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.     

Agricultural Adaptation to Drought for Different Cropping Systems in Southern China under Climate Change

This study investigates agricultural adaptation to drought for different cropping systems in southern China. The study area was divided into three regions: South China (SC), South of the Yangtze River (SYR), and Southwest China (SWC). An index of agricultural adaptation to drought (D) was established. Our findings indicated that the average total crop water demand varied greatly among the regions from 1961 to 2010 in southern China. The maximum value was found in the SC region, followed by the SYR and SWC regions. The effects of droughts on different crops were noticeable. Frequent droughts were recorded in late rice than in early rice in the SC and SYR regions. Droughts in the SWC region mainly affected winter wheat. Moreover, the effects of droughts on crops varied during different growth stages. More frequent and serious droughts occurred during the crop critical flowering stage. Particularly, the frequency of moderate and severe droughts for late rice in the SYR region was 62% during the critical flowering stage. For the SC and SYR regions, the D values of early rice (0.29 and 0.29) were lower than that of late rice (0.31 and 0.33), respectively. For the SWC region, the D values of winter wheat and rice were both low, with averages of 0.16 and 0.29, respectively. Our study provides interesting insights for improving the drought defense abilities for different cropping systems by changing crop planting proportion on a regional scale in China.     

The 2007‐2009 Drought in Athens,Georgia, United States: A Climatological Analysis and an Assessment of Future Water Availability1

Campana, Pete, John Knox, Andrew Grundstein, and John Dowd, 2012. The 2007‐2009 Drought in Athens, Georgia, United States: A Climatological Analysis and an Assessment of Future Water Availability. Journal of the American Water Resources Association (JAWRA) 48(2): 379‐390. DOI: 10.1111/j.1752‐1688.2011.00619.x Abstract: Population growth and development in many regions of the world increase the demand for water and vulnerability to water shortages. Our research provides a case study of how population growth can augment the severity of a drought. During 2007‐2009, a drought event that caused extreme societal impacts occurred in the Athens, Georgia region (defined as Clarke, Barrow, Oconee, and Jackson counties). An examination of drought indices and precipitation records indicates that conditions were severe, but not worse than during the 1925‐1927, 1954‐1956, and 1985‐1987 drought events. A drought of similar length to the 2007‐2009 drought would be expected to occur approximately every 25 years. Streamflow analysis shows that discharge levels in area streams were at a record low during 2007 before water restrictions were implemented, because of greater water usage caused by recent population increases. These population increases, combined with a lack of water conservation, led to severe water shortages in the Athens region during late 2007. Only after per capita usage decreased did water resources last despite continuing drought conditions through 2009. Retaining mitigation strategies and withdrawal levels such as seen during the height of the drought will be an essential strategy to prevent water shortages during future extreme drought events. The key mitigation strategy, independent local action to restrict water use in advance of state‐level restrictions, is now prohibited by Georgia State Law.     

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.     

Five Hundred Years of Hydrological Drought in the Upper Colorado River Basin1

Abstract: This article evaluates drought scenarios of the Upper Colorado River basin (UCRB) considering multiple drought variables for the past 500 years and positions the current drought in terms of the magnitude and frequency. Drought characteristics were developed considering water‐year data of UCRB’s streamflow, and basin‐wide averages of the Palmer Hydrological Drought Index (PHDI) and the Palmer Z Index. Streamflow and drought indices were reconstructed for the last 500 years using a principal component regression model based on tree‐ring data. The reconstructed streamflow showed higher variability as compared with reconstructed PHDI and reconstructed Palmer Z Index. The magnitude and severity of all droughts were obtained for the last 500 years for historical and reconstructed drought variables and ranked accordingly. The frequency of the current drought was obtained by considering two different drought frequency statistical approaches and three different methods of determining the beginning and end of the drought period (annual, 5‐year moving, and ten year moving average). It was concluded that the current drought is the worst in the observed record period (1923‐2004), but 6th to 14th largest in terms of magnitude and 1st to 12th considering severity in the past 500 years. Similarly, the current drought has a return period ranging from 37 to 103 years based on how the drought period was determined. It was concluded that if the 10‐year moving average is used for defining the drought period, the current drought appears less severe in terms of magnitude and severity in the last 500 years compared with the results using 1‐ and 5‐year averages.     

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.     

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.     

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.     

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.     

Crop biodiversity,productivity and production risk: Panel data micro‐evidence from Ethiopia

This paper uses data from the Central Highlands of Ethiopia to assess the productivity and production risk impacts of crop diversification. Using count index as a measure of crop biodiversity, results show that increasing crop biodiversity contributes positively to farm level productivity. In addition, the findings suggest that the level of production risk significantly responds to the level of diversity, with the effect highly conditional on the skewness. The major contribution of the paper is that, unlike previous similar studies that tended to focus on intra‐crop diversity, it incorporates the mutual interdependencies across crops within a farm by focusing on inter‐crop diversity. Hence the study adds to the growing empirical literature, particularly in Africa, that tests empirical relationships between productivity, risk and crop diversity. An important policy implication for a diversity rich country such as Ethiopia is that agro‐biodiversity can be used to improve agricultural productivity while promoting in situ conservation.     

