A Drought Cyberinfrastructure System for Improving Water Resource Management and Policy Making

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir

2015-04-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness, management, and response decision making. This presentation provides an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using both remote sensing observations and model simulations. Designed as a cyberinfrastructure system, GIDMaPS provides drought information based on a wide range of model simulations and satellite observations from different space agencies. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts, and better management and distribution of water resources among and across different users. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is designed to provide drought information for water resource management, and short-term decision making. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The presentation will highlight how this drought cyberinfrastructure system can be used to improve water resource management in California. Furthermore, the presentation provides an overview of the information farmers need for better decision making and how GIDMaPS can be used to improve decision making and reducing drought impacts. Further Reading Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1. Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure System, Eos, Transactions American Geophysical Union, 95(22), 182-183, doi:10.1002/2014EO220002. AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using Standardized Soil Moisture Index: Application to the 2012 United States Drought, Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014.

Towards Remotely Sensed Composite Global Drought Risk Modelling

NASA Astrophysics Data System (ADS)

Dercas, Nicholas; Dalezios, Nicolas

2015-04-01

Drought is a multi-faceted issue and requires a multi-faceted assessment. Droughts may have the origin on precipitation deficits, which sequentially and by considering different time and space scales may impact soil moisture, plant wilting, stream flow, wildfire, ground water levels, famine and social impacts. There is a need to monitor drought even at a global scale. Key variables for monitoring drought include climate data, soil moisture, stream flow, ground water, reservoir and lake levels, snow pack, short-medium-long range forecasts, vegetation health and fire danger. However, there is no single definition of drought and there are different drought indicators and indices even for each drought type. There are already four operational global drought risk monitoring systems, namely the U.S. Drought Monitor, the European Drought Observatory (EDO), the African and the Australian systems, respectively. These systems require further research to improve the level of accuracy, the time and space scales, to consider all types of drought and to achieve operational efficiency, eventually. This paper attempts to contribute to the above mentioned objectives. Based on a similar general methodology, the multi-indicator approach is considered. This has resulted from previous research in the Mediterranean region, an agriculturally vulnerable region, using several drought indices separately, namely RDI and VHI. The proposed scheme attempts to consider different space scaling based on agroclimatic zoning through remotely sensed techniques and several indices. Needless to say, the agroclimatic potential of agricultural areas has to be assessed in order to achieve sustainable and efficient use of natural resources in combination with production maximization. Similarly, the time scale is also considered by addressing drought-related impacts affected by precipitation deficits on time scales ranging from a few days to a few months, such as non-irrigated agriculture, topsoil moisture, wildfire danger, range and pasture conditions and unregulated stream flows. Keywords Remote sensing; Composite Drought Indicators; Global Drought Risk Monitoring.

Investigating Drought Onset, Termination and Recovery According to Water Quality Indicators

NASA Astrophysics Data System (ADS)

Ahmadi, B.; Moradkhani, H.

2016-12-01

Frequency and severity of droughts are increasing globally. Reduced catchment runoff and river flows caused by the meteorological drivers leads to hydrological drought. Hydrological droughts have significant impacts not only on water quantity but also on water quality. In this study, first the onset of historical hydrological droughts is estimated using daily threshold-based indicators. Then drought termination and recovery period in terms of water quantity is analyzed. This is followed by examination of water quality during these detected hydrological droughts. Four water quality parameters, i.e., water temperature, dissolved oxygen, pH and turbidity are investigated over Willamette river basin located in northwestern Oregon in the United States. Drought vulnerability and resiliency are analyzed for the study period. Droughts and the recovery period are found to have significant impact on water quality parameters. Also, the results indicate a deterioration of water quality during droughts and longer drought recovery if water quality indicators are considered in the analysis.

Understanding Atmospheric Anomalies Associated with Seasonal Pluvial-Drought Processes Using Southwest China as an Example

NASA Astrophysics Data System (ADS)

Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.

2017-12-01

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key results include: (1) The net vertical integral of water vapour flux (VIWVF) across the four boundaries may be a feasible indicator of pluvial-drought transition processes over SWC, because its SA-based index is almost consistent with process development. (2) The vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω) also coincides with the pluvial-drought transition processes well, and the SA-based index of regional D show relatively high correlation with the identified processes over SWC. (3) With respect to large-scale anomalies of circulation patterns, a well-organized Eurasian Pattern is one important feature during the pluvial-drought transition over SWC. (4) To explore the possibility of simulating drought development using previous pluvial anomalies, large-scale and regional atmospheric SA-based indices were used. As a whole, when SA-based indices of regional dynamic and water-vapor variables are introduced, simulated drought development only with large-scale anomalies can be improved a lot. (5) Eventually, pluvial-drought transition processes and associated regional atmospheric anomalies over nine Chinese drought study regions were investigated. With respect to regional D, vertically single or double "upper-positive-lower-negative" and "upper-negative-lower-positive" patterns are the most common vertical SA-based patterns during the pluvial and drought parts of transition processes, respectively.

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2018-01-01

Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric-oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric-oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.

RISA progress in the development of drought indicators to support decision making

NASA Astrophysics Data System (ADS)

Close, S.; Simpson, C.

2015-12-01

Communities around the country are increasingly recognizing the need to plan for water shortages and long-term drought. To build preparedness and help communities manage risk, researchers funded by NOAA's National Integrated Drought Information System (NIDIS) Coping with Drought initiative through the Regional Integrated Sciences and Assessments (RISA) program are working to better understand these impacts across the country and work with communities and resource managers to develop adaptation strategies that meet their needs. The Coping with Drought initiative supports research involving the use of climate predictions and forecast information in decision-making across a range of sectors including agriculture, natural and water resources management, and public health. As a component of this initiative, the RISA program supported research and engagement to develop indicators of drought designed to be of most use to managers and planners grappling with severe and in some cases ongoing drought in their regions. Indicators are being developed for coastal ecosystems in the Carolinas, water management in California, and native communities in Arizona. For instance, the California Nevada Applications Program (CNAP) RISA developed a percentile-based indicator system for analyzing historic droughts and characterizing the ongoing California drought. And in the Southwest, the Climate Assessment for the Southwest (CLIMAS) RISA has been working with the Hopi community on drought monitoring and planning to develop the first-ever Hopi Quarterly Drought Status Report which integrates scientific and local knowledge about drought. This presentation will discuss RISA's role in developing drought indicators based on engagement with decision makers and how this work fits into the larger role that RISAs are playing in the development of the NIDIS Regional Drought Early Warning Systems across the U.S.

Assessing Aridity, Hydrological Drought, and Recovery Using GRACE and GLDAS: a Case Study in Iraq

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Almamalachy, Y. S.; Yan, H.; Ahmadalipour, A.; Irannezhad, M.

2016-12-01

Iraq has suffered from several drought events during the period of 2003-2012, which imposed substantial impacts on natural environment and socioeconomic sectors, e.g. lower discharge of Tigris and Euphrates, groundwater depletion and increase in its salinity, population migration, and agricultural degradation. To investigate the aridity and climatology of Iraq, Global Land Data Assimilation System (GLDAS) monthly datasets of precipitation, temperature, and evapotranspiration at 0.25 degree spatial resolution are used. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived monthly Terrestrial Water Storage (TWS) deficit is used as the hydrological drought indicator. The data is available globally at 1 degree spatial resolution. This study aims to monitor hydrological drought and assess drought recovery time for the period of August 2002 until December 2015. Two approaches are implemented to derive the GRACE-based TWS deficit. The first approach estimates the TWS deficit based on the difference from its own climatology, while the second approach directly calculates the deficit from TWS anomaly. Severity of drought events are calculated by integrating monthly water deficit over the drought period. The results indicate that both methods are capable of capturing the severe drought events in Iraq, while the second approach quantifies higher deficit and severity. In addition, two methods are employed to assess drought recovery time based on the estimated deficit. Both methods indicate similar drought recovery times, varying from less than a month to 9 months. The results demonstrate that the GRACE TWS is a reliable indicator for drought assessment over Iraq, and provides useful information to decision makers for developing drought adaptation and mitigation strategies over data-sparse regions.

Drought evolution, severity and trends in mainland China over 1961-2013.

PubMed

Yao, Ning; Li, Yi; Lei, Tianjie; Peng, Lingling

2018-03-01

Droughts have destructive impacts on crop yields and water supplies, and researching droughts is vital for societal stability and human life. This work aimed to assess the spatiotemporal evolution of droughts in mainland China over 1961-2013 using four drought indices. These indices were the percentage of precipitation anomaly (Pa), standard precipitation index (SPI), standard precipitation evapotranspiration index (SPEI) and evaporative demand drought index (EDDI) at multiple timescales ranging from 1-week to 24-month. The variations of the SPI, SPEI and EDDI were compared with historical severe or extreme droughts. The general increases of the Pa, SPI and SPEI, and general decrease of the EDDI, consistently implied an overall relief of drought conditions over 1961-2013. The different drought indices revealed historical drought conditions, including the national extreme droughts in 1961, 1965, 1972, 1978, 1986, 1988, 1992, 1994, 1997, 1999 and 2000, but various drought severity levels were classified for each drought event since the classification standards differed. Although the SPI and SPEI performed better than the EDDI and there were higher correlations between the SPI and the SPEI, all the indices were regional- or station-specific and have identified historical severe or extreme drought events. At shorter timescales, the EDDI revealed earlier onsets and ends of flash droughts, unlike those indicated by the SPI and SPEI. The comparison of the different indices based on the historical drought events confirmed the uses of the Pa, SPI and SPEI for determining continuous droughts and that of the EDDI for identifying flash droughts. Copyright © 2017 Elsevier B.V. All rights reserved.

A quantitative analysis to objectively appraise drought indicators and model drought impacts

NASA Astrophysics Data System (ADS)

Bachmair, S.; Svensson, C.; Hannaford, J.; Barker, L. J.; Stahl, K.

2016-07-01

Drought monitoring and early warning is an important measure to enhance resilience towards drought. While there are numerous operational systems using different drought indicators, there is no consensus on which indicator best represents drought impact occurrence for any given sector. Furthermore, thresholds are widely applied in these indicators but, to date, little empirical evidence exists as to which indicator thresholds trigger impacts on society, the economy, and ecosystems. The main obstacle for evaluating commonly used drought indicators is a lack of information on drought impacts. Our aim was therefore to exploit text-based data from the European Drought Impact report Inventory (EDII) to identify indicators that are meaningful for region-, sector-, and season-specific impact occurrence, and to empirically determine indicator thresholds. In addition, we tested the predictability of impact occurrence based on the best-performing indicators. To achieve these aims we applied a correlation analysis and an ensemble regression tree approach, using Germany and the UK (the most data-rich countries in the EDII) as test beds. As candidate indicators we chose two meteorological indicators (Standardized Precipitation Index, SPI, and Standardized Precipitation Evaporation Index, SPEI) and two hydrological indicators (streamflow and groundwater level percentiles). The analysis revealed that accumulation periods of SPI and SPEI best linked to impact occurrence are longer for the UK compared with Germany, but there is variability within each country, among impact categories and, to some degree, seasons. The median of regression tree splitting values, which we regard as estimates of thresholds of impact occurrence, was around -1 for SPI and SPEI in the UK; distinct differences between northern/northeastern vs. southern/central regions were found for Germany. Predictions with the ensemble regression tree approach yielded reasonable results for regions with good impact data coverage. The predictions also provided insights into the EDII, in particular highlighting drought events where missing impact reports may reflect a lack of recording rather than true absence of impacts. Overall, the presented quantitative framework proved to be a useful tool for evaluating drought indicators, and to model impact occurrence. In summary, this study demonstrates the information gain for drought monitoring and early warning through impact data collection and analysis. It highlights the important role that quantitative analysis with impact data can have in providing "ground truth" for drought indicators, alongside more traditional stakeholder-led approaches.

Understanding Atmospheric Anomalies Associated With Seasonal Pluvial-Drought Processes Using Southwest China as an Example

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2017-11-01

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution or spatial patterns of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key procedures and results include the following: (1) Because regional atmospheric variables are more directly responsible for the transition processes, we investigate it in detail. The temporal evolution of net vertical integral water vapor flux (net VIWVF) across SWC, together with vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω), coincides well with pluvial-drought transition processes. (2) With respect to large-scale circulation patterns, a well-organized Eurasian (EU) Pattern is one important feature during the pluvial-drought transitions over SWC. (3) Based on these large-scale and regional atmospheric anomalous features, relevant SA-based indices were built, to explore the possibility of simulating drought development using previous pluvial anomalies. As a whole, simulated drought development only with SA-based indices of large-scale circulation patterns does not perform well. Further, it can be improved a lot when SA-based indices of regional D and net VIWVF are introduced. (4) In addition, the potential drought prediction using pluvial anomalies, together with the deep understanding of physical mechanisms responsible for pluvial-drought transitions, need to be further explored.

Characterizing Drought Risk Management and Assessing the Robustness of Snowpack-based Drought Indicators in the Upper Colorado River Basin.

NASA Astrophysics Data System (ADS)

Livneh, B.; Badger, A.; Lukas, J.; Dilling, L.; Page, R.

2017-12-01

Drought conditions over the past two decades have arisen during a time of increasing water demands in the Upper Colorado River Basin. The Basin's highly allocated and diverse water systems raise the question of how drought-based information, such as snowpack, streamflow, and reservoir conditions, can be used to inform drought risk management. Like most of the western U.S., snow-water equivalent (SWE) at key dates during the year (e.g., April 1) is routinely used in water resource planning because it is often the highest observed value during the season and it embodies stored water to be released, through melt, during critical periods later in the summer. This presentation will first focus on how water managers on Colorado's Western Slope (a) perceive drought-related risk, (b) use and access drought information, and (c) respond to drought. Preliminary findings will be presented from in-person interviews, document analysis, observations of planning meetings, and other interactions with seven water-management entities across the Western Slope. The second part of the presentation will focus on how the predictive power of snowpack-based drought indicators—identified as the most useful and reliable drought indicator by regional water stakeholders—are expected change in a warmer world, i.e. where expectations are for more rain versus snow, smaller snowpacks, and earlier snowmelt and peak runoff. We will present results from hydrologic simulations using climate projection to examine how a warming climate will affect the robustness of these snowpack-based drought indicators by mid-century.

The European 2015 drought from a hydrological perspective

NASA Astrophysics Data System (ADS)

Laaha, Gregor; Gauster, Tobias; Tallaksen, Lena M.; Vidal, Jean-Philippe; Stahl, Kerstin; Prudhomme, Christel; Heudorfer, Benedikt; Vlnas, Radek; Ionita, Monica; Van Lanen, Henny A. J.; Adler, Mary-Jeanne; Caillouet, Laurie; Delus, Claire; Fendekova, Miriam; Gailliez, Sebastien; Hannaford, Jamie; Kingston, Daniel; Van Loon, Anne F.; Mediero, Luis; Osuch, Marzena; Romanowicz, Renata; Sauquet, Eric; Stagge, James H.; Wong, Wai K.

2017-06-01

In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.

Evaluation of ET-based drought index derived from geostationary satellite data

USDA-ARS?s Scientific Manuscript database

The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle,...

How useful are meteorological drought indicators to assess agricultural drought impacts across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Tanguy, Maliko; Hannaford, Jamie; Stahl, Kerstin

2016-04-01

Drought monitoring and early warning (M&EW) is an important component of agricultural and silvicultural risk management. Meteorological indicators such as the Standardized Precipitation Index (SPI) are widely used in operational M&EW systems and for drought hazard assessment. Meteorological drought yet does not necessarily equate to agricultural drought given differences in drought susceptibility, e.g. crop-specific vulnerability, soil water holding capacity, irrigation and other management practices. How useful are meteorological indicators such as SPI to assess agricultural drought? Would the inclusion of vegetation indicators into drought M&EW systems add value for the agricultural sector? To answer these questions, it is necessary to investigate the link between meteorological indicators and agricultural impacts of drought. Crop yield or loss data is one source of information for drought impacts, yet mostly available as aggregated data at the annual scale. Remotely sensed vegetation stress data offer another possibility to directly assess agricultural impacts with high spatial and temporal resolution and are already used by some M&EW systems. At the same time, reduced crop yield and satellite-based vegetation stress potentially suffer from multi-causality. The aim of this study is therefore to investigate the relation between meteorological drought indicators and agricultural drought impacts for Europe, and to intercompare different agricultural impact variables. As drought indicators we used SPI and the Standardized Precipitation Evaporation Index (SPEI) for different accumulation periods. The focus regarding drought impact variables was on remotely sensed vegetation stress derived from MODIS NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) data, but the analysis was complemented with crop yield data and text-based information from the European Drought Impact report Inventory (EDII) for selected countries. A correlation analysis between meteorological drought indicators and remotely sensed vegetation stress at the EU NUTS3 region level revealed a high correlation between the two types of indicators for many regions; however some spatial variability was observed in (i) strength of correlation, (ii) performance of SPI versus SPEI, and (iii) best linked SPI/SPEI time scale. We additionally explored whether geographic properties like climate, soil texture, land use, and location explain the observed spatial patterns. Our study revealed that climatically dryer areas (water limited) showed high correlations between SPI/SPEI and vegetation stress, whereas the wettest parts of Europe (radiation limited regions) showed negative correlations especially for short accumulation periods, suggesting that for these regions, short droughts could actually be beneficial for vegetation growth. These findings suggest that relying solely on meteorological indicators for agricultural risk assessment in some regions might be inadequate. Overall, such information may help to tailor agricultural drought M&EW systems to specific regions.

InfoSequia: the first operational remote sensing-based Drought Monitoring System of Spain

NASA Astrophysics Data System (ADS)

Contreras, Sergio; Hunink, Johannes E.

2016-04-01

We present a satellite-based Drought Monitoring System that provides weekly updates of maps and bulletins with vegetation drought indices over the Iberian Peninsula. The web portal InfoSequía (http://infosequia.es) aims to complement the current Spanish Drought Monitoring System which relies on a hydrological drought index computed at the basin level using data on river flows and water stored in reservoirs. Drought indices computed by InfoSequia are derived from satellite data provided by MODIS sensors (TERRA and AQUA satellites), and report the relative anomaly observed in the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and in an additive combination of both. Similar to the U.S. Drought Monitoring System by NOAA, the indices include the Vegetation Condition Index (VCI, relative NDVI anomaly), the Temperature Condition Index (TCI, relative LST anomaly) and the Vegetation Health Index (VHI, relative NDVI-LST anomaly). Relative anomalies are codified into four warning levels, and all of them are provided for short periods of time (8-day windows), or longer periods (e.g. 1 year) in order to capture the cumulative effects of droughts in the state variables. Additionally, InfoSequia quantifies the seasonal trajectories of the cumulative deviation of the observed NDVI in relation with the averaged seasonal trajectory observed over a reference period. Through the weekly bulletins, the Drought Monitoring System InfoSequia aims to provide practical information to stakeholders on the sensitivity and resilience of native ecosystems and rainfed agrosystems during drought periods. Also, the remote sensed indices can be used as drought impact indicator to evaluate the skill of seasonal agricultural drought forecasting systems. InfoSequia is partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant.

A Generalized Framework for Different Drought Indices: Testing its Suitability in a Simulation of the last two Millennia for Europe

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Baerenbold, Oliver; Gomez-Navarro, Juan Jose

2016-04-01

Over the past decades, different drought indices have been suggested in the literature. This study tackles the problem of how to characterize drought by defining a general framework and proposing a generalized family of drought indices that is flexible regarding the use of different water balance models. The sensitivity of various indices and its skill to represent drought conditions is evaluated using a regional model simulation in Europe spanning the last two millennia as test bed. The framework combines an exponentially damped memory with a normalization method based on quantile mapping. Both approaches are more robust and physically meaningful compared to the existing methods used to define drought indices. Still, framework is flexible with respect to the water balance, enabling users to adapt the index formulation to the data availability of different locations. Based on the framework, indices with different complex water balances are compared with each other. The comparison shows that a drought index considering only precipitation in the water balance is sufficient for Western to Central Europe. However, in the Mediterranean temperature effects via evapotranspiration need to be considered in order to produce meaningful indices representative of actual water deficit. Similarly, our results indicate that in north-eastern Europe and Scandinavia, snow and runoff effects needs to be considered in the index definition to obtain accurate results.

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

PubMed Central

Maca, Petr; Pech, Pavel

2016-01-01

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons. PMID:26880875

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks.

PubMed

Maca, Petr; Pech, Pavel

2016-01-01

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were derived for the period of 1948-2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

Risk assessment of drought disaster in southern China

NASA Astrophysics Data System (ADS)

Wang, Y.

2015-12-01

Abstract: Drought has become an increasing concern in southern China, but the drought risk has not been adequately studied. This study presents a method for the spatial assessment of drought risk in southern China using a conceptual framework that emphasizes the combined role of hazard, vulnerability, and exposure.A drought hazard map was retrieved with a compound index of meteorological drought method in a GIS environment. Normally, a large variation in the disaster-inducing factor implies a high probability of economic/social losses caused by a drought disaster. The map indicated that areas with a higher risk of drought hazard were mainly distributed in mid-east Yunnan and the basins in eastern Sichuan.The vulnerability indices were based on climate factors as well as land use, geomorphological types, soil properties, and drainage density. The water preserving capability of purple calcareous soil in the basins in Sichuan and mid-east Yunnan, and the lateritic red soil in northeastern Guangdong is relatively weak. The main geomorphological features in Guangxi and Guangdong are hills, which leads to a serious expectation of soil and water losses. Thus, the main areas with a high risk of drought vulnerability are mid-east Yunnan and the basins in eastern Sichuan.The exposure indices were based on population density and agricultural production because population and agriculture experience the main impacts of a drought disaster. Higher exposure indices mean higher economic/social losses due to drought disasters. Areas with high exposure indices were mainly distributed in Guangdong and southern Guangxi.The overall risk was then calculated as the product of the hazard, vulnerability, and exposure. The results indicated a higher risk of drought disaster in the basins in eastern Sichuan,, northeastern Yunnan, and northeastern Guangdong. The main factor influencing the risk of a drought disaster was the hazard, but the vulnerability and exposure also played important roles.

Drought impact functions as intermediate step towards drought damage assessment

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Svensson, Cecilia; Prosdocimi, Ilaria; Hannaford, Jamie; Helm Smith, Kelly; Svoboda, Mark; Stahl, Kerstin

2016-04-01

While damage or vulnerability functions for floods and seismic hazards have gained considerable attention, there is comparably little knowledge on drought damage or loss. On the one hand this is due to the complexity of the drought hazard affecting different domains of the hydrological cycle and different sectors of human activity. Hence, a single hazard indicator is likely not able to fully capture this multifaceted hazard. On the other hand, drought impacts are often non-structural and hard to quantify or monetize. Examples are impaired navigability of streams, restrictions on domestic water use, reduced hydropower production, reduced tree growth, and irreversible deterioration/loss of wetlands. Apart from reduced crop yield, data about drought damage or loss with adequate spatial and temporal resolution is scarce, making the development of drought damage functions difficult. As an intermediate step towards drought damage functions we exploit text-based reports on drought impacts from the European Drought Impact report Inventory and the US Drought Impact Reporter to derive surrogate information for drought damage or loss. First, text-based information on drought impacts is converted into timeseries of absence versus presence of impacts, or number of impact occurrences. Second, meaningful hydro-meteorological indicators characterizing drought intensity are identified. Third, different statistical models are tested as link functions relating drought hazard indicators with drought impacts: 1) logistic regression for drought impacts coded as binary response variable; and 2) mixture/hurdle models (zero-inflated/zero-altered negative binomial regression) and an ensemble regression tree approach for modeling the number of drought impact occurrences. Testing the predictability of (number of) drought impact occurrences based on cross-validation revealed a good agreement between observed and modeled (number of) impacts for regions at the scale of federal states or provinces with good data availability. Impact functions representing localized drought impacts are more challenging to construct given that less data is available, yet may provide information that more directly addresses stakeholders' needs. Overall, our study contributes insights into how drought intensity translates into ecological and socioeconomic impacts, and how such information may be used for enhancing drought monitoring and early warning.

A Remotely Sensed Global Terrestrial Drought Severity Index

NASA Astrophysics Data System (ADS)

Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

2012-12-01

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

A satellite-based drought index describing anomalies in evapotranspiration for global crop monitoring

USDA-ARS?s Scientific Manuscript database

The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle, ...

Extreme Historical Droughts in the South-Eastern Alps — Analyses Based on Standardised Precipitation Index

NASA Astrophysics Data System (ADS)

Brenčič, Mihael

2016-10-01

Droughts are natural phenomena affecting the environment and human activities. There are various drought definitions and quantitative indices; among them is the Standardised Precipitation Index (SPI). In the drought investigations, historical events are poorly characterised and little data are available. To decipher past drought appearances in the southeastern Alps with a focus on Slovenia, precipitation data from HISTALP data repository were taken to identify extreme drought events (SPI ≤ -2.00) from the second half of the 19th century to the present day. Several long-term extreme drought crises were identified in the region (between the years 1888 and 1896; after World War I, during and after World War II). After 1968, drought patterns detected with SPI changed: shorter, extreme droughts with different time patterns appeared. SPI indices of different time spans showed correlated structures in space and between each other, indicating structured relations.

a Process-Based Drought Early Warning Indicator for Supporting State Drought Mitigation Decision

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, D. N.; Pu, B.

2014-12-01

Drought prone states such as Texas requires creditable and actionable drought early warning ranging from seasonal to multi-decadal scales. Such information cannot be simply extracted from the available climate prediction and projections because of their large uncertainties at regional scales and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA national multi-models ensemble experiment (NMME) and the IPCC AR5 (CMIP5) models, are much more reliable for winter and spring than for the summer season for the US Southern Plains. They also show little connection between the droughts in winter/spring and those in summer, in contrast to the observed dry memory from spring to summer over that region. To mitigate the weakness of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies. Based on these key processes and related fields, we have developed a multivariate principle component statistical model to provide a probabilistic summer drought early warning indicator, using the observed or predicted climate conditions in winter and spring on seasonal scale and climate projection for the mid-21stcentury. The summer drought early warning indicator is constructed in a similar way to the NOAA probabilistic predictions that are familiar to water resource managers. The indicator skill is assessed using the standard NOAA climate prediction assessment tools, i.e., the two alternative forced choice (2AFC) and the Receiver Operating Characteristic (ROC). Comparison with long-term observations suggest that this summer drought early warning indicator is able to capture nearly all the strong summer droughts and outperform the dynamic prediction in this regard over the US Southern Plains. This early warning indicator has been used by the state water agency in May 2014 in briefing the state drought preparedness council and will be provided to stake holders through the website of the Texas state water planning agency. We will also present the results of our ongoing work on using NASA satellite based soil moisture and vegetation stress measurements to further improve the reliability of the summer drought early warning indicator.

A vantage from space can detect earlier drought onset: an approach using relative humidity.

PubMed

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-02-25

Each year, droughts cause significant economic and agricultural losses across the world. The early warning and onset detection of drought is of particular importance for effective agriculture and water resource management. Previous studies show that the Standard Precipitation Index (SPI), a measure of precipitation deficit, detects drought onset earlier than other indicators. Here we show that satellite-based near surface air relative humidity data can further improve drought onset detection and early warning. This paper introduces the Standardized Relative Humidity Index (SRHI) based on the NASA Atmospheric Infrared Sounder (AIRS) observations. The results indicate that the SRHI typically detects the drought onset earlier than the SPI. While the AIRS mission was not originally designed for drought monitoring, we show that its relative humidity data offers a new and unique avenue for drought monitoring and early warning. We conclude that the early warning aspects of SRHI may have merit for integration into current drought monitoring systems.

A Vantage from Space Can Detect Earlier Drought Onset: An Approach Using Relative Humidity

PubMed Central

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-01-01

Each year, droughts cause significant economic and agricultural losses across the world. The early warning and onset detection of drought is of particular importance for effective agriculture and water resource management. Previous studies show that the Standard Precipitation Index (SPI), a measure of precipitation deficit, detects drought onset earlier than other indicators. Here we show that satellite-based near surface air relative humidity data can further improve drought onset detection and early warning. This paper introduces the Standardized Relative Humidity Index (SRHI) based on the NASA Atmospheric Infrared Sounder (AIRS) observations. The results indicate that the SRHI typically detects the drought onset earlier than the SPI. While the AIRS mission was not originally designed for drought monitoring, we show that its relative humidity data offers a new and unique avenue for drought monitoring and early warning. We conclude that the early warning aspects of SRHI may have merit for integration into current drought monitoring systems. PMID:25711500

Exploration of Use of Copulas in Analysing the Relationship between Precipitation and Meteorological Drought in Beijing, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Linlin; Wang, Hongrui; Wang, Cheng

Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less

Exploration of Use of Copulas in Analysing the Relationship between Precipitation and Meteorological Drought in Beijing, China

DOE PAGES

Fan, Linlin; Wang, Hongrui; Wang, Cheng; ...

2017-05-16

Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less

Probabilistic drought intensification forecasts using temporal patterns of satellite-derived drought indicators

NASA Astrophysics Data System (ADS)

Park, Sumin; Im, Jungho; Park, Seonyeong

2016-04-01

A drought occurs when the condition of below-average precipitation in a region continues, resulting in prolonged water deficiency. A drought can last for weeks, months or even years, so can have a great influence on various ecosystems including human society. In order to effectively reduce agricultural and economic damage caused by droughts, drought monitoring and forecasts are crucial. Drought forecast research is typically conducted using in situ observations (or derived indices such as Standardized Precipitation Index (SPI)) and physical models. Recently, satellite remote sensing has been used for short term drought forecasts in combination with physical models. In this research, drought intensification was predicted using satellite-derived drought indices such as Normalized Difference Drought Index (NDDI), Normalized Multi-band Drought Index (NMDI), and Scaled Drought Condition Index (SDCI) generated from Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) products over the Korean Peninsula. Time series of each drought index at the 8 day interval was investigated to identify drought intensification patterns. Drought condition at the previous time step (i.e., 8 days before) and change in drought conditions between two previous time steps (e.g., between 16 days and 8 days before the time step to forecast) Results show that among three drought indices, SDCI provided the best performance to predict drought intensification compared to NDDI and NMDI through qualitative assessment. When quantitatively compared with SPI, SDCI showed a potential to be used for forecasting short term drought intensification. Finally this research provided a SDCI-based equation to predict short term drought intensification optimized over the Korean Peninsula.

Comprehensive assessment of drought from 1960 to 2013 in China based on different perspectives

NASA Astrophysics Data System (ADS)

Lai, Wenli; Wang, Hongrui; Zhang, Jie

2017-10-01

Using daily and monthly precipitation data collected from 520 meteorological stations from 1960 to 2013, we compared a widely used drought index, the standardized precipitation index (SPI), with an extreme index, the maximum consecutive dry days index (CDD). Two other homogeneity test methods, namely the Gini coefficient (including both Total-Gini and Wet-Gini) and the precipitation concentration degree (PCD) were also applied to indirectly estimate extreme droughts. The changes in droughts determined using the SPI and the CDD exhibited similar spatial and temporal patterns throughout most parts of China, with the exception of Southwestern China. Comparison of the five indices indicated that Wet-Gini exhibited different or even opposite trends of drought across all of China. Finally, a trend analysis from 2000 to 2013 was applied to perform a regional empirical analysis of a classic extreme drought event in Southwestern China. All indices, except for Wet-Gini, indicated increasing drought risk.

Sensitivity of Drought Processes to Runoff Parameterizations in East Asia with the Community Land Model

NASA Astrophysics Data System (ADS)

Kim, J. B.; Um, M. J.; Kim, Y.

2016-12-01

Drought is one of the most powerful and extensive disasters and has the highest annual average damage among all the disasters. Focusing on East Asia, where over one fifth of all the people in the world live, drought has impacted as well as been projected to impact the region significantly. .Therefore it is critical to reasonably simulate the drought phenomenon in the region and thus this study would focus on the reproducibility of drought with the NCAR CLM. In this study, we examine the propagation of drought processes with different runoff parameterization of CLM in East Asia. Two different schemes are used; TOPMODEL-based and VIC-based schemes, which differentiate the result of runoff through the surface and subsurface runoff parameterization. CLM with different runoff scheme are driven with two atmospheric forcings from CRU/NCEP and NCEP reanalysis data. Specifically, propagation of drought from meteorological, agricultural to hydrologic drought is investigated with different drought indices, estimated with not only model simulated results but also observational data. The indices include the standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI) and standardized soil moisture index (SSMI). Based on these indices, the drought characteristics such as intensity, frequency and spatial extent are investigated. At last, such drought assessments would reveal the possible model deficiencies in East Asia. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180.

a Probability Model for Drought Prediction Using Fusion of Markov Chain and SAX Methods

NASA Astrophysics Data System (ADS)

Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Drought is one of the most powerful natural disasters which are affected on different aspects of the environment. Most of the time this phenomenon is immense in the arid and semi-arid area. Monitoring and prediction the severity of the drought can be useful in the management of the natural disaster caused by drought. Many indices were used in predicting droughts such as SPI, VCI, and TVX. In this paper, based on three data sets (rainfall, NDVI, and land surface temperature) which are acquired from MODIS satellite imagery, time series of SPI, VCI, and TVX in time limited between winters 2000 to summer 2015 for the east region of Isfahan province were created. Using these indices and fusion of symbolic aggregation approximation and hidden Markov chain drought was predicted for fall 2015. For this purpose, at first, each time series was transformed into the set of quality data based on the state of drought (5 group) by using SAX algorithm then the probability matrix for the future state was created by using Markov hidden chain. The fall drought severity was predicted by fusion the probability matrix and state of drought severity in summer 2015. The prediction based on the likelihood for each state of drought includes severe drought, middle drought, normal drought, severe wet and middle wet. The analysis and experimental result from proposed algorithm show that the product of this algorithm is acceptable and the proposed algorithm is appropriate and efficient for predicting drought using remote sensor data.

Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen

2016-07-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Application of NARR-based NLDAS Ensemble Simulations to Continental-Scale Drought Monitoring

NASA Astrophysics Data System (ADS)

Alonge, C. J.; Cosgrove, B. A.

2008-05-01

Government estimates indicate that droughts cause billions of dollars of damage to agricultural interests each year. More effective identification of droughts would directly benefit decision makers, and would allow for the more efficient allocation of resources that might mitigate the event. Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring, and offer many advantages over traditional modeling systems. The recently released North American Regional Reanalysis (NARR) covers the NLDAS domain and provides all fields necessary to force the NLDAS for 27 years. This presents an ideal opportunity to combine NARR and NLDAS resources into an effective real-time drought monitor. Toward this end, our project seeks to validate and explore the NARR's suitability as a base for drought monitoring applications - both in terms of data set length and accuracy. Along the same lines, the project will examine the impact of the use of different (longer) LDAS model climatologies on drought monitoring, and will explore the advantages of ensemble simulations versus single model simulations in drought monitoring activities. We also plan to produce a NARR- and observation-based high quality 27 year, 1/8th degree, 3-hourly, land surface and meteorological forcing data sets. An investigation of the best way to force an LDAS-type system will also be made, with traditional NLDAS and NLDASE forcing options explored. This presentation will focus on an overview of the drought monitoring project, and will include a summary of recent progress. Developments include the generation of forcing data sets, ensemble LSM output, and production of model-based drought indices over the entire NLDAS domain. Project forcing files use 32km NARR model output as a data backbone, and include observed precipitation (blended CPC gauge, PRISM gauge, Stage II, HPD, and CMORPH) and a GOES-based bias correction of downward solar radiation. Multiple LSM simulations have been conducted using the Noah, Mosaic, CLM3, HYSSiB, and Catchment LSMs. These simulations, along with the NARR-based forcing data form the basis for several drought indices. These include standard measures such as the Palmer-type indices, LDAS-type percentile and anomaly values, and CLM3-based vegetation condition index values.

Are the traditional large-scale drought indices suitable for shallow water wetlands? An example in the Everglades.

PubMed

Zhao, Dehua; Wang, Penghe; Zuo, Jie; Zhang, Hui; An, Shuqing; Ramesh, Reddy K

2017-08-01

Numerous drought indices have been developed over the past several decades. However, few studies have focused on the suitability of indices for studies of ephemeral wetlands. The objective is to answer the following question: can the traditional large-scale drought indices characterize drought severity in shallow water wetlands such as the Everglades? The question was approached from two perspectives: the available water quantity and the response of wetland ecosystems to drought. The results showed the unsuitability of traditional large-scale drought indices for characterizing the actual available water quantity based on two findings. (1) Large spatial variations in precipitation (P), potential evapotranspiration (PE), water table depth (WTD) and the monthly water storage change (SC) were observed in the Everglades; notably, the spatial variation in SC, which reflects the monthly water balance, was 1.86 and 1.62 times larger than the temporal variation between seasons and between years, respectively. (2) The large-scale water balance measured based on the water storage variation had an average indicating efficiency (IE) of only 60.01% due to the redistribution of interior water. The spatial distribution of variations in the Normalized Different Vegetation Index (NDVI) in the 2011 dry season showed significantly positive, significantly negative and weak correlations with the minimum WTD in wet prairies, graminoid prairies and sawgrass wetlands, respectively. The significant and opposite correlations imply the unsuitability of the traditional large-scale drought indices in evaluating the effect of drought on shallow water wetlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

2017-09-01

Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.

Investigate the Capabilities of Remotely Sensed Crop Indicators for Agricultural Drought Monitoring in Kansas

NASA Astrophysics Data System (ADS)

Zhang, J.; Becker-Reshef, I.; Justice, C. O.

2013-12-01

Although agricultural production has been rising in the past years, drought remains the primary cause of crop failure, leading to food price instability and threatening food security. The recent 'Global Food Crisis' in 2008, 2011 and 2012 has put drought and its impact on crop production at the forefront, highlighting the need for effective agricultural drought monitoring. Satellite observations have proven a practical, cost-effective and dynamic tool for drought monitoring. However, most satellite based methods are not specially developed for agriculture and their performances for agricultural drought monitoring still need further development. Wheat is the most widely grown crop in the world, and the recent droughts highlight the importance of drought monitoring in major wheat producing areas. As the largest wheat producing state in the US, Kansas plays an important role in both global and domestic wheat markets. Thus, the objective of this study is to investigate the capabilities of remotely sensed crop indicators for effective agricultural drought monitoring in Kansas wheat-grown regions using MODIS data and crop yield statistics. First, crop indicators such as NDVI, anomaly and cumulative metrics were calculated. Second, the varying impacts of agricultural drought at different stages were explored by examining the relationship between the derived indicators and yields. Also, the starting date of effective agricultural drought early detection and the key agricultural drought alert period were identified. Finally, the thresholds of these indicators for agricultural drought early warning were derived and the implications of these indicators for agricultural drought monitoring were discussed. The preliminary results indicate that drought shows significant impacts from the mid-growing-season (after Mid-April); NDVI anomaly shows effective drought early detection from Late-April, and Late-April to Early-June can be used as the key alert period for agricultural drought early warning; and drought occurring in Early-May has the most significant agricultural impacts. This research intends to help prototype an agricultural drought alert system, which could alert crop analysts to agricultural drought vulnerable areas/periods and provide tools for assessing crop outlooks in these regions.

Cloud Computing-based Platform for Drought Decision-Making using Remote Sensing and Modeling Products: Preliminary Results for Brazil

NASA Astrophysics Data System (ADS)

Vivoni, E.; Mascaro, G.; Shupe, J. W.; Hiatt, C.; Potter, C. S.; Miller, R. L.; Stanley, J.; Abraham, T.; Castilla-Rubio, J.

2012-12-01

Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this contribution, we present preliminary results on integrating a set of multi-resolution drought indices into a cloud computing-based visualization platform. We focused our initial efforts on Brazil due to a severe, on-going drought in a large agricultural area in the northeastern part of the country. The online platform includes drought products developed from: (1) a MODIS-based water stress index (WSI) based on inferences from normalized difference vegetation index and land surface temperature fields, (2) a volumetric water content (VWC) index obtained from application of the NASA CASA model, and (3) a set of AVHRR-based vegetation health indices obtained from NOAA/NESDIS. The drought indices are also presented in terms of anomalies with respect to a baseline period. Since our main objective is to engage stakeholders and decision-makers in Brazil, we incorporated other relevant geospatial data into the platform, including irrigation areas, dams and reservoirs, administrative units and annual climate information. We will also present a set of use cases developed to help stakeholders explore, query and provide feedback that allowed fine-tuning of the drought product delivery, presentation and analysis tools. Finally, we discuss potential next steps in development of the online platform, including applications at finer resolutions in specific basins and at a coarser global scale.

[Characteristics and adaptation of seasonal drought in southern China under the background of climate change. V. Seasonal drought characteristics division and assessment in southern China].

PubMed

Huang, Wan-Hua; Sui, Yue; Yang, Xiao-Guang; Dai, Shu-Wei; Li, Mao-Song

2013-10-01

Zoning seasonal drought based on the study of drought characteristics can provide theoretical basis for formulating drought mitigation plans and improving disaster reduction technologies in different arid zones under global climate change. Based on the National standard of meteorological drought indices and agricultural drought indices and the 1959-2008 meteorological data from 268 meteorological stations in southern China, this paper analyzed the climatic background and distribution characteristics of seasonal drought in southern China, and made a three-level division of seasonal drought in this region by the methods of combining comprehensive factors and main factors, stepwise screening indices, comprehensive disaster analysis, and clustering analysis. The first-level division was with the annual aridity index and seasonal aridity index as the main indices and with the precipitation during entire year and main crop growing season as the auxiliary indices, dividing the southern China into four primary zones, including semi-arid zone, sub-humid zone, humid zone, and super-humid zone. On this basis, the four primary zones were subdivided into nine second-level zones, including one semi-arid area-temperate-cold semi-arid hilly area in Sichuan-Yunnan Plateau, three sub-humid areas of warm sub-humid area in the north of the Yangtze River, warm-tropical sub-humid area in South China, and temperate-cold sub-humid plateau area in Southwest China, three humid areas of temperate-tropical humid area in the Yangtze River Basin, warm-tropical humid area in South China, and warm humid hilly area in Southwest China, and two super-humid areas of warm-tropical super-humid area in South China and temperate-cold super-humid hilly area in the south of the Yangtze River and Southwest China. According to the frequency and intensity of multiple drought indices, the second-level zones were further divided into 29 third-level zones. The distribution of each seasonal drought zone was illustrated, and the zonal drought characteristics and their impacts on the agricultural production were assessed. Accordingly, the drought prevention measures were proposed.

The current California drought through EDDI's eyes: early warning and monitoring of agricultural and hydrologic drought with the new Evaporative Demand Drought Index.

NASA Astrophysics Data System (ADS)

Hobbins, M.; McEvoy, D.; Huntington, J. L.; Wood, A. W.; Morton, C.; Verdin, J. P.

2015-12-01

We have developed a physically based, multi-scalar drought index—the Evaporative Demand Drought Index (EDDI)—to improve treatment of evaporative dynamics in drought monitoring. Existing popular drought indices—such as the Palmer Drought Severity Index that informs much of the US Drought Monitor (USDM)—have primarily relyied on precipitation and temperature (T) to represent hydroclimatic anomalies, leaving evaporative demand (E0) most often derived from poorly performing T-based parameterizations then used to derive actual evapotranspiration (ET) from LSMs. Instead, EDDI leverages the inter-relations of E0 and ET, measuring E0's physical response to surface drying anomalies due to two distinct land surface/atmosphere interactions: (i) in sustained drought, limited moisture availability forces E0 and ET into a complementary relation, whereby ET declines as E0 increases; and (ii) in "flash" droughts, E0 increases due to increasing advection or radiation. E0's rise in response to both drought types suggests EDDI's robustness as a monitor and leading indicator of drought. To drive EDDI, we use for E0 daily reference ET from the ASCE Standardized Reference ET equation forced by North American Land Data Assimilation System drivers. EDDI is derived by aggregating E0 anomalies from its long-term mean across a period of interest and normalizing them to a Z-score. Positive EDDI indicates drier than normal conditions (and so drought). We use the current historic California drought as a test-case in which to examine EDDI's performance in monitoring agricultural and hydrologic drought. We observe drought development and decompose the behavior of drought's evaporative drivers during in-drought intensification periods and wetting events. EDDI's performance as a drought leading indicator with respect to the USDM is tested in important agricultural regions. Comparing streamflow from several USGS gauges in the Sierra Nevada to EDDI, we find that EDDI tracks most major hydrologic droughts, with correlations to water-year streamflow that are highest at the 9- to 12-month aggregation periods, and during the summer. EDDI shows significant promise as a leading indicator of drought, thereby providing a valuable planning window for growers and water resource managers.

Dendrochronological assessment of drought severity indices for Panola Mountain Research Watershed, Georgia, U.S.A.

NASA Astrophysics Data System (ADS)

McKee, A.; Aulenbach, B. T.

2015-12-01

Quantifying the relation between drought severity and tree growth is important to predict future growth rates as climate change effects the frequency and severity of future droughts. Two commonly used metrics of drought severity are the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI). These indices are often calculated from proximal weather station data and therefore may not be very accurate at the local watershed scale. The accuracy of these commonly used measures of drought severity was compared to a recently developed, locally calibrated model of water limitation based on the difference between potential and actual evapotranspiration (ETDIFF). Relative accuracies of the drought indices were assessed on the strength of correlations with a 20-year tree-ring index chronology (1986-2006) developed from 22 loblolly pine (Pinus taeda) trees in water-limited landscape positions at the Panola Mountain Research Watershed (PMRW), a 41-hectare forested watershed located in north-central Georgia. We used SPI and PDSI index values from the weather station located at the Atlanta Airport, approximately 36 kilometers from PMRW. ETDIFF was calculated based on precipitation, temperature, runoff, and solar radiation data collected at PMRW. Annual index values for all three drought indices were calculated as the mean value over the growing season (May to September). All three indices had significant Pearson correlations with the tree-ring index (p = 0.044, 0.007, 0.002 for SPI, PDSI, and ETDIFF, respectively). The ETDIFF method had the strongest correlation (R2 = 0.40) compared to SPI and PDSI results (R2 = 0.19 and 0.32, respectively). Results suggest SPI and PDSI provided a general measure of drought conditions, however, the locally calibrated model of water limitation appears to measure drought severity more accurately. Future studies on the ecological effects of drought may benefit from adopting ETDIFF as a measure of drought severity.

How well do meteorological indicators represent agricultural and forest drought across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, S.; Tanguy, M.; Hannaford, J.; Stahl, K.

