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.     

SACRAMENTO RIVER FLOW RECONSTRUCTED TO A.D. 869 FROM TREE RINGS1

ABSTRACT: A time series of annual flow of the Sacramento River, California, is reconstructed to A.D. 869 from tree rings for a long‐term perspective on hydrologic drought. Reconstructions derived by principal components regression of flow on time‐varying subsets of tree‐ring chronologies account for 64 to 81 percent of the flow variance in the 1906 to 1977 calibration period. A Monte Carlo analysis of reconstructed n‐year running means indicates that the gaged record contains examples of drought extremes for averaging periods of perhaps = 6 to 10 years, but not for longer and shorter averaging periods. For example, the estimated probability approaches 1.0 that the flow in A.D. 1580 was lower than the lowest single‐year gaged flow. The tree‐ring record also suggests that persistently high or low flows over 50‐year periods characterize some parts of the long‐term flow history. The results should contribute to sensible water resources planning for the Sacramento Basin and to the methodology of incorporating tree‐ring data in the assessment of the probability of hydrologic drought.     

IMPLICATIONS OF CLIMATIC VARIABILITY FOR REGULATORY LOW FLOWS IN THE SOUTH PLATTE RIVER BASIN,COLORADO1

ABSTRACT: The maximum concentration of a regulated substance that is allowed in a wastewater effluent usually is determined from the amount of dilution provided by the receiving water. Dilution flow is estimated from historical data by application of statistical criteria that define low flow conditions for regulatory purposes. Such use of historical data implies that the past is a good indicator of future conditions, at least for the duration of a discharge permit. Short records, however, introduce great uncertainty in the estimation of low flows because they are unlikely to capture events with recurrence frequencies of multiple years (e.g., ENSO events or droughts). We conducted an analysis of daily flows at several gages with long records in the South Platte River basin of Colorado. Low flows were calculated for successive time blocks of data (3‐, 5‐, 10‐, and 20‐years), and these were compared with low flows calculated for the entire period of record (> 70 years). In unregulated streams, time blocks of three or five years produce estimates of low flows that are highly variable and consistently greater than estimates derived from a longer period of record. Estimates of low flow from 10‐year blocks, although more stable, differ from the long term estimates by as much as a factor of two because of climate variation. In addition, the hydrographs of most streams in Colorado have been influenced by dams, diversions, or water transfers. These alterations to the natural flow regime shorten the record that is useful for analysis, but also tend to increase the calculated low flows. The presence of an upward trend in low flows caused by water use represents an unanticipated risk because it fails to incorporate societal response to severe drought conditions. Thus, climate variability poses a significant risk for water quality both directly, because it may not be represented adequately in the short periods of the hydrologic record that are typically used in permits, and indirectly, through its potential to cause altered use of water during time of scarcity.     

Identifying and Evaluating a Suitable Index for Agricultural Drought Monitoring in the Texas High Plains

Drought is a complex and highly destructive natural phenomenon that affects portions of the United States almost every year, and severe water deficiencies can often become catastrophic for agricultural production. Evapotranspiration (ET) by crops is an important component in the agricultural water budget; thus, it is advantageous to include ET in agricultural drought monitoring. The main objectives of this study were to (1) conduct a literature review of drought indices with a focus to identify a simple but simultaneously adequate drought index for monitoring agricultural drought in a semiarid region and (2) using the identified drought index method, develop and evaluate time series of that drought index for the Texas High Plains. Based on the literature review, the Standardized Precipitation‐Evapotranspiration Index (SPEI) was found to satisfy identified constraints for assessing agricultural drought. However, the SPEI was revised by replacing reference ET with potential crop ET to better represent actual water demand. Data from the Texas High Plains Evapotranspiration network was used to calculate SPEIs for the major irrigated crops. Trends and magnitudes of crop‐specific, time‐series SPEIs followed crop water demand patterns for summer crops. Such an observation suggests that a modified SPEI is an appropriate index to monitor agricultural drought for summer crops, but it was found to not account for soil water stored during the summer fallow period for winter wheat.     

