USE OF THE KRIGING METHOD FOR STUDYING CHARACTERISTICS OF GROUND WATER DROUGHTS1

round water drought events were derived by taking a truncation level through the time series of daily ground water depth that are recorded elevation differences between the water table and land surface at a well site. Droughts of various truncation levels at 70, 80, 90, and 95 percent, were obtained, where a 70 percent truncation level means that 70 percent of ground water depth data are less than or equal to the truncated value. The conditional probability that a drought occurring at a certain truncation level will prolong and advance to that of the next higher level was estimated. The regionalization analysis was conducted assuming that conditional probabilities estimated at selected wells are regionalized variables. Contour lines of conditional probabilities for each truncation level were constructed to express their spatial variability in the region. Estimation errors associated with the regionalization were reasonably small.     

IS IT REALISTIC TO DEFINE A 100-YEAR DROUGHT FOR WATER MANAGEMENT?1

ABSTRACT: The concept of recurrence interval has been used for years in engineering designs. Can the same concept be applied to the drought analysis? This paper uses the plotting position method to define drought of various recurrence intervals based on stream-flow data. The method of truncation level was applied to the same data to examine the defined drought. Based on the method of truncation level, drought duration and its corresponding flow deficit were investigated. Eighteen flow gage stations from the Scioto River Basin in Ohio were selected for the study. The results show that flows of 100-year droughts using the plotting position method are practically nil. On the other hand, flows of droughts using the truncation method are gradually decreasing with an increase in truncation level, where flows of 95 percent are approximately equal to those of two-year droughts defined by the plotting position. It is also shown that there is a strung correlation between drought duration and deficit.     

EVALUATION OF NEXRAD STAGE III PRECIPITATION DATA OVER A SEMIARID REGION1

This study examines NEXRAD Stage III product (hourly, cell size 4 km by 4 km) for its ability in estimating precipitation in central New Mexico, a semiarid area. A comparison between Stage III and a network of gauge precipitation estimates during 1995 to 2001 indicates that Stage III (1) overestimates the hourly conditional mean (CM) precipitation by 33 percent in the monsoon season and 55 percent in the nonmonsoon season; (2) overestimates the hourly CM precipitation for concurrent radar‐gauge pairs (nonzero value) by 13 percent in the monsoon season and 6 percent in the nonmonsoon season; (3) overestimates the seasonal precipitation accumulation by 11 to 88 percent in monsoon season and underestimates by 18 to 89 percent in the nonmonsoon season; and (4) either overestimates annual precipitation accumulation up to 28.2 percent or underestimates it up to 11.9 percent. A truncation of 57 to 72 percent of the total rainfall hours is observed in the Stage III data in the nonmonsoon season, which may be the main cause for both the underestimation of the radar rainfall accumulation and the lower conditional probability of radar rainfall detection in the nonmonsoon season. The study results indicate that the truncation caused loss of small rainfall amounts (events) is not effectively corrected by the real‐time rain gauge calibration that can adjust the rainfall rates but cannot recover the truncated small rainfall events. However, the truncation error in the monsoon season may be suppressed due to the larger rainfall rate and/or combined effect of overestimates by bright band and hail contaminations, virga, advection, etc. In general, improvement in NEXRAD performance since the monsoon season in 1998 is observed, which is consistent with the systematic improvement in the NEXRAD network.     

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.     

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.     

MULTIYEAR DROUGHT SIMULATION1

ABSTRACT: Previous studies on multiyear droughts have often been limited to the analysis of historic annual flow series. A major disadvantage in this approach can be described as the unavailability of long historic flow records needed to obtain a significant number of drought events for the analysis. To overcome this difficulty, the present study proposes to use synthetically generated annual flow series. A methodology is presented to model annual flows based on an analysis of the harmonic and stochastic properties of the observed flows. Once the model is determined, it can be utilized to generate a flow series of desired length so as to include many hydrologic cycles within the process. The key parameter for a successful drought study is the truncation level used to distinguish low flows from high flows. In this paper, a concept of selecting the truncation level is also presented. The drought simulation procedure is illustrated by a case study of the Pequest watershed in New Jersey. For the above watershed, multiyear droughts were derived from both historic and generated flow series. Three important drought parameters, namely, the duration, severity, and magnitude, were determined for each drought event, and their probability distributions were studied. It was found that gamma and log normal probaility functions produce the best fit for the duration and severity, respectively. The derived probability curves from generated flows can be reliably used to predict the longest drought duration and the largest drought severity within a given return period.     