2018-03-01

Drought monitoring and early warning (M&EW) systems are an important component of agriculture/silviculture drought risk assessment. Many operational information systems rely mostly on meteorological indicators, and a few incorporate vegetation state information. However, the relationships between meteorological drought indicators and agricultural/silvicultural drought impacts vary across Europe. The details of this variability have not been elucidated sufficiently on a continental scale in Europe to inform drought risk management at administrative scales. The objective of this study is to fill this gap and evaluate how useful the variety of meteorological indicators are to assess agricultural/silvicultural drought across Europe. The first part of the analysis systematically linked meteorological drought indicators to remote sensing based vegetation indices (VIs) for Europe at NUTs3 administrative regions scale using correlation analysis for crops and forests. In a second step, a stepwise multiple linear regression model was deployed to identify variables explaining the spatial differences observed. Finally, corn crop yield in Germany was chosen as a case study to verify VIs’ representativeness of agricultural drought impacts. Results show that short accumulation periods of SPI and SPEI are best linked to crop vegetation stress in most cases, which further validates the use of SPI3 in existing operational drought monitors. However, large regional differences in correlations are also revealed. Climate (temperature and precipitation) explained the largest proportion of variance, suggesting that meteorological indices are less informative of agricultural/silvicultural drought in colder/wetter parts of Europe. These findings provide important context for interpreting meteorological indices on widely used national to continental M&EW systems, leading to a better understanding of where/when such M&EW tools can be indicative of likely agricultural stress and impacts.

Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming

NASA Astrophysics Data System (ADS)

Engda, T. A.; Kelleners, T. J.; Paige, G. B.

2013-12-01

Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.

Socioeconomic Drought in a Changing Climate: Modeling and Management

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally, we provide examples of using the proposed modeling framework for analyzing water availability in a changing climate considering local conditions. Reference: Mehran A., Mazdiyasni O., AghaKouchak A., 2015, A Hybrid Framework for Assessing Socioeconomic Drought: Linking Climate Variability, Local Resilience, and Demand, Journal of Geophysical Research, 120 (15), 7520-7533, doi: 10.1002/2015JD023147

Hydrologic Drought in the Colorado River Basin

NASA Astrophysics Data System (ADS)

Timilsena, J.; Piechota, T.; Hidalgo, H.; Tootle, G.

2004-12-01

This paper focuses on drought scenarios of the Upper Colorado River Basin (UCRB) for the last five hundred years and evaluates the magnitude, severity and frequency of the current five-year drought. Hydrologic drought characteristics have been developed using the historical streamflow data and tree ring chronologies in the UCRB. Historical data include the Colorado River at Cisco and Lees Ferry, Green River, Palmer Hydrologic Drought Index (PHDI), and the Z index. Three ring chronologies were used from 17 spatially representative sites in the UCRB from NOAA's International Tree Ring Data. A PCA based regression model procedures was used to reconstruct drought indices and streamflow in the UCRB. Hydrologic drought is characterized by its duration (duration in year in which cumulative deficit is continuously below thresholds), deficit magnitude (the cumulative deficit below the thresholds for consecutive years), severity (magnitude divided by the duration) and frequency. Results indicate that the current drought ranks anywhere from the 5th to 20th worst drought during the period 1493-2004, depending on the drought indicator and magnitude. From a short term perspective (using annual data), the current drought is more severe than if longer term average (i.e., 5 or 10 year averages) are used to define the drought.

Drought characterisation based on an agriculture-oriented standardised precipitation index

NASA Astrophysics Data System (ADS)

Tigkas, Dimitris; Vangelis, Harris; Tsakiris, George

2018-03-01

Drought is a major natural hazard with significant effects in the agricultural sector, especially in arid and semi-arid regions. The accurate and timely characterisation of agricultural drought is crucial for devising contingency plans, including the necessary mitigation measures. Many drought indices have been developed during the last decades for drought characterisation and analysis. One of the most widely used indices worldwide is the Standardised Precipitation Index (SPI). Although other comprehensive indices have been introduced over the years, SPI remains the most broadly accepted index due to a number of reasons, the most important of which are its simple structure and the fact that it uses only precipitation data. In this paper, a modified version of SPI is proposed, namely the Agricultural Standardised Precipitation Index (aSPI), based on the substitution of the total precipitation by the effective precipitation, which describes more accurately the amount of water that can be used productively by the plants. Further, the selection of the most suitable reference periods and time steps for agricultural drought identification using aSPI is discussed. This conceptual enhancement of SPI aims at improving the suitability of the index for agricultural drought characterisation, while retaining the advantages of the original index, including its dependence only on precipitation data. The evaluation of the performance of both SPI and aSPI in terms of correlating drought magnitude with crop yield response in four regions of Greece under Mediterranean conditions indicated that aSPI is more robust than the original index in identifying agricultural drought.

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

Documentary and instrumental-based drought indices for the Czech Lands back to AD 1501

NASA Astrophysics Data System (ADS)

Brázdil, Rudolf; Dobrovolný, Petr; Trnka, Miroslav; Büntgen, Ulf; Řezníčková, Ladislava; Kotyza, Oldřich; Valášek, Hubert; Štěpánek, Petr

2016-04-01

This study addresses the reconstruction of four slightly different drought indices in the Czech Lands (recent Czech Republic) back to 1501 AD. Reconstructed monthly temperatures for central Europe that are representative for the Czech territory, together with reconstructed seasonal precipitation totals from the same area, are used to calculate monthly, seasonal and annual drought indices (SPI, SPEI, Z-index, and PDSI). The resulting time-series reflect interannual-to multi-decadal drought variability. The driest episodes cluster around the beginning and end of the 18th century, while 1540 emerges as a particularly dry extreme year. The temperature-driven dryness of the past three decades is well captured by SPEI, Z-index and PDSI, whereas precipitation totals show no significant trend during this period (as reflected in SPI). Data and methodological uncertainty associated with Czech drought indices, as well as their position in a greater European context, are critically outlined. Further discussion is devoted to comparison with fir tree-rings from southern Moravia and a spatial subset of the "Old World Drought Atlas" (OWDA), which reveals significant correlation coefficients, of around 0.40 and 0.50, respectively. This study introduces a new documentary-based approach for the robust extension of standardized drought indices back into pre-instrumental times, which we also believe has great potential in other parts of the world where high-resolution paleoclimatic insight remains as yet limited.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Estimating drought risk across Europe from reported drought impacts, hazard indicators and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.

2015-12-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment.

Sensitivity analysis of the Commonly Used Drought Indices on the different land use Types - Case Study over Turkey

NASA Astrophysics Data System (ADS)

Ersoy, E. N.; Hüsami Afşar, M.; Bulut, B.; Onen, A.; Yilmaz, M. T.

2017-12-01

Droughts are climatic phenomenon that may impact large and small regions alike for long or short time periods and influence society in terms of industrial, agricultural, domestic and many more aspects. The characteristics of the droughts are commonly investigated using indices like Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). On the other hand, these indices may not necessarily yield similar performance over different vegetation types. The aim is to analyze the sensitivity of drought indices (SPI, SPEI, PDSI) to vegetation types over different climatic regions in Turkey. Here the magnitude of the drought severity is measured using MODIS NDVI data, while the vegetation type (e.g., non-irrigated arable lands, vineyards, fruit trees and berry plantations, olive groves, pastures, land principally occupied by agriculture) information is obtained using CORINE land cover classification. This study has compared the drought characteristics and vegetation conditions on different land use types using remotely sensed datasets (e.g., CORINE land use data, MODIS NDVI), and commonly used drought indices between 2000 and 2016 using gauge based precipitation and temperature measurements.

More than just consumers: Integrating local observations into drought monitoring to better support decision making

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Masayesva, A.; Meadow, A. M.; Crimmins, M.

2016-12-01

Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. In arid and semi-arid regions of the world, this challenge is particularly acute since social-ecological systems are already well-adapted to dry conditions. Understanding what drought means in these regions is an important first step in developing a decision-relevant monitoring system. Traditional drought indices may be of some use, but local observations may ultimately be more relevant for informing difficult decisions in response to unusually dry conditions. This presentation will focus on insights gained from a collaborative project between the University of Arizona and the Hopi Tribe-a Native American community in the U.S. Southwest-to develop a drought information system that is responsive to local needs. The primary goal of the project was to develop a system that: is based on how drought is experienced by Hopi citizens and resource managers, can incorporate local observations of drought impacts as well as conventional indicators, and brings together local expertise with conventional science-based observations. This kind of drought monitoring system can harnesses as much available information as possible to inform resource managers, political leaders, and citizens about drought conditions, but such a system can also engage these local drought stakeholders in observing, thinking about, and helping guide planning for drought.

An agricultural drought index to incorporate the irrigation process and reservoir operations: A case study in the Tarim River Basin

NASA Astrophysics Data System (ADS)

Li, Zehua; Hao, Zhenchun; Shi, Xiaogang; Déry, Stephen J.; Li, Jieyou; Chen, Sichun; Li, Yongkun

2016-08-01

To help the decision making process and reduce climate change impacts, hydrologically-based drought indices have been used to determine drought severity in the Tarim River Basin (TRB) over the past decades. As the major components of the surface water balance, however, the irrigation process and reservoir operations have not been incorporated into drought indices in previous studies. Therefore, efforts are needed to develop a new agricultural drought index, which is based on the Variable Infiltration Capacity (VIC) model coupled with an irrigation scheme and a reservoir module. The new drought index was derived from the simulated soil moisture data from a retrospective VIC simulation from 1961 to 2007 over the irrigated area in the TRB. The physical processes in the coupled VIC model allow the new agricultural drought index to take into account a wide range of hydrologic processes including the irrigation process and reservoir operations. Notably, the irrigation process was found to dominate the surface water balance and drought evolution in the TRB. Furthermore, the drought conditions identified by the new agricultural drought index presented a good agreement with the historical drought events that occurred in 1993-94, 2004, and 2006-07, respectively. Moreover, the spatial distribution of coupled VIC model outputs using the new drought index provided detailed information about where and to what extent droughts occurred.

Understanding Droughts and their Agricultural Impact in North America at the Basin Scale through the Development of Satellite Based Drought Indicators

NASA Astrophysics Data System (ADS)

Munoz Hernandez, A.; Lawford, R. G.

2012-12-01

Drought is a major constraint severely affecting numerous agricultural regions in North America. Decision makers need timely information on the existence of a drought as well as its intensity, frequency, likely duration, and economic and social effects in order to implement adaptation strategies and minimize its impacts. Countries like Mexico and Canada face a challenge associated with the lack of consistent and reliable in-situ data that allows the computation of drought indicators at resolutions that effectively supports decision makers at the watershed scale. This study focuses on (1) the development of near-real time drought indicators at high resolution utilizing various satellite data for use in improving adaptation plans and mitigation actions at the basin level; (2) the quantification of the relationships between current and historical droughts and their agricultural impacts by evaluating thresholds for drought impacts; and (3) the assessment of the effects of existing water policies, economic subsidies, and infrastructure that affect the vulnerability of a particular region to the economic impacts of a drought. A pilot study area located in Northwest Mexico and known as the Rio Yaqui Basin was selected for this study in order to make comparisons between the satellite based indicators derived from currently available satellite products to provide an assessment of the quality of the products generated. The Rio Yaqui Basin, also referred to as the "bread basket" of Mexico, is situated in an arid to semi-arid region where highly sophisticated irrigation systems have been implemented to support extensive agriculture. Although for many years the irrigation systems acted as a safety net for the farmers, recent droughts have significantly impacted agricultural output, affected thousands of people, and increase the dependence on groundwater. The drought indices generated are used in conjunction with a decision-support model to provide information on drought impacts and to identify times when drought intensity has exceeded local index thresholds for drought intensity and impacts on a regional basis. Future work includes the selection of several additional drought-prone areas located in Southwest United States, Northwest Mexico, and the Palliser Triangle in Canada and the comparison of national policies associated with drought mitigation programs.

Multivariate Drought Characterization in India for Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sreekumaran Unnithan, P.; Mondal, A.

2016-12-01

Droughts are one of the most important natural hazards that affect the society significantly in terms of mortality and productivity. The metric that is most widely used by the India Meteorological Department (IMD) to monitor and predict the occurrence, spread, intensification and termination of drought is based on the univariate Standardized Precipitation Index (SPI). However, droughts may be caused by the influence and interaction of many variables (such as precipitation, soil moisture, runoff, etc.), emphasizing the need for a multivariate approach for drought characterization. This study advocates and illustrates use of the recently proposed multivariate standardized drought index (MSDI) in monitoring and prediction of drought and assessing its concerned risk in the Indian region. MSDI combines information from multiple sources: precipitation and soil moisture, and has been deemed to be a more reliable drought index. All-India monthly rainfall and soil moisture data sets are analysed for the period 1980 to 2014 to characterize historical droughts using both the univariate indices, the precipitation-based SPI and the standardized soil moisture index (SSI), as well as the multivariate MSDI using parametric and non-parametric approaches. We confirm that MSDI can capture droughts of 1986 and 1990 that aren't detected by using SPI alone. Moreover, in 1987, MSDI indicated a higher severity of drought when a deficiency in both soil moisture and precipitation was encountered. Further, this study also explores the use of MSDI for drought forecasts and assesses its performance vis-à-vis existing predictions from the IMD. Future research efforts will be directed towards formulating a more robust standardized drought indicator that can take into account socio-economic aspects that also play a key role for water-stressed regions such as India.

Documentary evidence for the study of droughts in the Czech Lands

NASA Astrophysics Data System (ADS)

Řezníčková, Ladislava; Brázdil, Rudolf; Kotyza, Oldřich; Valášek, Hubert

2015-04-01

The study of droughts in the instrumental period can be based on various drought indices calculated usually from precipitation and temperature series. Documentary evidence, overlapping partly also with meteorological measurements, represents another important source utilisable particularly for the pre-instrumental period. Direct reports of drought or indirect indications of its impacts may be found in various individual or institutional sources: narrative written sources (annals, chronicles, commemorative records), weather diaries, personal and official correspondence, stall-keepers' and market songs, journalism, financial-economic records, religious sources (rogations, sermons, praying), special printed sources, chronograms, epigraphic sources ("hunger" stones). Corresponding data indicate directly meteorological drought and with describing of drought impacts also agricultural and hydrological droughts. The first credible direct drought information from the Czech Lands reports not any rain or snowfall during the 1090/1091 winter (Monk of Sázava). But data before AD 1500 are relatively scarce and they are related prevailingly to Bohemia. Density of precipitation/drought documentary records in the Czech Lands increases significantly after 1500. This allows create series of precipitation indices with classification of dry months in the scale -1 as dry, -2 as very dry and -3 as extremely dry month. Such dataset is important for the creation of 500-year Czech drought chronology.

A Five-Year Analysis of MODIS NDVI and NDWI for Rangeland Drought Assessment: Preliminary Results

NASA Astrophysics Data System (ADS)

Gu, Y.; Brown, J. F.; Verdin, J. P.; Wardlow, B.

2006-12-01

Drought is one of the most costly natural disasters in the United States. Traditionally, drought monitoring has been based on weather station observations, which lack the continuous spatial coverage needed to adequately characterize and monitor detailed spatial patterns of drought conditions. Satellite remote sensing observations can provide a synoptic view of the land and provide a spatial context for measuring drought. A common satellite-based index, the normalized difference vegetation index (NDVI) has a 30-year history of use for vegetation condition monitoring. NDVI is calculated from the visible red and near infrared channels and measures the changes in chlorophyll absorption and reflection in the spongy mesophyll of the vegetation canopy that are reflected in these respective bands. The normalized difference water index (NDWI) is another index, derived from the near-infrared and short wave infrared channels, and reflects changes in both the water content and spongy mesophyll in the vegetation canopy. As a result, the NDWI is influenced by both desiccation and wilting in the vegetation canopy and may be a more sensitive indicator than the NDVI for large- area drought monitoring. The objective of this study was to process and evaluate a 5-year history of 500-meter NDVI and NDWI data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument and to investigate methods for measuring and monitoring drought in rangeland over the southern plains of the United States. This initial study included: (1) the development of a climatological database for MODIS NDVI and NDWI, (2) a study of the relationship between the NDVI, NDWI, and drought condition over rangeland, (3) the development of a method to provide threshold NDVI/NDWI values under drought conditions based on the 5-year NDVI/NDWI/drought condition analysis, and (4) the investigation of additional vegetation drought information provided by the NDWI versus the NDVI in a 5-year comparison of the two indices. The MODIS data were obtained from the Land Processes Distributed Active Archive System. Results show strong relationships among NDVI, NDWI, and drought analyzed over grasslands in the Flint Hills region of Kansas and Oklahoma. During the summer months, the average NDVI and NDWI values were consistently lower (NDVI<0.5 and NDWI<0.3) for the tallgrass prairie under drought conditions than under normal climate conditions (NDVI>0.6 and NDWI>0.4). The distinctions between drought conditions and normal climate conditions are based on the historic U.S. Drought Monitor maps and the historic Palmer index data. To take advantage of information contained in both indices, we calculated the difference between NDVI and NDWI (NDVI-NDWI). The difference between NDVI and NDWI slightly increases during the summer drought condition. Based on these analyses, the NDWI appears to be more sensitive than NDVI to drought conditions. The results of statistical analysis of the relationships among these indices will be presented in the poster.

The impact of climate change on the drought variability over Australia

NASA Astrophysics Data System (ADS)

Kirono, D. G. C.; Hennessy, K.; Mpelasoka, F.; Bathols, J.; Kent, D.

2009-04-01

Drought has significant environmental and socio-economic impacts in Australia. Government assistance for drought events is guided by the current National Drought Policy (NDP). The Commonwealth Government provides support to farmers and rural communities under the Exceptional Circumstances (EC) arrangements and other drought programs, while state and territory governments also participate in the NDP and provide support measures of their own. To be classified as an EC event, the event must be rare, that is must not have occurred more than once on average in every 20-25 years. Given the likely increase in the area of the world affected by droughts in future due to climate change (IPCC, 2007), this paper presents assessments on how climate change may affect the concept of a one in 20-25 year event into the future for Australia. As droughts can be experienced and defined in different ways, many drought indices are available to monitor and to assess drought conditions. Commonly, these indices are categorised into four types: meteorological, hydrological, agricultural, and socio-economic. The meteorological drought indices are more widely used because they require data that are readily available and that they are relatively easy to calculate. However, meteorological drought indices based on rainfall alone fail to include the important contribution of evaporation. Here, the assessment is made using outputs of 13 global climate models (GCMs) and a meteorological drought index called the Reconnaissance Drought Index (RDI). It incorporates the aggregated deficits between the rainfall and the evaporative demand of the atmosphere. If the RDI were the sole trigger for EC declarations, then the mean projections indicate that more declarations would be likely in the future. As a comparison, results from an assessment based on other measures (temperature, rainfall, and soil wetness) will also be presented. IPCC, 2007: Climate Change 2007 - The physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Solomon, S. et al.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, www.ipcc.ch

Develop an early warning climate indicator to support the Nation's resilience to 'flash' droughts over the US Great Plains

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, D. N.; YANG, Z.; Solis, R.

2013-12-01

'Flash' droughts refer to those droughts that intensify rapidly in spring and summer, coupled with a strong increase of summer extreme temperatures, such as those that occurred over Texas in 2011 and the Great Plains in 2012. These droughts represent a great threat to North American water security. Climate models have failed to predict these 'flash' droughts and are ambiguous in projecting their future changes largely because of models' weaknesses in predicting summer rainfall and soil moisture feedbacks. By contrast, climate models are more reliable in simulating changes of large-scale circulation and warming of temperatures during the winter and spring seasons. We present a prototype of an early warning indicator for the risk of 'flash' droughts in summer by using the large-scale circulation and land surface conditions in winter and spring based on observed relationships between these conditions and their underlying physical mechanisms established by previous observations and numerical model simulations. This prototype 'flash' drought indicator (IFDW) currently uses global and regional reanalysis products (e.g., CFSR, MERRA, NLDAS products) in winter and spring to provide an assessment of summer drought severity similar to drought severity indices like PDSI (Palmer Drought Severity Index), SPI (Standard Precipitation Index) etc., provided by the National Integrated Drought Information Center (NIDIS) with additional information about uncertainty and past probability distributions of IFDW. Preliminary evaluation of hindcasts suggests that the indicator captures the occurrences of all the regional severe to extreme summer droughts during the past 63 years (1949-2011) over the US Great Plains, and 95% of the drought ending. This prototype IFDW has several advantages over the available drought indices that simply track local drought conditions in the past, present and future: 1) It mitigates the weakness of current climate models in predicting future summer droughts and takes advantage of model strengths and our understanding of the mechanisms that control 'flash' droughts; 2) It provides actionable drought risk information for stakeholders before droughts become fully developed in the current climate; 3) It can potentially link the future increase of temperatures in winter and spring to the risk of 'flash' droughts in summer. Such a link would make the projected changes of the 'flash' droughts more intuitive and compelling to high-level decision makers and the public.

InfoDROUGHT: Technical reliability assessment using crop yield data at the Spanish-national level

NASA Astrophysics Data System (ADS)

Contreras, Sergio; Garcia-León, David; Hunink, Johannes E.

2017-04-01

Drought monitoring (DM) is a key component of risk-centered drought preparedness plans and drought policies. InfoDROUGHT (www.infosequia.es) is a a site- and user-tailored and fully-integrated DM system which combines functionalities for: a) the operational satellite-based weekly-1km tracking of severity and spatial extent of drought impacts, b) the interactive and faster query and delivery of drought information through a web-mapping service. InfoDROUGHT has a flexible and modular structure. The calibration (threshold definitions) and validation of the system is performed by combining expert knowledge and auxiliary impact assessments and datasets. Different technical solutions (basic or advanced versions) or deployment options (open-standard or restricted-authenticated) can be purchased by end-users and customers according to their needs. In this analysis, the technical reliability of InfoDROUGHT and its performance for detecting drought impacts on agriculture has been evaluated in the 2003-2014 period by exploring and quantifying the relationships among the drought severity indices reported by InfoDROUGHT and the annual yield anomalies observed for different rainfed crops (maize, wheat, barley) at Spain. We hypothesize a positive relationship between the crop anomalies and the drought severity level detected by InfoDROUGHT. Annual yield anomalies were computed at the province administrative level as the difference between the annual yield reported by the Spanish Annual Survey of Crop Acreages and Yields (ESYRCE database) and the mean annual yield estimated during the study period. Yield anomalies were finally compared against drought greenness-based and thermal-based drought indices (VCI and TCI, respectively) to check the coherence of the outputs and the hypothesis stated. InfoDROUGHT has been partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant, and by the H2020-EU project "Bridging the Gap for Innovations in Disaster Resilience" (www.brigaid.eu).

Meteorological drought patterns and climate change for the island of Crete

NASA Astrophysics Data System (ADS)

Koutroulis, Aristeidis G.; Vrohidou, Aggeliki K.; Tsanis, Ioannis K.; Jacob, Daniela

2010-05-01

A new index, named SN-SPI (Spatially Normalized-Standardized Precipitation Index), has been developed for assessing meteorological droughts. The SN-SPI is a variant index to SPI (Standardized Precipitation Index) and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produces improved drought warnings. This index is applied in the island of Crete (Greece) and the drought results are compared to the ones of SPI. A 30-year long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias adjusted monthly precipitation estimates from REMO regional climate model used to quantify the influence of global warming to drought conditions over the period 2010 - 2100. Results based on both indices from 3 basins in west, central and east part of the island show that: a) the extreme drought periods are the same (5%-7% of time) but the intensities based on SN-SPI are lower, b) the area covered by extreme droughts is 25% and 80% based on the SN-SPI and SPI respectively, c) more than half of the area of Crete is experiencing drought conditions during 46% of the 1973-2004 period and 7%, 63% and 92% for 2010-2040, 2040-2070 and 2070-2100 respectively and d) extremely dry conditions will cover 5% of the island for the future 90-year period.

Towards Improved Understanding of Drought and Drought Impacts from Long Term Earth Observation Records

NASA Astrophysics Data System (ADS)

Champagne, C.; Wang, S.; Liu, J.; Hadwen, T. A.

2017-12-01

Drought is a complex natural disaster, which often emerges slowly, but can occur at various time scales and have impacts that are not well understood. Long term observations of drought intensity and frequency are often quantified from precipitation and temperature based indices or modelled estimates of soil water storage. The maturity of satellite based observations has created the potential to enhance the understanding of drought and drought impacts, particularly in regions where traditional data sets are limited by remoteness or inaccessibility, and where drought processes are not well-quantified by models. Long term global satellite data records now provide observations of key hydrological variables, including evaporation modelled from thermal sensors, soil moisture from microwave sensors, ground water from gravity sensors and vegetation condition that can be modelled from optical sensors. This study examined trends in drought frequency, intensity and duration over diverse ecoregions in Canada, including agricultural, grassland, forested and wetland areas. Trends in drought were obtained from the Canadian Drought Monitor as well as meteorological based indices from weather stations, and evaluated against satellite derived information on evaporative stress (Anderson et al. 2011), soil moisture (Champagne et al. 2015), terrestrial water storage (Wang and Li 2016) and vegetation condition (Davidson et al. 2009). Data sets were evaluated to determine differences in how different sensors characterize the hydrology and impacts of drought events from 2003 to 2016. Preliminary results show how different hydrological observations can provide unique information that can tie causes of drought (water shortages resulting from precipitation, lack of moisture storage or evaporative stress) to impacts (vegetation condition) that hold the potential to improve the understanding and classification of drought events.

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Lawrimore, Jay; Li, Bailing; Reichle, Rolf; Heim, Richard; Rosencrans, Matthew; Tinker, Rich; Famiglietti, James S.; Svoboda, Mark;

Development of a Coastal Drought Index Using Salinity Data

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Darby, L. S.

2014-12-01

The freshwater-saltwater interface in surface-water bodies along the coast is an important factor in the ecological and socio-economic dynamics of coastal communities. It influences community composition in freshwater and saltwater ecosystems, determines fisheries spawning habitat, and controls freshwater availability for municipal and industrial water intakes. These dynamics may be affected by coastal drought through changes in Vibrio bacteria impacts on shellfish harvesting and occurrence of wound infection, fish kills, harmful algal blooms, hypoxia, and beach closures. There are many definitions of drought, with most describing a decline in precipitation having negative impacts on water supply and agriculture. Four general types of drought are recognized: hydrological, agricultural, meteorological, and socio-economic. Indices have been developed for these drought types incorporating data such as rainfall, streamflow, soil moisture, groundwater levels, and snow pack. These indices were developed for upland areas and may not be appropriate for characterizing drought in coastal areas. Because of the uniqueness of drought impacts on coastal ecosystems, a need exists to develop a coastal drought index. The availability of real-time and historical salinity datasets provides an opportunity to develop a salinity-based coastal drought index. The challenge of characterizing salinity dynamics in response to drought is excluding responses attributable to occasional saltwater intrusion events. Our approach to develop a coastal drought index modified the Standardized Precipitation Index and applied it to sites in South Carolina and Georgia, USA. Coastal drought indices characterizing 1-, 3-, 6-, 9-, and12-month drought conditions were developed. Evaluation of the coastal drought index indicates that it can be used for different estuary types, for comparison between estuaries, and as an index for wet conditions (high freshwater inflow) in addition to drought conditions.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Assessment of Vegetation Responses and Sensitivity to the Millennium Drought in Australia

NASA Astrophysics Data System (ADS)

Jiao, T.; Williams, C. A.

2017-12-01

During the period from 1997 to 2009, Australia experienced one of the most severe and persistent drought known as the Millennium Drought (MD). Major water shortages were reported across the Australian continent as well as a great many tree mortality during and post this drought event. Given the projection of hotter and drier conditions for much of the continent (Hughes 2003), it is critical to analyze the impacts of climate extremes like MD as an indicator of possible impacts of future trends. A few drought assessments have been performed for the MD but their utilization of single-source Remote sensing data like vegetation indices makes it difficult to produce a comprehensive understanding of drought responses for diverse ecosystems in Australia. Furthermore, methods adopted in past drought assessments did not distinguish vegetation responses to drought events with different intensity, duration and sequence, which are critically important in determining the magnitude of vegetation responses to drought. Here, multi-source remote sensing datasets and an event-based drought assessment method were employed to assess the impacts of MD on vegetation in Australia in terms of the magnitude and sensitivity. Vegetation variables examined include fraction of photosynthetically absorbed radiation (Fpar), vegetation optical depth (VOD) and aboveground biomass (AGB). Drought indicators were calculated based on precipitation and potential evapotranspiration. Results show that most of Eastern Australia experienced abnormal water deficit during the MD and drought intensity was greatest in humid regions. The decline in aboveground biomass (ABC) demonstrates consistent variation with drought intensity across aridity levels. Drought impacts on Fpar and VOD were greatest at intermediate dryness and for woodier ecosystems, with impacts appearing in Fpar before VOD. Drought sensitivity was also greatest at intermediate dryness and for woodier ecosystems. The small difference in drought sensitivity, in terms of Fpar and VOD, across biomes suggests that trees, shrubs, and herbaceous are equally vulnerable to canopy dieback while the high drought sensitivity of trees as shown in ABC implies that a large amount of carbon could be released to the atmosphere if intense and long-duration drought occurs in forested areas.

A review of droughts on the African continent: a geospatial and long-term perspective

NASA Astrophysics Data System (ADS)

Masih, I.; Maskey, S.; Mussá, F. E. F.; Trambauer, P.

2014-09-01

This paper presents a comprehensive review and analysis of the available literature and information on droughts to build a continental, regional and country level perspective on geospatial and temporal variation of droughts in Africa. The study is based on the review and analysis of droughts occurred during 1900-2013, as well as evidence available from past centuries based on studies on the lake sediment analysis, tree-ring chronologies and written and oral histories and future predictions from the global climate change models. Most of the studies based on instrumental records indicate that droughts have become more frequent, intense and widespread during the last 50 years. The extreme droughts of 1972-1973, 1983-1984 and 1991-1992 were continental in nature and stand unique in the available records. Additionally, many severe and prolonged droughts were recorded in the recent past such as the 1999-2002 drought in northwest Africa, 1970s and 1980s droughts in western Africa (Sahel), 2010-2011 drought in eastern Africa (Horn of Africa) and 2001-2003 drought in southern and southeastern Africa, to name a few. The available (though limited) evidence before the 20th century confirms the occurrence of several extreme and multi-year droughts during each century, with the most prolonged and intense droughts that occurred in Sahel and equatorial eastern Africa. The complex and highly variant nature of many physical mechanisms such as El Niño-Southern Oscillation (ENSO), sea surface temperature (SST) and land-atmosphere feedback adds to the daunting challenge of drought monitoring and forecasting. The future predictions of droughts based on global climate models indicate increased droughts and aridity at the continental scale but large differences exist due to model limitations and complexity of the processes especially for Sahel and northern Africa. However, the available evidence from the past clearly shows that the African continent is likely to face extreme and widespread droughts in future. This evident challenge is likely to aggravate due to slow progress in drought risk management, increased population and demand for water and degradation of land and environment. Thus, there is a clear need for increased and integrated efforts in drought mitigation to reduce the negative impacts of droughts anticipated in the future.

A review of droughts in the African continent: a geospatial and long-term perspective

NASA Astrophysics Data System (ADS)

Masih, I.; Maskey, S.; Mussá, F. E. F.; Trambauer, P.

2014-03-01

This paper presents a comprehensive review and analysis of the available literature and information on droughts to build a continental, regional and country level perspective on geospatial and temporal variation of droughts in Africa. The study is based on the review and analysis of droughts occurred during 1900-2013 as well as evidence available from past centuries based on studies on the lake sediment analysis, tree-ring chronologies and written and oral histories and future predictions from the global climate change models. Most of the studies based on instrumental records indicate that droughts have become more frequent, intense and widespread during the last 50 yr. The extreme droughts of 1972-1973, 1983-1984 and 1991-1992 were continental in nature and stand unique in the available records. Additionally, many severe and prolonged droughts were recorded in the recent past such as the 1999-2002 drought in Northwest Africa, 1970s and 1980s droughts in West Africa (Sahel), 2010-2011 drought in East Africa (Horn of Africa) and 2001-2003 drought in Southern and Southeast Africa, to name a few. The available (though limited) evidence before the 20th century confirms the occurrence of several extreme and multi-year droughts during each century, with the most prolonged and intense droughts that occurred in Sahel and Equatorial East Africa regions. Complex and highly variant nature of many physical mechanisms such as El Niño-Southern Oscillation (ENSO), Sea Surface Temperature (SST) and land-atmosphere feedback adds to the daunting challenge of drought monitoring and forecasting. The future predictions of droughts based on global climate models indicate increased droughts and aridity at the continental scale but large differences exist due to model limitations and complexity of the processes especially for Sahel and North Africa regions. However, the available evidence from the past clearly shows that the African continent is likely to face extreme and widespread droughts in future. This evident challenge is likely to aggravate due to slow progress in drought risk management, increased population and demand for water and degradation of land and environment. Thus, there is a clear need for increased and integrated efforts in drought mitigation to reduce the negative impacts of droughts anticipated in future.

Toward a categorical drought prediction system based on U.S. Drought Monitor (USDM) and climate forecast

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Xia, Youlong; Luo, Lifeng; Singh, Vijay P.; Ouyang, Wei; Hao, Fanghua

2017-08-01

Disastrous impacts of recent drought events around the world have led to extensive efforts in drought monitoring and prediction. Various drought information systems have been developed with different indicators to provide early drought warning. The climate forecast from North American Multimodel Ensemble (NMME) has been among the most salient progress in climate prediction and its application for drought prediction has been considerably growing. Since its development in 1999, the U.S. Drought Monitor (USDM) has played a critical role in drought monitoring with different drought categories to characterize drought severity, which has been employed to aid decision making by a wealth of users such as natural resource managers and authorities. Due to wide applications of USDM, the development of drought prediction with USDM drought categories would greatly aid decision making. This study presented a categorical drought prediction system for predicting USDM drought categories in the U.S., based on the initial conditions from USDM and seasonal climate forecasts from NMME. Results of USDM drought categories predictions in the U.S. demonstrate the potential of the prediction system, which is expected to contribute to operational early drought warning in the U.S.

An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

2013-12-01

One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

A Framework for Drought Risk Management

NASA Astrophysics Data System (ADS)

Apurv, T.; Cai, X.

2016-12-01

Drought is one of the most expensive natural disasters as it affects many sectors of the economy. The threat posed by droughts is expected to further increase due to increasing water demands fuelled by increasing population and also due to climate change in many regions. Management of the increasing drought risk requires shift from traditional crisis management approaches to long term strategic planning for reduction of drought risk. This study proposes a framework for management of long term drought risk. The framework uses the system based approach proposed by Tsakiris et al. (2013), in which a watershed is considered as a system and different water sources in the watershed (like groundwater, reservoirs, streams etc.) are considered as subsystems associated with certain water requirements of different sectors. Droughts are defined separately for each subsystem considering water availability and requirement. The percentile based drought indicator framework proposed by Steinemann et al. (2015) is used for defining drought for each subsystem, allowing the selection of thresholds, variables of interest, and time scale which are most relevant for stakeholders dependent on a particular subsystem. Future drought risk under different drought management strategies are assessed using hydrologic models that model both hydrologic and human components of a watershed. The robustness of a management strategy is assessed by simulating system response across a wide range of stochastically generated future climate scenarios. The framework is useful for operational drought management as it allows direct management of drought risks with consideration of different water sources and water users. Steinemann, A., Iacobellis, S.F., Cayan, D.R., (2015) "Developing and evaluating drought indicators for decision-making" J. Hydrometeor. 16 (4), 1793-1803 Tsakiris, G, Nalbantis, I, Vangelis, H, Verbeiren, B, Huysmans, M, Tychon, B, Jacquemin, I, Canters, F, Vanderhaegen, S, Engelen, G, Poelmans, L, De Becker, P, Batelaan, O, (2013) "A system-based paradigm of drought analysis for operational management" Water Resour Manag 27(15):5281-5297

Application of Archimedean copulas to the analysis of drought decadal variation in China

NASA Astrophysics Data System (ADS)

Zuo, Dongdong; Feng, Guolin; Zhang, Zengping; Hou, Wei

2017-12-01

Based on daily precipitation data collected from 1171 stations in China during 1961-2015, the monthly standardized precipitation index was derived and used to extract two major drought characteristics which are drought duration and severity. Next, a bivariate joint model was established based on the marginal distributions of the two variables and Archimedean copula functions. The joint probability and return period were calculated to analyze the drought characteristics and decadal variation. According to the fit analysis, the Gumbel-Hougaard copula provided the best fit to the observed data. Based on four drought duration classifications and four severity classifications, the drought events were divided into 16 drought types according to the different combinations of duration and severity classifications, and the probability and return period were analyzed for different drought types. The results showed that the occurring probability of six common drought types (0 < D ≤ 1 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 1 < S ≤ 1.5, 1 < D ≤ 3 and 1.5 < S ≤ 2, 1 < D ≤ 3 and 2 < S, and 3 < D ≤ 6 and 2 < S) accounted for 76% of the total probability of all types. Moreover, due to their greater variation, two drought types were particularly notable, i.e., the drought types where D ≥ 6 and S ≥ 2. Analyzing the joint probability in different decades indicated that the location of the drought center had a distinctive stage feature, which cycled from north to northeast to southwest during 1961-2015. However, southwest, north, and northeast China had a higher drought risk. In addition, the drought situation in southwest China should be noted because the joint probability values, return period, and the analysis of trends in the drought duration and severity all indicated a considerable risk in recent years.

A new framework for evaluating the impacts of drought on net primary productivity of grassland.

PubMed

Lei, Tianjie; Wu, Jianjun; Li, Xiaohan; Geng, Guangpo; Shao, Changliang; Zhou, Hongkui; Wang, Qianfeng; Liu, Leizhen

2015-12-01

This paper presented a valuable framework for evaluating the impacts of droughts (single factor) on grassland ecosystems. This framework was defined as the quantitative magnitude of drought impact that unacceptable short-term and long-term effects on ecosystems may experience relative to the reference standard. Long-term effects on ecosystems may occur relative to the reference standard. Net primary productivity (NPP) was selected as the response indicator of drought to assess the quantitative impact of drought on Inner Mongolia grassland based on the Standardized Precipitation Index (SPI) and BIOME-BGC model. The framework consists of six main steps: 1) clearly defining drought scenarios, such as moderate, severe and extreme drought; 2) selecting an appropriate indicator of drought impact; 3) selecting an appropriate ecosystem model and verifying its capabilities, calibrating the bias and assessing the uncertainty; 4) assigning a level of unacceptable impact of drought on the indicator; 5) determining the response of the indicator to drought and normal weather state under global-change; and 6) investigating the unacceptable impact of drought at different spatial scales. We found NPP losses assessed using the new framework were more sensitive to drought and had higher precision than the long-term average method. Moreover, the total and average losses of NPP are different in different grassland types during the drought years from 1961-2009. NPP loss was significantly increased along a gradient of increasing drought levels. Meanwhile, NPP loss variation under the same drought level was different in different grassland types. The operational framework was particularly suited for integrative assessing the effects of different drought events and long-term droughts at multiple spatial scales, which provided essential insights for sciences and societies that must develop coping strategies for ecosystems for such events. Copyright © 2015 Elsevier B.V. All rights reserved.

Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-04-01

This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area.

A data fusion-based drought index

NASA Astrophysics Data System (ADS)

Azmi, Mohammad; Rüdiger, Christoph; Walker, Jeffrey P.

2016-03-01

Drought and water stress monitoring plays an important role in the management of water resources, especially during periods of extreme climate conditions. Here, a data fusion-based drought index (DFDI) has been developed and analyzed for three different locations of varying land use and climate regimes in Australia. The proposed index comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type. In deriving the proposed index, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were employed to first derive commonly used individual standardized drought indices (SDIs), which were then grouped using an advanced clustering method. Next, three different multivariate methods (principal component analysis, factor analysis, and independent component analysis) were utilized to aggregate the SDIs located within each group. For the two clusters in which the grouped SDIs best reflected the water availability and vegetation conditions, the variables were aggregated based on an averaging between the standardized first principal components of the different multivariate methods. Then, considering those two aggregated indices as well as the classifications of months (dry/wet months and active/non-active months), the proposed DFDI was developed. Finally, the symbolic regression method was used to derive mathematical equations for the proposed DFDI. The results presented here show that the proposed index has revealed new aspects in water stress monitoring which previous indices were not able to, by simultaneously considering both hydrometeorological and ecological concepts to define the real water stress of the study areas.

Modeling drought impact occurrence based on climatological drought indices for four European countries

NASA Astrophysics Data System (ADS)

Stagge, James H.; Kohn, Irene; Tallaksen, Lena M.; Stahl, Kerstin

2014-05-01

The relationship between atmospheric conditions and the likelihood of a significant drought impact has, in the past, been difficult to quantify, particularly in Europe where political boundaries and language have made acquiring comprehensive drought impact information difficult. As such, the majority of studies linking meteorological drought with the occurrence or severity of drought impacts have previously focused on specific regions, very detailed impact types, or both. This study describes a new methodology to link the likelihood of drought impact occurrence with climatological drought indices across different European climatic regions and impact sectors using the newly developed European Drought Impact report Inventory (EDII), a collaborative database of drought impact information (www.geo.uio.no/edc/droughtdb/). The Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) are used as predictor variables to quantify meteorological drought severity over prior time periods (here 1, 2, 3, 6, 9, 12, and 24 months are used). The indices are derived using the gridded WATCH Forcing Datasets, covering the period 1958-2012. Analysis was performed using logistic regression to identify the climatological drought index and accumulation period, or linear combination of drought indices, that best predicts the likelihood of a documented drought impact, defined by monthly presence/absence. The analysis was carried out for a subset of four European countries (Germany, UK, Norway, Slovenia) and four of the best documented impact sectors: Public Water Supply, Agriculture and Livestock Farming, Energy and Industry, and Environmental Quality. Preliminary results show that drought impacts in these countries occur most frequently due to a combination of short-term (2-6 month) precipitation deficits and long-term (12-24 month) potential evapotranspiration anomaly, likely associated with increased temperatures. Agricultural drought impacts were explained best by shorter, seasonal indices (2-6 months), while impacts to the Energy sector were best explained by long-duration (12-24 month) anomalies, related to hydropower reservoir storage. Notably, drought impacts in the UK were not affected by short (< 6 month) anomalies, which may point to successful management strategies or underlying geoclimatic differences. By identifying the climatological drought indices most strongly linked to drought impact occurrence and generating regression equations that can predict the likelihood of a drought event, this research is a valuable step towards measuring and predicting drought risk. This work provides a methodological example using only a subset of European countries and impact types, but the accuracy and scope of these results will improve as the EDII grows with further contributions and collaboration.

The use of infrared thermal imaging as a non-destructive screening tool for identifying drought-tolerant lentil genotypes.

PubMed

Biju, Sajitha; Fuentes, Sigfredo; Gupta, Dorin

2018-06-01

Lentil (Lens culinaris, Medik.) is an important legume crop, which often experience drought stress especially at the flowering and grain filling phenological stages. The availability of efficient and robust screening tools based on relevant non-destructive quantifiable traits would facilitate research on crop improvement for drought tolerance. The objective of this study was to evaluate the drought tolerance of 37 lentil genotypes using infrared thermal imaging (IRTI), drought tolerance parameters and multivariate data analysis. Potted plants were kept in a completely randomized design in a growth chamber with five replicates. Plants were subjected to three different drought treatments: 100, 50 and 20% of field capacity at the onset of reproductive period. The relative drought stress tolerance was determined based on a set of morpho-physiological parameters including non-destructive measures based on IRTI, such as: canopy temperature (Tc), canopy temperature depression (CTD) and crop water stress index (CWSI) during the growing period and destructive measures at harvest, such as: dry root-shoot ratio (RS ratio), relative water content (RWC) and harvest index (HI). The drought tolerance indices used were drought susceptibility index (DSI) and drought tolerance efficiency (DTE). Results showed that drought stress treatments significantly reduced the RWC, HI, CTD and DSI, whereas, the values of Tc, CWSI, RS ratio and DTE significantly increased for all the genotypes. The cluster analysis from morpho-physiological parameters clustered genotypes in three distinctive groups as per the level of drought stress tolerance. The genotypes with higher values of RS ratio, RWC, HI, DTE and CTD and lower values of DSI, Tc and CWSI were identified as drought-tolerant genotypes. Based on this preliminary screening, the genotypes Digger, Cumra, Indianhead, ILL 5588, ILL 6002 and ILL 5582 were identified as promising drought-tolerant genotypes. It can be concluded that the IRTI analysis is a high-throughput constructive screening tool along with RS ratio, RWC, HI and other drought tolerance indices to define the drought stress tolerance variability within lentil plants. These results provide a foundation for future research directed at identifying powerful drought assessment traits using rapid and non-destructive techniques, such as IRTI along with the yield traits, and understanding the biochemical and molecular mechanisms underlying lentil tolerance to drought stress. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Monitoring drought occurrences using MODIS evapotranspiration data: Direct impacts on agricultural productivity in Southern Brazil

NASA Astrophysics Data System (ADS)

Ruhoff, Anderson

2014-05-01

Evapotranspiration (ET), including water loss from plant transpiration and land evaporation, is of vital importance for understanding hydrological processes and climate dynamics and remote sensing is considered as the most important tool for estimate ET over large areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers an interesting opportunity to evaluate ET with spatial resolution of 1 km. The MODIS global evapotranspiration algorithm (MOD16) considers both surface energy fluxes and climatic constraints on ET (water or temperature stress) to predict plant transpiration and soil evaporation based on Penman-Monteith equation. The algorithm is driven by remotely sensed and reanalysis meteorological data. In this study, MOD16 algorithm was applied to Southern Brazil to evaluate drought occurrences and its impacts over the agricultural production. Drought is a chronic potential natural disaster characterized by an extended period of time in which less water is available than expected, typically classified as meteorological, agricultural, hydrological and socioeconomic. With human-induced climate change, increases in the frequency, duration and severity of droughts are expected, leading to negative impacts in several sectors, such as agriculture, energy, transportation, urban water supply, among others. The current drought indicators are primarily based on precipitation, however only a few indicators incorporate ET and soil moisture components. ET and soil moisture play an important role in the assessment of drought severity as sensitive indicators of land drought status. To evaluate the drought occurrences in Southern Brazil from 2000 to 2012, we used the Evaporative Stress Index (ESI). The ESI, defined as 1 (one) minus the ratio of actual ET to potential ET, is one of the most important indices denoting ET and soil moisture responses to surface dryness with effects over natural ecosystems and agricultural areas. Results showed that ESI captured major regional droughts (2005, 2010 and 2012) occurred in Southern Brazil, with similar wetting and drying patterns based on the Standardized Precipitation Index (SPI) and strong correlation with agricultural productivity. Overall, the MODIS remotely sensed drought indices reveal the efficacy and effectiveness for near-real time monitor land surface drought events. Furthermore, understanding and predicting the consequences of drought events on agricultural productivity is emerging as one of the greatest challenges currently due to the increasing global demand for food. Acknowledgements: This work was made possible through the support of the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).