Building resilience to drought in desertification-prone savannas in Sub-Saharan Africa: The water perspective

Securing sustainable livelihood conditions and reducing the risk of outmigration in savanna ecosystems hosted in the tropical semiarid regions is of fundamental importance for the future of humanity in general. Although precipitation in tropical drylands, or savannas, is generally more significant than one might expect, these regions are subject to considerable rainfall variability which causes frequent periods of water deficiency. This paper addresses the twin problems of “drought and desertification” from a water perspective, focusing on the soil moisture (green water) and plant water uptake deficiencies. It makes a clear distinction between long‐term climate change, meteorological drought, and agricultural droughts and dry spells caused by rainfall variability and land degradation. It then formulates recommendations to better cope with and to build resilience to droughts and dry spells. Coping with desertification requires a new conceptual framework based on green‐blue water resources to identify hydrological opportunities in a sea of constraints. This paper proposes an integrated land/water approach to desertification where ecosystem management supports agricultural development to build social‐ecological resilience to droughts and dry spells. This approach is based on the premise that to combat desertification, focus should shift from reducing trends of land degradation in agricultural systems to water resource management in savannas and to landscape‐wide ecosystem management.     

PREDICTIVE ASSESSMENT OF SEVERITY OF AGRICULTURAL DROUGHTS BASED ON AGRO-CLIMATIC FACTORS1

ABSTRACT: Past historical evidence indicates that droughts have had great impacts on human life. Drought (or scarcity of water) is assessed based on two key factors, namely, the estimated water demand, and the expected water supply. The formulation of these key factors for a region largely depends on the agro-climatic and economic conditions. Consideration of one such key factor is the relationship between the crop yield and water deficit in the assessment and prediction of agricultural droughts. The varying nature of this relationship from crop to crop adds to the complexity of agricultural drought analysis. To overcome this difficulty in analyzing agricultural droughts of a region, it is adequate to consider and place emphasis on a single crop (i.e., an index crop) grown homogeneously over the major area of the region. From one year to another year, the pattern of water requirement during the growing season of an index crop is rather stationary, and the water supply in arid and semi-arid area is mainly from seasonal random precipitation. In a region, grain yield of the index crop and, in turn, assessment of the severity of drought can reasonably be predicted as a function of the time of crop sowing and the distribution of rainfall, provided that temporal and spatial effects of other contributing factors (crop variety, soil fertility status, crop disease, pest control, cultivation practices etc.) on grain yield are considered to be uniformly distributed (i.e., stable). A predictive method of assessing agricultural droughts in an arid area of western India is presented. The major crop (Pearl Millet) of this region is grown from. July through September. The formulation of the proposed predictive method inherently implies that the grain yield of the main crop is a reliable indicator of agricultural drought. In the development of this predictive relationship (i.e., a regression type model) a number of potential yet simple variables affecting the grain yield in the region were investigated. The soil moisture index, although generally considered significant compared to the simple variables, has been found to account for insignificant variation in the grain yield. Results of our investigations suggest that it would be advisable to exclude the soil moisture index variable from the model. The proposed regression model can be used in the prediction of grain yield of the main crop several months ahead of crop harvesting operations and, in turn, the assessment of agricultural drought severity as mild, moderate, or severe. Such an assessment is expected to be helpful to planners for arranging appropriate measures to effectively combat agricultural drought situations.     

The Role of Climate and Human Influences in the Dry‐Up of the Jinci Springs,China1

Abstract: One of the largest karst springs in North China, the Jinci Springs, dried up and has remained dry since 1994. We develop a correlation analysis with time‐lag and a regression analysis with time‐lag to study the relation between spring flow and precipitation. This allows us to obtain a better understanding of karst hydrological processes by differentiating the contribution of variation in precipitation from anthropogenic impacts on the dry‐up of Jinci Springs. We divided the karstic hydrological processes into two phases: pre‐1961 and post‐1961. In the first phase (i.e., 1954‐1960) the groundwater recharge was affected by precipitation alone, and in the second phase (i.e., 1961‐1994) the groundwater recharge was influenced by both precipitation and human activities. Using precipitation and groundwater recharge data in the first phase, we set up a groundwater recharge model with time‐lags. By running the time‐lags model, we acquired the groundwater recharge likely to occur under the sole effect of precipitation in the second phase. Using a water‐balance calculation, we conclude that the groundwater recharge exhibited statistical stationarity, and the Jinci Springs dry‐up was the result of anthropogenic activities. At least three specific types of anthropogenic activities contributed to the drying‐up of Jinci Springs: (1) groundwater pumping accounts for 51%, (2) the dewatering from coal mining accounts for 33%, (3) and dam‐building 14%. The drying‐up of Jinci Springs meant that the groundwater drained from the aquifer’s fractures, and subsequently changed the structure of the karst aquifer. Although groundwater exploitation has been reduced, the flow at Jinci Springs has not reoccurred.     