The need for integration of drought monitoring tools for proactive food security management in sub‐Saharan Africa

Reducing the impact of drought and famine remains a challenge in sub‐Saharan Africa despite ongoing drought relief assistance in recent decades. This is because drought and famine are primarily addressed through a crisis management approach when a disaster occurs, rather than stressing preparedness and risk management. Moreover, drought planning and food security efforts have been hampered by a lack of integrated drought monitoring tools, inadequate early warning systems (EWS), and insufficient information flow within and between levels of government in many sub‐Saharan countries. The integration of existing drought monitoring tools for sub‐Saharan Africa is essential for improving food security systems to reduce the impacts of drought and famine on society in this region. A proactive approach emphasizing integration requires the collective use of multiple tools, which can be used to detect trends in food availability and provide early indicators at local, national, and regional scales on the likely occurrence of food crises. In addition, improving the ability to monitor and disseminate critical drought‐related information using available modern technologies (e.g., satellites, computers, and modern communication techniques) may help trigger timely and appropriate preventive responses and, ultimately, contribute to food security and sustainable development in sub‐Saharan Africa.     

REGIONAL FREQUENCY ANALYSIS OF HYDROLOGIC MULTIYEAR DROUGHTS1

This paper is concerned with regional frequency analysis of hydrologic multiyear droughts. A drought event is defined by three parameters: severity, duration, and magnitude. A method is proposed here to standardize drought severities with a duration adjustment to enable comparison among drought events. For purposes of a regional study, the index drought method is selected and applied to standardized droughts to give a regional frequency curve. However, the recurrence intervals of the drought events obtained from index drought method are limited to the historic period of record. Therefore, by taking advantage of random variations of droughts in both time and space, a multivariate simulation model is used to estimate exceedence probabilities associated with regional drought maxima. This method, named the regional extreme drought method, is capable of generating a series of drought events which, although they have not occurred historically, are more severe than historic events. By combining the results of the index drought method and regional extreme drought analysis, a regional drought probability graph is constructed which ranges from severe droughts to more frequent droughts. This procedure is applied to the mean annual flow records of streams located in the San Joaquin Valley of California, and drought-severity-frequency plots are prepared for 1-year, 2-year, and 3-year durations.     

IMPACT OF DROUGHT ON QUALITY OF POTENTIAL WATER SUPPLY SOURCES IN THE SANGAMON RIVER BASIN1

ABSTRACT: The analysis of stream flow and several water quality parameters in six Illinois rivers showed both deterioration and improvement in quality indicators during 1976–1977 drought. The adverse impacts were an increase of ammonia and manganese concentrations and, to a lesser degree, increased concentrations of phenol and specific conductance. At the worst point during the drought, the 12-month moving average of monthly ammonia concentration in the Sangamon River was about 620 percent higher than the antecedent value. On the other hand, average concentrations of nitrites and nitrates, total iron, and the number of coliform bacteria significantly decreased. This positive response suggests that streams which are considered unsuitable for municipal supply due to high levels of these quality indicators may be used as emergency sources during droughts.     

EFFECTIVENESS OF DROUGHT POLICIES FOR MUNICIPAL WATER MANAGEMENT1

During the 1976–77 drought, three principal mechanisms were used to reduce water use in Utah communities: price increases, maximum monthly use restrictions, and restrictions on outdoor watering times. A regression model was developed to explain observed changes in water use, with price, type of restriction, household size, and summer rainfall as independent variables. For an average system, a 1 percent increase in price would reduce water use by 0.07 to 0.09 percent. A 1 percent increase in outdoor watering time restriction reduces use by 0.064 to 0.075 percent. A 1 percent increase in quantity restrictions leads to a reduction in water use of 0.014 to 0.054 percent. The effectiveness of rationing policies is influenced by system characteristics. For example, outdoor watering time restrictions were less effective in systems with above average household size and below average monthly use.     