Global drought outlook by means of seasonal forecasts

NASA Astrophysics Data System (ADS)

Ziese, Markus; Fröhlich, Kristina; Rustemeier, Elke; Becker, Andreas

2017-04-01

Droughts are naturally occurring phenomena which are caused by a shortage of available water due to lower than normal precipitation and/or above normal evaporation. Depending on the length of the droughts, several sectors are affected starting with agriculture, then river and ground water levels and finally socio-economic losses at the long end of the spectrum of drought persistence. Droughts are extreme events that affect much larger areas and last much longer than floods, but are less geared towards media than floods being more short-scale in persistence and impacts. Finally the slow onset of droughts make the detection and early warning of their beginning difficult and time is lost for preparatory measures. Drought indices are developed to detect and classify droughts based on (meteorological) observations and possible additional information tailored to specific user needs, e.g. in agriculture, hydrology and other sectors. Not all drought indices can be utilized for global applications as not all input parameters are available at this scale. Therefore the Global Precipitation Climatology Centre (GPCC) developed a drought index as combination of the Standardized Drought Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), the GPCC-DI. The GPCC-DI is applied to drought monitoring and retrospective analyses on a global scale. As the Deutscher Wetterdienst (DWD) operates a seasonal forecast system in cooperation with Max-Planck-Institute for Meteorology Hamburg and University of Hamburg, these data are also used for an outlook of drought conditions by means of the GPCC-DI. The reliability of seasonal precipitation forecasts is limited, so the drought outlook is available only for forecast months two to four. Based on the GPCC-DI, DWD provides a retrospective analysis, near-real-time monitoring and outlook of drought conditions on a global scale and regular basis.

The turn-of-the-century drought in North America: The new normal?

NASA Astrophysics Data System (ADS)

Schwalm, C. R.; Williams, C. A.; Schaefer, K. M.; NACP Site Synthesis Team

2011-12-01

At the turn of the century, from 2000 to 2004, western North America (25°-50°N, 100°-125°W) experienced a severe drought with far reaching consequences for the terrestrial biosphere. We quantified the drought's water and carbon cycle implications using upscaled flux tower data, observed and simulated fluxes from the NACP Site Synthesis, remote sensing products, weather reanalysis, crop yield, and river discharge. During the turn of the century drought we found a widespread drydown of the terrestrial biosphere, large decreases in river discharge and greenness, and a ~10% loss in cropland productivity. At the footprint scale carbon uptake declined with an anomalous carbon source of 0.11 Pg C/yr integrated over the full domain. Flux towers also recorded a clear signal of reduced latent and increased sensible heat fluxes, apart from grasslands. Dendrochronological reconstructions of drought extent, duration, and severity, based on the Palmer Drought Severity Index drought metric, indicated that the turn of the century drought was unprecedented since 1200 CE. Predicted changes in precipitation and drought, based on the CMIP3 multi-model mean, could permanently disable the weak sink (NEE = -0.19 Pg C/yr) in western North America by the midpoint of the 21st Century. Projections indicate the turn-of-the-century drought will be wet compared to the latter half of the 21st Century.

Compound effects of temperature and precipitation in making droughts more frequent in Marathwada, India

NASA Astrophysics Data System (ADS)

Mondal, A.; Zachariah, M.; Achutarao, K. M.; Otto, F. E. L.

2017-12-01

The Marathwada region in Maharashtra, India is known to suffer significantly from agrarian crisis including farmer suicides resulting from persistent droughts. Drought monitoring in India is commonly based on univariate indicators that consider the deficiency in precipitation alone. However, droughts may involve complex interplay of multiple physical variables, necessitating an integrated, multivariate approach to analyse their behaviour. In this study, we compare the behaviour of drought characteristics in Marathwada in the recent years as compared to the first half of the twentieth century, using a joint precipitation and temperature-based Multivariate Standardized Drought Index (MSDI). Drought events in the recent times are found to exhibit exceptional simultaneous anomalies of high temperature and precipitation deficits in this region, though studies on precipitation alone show that these events are within the range of historically observed variability. Additionally, we also develop multivariate copula-based Severity-Duration-Frequency (SDF) relationships for droughts in this region and compare their natures pre- and post- 1950. Based on multivariate return periods considering both temperature and precipitation anomalies, as well as the severity and duration of droughts, it is found that droughts have become more frequent in the post-1950 period. Based on precipitation alone, such an observation cannot be made. This emphasizes the sensitivity of droughts to temperature and underlines the importance of considering compound effects of temperature and precipitation in order to avoid an underestimation of drought risk. This observation-based analysis is the first step towards investigating the causal mechanisms of droughts, their evolutions and impacts in this region, particularly those influenced by anthropogenic climate change.

Physiological and molecular characterization of drought responses and identification of candidate tolerance genes in cassava

PubMed Central

Turyagyenda, Laban F.; Kizito, Elizabeth B.; Ferguson, Morag; Baguma, Yona; Agaba, Morris; Harvey, Jagger J. W.; Osiru, David S. O.

2013-01-01

Cassava is an important root crop to resource-poor farmers in marginal areas, where its production faces drought stress constraints. Given the difficulties associated with cassava breeding, a molecular understanding of drought tolerance in cassava will help in the identification of markers for use in marker-assisted selection and genes for transgenic improvement of drought tolerance. This study was carried out to identify candidate drought-tolerance genes and expression-based markers of drought stress in cassava. One drought-tolerant (improved variety) and one drought-susceptible (farmer-preferred) cassava landrace were grown in the glasshouse under well-watered and water-stressed conditions. Their morphological, physiological and molecular responses to drought were characterized. Morphological and physiological measurements indicate that the tolerance of the improved variety is based on drought avoidance, through reduction of water loss via partial stomatal closure. Ten genes that have previously been biologically validated as conferring or being associated with drought tolerance in other plant species were confirmed as being drought responsive in cassava. Four genes (MeALDH, MeZFP, MeMSD and MeRD28) were identified as candidate cassava drought-tolerance genes, as they were exclusively up-regulated in the drought-tolerant genotype to comparable levels known to confer drought tolerance in other species. Based on these genes, we hypothesize that the basis of the tolerance at the cellular level is probably through mitigation of the oxidative burst and osmotic adjustment. This study provides an initial characterization of the molecular response of cassava to drought stress resembling field conditions. The drought-responsive genes can now be used as expression-based markers of drought stress tolerance in cassava, and the candidate tolerance genes tested in the context of breeding (as possible quantitative trait loci) and engineering drought tolerance in transgenics. PMID:23519782

Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

Drought vulnerability assessment: The case of wheat farmers in Western Iran

NASA Astrophysics Data System (ADS)

Zarafshani, Kiumars; Sharafi, Lida; Azadi, Hossein; Hosseininia, Gholamhossein; De Maeyer, Philippe; Witlox, Frank

2012-12-01

Drought, as a natural and slow-onset phenomenon, creates numerous damages to agricultural communities. As a drought prone area in the Middle East, Iran has currently launched a crisis management approach to mitigate the harmful impacts of drought. However, thus far studies indicate that effective drought management strategies should be designed based upon vulnerability management which can increase farmers' ability to challenge the impacts. The purpose of this study was to assess drought vulnerability across three drought intensities (very high, extremely high, and critical) areas in Western Iran. Accordingly, a survey study was applied and 370 wheat farmers who all experienced drought during 2007-2009 were selected through a multi-stage stratified random sampling method. Face to face interviews were used to collect data on vulnerability indices from the farmers. Me-Bar and Valdez's vulnerability formula was applied to assess the vulnerability of wheat farmers during drought. Results revealed that the farmers' vulnerability is influenced mainly by economic, socio-cultural, psychological, technical, and infrastructural factors. The results also indicated that the farmers in Sarpole-Zahab township were most vulnerable compared to those in the Kermanshah township as the least vulnerable. Accordingly, some conclusions and recommendations are drawn for both policy-makers and practitioners who often must prioritize limited resources in the design vulnerability-reducing interventions.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo River basin, southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-08-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo river basin, Southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-03-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer resolution version (0.05° x 0.05°) of the continental scale hydrological model PCR-GLOBWB was set up for the Limpopo river basin, one of the most water stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse droughts in the Limpopo river basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily time scale for the entire basin. PCR-GLOBWB was forced with daily precipitation, temperature and other meteorological variables obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI) were also computed for different aggregation periods. Results show that a carefully set up process-based model that makes use of the best available input data can successfully identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of droughts/floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6, SPI-12) is found to be a useful measure for identifying hydrological droughts in the Limpopo river basin. Additionally, it is possible to make a characterisation of the drought severity, indicated by its duration and intensity.

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Li, Bailing; Reichle, Rolf; Zaitchik, Benjamin F.

2012-01-01

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

[Spatio-temporal variation of drought condition during 1961 to 2012 based on composite index of meteorological drought in Altay region, China].

PubMed

Wu, Yan-feng; Bake, Batur; Li, Wei; Wei, Xiao-qin; Wozatihan, Jiayinaguli; Rasulov, Hamid

2015-02-01

Based on the daily meteorological data of seven stations in Altay region, China, this study investigated the temporal ( seasonal, inter-annual and decadal) and spatial variations of drought by using composite index of meteorological drought, as well as trend analysis, M-K abrupt analysis, wavelet analysis and interpolation tools in ArcGIS. The results indicated that the composite index of meteorological drought could reflect the drought condition in Altay region well. Although the frequency and the covered area of both inter-annual and seasonal droughts presented decreasing trends in the recent 52 a, the drought was still serious when considering the annual drought. The frequencies of inter-annual and spring droughts had no abrupt changes, whereas the frequencies of inter-summer, autumn and winter droughts had abrupt changes during the past 52 a. A significant periodic trend was also observed for the frequencies of inter-annual and seasonal droughts. The distribution of frequency and covered area suggested that the conditions of drought were heavily serious in Qinghe County, moderately serious in Altay City, Fuyun County, Buerjin County and Fuhai County, and slightly serious in Habahe County and Jimunai County.

Towards developing drought impact functions to advance drought monitoring and early warning

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Stahl, Kerstin; Hannaford, Jamie; Svoboda, Mark

2015-04-01

In natural hazard analysis, damage functions (also referred to as vulnerability or susceptibility functions) relate hazard intensity to the negative effects of the hazard event, often expressed as damage ratio or monetary loss. While damage functions for floods and seismic hazards have gained considerable attention, there is little knowledge on how drought intensity translates into ecological and socioeconomic impacts. One reason for this is the multifaceted nature of drought affecting different domains of the hydrological cycle and different sectors of human activity (for example, recognizing meteorological - agricultural - hydrological - socioeconomic drought) leading to a wide range of drought impacts. Moreover, drought impacts are often non-structural and hard to quantify or monetarize (e.g. impaired navigability of streams, bans on domestic water use, increased mortality of aquatic species). Knowledge on the relationship between drought intensity and drought impacts, i.e. negative environmental, economic or social effects experienced under drought conditions, however, is vital to identify critical thresholds for drought impact occurrence. Such information may help to improve drought monitoring and early warning (M&EW), one goal of the international DrIVER project (Drought Impacts: Vulnerability thresholds in monitoring and Early-warning Research). The aim of this study is to test the feasibility of designing "drought impact functions" for case study areas in Europe (Germany and UK) and the United States to derive thresholds meaningful for drought impact occurrence; to account for the multidimensionality of drought impacts, we use the broader term "drought impact function" over "damage function". First steps towards developing empirical drought impact functions are (1) to identify meaningful indicators characterizing the hazard intensity (e.g. indicators expressing a precipitation or streamflow deficit), (2) to identify suitable variables representing impacts, damage, or loss due to drought, and (3) to test different statistical models to link drought intensity with drought impact information to derive meaningful thresholds. While the focus regarding drought impact variables lies on text-based impact reports from the European Drought Impact report Inventory (EDII) and the US Drought Impact Reporter (DIR), the information gain through exploiting other variables such as agricultural yield statistics and remotely sensed vegetation indices is explored. First results reveal interesting insights into the complex relationship between drought indicators and impacts and highlight differences among drought impact variables and geographies. Although a simple intensity threshold evoking specific drought impacts cannot be identified, developing drought impact functions helps to elucidate how drought conditions relate to ecological or socioeconomic impacts. Such knowledge may provide guidance for inferring meaningful triggers for drought M&EW and could have potential for a wide range of drought management applications (for example, building drought scenarios for testing the resilience of drought plans or water supply systems).

A study on agricultural drought vulnerability at disaggregated level in a highly irrigated and intensely cropped state of India.

PubMed

Murthy, C S; Yadav, Manoj; Mohammed Ahamed, J; Laxman, B; Prawasi, R; Sesha Sai, M V R; Hooda, R S

2015-03-01

Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights.

Remotely sensed predictors of conifer tree mortality during severe drought

NASA Astrophysics Data System (ADS)

Brodrick, P. G.; Asner, G. P.

2017-11-01

Widespread, drought-induced forest mortality has been documented on every forested continent over the last two decades, yet early pre-mortality indicators of tree death remain poorly understood. Remotely sensed physiological-based measures offer a means for large-scale analysis to understand and predict drought-induced mortality. Here, we use laser-guided imaging spectroscopy from multiple years of aerial surveys to assess the impact of sustained canopy water loss on tree mortality. We analyze both gross canopy mortality in 2016 and the change in mortality between 2015 and 2016 in millions of sampled conifer forest locations throughout the Sierra Nevada mountains in California. On average, sustained water loss and gross mortality are strongly related, and year-to-year water loss within the drought indicates subsequent mortality. Both relationships are consistent after controlling for location and tree community composition, suggesting that these metrics may serve as indicators of mortality during a drought.

Integrated drought risk assessment of multi-hazard-affected bodies based on copulas in the Taoerhe Basin, China

NASA Astrophysics Data System (ADS)

Wang, Rui; Zhang, Jiquan; Guo, Enliang; Alu, Si; Li, Danjun; Ha, Si; Dong, Zhenhua

2018-02-01

Along with global warming, drought disasters are occurring more frequently and are seriously affecting normal life and food security in China. Drought risk assessments are necessary to provide support for local governments. This study aimed to establish an integrated drought risk model based on the relation curve of drought joint probabilities and drought losses of multi-hazard-affected bodies. First, drought characteristics, including duration and severity, were classified using the 1953-2010 precipitation anomaly in the Taoerhe Basin based on run theory, and their marginal distributions were identified by exponential and Gamma distributions, respectively. Then, drought duration and severity were related to construct a joint probability distribution based on the copula function. We used the EPIC (Environmental Policy Integrated Climate) model to simulate maize yield and historical data to calculate the loss rates of agriculture, industry, and animal husbandry in the study area. Next, we constructed vulnerability curves. Finally, the spatial distributions of drought risk for 10-, 20-, and 50-year return periods were expressed using inverse distance weighting. Our results indicate that the spatial distributions of the three return periods are consistent. The highest drought risk is in Ulanhot, and the duration and severity there were both highest. This means that higher drought risk corresponds to longer drought duration and larger drought severity, thus providing useful information for drought and water resource management. For 10-, 20-, and 50-year return periods, the drought risk values ranged from 0.41 to 0.53, 0.45 to 0.59, and 0.50 to 0.67, respectively. Therefore, when the return period increases, the drought risk increases.

Assessing the vegetation condition impacts of the 2011 drought across the U.S. southern Great Plains using the vegetation drought response index (VegDRI)

USGS Publications Warehouse

Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn F.; Svoboda, Mark; Hayes, Michael; Fuchs, Brian; Gutzmer, Denise

2015-01-01

The vegetation drought response index (VegDRI), which combines traditional climate- and satellite-based approaches for assessing vegetation conditions, offers new insights into assessing the impacts of drought from local to regional scales. In 2011, the U.S. southern Great Plains, which includes Texas, Oklahoma, and New Mexico, was plagued by moderate to extreme drought that was intensified by an extended period of record-breaking heat. The 2011 drought presented an ideal case study to evaluate the performance of VegDRI in characterizing developing drought conditions. Assessment of the spatiotemporal drought patterns represented in the VegDRI maps showed that the severity and patterns of the drought across the region corresponded well to the record warm temperatures and much-below-normal precipitation reported by the National Climatic Data Center and the sectoral drought impacts documented by the Drought Impact Reporter (DIR). VegDRI values and maps also showed the evolution of the drought signal before the Las Conchas Fire (the largest fire in New Mexico’s history). Reports in the DIR indicated that the 2011 drought had major adverse impacts on most rangeland and pastures in Texas and Oklahoma, resulting in total direct losses of more than $12 billion associated with crop, livestock, and timber production. These severe impacts on vegetation were depicted by the VegDRI at subcounty, state, and regional levels. This study indicates that the VegDRI maps can be used with traditional drought indicators and other in situ measures to help producers and government officials with various management decisions, such as justifying disaster assistance, assessing fire risk, and identifying locations to move livestock for grazing.

[Spatio-temporal characteristics of agricultural drought in Shaanxi Province, China based on integrated disaster risk index].

PubMed

He, Bin; Wang, Quan Jiu; Wu, Di; Zhou, Bei Bei

2016-10-01

With the change of climate, agricultural drought has directly threatened the food security. Based on the natural disaster risk theory, we analyzed the spatial and temporal characteristics of agricultural drought in Shanxi Province from 2009 to 2013. Four risk factors (hazard, exposure, vulnerability, and drought resistance ability) were selected with the consideration of influence factors of drought disasters. Subsequently, the index weight was determined by the analytic hierarchy process (AHP) and the aggregative indicator of natural disaster risk was established. The results showed that during the study period, the agricultural drought risk slightly declined in the northern Shaanxi, but increased sharply in the southern Shaanxi, especially in Shangluo City. While for the central part of Shaanxi Province, it maintained good stability, which was the highest in Xianyang City and the lowest in Xi'an City. Generally, the agricultural drought risk in Shaanxi Province gradually increased from south to north.

Multisource Data-Based Integrated Agricultural Drought Monitoring in the Huai River Basin, China

NASA Astrophysics Data System (ADS)

Sun, Peng; Zhang, Qiang; Wen, Qingzhi; Singh, Vijay P.; Shi, Peijun

2017-10-01

Drought monitoring is critical for early warning of drought hazard. This study attempted to develop an integrated remote sensing drought monitoring index (IRSDI), based on meteorological data for 2003-2013 from 40 meteorological stations and soil moisture data from 16 observatory stations, as well as Moderate Resolution Imaging Spectroradiometer data using a linear trend detection method, and standardized precipitation evapotranspiration index. The objective was to investigate drought conditions across the Huai River basin in both space and time. Results indicate that (1) the proposed IRSDI monitors and describes drought conditions across the Huai River basin reasonably well in both space and time; (2) frequency of drought and severe drought are observed during April-May and July-September. The northeastern and eastern parts of Huai River basin are dominated by frequent droughts and intensified drought events. These regions are dominated by dry croplands, grasslands, and highly dense population and are hence more sensitive to drought hazards; (3) intensified droughts are detected during almost all months except January, August, October, and December. Besides, significant intensification of droughts is discerned mainly in eastern and western Huai River basin. The duration and regions dominated by intensified drought events would be a challenge for water resources management in view of agricultural and other activities in these regions in a changing climate.

Drought Monitoring for 3 North American Case Studies Based on the North American Land Data Assimilation System (NLDAS)

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Mocko, David; Kumar, Sujay; Ek, Michael; Xia, Youlong; Dong, Jiarui

2012-01-01

Both NLDAS Phase 1 (1996-2007) and Phase 2 (1979-present) datasets have been evaluated against in situ observational datasets, and NLDAS forcings and outputs are used by a wide variety of users. Drought indices and drought monitoring from NLDAS were recently examined by Mo et al. (2010) and Sheffield et al. (2010). In this poster, we will present results analyzing NLDAS Phase 2 forcings and outputs for 3 North American Case studies being analyzed as part of the NOAA MAPP Drought Task Force: (1) Western US drought (1998- 2004); (2) plains/southeast US drought (2006-2007); and (3) Current Texas-Mexico drought (2011-). We will examine percentiles of soil moisture consistent with the NLDAS drought monitor.

Exploring drought vulnerability in Africa: an indicator based analysis to be used in early warning systems

NASA Astrophysics Data System (ADS)

Naumann, G.; Barbosa, P.; Garrote, L.; Iglesias, A.; Vogt, J.

2014-05-01

We propose a composite drought vulnerability indicator (DVI) that reflects different aspects of drought vulnerability evaluated at Pan-African level for four components: the renewable natural capital, the economic capacity, the human and civic resources, and the infrastructure and technology. The selection of variables and weights reflects the assumption that a society with institutional capacity and coordination, as well as with mechanisms for public participation, is less vulnerable to drought; furthermore, we consider that agriculture is only one of the many sectors affected by drought. The quality and accuracy of a composite indicator depends on the theoretical framework, on the data collection and quality, and on how the different components are aggregated. This kind of approach can lead to some degree of scepticism; to overcome this problem a sensitivity analysis was done in order to measure the degree of uncertainty associated with the construction of the composite indicator. Although the proposed drought vulnerability indicator relies on a number of theoretical assumptions and some degree of subjectivity, the sensitivity analysis showed that it is a robust indicator and hence able of representing the complex processes that lead to drought vulnerability. According to the DVI computed at country level, the African countries classified with higher relative vulnerability are Somalia, Burundi, Niger, Ethiopia, Mali and Chad. The analysis of the renewable natural capital component at sub-basin level shows that the basins with high to moderate drought vulnerability can be subdivided into the following geographical regions: the Mediterranean coast of Africa; the Sahel region and the Horn of Africa; the Serengeti and the Eastern Miombo woodlands in eastern Africa; the western part of the Zambezi Basin, the southeastern border of the Congo Basin, and the belt of Fynbos in the Western Cape province of South Africa. The results of the DVI at the country level were compared with drought disaster information from the EM-DAT disaster database. Even if a cause-effect relationship cannot be established between the DVI and the drought disaster database, a good agreement is observed between the drought vulnerability maps and the number of persons affected by droughts. These results are expected to contribute to the discussion on how to assess drought vulnerability and hopefully contribute to the development of drought early warning systems in Africa.

Assessing changes in drought characteristics with standardized indices

NASA Astrophysics Data System (ADS)

Vidal, Jean-Philippe; Najac, Julien; Martin, Eric; Franchistéguy, Laurent; Soubeyroux, Jean-Michel

2010-05-01

Standardized drought indices like the Standardized Precipitation Index (SPI) are more and more frequently adopted for drought reconstruction, monitoring and forecasting, and the SPI has been recently recommended by the World Meteorological Organization to characterize meteorological droughts. Such indices are based on the statistical distribution of a hydrometeorological variable (e.g., precipitation) in a given reference climate, and a drought event is defined as a period with continuously negative index values. Because of the way these indices are constructed, some issues may arise when using them in a non-stationnary climate. This work thus aims at highlighting such issues and demonstrating the different ways these indices may - or may not - be applied and interpreted in the context of an anthropogenic climate change. Three major points are detailed through examples taken from both a high-resolution gridded reanalysis dataset over France and transient projections from the ARPEGE general circulation model downscaled over France. The first point deals with the choice of the reference climate, and more specifically its type (from observations/reanalysis or from present-day modelled climate) and its record period. Second, the interpretation of actual changes are closely linked with the type of the selected drought feature over a future period: mean index value, under-threshold frequency, or drought event characteristics (number, mean duration and magnitude, seasonality, etc.). Finally, applicable approaches as well as related uncertainties depend on the availability of data from a future climate, whether in the form of a fully transient time series from present-day or only a future time slice. The projected evolution of drought characteristics under climate change must inform present decisions on long-term water resources planning. An assessment of changes in drought characteristics should therefore provide water managers with appropriate information that can help building effective adaptation strategies. This work thus aims at showing the potential of standardized indices to describe changes in drought characteristics, but also possible pitfalls and potentially misleading interpretations.

Unprecedented drought over tropical South America in 2016: significantly under-predicted by tropical SST.

PubMed

Erfanian, Amir; Wang, Guiling; Fomenko, Lori

2017-07-19

Tropical and sub-tropical South America are highly susceptible to extreme droughts. Recent events include two droughts (2005 and 2010) exceeding the 100-year return value in the Amazon and recurrent extreme droughts in the Nordeste region, with profound eco-hydrological and socioeconomic impacts. In 2015-2016, both regions were hit by another drought. Here, we show that the severity of the 2015-2016 drought ("2016 drought" hereafter) is unprecedented based on multiple precipitation products (since 1900), satellite-derived data on terrestrial water storage (since 2002) and two vegetation indices (since 2004). The ecohydrological consequences from the 2016 drought are more severe and extensive than the 2005 and 2010 droughts. Empirical relationships between rainfall and sea surface temperatures (SSTs) over the tropical Pacific and Atlantic are used to assess the role of tropical oceanic variability in the observed precipitation anomalies. Our results indicate that warmer-than-usual SSTs in the Tropical Pacific (including El Niño events) and Atlantic were the main drivers of extreme droughts in South America, but are unable to explain the severity of the 2016 observed rainfall deficits for a substantial portion of the Amazonia and Nordeste regions. This strongly suggests potential contribution of non-oceanic factors (e.g., land cover change and CO2-induced warming) to the 2016 drought.

European drought climatologies for the period 1950 to 2012

NASA Astrophysics Data System (ADS)

Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen V.; Barbosa, Paulo

2014-05-01

In the context of global climate change, characterized in particular by rising temperatures and more extreme weather events, drought is one of the most relevant natural disasters that has hit Europe frequently in the last decades. This paper presents climatologies of a set of drought indicators and derived drought characteristics at European scale for the period 1950-2012. Following the definitions in Spinoni et al. (2013), we computed drought frequency, duration, severity, and maximum intensity on a grid with spatial resolution of 0.25°x0.25°. Calculations have been based on three well-known drought indicators calculated for time scales of 3 and 12 months: the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). Indicators have been calculated on a monthly basis for the period 1951-2012, using statistical distributions fitted to a 30-year baseline period (1971-2000). Input data stem from the E-OBS (version 9.0) European grids (0.25°x0.25°) provided by the Royal Meteorological Service of The Netherlands (KNMI). Monthly precipitation data served as input for all indicators, while mean monthly temperature data were used to calculate Thornthwaite's potential evapotranspiration necessary to calculate SPEI and RDI. On the basis of these indicators, we then quantified, on a monthly basis, the total European area under meteorological drought conditions from 1950 to 2012 and their intensity. We further sub-divided Europe into 14 regions according to geographical borders and climatic features and for each of them we computed linear trends of different drought characteristics (i.e. frequency, duration, severity, and intensity) for the entire period, and for the sub-periods 1951-1980 and 1981-2010. Results show that the Mediterranean, the Balkans, and Eastern Europe are characterized by increasing drought frequency, duration, severity, and maximum intensity, while Russia and Northern Europe are characterized by a decrease, in particular with respect to drought severity. Finally, the most relevant drought events per region are presented. Spinoni J., Naumann G., Carrao, H., Barbosa P., and Vogt J.V. (2013): World drought frequency, duration, and severity for 1951-2010. Int. J. Climatol., DOI: 10.1002/joc.3875.

Vegetation canopy and physiological control of GPP decline during drought and heat wave

NASA Astrophysics Data System (ADS)

Zhang, Y.; Xiao, X.; Zhou, S.; McCarthy, H. R.; Ciais, P.; Luo, Y.

2015-12-01

Different vegetation indices derived from satellites were often used as a proxy of vegetation activity to monitor and evaluate the impacts of drought and heat wave on ecosystem carbon fluxes (gross primary production, respiration) through the production efficiency models (PEMs). However, photosynthesis is also regulated by a series of physiological processes which cannot be directly observed through satellites. In this study, we analyzed the response of drought and heat wave induced GPP and climate anomaly from 15 Euroflux sites and the corresponding vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Correlation analysis suggests that the vegetation indices are more responsive to GPP variation in grasslands and open shrublands, but less responsive in forest ecosystems. Physiology control can be up to 20% of the total GPP during the drought period without changing the canopy structure. At temporal scale for each site, VPD and vegetation indices can be used to track the GPP for forest and non-forest, respectively. However, different stand characteristics should be taken into consideration for forest ecosystems. Based on the above findings, a conceptual model is built to illuminate the physiological and canopy control on the GPP during the drought period. Improvement for future PEMs should incorporate better indicators to deal with drought conditions for different ecosystems.

Benchmarking LSM root-zone soil mositure predictions using satellite-based vegetation indices

USDA-ARS?s Scientific Manuscript database

The application of modern land surface models (LSMs) to agricultural drought monitoring is based on the premise that anomalies in LSM root-zone soil moisture estimates can accurately anticipate the subsequent impact of drought on vegetation productivity and health. In addition, the water and energy ...

Drought frequency in central California since 101 B.C. recordered in giant sequoia tree rings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hughes, M.K.; Brown, P.M.

1992-01-01

Well replicated tree-ring width index chronologies have been developed for giant sequoia at three sites in the Sierra Nevada, California. Extreme low-growth events in these chronologies correspond with regional drought events in the twentieth century in the San Joaquin drainage, in which the giant sequoia sites are located. This relationship is based upon comparison of tree-ring indices with August Palmer Drought Severity Indices for California Climate Division 5. Ring-width indices in the lowest decile from each site were compared. The frequency of low-growth events which occurred at all three sites in the same year is reconstructed from 101 B.C. tomore » A.D. 1988. The inferred frequency of severe drought events changes through time, sometimes suddenly. The period from roughly 1850 to 1950 had one of the lowest frequencies of drought of any one hundred year period in the 2089 year record. The twentieth century so far has had a below-average frequency of extreme droughts. 26 refs., 6 figs., 1 tab.« less

Drought Characterisation Using Ground and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Hore, Sudipta Kumar; Werner, Micha; Maskey, Shreedhar

2016-04-01

The North-West of Bangladesh is frequently affected by drought, which may have profound impacts to different water related sectors. The characterisation and identification of drought is, however, challenging. Despite several standard drought indices being available it is important that indicators proposed in support of an effective drought management are related to the impacts drought may have. In this study we present the characterisation of drought in the districts of Rajshahi and Rangpur in North-Western Bangladesh. Drought indicators were developed using available temperature, precipitation, river discharge and groundwater level data, as well as from remotely sensed NDVI data. We compare these indicators to records of drought impacts to agriculture, fisheries and migration collected from relevant organisations, as well as through interviews with key stakeholders, key informants, and community leaders. The analysis shows that droughts occur frequently, with nine occurrences in the last 42 years, as found using common meteorological drought indicators. NDVI data corroborated these events, despite being only available from 2001. The agricultural sector was adversely impacted in all events, with impacts correlated to drought severity. Impacts to the fisheries sector were, however, reported only three times, though impacts to fisheries are less well recorded. Interestingly, the good relationship between meteorological drought indicators and agricultural impacts weakens in the last decade. This appears to be due to the intensification of irrigation using groundwater, with the declining groundwater levels found in Rajshahi district suggesting overexploitation of the resource, and the increasing importance of groundwater drought indicators. The study reveals the drought indicators that are important to the agriculture and fisheries sectors, and also tentative threshold values at which drought start to impact these sectors. Such sector relevant drought indicators, as well as appropriate thresholds, can be useful in drought identification and management.

A Hybrid Index for Characterizing Drought Based on a Nonparametric Kernel Estimator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong

This study develops a nonparametric multivariate drought index, namely, the Nonparametric Multivariate Standardized Drought Index (NMSDI), by considering the variations of both precipitation and streamflow. Building upon previous efforts in constructing Nonparametric Multivariate Drought Index, we use the nonparametric kernel estimator to derive the joint distribution of precipitation and streamflow, thus providing additional insights in drought index development. The proposed NMSDI are applied in the Wei River Basin (WRB), based on which the drought evolution characteristics are investigated. Results indicate: (1) generally, NMSDI captures the drought onset similar to Standardized Precipitation Index (SPI) and drought termination and persistence similar tomore » Standardized Streamflow Index (SSFI). The drought events identified by NMSDI match well with historical drought records in the WRB. The performances are also consistent with that by an existing Multivariate Standardized Drought Index (MSDI) at various timescales, confirming the validity of the newly constructed NMSDI in drought detections (2) An increasing risk of drought has been detected for the past decades, and will be persistent to a certain extent in future in most areas of the WRB; (3) the identified change points of annual NMSDI are mainly concentrated in the early 1970s and middle 1990s, coincident with extensive water use and soil reservation practices. This study highlights the nonparametric multivariable drought index, which can be used for drought detections and predictions efficiently and comprehensively.« less

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

NASA Astrophysics Data System (ADS)

Konapala, Goutam; Mishra, Ashok

2017-12-01

The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought propagation as well as other hydroclimatic extreme events. Although the propagation of droughts is investigated using the network approach, however process (physics) based approaches is essential to further understand the dynamics of hydroclimatic extreme events.

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less

The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

NASA Astrophysics Data System (ADS)

Linés, Clara; Werner, Micha; Bastiaanssen, Wim

2017-09-01

The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

NASA Astrophysics Data System (ADS)

Park, D. H.; Lee, J. Y.; Lee, J. H.; KIm, T. W.

2017-12-01

Drought monitoring has already been extensively studied due to the widespread impacts and complex causes of drought. The most important component of drought monitoring is to estimate the characteristics and extent of drought by quantitatively measuring the characteristics of drought. Drought assessment considering different aspects of the complicated drought condition and uncertainty of drought index is great significance in accurate drought monitoring. This study used the dynamic Naïve Bayesian Classifier (DNBC) which is an extension of the Hidden Markov Model (HMM), to model and classify drought by using various drought indices for integrated drought assessment. To provide a stable model for combined use of multiple drought indices, this study employed the DNBC to perform multi-index drought assessment by aggregating the effect of different type of drought and considering the inherent uncertainty. Drought classification was performed by the DNBC using several drought indices: Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Normalized Vegetation Supply Water Index (NVSWI)) that reflect meteorological, hydrological, and agricultural drought characteristics. Overall results showed that in comparison unidirectional (SPI, SDI, and NVSWI) or multivariate (Composite Drought Index, CDI) drought assessment, the proposed DNBC was able to synthetically classify of drought considering uncertainty. Model provided method for comprehensive drought assessment with combined use of different drought indices.

Satellite-based drought monitoring in Kenya in an operational setting

NASA Astrophysics Data System (ADS)

Klisch, A.; Atzberger, C.; Luminari, L.

2015-04-01

The University of Natural Resources and Life Sciences (BOKU) in Vienna (Austria) in cooperation with the National Drought Management Authority (NDMA) in Nairobi (Kenya) has setup an operational processing chain for mapping drought occurrence and strength for the territory of Kenya using the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI at 250 m ground resolution from 2000 onwards. The processing chain employs a modified Whittaker smoother providing consistent NDVI "Mondayimages" in near real-time (NRT) at a 7-daily updating interval. The approach constrains temporally extrapolated NDVI values based on reasonable temporal NDVI paths. Contrary to other competing approaches, the processing chain provides a modelled uncertainty range for each pixel and time step. The uncertainties are calculated by a hindcast analysis of the NRT products against an "optimum" filtering. To detect droughts, the vegetation condition index (VCI) is calculated at pixel level and is spatially aggregated to administrative units. Starting from weekly temporal resolution, the indicator is also aggregated for 1- and 3-monthly intervals considering available uncertainty information. Analysts at NDMA use the spatially/temporally aggregated VCI and basic image products for their monthly bulletins. Based on the provided bio-physical indicators as well as a number of socio-economic indicators, contingency funds are released by NDMA to sustain counties in drought conditions. The paper shows the successful application of the products within NDMA by providing a retrospective analysis applied to droughts in 2006, 2009 and 2011. Some comparisons with alternative products (e.g. FEWS NET, the Famine Early Warning Systems Network) highlight main differences.

Assessing Impacts of National Scale Droughts on Cereal Production

NASA Astrophysics Data System (ADS)

Udmale, P. D.; Ichikawa, Y.

2017-12-01

Till date, several drought indices have been developed and used to monitor local to regional scale droughts on various temporal scales. However, there are no generalized criteria to define a threshold to declare a national level drought using drought indices. EM-DAT (a global database on natural and technological disasters) lists disasters (including drought) from 1900 until the present confirming one of the following criteria: 10 or more people dead; 100 or more people affected; the declaration of a state of emergency; or a call for international assistance. This data is gathered from various organizations like United Nations Institutes, Governments, etc. and do not cover all disasters or have political limitations that could affect the numbers. These criteria are neither objective nor quantitative, and accordingly may cause uncertainties when the data is used for further investigation on disaster impacts. Here we present a methodology to define drought at a national scale and its impacts on national level crop production (mainly cereals). We define drought based on the percentage of cropland area affected by drought in a country during its seasonal rainfall. For this purpose meteorological definition of drought in combination with country's cropland area is proposed to prepare a drought inventory for major cereal producing countries (1902-2012). This drought inventory together with FAO's Crop data is used to identify the impacts of drought on a national level cereal production (and yield) using Superposed Epoch Analysis for the period 1961-2012.

The Impact of Land-Atmosphere Coupling on the 2017 Northern Great Plains Drought

NASA Astrophysics Data System (ADS)

Roundy, J. K.; Santanello, J. A., Jr.

2017-12-01

In a changing climate, the potential for increased frequency and duration of drought implies devastating impacts on many aspects of society. The negative impacts of drought can be reduced through informing sustainable water management made possible by real-time monitoring and prediction. The refinement of forecast models is best realized through large-scale observation based datasets, yet there are few of these datasets currently available. The Coupling Drought Index (CDI) is a metric based on the persistence of Land-Atmosphere (L-A) coupling into distinct regimes derived from observations of the land and atmospheric state. The coupling regime persistence has been shown to relate to drought intensification and recovery and is the basis for the Coupling Statistical Model (CSM), which uses a Markov Chain framework to make statistical predictions. The CDI and CSM have been used to understand the predictability of L-A interactions in NCEP's Climate Forecasts System version 2 (CFSv2) and indicated that the forecasts exhibit strong biases in the L-A coupling that produced biases in the precipitation and limited the predictability of drought. The CDI can also be derived exclusively from satellite data which provides an observational large-scale metric of L-A coupling and drought evolution. This provides a unique observational tool for understanding the persistence and intensification of drought through land-atmosphere interactions. During the Spring and Summer of 2017, a drought developed over the Norther great plains that caused substantial agricultural losses in parts of Montana and North and South Dakota. In this work, we use satellite derived CDI to explore the impact of Land-Atmosphere Interactions on the persistence and intensification of the 2017 Northern Great Plains drought. To do this we analyze and quantify the change in CDI at various spatial and temporal scales and correlate these changes with other drought indicators including the U.S. Drought Monitor (http://droughtmonitor.unl.edu). The 2017 Northern Great Plains drought is compared to previous droughts in the region and the predictability of 2017 drought from the CSM as well as future droughts for the area is assessed.

Spatial comparability of drought characteristics and related return periods in mainland China over 1961-2013

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Yao, Ning

2017-07-01

The proper understanding of the spatiotemporal characteristics of multi-year droughts and return periods is important for drought risk assessment. This study evaluated and compared the spatiotemporal variations of drought characteristics and return periods within mainland China between 1961 and 2013. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Composite Index (CI) were calculated at multiple timescales, the run theory was used for objective identification and characterization of drought events while Kendall's τ method was used to analyze their dependencies. Within the univariate framework, marginal distributions of duration, severity, and peak were derived by fitting Exponential, Weibull and GDP distributions respectively and the drought return periods was investigated and mapped. Comparison of drought indices showed that SPEI and CI performed better than SPI in delineating spatial patterns of drought characteristics. This might be attributed to the temperature effect on evapotranspiration and therefore on drought index. Considering the increasing trend in reference evapotranspiration in the 21st century, the importance of utilizing temperature-based drought index is imperative. Severe and extreme droughts occurred in the late 1990s in many places in China while persistent multi-year severe droughts occurred more frequently over North China, Northeast China, Northwest China and Southwest China. The spatial patterns showed that regions characterized by higher drought severity were associated with higher drought duration. The North China, Northwest China, and Southwest China had much longer drought durations during the 1990s and 2000s. As droughts normally cover large areas, regional drought return periods has been showed to be more effective in providing support for drought management than station based drought return periods. Studies on the spatial comparability of drought return periods across mainland China have therefore been undertaken for drought mitigation and effective utilization of water resources.

Development of a Strategic Framework for Drought Management

NASA Astrophysics Data System (ADS)

Kang, Jaewon; Kim, Sooyoung; Suh, Aesook; Cho, Younghyun

2017-04-01

A drought starts with lack of precipitation; as the deficit of precipitation is prolonged, the loss of water influences on the amount of soil water because of evapotranspiration. In addition, the decreased runoff of surface and underground water also reduces discharge in rivers and storage in reservoirs; these reductions then lead to the decline in the supply capability of water resources supply facilities. Therefore, individuals may experience a given drought differently depending on their circumstances. In an area with a metropolitan water supply network that draws water from a multipurpose dam, residents might not realize that a meteorological drought is present since they are provided with sufficient water. Similar situation might occur in farmlands for which an irrigation system supplies water from an agricultural reservoir. In Korea, several institutions adopt each drought indices in their roles. Since March 2016, the Ministry of Public Safety and Security, via inter-ministerial cooperation, has been classifying and announcing drought situations in each administrative district of Korea into three types, meteorological, agricultural, or hydrological droughts, with three levels such as 'caution,' 'serious,' or 'very serious.' Deriving the drought index considering storage facilities and other factors and expressing them in three categories are valid as methods. However, the current method that represent the drought situation in an administrative district as a whole should be improved to recognize the drought situation more realistically and to make appropriate strategic responses. This study designs and implements a pilot model of a framework that re-establishes zones for drought situation representation, taking water usage and water supply infrastructure into account based on land use maps. In addition, each resulting district is provided with statistical indices that can assist in the application of appropriate drought indices and the understanding of situations. In the framework, different areas classified as forest/grassland, paddy fields with an irrigation system, paddy/dry fields relying on rainwater, areas with a metropolitan or provincial water supply, or areas with other residential/industrial water supply, in a single administrative district have different values for meteorological, agricultural, or hydrological droughts. And the situation can be analyzed on a daily basis to take into account areas with a possibility that the drought may be relieved by a short-term downpour or similar event. Keywords: drought management, strategic framework, drought indices

Women in Mauritania: The Effects of Drought and Migration on Their Economic Status and Implications for Development Programs.

ERIC Educational Resources Information Center

Smale, Melinda

In order to indicate potential income-generating programs for women, 67 women in the river region and selected sites in the Assaba and the Guidimakha were interviewed in 1980 to illuminate effects of the 1970s-80s drought and male migration on Mauritanian women. Hypotheses were based on the drought causing unprecedented disruption to Mauritanian…

Assessment of MODIS-derived indices (2001-2013) to drought across Taiwan's forests

NASA Astrophysics Data System (ADS)

Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

2018-05-01

Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan ( r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

Assessment of MODIS-derived indices (2001-2013) to drought across Taiwan's forests

NASA Astrophysics Data System (ADS)

Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

2017-12-01

Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan (r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

A Global Drought Observatory for Emergency Response

NASA Astrophysics Data System (ADS)

Vogt, Jürgen; de Jager, Alfred; Carrão, Hugo; Magni, Diego; Mazzeschi, Marco; Barbosa, Paulo

2016-04-01

Droughts are occurring on all continents and across all climates. While in developed countries they cause significant economic and environmental damages, in less developed countries they may cause major humanitarian catastrophes. The magnitude of the problem and the expected increase in drought frequency, extent and severity in many, often highly vulnerable regions of the world demand a change from the current reactive, crisis-management approach towards a more pro-active, risk management approach. Such approach needs adequate and timely information from global to local scales as well as adequate drought management plans. Drought information systems are important for continuous monitoring and forecasting of the situation in order to provide timely information on developing drought events and their potential impacts. Against this background, the Joint Research Centre (JRC) is developing a Global Drought Observatory (GDO) for the European Commission's humanitarian services, providing up-to-date information on droughts world-wide and their potential impacts. Drought monitoring is achieved by a combination of meteorological and biophysical indicators, while the societal vulnerability to droughts is assessed through the targeted analysis of a series of social, economic and infrastructural indicators. The combination of the information on the occurrence and severity of a drought, on the assets at risk and on the societal vulnerability in the drought affected areas results in a likelihood of impact, which is expressed by a Likelihood of Drought Impact (LDI) indicator. The location, extent and magnitude of the LDI is then further analyzed against the number of people and land use/land cover types affected in order to provide the decision bodies with information on the potential humanitarian and economic bearings in the affected countries or regions. All information is presented through web-mapping interfaces based on OGC standards and customized reports can be drawn by the user. The system will be further developed by increasing the number of sectorial impact indicators and validated against known and documented cases around the world. The poster will provide an overview on the system, the LDI and first analysis results.

Regional analysis and derivation of copula-based drought Severity-Area-Frequency curve in Lake Urmia basin, Iran.

PubMed

Amirataee, Babak; Montaseri, Majid; Rezaie, Hossein

2018-01-15

Droughts are extreme events characterized by temporal duration and spatial large-scale effects. In general, regional droughts are affected by general circulation of the atmosphere (at large-scale) and regional natural factors, including the topography, natural lakes, the position relative to the center and the path of the ocean currents (at small-scale), and they don't cover the exact same effects in a wide area. Therefore, drought Severity-Area-Frequency (S-A-F) curve investigation is an essential task to develop decision making rule for regional drought management. This study developed the copula-based joint probability distribution of drought severity and percent of area under drought across the Lake Urmia basin, Iran. To do this end, one-month Standardized Precipitation Index (SPI) values during the 1971-2013 were applied across 24 rainfall stations in the study area. Then, seven copula functions of various families, including Clayton, Gumbel, Frank, Joe, Galambos, Plackett and Normal copulas, were used to model the joint probability distribution of drought severity and drought area. Using AIC, BIC and RMSE criteria, the Frank copula was selected as the most appropriate copula in order to develop the joint probability distribution of severity-percent of area under drought across the study area. Based on the Frank copula, the drought S-A-F curve for the study area was derived. The results indicated that severe/extreme drought and non-drought (wet) behaviors have affected the majority of study areas (Lake Urmia basin). However, the area covered by the specific semi-drought effects is limited and has been subject to significant variations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of meteorological droughts on agricultural water resources in southern China

NASA Astrophysics Data System (ADS)

Lu, Houquan; Wu, Yihua; Li, Yijun; Liu, Yongqiang

2017-05-01

With the global warming, frequencies of drought are rising in the humid area of southern China. In this study, the effects of meteorological drought on the agricultural water resource based on the agricultural water resource carrying capacity (AWRCC) in southern China were investigated. The entire study area was divided into three regions based on the distributions of climate and agriculture. The concept of the maximum available water resources for crops was used to calculate AWRCC. Meanwhile, an agricultural drought intensity index (ADI), which was suitable for rice planting areas, was proposed based on the difference between crop water requirements and precipitation. The actual drought area and crop yield in drought years from 1961 to 2010 were analyzed. The results showed that ADI and AWRCC were significantly correlated with the actual drought occurrence area and food yield in the study area, which indicated ADI and AWRCC could be used in drought-related studies. The effects of seasonal droughts on AWRCC strongly depended on both the crop growth season and planting structure. The influence of meteorological drought on agricultural water resources was pronounced in regions with abundant water resources, especially in Southwest China, which was the most vulnerable to droughts. In Southwest China, which has dry and wet seasons, reducing the planting area of dry season crops and rice could improve AWRCC during drought years. Likewise, reducing the planting area of double-season rice could improve AWRCC during drought years in regions with a double-season rice cropping system. Our findings highlight the importance of adjusting the proportions of crop planting to improve the utilization efficiency of agricultural water resources and alleviate drought hazards in some humid areas.

