‐free approach for inducing desired rank correlation between precipitation depth and D can improve storm pattern generations. Mean absolute relative errors (MAREs) for simulating daily, monthly, annual, and annual maximum daily precipitation depth across all 12 stations were 3.5, 1.7, 1.7, and 5.0% for the mean and 5.0, 4.5, 13.0, and 13.6% for the standard deviations (SD), respectively. The model reproduced the distributions of monthly and annual precipitation depths well (p > 0.3), but the distribution of daily precipitation depth was less well produced. The first‐order, two‐state Markov chain algorithm was adequate for generating precipitation occurrence for the Loess Plateau of China; however, it underpredicted the longest dry periods. The CLIGEN‐generated storm patterns poorly. It underpredicted mean and SD of D for storms ≥10 mm by ?60.4 and ?72.6%, respectively. Compared with D, ip, and rp were slightly better reproduced. The MAREs of mean and SD were 21.0 and 52.1% for ip, and 31.2 and 55.2% for rp, respectively. When an exponential distribution was used to generate D, MAREs were reduced to 2.6% for the mean and 7.8% for the SD. However, ip estimation became much worse with MAREs being 128.9% for the mean and 241.1% for the SD. Overall, storm pattern generation needs improvement. For better storm pattern generation for the region, precipitation depth, D, and rp may be generated correlatively using Copula methods.     

A 396-YEAR RECONSTRUCTION OF PRECIPITATION IN SOUTHERN JORDAN1

ABSTRACT: Water resources are the lifeblood of the Near East region. Careful planning and management of water resources in dry land regions requires information on the likelihood of extreme events, especially prolonged drought. It is essential to understand the variability of climate on time scales of decades to centuries to assign reasonable probabilities to such events. Tree-ring analysis is one way to increase our knowledge of the climate variability beyond the short period covered by the instrumental data. In this paper, we reconstruct October-May precipitation from a Juniperus phoenicia tree-ring chronology in southern Jordan to gain a long-term (A.D. 1600–1995) perspective on runs of dry years and on time series fluctuations in precipitation averaged over several years. The reconstruction equation derived by regression of log-transformed precipitation on tree-ring indices explains 44 percent of the variance of observed precipitation. The longest reconstructed drought, as defined by consecutive years below a threshold of 217.4 mm, was four years, compared with three years for the 1946–95 instrumental data. A Monte Carlo analysis designed to account for uncertainty in the reconstruction indicates a lower than 50 percent chance that the region has experienced drought longer than five years in the past 400 years.