Consideration of User Needs and Spatial Accuracy in Drought Mapping1

Abstract: The increasing availability of web mapping tools creates new opportunities to bridge decision‐makers’ climate information needs with technical capabilities. These new tools, however, raise familiar, unresolved issues related to cartographic representation. Using an on‐line drought mapping tool, this study seeks to understand which spatial unit best meets the desire drought managers have for “local” information, their comprehension of uncertainties introduced in mapping information at local scales, and their willingness to trade off accuracy for information at a desired unit. We found that the most useful local map information includes regional context and boundaries which present their local area of interest. Even among this experienced, well‐educated, professional group, those who had not taken a GIS or cartography class did not fully recognize the role of interpolation in creating and introducing uncertainty to some drought maps. Those who did recognize the uncertainty introduced by interpolation still strongly favored maps that provided estimated values for all areas vs. station point accuracy. Mapping poses a unique set of challenges to communicating risk and uncertainty. As more decision‐support efforts incorporate web mapping, greater attention is needed to assure that users understand the tradeoffs between accuracy and precision in creating local information, the imprecision of boundaries, as well as the limits of forecasts. Clearly conveying spatial accuracy and uncertainty is a challenge that merits greater attention in using maps to communicate drought and other environmental risk information.     

Analysis and Predictive Models of Single‐Family Customer Response to Water Curtailments During Drought1

Polebitski, Austin S. and Richard N. Palmer, 2012. Analysis and Predictive Models of Single‐Family Customer Response to Water Curtailments During Drought. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/j.1752‐1688.2012.00691.x Abstract: This research investigates customer response to demand management strategies during two drought periods in the City of Seattle. An analysis of customer response to voluntary water curtailments is conducted using k‐means clustering to identify like groups of customers and behavior patterns. The clustering method identified important variables (household income, lot size, living space, and family size) useful in determining customer response to water curtailments. Ordinary least squares and spatial lag regression models are estimated using the first and second principal components of variables identified in the clustering analysis. Larger values of income, lot size, and living space enhanced water reductions whereas larger family size tended to reduce the effectiveness of curtailments. Projections of changes in Seattle’s built environment and demographics between 2000 and 2030 were obtained from an urban simulation model (UrbanSim) and were processed through the regression models to investigate changes in future curtailment effectiveness. This research found that increasing household size hardened demands (decreased curtailment effectiveness) whereas decreasing household size increased per‐capita curtailment effectiveness. These results suggest that changes in the number of residents within a home is likely to be the most important factor in determining future curtailment effectiveness.     

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.     

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.     

HYDROLOGIC SCENARIOS FOR SEVERE SUSTAINED DROUGHT IN THE SOUTHWESTERN UNITED STATES1

ABSTRACT: This paper considers the risk of drought and develops drought scenarios for use in the study of severe sustained drought in the Southwestern United States. The focus is on the Colorado River Basin and regions to which Colorado River water is exported, especially southern California, which depends on water from the Colorado River. Drought scenarios are developed using estimates of unimpaired historic streamflow as well as reconstructions of streamflow based on tree ring widths. Drought scenarios in the Colorado River Basin are defined on the basis of annual flow at Lees Ferry. The risk, in terms of return period, of the drought scenarios developed, is assessed using stochastic models.     

Analysis of Meteorological Drought Pattern During Different Climatic and Cropping Seasons in Bangladesh

Drought is one of the most frequent natural disasters in Bangladesh which severely affect agro‐based economy and people's livelihood in almost every year. Characterization of droughts in a systematic way is therefore critical in order to take necessary actions toward drought mitigation and sustainable development. In this study, standardized precipitation index is used to understand the spatial distribution of meteorological droughts during various climatic seasons such as premonsoon, monsoon, and winter seasons as well as cropping seasons such as Pre‐Kharif (March‐May), Kharif (May‐October), and Rabi (December‐February). Rainfall data collected from 29 rainfall gauge stations located in different parts of the country were used for a period of 50 years (1961‐2010). The study reveals that the spatial characteristics of droughts vary widely according to season. Premonsoon droughts are more frequent in the northwest, monsoon droughts mainly occur in the west and northwest, winter droughts in the west, and the Rabi and Kharif droughts are more frequent in the north and northwest of Bangladesh. It is expected that the findings of the study will support drought monitoring and mitigation activities in Bangladesh.     

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.     

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.     

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.     

COMPARATIVE STUDY OF DROUGHT PREDICTION TECHNIQUES FOR RESERVOIR OPERATION1

ABSTRACT: Predicting the likelihood of a drought markedly enhances the efficiency of reservoir operations. This study applies the kriging method and time series analysis to predict inflows to Shihmen Reservoir in northern Taiwan. A subsequent reservoir operation simulation is employed to determine the drought lead time (DLT), the time before the onset of a drought. A more efficient reservoir operational strategy can be established with the aid of DLT and the probability of successful drought prediction (P s). Simulation results of reservoir operation over a period of three decades demonstrate that, at one month DLT, the kriging approach achieves 0.86 of P s for moderate droughts and 0.94 of P s for severe droughts. The kriging approach generally outperformed the time series approach in terms of DLT, P s of drought prediction, and the number of correctly predicted drought events.