Application of Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

NASA Astrophysics Data System (ADS)

Jayasinghe, S.; Dutta, R.; Basnayake, S. B.; Granger, S. L.; Andreadis, K. M.; Das, N.; Markert, K. N.; Cutter, P. G.; Towashiraporn, P.; Anderson, E.

2017-12-01

The Lower Mekong Region has been experiencing frequent and prolonged droughts resulting in severe damage to agricultural production leading to food insecurity and impacts on livelihoods of the farming communities. Climate variability further complicates the situation by making drought harder to forecast. The Regional Drought and Crop Yield Information System (RDCYIS), developed by SERVIR-Mekong, helps decision makers to take effective measures through monitoring, analyzing and forecasting of drought conditions and providing early warnings to farmers to make adjustments to cropping calendars. The RDCYIS is built on regionally calibrated Regional Hydrologic Extreme Assessment System (RHEAS) framework that integrates the Variable Infiltration Capacity (VIC) and Decision Support System for Agro-technology Transfer (DSSAT) models, allowing both nowcast and forecast of drought. The RHEAS allows ingestion of numerus freely available earth observation and ground observation data to generate and customize drought related indices, variables and crop yield information for better decision making. The Lower Mekong region has experienced severe drought in 2016 encompassing the region's worst drought in 90 years. This paper presents the simulation of the 2016 drought event using RDCYIS based on its hindcast and forecast capabilities. The regionally calibrated RDCYIS can help capture salient features of drought through a variety of drought indices, soil variables, energy balance variables and water balance variables. The RDCYIS is capable of assimilating soil moisture data from different satellite products and perform ensemble runs to further reduce the uncertainty of it outputs. The calibrated results have correlation coefficient around 0.73 and NSE between 0.4-0.5. Based on the acceptable results of the retrospective runs, the system has the potential to generate reliable drought monitoring and forecasting information to improve decision-makings at operational, technological and institutional level of mandated institutes of lower Mekong countries. This is turn would help countries to prepare for and respond to drought situations by taking short and long-term risk mitigation measures such as adjusting cropping calendars, rainwater harvesting, and so on.

Regional droughts and food security relationships in the Zambezi River Basin

NASA Astrophysics Data System (ADS)

Tirivarombo, S.; Hughes, D. A.

Analyses of long records of rainfall data indicate that the African climate has always been variable both intra-seasonally and inter-seasonally. Associated with this variability are extreme flood and drought events that have impacted negatively on the availability and use of water resources. It is necessary to put into perspective the historical variability so as to provide a background against which future projections and a basis for adaptive management can be made. In Africa this process is complicated by the fact that data availability is sparse and of limited spatial coverage thus posing some degree of uncertainty. These limitations have in some cases compelled researchers to resort to different sources of data but the outcomes may be fraught with inconsistencies between the datasets. Three monthly rainfall data sets CRU, GHCN and locally gauged data for the period 1960-2002 were used to generate standardized precipitation indices (SPI) for a comparative analysis of an agricultural drought in relation to food security in selected parts of the Zambezi River Basin. The aim of the study was to calibrate a rainfall based drought index for crop production forecasts, to check whether the approach (using global data sets) could be used with climate change data for future predictions and to establish the best predictor combination of drought indices. Standardized Precipitation Indices (SPIs) appropriate to the life cycle of a crop were generated using the SPATSIM (spatial and time series information modeling) software package and these were examined for detectable trends during the planting and growing stages. FAO crop production statistics were used to validate the results. The results indicated that the SPI could be used as a drought monitoring tool if used in conjunction with other drought indices. There was no significant difference between the uses of different sets of data in the generation of the drought indices.

Indonesian drought monitoring from space. A report of SAFE activity: Assessment of drought impact on rice production in Indonesia by satellite remote sensing and dissemination with web-GIS

NASA Astrophysics Data System (ADS)

Shofiyati, Rizatus; Takeuchi, Wataru; Sofan, Parwati; Darmawan, Soni; Awaluddin; Supriatna, Wahyu

2014-06-01

Long droughts experienced in Indonesia in the past are identified as one of the main factors in the failure of rice production. In this regard, special attention to monitor the condition is encouraged to reduce the damage. Currently, various satellite data and approaches can withdraw valuable information for monitoring and anticipating drought hazards. Two types of drought, Meteorology and Agriculture, have been assessed. During the last 10 years, daily and monthly rainfall data derived from TRMM and GSMaP. MTSAT and AMSR-E data have been analyzed to identify meteorological drought. Agricultural drought has been studied by observing the character of some indices (EVI, VCI, VHI, LST, and NDVI) of sixteen-day and monthly MODIS data at a period of 5 years (2009 - 2013). Network for data transfer has been built between LAPAN (data provider), ICALRD (implementer), IAARD Cloud Computing, and University of Tokyo (technical supporter). A Web-GIS based Drought Monitoring Information System has been developed to disseminate the information to end users. This paper describes the implementation of remote sensing drought monitoring model and development of Web-GIS and satellite based information system.

Assessment of Drought Scenario in Western Nepal

NASA Astrophysics Data System (ADS)

Pandey, V. P.; Khatiwada, K. R.

2017-12-01

Drought is a frequent phenomenon in relatively drier western Nepal. Lack of hydro-climatic information with wider spatial coverage is hindering effective assessment of the drought events. Furthermore, drought assessment is not getting adequate attention in Nepal. This study aims to develop drought scenario for Western Nepal by evaluating various types of drought indices in Karnali River Basin (area = 4,6150 km2) and recommend the most suited set of indices for data-poor regions. On the climatic data at ten stations, drought indices were calculated from following seven selected indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), (self-calibrating) Palmer Drought Severity Index (scPDSI), Reconnaissance Drought Index (RDI), Standardized Streamflow Index (SSFI), and Palmer Hydrological Drought Index (PHDI). Initial results reflect that the basin is affected by severe meteorological drought. Most of the indices show the extreme dryness scenario during the years 1984-85, 1992-93, 1995, 2000, 20002, 2008-09, and 2012. The results from the stations with long-term temperature and precipitation data sets showed a higher (up to 0.9) correlation between SPI and RDI than for SPEI and other Palmer Drought Indices, which ranged from 0.6 to 0.8 only. This suggests ability of SPI to represent magnitude and duration of the drought events fairly well in the study basin, and therefore, has potential to represent drought dynamics in data-poor regions. Keywords: Drought; Karnali River Basin; Nepal Himalaya

Application of effective drought index for quantification of meteorological drought events: a case study in Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Byun, Hi-Ryong; Adamowski, Jan F.; Begum, Khaleda

2017-04-01

Drought indices (DIs) that quantify drought events by their onset, termination, and subsequent properties such as the severity, duration, and peak intensity are practical stratagems for monitoring and evaluating the impacts of drought. In this study, the effective drought index (EDI) calculated over daily timescales was utilized to quantify short-term (dry spells) and ongoing drought events using drought monitoring data in Australia. EDI was an intensive DI that considered daily water accumulation with a weighting function applied to daily rainfall data with the passage of time. A statistical analysis of the distribution of water deficit period relative to the base period was performed where a run-sum method was adopted to identify drought onset for any day ( i) with EDI i < 0 (rainfall below normal). Drought properties were enumerated in terms of (1) severity (AEDI ≡ accumulated sum of EDIi < 0), (2) duration (DS ≡ cumulative number of days with EDIi < 0), (3) peak intensity (EDImin ≡ minimum EDI of a drought event), (4) annual drought severity (YAEDI ≡ yearly accumulated negative EDI), and (5) accumulated severity of ongoing drought using event-accumulated EDI (EAEDI). The analysis of EDI signal enabled the detection and quantification of a number of drought events in Australia: Federation Drought (1897-1903), 1911-1916 Drought, 1925-1929 Drought, World War II Drought (1937-1945), and Millennium Drought (2002-2010). In comparison with the other droughts, Millennium Drought was exemplified as an unprecedented dry period especially in Victoria (EAEDI ≈ -4243, DS = 1946 days, EDImin = -4.05, and YAEDI = -4903). For the weather station tested in Northern Territory, the worst drought was recorded during 1925-1929 period. The results justified the suitability of effective drought index as a useful scientific tool for monitoring of drought progression, onset and termination, and ranking of drought based on severity, duration, and peak intensity, which allows an assessment of accumulated stress caused by short- and long-term (protracted) dry events.

Exploiting teleconnection indices for probabilistic forecasting of drought class transitions in Sicily region (Italy)

NASA Astrophysics Data System (ADS)

Bonaccorso, Brunella; Cancelliere, Antonino

2015-04-01

In the present study two probabilistic models for short-medium term drought forecasting able to include information provided by teleconnection indices are proposed and applied to Sicily region (Italy). Drought conditions are expressed in terms of the Standardized Precipitation-Evapotranspiration Index (SPEI) at different aggregation time scales. More specifically, a multivariate approach based on normal distribution is developed in order to estimate: 1) on the one hand transition probabilities to future SPEI drought classes and 2) on the other hand, SPEI forecasts at a generic time horizon M, as functions of past values of SPEI and the selected teleconnection index. To this end, SPEI series at 3, 4 and 6 aggregation time scales for Sicily region are extracted from the Global SPEI database, SPEIbase , available at Web repository of the Spanish National Research Council (http://sac.csic.es/spei/database.html), and averaged over the study area. In particular, SPEIbase v2.3 with spatial resolution of 0.5° lat/lon and temporal coverage between January 1901 and December 2013 is used. A preliminary correlation analysis is carried out to investigate the link between the drought index and different teleconnection patterns, namely: the North Atlantic Oscillation (NAO), the Scandinavian (SCA) and the East Atlantic-West Russia (EA-WR) patterns. Results of such analysis indicate a strongest influence of NAO on drought conditions in Sicily with respect to other teleconnection indices. Then, the proposed forecasting methodology is applied and the skill in forecasting of the proposed models is quantitatively assessed through the application of a simple score approach and of performance indices. Results indicate that inclusion of NAO index generally enhance model performance thus confirming the suitability of the models for short- medium term forecast of drought conditions.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

PubMed

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; Xie, Yangyang; Liu, Saiyan; Meng, Erhao; Li, Pei

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

A global examination of the response of ecosystem water-use efficiency to drought based on MODIS data.

PubMed

Huang, Ling; He, Bin; Han, Le; Liu, Junjie; Wang, Haiyan; Chen, Ziyue

2017-12-01

Ecosystem water-use efficiency (WUE) plays an important role in carbon and water cycles. Currently, the response of WUE to drought disturbance remains controversial. Based on the global ecosystem gross primary productivity (GPP) product and the evapotranspiration product (ET), both of which were retrieved from the moderate resolution imaging spectroradiometer (MODIS), as well as the drought index, this study comprehensively examined the relationship between ecosystem WUE (WUE=GPP/ET) and drought at the global scale. The response of WUE to drought showed large differences in various regions and biomes. WUE for arid ecosystems typically showed a negative response to drought, whereas WUE for humid ecosystems showed both positive and negative response to drought. Legacy effects of drought on ecosystem WUE were observed. Furthermore, ecosystems showed a sensitive response to abrupt changes in hydrological climatic conditions. The transition from wet to dry years should increase ecosystem WUE, and the opposite change in WUE should occur when an ecosystem experiences a transition from dry to wet years. This indicates the resilience of ecosystems to drought disturbance. Knowledge from this study should provide an in-depth understanding of ecosystem strategies for coping with drought. Copyright © 2017 Elsevier B.V. All rights reserved.

Future Drought Projections over the Iberian Peninsula using Drought Indices

NASA Astrophysics Data System (ADS)

Garcia-Valdecasas Ojeda, M.; Yeste Donaire, P.; Góngora García, T. M.; Gámiz-Fortis, S. R.; Castro-Diez, Y.; Esteban-Parra, M. J.

2017-12-01

Currently, drought events are the cause of numerous annual economic losses. In a context of climate change, it is expected an increase in the severity and the frequency of drought occurrences, especially in areas such as the Mediterranean region. This study makes use of two drought indices in order to analyze the potential changes on future drought events and their effects at different time scales over a vulnerable region, the Iberian Peninsula. The indices selected were the Standardized Precipitation Evapotranspiration Index (SPEI), which takes into account the global warming through the temperature, and the Standardized Precipitation Index (SPI), based solely on precipitation data, at a spatial resolution of 0.088º ( 10 km). For their computation, current (1980-2014) and future (2021-2050 and 2071-2100) high resolution simulations were carried out using the Weather Research and Forecasting (WRF) model over a domain centered in the Iberian Peninsula, and nested in the 0.44 EUROCORDEX region. WRF simulations were driven by two different global bias-corrected climate models: the version 1 of NCAR's Community Earth System Model (CESM1) and the Max Planck Institute's Earth System Model (MPI-ESM-LR), and under two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Future projections were analyzed regarding to changes in mean, median and variance of drought indices with respect to the historical distribution, as well as changes in the frequency and duration of moderate and severe drought events. In general, results suggest an increase in frequency and severity of drought, especially for 2071-2100 period in the RCP 8.5 scenario. Results also shown an increase of drought phenomena more evident using the SPEI. Conclusions from this study could provide a valuable contribution to the understanding of how the increase of the temperature would affect the drought variability in the Mediterranean regions which is necessary for a suitable decision making.Keywords: Drought, SPEI, SPI, Climatic change, Regional projections, WRF.ACKNOWLEDGEMENTS: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía) and CGL2013-48539-R (MINECO-Spain, FEDER). This analysis was carried out in the ALHAMBRA computer infrastructure at the University of Granada.

Agricultural biomass monitoring on watersheds based on remotely sensed data.

PubMed

Tamás, János; Nagy, Attila; Fehér, János

2015-01-01

There is a close quality relationship between the harmful levels of all three drought indicator groups (meteorological, hydrological and agricultural). However, the numerical scale of the relationships between them is unclear and the conversion of indicators is unsolved. Different areas or an area with different forms of drought cannot be compared. For example, from the evaluation of meteorological drought using the standardized precipitation index (SPI) values of a river basin, it cannot be stated how many tonnes of maize will be lost during a given drought period. A reliable estimated rate of yield loss would be very important information for the planned interventions (i.e. by farmers or river basin management organisations) in terms of time and cost. The aim of our research project was to develop a process which could provide information for estimating relevant drought indexes and drought related yield losses more effectively from remotely sensed spectral data and to determine the congruency of data derived from spectral data and from field measurements. The paper discusses a new calculation method, which provides early information on physical implementation of drought risk levels. The elaborated method provides improvement in setting up a complex drought monitoring system, which could assist hydrologists, meteorologists and farmers to predict and more precisely quantify the yield loss and the role of vegetation in the hydrological cycle. The results also allow the conversion of different-purpose drought indices, such as meteorological, agricultural and hydrological ones, as well as allow more water-saving agricultural land use alternatives to be planned in the river basins.

Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

NASA Astrophysics Data System (ADS)

Chanda, Kironmala; Maity, Rajib; Sharma, Ashish; Mehrotra, Rajeshwar

2014-10-01

This paper characterizes the long-term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability-resilience-vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five-yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area, indicating a reasonably good potential for drought management in the medium term water resources planning horizon.

Categorisation of Drought Indices Used in Agricultural Meteorology

NASA Astrophysics Data System (ADS)

Dunkel, Z.

2009-09-01

The research and the operative work use many type of indices in everyday meteorological practice. The goal of present summary is to group the indices used for identification of drought phenomenon in the agricultural meteorology practice. Besides summarising the indices the different drought definitions are evaluated. Drought indices seem to be the simplest tools in drought analysis. The more or less well known and popular indices have been collected and compared not only with the well known simple but more complicated water balance and so called ‘recursive' indices beside few ones use remotely sensed data, mainly satellite born information. The indices are classified into five groups, namely ‘precipitation', ‘water balance', ‘soil moisture', ‘recursive' and ‘remote sensing' indices. For every group typical expressions are given and analysed for their performance and comparability. Taking into consideration that the drought is a compound concept few drought definitions are examined together with the drought indices. As any classification the presented categories have got their limitation but the hope is that as wide review is given as it is possible using mainly meteorological data and information.

Dehydrin gene expression provides an indicator of low temperature and drought stress: transcriptome-based analysis of barley (Hordeum vulgare L.).

PubMed

Tommasini, Livia; Svensson, Jan T; Rodriguez, Edmundo M; Wahid, Abdul; Malatrasi, Marina; Kato, Kenji; Wanamaker, Steve; Resnik, Josh; Close, Timothy J

2008-11-01

Low temperature and drought have major influences on plant growth and productivity. To identify barley genes involved in responses to these stresses and to specifically test the hypothesis that the dehydrin (Dhn) multigene family can serve as an indicator of the entire transcriptome response, we investigated the response of barley cv. Morex to: (1) gradual drought over 21 days and (2) low temperature including chilling, freeze-thaw cycles, and deacclimation over 33 days. We found 4,153 genes that responded to at least one component of these two stress regimes, about one fourth of all genes called "present" under any condition. About 44% (1,822 of 4,153) responded specifically to drought, whereas only 3.8% (158 of 4,153) were chilling specific and 2.8% (119 of 4,153) freeze-thaw specific, with 34.1% responsive to freeze-thaw and drought. The intersection between chilling and drought (31.9%) was somewhat smaller than the intersection between freeze-thaw and drought, implying an element of osmotic stress response to freeze-thaw. About 82.4% of the responsive genes were similar to Arabidopsis genes. The expression of 13 barley Dhn genes mirrored the global clustering of all transcripts, with specific combinations of Dhn genes providing an excellent indicator of each stress response. Data from these studies provide a robust reference data set for abiotic stress.

Transition of the GOES Evapotranspiration and Drought Product System (GET-D) into Operations at NOAA/NESDIS

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Fang, L.; Zhan, X.; Otkin, J.

2016-12-01

Abnormally dry conditions can adversely affect the health of agricultural crops if the dryness persists for an extended period of time or if it occurs at a sensitive stage of crop development. Depending on its severity and timing, drought can result in significant yield loss, with impacts on both local and global markets as signified by reduced economic output and higher grain and food prices. Due to changing climate conditions, we are moving into a regime where processes controlling drought evolution are becoming more variable and are shifting in intensity, frequency and duration. The unusually rapid increase in water stress during some of these drought events are not well predicted by standard drought indicators. Different remote sensing indicators sample moisture and vegetation conditions occurring on different time scales during the typical evolution of agricultural drought. It has been shown that the thermal-based Evaporative Stress Index (ESI), based on land surface temperature, has an early warning component where vegetation stress manifested through decreased root-zone soil moisture leads to detectable vegetation stress in the LST signal before degradation in vegetation health is observed in VIS/NIR drought indices (e.g., NDVI). To provide this data to a larger user community and address the needs of our project stakeholders, the GOES Evapotranspiration and Drought Product System (GET-D) has been developed to operationally generate daily ET and ESI maps over the North America. The core model in GET-D is the Atmosphere-Land Exchange Inverse model (ALEXI), which is built on the two-source energy (TSEB) approach and partitions the GOES land surface temperature into characteristic soil and canopy temperatures, based on the fraction of vegetation cover. The primary operational data products of the GET-D system include the daily clear-sky ET and daily 2, 4, 8 and 12 week composites of the Evaporative Stress Index (ESI) computed from the ET daily estimates over North America at a spatial resolution of 8 km. This talk will focus on the evaluation of the operational data products, lessons learned from the transition into operations and the planned global expansion of the GET-D system at NOAA.

Modelling drought-related yield losses in Iberia using remote sensing and multiscalar indices

NASA Astrophysics Data System (ADS)

Ribeiro, Andreia F. S.; Russo, Ana; Gouveia, Célia M.; Páscoa, Patrícia

2018-04-01

The response of two rainfed winter cereal yields (wheat and barley) to drought conditions in the Iberian Peninsula (IP) was investigated for a long period (1986-2012). Drought hazard was evaluated based on the multiscalar Standardized Precipitation Evapotranspiration Index (SPEI) and three remote sensing indices, namely the Vegetation Condition (VCI), the Temperature Condition (TCI), and the Vegetation Health (VHI) Indices. A correlation analysis between the yield and the drought indicators was conducted, and multiple linear regression (MLR) and artificial neural network (ANN) models were established to estimate yield at the regional level. The correlation values suggested that yield reduces with moisture depletion (low values of VCI) during early-spring and with too high temperatures (low values of TCI) close to the harvest time. Generally, all drought indicators displayed greatest influence during the plant stages in which the crop is photosynthetically more active (spring and summer), rather than the earlier moments of plants life cycle (autumn/winter). Our results suggested that SPEI is more relevant in the southern sector of the IP, while remote sensing indices are rather good in estimating cereal yield in the northern sector of the IP. The strength of the statistical relationships found by MLR and ANN methods is quite similar, with some improvements found by the ANN. A great number of true positives (hits) of occurrence of yield-losses exhibiting hit rate (HR) values higher than 69% was obtained.

Middle-term Metropolitan Water Availability Index Assessment Based on Synergistic Potentials of Multi-sensor Data

EPA Science Inventory

The impact of recent drought and water pollution episodes results in an acute need to project future water availability to assist water managers in water utility infrastructure management within many metropolitan regions. Separate drought and water quality indices previously deve...

Forecasting European Droughts using the North American Multi-Model Ensemble (NMME)

NASA Astrophysics Data System (ADS)

Thober, Stephan; Kumar, Rohini; Samaniego, Luis; Sheffield, Justin; Schäfer, David; Mai, Juliane

2015-04-01

Soil moisture droughts have the potential to diminish crop yields causing economic damage or even threatening the livelihood of societies. State-of-the-art drought forecasting systems incorporate seasonal meteorological forecasts to estimate future drought conditions. Meteorological forecasting skill (in particular that of precipitation), however, is limited to a few weeks because of the chaotic behaviour of the atmosphere. One of the most important challenges in drought forecasting is to understand how the uncertainty in the atmospheric forcings (e.g., precipitation and temperature) is further propagated into hydrologic variables such as soil moisture. The North American Multi-Model Ensemble (NMME) provides the latest collection of a multi-institutional seasonal forecasting ensemble for precipitation and temperature. In this study, we analyse the skill of NMME forecasts for predicting European drought events. The monthly NMME forecasts are downscaled to daily values to force the mesoscale hydrological model (mHM). The mHM soil moisture forecasts obtained with the forcings of the dynamical models are then compared against those obtained with the Ensemble Streamflow Prediction (ESP) approach. ESP recombines historical meteorological forcings to create a new ensemble forecast. Both forecasts are compared against reference soil moisture conditions obtained using observation based meteorological forcings. The study is conducted for the period from 1982 to 2009 and covers a large part of the Pan-European domain (10°W to 40°E and 35°N to 55°N). Results indicate that NMME forecasts are better at predicting the reference soil moisture variability as compared to ESP. For example, NMME explains 50% of the variability in contrast to only 31% by ESP at a six-month lead time. The Equitable Threat Skill Score (ETS), which combines the hit and false alarm rates, is analysed for drought events using a 0.2 threshold of a soil moisture percentile index. On average, the NMME based ensemble forecasts have consistently higher skill than the ESP based ones (ETS of 13% as compared to 5% at a six-month lead time). Additionally, the ETS ensemble spread of NMME forecasts is considerably narrower than that of ESP; the lower boundary of the NMME ensemble spread coincides most of the time with the ensemble median of ESP. Among the NMME models, NCEP-CFSv2 outperforms the other models in terms of ETS most of the time. Removing the three worst performing models does not deteriorate the ensemble performance (neither in skill nor in spread), but would substantially reduce the computational resources required in an operational forecasting system. For major European drought events (e.g., 1990, 1992, 2003, and 2007), NMME forecasts tend to underestimate area under drought and drought magnitude during times of drought development. During drought recovery, this underestimation is weaker for area under drought or even reversed into an overestimation for drought magnitude. This indicates that the NMME models are too wet during drought development and too dry during drought recovery. In summary, soil moisture drought forecasts by NMME are more skillful than those of an ESP based approach. However, they still show systematic biases in reproducing the observed drought dynamics during drought development and recovery.

Effects of Geographic Diversification on Risk Pooling to Mitigate Drought-Related Financial Losses for Water Utilities

NASA Astrophysics Data System (ADS)

Baum, Rachel; Characklis, Gregory W.; Serre, Marc L.

2018-04-01

As the costs and regulatory barriers to new water supply development continue to rise, drought management strategies have begun to rely more heavily on temporary conservation measures. While these measures are effective, they often lead to intermittent and unpredictable reductions in revenues that are financially disruptive to water utilities, raising concerns over lower credit ratings and higher rates of borrowing for this capital intensive sector. Consequently, there is growing interest in financial risk management strategies that reduce utility vulnerabilities. This research explores the development of financial index insurance designed to compensate a utility for drought-related losses. The focus is on analyzing candidate hydrologic indices that have the potential to be used by utilities across the US, increasing the potential for risk pooling, which would offer the possibility of both lower risk management costs and more widespread implementation. This work first analyzes drought-related financial risks for 315 publicly operated water utilities across the country and examines the effectiveness of financial contracts based on several indices both in terms of their correlation with utility revenues and their spatial autocorrelation across locations. Hydrologic-based index insurance contracts are then developed and tested over a 120 year period. Results indicate that risk pooling, even under conditions in which droughts are subject to some level of spatial autocorrelation, has the potential to significantly reduce the cost of managing financial risk.

Development Of Index To Assess Drought Conditions Using Geospatial Data A Case Study Of Jaisalmer District, Rajasthan, India

NASA Astrophysics Data System (ADS)

Chhajer, Vaidehi; Prabhakar, Sumati; Rama Chandra Prasad, P.

2015-12-01

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006-2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

A new comprehensive index for drought monitoring with TM data

NASA Astrophysics Data System (ADS)

Wang, Yuanyuan

2017-10-01

Drought is one of the most important and frequent natural hazards to agriculture production in North China Plain. To improve agriculture water management, accurate drought monitoring information is needed. This study proposed a method for comprehensive drought monitoring by combining a meteorological index and three satellite drought indices of TM data together. SPI (Standard Precipitation Index), the meteorological drought index, is used to measure precipitation deficiency. Three satellite drought indices (Temperature Vegetation Drought Index, Land Surface Water Index, Modified Perpendicular Drought Index) are used to evaluate agricultural drought risk by exploring data from various channels (VIS, NIR, SWIR, TIR). Considering disparities in data ranges of different drought indices, normalization is implemented before combination. First, SPI is normalized to 0 — 100 given that its normal range is -4 - +4. Then, the three satellite drought indices are normalized to 0 - 100 according to the maximum and minimum values in the image, and aggregated using weighted average method (the result is denoted as ADI, Aggregated drought index). Finally, weighed geometric mean of SPI and ADI are calculated (the result is denoted as DIcombined). A case study in North China plain using three TM images acquired during April-May 2007 show that the method proposed in this study is effective. In spatial domain, DIcombined demonstrates dramatically more details than SPI; in temporal domain, DIcombined shows more reasonable drought development trajectory than satellite indices that are derived from independent TM images.

Drought vulnerability assessment for prioritising drought warning implementation

NASA Astrophysics Data System (ADS)

Naumann, Gustavo; Faneca Sànchez, Marta; Mwangi, Emmah; Barbosa, Paulo; Iglesias, Ana; Garrote, Luis; Werner, Micha

2014-05-01

Drought warning provides a potentially efficient approach to mitigation of drought impacts, and should be targeted at areas most vulnerable to being adversely impacted. Assessing drought vulnerability is, however, complex and needs to consider susceptibility to drought impact as well as the capacity to cope with drought. In this paper a Drought Vulnerability Index (DVI) is proposed that considers four primary components that reflect the capacity of society to adapt to drought; the renewable natural capital, the economic capacity, the human and civic resources, and the available infrastructure and technology. The DVI is established as a weighted combination of these four components, each a composite of selected indicators. Constituent indicators are calculated based on national and/or regional census data and statistics, and while the resulting DVI should not be considered an absolute measure of drought vulnerability it does provide for a prioritisation of areas that can be used to target drought warning efforts. Sensitivity analysis of weights applied show the established DVI to be robust. Through the DVI the development of drought forecasting and warning can be targeted at the most vulnerable areas. The proposed DVI is applied at both the continental scale in Africa to assess drought vulnerability of the different nations across Africa, and at the national level in Kenya, allowing for prioritisation of the counties within Kenya to drought vulnerability. Results show the relative vulnerability of countries and counties vulnerable to drought. At the continental scale, Somalia, Burundi, Niger, Ethiopia, Mali and Chad are found to be the countries most vulnerable to drought. At the national level, the relative vulnerability of the counties across Kenya is found, with counties in the North-East of Kenya having the highest values of DVI. At the country level results were compared with drought disaster information from the EM-DAT disaster database, showing a good agreement between recorded drought impact and the established DVI classes. Kenya counties most vulnerable to drought are primarily located in the North-East of the country, showing a reasonable agreement with the spatial distribution of impacts of the 2010/2011 drought, despite the drought itself being more widespread.

Influence of mathematical and physical background of drought indices on their complementarity and drought recognition ability

NASA Astrophysics Data System (ADS)

Frank, Anna; Armenski, Tanja; Gocic, Milan; Popov, Srdjan; Popovic, Ljiljana; Trajkovic, Slavisa

2017-09-01

The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation - Evapotranspiration Index (SPEI) - 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process.

Development of a global Agricultural Stress Index System (ASIS) based on remote sensing data

NASA Astrophysics Data System (ADS)

Van Hoolst, R.

2016-12-01

According to the 2012 IPCC SREX report, extreme drought events are projected to become more frequent and intense in several regions of the world. Wide and timely monitoring systems are required to mitigate the impact of agricultural drought. Therefore, FAO's Global Information and Early Warning System (GIEWS) and the Climate, Energy and Tenure Division (NRC) have established the `Agricultural Stress Index System' (ASIS). The ASIS is a remote sensing application that provides early warnings of agricultural drought at a global scale. The ASIS has first been designed and described by Rojas et al. (2011). This study focused on the African continent and was based on the back processing of low resolution data of the NOAA-satellites. In the current setup, developed by VITO (Flemish Institute for Technological Research), the system operates in Near Real Time using data from the METOP-AVHRR sensor. The Agricultural Stress Index (ASI) is the percentage of agricultural area affected by drought in the course of the growing season within a given administrative unit. The start and end of the growing season are derived per pixel from the long term NDVI average of SPOT-VEGETATION. The Global Administrative Unit Layer (GAUL) defines the administrative boundaries at level 0, 1 and 2. A global cropland and grassland map eliminates non-agricultural areas. Temperature and NDVI anomalies are used as drought indicators and calculated at a per pixel base. The ASIS aggregates this information and produces every dekad global maps to highlight hotspots of drought stress. New developments are ongoing to strengthen the ASIS to produce country specific outputs, improve existing drought indicators and estimate production deficits using a probabilistic approach.

Relating the dynamics of climatological and hydrological droughts in semiarid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.

2018-06-01

Dynamics of droughts have been an associated feature of climate variability particularly in semiarid regions which impact on the response of hydrological systems. This study attempts to determine drought timescale that is suitable for monitoring the effects of drought on hydrological systems which can then be used to assess the long term persistence or reversion and forecasts of the dynamics. Based on this, climatological and hydrological drought indices characterized by Standardized precipitation evapotranspiration index (SPEI) and Standardized flow index (SFI) respectively have been determined using monthly rainfall, temperature and flow data from two major river systems. The association between climatological and hydrological droughts in Botswana has been investigated using these river systems namely: Okavango that is predominantly a storage type and Limpopo which is non-storage for a period of 1975-2014. Dynamics of climatological and hydrological droughts are showing trends towards drying conditions at both river systems. It was also observed that hydrological droughts lag climatological droughts by 7 months in Limpopo and 6 months in Okavango river systems respectively. Analyses of the association between climatic and flow indices indicate that the degree of association becomes stronger with increasing timescale at the Okavango river system. However in the Limpopo river system, it was observed that high timescales of 18- and 24-months were not useful in drought monitoring. 15-months timescale was identified to best monitor drought dynamics at both locations. Therefore SPEIs and SFIs computed at 15-months timescale have been used to assess the variability and long term persistence in drought dynamics through rescaled range analysis (R/S). H-coefficients of 0.06 and 0.08 resulted for Limpopo and Okavango respectively. These H-coefficients being significantly less than 0.5 is an indication of high variability and suggests a change in dynamics from the existing conditions in these river systems. To forecast possible changes, the nonlinear autoregressive with exogenous input (NARX) artificial neural network model has been used. Results from this model agree with those of the R/S and projects generally dry conditions for the next 40 months. Results from this study are helpful not only in choosing a proper timescale but also in evaluating the futuristic drought dynamics necessary for water resources planning and management.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

DOE PAGES

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; ...

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

Monitoring Drought at Continental Scales Using Thermal Remote Sensing of Evapotranspiration (Invited)

NASA Astrophysics Data System (ADS)

Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.

2009-12-01

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for assessing standard meteorologically-based drought indicators, and may be more robust in regions with limited monitoring networks. In this study, monthly maps of ESI anomalies for 2000-2008 are compared to standard drought indices and to drought classifications in the U.S. Drought Monitor. The ESI shows better skill in ranking drought severity than do precipitation-based indices composited over comparable time intervals. The thermal remote sensing inputs to ALEXI detect drought conditions even under the dense forest cover along the East Coast of the United States, where microwave soil moisture retrievals typically lose sensitivity. On the other hand, microwave observations are not constrained by cloud cover and provide better temporal continuity, but typically at significantly lower spatial resolution. A merged TIR-microwave moisture anomaly product may have potential for optimizing both spatial and temporal coverage in continental-scale drought monitoring.

Comparison of SPI and SPEI indices for Drought Characterization under Climate Change Scenario in India

NASA Astrophysics Data System (ADS)

Gupta, V.; Jain, M. K.

2017-12-01

Many drought indices are available for quantifying and characterizing the drought events. Selection of a particular drought index could influence the outcome of the study. In this study, we compared two drought indices namely, Standardized precipitation index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) under climate change condition. Data from 7 RCM models namely, CCCma-CanESM2, CERFACS-CNRM-CM5, GFDL-ESM2M, MOHC-HadGEM2, MIROC-MIROC5, MPI-ESM-LR and MPI-ESM-MR for RCP 4.5 scenario have been used to calculate 12 month SPI and SPEI values. L-moments which provides robust distribution parameter estimation, have been used to identify best fit distribution for projected data at each grid point for each month. Mann-Kendall and Sen's slope test have been used to detect trends in drought severity, duration, peak, and interval between drought events. Results of this study reveal that SPI shows decreasing trends in drought severity, duration and peak with negative Sen's slope, however, the SPEI shows increasing trends of severity, duration and peak with a positive Sen's slope for almost all over India. The analysis reveals that projected percentage of drought affected area based on SPI in the first half of the 21st century is higher compared to those obtained using SPEI, however for the second half of the 21st century, the projected drought affected computed using SPEI is higher compared to the corresponding area obtained using SPI. Decrease in droughts severity, duration and peaks in SPI analysis could be attributed to projected increase in monsoon rainfall in Indian Subcontinent during second half of 21st century however, SPI was found incapable to account the increase in temperature thus neglecting the drying due to increased evapotranspiration whereas SPEI shows significant drying in Indian subcontinent on account of increasing trend in temperature observed in projected future RCM scenarios.

Evolution and characterization of drought events from GRACE and other satellite and observation.

NASA Astrophysics Data System (ADS)

Zhao, M.; A, G.; Velicogna, I.; Kimball, J. S.

2015-12-01

We use GRACE Terrestrial Water Storage (TWS) changes to calculate a newly developed global drought severity index (GRACE-DSI) for monthly monitoring of water supply changes during 2002-2015. We compare GRACE-DSI with Palmer Drought Severity Index (PDSI) and other ancillary data to characterize drought timing, evolution and magnitude in the continental US since 2002. Overall GRACE-DSI and PDSI show an excellent correspondence in the US. However PDSI is very sensitive to atmospheric moisture stress, while GRACE-DSI only responds to changes in terrestrial water storage. We use the complementary nature of these two indices together with temperature and precipitation observations to characterize drought evolution and its nature. For instance, during the 2012 flash drought in the Great Plains, the PDSI decreases several months earlier than the GRACE-DSI in response to the enhanced atmosphere moisture demand caused by unusual early season warming. When the drought peaks later in the summer, the PDSI indicates exceptional drought, while the GRACE-DSI observes moderate drought conditions in the underlying total water supply, implying a meteorological drought in nature. GRACE-DSI is based solely on satellite observations; hence it has the advantage of not being affected by uncertainty associated with variable that are not well known at the global scale (e.g. precipitation estimates) and by biases associated to global climate model outputs. We find that GRACE-DSI captures major drought events in the globe occurring during 2002-2015, including those in sub-Sahara Africa, Australia, Amazon, Asia, North America and the Arctic.

Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS.

PubMed

Bajgain, Rajen; Xiao, Xiangming; Basara, Jeffrey; Wagle, Pradeep; Zhou, Yuting; Zhang, Yao; Mahan, Hayden

2017-02-01

Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June-August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations (r 2  = 0.62-0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ∼30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

GRACE-Assimilated Drought Indicators for the U.S. Drought Monitor

NASA Technical Reports Server (NTRS)

Rui, Hualan; Vollmer, Bruce; Teng, Bill; Loeser, Carlee; Beaudoing, Hiroko; Rodell, Matt

2018-01-01

The Gravity Recovery and Climate Experiment (GRACE) mission detects changes in Earth's gravity field by precisely monitoring the changes in distance between two satellites orbiting the Earth in tandem. Scientists at NASA's Goddard Space Flight Center generate GRACE-assimilated groundwater and soil moisture drought indicators each week, for drought monitor-related studies and applications. The GRACE-assimilated Drought Indicator Version 2.0 data product (GRACE-DA-DM V2.0) is archived at, and distributed by, the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center). More information about the data and data access is available on the data product landing page at https://disc.gsfc.nasa.gov/datasets /GRACEDADM_CLSM0125US_7D_2.0/summary. The GRACE-DA-DM V2.0 data product contains three drought indicators: Groundwater Percentile, Root Zone Soil Moisture Percentile, and Surface Soil Moisture Percentile. The drought indicators are of wet or dry conditions, expressed as a percentile, indicating the probability of occurrence within the period of record from 1948 to 2012. These GRACE-assimilated drought indicators, with improved spatial and temporal resolutions, should provide a more comprehensive and objective identification of drought conditions. This presentation describes the basic characteristics of the data and data services at NASA GES DISC and collaborative organizations, and uses a few examples to demonstrate the simple ways to explore the GRACE-assimilated drought indicator data.

Assessing water resource system vulnerability to unprecedented hydrological drought using copulas to characterize drought duration and deficit

PubMed Central

Pflug, Georg; Hall, Jim W.; Hochrainer‐Stigler, Stefan

2015-01-01

Abstract Global climate models suggest an increase in evapotranspiration, changing storm tracks, and moisture delivery in many parts of the world, which are likely to cause more prolonged and severe drought, yet the weakness of climate models in modeling persistence of hydroclimatic variables and the uncertainties associated with regional climate projections mean that impact assessments based on climate model output may underestimate the risk of multiyear droughts. In this paper, we propose a vulnerability‐based approach to test water resource system response to drought. We generate a large number of synthetic streamflow series with different drought durations and deficits and use them as input to a water resource system model. Marginal distributions of the streamflow for each month are generated by bootstrapping the historical data, while the joint probability distributions of consecutive months are constructed using a copula‐based method. Droughts with longer durations and larger deficits than the observed record are generated by perturbing the copula parameter and by adopting an importance sampling strategy for low flows. In this way, potential climate‐induced changes in monthly hydrological persistence are factored into the vulnerability analysis. The method is applied to the London water system (England) to investigate under which drought conditions severe water use restrictions would need to be imposed. Results indicate that the water system is vulnerable to drought conditions outside the range of historical events. The vulnerability assessment results were coupled with climate model information to compare alternative water management options with respect to their vulnerability to increasingly long and severe drought. PMID:27609995

Potential evapotranspiration and the likelihood of future drought

NASA Technical Reports Server (NTRS)

Rind, D.; Hansen, J.; Goldberg, R.; Rosenzweig, C.; Ruedy, R.

1990-01-01

The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.

Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions

NASA Astrophysics Data System (ADS)

Rad, Arash Modaresi; Ghahraman, Bijan; Khalili, Davar; Ghahremani, Zahra; Ardakani, Samira Ahmadi

2017-09-01

Conventionally, drought analysis has been limited to single drought category. Utilization of models incorporating multiple drought categories, can relax this limitation. A copula-based model is proposed, which uses meteorological and hydrological drought characteristics to assess drought events for ultimate management of water resources, at small scales, i.e., sub-watersheds. The chosen study area is a sub-basin located at Karkheh watershed (western Iran), with five raingauge stations and one hydrometric station, located upstream and at the outlet, respectively, which represent 41-year of data. Prior to drought analysis, time series of precipitation and streamflow records are investigated for possible dependency/significant trend. Considering semi-arid nature of the study area, boxplots are utilized to graphically capture the rainy months, which are used to evaluate the degree of correlation between streamflow and precipitation records via nonparametric correlations. Time scales of 3- and 12-month are considered, which are used to study vulnerability of early vegetation establishment and long-term ecosystem resilience, respectively. Among four common goodness of fit (GOF) tests, Anderson-Darling is found preferable for defining copula distribution functions through GOF measures, i.e., Akaike and Bayesian information criteria and normalized root mean square error. Furthermore, a GOF method is proposed to evaluate the uncertainty associated with different copula models using the concept of entropy. A new bivariate drought modeling approach is proposed through copulas. The proposed index named standardized precipitation-streamflow index (SPSI) unlike common indices which are used in conjunction with station data, can be applied on a regional basis. SPDI is compared with widely applied streamflow drought index (SDI) and standardized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall-τ and upper tail coefficient relation is investigated for all stations located within the region. According to results, SPSI similar to nonparametric multivariate standardized drought index (NMSDI) was able to detect both onset of droughts dominated by precipitation as is similarly indicated by SPI and persistence of droughts dominated by streamflow as is similarly indicated by SDI. It also captures discordant case of normal period precipitation with dry period streamflow and vice versa. This makes SPSI a powerful tool for estimating a more practical and realistic drought condition. Finally, combination of severity-duration-frequency (SDF) of drought events through copulas resulted in SDF curves that can be used to obtain the recurrence of extreme droughts and assess drought related ecosystem failure or to aid in optimization of water resources allocation. Results indicated that the newly proposed index (SPSI) is able to represent two main characteristics of meteorological and hydrological drought (drought onset and persistency) and also providing an accurate estimation of the recurrence interval of extreme droughts. The procedures can be used to undertake proactive water resource management and planning to assure water security and sustainable agriculture and ecosystem survival for regions experiencing extreme droughts.

Exacerbated degradation and desertification of grassland in Central Asia

NASA Astrophysics Data System (ADS)

Zhang, G.; Xiao, X.; Biradar, C. M.; Dong, J.; Zhou, Y.; Qin, Y.; Zhang, Y.; Liu, F.; Ding, M.; Thomas, R. J.

2016-12-01

Grassland desertification is a complex process, including both state conversion (e.g., grasslands to deserts) and gradual within-state change (e.g., greenness dynamics). Existing studies generally did not separate the two components and analyzed them based on time series vegetation indices, which however cannot provide a clear and comprehensive picture for desertification. Here we proposed a desertification zone classification-based grassland degradation strategy to detect the grassland desertification process in Central Asia. First, annual spatially explicit maps of grasslands and deserts were generated to track the conversion between grasslands and deserts. The results showed that 13 % of grasslands were converted to deserts from 2000 to 2014, with an increasing desertification trend northward in the latitude range of 43-48°N. Second, a fragile and unstable Transitional zone was identified in southern Kazakhstan based on desert frequency maps. Third, gradual vegetation dynamics during the thermal growing season (EVITGS) were investigated using linear regression and Mann-Kendall approaches. The results indicated that grasslands generally experienced widespread degradation in Central Asia, with an additional hotspot identified in the northern Kazakhstan. Finally, attribution analyses of desertification were conducted by correlating vegetation dynamics with three different drought indices (Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), and Drought Severity Index (DSI)), precipitation, and temperature, and showed that grassland desertification was exacerbated by droughts, and persistent drought was the main factor for grassland desertification in Central Asia. This study provided essential information for taking practical actions to prevent the further desertification and targeting right spots for better intervention to combat the land degradation in the region.

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Housborg, Rasmus; Rodell, Matthew

2010-01-01

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Development of a coastal drought index using salinity data

USGS Publications Warehouse

Conrads, Paul; Darby, Lisa S.

2017-01-01

A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.

Evaluation of the Performance of Multiple Drought Indices for Tunisia

NASA Astrophysics Data System (ADS)

Geli, H. M. E.; Jedd, T.; Svoboda, M.; Wardlow, B.; Hayes, M. J.; Neale, C. M. U.; Hain, C.; Anderson, M. C.

2016-12-01

The recent and frequent drought events in the Middle East and Northern Africa (MENA) create an urgent need for scientists, stakeholders, and decision makers to improve the understanding of drought in order to mitigate its effects. It is well documented that drought is not caused by meteorological or hydrological conditions alone; social, economic, and political governance factors play a large part in whether the components in a water supply system are balanced. In the MENA region, for example, agricultural production can place a significant burden on water supply systems. Understanding the connection between drought and agricultural production is an important first step in developing a sound drought monitoring and mitigation system that links physical indicators with on-the-ground impacts. Drought affect crop yield, livestock health, and water resources availability, among others. A clear depiction of drought onset, duration and severity is essential to provide valuable information to adapt and mitigate drought impact. Therefore, it is important that to be able to connect and evaluate scientific drought data and informational products with societal impact data to more effectively initiate mitigation actions. This approach will further the development of drought maps that are tailored and responsive to immediate and specific societal needs for a region or country. Within the context of developing and evaluating drought impacts maps for the MENA region, this analysis investigates the use of different drought indices and indicators including the Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI) anomaly, land surface temperature (LST), and Evaporative Stress Index (ESI) for their ability to characterize historic drought events in Tunisia. Evaluation of a "drought map" product is conducted using data at the county level including crop yield, precipitation, in-country interviews with drought monitoring experts and agricultural producers, and a questionnaire follow-up written survey to evaluate stakeholder perceptions of its effectiveness. This case study results indicate an urgent need to contextualize the meteorological, hydrological, and phenological indicators of drought within the larger socio-political context of the MENA region.

Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time

NASA Astrophysics Data System (ADS)

Van Loon, Anne F.; Kumar, Rohini; Mishra, Vimal

2017-04-01

In 2015, central and eastern Europe were affected by a severe drought. This event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater situation has been performed. One of the reasons is that real-time groundwater level observations often are not available. In this study, we evaluate two alternative approaches to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. The first approach is based on spatially explicit relationships between meteorological conditions and historic groundwater level observations. The second approach uses the Gravity Recovery Climate Experiment (GRACE) terrestrial water storage (TWS) and groundwater anomalies derived from GRACE-TWS and (near-)surface storage simulations by the Global Land Data Assimilation System (GLDAS) models. We combined the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardised Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.25° gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on the estimated optimal accumulation periods and available meteorological time series, we reconstructed the groundwater anomalies up to 2015 and found that in Germany a uniform severe groundwater drought persisted for several months during this year, whereas the Netherlands appeared to have relatively high groundwater levels. The differences between this event and the 2003 European benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany. This is because slowly responding wells (the ones with optimal accumulation periods of more than 12 months) still were above average from the wet year of 2002, which experienced severe flooding in central Europe. GRACE-TWS and GRACE-based groundwater anomalies did not capture the spatial variability of the 2003 and 2015 drought events satisfactorily. GRACE-TWS did show that both 2003 and 2015 were relatively dry, but the differences between Germany and the Netherlands in 2015 and the spatially variable groundwater drought pattern in 2003 were not captured. This could be associated with the coarse spatial scale of GRACE. The simulated groundwater anomalies based on GRACE-TWS deviated considerably from the GRACE-TWS signal and from observed groundwater anomalies. The uncertainty in the GRACE-based groundwater anomalies mainly results from uncertainties in the simulation of soil moisture by the different GLDAS models. The GRACE-based groundwater anomalies are therefore not suitable for use in real-time groundwater drought monitoring in our case study regions. The alternative approach based on the spatially variable relationship between meteorological conditions and groundwater levels is more suitable to quantify groundwater drought in near real-time. Compared to the meteorological drought and streamflow drought (described in previous studies), the groundwater drought of 2015 had a more pronounced spatial variability in its response to meteorological conditions, with some areas primarily influenced by short-term meteorological deficits and others influenced by meteorological deficits accumulated over the preceding 2 years or more. In drought management, this information is very useful and our approach to quantify groundwater drought can be used until real-time groundwater observations become readily available.

Assessment of Drought Severity Techniques - A Historical Perspective

NASA Astrophysics Data System (ADS)

Panu, U. S.; Crinklaw, T.

2011-12-01

Droughts are natural phenomenon experienced by all nations across the globe. Drought inherently means a scarcity of water, which adversely affects various sectors of human socio-economic spectrum, e.g. agriculture, hydropower generation, water supply, industry, recreation, navigation, fish production etc. The prime cause of droughts is the occurrence of less than optimal (below normal) precipitation, which has its origin to various natural reasons, the most important being the global climatic forcing. Droughts are also referred to as sustained and regionally extensive occurrences of below average water availability which invariably cultivate into environmental disasters. The evolution of a drought event is defined into four types; meteorological, agricultural, hydrological, and socio-economic. Drought affects all aspects of societal systems irrespective of how it is defined. This has led to a wide range of studies conducted by meteorologists, ecologists, environmentalists, hydrologists, geologists and agricultural scientists in attempts to understand drought processes as required to analyze and predict the impacts of droughts. A conceptual definition, such as a shortage of water relied on by human activity, avoids quantification of a drought event. On the other hand, the purpose of an operational definition is to determine the beginning, termination, and severity of a drought event. The severity assessment of droughts is of primary importance for allocation and management of available water resources. The progression and impact of historical droughts in a region is helpful for developing relationships and techniques to investigate relevant characteristics of droughts. For optimum drought preparedness and mitigative responses, professional bodies need to provide information to private and government agencies in a manner that may also be understood by their employers, stakeholders and the general public. Drought indicators bridge this communication gap between all parties by the quantification of an extensive amount of meteorological and/or hydrological information in a simple and understandable manner. Each type of drought; meteorological, agricultural, hydrological, and socio-economic has developed numerous drought indicators to deal with a variety of situations pertaining to the degree of drought severity. There exist over 80 drought indictors to effectively signify the degree of severity of a particular type of drought. The focus of this paper is to reassess the effectiveness of these drought indicators and to identify the most effective indicators in each type of drought. First, the paper discusses the key features of the drought indictors with a deconstruction of their vital components to enhance their understanding and applicability. Second, the paper identifies the caveats and limitations of each indicator in an effort for an effective analysis of droughts. This paper allows for enhanced certainty in the use of existing drought indictors and thus leads to optimized drought analysis, drought characterization and drought prediction. The paper also highlights potential opportunities for improvement within selected drought indicators.

Variation in drought resistance, drought acclimation and water conservation in four willow cultivars used for biomass production.

PubMed

Wikberg, Jenny; Ogren, Erling

2007-09-01

Growth and water-use parameters of four willow (Salix spp.) clones grown in a moderate drought regime or with ample water supply were determined to characterize their water-use efficiency, drought resistance and capacity for drought acclimation. At the end of the 10-week, outdoor pot experiment, clonal differences were observed in: (1) water-use efficiency of aboveground biomass production (WUE); (2) resistance to xylem cavitation; and (3) stomatal conductance to leaf-specific, whole-plant hydraulic conductance ratio (g(st)/K(P); an indicator of water balance). Across clones and regimes, WUE was positively correlated with the assimilation rate to stomatal conductance ratio (A/g(st)), a measure of instantaneous water-use efficiency. Both of these water-use efficiency indicators were generally higher in drought-treated trees compared with well-watered trees. However, the between-treatment differences in (shoot-based) WUE were smaller than expected, considering the differences in A/g(st) for two of the clones, possibly because plants reallocated dry mass from shoots to roots when subject to drought. Higher root hydraulic conductance to shoot hydraulic conductance ratios (K(R)/K(S)) during drought supports this hypothesis. The same clones were also the most sensitive to xylem cavitation and, accordingly, showed the strongest reduction in g(st)/K(P) in response to drought. Drought acclimation was manifested in decreased g(st), g(st)/K(P), osmotic potential and leaf area to vessel internal cross-sectional area ratio, and increased K(R), K(P) and WUE. Increased resistance to stem xylem cavitation in response to drought was observed in only one clone. It is concluded that WUE and drought resistance traits are inter-linked and that both may be enhanced by selection and breeding.

An Evaluation of Drought Indices in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Shahabfar, A.; Eitzinger, J.

2009-04-01

Drought has become a recurrent phenomenon in Iran in the last few decades. Significant drought conditions were observed during years of late 2000s and the trend continued up to now. The country's agricultural sector and water resources have been under severe constraints from the recurrent droughts. In this study, spatial and temporal dimensions of meteorological droughts in Iran have been investigated from vulnerability concept. The Standardized Precipitation Index (SPI) was developed to detect drought and wet periods at different time scales, an important characteristic that is not accomplished with typical drought indices. More and more users employ the SPI to monitor droughts. Although calculation of the SPI is easier than other drought indices, such as the Palmer Drought Index, it is still relatively complex. Two indices called the China-Z Index (CZI) and Modified China-Z Index (CZI) have been used by many scientists to monitor moisture conditions across their country or their case study area. The calculations of these indices are easier than the SPI. Another indices, the statistical Z-Score and percent of normal (PN), can also be used to monitor droughts. This paper evaluates the SPI, CZI, MCZI, Z-Score and PN on 1-, 3-, 6-, 9- and 12-month time scales using monthly precipitation totals for six climatic regions in Iran from January 2000 to December 2005 as a sever dry period and representing six climatic regions include: mountain, semi mountain, desert, semi-desert, coastal desert and coastal wet. Advantages and disadvantages for the application of each index are compared. Study results indicate that the CZI, MCZI, Z-Score and PN can provide results similar to the SPI for all time scales, and that the calculations of these indices are relatively easy compared with the SPI, possibly offering better tools to monitor moisture conditions. KEY WORDS: drought monitoring, drought indices, soil moisture, climatic regions.

Proteomic analysis of Camellia sinensis (L.) reveals a synergistic network in the response to drought stress and recovery.

PubMed

Wang, Yu; Fan, Kai; Wang, Jing; Ding, Zhao-Tang; Wang, Hui; Bi, Cai-Hong; Zhang, Yun-Wei; Sun, Hai-Wei

2017-12-01

Drought is a crucial limiting factor for tea yield and quality. To systematically characterize the molecular response of tea plants to drought stress and its capacity to recover, we used iTRAQ-based comparative proteomic approach to investigate the effects of drought on protein expression profiles in tea seedlings subjected to different drought treatments. A total of 3274 proteins were identified, of which 2169 and 2300 showed differential expressions during drought and recovery, respectively. Functional annotation showed that multiple biological processes were regulated, suggesting that tea plants probably employed multiple and synergistic resistance mechanisms in dealing with drought stress. Hierarchical clustering showed that chlorophyll a/b-binding proteins were up-regulated in DB and RE, suggesting that tea plants might regulate expression of chlorophyll a/b-binding proteins to maintain the photosystem II function during drought stress. Abundant proteins involved in sulfur-containing metabolite pathways, such as glutathione, taurine, hypotaurine, methionine, and cysteine, changed significantly during drought stress. Among them, TL29 interacted with LHCb6 to connect S-containing metabolites with chlorophyll a/b-binding proteins. This suggests that sulfur-containing compounds play important roles in the response to drought stress in tea plants. In addition, the expression of PAL was up-regulated in DA and down-regulated in DB. Cinnamyl alcohol dehydrogenase, caffeic acid O-methyltransferase, and 4-coumarate-CoA ligase also showed significant changes in expression levels, which regulated the biosynthesis of polyphenols. The results indicate that slight drought stress might promote polyphenol biosynthesis, while serious drought stress leads to inhibition. The expression of lipoxygenase and short-chain dehydrogenase increased during slight drought stress and some volatile metabolite pathways were enriched, indicating that drought stress might affect the tea aroma. The study provides valuable information that will lay the foundation for studies investigating the functions of drought response genes in tea leaves. Copyright © 2017 Elsevier GmbH. All rights reserved.

Gene regulation network behind drought escape, avoidance and tolerance strategies in black poplar (Populus nigra L.).

PubMed

Yıldırım, Kubilay; Kaya, Zeki

2017-06-01

Drought is the major environmental problem limiting the productivity and survival of plant species. Here, previously identified three black poplar genotypes having contrasting response to drought were subjected to gradual soil water depletion in a pot trial to identify their physiological, morphological and antioxidation related adaptations. We also performed a microarray based transcriptome analyses on the leaves of genotypes by using Affymetrix poplar Genome Array containing 56,000 transcripts. Phenotypic analyses of each genotype confirmed their differential adaptations to drought that could be classified as drought escape, avoidance and tolerance. Comparative transcriptomic analysis indicated highly divergent gene expression patterns among the genotypes in response to drought and post drought re-watering (PDR). We identified 10641, 3824 and 9411 transcripts exclusively regulated in drought escape, avoidance and tolerant genotypes, respectively. The key genes involved in metabolic pathways, such as carbohydrate metabolism, photosynthesis, lipid metabolism, generation of precursor metabolites/energy, protein folding, redox homeostasis, secondary metabolic process and cell wall component biogenesis, were affected by drought stresses in the leaves of these genotypes. Transcript isoforms showed increased expression specificity in the genes coding for bark storage proteins and small heat shock proteins in drought tolerant genotype. On the other hand, drought-avoiding genotype specifically induced the transcripts annotated to the genes functional in secondary metabolite production that linked to enhanced leaf water content and growth performance under drought stress. Transcriptome profiling of drought escape genotype indicated specific regulation of the genes functional in programmed cell death and leaf senescence. Specific upregulation of GTP cyclohydrolase II and transcription factors (WRKY and ERFs) in only this genotype were associated to ROS dependent signalling pathways and gene regulation network responsible in induction of many degrading enzymes acting on cell wall carbohydrates, fatty acids and proteins under drought stress. Our findings provide new insights into the transcriptome dynamics and components of regulatory network associated with drought adaptation strategies. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey

NASA Astrophysics Data System (ADS)

Dogan, Selim; Berktay, Ali; Singh, Vijay P.

2012-11-01

SummaryMany drought indices (DIs) have been introduced to monitor drought conditions. This study compares Percent of Normal (PN), Rainfall Decile based Drought Index (RDDI), statistical Z-Score, China-Z Index (CZI), Standardized Precipitation Index (SPI), and Effective Drought Index (EDI) to identify droughts in a semi-arid closed basin (Konya), Turkey. Comparison studies of DIs under different climatic conditions is always interesting and may be insightful. Employing and comparing 18 different timesteps, the objective of comparison is twofold: (1) to determine the effect of timestep for choosing an appropriate value, and (2) to determine the sensitivity of DI to timestep and the choice of a DI. Monthly rainfall data obtained from twelve spatially distributed stations was used to compare DIs for timesteps ranging from 1 month to 48 months. These DIs were evaluated through correlations for various timesteps. Surprisingly, in many earlier studies, only 1-month time step has been used. Results showed that the employment of median timesteps was essential for future studies, since 1-month timestep DIs were found as irrelevant to those for other timesteps in arid/semi-arid regions because seasonal rainfall deficiencies are common there. Comparing time series of various DI values (numerical values of drought severity) instead of drought classes was advantageous for drought monitoring. EDI was found to be best correlated with other DIs when considering all timesteps. Therefore, drought classes discerned by DIs were compared with EDI. PN and RDDI provided different results than did others. PN detected a decrease in drought percentage for increasing timestep, while RDDI overestimated droughts for all timesteps. SPI and CZI were more consistent in detecting droughts for different timesteps. The response of DI and timestep combination to the change of monthly and multi-monthly rainfall for a qualitative comparison of severities (drought classes) was investigated. Analyzing the 1973-1974 dry spell at Beysehir station, EDI was found sensitive to monthly rainfall changes with respect to cumulative rainfall changes, especially more sensitive than other DIs for shorter timesteps. Overall, EDI was consistent with DIs for various timesteps and was preferable for monitoring long-term droughts in arid/semi-arid regions. The use of various DIs for timesteps of 6, 9, and 12 months is essential for long term drought studies. 1-month DIs should not be used solely in comparison studies to present a DI, unless there is a specific reason. This investigation showed that the use of an appropriate timestep is as important as the type of DI used to identify drought severities.

A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains

USGS Publications Warehouse

Tadesse, Tsegaye; Brown, Jesslyn F.; Hayes, M.J.

2005-01-01

Droughts are normal climate episodes, yet they are among the most expensive natural disasters in the world. Knowledge about the timing, severity, and pattern of droughts on the landscape can be incorporated into effective planning and decision-making. In this study, we present a data mining approach to modeling vegetation stress due to drought and mapping its spatial extent during the growing season. Rule-based regression tree models were generated that identify relationships between satellite-derived vegetation conditions, climatic drought indices, and biophysical data, including land-cover type, available soil water capacity, percent of irrigated farm land, and ecological type. The data mining method builds numerical rule-based models that find relationships among the input variables. Because the models can be applied iteratively with input data from previous time periods, the method enables to provide predictions of vegetation conditions farther into the growing season based on earlier conditions. Visualizing the model outputs as mapped information (called VegPredict) provides a means to evaluate the model. We present prototype maps for the 2002 drought year for Nebraska and South Dakota and discuss potential uses for these maps.

Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

PubMed Central

Gehan, Malia A; Mockler, Todd C; Weinig, Cynthia; Ewers, Brent E

2017-01-01

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought. PMID:28826479

Livestock mortality in pastoralist herds in Ethiopia and implications for drought response.

PubMed

Catley, Andy; Admassu, Berhanu; Bekele, Gezu; Abebe, Dawit

2014-07-01

Participatory epidemiology methods were employed retrospectively in three pastoralist regions of Ethiopia to estimate the specific causes of excess livestock mortality during drought. The results showed that starvation/dehydration accounted for between 61.5 and 100 per cent of excess livestock mortality during drought, whereas disease-related mortality accounted for between 0 and 28.1 per cent of excess mortality. Field observations indicate that, in livestock, disease risks and mortality increase in the immediate post-drought period, during rain. The design of livelihoods-based drought response programmes should include protection of core livestock assets, and it should take account of the specific causes of excess livestock mortality during drought and immediately afterwards. This study shows that, when comparing livestock feed supplementation and veterinary support, relatively more aid should be directed at the former if the objective is to protect core livestock during drought. Veterinary support should consider disease-related mortality in the immediate post-drought period, and tailor inputs accordingly. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

AVHRR-based drought-observing system for monitoring the environment and socioeconomic activities

NASA Astrophysics Data System (ADS)

Kogan, F.

From all natural disaster, drought is the least understandable and the most damaging environmental phenomenon. Although in pre-satellite era, climate data were used for drought monitoring, drought specifics created problems in early drought detection start/end, monitoring its expansion/contraction, intensity and area coverage and the most important, timely estimation of the impacts on the environment and socioeconomic activities. The latest prevented to take prompt measures in mitigating negative consequences of drought for the society. Advances in remote sensing of the past ten years, contributed to the development of comprehensive drought monitoring system and numerous applications, which helped to make decisions for monitoring the environment and predicting sustainable socioeconomic activities. This paper discusses satellite-based land-surface observing system, which provides wells of information used for monitoring such unusual natural disaster as drought. This system was developed from the observations of the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA operational polar-orbiting satellites. The AVHRR data were packed into the Global Vegetation Index (GVI) product, which have served the global community since 1981. The GVI provided reflectances and indices (4 km spacial resolution) every seven days for each 16 km map cell between 75EN and 55ES covering all land ecosystems. The data includes raw and calibrated radiances in the visible, near infrared and infrared spectral bands, processed (with eliminated high frequency noise) radiances, normalized difference vegetation index (NDVI), 20-year climatology, vegetation condition indices and also products, such as vegetation health, drought, vegetation fraction, fire risk etc. In the past ten years, users around the world used this information addressing different issues of drought impacts on socioeconomic activities and responded positively to real time drought information place regularly on the following web site http://orbit-net.nesdis.noaa.gov/crad/sat/surf/vci/. Drought assessments were compared with ground observations in twenty two countries around the world and showed good results in early drought detection and monitoring its development and impacts on the environment and socioeconomic activities, for assessment of biomass/crop production losses and fire risk. In addition, the AVHRR-based products showed potential in monitoring mosquito-born epidemics, amount of water required for irrigation, and predicting ENSO impacts on productivity of land ecosystems. These applications were used in agriculture, forestry, weather models, climatology. This presentation will be illustrated with many examples of data applications and also with explanations of data structure and use.

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre

2014-05-01

Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as the water shortage can be sensed several weeks before the vegetation dryness occures. Keywords: SMOS, microwave, level 4, soil moisture, drought, precipitation, hydrological model, vegetation index

Climate- and remote sensing-based tools for drought management application in North and South Korea

NASA Astrophysics Data System (ADS)

Nam, W.; Wardlow, B.; Hayes, M. J.; Tadesse, T.; Svoboda, M.; Fuchs, B.; Wilhite, D. A.

2015-12-01

North and South Korea have experienced more frequent and extreme droughts since the late 1990s. In recent years, severe droughts in 2000-2001, 2012, and 2015 have led to widespread agricultural and environmental impacts, and resulted in water shortages and large reductions in crop yields. This has been particularly problematic in the agricultural sector of North Korea, which has a high-level of vulnerability due to variations of climate and this, in turn, results in food security issues. This vulnerability is exacerbated by North Korea's relatively small area of arable land, most of which is not very productive. The objective of this study was to develop a drought management application using climate- and remote sensing-based tools for North and South Korea. These tools are essential for improving drought planning and preparedness in this area. In this study, various drought indicators derived from climate and remote sensing data (SPI, SC-PDSI, SPEI, and VegDRI-Korea) were investigated to monitor the current drought condition and evaluate their ability to characterize agricultural and meteorological drought events and their potential impacts. Results from this study can be used to develop or improve the national-level drought management application for these countries. The goal is to provide improved and more timely information on both the spatial and temporal dimensions of drought conditions and provide a tool to identify both past and present drought events in order to make more informed management decisions and reduce the impacts of current droughts and reduce the risk to future events.

Flow variations and macroinvertebrate community responses in a small groundwater-dominated stream in south east England

USGS Publications Warehouse

Bendix, J.; Hupp, C.R.

2000-01-01

Changes in the macroinvertebrate community in response to flow variations in the Little Stour River, Kent, UK, were examined over a 6 year period (1992-1997). This period included the final year of the 1988-1992 drought, followed by some of the wettest conditions recorded this century and a second period of drought between 1996 and 1997. Each year, samples were collected from 15 sites during late-summer base-flow conditions. Correspondence analysis identified clear differences between samples from upstream and downstream sites, and between drought and non-drought years. Step-wise multiple regression was used to identify hydrological indicators of community variation. Several different indices were used to describe the macroinvertebrate community, including macroinvertebrate community abundance, number of families and species, and individual species. Site characteristics were fundamental in accounting for variation in the unstandardized macroinvertebrate community. However, when differences between sites were controlled, hydrological conditions were found to play a dominant role in explaining ecological variation. Indices of high discharge (or their absence), 4-7 months prior to sampling (i.e. winter-spring), were found to be the most important variables for describing the late-summer community The results are discussed in relation to the role of flow variability in shaping instream communities and management implications. Copyright ?? 2000 John Wiley & Sons, Ltd.Changes in the macroinvertebrate community in response to flow variations in the Little Stour River, Kent, UK, were examined over a 6 year period (1992-1997). This period included the final year of the 1988-1992 drought, followed by some of the wettest conditions recorded this century and a second period of drought between 1996 and 1997. Each year, samples were collected from 15 sites during late-summer base-flow conditions. Correspondence analysis identified clear differences between samples from upstream and downstream sites, and between drought and non-drought years. Step-wise multiple regression was used to identify hydrological indicators of community variation. Several different indices were used to describe the macroinvertebrate community, including macroinvertebrate community abundance, number of families and species, and individual species. Site characteristics were fundamental in accounting for variation in the unstandardized macroinvertebrate community. However, when differences between sites were controlled, hydrological conditions were found to play a dominant role in explaining ecological variation. Indices of high discharge (or their absence), 4-7 months prior to sampling (i.e. winter-spring), were found to be the most important variables for describing the late-summer community. The results are discussed in relation to the role of flow variability in shaping instream communities and management implications.

Global drought watch from space at work: Crop losses and food security

NASA Astrophysics Data System (ADS)

Kogan, F.

2012-12-01

Drought is one of the most adverse environmental disasters. It affects countries economies, environment a very large number of people in the world. Only in the USA drought costs taxpayers nearly $6 billion each year. Drought is a very unusual phenomenon because unlike other environmental disaster it starts unnoticeably, develop cumulatively, the impact is also cumulative and by the time when the effect of drought is observable it is too late to mitigate the consequences. Therefore, it is difficult to mitigate droughts using in situ data. The National Oceanic and Atmospheric Administration (NOAA) developed new method for drought detection and monitoring from reflectance measured by the Advanced Very High Resolution Radiometer flown on NOAA polar-orbiting operational environmental satellites. The method calculates Vegetation Health (VH) indices, which estimate vegetation condition (health) on a scale from extreme stress to favorable conditions based on intensity of greenness, vigor and thermal condition of vegetation canopy. The VH is estimated every week for each 4 by 4 km earth surface and is delivered to the NOAA/NESDIS web site in digital and color-coded form. The web site address is the following http://www.star.nesdis.noaa.gov/smcd/emb/vci/VH/index.php In addition to drought and vegetation health monitoring, the VH indices are applied in agriculture, forestry, mosquito-borne diseases, climate, invasive species and others. During the first seven months of 2009, drought was observed in the southern US (especially Texas), Argentina (very intensive drought), some of the countries of sub-Sahara Africa, India (central and eastern), Kazakhstan and Australia.

Spatiotemporal Drought Analysis and Drought Indices Comparison in India

NASA Astrophysics Data System (ADS)

Janardhanan, A.

2017-12-01

Droughts and floods are an ever-occurring phenomenon that has been wreaking havoc on humans since the start of time. As droughts are on a very large scale, studying them within a regional context can minimize confounding factors such as climate change. Droughts and floods are extremely erratic and very difficult to predict and therefore necessitate modeling through advanced statistics. The SPI (Standard Precipitation Index) and the SPEI (Standard Precipitation Evapotranspiration Index) are two ways to temporally model drought and flood patterns across each metrological sub basin in India over a variety of different time scales. SPI only accounts for precipitation values, while the SPEI accounts for both precipitation and temperature and is commonly regarded as a more reliable drought index. Using monthly rainfall and temperature data from 1871-2016, these two indices were calculated. The results depict the drought and flood severity index, length of drought, and average SPI or SPEI value for each meteorological sub region in India. A Wilcox Ranksum test was then conducted to determine whether these two indices differed over the long term for drought analysis. The drought return periods were analyzed to determine if the population mean differed between the SPI and SPEI values. Our analysis found no statistical difference between SPI and SPEI with regards to long-term drought analysis. This indicates that temperature is not needed when modeling drought on a long-term time scale and that SPI is just as effective as SPEI, which has the potential to save a lot of time and resources on calculating drought indices.

Drought forecasting in Luanhe River basin involving climatic indices

NASA Astrophysics Data System (ADS)

Ren, Weinan; Wang, Yixuan; Li, Jianzhu; Feng, Ping; Smith, Ronald J.

2017-11-01

Drought is regarded as one of the most severe natural disasters globally. This is especially the case in Tianjin City, Northern China, where drought can affect economic development and people's livelihoods. Drought forecasting, the basis of drought management, is an important mitigation strategy. In this paper, we evolve a probabilistic forecasting model, which forecasts transition probabilities from a current Standardized Precipitation Index (SPI) value to a future SPI class, based on conditional distribution of multivariate normal distribution to involve two large-scale climatic indices at the same time, and apply the forecasting model to 26 rain gauges in the Luanhe River basin in North China. The establishment of the model and the derivation of the SPI are based on the hypothesis of aggregated monthly precipitation that is normally distributed. Pearson correlation and Shapiro-Wilk normality tests are used to select appropriate SPI time scale and large-scale climatic indices. Findings indicated that longer-term aggregated monthly precipitation, in general, was more likely to be considered normally distributed and forecasting models should be applied to each gauge, respectively, rather than to the whole basin. Taking Liying Gauge as an example, we illustrate the impact of the SPI time scale and lead time on transition probabilities. Then, the controlled climatic indices of every gauge are selected by Pearson correlation test and the multivariate normality of SPI, corresponding climatic indices for current month and SPI 1, 2, and 3 months later are demonstrated using Shapiro-Wilk normality test. Subsequently, we illustrate the impact of large-scale oceanic-atmospheric circulation patterns on transition probabilities. Finally, we use a score method to evaluate and compare the performance of the three forecasting models and compare them with two traditional models which forecast transition probabilities from a current to a future SPI class. The results show that the three proposed models outperform the two traditional models and involving large-scale climatic indices can improve the forecasting accuracy.

Drought monitoring over the Horn of Africa using remotely sensed evapotranspiration, soil moisture and vegetation parameters

NASA Astrophysics Data System (ADS)

Timmermans, J.; Gokmen, M.; Eden, U.; Abou Ali, M.; Vekerdy, Z.; Su, Z.

2012-04-01

The need to good drought monitoring and management for the Horn of Africa has never been greater. This ongoing drought is the largest in the past sixty years and is effecting the life of around 10 million people, according to the United Nations. The impact of drought is most apparent in food security and health. In addition secondary problems arise related to the drought such as large migration; more than 15000 Somalia have fled to neighboring countries to escape the problems caused by the drought. These problems will only grow in the future to larger areas due to increase in extreme weather patterns due to global climate change. Monitoring drought impact and managing the drought effects are therefore of critical importance. The impact of a drought is hard to characterize as drought depends on several parameters, like precipitation, land use, irrigation. Consequently the effects of the drought vary spatially and range from short-term to long-term. For this reason a drought event can be characterized into four categories: meteorological, agricultural, hydrological and socio-economical. In terms of food production the agricultural drought, or short term dryness near the surface layer, is most important. This drought is usually characterized by low soil moisture content in the root zone, decreased evapotranspiration, and changes in vegetation vigor. All of these parameters can be detected with good accuracy from space. The advantage of remote sensing in Drought monitoring is evident. Drought monitoring is usually performed using drought indices, like the Palmer Index (PDSI), Crop Moisture Index (CMI), Standard Precipitation Index (SPI). With the introduction of remote sensing several indices of these have shown great potential for large scale application. These indices however all incorporate precipitation as the main surface parameter neglecting the response of the surface to the dryness. More recently two agricultural drought indices, the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI), have been proposed to investigate this. The ETDI considers the stress ratio caused by the difference between potential and actual evapotranspiration, while SMDI considers the variation in soil moisture availability to the plant. As there is not a single unique accepted definition of drought, investigation into the impact of drought should not be confined to a single drought index; instead several indices need to be used for this purpose. The objective of this research is to investigate the drought in the Horn of Africa using several remote sensing drought indices and vegetation parameters. In this research the drought will be investigated using SPI, ETDI, SMDI, NDVI and SPI. For this purpose ETDI and SMDI will be estimated from remote sensing products for the period from 2002 till 2011that are created in framework of the WACMOS project. The research involves the comparison of the different drought indices and the research into possible synergies to enhance drought monitoring.

Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010.

PubMed

Qian, Xiaojin; Liang, Liang; Shen, Qiu; Sun, Qin; Zhang, Lianpeng; Liu, Zhixiao; Zhao, Shuhe; Qin, Zhihao

2016-11-01

Drought is a type of natural disaster that has the most significant impacts on agriculture. Regional drought monitoring based on remote sensing has become popular due to the development of remote sensing technology. In this study, vegetation condition index (VCI) data recorded from 1982 to 2010 in agricultural areas of China were obtained from advanced very high resolution radiometer (AVHRR) data, and the temporal and spatial variations in each drought were analyzed. The relationships between drought and climate factors were also analyzed. The results showed that from 1982 to 2010, the agricultural areas that experienced frequent and severe droughts were mainly concentrated in the northwestern areas and Huang-Huai Plain. Moreover, the VCI increased in the majority of agricultural areas, indicating that the drought frequency decreased over time, and the decreasing trend in the southern region was more notable than that in the northern region. A correlation analysis showed that temperature and wind velocity were the main factors that influenced drought in the agricultural areas of China. From a regional perspective, excluding precipitation, the climate factors had various effects on drought in different regions. However, the correlation between the VCI and precipitation was low, possibly due to the widespread use of artificial irrigation technology, which reduces the reliance of agricultural areas on precipitation.

[Effects of drought stress on growth and water use efficiency of two medicinal plants].

PubMed

Chen, Ping; Meng, Ping; Zhang, Jin-Song; He, Chun-Xia; Jia, Chang-Rong; Li, Jian-Zhong

2014-05-01

Growth characteristics, stable carbon isotope discrimination (Delta13C), water use efficiency (WUE), and their correlation of Cassia obtusifolia and Isatis indigotica were measured at three soil water levels, i. e., 30%, 50% and 75% of field water holding capacity (FWHC), and at three growth stages. The growth indices of the two medicinal plants at 75% of FWHC were higher than those at 30% and 50% of FWHC, suggesting that the two medicinal plants could obtain high production under sufficient moisture condition. The Delta13C(A) (aboveground biomass-based Delta13C) and Delta13C(T) (total biomass-based Delta13C) decreased, and the WUE(A) (aboveground biomass-based WUE) and WUE(T) (total biomass-based WUE) of C. obtusifolia and I. indigotica increased with the increasing degree of drought stress. The growth indices of the two medicinal plants had little difference in the different water treatments, which indicated that the two medicinal plants were insensitive to drought stress. Water use efficiency of I. indigotica had significant negative relationships with aboveground biomass and total biomass, while that of C. obtusifolia had a significant positive correlation with the root/shoot ratio.

Contribution of Temperature to Chilean Droughts Using Ensemble Climate Projections

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, M.; Alfieri, L.; Naumann, G.; Garreaud, R. D.

2017-12-01

Precipitation deficit is traditionally considered as the main driver of drought events, however the evolution of drought conditions is also influenced by other variables such as temperature, wind speed and evapotranspiration. In view of global warming, the effect of rising temperatures may lead to increased socio-economic drought impacts, particularly in vulnerable developing countries. In this work, we used two drought indices to analyze the impacts of precipitation and temperature on the frequency, severity and duration of Chilean droughts (25°S-56°S) during the XXI century, using multi-model climate projections consistent with the high-end RCP 8.5 scenario. An ensemble of seven global CMIP5 simulations were used to drive the Earth System Model EC-EARTH3-HR v3.1 over the 1976-2100 period, in order to increase the spatial resolution from the original grid to 0.35°. The Standardized Precipitation Index (SPI) was used to describe the impact of precipitation on drought conditions, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the effect of temperature -throughout changes in potential evapotranspiration- on drought characteristics at different time scales. Drought indices along with duration, severity and frequency of drought events were computed for a 30-year baseline period (1976-2005) and then compared to three 30-year periods representing short, medium and long-term scenarios (2011-2040, 2041-2070 and 2071-2100). Indices obtained from climate simulations during the baseline period were compared against the corresponding values derived from ground observations. Results obtained with SPI-12 reveal a progressive decrease in precipitation in Chile, which is consistent through all climate models, though each of them shows a different spatial pattern. Simulations based on SPEI-12 show that the expected increase in evaporative demand (driven by the temperature increase) for the region is likely to exacerbate the severity and duration of drought events. Findings of this work are an important support for timely preparation of drought adaptation and mitigation plans to improve water management strategies and resilience during the XXI century.

Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China

NASA Astrophysics Data System (ADS)

Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song

2017-06-01

Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.

Human influences on streamflow drought characteristics in England and Wales

NASA Astrophysics Data System (ADS)

Tijdeman, Erik; Hannaford, Jamie; Stahl, Kerstin

2018-02-01

Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff) of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1) the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils), (2) the correlation between streamflow and precipitation and (3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for some of the catchments affected by groundwater abstractions and a decrease in streamflow drought occurrence for some of the catchments with either reservoirs or groundwater abstractions. In conclusion, the proposed screening approaches were sometimes successful in identifying streamflow records with deviating drought characteristics that are likely related to different human influences. However, a quantitative attribution of the impact of human influences on streamflow drought characteristics requires more detailed case-by-case information about the type and degree of all different human influences. Given that, in many countries, such information is often not readily accessible, the approaches adopted here could provide useful in targeting future efforts. In England and Wales specifically, the catchments with deviating streamflow drought characteristics identified in this study could serve as the starting point of detailed case study research.

Implementing drought early warning systems: policy lessons and future needs

NASA Astrophysics Data System (ADS)

Iglesias, Ana; Werner, Micha; Maia, Rodrigo; Garrote, Luis; Nyabeze, Washington

2014-05-01

Drought forecasting and Warning provides the potential of reducing impacts to society due to drought events. The implementation of effective drought forecasting and warning, however, requires not only science to support reliable forecasting, but also adequate policy and societal response. Here we propose a protocol to develop drought forecasting and early warning based in the international cooperation of African and European institutions in the DEWFORA project (EC, 7th Framework Programme). The protocol includes four major phases that address the scientific knowledge and the social capacity to use the knowledge: (a) What is the science available? Evaluating how signs of impending drought can be detected and predicted, defining risk levels, and analysing of the signs of drought in an integrated vulnerability approach. (b) What are the societal capacities? In this the institutional framework that enables policy development is evaluated. The protocol gathers information on vulnerability and pending hazard in advance so that early warnings can be declared at sufficient lead time and drought mitigation planning can be implemented at an early stage. (c) How can science be translated into policy? Linking science indicators into the actions/interventions that society needs to implement, and evaluating how policy is implemented. Key limitations to planning for drought are the social capacities to implement early warning systems. Vulnerability assessment contributes to identify these limitations and therefore provides crucial information to policy development. Based on the assessment of vulnerability we suggest thresholds for management actions to respond to drought forecasts and link predictive indicators to relevant potential mitigation strategies. Vulnerability assessment is crucial to identify relief, coping and management responses that contribute to a more resilient society. (d) How can society benefit from the forecast? Evaluating how information is provided to potentially affected groups, and how mitigation strategies can be taken in response. This paper presents an outline of the protocol that was developed in the DEWFORA project, outlining the complementary roles of science, policy and societal uptake in effective drought forecasting and warning. A consensus on the need to emphasise the social component of early warning was reached when testing the DEWFORA early warning system protocol among experts from 18 countries.

Tree-ring-width-based PDSI reconstruction for central Inner Mongolia, China over the past 333 years

NASA Astrophysics Data System (ADS)

Liu, Yu; Zhang, Xinjia; Song, Huiming; Cai, Qiufang; Li, Qiang; Zhao, Boyang; Liu, Han; Mei, Ruochen

2017-02-01

A tree-ring-width chronology was developed from Pinus tabulaeformis aged up to 333 years from central Inner Mongolia, China. The chronology was significantly correlated with the local Palmer Drought Severity Index (PDSI). We therefore reconstructed the first PDSI reconstruction from March to June based on the local tree ring data from 1680 to 2012 AD. The reconstruction explained 40.7 % of the variance (39.7 % after adjusted the degrees of freedom) of the actual PDSI during the calibration period (1951-2012 AD). The reconstructed PDSI series captured the severe drought event of the late 1920s, which occurred extensively in northern China. Running variance analyses indicated that the variability of drought increased sharply after 1960, indicating more drought years, which may imply anthropogenic related global warming effects in the region. In the entire reconstruction, there were five dry periods: 1730-1814 AD, 1849-1869 AD, 1886-1942 AD (including severe drought in late 1920s), 1963-1978 AD and 2004-2007 AD; and five wet periods: 1685-1729 AD, 1815-1848 AD, 1870-1885 AD, 1943-1962 AD and 1979-2003 AD. Conditions turned dry after 2003 AD, and the PDSI from March to June (PDSI36) captured many interannual extreme drought events since then, such as 2005-2008 AD. The reconstruction is comparable to other tree-ring-width-based PDSI series from the neighboring regions, indicating that our reconstruction has good regional representativeness. Significant relationships were found between our PDSI reconstruction and the solar radiation cycle and the sun spot cycle, North Atlantic Oscillation, the El Niño-Southern Oscillation, as well as the Pacific Decadal Oscillation. Power spectral analyses detected 147.0-, 128.2-, 46.5-, 6.5-, 6.3-, 2.6-, 2.2- and 2.0-year quasi-cycles in the reconstructed series.

Drought Risk Assessment based on Natural and Social Factors

NASA Astrophysics Data System (ADS)

Huang, Jing; Wang, Huimin; Han, Dawei

2015-04-01

In many parts of the world, drought hazard is becoming more frequent and severe due to climate change and human activities. It is crucial to monitor and assess drought conditions, especially for decision making support in agriculture sector. The vegetation index (VI) decreases, and the land surface temperature (LST) increases when the vegetation is under drought stress. Therefore both of these remotely sensed indices are widely used in drought monitoring and assessment. Temperature-Vegetation Dryness Index (TVDI) is obtained by establishing the feature space of the normalized difference vegetation index (NDVI) and LST, which reflects agriculture dry situation by inverting soil moisture. However, these indices only concern the natural hazard-causing factors. Our society is a complex large-scale system with various natural and social elements. The drought risk is the joint consequence of hazard-causing factors and hazard-affected bodies. For example, as the population increases, the exposure of the hazard-affected bodies also tends to increase. The high GDP enhances the response ability of government, and the irrigation and water conservancy reduces the vulnerability. Such characteristics of hazard-affected bodies should be coupled with natural factors. In this study, the 16-day moderate-resolution imaging spectroradiometer (MODIS) NDVI and LST data are combined to establish NDVI-Ts space according to different land use types in Yunnan Province, China. And then, TVDIs are calculated through dry and wet edges modeled as a linear fit to data for each land cover type. Next, the efforts are turned to establish an integrated drought assessment index of social factors and TVDI through ascertaining attribute weight based on rough sets theory. Thus, the new CDI (comprehensive drought index) recorded during spring of 2010 and the spatial variations in drought are analyzed and compared with TVDI dataset. Moreover, actual drought risk situation in the study area is given to verify the effectiveness of the CDI. In addition, GIS is applied to provide geographically referenced information, i.e. information involving location, elevation, land use, water resources distance and so on, which are essential inputs for spatial analysis in drought risk assessment. On the whole, this study has proposed a new idea on drought risk assessment integrating natural factors with social factors, as well as providing a real-time drought monitoring method in a social context.

Assessing spatiotemporal variation of drought and its impact on maize yield in Northeast China

NASA Astrophysics Data System (ADS)

Guo, Enliang; Liu, Xingpeng; Zhang, Jiquan; Wang, Yongfang; Wang, Cailin; Wang, Rui; Li, Danjun

2017-10-01

In the context of global climate change, drought has become an important factor that affects the maize yield in China. To analyse the impact of drought on maize yield loss in Northeast China in current and future climate scenarios, the Composite Meteorological Drought Index (CI) is introduced to reconstruct the following drought indicators: drought accumulative days (DAD), drought accumulative intensity (DAI), and consecutive drought days (CDD). These three drought indicators are used to describe the three-dimensional characteristics of drought in this study. Sen's slope method and three-dimensional copula functions are adopted to analyse the variety of drought features, and Ensemble Empirical Mode Decomposition (EEMD) is used to analyse the variations in maize yield. A temporal assessment of the standardized yield residuals series (SYRS) of maize from 1961 to 2014 is conducted. A panel regression model is applied to demonstrate the drought impact on maize yield at various growth stages under the RCP4.5 scenario. The results show that the drought risk level for midwest Jilin Province, western Liaoning, and eastern Heilongjiang increase with global warming in the current scenario. The shorter three-dimensional joint return periods, 44-80 yr, were mainly located in western Jilin Province, Liaodong Peninsula, and northwestern Liaoning. Eastern Heilongjiang has a slightly longer joint return period of 80-100 yr. The SYRS shows a strong statistical correlation with drought indicator variations; drought-prone regions exhibit strong positive correlations. In comparison, excess precipitation regions show strong negative correlations with drought indicators in most growth stages. Drought indicators have a relatively strong association with SYRS at the milky-mature maize growth stage, and the occurrence of drought during this period primarily determines the maize yield changes in the future. Maize yield changes are -2.04%, -2.65% and -1.57% for Liaoning, Jilin, and Heilongjiang Province under the RCP4.5 scenario. These results can be used as a tool for early warning of drought risk to maize, and will accelerate the progress of drought disaster risk management.

Examining the extreme 2017 spring drought event in South Korea using a suite of drought indices (SPI, SC-PDSI, SPEI, EDI)

NASA Astrophysics Data System (ADS)

Nam, W. H.; Hayes, M. J.; Svoboda, M. D.; Fuchs, B.; Tadesse, T.; Wilhite, D. A.; Hong, E. M.; Kim, T.

2017-12-01

South Korea has experienced extreme droughts in 1994-1995, 2000-2001, 2012, 2015, and 2016-2017. The 2017 spring drought (with especially low winter precipitation recorded in winter 2016) affected a large portion of central and western South Korea, and was one of the most severe droughts in the region since the 2000-2001 drought. The spring drought of 2017 was characterized by exceptionally low precipitation with total precipitation from January to June being 50% lower than the mean normal precipitation record (1981-2010) over most of western South Korea. It was the climatologically driest spring over the 1961-2016 record period. Effective drought monitoring and management depends on which drought indices are selected because each drought index has different drought criteria or levels of drought severity, associated with drought responses. In this study, for the quantitative analysis of the spring 2017 drought event in South Korea, four widely-used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Self-Calibrated Palmer Drought Severity Index (SC-PDSI), and the Effective Drought Index (EDI) are compared with observed drought damaged areas in the context of agricultural drought impacts. The South Korean government (Ministry of Agriculture, Food and Rural Affairs (MAFRA) and Korea Rural Community Corporation (KRC)) has been operating a government-level drought monitoring system since 2016. Results from this study can be used to improve the drought monitoring applications, as well as drought planning and preparedness in South Korea.

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

A New EO-Based Indicator for Assessing and Monitoring Climate-Related Vegetation Stress

NASA Astrophysics Data System (ADS)

McCormick, Niall; Gobron, Nadine

2016-08-01

This paper describes a study in which a new environmental indicator, called Annual Vegetation Stress (AVS), has been developed, based on annual anomalies of satellite-measured Fraction of Absorbed Photosynthetically Active Radiation (FAPAR ), and used to map the area affected annually by vegetation stress during the period 2003-2014, for 108 selected developing countries. Analysis of the results for six countries in the "tropical and subtropical forests" ecoregion, reveals good correspondence between high AVS values, and the occurrence of climatic extremes (droughts) and anthropogenic disturbance (deforestation). The results for Equatorial Guinea suggest that the recent trend of large-scale droughts and rainfall deficits in Central and Western Africa, contribute to increased vegetation stress in the region's tropical rainforests. In East Timor there is evidence of a "biological lag" effect, whereby the main impacts of drought on the country's seasonally dry tropical forests are delayed until the year following the climate event.

Impacts of climate change on vegetation, hydrological and socio-economic droughts in a transitional wet-to-dry Mediterranean region

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Pulquério, Mário; Grosso, Nuno; Duarte Santos, Filipe; João Cruz, Maria

2015-04-01

The Tagus river basin is located in a transitional region between humid and semi-arid climate. The lower part of the basin is a strategic source of water for Portugal, providing water for agricultural irrigation, hydropower generation, and domestic water supplies for over 4 million people. Climate change in this region is expected to lead to higher temperatures and lower rainfall, therefore increasing climatic aridity. In this transitional region, this could lead to an increased frequency of severe droughts, threatening climatic support for current agricultural and forestry practices, as well as the sustainability of domestic water supplies. This work evaluated the impacts of climate change on drought frequency and severity for the Portuguese part of the Tagus river basin. Climate change scenarios for 2010-2100 (A2 greenhouse emission scenarios) were statistically downscaled for the study area. They were evaluated with the Soil and Water Assessment Tool (SWAT) eco-hydrological model, which simulated vegetation water demand and drought stress, soil water availability, irrigation abstraction, streamflow, reservoir storage and groundwater recharge. Water inflows from Spain were estimated using an empirical climate-based model. Drought occurrence and severity was analyzed in terms of: * meteorological drought, based on (i) the Standardized Precipitation Index and (ii) the Aridity Index; * vegetation/agricultural drought, based on plant water stress; * hydrological drought, based on (i) streamflow rates and (ii) reservoir storage; * socio-economic drought, based on (i) the capacity of the main reservoir in the system (Castelo de Bode) to sustain hydropower and domestic supplies, and (ii) the rate of groundwater extraction vs. irrigation demands for the cultures located in the intensive cultivation regions of the Lezírias near the Tagus estuary. The results indicate a trend of increasing frequency and severity of most drought types during the XXIst century, with a noticeable increase in the latter decades. The exceptions are agricultural droughts for annual crops, which appear to benefit from a milder and rainier winter; and domestic water supplies, which are not threatened in any scenario as long as they are prioritized over other water uses.