AN EARLY WARNING SYSTEM FOR DROUGHT MANAGEMENT USING THE PALMER DROUGHT INDEX1

ABSTRACT: The Palmer Drought Severity Index (PDSI) is used in a non-homogeneous Markov chain model to characterize the stochastic behavior of drought. Based on this characterization an early warning system in the form of a decision tree enumerating all possible sequences of drought progression is proposed for drought management. Besides yielding probabilities of occurrence of different drought severity classes, the method associates a secondary measure in terms of likely cumulative precipitation deficit to provide timely guidance in deciding drought mitigation actions. The proposed method is particularly useful for water availability task forces in various states for issuing drought warnings in advance. The applicability of the technique is illustrated for the Tidewater climatic division of Virginia.     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.     

REGION OF INFLUENCE REGRESSION FOR ESTIMATING THE 50-YEAR FLOOD AT UNGAGED SITES1

ABSTRACT: Five methods of developing regional regression models to estimate flood characteristics at ungaged sites in Arkansas are examined. The methods differ in the manner in which the State is divided into subregions. Each successive method (A to E) is computationally more complex than the previous method. Method A makes no subdivision. Methods B and C define two and four geographic subregions, respectively. Method D uses cluster/discriminant analysis to define subregions on the basis of similarities in watershed characteristics. Method E, the new region of influence method, defines a unique subregion for each ungaged site. Split-sample results indicate that, in terms of root-mean-square error, method E (38 percent error) is best. Methods C and D (42 and 41 percent error) were in a virtual tie for second, and methods B (44 percent error) and A (49 percent error) were fourth and fifth best.     

Enhancing the Ability of a Soil Moisture‐based Index for Agricultural Drought Monitoring by Incorporating Root Distribution

Agricultural drought differs from meteorological, hydrological, and socioeconomic drought, being closely related to soil water availability in the root zone, specifically for crop and crop growth stage. In previous studies, several soil moisture indices (e.g., the soil moisture index, soil water deficit index) based on soil water availability have been developed for agricultural drought monitoring. However, when developing these indices, it was generally assumed that soil water availability to crops was equal throughout the root zone, and the effects of root distribution and crop growth stage on soil water uptake were ignored. This article aims to incorporate root distribution into a soil moisture‐based index and to evaluate the performance of the improved soil moisture index for agricultural drought monitoring. The Huang‐Huai‐Hai Plain of China was used as the study area. Overall, soil moisture indices were significantly correlated with the crop moisture index (CMI), and the improved root‐weighted soil moisture index (RSMI) was more closely related to the CMI than averaged soil moisture indices. The RSMI correctly identified most of the observed drought events and performed well in the detection of drought levels. Furthermore, the RSMI had a better performance than averaged soil moisture indices when compared to crop yield. In conclusion, soil moisture indices could improve agricultural drought monitoring by incorporating root distribution.     

DROUGHT INDICATORS AND TRIGGERS: A STOCHASTIC APPROACH TO EVALUATION1

ABSTRACT: Drought management depends on indicators to detect drought conditions, and triggers to activate drought responses. But determining those indicators and triggers presents challenges. Indicators often lack spatial and temporal transferability, comparability among scales, and relevance to critical drought impacts. Triggers often lack statistical integrity, consistency among drought categories, and correspondence with desired management goals. This article presents an approach for developing and evaluating drought indicators and triggers, using a probabilistic framework that offers comparability, consistency, and applicability. From that, a multistate Markov model investigates the stochastic behavior of indicators and triggers, including transitioning, duration, and frequency within drought categories. This model is applied to the analysis of drought in the Apalachicola‐Chattahoochee‐Flint River Basin in the southeastern United States, using indicators of the Standardized Precipitation Index (for 3, 6, 9, and 12 months), the Palmer Drought Severity Index, and the Palmer Hydrologic Drought Index. The analysis revealed differences among the performance of indicators and their trigger thresholds, which can influence drought responses. Results contribute to improved understanding of drought phenomena, statistical methods for indicators and triggers, and insights for drought management.     