TREE RING RECONSTRUCTIONS OF STREAMFLOW FOR THREE CANADIAN PRAIRIE RIVERS1

ABSTRACT: Information regarding long term hydrological variability is critical for the effective management of surface water resources. In the Canadian Prairie region, growing dependence on major river systems for irrigation and other consumptive uses has resulted in an increasing vulnerability to hydrological drought and growing interprovincial tension. This study presents the first dendrochronological records of streamflow for Canadian Prairie rivers. We present 1,113‐year, 522‐year, and 325‐year reconstructions of total water year (October to September) streamflow for the North Saskatchewan, South Saskatchewan, and Saskatchewan Rivers, respectively. The reconstructions indicate relatively high flows during the 20th Century and provide evidence of past prolonged droughts. Low flows during the 1840s correspond with aridity that extended over much of the western United States. Similarly, an exceptional period of prolonged low flow conditions, approximately 900 A.D. to 1300 A.D., is coincident with evidence of sustained drought across central and western North America. The 16th Century megadrought of the western United States and Mexico, however, does not appear to have had a major impact on the Canadian rivers. The dendrohydrological records illustrate the risks involved if future water policy and infrastructure development in the Canadian Prairies are based solely on records of streamflow variability over the historical record.     

Comparison of Field Performance of Multiple Soil Moisture Sensors in a Semi‐Arid Rangeland1

Abstract:  Automated electronic soil moisture sensors, such as time domain reflectometry (TDR) and capacitance probes are being used extensively to monitor and measure soil moisture in a variety of scientific and land management applications. These sensors are often used for a wide range of soil moisture applications such as drought forage prediction or validation of large‐scale remote sensing instruments. The convergence of three different research projects facilitated the evaluation and comparison of three commercially available electronic soil moisture probes under field application conditions. The sensors are all installed in shallow soil profiles in a well instrumented small semi‐arid shrub covered subwatershed in Southeastern Arizona. The sensors use either a TDR or a capacitance technique; both of which indirectly measure the soil dielectric constant to determine the soil moisture content. Sensors are evaluated over a range of conditions during three seasons comparing responses to natural wetting and drying sequences and using water balance and infiltration simulation models. Each of the sensors responded to the majority of precipitation events; however, they varied greatly in response time and magnitude from each other. Measured profile soil moisture storage compared better to water balance estimates when soil moisture in deeper layers was accounted for in the calculations. No distinct or consistent trend was detected when comparing the responses from the sensors or the infiltration model to individual precipitation events. The results underscore the need to understand how the sensors respond under field application and recognize the limitations of soil moisture sensors and the factors that can affect their accuracy in predicting soil moisture in situ.     

Assessment of Future Drought Conditions in the Chesapeake Bay Watershed

Impacts of climate change on the severity and intensity of future droughts can be evaluated based on precipitation and temperature projections, multiple hydrological models, simulated hydrometeorological variables, and various drought indices. The objective of this study was to assess climate change impacts on future drought conditions and water resources in the Chesapeake Bay (CB) watershed. In this study, the Soil and Water Assessment Tool (SWAT) and the Variable Infiltration Capacity model were used to simulate a Modified Palmer Drought Severity Index (MPDSI), a Standardized Soil Moisture index (SSI), a Multivariate Standardized Drought Index (MSDI), along with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for both historical and future periods (f1: 2020‐2049, f2: 2050‐2079). The results of the SSI suggested that there was a general increase in agricultural droughts in the entire CB watershed because of increases in surface and groundwater flow and evapotranspiration. However, MPDSI and MSDI showed an overall decrease in projected drought occurrences due to the increases in precipitation in the future. The results of this study suggest that it is crucial to use multiple modeling approaches with specific drought indices that combine the effects of both precipitation and temperature changes.     