Incorporation of GRACE Data into a Bayesian Model for Groundwater Drought Monitoring

NASA Astrophysics Data System (ADS)

Slinski, K.; Hogue, T. S.; McCray, J. E.; Porter, A.

2015-12-01

Groundwater drought, defined as the sustained occurrence of below average availability of groundwater, is marked by below average water levels in aquifers and reduced flows to groundwater-fed rivers and wetlands. The impact of groundwater drought on ecosystems, agriculture, municipal water supply, and the energy sector is an increasingly important global issue. However, current drought monitors heavily rely on precipitation and vegetative stress indices to characterize the timing, duration, and severity of drought events. The paucity of in situ observations of aquifer levels is a substantial obstacle to the development of systems to monitor groundwater drought in drought-prone areas, particularly in developing countries. Observations from the NASA/German Space Agency's Gravity Recovery and Climate Experiment (GRACE) have been used to estimate changes in groundwater storage over areas with sparse point measurements. This study incorporates GRACE total water storage observations into a Bayesian framework to assess the performance of a probabilistic model for monitoring groundwater drought based on remote sensing data. Overall, it is hoped that these methods will improve global drought preparedness and risk reduction by providing information on groundwater drought necessary to manage its impacts on ecosystems, as well as on the agricultural, municipal, and energy sectors.

Remotely-sensed detection of effects of extreme droughts on gross primary production.

PubMed

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-06-15

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.

A Newly Global Drought Index Product Basing on Remotely Sensed Leaf Area Index Percentile Using Severity-Area-Duration Algorithm

NASA Astrophysics Data System (ADS)

Li, Xinlu; Lu, Hui; Lyu, Haobo

2017-04-01

Drought is one of the typical natural disasters around the world, and it has also been an important climatic event particular under the climate change. Assess and monitor drought accurately is crucial for addressing climate change and formulating corresponding policies. Several drought indices have been developed and widely used in regional and global scale to present and monitor drought, which integrate datasets such as precipitation, soil moisture, snowpack, streamflow, evapotranspiration that deprived from land surface models or remotely sensed datasets. Vegetation is a prominent component of ecosystem that modulates the water and energy flux between land surface and atmosphere, and thus can be regarded as one of the drought indicators especially for agricultural drought. Leaf area index (LAI), as an important parameter that quantifying the terrestrial vegetation conditions, can provide a new way for drought monitoring. Drought characteristics can be described as severity, area and duration. Andreadis et al. has constructed a severity-area-duration (SAD) algorithm to reflect the spatial patterns of droughts and their dynamics over time, which is a progress of drought analysis. In our study, a newly drought index product was developed using the LAI percentile (LAIpct) SAD algorithm. The remotely sensed global GLASS (Global LAnd Surface Satellite) LAI ranging from 2001-2011 has been used as the basic data. Data was normalized for each time phase to eliminate the phenology effect, and then the percentile of the normalized data was calculated as the SAD input. 20% was set as the drought threshold, and a clustering algorithm was used to identify individual drought events for each time step. Actual drought events were identified when considering multiple clusters merge to form a larger drought or a drought event breaks up into multiple small droughts according to the distance of drought centers and the overlapping drought area. Severity, duration and area were recorded for each actual drought event. Finally, we utilized the existing DSI drought index product for comparison. LAIpct drought index can detect both short-term and long-term drought events. In the last decades, most of the droughts at global scale are short-term that less than 1 year, and the longest drought event lasts for 3 year. The LAIpct drought area percentage consist well with DSI, and according to the drought severity classification of United States Drought Monitor system, we found the 20% LAIpct corresponds to moderate drought, 15% LAIpct corresponds to severe drought, and 10% LAIpct corresponds to extreme drought. For some typical drought event, we found the LAIpct drought spatial patterns agree well with DSI, and from the aspect of temporal consistency, LAIpct seems smoother and fitter to the reality than DSI product. Although the short period LAIpct drought index product hinders the analysis of global climate change to some extent, it provides a new way to better monitor the agricultural drought.

The European 2015 drought from a hydrological perspective

NASA Astrophysics Data System (ADS)

Laaha, Gregor; Gauster, Tobias; Delus, Claire; Vidal, Jean-Philippe

2016-04-01

The year 2015 was hot and dry in many European countries. A timely assessment of its hydrological impacts constitutes a difficult task, because stream flow records are often not available within 2-3 years after recording. Moreover, monitoring is performed on a national or even provincial basis. There are still major barriers of data access, especially for eastern European countries. Wherever data are available, their compatibility poses a major challenge. In two companion papers we summarize a collaborative initiative of members of UNESCO's FRIEND-Water program to perform a timely Pan-European assessment of the 2015 drought. In this second part we analyse the hydrological perspective based on streamflow observations. We first describe the data access strategy and the assessment method. We than present the results consisting of a range of low flow indices calculated for about 800 gauges across Europe. We compare the characteristics of the 2015 drought with the average, long-term conditions, and with the specific conditions of the 2003 drought, which is often used as a worst-case benchmark to gauge future drought events. Overall, the hydrological 2015 drought is characterised by a much smaller spatial extend than the 2003 drought. Extreme streamflows are observed mainly in a band North of the Alps spanning from E-France to Poland. In terms of flow magnitude, Czech, E-Germany and N-Austria were most affected. In this region the low flows often had return periods of 100 years and more, indicating that the event was much more severe than the 2003 event. In terms of deficit volumes, the centre of the event was more oriented towards S-Germany. Based on a detailed assessment of the spatio-temporal characteristics at various scales, we are able to explain the different behaviour in these regions by diverging wetness preconditions in the catchments. This suggest that the sole knowledge of atmospheric indices is not sufficient to characterise hydrological drought events. We claim that assessment of impacts on water resources requires hydrological data and additional efforts of Pan-European dimension need to be undertaken to make hydrological assessments more operational in the future.

Characterising droughts in Central America with uncertain hydro-meteorological data

NASA Astrophysics Data System (ADS)

Quesada Montano, B.; Westerberg, I.; Wetterhall, F.; Hidalgo, H. G.; Halldin, S.

2015-12-01

Droughts studies are scarce in Central America, a region frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation is important for water management and planning and can be done with the help of drought indices. Many indices have been developed in the last decades but their ability to suitably characterise droughts depends on the region of application. In Central America, comprehensive and high-quality observational networks of meteorological and hydrological data are not available. This limits the choice of drought indices and denotes the need to evaluate the quality of the data used in their calculation. This paper aimed to find which combination(s) of drought index and meteorological database are most suitable for characterising droughts in Central America. The drought indices evaluated were the standardised precipitation index (SPI), deciles (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with station (CHIRPS), CRN073, the Climate Research Unit (CRU), ERA-Interim and station databases, and temperature data from the CRU database. All the indices were calculated at 1-, 3-, 6-, 9- and 12-month accumulation times. As a first step, the large-scale meteorological precipitation datasets were compared to have an overview of the level of agreement between them and find possible quality problems. Then, the performance of all the combinations of drought indices and meteorological datasets were evaluated against independent river discharge data, in form of the standardised streamflow index (SSI). Results revealed the large disagreement between the precipitation datasets; we found the selection of database to be more important than the selection of drought index. We found that the best combinations of meteorological drought index and database were obtained using the SPI and DI, calculated with CHIRPS and station data.

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

A two millennium-long hot drought in the southwestern United States driven by Arctic sea-ice retreat

NASA Astrophysics Data System (ADS)

Lachniet, M. S.; Asmerom, Y.; Polyak, V. J.; Denniston, R. F.

2017-12-01

The Great Basin and lower Colorado River Basin are susceptible to sustained droughts that impact water resources and economic activity for millions of residents of the southwestern United States. The causes of past droughts in the basin remain debated. Herein, we document a strong Arctic to mid-latitude teleconnection during the Holocene that resulted in an extreme `hot drought' persisting for more than two millennia in the southwestern United States, based on a continuous growth rate and new high-resolution carbon and oxygen isotopic time series from a precisely-dated stalagmite from Leviathan Cave, Nevada. Between 9850-7670 yr B2k, highest Holocene oxygen isotope values indicate warm temperatures and moisture-sensitive proxies of high carbon isotope values and low stalagmite growth rate and minimal soil productivity and aquifer recharge. We refer to this period as the Altithermal Hot Drought. A second interval (6770 to 5310 yr B2k) indicates a warm drought. The two Altithermal droughts exceed in severity and duration any droughts observed in the modern and tree-ring records. Further, we show that Altithermal hot droughts were widespread in the southwestern United States, at a time when human populations in the Great Basin were low. The droughts show strong similarities to proxies for Arctic paleoclimate and we suggest that insolation-driven changes in sea ice and snow cover extent in the high latitudes drove atmospheric circulation anomalies in the Great Basin. Because rising greenhouse gas concentrations are projected to increase global and Arctic temperatures with a possible loss of summer sea by the end of the 21st century, our record suggests that a return to prolonged hotter and drier conditions in the southern Great Basin and lower Colorado River Basin is possible within coming centuries.

Effects of increasing root carbon investment on the mortality and resprouting of Haloxylon ammodendron seedlings under drought.

PubMed

Zhang, Y; Xie, J-B; Li, Y

2017-03-01

Tree mortality induced by drought is one of the most complex processes in ecology. Although two mechanisms associated with water and carbon balance are proposed to explain tree mortality, outstanding problems still exist. Here, in order to test how the root system benefits survival and resprouting of Haloxylon ammodendron seedlings, we examined the various water- and carbon-related physiological indicators (shoot water potential, photosynthesis, dark respiration, hydraulic conductance and non-structural carbohydrates [NSC]) of H. ammodendron seedlings, which were grown in drought and control conditions throughout a grow season in greenhouse. The survival time of the seedling root system (died 70 days after drought) doubled the survival time of the shoot (died at 35 days). Difference in survival time between shoot and root resulted from sustained root respiration supported by increased NSC in roots under drought. Furthermore, investment into the root contributed to resprouting following drought. Based on these results, a death criterion is proposed for this species. The time sequence of major events indicated that drought shifted carbon allocation between shoot and root and altered the flux among different sinks (growth, respiration or storage). The interaction of water and carbon processes determined death or survival of droughted H. ammodendron seedlings. These findings revealed that the 'root protection' strategy is critical in determining survival and resprouting of this species, and provided insights into the effects of carbon and water dynamics on tree mortality. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

Drought and Fire in the Western United States: Contrasting the Causes, Distributions, and Effects of Drought in the 20th and 21st Centuries with a Multiyear Moisture Deficit Drought Index

NASA Astrophysics Data System (ADS)

Crockett, J.; Westerling, A. L.

2016-12-01

The current drought in California is considered to be most severe drought event of the 20th and 21st century. Climate models forecast increasing temperatures in the Western United States but are less certain regarding precipitation patterns. Here we impose a novel index based on sustained, multiyear moisture deficit anomalies onto a 1/8° grid of the Western United States to investigate 1) whether California's drought is irregular in the recent history of the Western States; 2) how temperature and precipitation affected the development of large drought events; and 3) what impact did drought events have on burn area and severity of fires. Fire records were compiled from the Monitoring Trends in Burn Severity database and compared to drought events since 1984. Results indicate that drought events similar in size and duration to the current drought have occurred in the West since 1918, though previous drought events were not as severe nor centered on California. Six drought events of similar size to the 2012 - 2014 drought were compared: while they were characterized by negative precipitation anomalies, only the 2012 - 2014 event exhibited temperature anomalies that increased over the drought's duration. In addition, we found that large fires ( > 1000 acres) within drought areas had greater total area burned as well as area burned at medium and high severities compared to fires in non-drought areas. Our results suggest that though uncertainty of future precipitation patterns exists, increasing temperatures will exacerbate drought severity when events do occur. In addition, understanding the relationships between droughts and fire can guide land managers to more effective fire management during drought events.

Using weather data to determine dry and wet periods relative to ethnographic records

NASA Astrophysics Data System (ADS)

Felzer, B. S.; Jiang, M.; Cheng, R.; Ember, C. R.

2017-12-01

Ethnographers record flood or drought events that affect a society's food supply and can be interpreted in terms of a society's ability to adapt to extreme events. Using daily weather station data from the Global Historical Climatology Network for wet events, and monthly gridded climatic data from the Climatic Research Unit for drought events, we determine if it is possible to relate these measured data to the ethnographic records. We explore several drought and wetness indices based on temperature and precipitation, as well as the Colwell method to determine the predictability, seasonality, and variability of these extreme indices. Initial results indicate that while it is possible to capture the events recorded in the ethnographic records, there are many more "false" captures of events that are not recorded in these records. Although extreme precipitation is a poor indicator of floods due to antecedent moisture conditions, even using streamflow for selected sites produces false captures. Relating drought indices to actual food supply as measured in crop yield only related to minimum crop yield in half the cases. Further mismatches between extreme precipitation and drought indices and ethnographic records may relate to the fact that only extreme events that affect food supply are recorded in the ethnographic records or that not all events are recorded by the ethnographers. We will present new results on how predictability measures relate to the ethnographic disasters. Despite the highlighted technical challenges, our results provide a historic perspective linking environmental stressors with socio-economic impacts, which in turn, will underpin the current efforts of risk assessment in a changing environment.

Towards the construction of a Drought Early Warning System in México

NASA Astrophysics Data System (ADS)

Neri, C.; Magaña, V. O.

2011-12-01

Droughts in Mexico are related to severe impacts in agricultural and livestock activities, water management and with the occurrence of wildfire. Droughts are recurrent, on time scales from years to decades. The impacts however, depend on the vulnerability. The negative impacts may be reduced by studying and monitoring the dynamical evolution of meteorological drought, and by identifying the factors that result in vulnerability, in the context of risk management. Considering the analysis of the vulnerability in the northern of Mexico, a semiarid region highly vulnerable to drought, a Drought Early Warning System was created based on the use of climate information. The first step was to identify the capacity to provide useful climate information to develop prevention actions. Results confirm that the drought in northern Mexico is a well-diagnosed phenomenon from the point of view of impacts in various sectors. However, the use of climate information is still very limited resulting in response to mitigate drought impacts rather than preparing for drought. Part of the problem is the limited capacity to interpret probabilistic forecasts to define actions. Therefore, a key element in a Drought Early Warning System is the development of reliable climate information and the use of indicators to determine of the onset, maximum intensity and duration of the event. The occurrence and severity of drought may be estimated using climate diagnosis and forecast. A preventive response to drought may be defined if the severity and duration surpass a threshold value after which a decision action should be made. In order to establish the relevance of indicators for drought risk management, retroactive analyses have been developed considering the case of northwestern Mexico. After a vulnerability analysis that considers the institutional capacity to make use of climate information, a Drought Early warning System has been designed that considers a number of actions that may be put forward in order to reduce the impacts of such climatic hazard. The potential impact of such system is examined considering a number of actions that may be implemented in the water, agricultural and cattle ranching sectors. We conclude that there are great opportunities to reduce the negative impacts of drought if climate information is used.

Towards risk-based drought management in the Netherlands: quantifying the welfare effects of water shortage

NASA Astrophysics Data System (ADS)

van der Vat, Marnix; Femke, Schasfoort; Rhee Gigi, Van; Manfred, Wienhoven; Nico, Polman; Joost, Delsman; den Hoek Paul, Van; Maat Judith, Ter; Marjolein, Mens

2016-04-01

It is widely acknowledged that drought management should move from a crisis to a risk-based approach. A risk-based approach to managing water resources requires a sound drought risk analysis, quantifying the probability and impacts of water shortage due to droughts. Impacts of droughts are for example crop yield losses, hydropower production losses, and water shortage for municipal and industrial use. Many studies analyse the balance between supply and demand, but there is little experience in translating this into economic metrics that can be used in a decision-making process on investments to reduce drought risk. We will present a drought risk analysis method for the Netherlands, with a focus on the underlying economic method to quantify the welfare effects of water shortage for different water users. Both the risk-based approach as well as the economic valuation of water shortage for various water users was explored in a study for the Dutch Government. First, an historic analysis of the effects of droughts on revenues and prices in agriculture as well as on shipping and nature was carried out. Second, a drought risk analysis method was developed that combines drought hazard and drought impact analysis in a probabilistic way for various sectors. This consists of a stepwise approach, from water availability through water shortage to economic impact, for a range of drought events with a certain return period. Finally, a local case study was conducted to test the applicability of the drought risk analysis method. Through the study, experience was gained into integrating hydrological and economic analyses, which is a prerequisite for drought risk analysis. Results indicate that the risk analysis method is promising and applicable for various sectors. However, it was also found that quantification of economic impacts from droughts is time-consuming, because location- and sector-specific data is needed, which is not always readily available. Furthermore, for some sectors hydrological data was lacking to make a reliable estimate of drought return periods. By 2021, the Netherlands Government aims to agree on the water supply service levels, which should describe water availability and quality that can be delivered with a certain return period. The Netherlands' Ministry of Infrastructure and the Environment, representatives of the regional water boards and Rijkswaterstaat (operating the main water system) as well as several consultants and research institutes are important stakeholders for further development of the method, evaluation of cases and the development of a quantitative risk-informed decision-making tool.

Diverging drought resistance of Scots pine provenances revealed by infrared thermography and mortality

NASA Astrophysics Data System (ADS)

Seidel, Hannes; Schunk, Christian; Matiu, Michael; Menzel, Annette

2016-04-01

Climate warming and more frequent and severe drought events will alter the adaptedness and fitness of tree species. Especially, Scots pine forests have been affected above average by die-off events during the last decades. Assisted migration of adapted provenances might help alleviating impacts by recent climate change and successfully regenerating forests. However, the identification of suitable provenances based on established ecophysiological methods is time consuming, sometimes invasive, and data on provenance-specific mortality are lacking. We studied the performance, stress and survival of potted Scots pine seedlings from 12 European provenances grown in a greenhouse experiment with multiple drought and warming treatments. In this paper, we will present results of drought stress impacts monitored with four different thermal indices derived from infrared thermography imaging as well as an ample mortality study. Percent soil water deficit (PSWD) was shown to be the main driver of drought stress response in all thermal indices. In spite of wet and dry reference surfaces, however, fluctuating environmental conditions, mainly in terms of air temperature and humidity, altered the measured stress response. In linear mixed-effects models, besides PSWD and meteorological covariates, the factors provenance and provenance - PSWD interactions were included. The explanatory power of the models (R2) ranged between 0.51 to 0.83 and thus, provenance-specific responses to strong and moderate drought and subsequent recovery were revealed. However, obvious differences in the response magnitude of provenances to drought were difficult to explicitly link to general features such Mediterranean - continental type or climate at the provenances' origin. We conclude that seedlings' drought resistance may be linked to summer precipitation and their experienced stress levels are a.o. dependent on their above ground dimensions under given water supply. In respect to mortality, previous drought stress experience lowered the current risk and obvious provenance effects were largely related to different growth traits (dimensions). Our experimental results suggest besides evidence for abiotic stress hardening provenance-specific variation in drought resilience. Thus, there is room for provenance-based assisted migration as tool for climate change adaptation in forestry.

Drought Analysis of the Haihe River Basin Based on GRACE Terrestrial Water Storage

PubMed Central

Wang, Jianhua; Jiang, Dong; Huang, Yaohuan; Wang, Hao

2014-01-01

The Haihe river basin (HRB) in the North China has been experiencing prolonged, severe droughts in recent years that are accompanied by precipitation deficits and vegetation wilting. This paper analyzed the water deficits related to spatiotemporal variability of three variables of the gravity recovery and climate experiment (GRACE) derived terrestrial water storage (TWS) data, precipitation, and EVI in the HRB from January 2003 to January 2013. The corresponding drought indices of TWS anomaly index (TWSI), precipitation anomaly index (PAI), and vegetation anomaly index (AVI) were also compared for drought analysis. Our observations showed that the GRACE-TWS was more suitable for detecting prolonged and severe droughts in the HRB because it can represent loss of deep soil water and ground water. The multiyear droughts, of which the HRB has sustained for more than 5 years, began in mid-2007. Extreme drought events were detected in four periods at the end of 2007, the end of 2009, the end of 2010, and in the middle of 2012. Spatial analysis of drought risk from the end of 2011 to the beginning of 2012 showed that human activities played an important role in the extent of drought hazards in the HRB. PMID:25202732

Drought analysis of the Haihe river basin based on GRACE terrestrial water storage.

PubMed

Wang, Jianhua; Jiang, Dong; Huang, Yaohuan; Wang, Hao

2014-01-01

The Haihe river basin (HRB) in the North China has been experiencing prolonged, severe droughts in recent years that are accompanied by precipitation deficits and vegetation wilting. This paper analyzed the water deficits related to spatiotemporal variability of three variables of the gravity recovery and climate experiment (GRACE) derived terrestrial water storage (TWS) data, precipitation, and EVI in the HRB from January 2003 to January 2013. The corresponding drought indices of TWS anomaly index (TWSI), precipitation anomaly index (PAI), and vegetation anomaly index (AVI) were also compared for drought analysis. Our observations showed that the GRACE-TWS was more suitable for detecting prolonged and severe droughts in the HRB because it can represent loss of deep soil water and ground water. The multiyear droughts, of which the HRB has sustained for more than 5 years, began in mid-2007. Extreme drought events were detected in four periods at the end of 2007, the end of 2009, the end of 2010, and in the middle of 2012. Spatial analysis of drought risk from the end of 2011 to the beginning of 2012 showed that human activities played an important role in the extent of drought hazards in the HRB.

Remotely-sensed detection of effects of extreme droughts on gross primary production

PubMed Central

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-01-01

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671

500-year April-September droughts in the Czech Lands based on documentary data and instrumental records

NASA Astrophysics Data System (ADS)

Řezníčková, Ladislava; Brázdil, Rudolf; Trnka, Miroslav; Dobrovolný, Petr; Kotyza, Oldřich; Štěpánek, Petr; Zahradníček, Pavel; Valášek, Hubert

2013-04-01

This paper analyses temporal and spatial variability of April-September (the vegetation period) droughts in the Czech Lands over the last 500 years. The study is based on different types of documentary data (e.g. chronicles, newspapers, economic sources, weather diaries) covering the pre-instrumental period AD 1501-1804 and on the systematic instrumental meteorological measurements afterwards. Historical-climatological database of the Czech Lands is used for the study of the duration and intensity of drought episodes based on the series of precipitation indices created from documentary data in a 7-degree scale from -3 (extremely dry) to +3 (extremely wet). For the instrumental period of 1805-2012 Palmer's Z-index and PDSI series for mean Czech temperature and precipitation series are used (they were calculated from homogeneous series of 10 and 14 stations respectively). Consequently the 500-year chronology of drought episodes derived from documentary and instrumental data is compiled and the temporal (frequency, seasonality and intensity) and spatial variability of droughts in the Czech Lands from AD 1501 is analysed. The most outstanding drought events are selected and analysed in detail also with respect to their human impacts. The results obtained for the Czech Lands are compared with drought episodes known in Central Europe from other studies and are evaluated with respect to climate variability in Central Europe during the last 500 years (this research is supported by projects InterDrought no. CZ.1.07/2.3.00/20.0248, and GA CR no. P209/11/0956).

A Refined Crop Drought Monitoring Method Based on the Chinese GF-1 Wide Field View Data

PubMed Central

Chang, Sheng; Wu, Bingfang; Yan, Nana; Zhu, Jianjun; Wen, Qi; Xu, Feng

2018-01-01

In this study, modified perpendicular drought index (MPDI) models based on the red-near infrared spectral space are established for the first time through the analysis of the spectral characteristics of GF-1 wide field view (WFV) data, with a high spatial resolution of 16 m and the highest frequency as high as once every 4 days. GF-1 data was from the Chinese-made, new-generation high-resolution GF-1 remote sensing satellites. Soil-type spatial data are introduced for simulating soil lines in different soil types for reducing errors of using same soil line. Multiple vegetation indices are employed to analyze the response to the MPDI models. Relative soil moisture content (RSMC) and precipitation data acquired at selected stations are used to optimize the drought models, and the best one is the Two-band enhanced vegetation index (EVI2)-based MPDI model. The crop area that was statistically significantly affected by drought from a local governmental department, and used for validation. High correlations and small differences in drought-affected crop area was detected between the field observation data from the local governmental department and the EVI2-based MPDI results. The percentage of bias is between −21.8% and 14.7% in five sub-areas, with an accuracy above 95% when evaluating the performance via the data for the whole study region. Generally the proposed EVI2-based MPDI for GF-1 WFV data has great potential for reliably monitoring crop drought at a relatively high frequency and spatial scale. Currently there is almost no drought model based on GF-1 data, a full exploitation of the advantages of GF-1 satellite data and further improvement of the capacity to observe ground surface objects can provide high temporal and spatial resolution data source for refined monitoring of crop droughts. PMID:29690639

A Refined Crop Drought Monitoring Method Based on the Chinese GF-1 Wide Field View Data.

PubMed

Chang, Sheng; Wu, Bingfang; Yan, Nana; Zhu, Jianjun; Wen, Qi; Xu, Feng

2018-04-23

In this study, modified perpendicular drought index (MPDI) models based on the red-near infrared spectral space are established for the first time through the analysis of the spectral characteristics of GF-1 wide field view (WFV) data, with a high spatial resolution of 16 m and the highest frequency as high as once every 4 days. GF-1 data was from the Chinese-made, new-generation high-resolution GF-1 remote sensing satellites. Soil-type spatial data are introduced for simulating soil lines in different soil types for reducing errors of using same soil line. Multiple vegetation indices are employed to analyze the response to the MPDI models. Relative soil moisture content (RSMC) and precipitation data acquired at selected stations are used to optimize the drought models, and the best one is the Two-band enhanced vegetation index (EVI2)-based MPDI model. The crop area that was statistically significantly affected by drought from a local governmental department, and used for validation. High correlations and small differences in drought-affected crop area was detected between the field observation data from the local governmental department and the EVI2-based MPDI results. The percentage of bias is between −21.8% and 14.7% in five sub-areas, with an accuracy above 95% when evaluating the performance via the data for the whole study region. Generally the proposed EVI2-based MPDI for GF-1 WFV data has great potential for reliably monitoring crop drought at a relatively high frequency and spatial scale. Currently there is almost no drought model based on GF-1 data, a full exploitation of the advantages of GF-1 satellite data and further improvement of the capacity to observe ground surface objects can provide high temporal and spatial resolution data source for refined monitoring of crop droughts.

Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

USGS Publications Warehouse

Otkin, Jason A.; Anderson, Martha C.; Hain, Christopher; Svoboda, Mark; Johnson, David; Mueller, Richard; Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn

2016-01-01

This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS).Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 wk depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2–4 wk), whereas corn conditions were more closely related to longer-range (8–12 wk) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.

Development of a Remote-Sensing Based Framework for Mapping Drought over North America

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Zhan, X.; Gao, F.; Svoboda, M.; Wardlow, B.; Mladenova, I. E.

2012-12-01

This presentation will address the development of a multi-scale drought monitoring tool for North America based on remotely sensed estimates of evapotranspiration. The North American continent represents a broad range in vegetation and climate conditions, from the boreal forests in Canada to the arid deserts in Mexico. This domain also encompasses a range in constraints limiting vegetation growth, with a gradient from radiation/energy limitation in the north to moisture limits in the south. This feasibility study over NA will provide a valuable test bed for future implementation world-wide in support of proposed global drought monitoring and early warning efforts. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET (fPET), generated with the thermal remote sensing based Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance model and associated disaggregation algorithm, DisALEXI demonstrated that ESI maps over the continental US (CONUS) show good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall, for example in areas where drought impacts are being mitigated by intense irrigation or shallow water tables. As such, the ESI is a measure of actual stress rather than potential for stress, and has physical relevance to projected crop development. Because precipitation is not used in construction of the ESI, this index provides an independent assessment of drought conditions and will have particular utility for real-time monitoring in regions with sparse rainfall data or significant delays in meteorological reporting. The North American ESI product will be quantitatively compared with spatiotemporal patterns in the NADM, and with standard meteorological, remote sensing and modeled drought indices that are routinely produced over NA. Importantly, the robustness of these various indicators will be assessed in their ability to anticipate and correctly diagnose known drought events (as recorded in the NADM archive).

Satellite gravity measurement monitoring terrestrial water storage change and drought in the continental United States.

PubMed

Yi, Hang; Wen, Lianxing

2016-01-27

We use satellite gravity measurements in the Gravity Recovery and Climate Experiment (GRACE) to estimate terrestrial water storage (TWS) change in the continental United States (US) from 2003 to 2012, and establish a GRACE-based Hydrological Drought Index (GHDI) for drought monitoring. GRACE-inferred TWS exhibits opposite patterns between north and south of the continental US from 2003 to 2012, with the equivalent water thickness increasing from -4.0 to 9.4 cm in the north and decreasing from 4.1 to -6.7 cm in the south. The equivalent water thickness also decreases by -5.1 cm in the middle south in 2006. GHDI is established to represent the extent of GRACE-inferred TWS anomaly departing from its historical average and is calibrated to resemble traditional Palmer Hydrological Drought Index (PHDI) in the continental US. GHDI exhibits good correlations with PHDI in the continental US, indicating its feasibility for drought monitoring. Since GHDI is GRACE-based and has minimal dependence of hydrological parameters on the ground, it can be extended for global drought monitoring, particularly useful for the countries that lack sufficient hydrological monitoring infrastructures on the ground.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Contribution of precipitation and reference evapotranspiration to drought indices under different climates

NASA Astrophysics Data System (ADS)

Vicente-Serrano, Sergio M.; Van der Schrier, Gerard; Beguería, Santiago; Azorin-Molina, Cesar; Lopez-Moreno, Juan-I.

2015-07-01

In this study we analyzed the sensitivity of four drought indices to precipitation (P) and reference evapotranspiration (ETo) inputs. The four drought indices are the Palmer Drought Severity Index (PDSI), the Reconnaissance Drought Index (RDI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Palmer Drought Index (SPDI). The analysis uses long-term simulated series with varying averages and variances, as well as global observational data to assess the sensitivity to real climatic conditions in different regions of the World. The results show differences in the sensitivity to ETo and P among the four drought indices. The PDSI shows the lowest sensitivity to variation in their climate inputs, probably as a consequence of the standardization procedure of soil water budget anomalies. The RDI is only sensitive to the variance but not to the average of P and ETo. The SPEI shows the largest sensitivity to ETo variation, with clear geographic patterns mainly controlled by aridity. The low sensitivity of the PDSI to ETo makes the PDSI perhaps less apt as the suitable drought index in applications in which the changes in ETo are most relevant. On the contrary, the SPEI shows equal sensitivity to P and ETo. It works as a perfect supply and demand system modulated by the average and standard deviation of each series and combines the sensitivity of the series to changes in magnitude and variance. Our results are a robust assessment of the sensitivity of drought indices to P and ETo variation, and provide advice on the use of drought indices to detect climate change impacts on drought severity under a wide variety of climatic conditions.

Biomass measurement from LANDSAT: Drought and energy applications

NASA Technical Reports Server (NTRS)

Maxwell, E. L.

1981-01-01

The theory supporting the use of vegetation indices derived from LANDSAT data for the direct measurement of biomass is reviewed. The use of multispectral data to measure biomass is a natural and viable application since the photosynthetic production of biomass gives vegetation its unique spectral properties. Vegetation indices also perform a normalization function which tends to make them insensitive to atmospheric and soil color variations. Optical and digital LANDSAT products are discussed relative to the use of vegetation indices to monitor drought impact. Based on results obtained in Colorado, operational use of LANDSAT to monitor drought is cost effective, practical and ready for implementation today. The direct measurement of biomass energy resources may also benefit from LANDSAT technology. Measurement of total biomass and annual primary production may be feasible. Identification of that component of biomass resources available for energy use will require other sources of information, however.

Drought tolerance of selected bottle gourd [Lagenaria siceraria (Molina) Standl.] landraces assessed by leaf gas exchange and photosynthetic efficiency.

PubMed

Mashilo, Jacob; Odindo, Alfred O; Shimelis, Hussein A; Musenge, Pearl; Tesfay, Samson Z; Magwaza, Lembe S

2017-11-01

Successful cultivation of bottle gourd in arid and semi-arid areas of sub-Saharan Africa and globally requires the identification of drought tolerant parents for developing superior genotypes with increased drought resistance. The objective of this study was to determine the level of drought tolerance among genetically diverse South African bottle gourd landraces based on leaf gas exchange and photosynthetic efficiency and identify promising genotypes for breeding. The responses of 12 bottle gourd landraces grown in glasshouse under non-stressed (NS) and drought-stressed (DS) conditions were studied. A significant genotype x water regime interaction was observed for gs, T, A, A/C i , IWUE, WUE ins , F m ', F v '/F m ', Ф PSII , qP, qN, ETR, ETR/A and AES indicating variability in response among the studied bottle gourd landraces under NS and DS conditions. Principal component analysis identified three principal components (PC's) under drought stress condition contributing to 82.9% of total variation among leaf gas exchange and chlorophyll fluorescence parameters measured. PC1 explained 36% of total variation contributed by gs, T, F 0 ', F m ', F v '/F m ' and qN, while PC2 explained 28% of the variation and highly correlated with A, A/C i , IWUE, WUE ins ETR/A and AES. PC3 explained 14% of total variation contributed by Ф PSII , qP and ETR. Principal biplot analysis allowed the identification of drought tolerant genotypes such as BG-27, BG-48, BG-58, BG-79, BG-70 and BG-78 which were grouped based on high gs, A, F m 'F v '/F m ', qN, ETR/A and AES under DS condition. The study suggests that the identified physiological traits could be useful indicators in the selection of bottle gourd genotypes for increased drought tolerance. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Bias correction of precipitation data and its effects on aridity and drought assessment in China over 1961-2015.

PubMed

Yao, Ning; Li, Yi; Li, Na; Yang, Daqing; Ayantobo, Olusola Olaitan

2018-10-15

The accuracy of gauge-measured precipitation (P m ) affects drought assessment since drought severity changes due to precipitation bias correction. This research investigates how drought severity changes as the result of bias-corrected precipitation (P c ) using the Erinc's index I m and standardized precipitation evapotranspiration index (SPEI). Daily and monthly P c values at 552 sites in China were determined using daily P m and wind speed and air temperature data over 1961-2015. P c -based I m values were generally larger than P m -based I m for most sub-regions in China. The increased P c and P c -based I m values indicated wetter climate conditions than previously reported for China. After precipitation bias-correction, Climate types changed, e.g., 20 sites from severe-arid to arid, and 11 sites from arid to semi-arid. However, the changes in SPEI were not that obvious due to precipitation bias correction because the standardized index SPEI removed the effects of mean precipitation values. In conclusion, precipitation bias in different sub-regions of China changed the spatial and temporal characteristics of drought assessment. Copyright © 2018 Elsevier B.V. All rights reserved.

Recovery of Ecosystem Carbon and Energy Fluxes From the 2003 Drought in Europe and the 2012 Drought in the United States

NASA Astrophysics Data System (ADS)

He, Bin; Liu, Junjie; Guo, Lanlan; Wu, Xiuchen; Xie, Xaoming; Zhang, Yafeng; Chen, Chen; Zhong, Ziqian; Chen, Ziyue

2018-05-01

Recovery of an ecosystem from drought is an important indicator of ecosystem resilience. However, few investigations have heretofore focused on the recovery of ecosystem carbon and energy fluxes but have mainly focused on the drought recovery of plant growth and ecosystem productions. Therefore, the present study uses in situ observations from FLUXNET 2015 to examine the recovery of carbon flux and energy flux of ecosystems from the 2003 European drought and the 2012 U.S. drought on the daily scale. The results reveal the strong impact of these two extreme droughts on ecosystem gross primary production, total ecosystem respiration, net ecosystem exchange, and latent heat flux. In addition, the recovery time of these indicators differ significantly. At the regional scale, the recovery of gross primary production, total ecosystem respiration, net ecosystem exchange, and latent heat flux took 44, 23, 63, and 27 days after the 2003 European drought, and the recovery for corresponding indicators for the 2012 U.S. drought took 42, 63, 15, and 33 days, respectively. Further investigations suggest that indicator background conditions and drought-damage magnitudes played an important role in regulating drought recovery in the 2003 European drought, with lower background value and greater damage leading to a longer recovery time. The ecosystem recovery from the 2012 U.S. drought, however, was dominated by the precipitation condition during the recovery period, with more precipitation associated with a shorter recovery time. These results provide crucial insight into the divergent recovery trajectories for different carbon-water processes among diverse bioclimatic regions.

Drought Prediction for Socio-Cultural Stability Project

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa; Eylander, John B.; Koster, Randall; Narapusetty, Balachandrudu; Kumar, Sujay; Rodell, Matt; Bolten, John; Mocko, David; Walker, Gregory; Arsenault, Kristi;

Forest response to 1,000 years of drought variability in the Southwestern United States

NASA Astrophysics Data System (ADS)

Williams, A. P.; Meko, D. M.; Woodhouse, C. A.; Cook, E.; Swetnam, T. W.; Macalady, A. K.; Allen, C. D.; Rauscher, S. A.; Jiang, X.; Grissino-Mayer, H.; McDowell, N. G.; Cai, M.

2011-12-01

Droughts in the early 1950s and early 2000s significantly accelerated tree mortality rates in the Southwestern United States. During the early 2000s, forest inventory data indicate that the proportion of dead piñon pine, ponderosa pine, and Douglas-fir trees doubled in the Southwest. The 2000s drought peaked in 2002 and was the most severe drought in at least 100 years. In 2011, precipitation, dew-point, and wind data indicate the intensity of the 2002 drought has been surpassed in a number of ways. Measurements of water potential in piñon pine trees in northern New Mexico indicate that, at present, trees have less access to soil moisture than in 2002 when widespread mortality occurred. How do these recent droughts compare to those of the last 1000 years? We used records of annual tree-ring widths from 309 populations of piñon pine, ponderosa pine, and Douglas-fir throughout the Southwestern United States to reconstruct a single record of regional drought stress from 1000-2005 AD. This record indicates that the last Southwestern drought similar in intensity to one in the early 2000s occurred in the late 1600s. Both of these droughts, however, paled in comparison to a mega-drought that occurred from 1575-1595. The emergence from this mega-drought, around 1600 AD, appears to mark a transition period from a time when droughts similar the early 2000s drought were much more common. Tree-age studies indicate a scarcity of Southwestern trees with rings extending back beyond the mega-drought of the late 1500s. This suggests that (1) the late-1500s mega-drought triggered a massive die-off of forests and/or (2) the higher frequency of drought events prior to the mega-drought sustained a much more sparse forest population than the one that has thrived from the 1600s through present. Given this apparent plasticity of Southwestern forests, a change in the forest population should be underway if higher temperatures contribute to forest drought stress. The Southwestern tree-ring record indicates that this is the case. During the 20th century, tree-ring widths correlated very positively with total winter precipitation and very negatively with spring-summer maximum temperature. This indicates that Southwestern forest growth is significantly impacted by both the amount of water delivered before the growing season and temperature during the growing season. We conclude that in the absence of a significant increase in winter precipitation, continued warming should lead to a more sparsely populated Southwestern forest population, similar to the one that appears to have existed during 1000-1600 AD.

New insights on historic droughts in the UK: Analysis of 200 river flow reconstructions for 1890-2015

NASA Astrophysics Data System (ADS)

Parry, Simon; Barker, Lucy; Hannaford, Jamie; Prudhomme, Christel; Smith, Katie; Svensson, Cecilia; Tanguy, Maliko

2017-04-01

Hydrological droughts of the last 50 years in the UK have been well characterised owing to a relatively dense hydrometric network. Prior to this, observed river flow data were generally limited in their spatial coverage and often subject to considerable uncertainty. Whilst qualitative records indicate the occurrence of severe droughts in the late 19th and early 20th centuries, including scenarios which may cause substantial impacts to contemporary water supply systems, existing observations are not sufficient to describe their spatio-temporal characteristics. As such, insights on drought in the UK are constrained and a range of stakeholders including water companies and regulators would benefit from a more thorough assessment of historic drought characteristics and their variability. The multi-disciplinary Historic Droughts project aims to rigorously characterise droughts in the UK to inform improved drought management and communication. Driven by rainfall and potential evapotranspiration data that have been extended using recovered records, lumped catchment hydrological models are used to reconstruct daily river flows from 1890 to 2015 for more than 200 catchments across the UK. The reconstructions are derived within a state-of-the-art modelling framework which allows a comprehensive assessment of model, structure and parameter uncertainty. Standardised and threshold-based indicators are applied to the river flow reconstructions to identify and characterise hydrological drought events. The reconstructions are most beneficial in comprehensively describing well known but poorly quantified late 19th and early 20th century droughts, placing the spatial and temporal footprint of these often extreme events within the context of modern episodes for the first time. Oscillations between drought-rich and drought-poor periods are shown not to be limited to the recent observational past, providing an increased sample size of events against which to test a range of airflow and oceanic index patterns as potential drivers of streamflow drought. The quantification of changes over time in both the mean and the variability of drought frequency, duration, severity and termination benefits from the temporal extent of the river flow reconstructions, assessing the temporal variability of drought over more prolonged timescales than previous drought trend studies. When considered alongside complimentary reconstructions of rainfall and groundwater levels, the characteristics of propagation from meteorological to hydrological drought are analysed to an extent not previously possible. The unprecedented spatio-temporal coverage of the river flow reconstructions has yielded important new insights on historic droughts in the UK. It is hoped that this more robust assessment of the historical variability of hydrological drought in the UK will underpin enhanced drought planning and management.

Effects of drought on avian community structure

Treesearch

Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Brian D. Wardlow; Volker C. Radeloff

2010-01-01

Droughts are expected to become more frequent under global climate change. Avifauna depend on precipitation for hydration, cover, and food. While there are indications that avian communities respond negatively to drought, little is known about the response of birds with differing functional and behavioural traits, what time periods and indicators of drought are most...

From drought indicators to impacts: developing improved tools for monitoring and early warning with decision-makers in mind

NASA Astrophysics Data System (ADS)

Hannaford, Jamie; Barker, Lucy; Svensson, Cecilia; Tanguy, Maliko; Laize, Cedric; Bachmair, Sophie; Tijdeman, Erik; Stahl, Kerstin; Collins, Kevin

2016-04-01

Droughts pose a threat to water security in most climate zones and water use sectors. With projections suggesting that droughts will intensify in many parts of the globe, the magnitude of this threat is likely to increase in the future and thus vulnerability of society to drought must be reduced through better preparedness. While the occurrence of drought cannot be prevented in the short term, a number of actions can be taken to reduce vulnerability. Monitoring and early warning (M&EW) systems are often central to drought management strategies aimed at reducing vulnerability, but they are generally less developed than for other hazards. There are many drought indicators available for characterising the hazard but they have only rarely been tested for their ability to capture observed impacts on society or the environment. There is a pressing need to better integrate the physical and social vulnerability elements of drought to improve M&EW systems. The Belmont Forum project DrIVER (Drought Impacts: Vulnerability thresholds in monitoring and Early-warning Research, 2014 - 2016) aims to fill this gap by strengthening the link between natural (hydrometeorological) drought characterisation and ecological and socio-economic impacts on three continents (North America, Europe and Australia). The UK is a key DrIVER case study area. The UK has a well-developed hydrological monitoring programme, but there is currently no national drought focused M&EW system; different actors (water companies, regulators, farmers or industry) typically conduct M&EW for their own particular purposes. In this paper we present the early outcomes of an extensive programme of research designed to provide a scientific foundation for improved M&EW systems for the UK in future. The UK is used here as an example, and the findings could prove useful for other localities seeking to develop M&EW systems. Firstly, we present the results of stakeholder engagement exercises designed to ascertain current use of M&EW and future aspirations. Different stakeholders clearly have different goals for M&EW, but there are a number of common themes, including a desire to better understand the links between the outputs of large-scale M&EW systems (rainfall, river flow, etc), localised triggers used by decision-makers during drought episodes, and actual impacts of drought. Secondly, we present analyses designed to test the utility of a wide range of drought indicators for their use in UK applications. We demonstrate the suitability of standardised indicators (like the SPI) for use in the UK, addressing the suitability of statistical distributions and using these indicators for drought severity quantification and for understanding propagation from meteorological to hydrological drought; all of which are currently poorly understood aspects that are vital for future monitoring. We then address the extent to which these indicators can be used to predict drought impacts, focusing on several sectors (water supply, agriculture and ecosystems). These analyses test which indicators perform best at predicting drought impacts, and seek to identify indicator thresholds that trigger impact occurrence. Unsurprisingly, we found that no single indicator best predicts impacts, and results are domain, sector and season specific. However, we reveal important linkages between indicators and impacts that could enhance the design and delivery of monitoring and forecasting information and its uptake by decision-makers concerned with drought.

Performing drought indices to identify the relationship between agricultural losses and drought events in Spain.

NASA Astrophysics Data System (ADS)

Peña Gallardo, Marina; Serrano, Sergio Martín Vicente; Portugués Santiago, Beguería; Burguera Miquel, Tomás

2017-04-01

Drought leads to crop failures reducing the productivity. For this reason, the need of appropriate tool for recognize dry periods and evaluate the impact of drought on crop production is important. In this study, we provide an assessment of the relationship between drought episodes and crop failures in Spain as one of the direct consequences of drought is the diminishing of crop yields. First, different drought indices [the Standardized Precipitation and Evapotranspiration Index (SPEI); the Standardized Precipitation Index (SPI); the self-calibrated Palmer Moisture Anomaly Index (Z-Index), the self-calibrated Crop Moisture Index (CMI) and the Standardized Palmer Drought Index (SPDI)] have been calculated at different time scales in order to identify the dry events occurred in Spain and determine the duration and intensity of each event. Second, the drought episodes have been correlated with crop production estimated and final crop production data provided by the Spanish Crop Insurance System for the available period from 1995 to 2014 at the municipal spatial scale, with the purpose of knowing if the characteristics of the drought episodes are reflected on the agricultural losses. The analysis has been carried out in particular for two types of crop, wheat and barley. The results indicate the existence of an agreement between the most important drought events in Spain and the response of the crop productions and the proportion of hectare insurance. Nevertheless, this agreement vary depending on the drought index applied. Authors found a higher competence of the drought indices calculated at different time scales (SPEI, SPI and SPDI) identifying the begging and end of the drought events and the correspondence with the crop failures.