CLIMATE SCIENCE AND DROUGHT PLANNING: THE ARIZONA EXPERIENCE1

ABSTRACT: In response to recent severe drought conditions throughout the state, Arizona recently developed its first drought plan. The Governor's Drought Task Force focused on limiting the economic and social impacts of future droughts through enhanced adaptation and mitigation efforts. The plan was designed to maximize the use of new, scientific breakthroughs in climate monitoring and prediction and in vulnerability assessment. The long term objective of the monitoring system is to allow for evaluation of conditions in multiple sectors and at multiple scales. Stakeholder engagement and decision support are key objectives in reducing Arizona's vulnerability in light of the potential for severe, sustained drought. The drivers of drought conditions in Arizona include the El Nino‐Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation.     

THE TREE-RING RECORD OF SEVERE SUSTAINED DROUGHT1

ABSTRACT: Frequent and persistent droughts exacerbate the problems caused by the inherent scarcity of water in the semiarid to arid parts of the southwestern United States. The occurrence of drought is driven by climatic variability, which for years before about the beginning of the 20th century in the Southwest must be inferred from proxy records. As part of a multidisciplinary study of the potential hydrologic impact of severe sustained drought on the Colorado River, the physical basis and limitations of tree rings as indicators of severe sustained drought are reviewed, and tree-ring data are analyzed to delineate a “worst-case” drought scenario for the Upper Colorado River Basin (UCRB). Runs analysis of a 121-site tree-ring network, 1600–1962, identifies a four-year drought in the 1660s as the longest-duration large-scale drought in the Southwest in the recent tree-ring record. Longer tree-ring records suggest a much longer and more severe drought in 1579–1598. The regression estimate of the mean annual Colorado River flow for this period is 10.95 million acre-feet, or 81 percent of the long-term mean. The estimated flows for the 1500s should be used with caution in impact studies because sample size is small and some reconstructed values are extrapolations.     

Implications of Land Use Changes on Carbon Dynamics and Sequestration—Evaluation from Forestry Datasets, India

Forests and soils are a major sink of carbon, and land use changes can affect the magnitude of above ground and below ground carbon stores and the net flux of carbon between the land and the atmosphere. Studies on methods for examining the future consequences of changes in patterns of land use change and carbon flux gains importance, as they provide different options for CO₂ mitigation strategies. In this study, a simulation approach combining Markov chain processes and carbon pools for forests and soils has been implemented to study the carbon flows over a period of time. Markov chains have been computed by converting the land use change and forestry data of India from 1997 to 1999 into a matrix of conditional probabilities reflecting the changes from one class at time t to another class time t+1. Results from Markov modeling suggested Indian forests as a potential sink for 0.94 Gt carbon, with an increase in dense forest area of about 75.93 Mha and decrease of about 3.4 Mha and 5.0 Mha in open and scrub forests, if similar land use changes that occurred during 1997–1999 would continue. The limiting probabilities suggested 34.27 percent as dense forest, 6.90 as open forest, 0.4 percent mangrove forest, 0.1 percent scrub and 58 percent as non-forest area. Although Indian forests are found to be a potential carbon sink, analysis of results from transition probabilities for different years till 2050 suggests that, the forests will continue to be a source of about 20.59 MtC to the atmosphere. The implications of these results in the context of increasing anthropogenic pressure on open and scrub forests and their contribution to carbon source from land use change and forestry sector are discussed. Some of the mitigation aspects to reduce greenhouse gas emissions from land use change and forestry sector in India are also reviewed in the study.     

COMPLEMENTING OBJECTIVE PROCEDURES WITH SUBJECTIVE PRIORS IN WATER RESOURCE PLANNING1

A procedure is outlined which allows consideration of both objective and subjective indicators to establish priorities in plan implementation of water resource development. The objective procedure utilizes stepwise multiple discriminant analysis to predict community performance regarding planned project implementation, based on previous project implementation in the Northeast. The subjective procedure incorporates prior probabilities developed by the planner, based on observation and experience gained through the planning process. The proposed analysis could eliminate waste through better allocation of planning funds to implementation studies exhibiting higher probability of early implementation.     

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.