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.     

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.     

DROUGHT EFFECTS ON WATER QUALITY IN THE SOUTH PLATTE RIVER BASIN,COLORADO1

ABSTRACT: Twenty‐three stream sites representing a range of forested, agricultural, and urban land uses were sampled in the South Platte River Basin of Colorado from July through September 2002 to characterize water quality during drought conditions. With a few exceptions, dissolved ammonia, Kjeldahl nitrogen, total phosphorus, and dissolved orthophosphate concentrations were similar to seasonal historical levels in all land use areas during the drought. At some agricultural sites, decreased dilution of irrigation return flow may have contributed to higher concentrations of some nutrient species, increased primary productivity, and higher dissolved oxygen concentrations. At some urban sites, decreased dilution of base flow and wastewater treatment plant effluent may have contributed to higher dissolved nitrite‐plus‐nitrate concentrations, increased primary productivity, and higher dissolved oxygen concentrations. Total pesticide concentrations in urban and agricultural areas were not consistently higher or lower during the drought. At most forested sites, decreased dilution of ground water‐derived calcium bicarbonate type base flow likely led to elevated pH and specific‐conductance values. Water temperatures at many of the forested sites also were higher, contributing to lower dissolved oxygen concentrations during the drought.     

Statistical and Hybrid Methods Implemented in a Web Application for Predicting Reservoir Inflows during Flood Events

Reservoir management is a critical component of flood management, and information on reservoir inflows is particularly essential for reservoir managers to make real‐time decisions given that flood conditions change rapidly. This study's objective is to build real‐time data‐driven services that enable managers to rapidly estimate reservoir inflows from available data and models. We have tested the services using a case study of the Texas flooding events in the Lower Colorado River Basin in November 2014 and May 2015, which involved a sudden switch from drought to flooding. We have constructed two prediction models: a statistical model for flow prediction and a hybrid statistical and physics‐based model that estimates errors in the flow predictions from a physics‐based model. The study demonstrates that the statistical flow prediction model can be automated and provides acceptably accurate short‐term forecasts. However, for longer term prediction (2 h or more), the hybrid model fits the observations more closely than the purely statistical or physics‐based prediction models alone. Both the flow and hybrid prediction models have been published as Web services through Microsoft's Azure Machine Learning (AzureML) service and are accessible through a browser‐based Web application, enabling ease of use by both technical and nontechnical personnel.     

DROUGHT,TREE RINGS,AND RESERVOIR DESIGN1

Droughts constitute one of the most important factors affecting the design and operation of water resources infrastructure. Hydrologists ascertain their duration, severity, and pattern of recurrence from instrumental records of precipitation or stream‐flow. Under suitable conditions, and with proper analysis, tree rings obtained from long living, climate sensitive species of trees can extend instrumental records of streamflow and precipitation over periods spanning several centuries. Those tree‐ring “reconstructions” provide a valuable insight about climate variability and drought occurrence in the Holocene, and yield long term hydrological data useful in the design of water infrastructure. This work presents a derivation of drought risk based on a renewal model of drought recurrence, a brief review of the basic theory of tree‐ring reconstructions, and a stochastic model for optimizing the design of water supply reservoirs. Examples illustrate the methodology developed in this work and the supporting role that tree‐ring reconstructed streamflow can play in characterizing hydrologic variability.     

Managing Drought Through Water Markets: Farmer Preferences in the Rio Grande Basin1

Abstract: Managing drought in agriculture has taken on growing importance as population growth and environmental concerns place increasing pressures on agricultural water use. One alternative for agricultural water resource management in areas of recurrent drought is allocation through market mechanisms. While past research has aimed to explain why farmers are reluctant to participate in already established water markets, this research seeks to identify the appropriate market mechanism given farmers’ preexisting attitudes toward water markets. Statistical analysis of survey data from 166 farmer interviews in the Rio Grande Basin indicate that farmers are significantly more likely to participate in short‐term water mechanisms, such as spot water markets and water banks than in permanent transfer mechanisms, particularly those that fully separate water rights from land. In sharp contrast to expectations, the choice of market mechanism did not differ significantly between farmers based on their a priori intention to buy, sell or both buy and sell in these markets. Choice of market mechanism also did not differ among farmer types although small, lifestyle or hobby farmers clearly preferred spot water markets to other types of short‐term mechanisms. Evaluating these attitudes a priori may help to design more suitable water market mechanisms for the basin.     