Towards drought risk mapping on a pan-European scale

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Gudmundsson, Lukas; Stahl, Kerstin; Seneviratne, Sonia

2014-05-01

Drought is a very complex and multifarious natural hazard, which causes a variety of direct and indirect environmental and socio-economic impacts. For the last 30 years, droughts in Europe caused over 100 billion Euros of losses from impacts in various sectors e.g. agriculture, water quality or energy production. Despite the apparent importance of this hazard observed pan-European drought impacts have not yet been quantitatively related to the most important climatological drivers. Fundamentally, a common approach to describe drought risk on a pan-European scale is still missing. This contribution presents an approach for linking climatological drought indices with observed drought impacts at the European scale. Standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) for different time scales were calculated based on E-OBS data and are used to describe the drought hazard. Data from the European Drought Impact Inventory (EDII) compiled by the EU FP7 Drought R&SPI (Fostering European Drought Research and Science-Policy Interfacing) project are used as a proxy for multi-sectorial (impact categories) vulnerability following the assumption that a reported impact reflects a region's vulnerability to the hazard. Drought risk is then modelled statistically by applying logistic regression to estimate the probability of impact report occurrence as a function of SPI and SPEI. This approach finally allows to map the probability of drought impact occurrence on a year by year basis. The emerging patterns compare well to many known European drought events. Such maps may become an essential component of Drought Risk Management to foster resilience for this hazard at the large scale.

Forest resilience to drought varies across biomes.

PubMed

Gazol, Antonio; Camarero, Jesus Julio; Vicente-Serrano, Sergio M; Sánchez-Salguero, Raúl; Gutiérrez, Emilia; de Luis, Martin; Sangüesa-Barreda, Gabriel; Novak, Klemen; Rozas, Vicente; Tíscar, Pedro A; Linares, Juan C; Martín-Hernández, Natalia; Martínez Del Castillo, Edurne; Ribas, Montse; García-González, Ignacio; Silla, Fernando; Camisón, Alvaro; Génova, Mar; Olano, José M; Longares, Luis A; Hevia, Andrea; Tomás-Burguera, Miquel; Galván, J Diego

2018-05-01

Forecasted increase drought frequency and severity may drive worldwide declines in forest productivity. Species-level responses to a drier world are likely to be influenced by their functional traits. Here, we analyse forest resilience to drought using an extensive network of tree-ring width data and satellite imagery. We compiled proxies of forest growth and productivity (TRWi, absolutely dated ring-width indices; NDVI, Normalized Difference Vegetation Index) for 11 tree species and 502 forests in Spain corresponding to Mediterranean, temperate, and continental biomes. Four different components of forest resilience to drought were calculated based on TRWi and NDVI data before, during, and after four major droughts (1986, 1994-1995, 1999, and 2005), and pointed out that TRWi data were more sensitive metrics of forest resilience to drought than NDVI data. Resilience was related to both drought severity and forest composition. Evergreen gymnosperms dominating semi-arid Mediterranean forests showed the lowest resistance to drought, but higher recovery than deciduous angiosperms dominating humid temperate forests. Moreover, semi-arid gymnosperm forests presented a negative temporal trend in the resistance to drought, but this pattern was absent in continental and temperate forests. Although gymnosperms in dry Mediterranean forests showed a faster recovery after drought, their recovery potential could be constrained if droughts become more frequent. Conversely, angiosperms and gymnosperms inhabiting temperate and continental sites might have problems to recover after more intense droughts since they resist drought but are less able to recover afterwards. © 2018 John Wiley & Sons Ltd.

Groundwater as an emergency source for drought mitigation in the Crocodile River catchment, South Africa

NASA Astrophysics Data System (ADS)

Mussá, F. E. F.; Zhou, Y.; Maskey, S.; Masih, I.; Uhlenbrook, S.

2015-02-01

Global climate change has received much attention worldwide in the scientific as well as in the political community, indicating that changes in precipitation, extreme droughts and floods may increasingly threaten many regions. Drought is a natural phenomenon that causes social, economical and environmental damage to society. In this study, we assess the drought intensity and severity and the groundwater potential to be used as a supplementary source of water to mitigate drought impacts in the Crocodile River catchment, a water-stressed sub-catchment of the Incomati River catchment in South Africa. The research methodology consists of three parts. First, the spatial and temporal variation of the meteorological and hydrological drought severity and intensity over the catchment were evaluated. The Standardized Precipitation Index (SPI) was used to analyse the meteorological drought and the Standardized Runoff Index (SRI) was used for the hydrological drought. Second, the water deficit in the catchment during the drought period was computed using a simple water balance method. Finally, a groundwater model was constructed in order to assess the feasibility of using groundwater as an emergency source for drought impact mitigation. Results show that the low-rainfall areas are more vulnerable to severe meteorological droughts (lower and upper crocodile). Moreover, the most water stressed sub-catchments with high level of water uses but limited storage, such as the Kaap located in the middle catchment and the Lower Crocodile sub-catchments, are more vulnerable to severe hydrological droughts. The analysis of the potential groundwater use during droughts showed that a deficit of 97 Mm3 yr-1 could be supplied from groundwater without considerable adverse impacts on the river base flow and groundwater storage. Abstraction simulations for different scenarios of extremely severe droughts reveal that it is possible to use groundwater to cope with the droughts in the catchment. However, local groundwater exploitation in Nelspruit and White River sub-catchment will cause large drawdowns (> 10 m) and high base flow reduction (> 20%). This case study shows that conjunctive water management of groundwater and surface water resources is necessary to mitigate the impacts of droughts.

The European 2015 drought from a groundwater perspective

NASA Astrophysics Data System (ADS)

Van Loon, Anne; Kumar, Rohini; Mishra, Vimal

2017-04-01

In 2015 central and eastern Europe were affected by severe drought. Impacts of the drought were felt across many sectors, incl. agriculture, drinking water supply, electricity production, navigation, fisheries, and recreation. This drought event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater drought has been performed. This is not surprising because real-time groundwater level observations often are not available. In this study we use previously established spatially-explicit relationships between meteorological drought and groundwater drought to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. We also tested the applicability of the Gravity Recovery Climate Experiment (GRACE) Terrestrial Water Storage (TWS) and GRACE-based groundwater anomalies to capture the spatial variability of the 2003 and 2015 drought events. We use the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardized Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.250 gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on these optimal accumulation periods, we found that in Germany a uniform severe groundwater drought persisted for several months (i.e. SGI below the drought threshold of 20th percentile for almost all grid cells in August, September and October 2015), whereas the Netherlands appeared to have relatively high groundwater levels (never below the drought threshold of 20th percentile). The differences between this event and the European 2003 benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany, with the regional averaged SGI above the 50th percentile. This is because slowly responding wells still were above average from the wet year of 2002-2003, which experienced severe flooding in central Europe. GRACE-TWS does show that both 2003 and 2015 were relatively dry, but the difference between Germany and the Netherlands in 2015 and the spatially-variable groundwater drought pattern in 2003 were not captured. This could be associated to the coarse spatial scale of GRACE. The simulated groundwater anomalies based on GRACE-TWS deviated considerably from the GRACE-TWS signal and from observed groundwater anomalies. These are therefore not suitable for use in real-time groundwater drought monitoring in our case study regions. Our study shows that the relationship between meteorological drought and groundwater drought can be used to quantify groundwater drought and that the 2015 groundwater drought in southern Germany was more severe than the 2003 drought, because of preconditions in slowly responding groundwater wells. For sustainable groundwater drought management strategies the use of groundwater level monitoring is needed to study the spatial variability of local groundwater drought, which mostly coincides with drought impacts.

Exploring the Appropriate Drought Index in a Humid Tropical Area with Complex Terrain

NASA Astrophysics Data System (ADS)

Lee, C. H.; Chen, W. T.; Lo, M. H.; Chu, J. L.; Chen, Y. J.; Chen, Y. M.

2017-12-01

The goal of the present study is to identify the most appropriate index to monitor droughts in Taiwan, an extremely humid region with steep terrain. Three drought indices were calculated using in situ high resolution rainfall observations and compared: the Standardized Precipitation Index (SPI), the self-calibrating Palmer Drought Severity Index (sc-PDSI), and the Standardized Precipitation Evapotranspiration Index (SPEI). In Taiwan, the average amount of precipitation is around 2500 mm per year, which is six times of the global average. However, with the complexity of topography and the uneven distribution throughout the year in Taiwan, abundant rainfall during the wet season is mostly lost as runoff. Severe droughts occur frequently at approximately once per decade, while moderate droughts occur every 2 years. Earlier studies indicated that the SPI is limited in describing drought events because the temperature effect is not taken into account in SPI as in the sc-PDSI. In addition, SPEI, which take the Penman-Monteith Potential Evapotranspiration (PET_pm) into account, is also considered in the present study. The atmospheric water demand increases as temperature increasing, which is reflected in PET_pm. To calculate the three drought indices, we will use the monthly average temperature to calculate the PET_pm and monthly accumulated precipitation from automatic weather stations from the Central Weather Bureau. All of the detected droughts are evaluated against the dataset of historical drought records in Taiwan. We explore whether the temperature is an important factor for the occurrence of droughts in Taiwan first. In addition to severe droughts, we expect that SPEI and sc-PDSI can detect more moderate droughts in Taiwan. Second, we survey the performance of three drought indices for the detection of droughts in Taiwan. Because the soil water model used in sc-PDSI doesn't consider the effect of steep terrain, and because SPI only considers the monthly precipitation, we expect SPEI to be the more appropriate index for monitoring drought events in Taiwan.

Variability of runoff-based drought conditions in the conterminous United States

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.; Austin, Samuel H.

2017-01-01

In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.

Proteome Analysis of Date Palm (Phoenix dactylifera L.) under Severe Drought and Salt Stress.

PubMed

El Rabey, Haddad A; Al-Malki, Abdulrahman L; Abulnaja, Khalid O

2016-01-01

Date palm cultivars differently tolerate salinity and drought stress. This study was carried out to study the response of date palm to severe salinity and drought based on leaf proteome analysis. Eighteen-month-old date palm plants were subjected to severe salt (48 g/L NaCl) and drought (82.5 g/L PEG or no irrigation) conditions for one month. Using a protein 2D electrophoresis method, 55 protein spots were analyzed using mass spectrometry. ATP synthase CF1 alpha chains were significantly upregulated under all three stress conditions. Changes in the abundance of RubisCO activase and one of the RubisCO fragments were significant in the same spots only for salt stress and drought stress with no irrigation, and oxygen-evolving enhancer protein 2 was changed in different spots. Transketolase was significantly changed only in drought stress with PEG. The expression of salt and drought stress genes of the chosen protein spots was either overexpressed or downexpressed as revealed by the high or low protein abundance, respectively. In addition, all drought tolerance genes due to no irrigation were downregulated. In conclusion, the proteome analysis of date palm under salinity and drought conditions indicated that both salinity and drought tolerance genes were differentially expressed resulting in high or low protein abundance of the chosen protein spots as a result of exposure to drought and salinity stress condition.

Integrating effective drought index (EDI) and remote sensing derived parameters for agricultural drought assessment and prediction in Bundelkhand region of India

NASA Astrophysics Data System (ADS)

Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.

2014-11-01

Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.

Relationship between drought severity and observed regional yields in the Czech Republic

NASA Astrophysics Data System (ADS)

Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Možný, Martin; Žalud, Zdeněk; Trnka, Miroslav

2015-04-01

Although the Czech Republic is not generally characterized as a drought prone region within European context, drought occurs and is one of the most important climatic extremes in terms of economic damages. Crop production is highly sensitive to soil water availability and the rainfed agriculture almost dominantly prevails in the Czech Republic. Generally we can observe trends towards drier conditions with more often and more severe drought episodes. Based on this, the impact analyzes are very important. The relationship between drought episodes (with various timing and severity) and observed decrease of yields at district level (NUTS4) during the period from 2000 to 2014 was analyzed within submitted study. The observed yields of spring barley, winter wheat and oilseed winter rape from 14 districts were used (210 seasons are included). All districts are positioned within southeastern part of the Czech Republic and represent various agro-climatic conditions. The regressions between various drought indicators (as independent variables) and yields (dependent variable) were established. For this purpose the several drought indicators in monthly time step were derived as spatial average for arable land (each district separately). The difference between precipitation and reference evapotranspiration (ET0), average soil moisture content available for crops up to 40 cm and 100 cm depth, percent of time with soil moisture below 50 % and below 30 % of available soil moisture up to 100 cm depth were used. For reference evapotranspiration (ET0) and soil water estimates SoilClim model was used. This software is the main module used within Drought monitoring system in the Czech Republic (www.intersucho.cz). Within this study SoilClim was used in resolution 500 x 500 meters within grids of arable land. The soil water holding capacity as well as vegetation development was considered. By this way the yield losses due to various drought intensity was identified and compared. In case of extremely dry years (e.g. 2000, 2012, …) yields declines (often devastating) were mostly explained by water balance. Moreover the differences among regions were analyzed in high detail. Based on achieved results could be concluded that SoilClim software is proper tool for quantification of drought impact within yields. The difference between precipitation and ET0 (from April to June) was identified as reasonably robust indicator but also soil water holding capacity consideration is very important. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".

Impacts of European drought events: insights from an international database of text-based reports

NASA Astrophysics Data System (ADS)

Stahl, K.; Kohn, I.; Blauhut, V.; Urquijo, J.; De Stefano, L.; Acacio, V.; Dias, S.; Stagge, J. H.; Tallaksen, L. M.; Kampragou, E.; Van Loon, A. F.; Barker, L. J.; Melsen, L. A.; Bifulco, C.; Musolino, D.; de Carli, A.; Massarutto, A.; Assimacopoulos, D.; Van Lanen, H. A. J.

2015-09-01

Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Assessing and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The data also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and public water supply) and sector-specific impacts in central and northern regions (e.g. on forestry or energy production). As a text-based database, the EDII presents a new challenge for quantitative analysis; however, the EDII provides a new and more comprehensive view on drought impacts. Related studies have already developed statistical techniques to evaluate the link between drought indices and impacts using the EDII. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This data coverage may help drought policy planning at national to international levels.

Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data. [Great Plains

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A. (Principal Investigator)

1978-01-01

The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

Correlation between Annual Corn Crop per Hectare in Croatia and Drought Indices for Zagreb-Gric Observatory

NASA Astrophysics Data System (ADS)

Pandzic, Kreso; Likso, Tanja

2017-04-01

Correlation coefficients between annual corn crop per hectare in Croatia and 9-month Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) for Zagreb - Gric for August are shown as significant. The results indicate that there is also a significant correlation between those drought indices and drought damages. Thus a forecast of the indices for August could be used for estimation e.g. annual corn crop per hectare in Croatia. Better results could be expected if statistical relationship between annual corn crops per hectare will be considered on county level instead the whole Croatia and indices calculated for weather stations for the same county. Effective way for reduction of drought damages is irrigation which need to be significantly improved in future in Croatia

Integrated Mapping of Drought-Impacted Areas in the Sierra-Nevada Foothills Region of California Using Landsat Imagery

NASA Astrophysics Data System (ADS)

Rao, M.

2014-12-01

Drought is a natural disaster with serious implications to environmental, social and economic well-being at local, regional and global scales. In its third year, California's drought condition has seriously impacted not just the agricultural sector, but also the natural resources sector including forestry, wildlife, and fisheries. As of July 15, 2014, the National Weather Service drought monitor shows 81% of California in the category of extreme drought. As future predictions of drought and fire severity become more real in California, there is an increased awareness to pursue innovative and cost-effective solutions that are based on silvicultural treatments and controlled burns to improve forest health and reduce the risk of high-severity wildfires. The main goal of this study is to develop a GIS map of the drought-impacted region of northern and central California using remote sensing data. Specifically, based on a geospatial database for the study region, Landsat imagery in conjunction with field and ancillary data will be analyzed using a combination of supervised and unsupervised classification techniques in addition to spectral indices such as the Modified Perpendicular Drought Index (MPDI). This spectral index basically scales the line perpendicular to the soil line defined in the Red-NIR feature space in conjunction with added information about vegetative fraction derived using NDVI. The image processing will be conducted for two time periods (2001 and 2014) to characterize the severity of the drought. In addition to field data, data collected by state agencies including calforests.org will be used in the classification and accuracy assessment procedures. Visual assessment using high-resolution imagery such as NAIP will be used to further refine the spatial maps. The drought severity maps produced will greatly facilitate site-specific planning efforts aimed at implementing resource management decisions.

Does drought legacy alter the recovery of grassland carbon dynamics from drought?

NASA Astrophysics Data System (ADS)

Bahn, M.; Hasibeder, R.; Fuchslueger, L.; Ingrisch, J.; Ladreiter-Knauss, T.; Lair, G.; Reinthaler, D.; Richter, A.; Kaufmann, R.

2016-12-01

Climate projections suggest an increase in the frequency and the severity of extreme climatic events, such as droughts, with consequences for the carbon cycle and its feedbacks to the climate system. An important implication of increasing drought frequency is that possible legacies of previous droughts may increasingly affect ecosystem responses to new drought events, though this has been rarely tested. Based on a series of severe experimental droughts performed during nine subsequent years on a mountain grassland in the Austrian Alps, we present evidence of effects of drought legacies on the recovery of grassland carbon dynamics from drought and analyse the underlying mechanisms. Both single and recurrent droughts led to increased aboveground productivity during drought recovery relative to control plots, favoring the biomass production and leaf area of grass species more strongly than of forbs. Belowground productivity was significantly increased during recovery. This led to higher total root length, even though specific root length was strongly reduced during recovery, particularly after recurrent drought events. Following rewetting, the temperature dependence of soil respiration was increasingly diminished and the Birch effect declined with progressive recurrence of droughts. This was paralleled by a change in soil aggregate stability and soil porosity in plots repeatedly exposed to drought. Pulse-labelling experiments revealed effects of drought legacy on plant carbon uptake and belowground allocation and altered microbial turnover of recent plant-derived carbon during and after a subsequent drought. Shifts in tissue nitrogen concentration indicate that drought effects on soil nitrogen turnover and availability could play an important role in the recovery of grassland carbon dynamics following both single and recurrent droughts. In conclusion, drought legacies can alter the recovery of grassland carbon dynamics from drought, the effects increasing with increasing drought frequency and involving changes in both plant functional composition and soil structure and processes.

Does drought legacy alter the recovery of grassland carbon dynamics from drought?

NASA Astrophysics Data System (ADS)

Bahn, Michael; Hasibeder, Roland; Fuchslueger, Lucia; Ingrisch, Johannes; Ladreiter-Knauss, Thomas; Lair, Georg; Reinthaler, David; Richter, Andreas; Kaufmann, Rüdiger

2017-04-01

Climate projections suggest an increase in the frequency and the severity of extreme climatic events, such as droughts, with consequences for the carbon cycle and its feedbacks to the climate system. An important implication of increasing drought frequency is that possible legacies of previous droughts may increasingly affect ecosystem responses to new drought events, though this has been rarely tested. Based on a series of severe experimental droughts performed during nine subsequent years on a mountain grassland in the Austrian Alps, we present evidence of effects of drought legacies on the recovery of grassland carbon dynamics from drought and analyse the underlying mechanisms. Both single and recurrent droughts led to increased aboveground productivity during drought recovery relative to control plots, favoring the biomass production and leaf area of grass species more strongly than of forbs. Belowground productivity was significantly increased during recovery. This led to higher total root length, even though specific root length was strongly reduced during recovery, particularly after recurrent drought events. Following rewetting, the temperature dependence of soil respiration was increasingly diminished and the Birch effect declined with progressive recurrence of droughts. This was paralleled by a change in soil aggregate stability and soil porosity in plots repeatedly exposed to drought. Isotopic pulse-labelling experiments revealed effects of drought legacy on plant carbon uptake and belowground allocation and altered microbial turnover of recent plant-derived carbon during and after a subsequent drought. Shifts in tissue nitrogen concentration indicate that drought effects on soil nitrogen turnover and availability could play an important role in the recovery of grassland carbon dynamics following both single and recurrent droughts. In conclusion, drought legacies can alter the recovery of grassland carbon dynamics from drought, the effects increasing with increasing drought frequency and involving changes in both plant functional composition and soil structure and processes.

Global patterns of extreme drought-induced loss in land primary production: Identifying ecological extremes from rain-use efficiency.

PubMed

Du, Ling; Mikle, Nathaniel; Zou, Zhenhua; Huang, Yuanyuan; Shi, Zheng; Jiang, Lifen; McCarthy, Heather R; Liang, Junyi; Luo, Yiqi

2018-07-01

Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. In this study, a novel method based on maximum rain-use efficiency (RUE max ) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001-2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain >70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

Drought events in the Czech Republic: past, present, future

NASA Astrophysics Data System (ADS)

Brázdil, Rudolf; Trnka, Miroslav; Mikšovský, Jiří; Tolasz, Radim; Dobrovolný, Petr; Řezníčková, Ladislava; Dolák, Lukáš

2017-04-01

Droughts are, together with floods, the most important natural extremes in the Czech Republic. In the last c. 20 years even some irregular alternations of years with severe droughts on the one hand (2000, 2003, 2007, 2011-2012, 2014-2015) and severe floods on the other (1997, 1998, 2002, 2005, 2009, 2010, 2013), reflecting greater variability of the water cycle, can be observed. Great attention devoted to the study of past, present and future of droughts in the Czech Republic in a few last years allowed to obtain basic knowledge related to long-term spatial-temporal variability of droughts, combining dendrochronological, documentary and instrumental data, synoptic causes and climate forcings of droughts, case studies of important drought anomalies with significant social-economic consequences (like drought of 1947), impacts of droughts in agriculture, forestry or water management, and future droughts according to model estimates. Basic results obtained are summarised and documented by several typical examples. Such level of drought knowledge became a basis for formulation of the new research project, trying to analyse the climate forcings and triggers involved in the occurrence, course and severity of drought events in the Czech Republic in the context of Central Europe and explanations of their physical mechanisms, based on a 515-year series of drought indices reconstructed from documentary and instrumental data. Presentation of this new project for 2017-2019 is included in the second part of the paper. (This work was supported by Czech Science Foundation, project no. 17-10026S "Drought events in the Czech Republic and their causes".)

Drought variability in six catchments in the UK

NASA Astrophysics Data System (ADS)

Kwok-Pan, Chun; Onof, Christian; Wheater, Howard

2010-05-01

Drought is fundamentally related to consistent low precipitation levels. Changes in global and regional drought patterns are suggested by numerous recent climate change studies. However, most of the climate change adaptation measures are at a catchment scale, and the development of a framework for studying persistence in precipitation is still at an early stage. Two stochastic approaches for modelling drought severity index (DSI) are proposed to investigate possible changes in droughts in six catchments in the UK. They are the autoregressive integrated moving average (ARIMA) and the generalised linear model (GLM) approach. Results of ARIMA modelling show that mean sea level pressure and possibly the North Atlantic Oscillation (NAO) index are important climate variables for short term drought forecasts, whereas relative humidity is not a significant climate variable despite its high correlation with the DSI series. By simulating rainfall series, the generalised linear model (GLM) approach can provide the probability density function of the DSI. GLM simulations indicate that the changes in the 10th and 50th quantiles of drought events are more noticeable than in the 90th extreme droughts. The possibility of extending the GLM approach to support risk-based water management is also discussed.

Drought early warning and risk management in a changing environment

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2011-12-01

Drought has long been recognized as falling into the category of incremental but long-term and cumulative environmental changes, also termed slow-onset or creeping events. These event types would include: air and water quality decline, desertification processes, deforestation and forest fragmentation, loss of biodiversity and habitats, and nitrogen overloading, among others. Climate scientists continue to struggle with recognizing the onset of drought and scientists and policy makers continue to debate the basis (i.e., criteria) for declaring an end to a drought. Risk-based management approaches to drought planning at the national and regional levels have been recommended repeatedly over the years but their prototyping, testing and operational implementation have been limited. This presentation will outline two avenues for disaster risk reduction in the context of drought (1) integrated early warning information systems, and (2) linking disaster risk reduction to climate change adaptation strategies. Adaptation involves not only using operational facilities and infrastructure to cope with the immediate problems but also leaving slack or reserve for coping with multiple stress problems that produce extreme impacts and surprise. Increasing the 'anticipatability' of an event, involves both monitoring of key indicators from appropriate baseline data, and observing early warning signs that assumptions in risk management plans are failing and critical transitions are occurring. Illustrative cases will be drawn from the IPCC Special Report on Managing the Risks of Extreme Events and Disasters (2011), the UN Global Assessment of Disaster Risk Reduction (2011) and implementation activities in which the author has been engaged. Most drought early warning systems have tended to focus on the development and use of physical system indicators and forecasts of trends and thresholds. We show that successful early warning systems that meet expectations of risk management also have explicit foci on (1) integrating physical and social vulnerability indicators across timescales, (2) analytical capacity to generate local scenarios of risk using both analogs and projections, (3) the communication of risk-based information, and (4) the support and governance of a collaborative framework for early warning structures across spatial scales.

Drought assessment by evapotranspiration mapping in Twente

NASA Astrophysics Data System (ADS)

Eden, U.; Timmermans, J.; van der Velde, R.; Su, Z.

2012-04-01

Drought is a reoccurring worldwide problem with impacts ranging from food production to infrastructure. Droughts are different from other natural hazards (floods, hurricanes, and earthquakes) because the effects can only be witnessed slowly and with a time delay. Effects of droughts are diverse, like famine and migration of people. Droughts are caused by natural causes but also by interaction between the natural events and water demand. Not only typical dry regions, like the Horn of Africa, are affected, but even semi-humid environments, like Europe. Temperature rise and precipitation deficit in the summers of 2003 and 2006 caused substantial crop losses in the agricultural sector in the Netherlands. In addition increased river water temperatures and low water levels caused cooling problems for power plants. Heat waves and prolonged absence of precipitation is expected to increase due to climate change. Therefore assessing and monitoring drought in the Netherlands is thus very important. Various drought indices are available to assess the severity, duration and spatial extend of the drought. Some of the commonly indices used are Standardized precipitation index (SPI) and the Palmer Drought Severity Index (PDSI). However each of these indices do not take into account the actual state of the land surface in respect to the dryness. By analysing drought through actual evapotranspiration (ET) estimations from remote sensing this can be circumvented. The severity of the droughts was quantified by ET-mapping from 2003-2010. The assessment was based on the spatial and temporal distribution of ET using the Evapotranspiration Deficit Index (ETDI) drought index. Surface energy fluxes, like ET, were estimated using WACMOS methodology. The input data consisted of remote sensing products like land surface temperature, LAI, and albedo from MODIS; and meteorological data like air-temperature, humidity and wind speed from the European Centre for Medium weather forecast (ECMWF). ETDI was then calculated using the estimated actual ET in combination with reference ET from Penman-Moneith. Investigations on temperature and precipitation anomalies, using SPI, are also included because of their contribution to the droughts. For this precipitation data from ground measurements were used to calculate the SPI for comparison with ETDI. Preliminary results show that SEBS ET from MODIS 1km resolution and ECMWF can be used for estimating ET for Twente region. The ET maps show that evapotranspiration in all years follow a seasonal trend with higher ET during the growing season as compared to other seasons. Investigation into ET shows small spatial variability, and investigation into SPI shows large temporal variability with 2003 and 2006 being very dry years.

An improvement of drought monitoring through the use of a multivariate magnitude index

NASA Astrophysics Data System (ADS)

Real-Rangel, R. A.; Alcocer-Yamanaka, V. H.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.; Ocón-Gutiérrez, A. R.

2017-12-01

In drought monitoring activities it is widely acknowledged that the severity of an event is determined in relation to monthly values of univariate indices of one or more hydrological variables. Normally, these indices are estimated using temporal windows from 1 to 12 months or more to aggregate the effects of deficits in the variable of interest. However, the use of these temporal windows may lead to a misperception of both, the drought event intensity and the timing of its occurrence. In this context, this work presents the implementation of a trivariate drought magnitude index, considering key hydrological variables (e.g., precipitation, soil moisture and runoff) using for this the framework of the Multivariate Standardized Drought Index (MSDI). Despite the popularity and simplicity of the concept of drought magnitude for standardized drought indices, its implementation in drought monitoring and early warning systems has not been reported. This approach has been tested for operational purposes in the recently launched Multivariate Drought Monitor of Mexico (MOSEMM) and the results shows that the inclusion of a Magnitude index facilitates the drought detection and, thus, improves the decision making process for emergency managers.

The Value of Information from a GRACE-Enhanced Drought Severity Index

NASA Astrophysics Data System (ADS)

Kuwayama, Y.; Bernknopf, R.; Macauley, M.; Brookshire, D.; Zaitchik, B. F.; Rodell, M.

2013-12-01

Water storage anomalies derived from the Gravity Recovery and Climate Experiment Data Assimilation System (GRACE-DAS) have been used to enhance the information contained in drought indicators. The potential value of this information is to inform local and regional decisions to improve economic welfare in the face of drought. Based on a characterization of current drought evaluations, a modeling framework has been structured to analyze the contributed value of the Earth observations in the assessment of the onset and duration of droughts and their regional impacts. The analysis focuses on (1) characterizing how GRACE-DAS provides Earth observation information for a drought warning, (2) assessing how a GRACE-DAS-enhanced U.S. Drought Monitor would improve economic outcomes in a region, and (3) applying this enhancement process in a decision framework to illustrate the potential role of GRACE data products in a recent drought and response scenario for a value-of-information (VOI) analysis. The VOI analysis quantifies the relative contribution of enhanced understanding and communication of the societal benefits associated with GRACE Earth observation science. Our emphasis is to illustrate the role of an enhanced National Integrated Drought Information System outlook on three key societal outcomes: effects on particular economic sectors, changes in land management decisions, and reductions in damages to ecosystem services.

Quantifying agricultural drought impacts using soil moisture model and drought indices in South Korea

NASA Astrophysics Data System (ADS)

Nam, W. H.; Bang, N.; Hong, E. M.; Pachepsky, Y. A.; Han, K. H.; Cho, H.; Ok, J.; Hong, S. Y.

2017-12-01

Agricultural drought is defined as a combination of abnormal deficiency of precipitation, increased crop evapotranspiration demands from high-temperature anomalies, and soil moisture deficits during the crop growth period. Soil moisture variability and their spatio-temporal trends is a key component of the hydrological balance, which determines the crop production and drought stresses in the context of agriculture. In 2017, South Korea has identified the extreme drought event, the worst in one hundred years according to the South Korean government. The objective of this study is to quantify agricultural drought impacts using observed and simulated soil moisture, and various drought indices. A soil water balance model is used to simulate the soil water content in the crop root zone under rain-fed (no irrigation) conditions. The model used includes physical process using estimated effective rainfall, infiltration, redistribution in soil water zone, and plant water uptake in the form of actual crop evapotranspiration. Three widely used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Self-Calibrated Palmer Drought Severity Index (SC-PDSI) are compared with the observed and simulated soil moisture in the context of agricultural drought impacts. These results demonstrated that the soil moisture model could be an effective tool to provide improved spatial and temporal drought monitoring for drought policy.

Assessing and mapping drought hazard in Africa and South-Central America with a Meteorological Drought Severity Index

NASA Astrophysics Data System (ADS)

Carrao, Hugo; Barbosa, Paulo; Vogt, Jürgen

2015-04-01

Drought is a recurring extreme climate event characterized by a temporary deficit of precipitation, soil moisture, streamflow, or any combination of the three taking place at the same time. The immediate consequences of short-term (i.e. a few weeks duration) droughts are, for example, a fall in crop production, poor pasture growth and a decline in fodder supplies from crop residues, whereas prolonged water shortages (e.g. of several months or years duration) may, amongst others, lead to a reduction in hydro-electrical power production and an increase of forest fires. As a result, comprehensive drought risk management is nowadays critical for many regions in the world. Examples are many African and South-and Central American countries that strongly depend on rain-fed agriculture for economic development with hydroelectricity and biomass as main sources of energy. Drought risk is the probability of harmful consequences, or expected losses resulting from interactions between drought hazard, i.e. the physical nature of droughts, and the degree to which a population or activity is vulnerable to its effects. As vulnerability to drought is increasing globally and certain tasks, such as distributive policies (e.g. relief aid, regulatory exemptions, or preparedness investments), require information on drought severity that is comparable across different climatic regions, greater attention has recently been directed to the development of methods for a standardized quantification of drought hazard. In this study we, therefore, concentrate on a methodology for assessing the severity of historical droughts and on mapping the frequency of their occurrence. To achieve these goals, we use a new Meteorological Drought Severity Index (MDSI). The motivation is twofold: 1) the observation that primitive indices of drought severity directly measure local precipitation shortages and cannot be compared geographically; and that 2) standardized indices of drought do not take into account the intra-annual variability of precipitation in estimating the severity of events that can impact on seasonal activities. The MDSI is standardized in space and time, and considers the relative monthly precipitation deficits and the seasonal influence of precipitation regimes in the meteorological drought severity computation. In this study, the calculation of the MDSI is performed with monthly precipitation totals from the Full Data Reanalysis Monthly Product Version 6.0 of the Global Precipitation Climatology Centre (GPCC). This dataset provides a global analysis at 0.5 dd latitude/longitude grid spacing of monthly precipitation over land from operational in situ rain gauges collected between January 1901 and December 2010. Using the MDSI, we estimated the severity of drought events that occurred in the past 100 years in Africa and South-Central America, and produced drought hazard maps based on the probability of exceedance the median historical severity. Overall, results indicate that drought hazard is high for semiarid areas, such as Northeastern and Southern South America, as well as Eastern and Southwestern Africa. Since available water resources in semiarid areas are already insufficient to permanently meet the demands of human activities, the outcomes highlight the aggravated risk for food security and confirm the need for the implementation of disaster mitigation measures in those regions.

Drought Persistence Errors in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

2018-04-01

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China

NASA Astrophysics Data System (ADS)

Xu, Lei; Chen, Nengcheng; Zhang, Xiang

2018-02-01

Drought is an extreme natural disaster that can lead to huge socioeconomic losses. Drought prediction ahead of months is helpful for early drought warning and preparations. In this study, we developed a statistical model, two weighted dynamic models and a statistical-dynamic (hybrid) model for 1-6 month lead drought prediction in China. Specifically, statistical component refers to climate signals weighting by support vector regression (SVR), dynamic components consist of the ensemble mean (EM) and Bayesian model averaging (BMA) of the North American Multi-Model Ensemble (NMME) climatic models, and the hybrid part denotes a combination of statistical and dynamic components by assigning weights based on their historical performances. The results indicate that the statistical and hybrid models show better rainfall predictions than NMME-EM and NMME-BMA models, which have good predictability only in southern China. In the 2011 China winter-spring drought event, the statistical model well predicted the spatial extent and severity of drought nationwide, although the severity was underestimated in the mid-lower reaches of Yangtze River (MLRYR) region. The NMME-EM and NMME-BMA models largely overestimated rainfall in northern and western China in 2011 drought. In the 2013 China summer drought, the NMME-EM model forecasted the drought extent and severity in eastern China well, while the statistical and hybrid models falsely detected negative precipitation anomaly (NPA) in some areas. Model ensembles such as multiple statistical approaches, multiple dynamic models or multiple hybrid models for drought predictions were highlighted. These conclusions may be helpful for drought prediction and early drought warnings in China.

Coping with drought: A High Resolution Drought Monitoring and Prediction System for the Pacific Northwest

NASA Astrophysics Data System (ADS)

Xiao, M.; Nijssen, B.; Shukla, S.; Lettenmaier, D. P.

2013-12-01

The Pacific Northwest (PNW) region in North America (defined here as the Columbia and Klamath River basins plus the coastal drainages) is a diverse geographic region with complex topography and a variety of climates. Agriculture (dryland and irrigated), forestry, fisheries, and hydropower provide significant economic benefit to the region and are directly dependent on the availability of sufficient water at the right time. Additional demands are made on water supplies by recreation, ecosystem services and emerging needs such as hydropower generation in support of wind energy integration. Several major droughts have occurred over the region in recent decades (notably 1977, 2001, and 2004), which have had significant consequences for the region's agricultural, hydropower production, and environment. An emerging need for the region is the coordination of existing regional climate activities, including a better awareness of the current water availability conditions across the region. The University of Washington has operated a surface water monitor for the continental United States since 2005, which provides near real-time estimates of surface water conditions at a spatial resolution of 1/2 degree in terms of soil moisture, snow water equivalent, and total moisture based on a suite of land surface models. A higher resolution Drought Monitoring and Prediction System (DMPS) for Washington State was originally implemented at 1/8 degree and later increased to 1/16 degree. This presentation describes the extension of this system to the entire PNW region at 1/16 degree. The expanded system provides daily updates of three primary drought-related indices based on near real-time station observations in the region: Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Soil Moisture Percentiles (SMP). To make the drought measures relevant to water managers, surface water conditions are not only reported on a gridded map, but watershed-level drought summary indices are reported for larger aggregates such as the Water Resource Inventory Areas (WRIAs) in Washington State and the Water Allocation Basins (WABs) within Oregon. We explore the ability of the system to reproduce historic droughts for the period since 1915 and analyze regional differences in drought dynamics within the PNW. We also evaluate the lead time that would have been provided by the system had it been available relative to official drought declarations.

Groundwater as an emergency source for drought mitigation in the Crocodile River catchment, South Africa

NASA Astrophysics Data System (ADS)

Mussá, F. E. F.; Zhou, Y.; Maskey, S.; Masih, I.; Uhlenbrook, S.

2014-03-01

Global climate change has received much attention worldwide in the scientific as well as in the political community, indicating that changes in precipitation, extreme droughts and floods may threaten increasingly many regions. Drought is a natural phenomenon that may cause social, economical and environmental damages to the society. In this study, we assess the drought intensity and severity and the groundwater potential to be used as a supplement source of water to mitigate drought impacts in the Crocodile River catchment, a water-stressed sub-catchment of the Incomati River catchment in South Africa. The research methodology consists mainly of three parts. First, the spatial and temporal variation of the meteorological and hydrological drought severity and intensity over the catchment were evaluated. The Standardized Precipitation Index (SPI) was used to analyse the meteorological drought and the Standardized Runoff Index (SRI) was used for the hydrological drought. Second, the water deficit in the catchment during the drought period was computed using a simple water balance method. Finally, a groundwater model was constructed in order to assess the feasibility of using groundwater as an emergency source for drought impact mitigation. Results show that the meteorological drought severity varies accordingly with the precipitation; the low rainfall areas are more vulnerable to severe meteorological droughts (lower and upper crocodile). Moreover, the most water stressed sub-catchments with high level of water uses but limited storage, such as the Kaap located in the middle catchment and the Lower Crocodile sub-catchments are those which are more vulnerable to severe hydrological droughts. The analysis of the potential groundwater use during droughts showed that a deficit of 97 Mm3 yr-1 could be supplied from groundwater without considerable adverse impacts on the river base flow and groundwater storage. Abstraction simulations for different scenarios of extremely severe droughts reveal that it is possible to use groundwater to cope with the droughts in the catchment. However, local groundwater exploitation in Nelspruit and White River sub-catchment will cause large drawdowns (> 10 m) and high base flow reduction (> 20%). This case study shows that conjunctive water management of groundwater and surface water resources is the necessary to mitigate the impacts of droughts.

Historical drought patterns over Canada and their teleconnections with large-scale climate signals

NASA Astrophysics Data System (ADS)

Asong, Zilefac Elvis; Wheater, Howard Simon; Bonsal, Barrie; Razavi, Saman; Kurkute, Sopan

2018-06-01

Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950-2013. The Mann-Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified - the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific-North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

Evaluation of meteorological drought indices for streamflow modeling

NASA Astrophysics Data System (ADS)

Haslinger, Klaus; Koffler, Daniel; Blöschl, Günter; Parajka, Juraj; Schöner, Wolfgang; Laaha, Gregor

2013-04-01

In this paper we present a comprehensive analysis which aims to link various meteorological drought indices to streamflow data in Austria and Central Europe. The motivation arises from the fact that discharge time series are usually shorter (beginning in the middle of the 20th century) than meteorological time series. In the European Greater Alpine Region we are fortunate of having a gridded dataset for temperature and solid/liquid precipitation on a monthly time scale that spans from 1801 to 2003 - the HISTALP database. If there is a link between meteorological drought indices and streamflow, a reconstruction of streamflow, with emphasis on low flows, will be possible for the last 200 years. As meteorological drought indices the self-calibrating Palmer Drought Severity Index (scPDSI), the Standardized Precipitation Index (SPI) on various time scales as well as the moisture departure value d from the soil moisture modeling procedure of the scPDSI are used. The analysis focuses on three aspects, (i) temporal co-evolution of meteorological drought and streamflow indices, (ii) their at-site correlation at gauges, and (iii) their regional correlation structure depending on different climate and catchment conditions. The whole analysis is stratified by seasons, what allows us to explore the strength of the link for the dominant low flow generating process. In order to show a connection between these indices and streamflow data the drought event of 2003 serves as a reference. We will show the temporal evolution of the drought indices parallel to streamflow indices like MQ, Q95 and MAM(7) for the period from summer 2002, which encompasses a major flood event in the northern parts of Austria, to fall 2003 when the streamflow drought was most severe. This is carried out for different regions in Austria, representing different climatic and soil-specific characteristics. To quantify the link between drought indices and streamflow indices for the whole time series from 1801-2003, rank correlations are calculated, stratified by three different approaches. First, as mentioned above, a regional assessment is carried out. Second, the correlations are calculated separately for seasons (DJF, MAM, JJA, and SON). Third, different quantiles of the streamflow-data, ranging from Q50 to Q95, will be correlated with the drought indices. The results show that there is definitely a strong connection between the MQ and the scPDSI in one target region in the Northwest of Austria. The results are encouraging for further attempts to reconstruct extreme low flow events from meteorological data only. A statistical model for linking meteorological drought indices with streamflow under dry conditions is currently under development and results will be presented in the near future.

Resilience of coastal wetlands to extreme hydrologicevents in Apalachicola Bay

NASA Astrophysics Data System (ADS)

Medeiros, S. C.; Singh, A.; Tahsin, S.

2017-12-01

Extreme hydrologic events such as hurricanes and droughts continuously threaten wetlands which provide key ecosystem services in coastal areas. The recovery time for vegetation after impact fromthese extreme events can be highly variable depending on the hazard type and intensity. Apalachicola Bay in Florida is home to a rich variety of saltwater and freshwater wetlands and is subject to a wide rangeof hydrologic hazards. Using spatiotemporal changes in Landsat-based empirical vegetation indices, we investigate the impact of hurricane and drought on both freshwater and saltwater wetlands from year 2000to 2015 in Apalachicola Bay. Our results indicate that saltwater wetlands are more resilient than freshwater wetlands and suggest that in response to hurricanes, the coastal wetlands took almost a year to recover,while recovery following a drought period was observed after only a month.

Resilience of coastal wetlands to extreme hydrologic events in Apalachicola Bay

NASA Astrophysics Data System (ADS)

Tahsin, Subrina; Medeiros, Stephen C.; Singh, Arvind

2016-07-01

Extreme hydrologic events such as hurricanes and droughts continuously threaten wetlands which provide key ecosystem services in coastal areas. The recovery time for vegetation after impact from these extreme events can be highly variable depending on the hazard type and intensity. Apalachicola Bay in Florida is home to a rich variety of saltwater and freshwater wetlands and is subject to a wide range of hydrologic hazards. Using spatiotemporal changes in Landsat-based empirical vegetation indices, we investigate the impact of hurricane and drought on both freshwater and saltwater wetlands from year 2000 to 2015 in Apalachicola Bay. Our results indicate that saltwater wetlands are more resilient than freshwater wetlands and suggest that in response to hurricanes, the coastal wetlands took almost a year to recover, while recovery following a drought period was observed after only a month.

Geospatial approach for assessment of biophysical vulnerability to agricultural drought and its intra-seasonal variations.

PubMed

Sehgal, Vinay Kumar; Dhakar, Rajkumar

2016-03-01

The study presents a methodology to assess and map agricultural drought vulnerability during main kharif crop season at local scale and compare its intra-seasonal variations. A conceptual model of vulnerability based on variables of exposure, sensitivity, and adaptive capacity was adopted, and spatial datasets of key biophysical factors contributing to vulnerability were generated using remote sensing and GIS for Rajasthan State of India. Hazard exposure was based on frequency and intensity of gridded standardized precipitation index (SPI). Agricultural sensitivity was based on soil water holding capacity as well as on frequency and intensity of normalized difference vegetation index (NDVI)-derived trend adjusted vegetation condition index (VCITadj). Percent irrigated area was used as a measure of adaptive capacity. Agricultural drought vulnerability was derived separately for early, mid, late, and whole kharif seasons by composting rating of factors using linear weighting scheme and pairwise comparison of multi-criteria evaluation. The regions showing very low to extreme rating of hazard exposure, drought sensitivity, and agricultural vulnerability were identified at all four time scales. The results indicate that high to extreme vulnerability occurs in more than 50% of net sown area in the state and such areas mostly occur in western, central, and southern parts. The higher vulnerability is on account of non-irrigated croplands, moderate to low water holding capacity of sandy soils, resulting in higher sensitivity, and located in regions with high probability of rainfall deficiency. The mid and late season vulnerability has been found to be much higher than that during early and whole season. Significant correlation of vulnerability rating with food grain productivity, drought recurrence period, crop area damaged in year 2009 and socioeconomic indicator of human development index (HDI) proves the general soundness of methodology. Replication of this methodology in other areas is expected to lead to better preparedness and mitigation-oriented management of droughts.

Drought evaluation using the GRACE terrestrial water storage deficit over the Yangtze River Basin, China.

PubMed

Sun, Zhangli; Zhu, Xiufang; Pan, Yaozhong; Zhang, Jinshui; Liu, Xianfeng

2018-09-01

Droughts are some of the worst natural disasters that bring significant water shortages, economic losses, and adverse social consequences. Gravity Recovery and Climate Experiment (GRACE) satellite data are widely used to characterize and evaluate droughts. In this work, we evaluate drought situations in the Yangtze River Basin (YRB) using the GRACE Texas Center for Space Research (CSR) mascon (mass concentration) data from 2003 to 2015. Drought events are identified by water storage deficits (WSDs) derived from GRACE data, while the drought severity evaluation is based on the water storage deficit index (WSDI), standardized WSD time series, and total water storage deficit (TWSD). The WSDI is subsequently compared with the Palmer drought severity index (PDSI), standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and standardized runoff index (SRI). The results indicate the YRB experienced increased wetness during the study period, with WSD values increasing at a rate of 5.20mm/year. Eight drought events are identified, and three major droughts occurred in 2004, 2006, and 2011, with WSDIs of -2.05, -2.38, and -1.30 and TWSDs of -620.96mm, -616.81mm, and -192.44mm, respectively. Our findings suggest that GRACE CSR mascon data can be used effectively to assess drought features in the YRB and that the WSDI facilitates robust and reliable characterization of droughts over large-scale areas. Copyright © 2018 Elsevier B.V. All rights reserved.