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.     

Restoration of Riparian Buffer Function in Reclaimed Surface Mine Soils

Ecosystem processes such as water infiltration and denitrification largely determine how riparian buffers function to protect surface water quality. Reclaimed mine areas offer a unique opportunity to study the restoration of riparian function without the confounding influence of past land use. Between 1980 and 2000 in southern Illinois, agricultural fields with forest buffers were established along three restored stream reaches in reclaimed mine land. Our research objective was to compare common indicators of soil quality (infiltration, soil C and N, bulk density, and soil moisture) between forest and cultivated riparian zones to determine if riparian function was being restored. Soil bulk density was significantly lower in the forest buffers compared to the agricultural fields. The forest buffers had greater soil total C, total N, and moisture levels than agricultural fields likely due to greater organic matter inputs. Soil total C and N levels in forest buffers were positively related to age of restoration, indicating soil quality is gradually being restored in the buffers. Restoration success of riparian buffers should not be estimated by the return of structure alone; it also includes reestablishment of functions such as nutrient cycling and water retention that largely determine water quality benefits. Watershed planning efforts can expect a lag time on the order of decades between riparian restoration activities and surface water quality improvement.     

Spatial Dynamics of Soil Moisture in a Complex Terrain in the Semi‐Arid Loess Plateau Region,China1

Abstract: Soil moisture is an important hydrological variable in reforestation practices in a water‐limited region of the Loess Plateau of northwestern China. The objective of this study was to quantify the spatial dynamics of soil moisture on a complex terrain. During 2004‐2006, a total of 313 sample points in two kinds of grid (2 × 2 m and 20 × 20 m) were arranged for soil moisture measurements (two soil layers: 0‐30 and 30‐60 cm) with Time Domain Reflectometry. The geostatistical properties of soil moisture patterns, the variance and correlation structure of the soil moisture, and the effects of terrain factors on soil moisture were analyzed. The results suggested that our sampling grid captured the spatial variability of soil moisture distributions for this complex terrain. Principal Component Analysis and Cluster Analysis statistics showed that soil moisture decreased as slope gradient increased; that sunny aspects (112.5°‐292.5°) had relatively lower soil moisture than did shady aspects (292.5°‐112.5°); that soil moisture was lowest in the SWW direction and highest in the NWN direction; and that hillslope aspect was the main factor affecting soil moisture in the 0‐ to 30‐cm soil layer, whereas the main factor for the 30‐ to 60‐cm layer was slope gradient. It was found that the relative values of soil moisture for steep slopes (>36%) with shady aspect (292.5°‐112.5°), gentle slopes (<36%) with sunny aspect (112.5°‐292.5°), and steep slopes with sunny aspect were 99, 82, and 80, respectively – assuming a soil moisture value of 100 for gentle slopes with shady aspect. The results of this study are expected to be relevant to and useful for reforestation planning and design, parameterization of distributed hydrology models, and land productivity assessment in the study region.     

Characterization of Drought in the South Atlantic,United States

Drought has been less extensively characterized in the humid South Atlantic compared to the arid western United States. Our objective was to characterize drought in the South Atlantic and to understand whether drought has become more severe in this region over time. Here we used monthly streamflow to characterize hydrological drought. Hydrological drought occurred when streamflow fell below the 20th percentile over three consecutive months and terminated once streamflow remained above the 20th percentile for three consecutive months. We characterized the frequency, duration, magnitude, and severity of events using the above definition. Significant changes in drought characteristics were tested with Mann‐Kendall over three periods: 1930‐2010, 1930‐1969, and 1970‐2010. We show that 71% of drought events were shorter than six months, while 7% were multiyear events. There was little evidence of trends in drought characteristics to support the claim of drought becoming more severe in the South Atlantic over the 20th Century. The one exception was a significant increase in the joint probability of nearby basins being simultaneously in drought conditions in the southern portion of the study area from 1970 to 2010. While drought characteristics have changed little through time, decreasing average streamflow in non drought periods coupled with increasing water demand provide the context within which recent multiyear drought events have produced significant stress on existing water infrastructure.