High-Throughput Phenotyping to Detect Drought Tolerance QTL in Wild Barley Introgression Lines

PubMed Central

Honsdorf, Nora; March, Timothy John; Berger, Bettina; Tester, Mark; Pillen, Klaus

2014-01-01

Drought is one of the most severe stresses, endangering crop yields worldwide. In order to select drought tolerant genotypes, access to exotic germplasm and efficient phenotyping protocols are needed. In this study the high-throughput phenotyping platform “The Plant Accelerator”, Adelaide, Australia, was used to screen a set of 47 juvenile (six week old) wild barley introgression lines (S42ILs) for drought stress responses. The kinetics of growth development was evaluated under early drought stress and well watered treatments. High correlation (r = 0.98) between image based biomass estimates and actual biomass was demonstrated, and the suitability of the system to accurately and non-destructively estimate biomass was validated. Subsequently, quantitative trait loci (QTL) were located, which contributed to the genetic control of growth under drought stress. In total, 44 QTL for eleven out of 14 investigated traits were mapped, which for example controlled growth rate and water use efficiency. The correspondence of those QTL with QTL previously identified in field trials is shown. For instance, six out of eight QTL controlling plant height were also found in previous field and glasshouse studies with the same introgression lines. This indicates that phenotyping juvenile plants may assist in predicting adult plant performance. In addition, favorable wild barley alleles for growth and biomass parameters were detected, for instance, a QTL that increased biomass by approximately 36%. In particular, introgression line S42IL-121 revealed improved growth under drought stress compared to the control Scarlett. The introgression line showed a similar behavior in previous field experiments, indicating that S42IL-121 may be an attractive donor for breeding of drought tolerant barley cultivars. PMID:24823485

Impacts of Water Stress on Forest Recovery and Its Interaction with Canopy Height.

PubMed

Xu, Peipei; Zhou, Tao; Yi, Chuixiang; Luo, Hui; Zhao, Xiang; Fang, Wei; Gao, Shan; Liu, Xia

2018-06-13

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI > 0.85), no significant difference in the recovery was found between short and tall trees ( p > 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management.

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Diverse responses of different structured forest to drought in Southwest China through remotely sensed data

NASA Astrophysics Data System (ADS)

Xu, Peipei; Zhou, Tao; Zhao, Xiang; Luo, Hui; Gao, Shan; Li, Zheng; Cao, Leyao

2018-07-01

Global climate change leads to gradual increases in the frequency, intensity, and duration of extreme drought events. Human activities such as afforestation and deforestation have led to spatial variation in forest structure, causing forests to exhibit an age-spatial structure relationship. Thus, it is of great importance to accurately evaluate the effects of drought stress on forest ecosystems with different forest age structures. Because the spatial heterogeneity varies with drought stress intensity, forest age, there are still a lot of uncertainties in current studies. In this study, based on the field measurement, and the proxy index of stand age (based on forest canopy height from LiDAR and stock volume from inventory) at the regional scale, we analyzed the different drought responses of forest ecosystems with various forest ages across different scales in Yunnan province, southwest China from 2001 to 2014. At the local scale, significant differences in the effects of drought stress were found among forests with various ages, suggesting that older forests suffer more under drought stress than younger forests. At the regional scale, the investigation statistics of forest damage indicated a maximum damage ratio in the forest with tall trees (>32 m), whereas damage was minimal in the forest with short trees (<25 m). The stock volume of the forest exhibited the same pattern, that is, the forest damage ratio increased as the stock volume increased. These data demonstrate that the responses of forest drought could be affected by forest age. Under drought stress, older forests show greater vulnerability and risk of damage, which will require special attention for forest managers, as well as improved risk assessments, in the context of future climate change.

The hydrological vulnerability of western North American boreal tree species based on ground-based observations of tree mortality

NASA Astrophysics Data System (ADS)

Hember, R. A.; Kurz, W. A.; Coops, N. C.

2017-12-01

Several studies indicate that climate change has increased rates of tree mortality, adversely affecting timber supply and carbon storage in western North American boreal forests. Statistical models of tree mortality can play a complimentary role in detecting and diagnosing forest change. Yet, such models struggle to address real-world complexity, including expectations that hydrological vulnerability arises from both drought stress and excess-water stress, and that these effects vary by species, tree size, and competitive status. Here, we describe models that predict annual probability of tree mortality (Pm) of common boreal tree species based on tree height (H), biomass of larger trees (BLT), soil water content (W), reference evapotranspiration (E), and two-way interactions. We show that interactions among H and hydrological variables are consistently significant. Vulnerability to extreme droughts consistently increases as H approaches maximum observed values of each species, while some species additionally show increasing vulnerability at low H. Some species additionally show increasing vulnerability to low W under high BLT, or increasing drought vulnerability under low BLT. These results suggest that vulnerability of trees to increasingly severe droughts depends on the hydraulic efficiency, competitive status, and microclimate of individual trees. Static simulations of Pm across a 1-km grid (i.e., with time-independent inputs of H, BLT, and species composition) indicate complex spatial patterns in the time trends during 1965-2014 and a mean change in Pm of 42 %. Lastly, we discuss how the size-dependence of hydrological vulnerability, in concert with increasingly severe drought events, may shape future responses of stand-level biomass production to continued warming and increasing carbon dioxide concentration in the region.

A nonparametric multivariate standardized drought index for characterizing socioeconomic drought: A case study in the Heihe River Basin

NASA Astrophysics Data System (ADS)

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong; Liu, Saiyan

2016-11-01

Among various drought types, socioeconomic drought is the least investigated type of droughts. Most existing drought indicators ignore the role of local reservoirs and water demand in coping with climatic extremes. In this study, a Multivariate Standardized Reliability and Resilience Index (MSRRI) combining inflow-demand reliability index (IDR) and water storage resilience index (WSR) was applied to examine the evolution characteristics of the socioeconomic droughts in the Heihe River Basin, the second largest inland river basin in northwestern China. Furthermore, the cross wavelet analysis was adopted to explore the associations between annual MSRRI series and El Niño Southern Oscillation (ENSO)/Atlantic Oscillation (AO). Results indicated that: (1) the developed MSRRI is more sensitive to the onset and termination of socioeconomic droughts than IDR and WSR, owing to its joint distribution function of IDR and WSR, responding to changes in either or both of the indices; (2) the MSRRI series in the Heihe River Basin shows non-significant trends at both monthly and annual scales; (3) both ENSO and AO contribute to the changes in the socioeconomic droughts in the Heihe River Basin, and the impacts of ENSO on the socioeconomic droughts are stronger than those of AO.

Enhanced agricultural drought monitoring using a soil water anomaly-based drought index in south-west India

NASA Astrophysics Data System (ADS)

Hochstöger, Simon; Pfeil, Isabella; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

2017-04-01

In India, agriculture accounts for roughly 17% of the GDP and employs around 50% of the total workforce. Especially in the western part of India, most of the agricultural fields are non-irrigated. Hence, agriculture is highly dependent on the monsoon in these areas. However, the absence of rainfall during the monsoon season increases the occurrence of drought periods, which is the main environmental factor affecting agricultural productivity. Rainfall is often not accessible to plants due to runoff or increased rates of evapotranspiration. Therefore, knowledge of the soil moisture state in the root zone of the soil is of great interest in the field of agricultural drought monitoring and operational decision-support. By introducing soil moisture, retrieved via active or passive microwave remote sensors, the gap between rainfall and the subsequent response of vegetation can be closed. Agricultural droughts are strongly influenced by a lack of water availability in the root zone of the soil, making anomalies of the Advanced Scatterometer (ASCAT) soil water index (SWI), representing the water content in lower soil layers, a suitable measure to estimate the water deficit in the soil. These anomalies describe the difference of the actual soil moisture value to the long-term average calculated for the same period. The objective of the study is to investigate the usability of soil moisture anomalies for developing an indicator that is based on critical thresholds, which finally results in a classification with different drought severity levels. In order to evaluate the performance of the drought index, it is compared to the Integrated Drought Severity Index (IDSI), which is developed at the International Water Management Institute in Colombo, Sri Lanka and to rainfall data from the Indian Meteorological Department (IMD). Overall, first analyses show a high potential of using SWI anomalies for agricultural drought monitoring. Most of the drought events detected by negative SWI anomalies correspond to IDSI drought events and also to reduced precipitation during that time.

Analysis of Drought in North Darfur Region of Sudan: Application of the DPSIR Framework on Long Term Data

NASA Astrophysics Data System (ADS)

Mohmmed, Alnail; Zhange, Ke; Makomere, Reuben; Twecan, Dalson; Mohamme, Mustafa

2017-04-01

Darfur region in western Sudan is located in one of the world's most inhospitable environments, adjacent to the Sahara desert, conflicts and drought have severely degraded this fragile area, devastating the environment, livestock and people. Northern Darfur is bedeviled with frequent drought due to insufficient water resources, high summer temperatures, and poor precipitation. Monitoring drought and providing timely seasonal predictions is important for integrated drought risk reduction in the region. This paper evaluates drought conditions in North Darfur by applying meteorological, remote sensing and crop production data, as well as the Driving force-Pressure-State-Impacts-Response (DPSIR) assessment framework. Interviews, group discussions and participant observations were conducted in order to understand the DPSIR framework indicators. The relationship between the Reconnaissance Drought Index (RDI), Vegetation Condition Index (VCI) and Soil Moisture Content Index (SMCI) were evaluated utilizing data from all five North Darfur counties during 10 growing seasons (2004-2013). Our results showed a strong correlation between RDI, VCI, and SMAI. Also, a significant agreement was noticed between Yield Anomaly Index (YAI) and Rainfall Anomaly Index (RAI). Generally, a high correlation coefficient was obtained between the meteorology drought index and remote sensing indices, which demonstrates the effectiveness of the above indices for evaluating agricultural drought in the sub-Saharan area. Keywords: Drought; Vegetation Condition Index; Reconnaissance Drought Index; Soil Moisture Content Index; North Darfur.

Stem girdling indicates prioritized carbon allocation to the root system at the expense of radial stem growth in Norway spruce under drought conditions

PubMed Central

Oberhuber, Walter; Gruber, Andreas; Lethaus, Gina; Winkler, Andrea; Wieser, Gerhard

2017-01-01

The early culmination of maximum radial growth (RG) in late spring has been found in several coniferous species in a dry inner Alpine environment. We hypothesized that an early decrease in RG is an adaptation to cope with drought stress, which might require an early switch of carbon (C) allocation to belowground organs. To test this hypothesis, we experimentally subjected six-year-old Norway spruce saplings (tree height: 1.35 m; n = 80 trees) to two levels of soil water availability (watered versus drought conditions) and manipulated tree C status by physically blocking phloem transport at three girdling dates (GD). The influence of C availability and drought on tree growth (radial and shoot growth; root biomass) in response to girdling was analyzed in both treatments. Non-structural carbohydrates (NSCs, soluble sugars and starch) were measured in the stem, root and current leader to evaluate changes in tree C status due to girdling. The main finding was a significant increase in RG of the girdled trees compared to the controls above the girdling zone (UZ). At all girdling dates the RG increase was significantly more intense in the drought-stressed compared with watered trees (c. 3.3 and 1.9-fold higher compared with controls in the drought-stressed and watered trees, respectively), most likely indicating that an early switch of C allocation to belowground occurs as an adaptation to maintain tree water status under drought conditions. Reactivation of the cambium after the cessation of its regular activity was detected in UZ in drought-stressed trees, while below the girdling zone no xylem formation was found and the NSC content was strikingly reduced. Irrespective of water availability, girdling before growth onset significantly reduced the progression of bud break (P < 0.05) and the length of the current leader shoot by −47% (P < 0.01) indicating a reduction in xylem hydraulic conductance, which was corroborated by significantly reduced xylem sap flow (P < 0.001). Based on our findings, we conclude that during the growing season drought stress prioritizes an early switch of C allocation to the root system as an adaptation to maintain adequate tree water status in drought-prone environments. PMID:28392608

The relationship of large fire occurrence with drought and fire danger indices in the western USA, 1984-2008: The role of temporal scale

Treesearch

Karin L. Riley; John T. Abatzoglou; Isaac C. Grenfell; Anna E. Klene; Faith Ann Heinsch

2013-01-01

The relationship between large fire occurrence and drought has important implications for fire prediction under current and future climates. This study’s primary objective was to evaluate correlations between drought and fire-danger- rating indices representing short- and long-term drought, to determine which had the strongest relationships with large fire occurrence...

A first look at global flash drought: long term change and short term predictability

NASA Astrophysics Data System (ADS)

Yuan, Xing; Wang, Linying; Ji, Peng

2017-04-01

"Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term predictability of flash drought via a perfect model assumption.

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

NASA Astrophysics Data System (ADS)

Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2014-05-01

By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal forecasting tool on a monthly basis from April till October each year. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential for seasonal agrometeorological drought. Key words: agrometeorological drought, risk identification, remote sensing.

Changes in grassland plant composition explain 2011 drought-triggered legacy effects

NASA Astrophysics Data System (ADS)

Xu, X.; Polley, W.; Hofmockel, K. S.; Wilsey, B. J.

2016-12-01

There is widespread recognition that extreme droughts can have profound direct consequences for terrestrial ecosystems, but it is poorly known how common drought legacies are and what ecological factors are associated with them. Legacies are found when ecosystem functioning is below what is expected based on precipitation levels in the time period after a perturbation has ended. Here, we tested for legacies after an extreme drought in pure native and exotic experimental communities in central Texas in a long-term experiment. An extreme drought in 2011 decreased aboveground biomass (AGB) by 92 % and triggered species reorganization that led to a drought legacy in rain-use efficiency (RUE, biomass production per unit of rainfall) that lasted an average of 20 months and 48 months in exotic and native communities, respectively. Across plots within community types, reductions in RUE (DRUE) were smallest in native communities with a high proportion of C3 forb biomass and in exotic communities with a low proportion of short grass biomass. Our results indicate that the 2011 drought exerted differential impacts on plant functional groups and altered plant community composition to the extent that, RUE, an ecosystem function, shifted with possible long-term repercussions.

Size-dependence of tree growth response to drought for Norway spruce and European beech individuals in monospecific and mixed-species stands.

PubMed

Ding, H; Pretzsch, H; Schütze, G; Rötzer, T

2017-09-01

Climate anomalies have resulted in changing forest productivity, increasing tree mortality in Central and Southern Europe. This has resulted in more severe and frequent ecological disturbances to forest stands. This study analysed the size-dependence of growth response to drought years based on 384 tree individuals of Norway spruce [Picea abies (L.) Karst.] and European beech [Fagus sylvatica ([L.)] in Bavaria, Germany. Samples were collected in both monospecific and mixed-species stands. To quantify the growth response to drought stress, indices for basal area increment, resistance, recovery and resilience were calculated from tree ring measurements of increment cores. Linear mixed models were developed to estimate the influence of drought periods. The results show that ageing-related growth decline is significant in drought years. Drought resilience and resistance decrease significantly with growth size among Norway spruce individuals. Evidence is also provided for robustness in the resilience capacity of European beech during drought stress. Spruce benefits from species mixing with deciduous beech, with over-yielding spruce in pure stands. The importance of the influence of size-dependence within tree growth studies during disturbances is highlighted and should be considered in future studies of disturbances, including drought. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

Transcriptomic basis for drought-resistance in Brassica napus L.

NASA Astrophysics Data System (ADS)

Wang, Pei; Yang, Cuiling; Chen, Hao; Song, Chunpeng; Zhang, Xiao; Wang, Daojie

2017-01-01

Based on transcriptomic data from four experimental settings with drought-resistant and drought-sensitive cultivars under drought and well-watered conditions, statistical analysis revealed three categories encompassing 169 highly differentially expressed genes (DEGs) in response to drought in Brassica napus L., including 37 drought-resistant cultivar-related genes, 35 drought-sensitive cultivar-related genes and 97 cultivar non-specific ones. We provide evidence that the identified DEGs were fairly uniformly distributed on different chromosomes and their expression patterns are variety specific. Except commonly enriched in response to various stimuli or stresses, different categories of DEGs show specific enrichment in certain biological processes or pathways, which indicated the possibility of functional differences among the three categories. Network analysis revealed relationships among the 169 DEGs, annotated biological processes and pathways. The 169 DEGs can be classified into different functional categories via preferred pathways or biological processes. Some pathways might simultaneously involve a large number of shared DEGs, and these pathways are likely to cross-talk and have overlapping biological functions. Several members of the identified DEGs fit to drought stress signal transduction pathway in Arabidopsis thaliana. Finally, quantitative real-time PCR validations confirmed the reproducibility of the RNA-seq data. These investigations are profitable for the improvement of crop varieties through transgenic engineering.

Pasture Drought Insurance Based on NDVI and SAVI

NASA Astrophysics Data System (ADS)

Escribano Rodríguez, J. A.; Tarquis, A. M.; Hernandez Díaz-Ambrona, C. G.

2012-04-01

Drought is a complex phenomenon, which is difficult to define. The term is used to refer to deficiency in rainfall, soil moisture, vegetation greenness, ecological conditions or socio economic conditions, and different drought types can be inferred. In this study, drought is considered as a period when the pasture growth is low in regard to long-term average conditions. The extensive livestock production is based on the natural resources available. The good management practices concurs the maximum livestock nutrition needs with the maximum pasture availability. Therefore, early drought detection and impact assessment on the amount of pasture biomass are important in several areas in Spain, whose economy strongly depends on livestock production. The use of remote sensing data presents a number of advantages when determining drought impact on vegetation. The information covers the whole of a territory and the repetition of images provides multi-temporal measurements. In addition, vegetation indexes, being NDVI (normalized difference vegetation index) and SAVI (soil-adjusted vegetation index) the most common ones, obtainedfrom satellite data allow areas affected by droughts to be identified. These indices are being used for estimation of vegetation photosynthesis activity and monitoring drought. The present study shows the application of these vegetation indices for pasture drought monitoring in three places in Spain and their correlation with several field measurements. During 2010 and 2011 three locations, El Cubo de Don Sancho (Salamanca), Trujillo (Cáceres) and Pozoblanco (Córdoba), were selected and a periodic pasture monitoring and botanic composition were achieved. Daily precipitation, temperature and monthly soil water content were measurement as well as fresh and dry pasture weight. At the same time, remote sensing images were capture by DEIMOS-1 of the chosen places.This satellite is based on the concept Microsat-100 from Surrey. It is conceived for obtaining Earth images with a good enough resolution to study the terrestrial vegetation cover (20x20 m), although with a great range of visual field (600 km) in order to obtain those images with high temporal resolution and at a reduced cost. It has 6 cameras in red, green and near infrared bands, equivalent to Landsat ones. A discussion on the correlations found between field measurements and both vegetation index considering seasonal pattern and location are presented. Acknowledgements. This work was partially supported by ENESA under project P10 0220C-823. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. AGL2010-21501/AGR is greatly appreciated.

The European Drought Observatory (EDO): Current State and Future Directions

NASA Astrophysics Data System (ADS)

Vogt, Jürgen; Sepulcre, Guadalupe; Magni, Diego; Valentini, Luana; Singleton, Andrew; Micale, Fabio; Barbosa, Paulo

2013-04-01

Europe has repeatedly been affected by droughts, resulting in considerable ecological and economic damage and climate change studies indicate a trend towards increasing climate variability most likely resulting in more frequent drought occurrences also in Europe. Against this background, the European Commission's Joint Research Centre (JRC) is developing methods and tools for assessing, monitoring and forecasting droughts in Europe and develops a European Drought Observatory (EDO) to complement and integrate national activities with a European view. At the core of the European Drought Observatory (EDO) is a portal, including a map server, a metadata catalogue, a media-monitor and analysis tools. The map server presents Europe-wide up-to-date information on the occurrence and severity of droughts, which is complemented by more detailed information provided by regional, national and local observatories through OGC compliant web mapping and web coverage services. In addition, time series of historical maps as well as graphs of the temporal evolution of drought indices for individual grid cells and administrative regions in Europe can be retrieved and analysed. Current work is focusing on validating the available products, developing combined indicators, improving the functionalities, extending the linkage to additional national and regional drought information systems and testing options for medium-range probabilistic drought forecasting across Europe. Longer-term goals include the development of long-range drought forecasting products, the analysis of drought hazard and risk, the monitoring of drought impact and the integration of EDO in a global drought information system. The talk will provide an overview on the development and state of EDO, the different products, and the ways to include a wide range of stakeholders (i.e. European, national river basin, and local authorities) in the development of the system as well as an outlook on the future developments.

Implications of the 2015 European drought on groundwater storage

NASA Astrophysics Data System (ADS)

Rangecroft, S.; Van Loon, A.; Kumar, R.; Mishra, V.

2016-12-01

In 2015 central and eastern Europe were affected by severe drought. Impacts of the drought were felt across many sectors, incl. agriculture, drinking water supply, electricity production, navigation, fisheries, and recreation. This drought event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater (GW) drought has been performed. This is not surprising because real-time GW level observations often are not available. In this study we use previously established spatially-explicit relationships between meteorological drought and GW drought to quantify the 2015 GW drought over two regions in southern Germany and eastern Netherlands. We use the monthly GW observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardized Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.250 gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in GW response time to meteorological input over the region. Based on these optimal accumulation periods, we found that in Germany a uniform severe GW drought persisted for several months (i.e. SGI below the drought threshold of 20th percentile for almost all grid cells in August, September and October 2015), whereas the Netherlands appeared to had relatively high GW levels (never below the drought threshold of 20th percentile). The differences between this event and the European 2003 benchmark drought are striking. The 2003 GW drought was less uniformly pronounced, both in the Netherlands and Germany, with the regional averaged SGI above the 50th percentile. This is because slowly responding wells still were above average from the wet year of 2002-2003, which experienced severe flooding in central Europe. Our study shows that the relationship between meteorological drought and GW drought can be used to quantify GW drought and that the 2015 GW drought in southern Germany was more severe than the 2003 drought, because of preconditions in slowly responding GW wells. For sustainable GW drought management strategies the use of GW level monitoring is needed to study the spatial variability of local GW drought, which mostly coincides with drought impacts.

The Gaussian copula model for the joint deficit index for droughts

NASA Astrophysics Data System (ADS)

Van de Vyver, H.; Van den Bergh, J.

2018-06-01

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.

Co-occurring woody species have diverse hydraulic strategies and mortality rates during an extreme drought: Belowground hydraulic failure during drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Daniel M.; Domec, Jean-Christophe; Carter Berry, Z.

From 2011 to 2013, Texas experienced its worst drought in recorded history. This event provided a unique natural experiment to assess species-specific responses to extreme drought and mortality of four co-occurring woody species: Quercus fusiformis, Diospyros texana, Prosopis glandulosa and Juniperus ashei. We examined hypothesized mechanisms that could promote these species’ diverse mortality patterns using post-drought measurements on surviving trees coupled to retrospective process modeling. The species exhibited a wide range of gas exchange responses, hydraulic strategies, and mortality rates. Multiple proposed indices of mortality mechanisms were not consistent with the observed mortality patterns across species, including measures of iso/anisohydry,more » photosynthesis, carbohydrate depletion, and hydraulic safety margins. Large losses of growing season whole-tree conductance (driven by belowground losses of conductance), and shallower rooting depths, were associated with species that exhibited greater mortality. Based on this retrospective analysis, we suggest that species more vulnerable to drought were more likely to have succumbed to hydraulic failure belowground.« less

The ethylene response factor OsERF109 negatively affects ethylene biosynthesis and drought tolerance in rice.

PubMed

Yu, Yanwen; Yang, Dexin; Zhou, Shirong; Gu, Juntao; Wang, Fengru; Dong, Jingao; Huang, Rongfeng

2017-01-01

Drought is an important factor limiting plant development and crop production. Dissecting the factors involved in this process is the key for enhancement of plant tolerance to drought stress by genetic approach. Here, we evaluated the regulatory function of a novel rice ethylene response factor (ERF) OsERF109 in drought stress. Expression of OsERF109 was rapidly induced by stress and phytohormones. Subcellular localization and transactivation assay demonstrated that OsERF109 was localized in nucleus and possessed transactivation activity. Transgenic plants overexpressing (OE) and knockdown with RNA interfering (RI) OsERF109 exhibited significantly reduced and improved drought resistance, respectively, indicating that OsERF109 negatively regulates drought resistance in rice. Furthermore, measurement by gas chromatography showed that ethylene contents were less in OE while more in RI lines than these in wild types, supporting the data of drought tolerance and water loss in transgenic lines. Quantitative real-time PCR analysis also proved the regulation of OsERF109 in the expression of OSACS6, OSACO2, and OsERF3, which have been identified to play important roles in ethylene biosynthesis. Based on these results, our data evidence that OsERF109 regulates drought resistance by affecting the ethylene biosynthesis in rice. Overall, our study reveals the negative role of OsERF109 in ethylene biosynthesis and drought tolerance in rice.

Drought Assessment over the Four Major River Basins of India using GRACE-based estimates of Water Availability

NASA Astrophysics Data System (ADS)

Sinha, D.; Syed, T. H.

2017-12-01

Drought is a natural disaster that has mutilating consequences over agriculture, ecosystems, economy and the society. Over the past few decades, drought related catastrophe, associated with global climate change, has escalated all across the world. Identification and analysis of drought utilizing individual hydrologic variables may be inadequate owing to the multitude of factors that are associated with the phenomenon. Therefore it is crucial to develop techniques that warrant comprehensive monitoring and assessment of droughts. In this study we propose a novel drought index (Water Availability Index (WAI)) that comprehends all the aspects of meteorologic, agricultural and hydrologic droughts. The proposed framework underscores the conceptualization and utilization of water availability, quantified as an integrated estimate of land water storage, using Gravity Recovery and Climate Experiment (GRACE) observations, and precipitation. The methodology is employed over four major river basins of India (i.e. Ganga, Krishna, Godavari and Mahanadi) for a period of 155 months (April 2002 to February 2015). Results exhibit the potential of the propounded index (WAI) to recognize drought events and impart insightful quantification of drought severity. WAI also demonstrates enhanced outcomes in comparison to other commonly used drought indices like PDSI, SPI, SPEI and SRI. In general there are at least three major drought periods with intensities ranging from moderate to severe in almost all river basins. The longest drought period, extending for 27 months, from September 2008 to November 2010, is observed in the Mahanadi basin. Results from this study confirm the potential of this technique as an effective tool for the characterization of drought at large spatial scales, which will only excel with better quantification and extended availability of terrestrial water storage observations from the GRACE-Follow On mission.

The impact of drought on the association between food security and mental health in a nationally representative Australian sample.

PubMed

Friel, Sharon; Berry, Helen; Dinh, Huong; O'Brien, Léan; Walls, Helen L

2014-10-24

The association between food insecurity and mental health is established. Increasingly, associations between drought and mental health and drought and food insecurity have been observed in a number of countries. The impact of drought on the association between food insecurity and mental health has received little attention. Population-based study using data from a nationally representative panel survey of Australian adults in which participants report behaviour, health, social, economic and demographic information annually. Exposure to drought was modelled using annual rainfall data during Australia's 'Big Dry'. Regression modelling examined associations between drought and three indicative measures of food insecurity and mental health, controlling for confounding factors. People who reported missing meals due to financial stress reported borderline moderate/high distress levels. People who consumed below-average levels of core foods reported more distress than those who consumed above the average level, while people consuming discretionary foods above the average level reported greater distress than those consuming below the threshold. In all drought exposure categories, people missing meals due to cost reported higher psychological distress than those not missing meals. Compared to drought-unadjusted psychological distress levels, in most drought categories, people consuming higher-than-average discretionary food levels reported higher levels of distress. Exposure to drought moderates the association between measures of food insecurity and psychological distress, generally increasing the distress level. Climate adaptation strategies that consider social, nutrition and health impacts are needed.

Variability of hydrological droughts in the conterminous United States, 1951 through 2014

USGS Publications Warehouse

Austin, Samuel H.; Wolock, David M.; Nelms, David L.

2018-02-22

Spatial and temporal variability in the frequency, duration, and severity of hydrological droughts across the conterminous United States (CONUS) was examined using monthly mean streamflow measured at 872 sites from 1951 through 2014. Hydrological drought is identified as starting when streamflow falls below the 20th percentile streamflow value for 3 consecutive months and ending when streamflow remains above the 20th percentile streamflow value for 3 consecutive months. Mean drought frequency for all aggregated ecoregions in CONUS is 16 droughts per 100 years. Mean drought duration is 5 months, and mean drought severity is 39 percent on a scale ranging from 0 percent to 100 percent (with 100% being the most severe). Hydrological drought frequency is highest in the Western Mountains aggregated ecoregion and lowest in the Eastern Highlands, Northeast, and Southeast Plains aggregated ecoregions. Hydrological drought frequencies of 17 or more droughts per 100 years were found for the Central Plains, Southeast Coastal Plains, Western Mountains, and Western Xeric aggregated ecoregions. Drought duration and severity indicate spatial variability among the sites, but unlike drought frequency, do not show coherent spatial patterns. A comparison of an older period (1951–82) with a recent period (1983–2014) indicates few sites have statistically significant changes in drought frequency, drought duration, or drought severity at a 95-percent confidence level.

On the role of rising global temperatures on 2015-2016 Caribbean drought

NASA Astrophysics Data System (ADS)

Herrera, D. A.; Ault, T.

2016-12-01

In 2015 the Caribbean faced one of the worst droughts ever recorded. On some islands, like Cuba, the event represents the worst in over 100 years. Although this exceptional drought has been linked primarily to the recent El Niño, it is unclear whether its severity could have been enhanced by anthropogenic climate change. In this work, an analysis of the role played by anthropogenic warming on the 2015-2016 drought in the Caribbean is presented, using high-resolution drought datasets based on the self-calibrated Palmer Drought Severity Index (scPDSI), with the Penman-Monteith approximation of evapotranspiration. This effort further uses statistically-downscaled reanalysis products that span 1950 to the near present to establish an historical baseline for characterizing and monitoring drought in real time. The relative contribution of global warming is estimated by comparing the scPDSI calculated using detrended temperatures, against the scPDSI computed with the observed trend while holding all other terms at their historical or climatological values. Results indicate that during 2015, 70% of the Caribbean was affected by mild drought (-2 to -3 scPDSI units), 43% by moderate drought (-4 to -3) and 14% by severe drought (<-4). Consequently, this event was the most regionally-widespread since at least 1950. In contrast, during the 1997 drought, 47% of the region was under mild drought, 25% moderate drought and 8% severe drought. The approximate relative contribution of warmth on the 2015-2016 event varies substantially along the Caribbean, ranging from 8-12% in Puerto Rico and Lesser Antilles, to 14-29 % in Cuba and the Hispaniola Island. The inherent insular nature of the Caribbean island make them especially vulnerable to drought because water cannot be collected, moved, and stored on large spatial scales, like it can in the US Southwest. These results underscore the likely role climate change is playing in exacerbating regional drought impacts by favoring higher evapotranspiration rates from higher temperatures, and hence greater moisture losses during anomalous dry periods.

Possible Climate Change/Variability and Human Impacts, Vulnerability of African Drought Prone Regions, its Water Resources and Capacity Building

NASA Astrophysics Data System (ADS)

Gan, T. Y. Y.; Qin, X.; Ito, M.; Hülsmann, S.; Xixi, L.; Liong, S. Y.; Disse, M.; Koivusalo, H. J.

2017-12-01

This review article discusses the climate, water resources and historical droughts of Africa, drought indices, vulnerability, impact of global warming and landuse to drought-prone regions in West, Southern, and Greater Horn of Africa, which have suffered recurrent severe droughts in the past. Recent studies detected warming and drying trends in Africa since the mid-20th century. Based on the 4th Assessment Report of the Intergovernmental Panel of Climate Change, and that of the 5th Coupled Model Intercomparison Project (CMIP5), both northern and southern Africa are projected to experience drying such as decreasing precipitation, runoff and soil moisture in the 21st Century and could become more vulnerable to impact of droughts. The daily maximum temperature is projected to increase up to 8oC (RCP8.5 of CMIP5), precipitation indices such as total wet day precipitation (PRCPTOT) and heavy precipitation days (R10mm) could decrease, while warm spell duration (WSDI) and consecutive dry days (CDD) could increase. Uncertainties of the above long-term projections, teleconnections to climate anomalies such as ENSO and Madden Julian Oscillation which could also affect water resources of Africa, and capacity building in terms of physical infrastructure and non-structural solutions, are also discussed. Given traditional climate and hydrologic data observed in Africa are generally limited, satellite data should also be exploited to fill in the data gap for Africa in future.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Numerical simulation of groundwater flow, resource optimization, and potential effects of prolonged drought for the Citizen Potawatomi Nation Tribal Jurisdictional Area, central Oklahoma

USGS Publications Warehouse

Ryter, Derek W.; Kunkel, Christopher D.; Peterson, Steven M.; Traylor, Jonathan P.

2015-08-13

The hypothetical decrease in recharge during the simulated drought caused groundwater in storage over the entire model in the study area to decrease by 361,500 acre-feet (14,100 acre-feet in the North Canadian River alluvial aquifer and 347,400 acre-feet in the Central Oklahoma aquifer), or approximately 0.2 percent of the total groundwater in storage over the drought period. This small percentage of groundwater loss showed that the Central Oklahoma aquifer as a bedrock aquifer has relatively low rates of recharge from the surface relative to the approximate storage. The budget for base flow to the North Canadian River indicated that the change in groundwater flow to the North Canadian River decreased during the 10-year drought by 386,500 acre-feet, or 37 percent. In all other parts of the Citizen Potawatomi Nation Tribal Jurisdictional Area, base flow decreased by 292,000 acre-feet, or 28 percent. Streamflow in the North Canadian River at the streamflow-gaging station at Shawnee, Okla., decreased during the hypothetical drought by as much as 28 percent, and the mean change in streamflow decreased as much as 16 percent. Streamflow at the Shawnee streamflow-gaging station did not recover to nondrought conditions until about 3 years after the simulated drought ended, during the relatively wet year of 2007.

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ping; Omani, Nina; Chaubey, Indrajeet

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify thesemore » services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.« less

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin.

PubMed

Li, Ping; Omani, Nina; Chaubey, Indrajeet; Wei, Xiaomei

2017-05-08

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index ( SPI ), standardized soil water content index ( SSWI ), and standardized streamflow index ( SSI ). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI 12 than SPI 12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

PubMed Central

Li, Ping; Omani, Nina; Chaubey, Indrajeet; Wei, Xiaomei

2017-01-01

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB. PMID:28481311

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

DOE PAGES

Li, Ping; Omani, Nina; Chaubey, Indrajeet; ...

2017-05-08

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify thesemore » services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.« less

Impacts of European drought events: insights from an international database of text-based reports

NASA Astrophysics Data System (ADS)

Stahl, Kerstin; Kohn, Irene; Blauhut, Veit; Urquijo, Julia; De Stefano, Lucia; Acácio, Vanda; Dias, Susana; Stagge, James H.; Tallaksen, Lena M.; Kampragou, Eleni; Van Loon, Anne F.; Barker, Lucy J.; Melsen, Lieke A.; Bifulco, Carlo; Musolino, Dario; de Carli, Alessandro; Massarutto, Antonio; Assimacopoulos, Dionysis; Van Lanen, Henny A. J.

2016-03-01

Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Providing an impact assessment and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The analysis also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and public water supply) and sector-specific impacts in central and northern regions (e.g., on forestry or energy production). The protocol developed thus enabled a new and more comprehensive view on drought impacts across Europe. Related studies have already developed statistical techniques to evaluate the link between drought indices and the categorized impacts using EDII data. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This insight can therefore inform drought policy planning at national to international levels.

The Roles of Shallow and Deep Groundwater Storage During Drought at Panola Mountain Research Watershed, Georgia, U.S.A.

NASA Astrophysics Data System (ADS)

Aulenbach, B. T.; Peters, N. E.

2016-12-01

Southeastern U.S. experiences recurring droughts, which can reduce water availability and can result in water-limiting conditions. Monthly water budgets were estimated at Panola Mountain Research Watershed, a small 41-hectare forested watershed near Atlanta, Georgia, from 1985 through 2015, to quantify the effects of climatic variability on groundwater (GW) storage. A relation between stream base flow and watershed GW storage was developed. The relation indicated that both shallow and deep GW storage contribute to base-flow runoff, except for the bottom third (78 mm) of the range in observed shallow soil moisture. The base flow-storage relation was then used to estimate monthly evapotranspiration (ET) using a closed water budget approach. Growing season droughts were almost always preceded by low GW storage at the onset of the growing season. The low base flow and GW storage conditions were caused by low precipitation (P) during the dormant season, and to a lesser extent, carryover of low GW storage conditions from the previous growing season. Growing season P had little impact on drought, as most P ultimately resulted in ET instead of deeper GW recharge. Water-limited growing season conditions were indicated when potential ET (PET) >> ET, and occurred during months having a large "P-deficit", PET - P, and when shallow storage was already near its observed minimum—such that the P-deficits exceeded the extractable water in shallow storage. These observations can be used to hypothesize how projected future increases in temperature, and how resulting increases in PET affect water budgets in Southeastern U.S. The dormant season will become shorter and ET will increase, causing decreased GW recharge during the dormant season, and will result in more frequent and severe growing season droughts. Higher growing season PET would increase the frequency and duration of water limiting conditions due to higher P-deficits and more frequent occurrences of low shallow storage.

The potential of SMAP soil moisture data for analyzing droughts

NASA Astrophysics Data System (ADS)

Rajasekaran, E.; Das, N. N.; Entekhabi, D.; Yueh, S. H.

2017-12-01

Identification of the onset and the end of droughts are important for socioeconomic planning. Different datasets and tools are either available or being generated for drought analysis to recognize the status of drought. The aim of this study is to understand the potential of the SMAP soil moisture (SM) data for identification of onset, persistence and withdrawal of droughts over the Contiguous United States. We are using the SMAP-passive level 3 soil moisture observations and the United States Drought Monitor (http://droughtmonitor.unl.edu) data for understanding the relation between change in SM and drought severity. The daily observed SM data are temporally averaged to match the weekly drought monitor data and subsequently the weekly, monthly, 3 monthly and 6 monthly change in SM and drought severity were estimated. The analyses suggested that the change in SM and drought severity are correlated especially over the mid-west and west coast of USA at monthly and longer time scales. The spatial pattern of the SM change maps clearly indicated the regions that are moving between different levels of drought severity. Further, the time series of effective saturation [Se =(θ-θr)/(θs-θr)] indicated the temporal dynamics of drought conditions over California which is recovering from a long-term drought. Additional analyses are being carried out to develop statistics between drought severity and soil moisture level.

Risk to Drought in Mexico

NASA Astrophysics Data System (ADS)

Magana, V.

2016-12-01

Drought is one of the major meteorological hazards in Mexico given the semiarid and arid conditions in most of its territory. The recent drought event between 2011 and 2013 led to one of the major socioeconomic and environmental crisis in recent years in relation to water deficit mainly in northern Mexico. But the impacts of meteorological droughts are not only related to precipitation deficit, but to the water crisis context in which the climatic anomaly occurs. In other words, the drought hazard occurs in a vulnerability context that results in risks at levels that translate into hydrological, agricultural and socioeconomic droughts. The dynamics of prolonged droughts in Mexico has been studied in relation to low frequency oscillations in the Pacific and Atlantic oceans (Méndez and Magaña 2010). On the other hand, the vulnerability to drought has been characterized by means of socioeconomic and physical indicators that reflect the dynamical and multifactorial characteristics of this element (Neri and Magaña 2016). The combination of hazard and vulnerability led to an estimate of risk to drought that explains the drought impacts in recent years. The Mexican government has developed a national strategy to prevent or at least ameliorate the impacts of droughts by establishing the National Program against Drought (PRONACOSE) for each one of the thirteen hydrologic administrative regions that compose the Mexican territory. The main idea behind PRONACOSE is to respond to drought as it reaches a higher level of intensity. Some of the protocols in PRONACOSE are based on a risk analysis and proposals by water stakeholders. It is found that PRONACOSE could better work if a risk management preventive scheme is implemented making use of the knowledge on the predictability of drought in Mexico on various time scales. The examples of potential risk to drought management schemes in Mexico for some of the hydrologic administrative regions are presented.

Predicting the Vegetation Condition of the 2015/16 Drought across the Great Horn of Africa (GHA): Model Evaluation and Preliminary Result

NASA Astrophysics Data System (ADS)

Tadesse, T.; Bayissa, Y. A.; Demisse, G. B.; Wardlow, B.

2017-12-01

The National Drought Mitigation Center (NDMC) funded by NASA has developed a new tool for predicting the general vegetation condition called: the "Vegetation outlook for the Greater Africa (VegOut-GHA)." In this study, the 2015/16 drought across the GHA that has been considered one of the worst in decades across the region was assessed and evaluated using the VegOut-GHA models and products. The VegOut-GHA maps (hindsight prediction maps) for the growing season (June - September) were generated to predict a standardized seasonal greenness (SSG) that is based on seasonally integrated normalized difference vegetation index (a measure that represents a general indicator of relative vegetation health within a growing season). The vegetation condition outlooks were made for 10-day, 1-month, 2-month, and 3-month in hindsight and compared to the observed values of the SSG. The VegOut-GHA model was evaluated and compared to crop yield and other satellite-derived data (e.g., standardized seasonal precipitation based on "Enhancing National Climate Services (ENACTS)" datasets for GHA). Thus, the VegOut-GHA model and its evaluation results will be discussed based on the 2015/2016 drought season in the region. This preliminary results suggest an opportunity to improve management of drought risk in agriculture and food security.

Mapping Drought Impacts on Agricultural Production in California's Central Valley

NASA Astrophysics Data System (ADS)

Melton, F. S.; Guzman, A.; Johnson, L.; Rosevelt, C.; Verdin, J. P.; Dwyer, J. L.; Mueller, R.; Zakzeski, A.; Thenkabail, P. S.; Wallace, C.; Jones, J.; Windell, S.; Urness, J.; Teaby, A.; Hamblin, D.; Post, K. M.; Nemani, R. R.

2014-12-01

The ongoing drought in California has substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, and allocation of emergency funds to mitigate drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in idle acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 640 fields from March - September, 2014. We present the algorithm along with updated results from the accuracy assessment, and discuss potential applications to other regions.

Mechanisms of piñon pine mortality after severe drought: a retrospective study of mature trees.

PubMed

Gaylord, Monica L; Kolb, Thomas E; McDowell, Nate G

2015-08-01

Conifers have incurred high mortality during recent global-change-type drought(s) in the western USA. Mechanisms of drought-related tree mortality need to be resolved to support predictions of the impacts of future increases in aridity on vegetation. Hydraulic failure, carbon starvation and lethal biotic agents are three potentially interrelated mechanisms of tree mortality during drought. Our study compared a suite of measurements related to these mechanisms between 49 mature piñon pine (Pinus edulis Engelm.) trees that survived severe drought in 2002 (live trees) and 49 trees that died during the drought (dead trees) over three sites in Arizona and New Mexico. Results were consistent over all sites indicating common mortality mechanisms over a wide region rather than site-specific mechanisms. We found evidence for an interactive role of hydraulic failure, carbon starvation and biotic agents in tree death. For the decade prior to the mortality event, dead trees had twofold greater sapwood cavitation based on frequency of aspirated tracheid pits observed with scanning electron microscopy (SEM), smaller inter-tracheid pit diameter measured by SEM, greater diffusional constraints to photosynthesis based on higher wood δ(13)C, smaller xylem resin ducts, lower radial growth and more bark beetle (Coleoptera: Curculionidae) attacks than live trees. Results suggest that sapwood cavitation, low carbon assimilation and low resin defense predispose piñon pine trees to bark beetle attacks and mortality during severe drought. Our novel approach is an important step forward to yield new insights into how trees die via retrospective analysis. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analysis of extreme hydrological phenomena in southern Italy (Calabria region)

NASA Astrophysics Data System (ADS)

Caloiero, Tommaso; Aceto, Luigi; Aurora Pasqua, A.; Petrucci, Olga

2017-04-01

Calabria (southern Italy) is a region exposed to the effects of contrasting climatic and hydrological phenomena. In fact, due to its oblong shape, to its position in the middle of the Mediterranean Basin, and for its mountainous nature, Calabria shows a high spatial variability of the climatic features and of related phenomena such as floods and drought. The present paper is based on the historical database ASICal (Historically flooded areas in Calabria), a catalogue of effects of floods and rain-related landslides that occurred in the region since the XIX Century. The catalogue has been built using the typical historical data sources as chronicles, diaries, historical books, local and regional agencies, press archives, scientific papers, and documents of civil protection offices. From these sources, we selected information on damage caused by rain related phenomena at a municipal scale and chronologically sorted by year, month and day. The analysis of the entire catalogue allows highlighting the regional Damaging Hydrogeological Events (DHE), defined as periods of intense rain causing damage on regional sectors conventionally selected as larger than 30% of the entire regional territory. For each event, as a measure of the magnitude of rainfall, the return period of the daily rainfall recorded during the event has been evaluated. In addition, we recently carried out a similar historical research to identify the main drought events affecting the region. In this case, due to the spatial and temporal characteristics of drought, data are collected both at municipal and regional scale, and the temporal scale is generally monthly or annual. For each event, we used as climatic descriptors a drought index for monitoring drought phenomena. Among drought indices, we used the Standardized Precipitation Index (SPI) which can be considered the most robust and effective, since it can be calculated for different time-scales and can be used to analyse different drought categories. Moreover, the SPI is easier to calculate than complex indices, as it is based on precipitation alone, and allows comparing drought conditions among different periods and regions. Both the series have been analysed jointly, in order to obtain the general trend of extreme rain and drought, characterised by mean of descriptive climatic features and damage caused. The results supply a glance in the past climatic history of the region that can be used to project to future and be prepared for ongoing changes related to climate changes. In fact, the identification of the most floods and drought prone areas can be useful for both civil protection mitigation strategies and water resources management (water used for home, industrial, and agricultural purposes).

Analysis of natural variation in bermudagrass (Cynodon dactylon) reveals physiological responses underlying drought tolerance.

PubMed

Shi, Haitao; Wang, Yanping; Cheng, Zhangmin; Ye, Tiantian; Chan, Zhulong

2012-01-01

Bermudagrass (Cynodon dactylon) is a widely used warm-season turfgrass and one of the most drought tolerant species. Dissecting the natural variation in drought tolerance and physiological responses will bring us powerful basis and novel insight for plant breeding. In the present study, we evaluated the natural variation of drought tolerance among nine bermudagrass varieties by measuring physiological responses after drought stress treatment through withholding water. Three groups differing in drought tolerance were identified, including two tolerant, five moderately tolerant and two susceptible varieties. Under drought stress condition, drought sensitive variety (Yukon) showed relative higher water loss, more severe cell membrane damage (EL), and more accumulation of hydrogen peroxide (H₂O₂) and malondialdehyde (MDA), while drought tolerant variety (Tifgreen) exhibited significantly higher antioxidant enzymes activities. Further results indicated that drought induced cell injury in different varieties (Yukon, SR9554 and Tifgreen) exhibited liner correlation with leaf water content (LWC), H₂O₂ content, MDA content and antioxidant enzyme activities. Additionally, Tifgreen plants had significantly higher levels of osmolytes (proline level and soluble sugars) when compared with Yukon and SR9554 under drought stress condition. Taken together, our results indicated that natural variation of drought stress tolerance in bermudagrass varieties might be largely related to the induced changes of water status, osmolyte accumulation and antioxidant defense system.

Assessment of Vegetation Responses and Sensitivity to the Millennium Drought in Australia

NASA Astrophysics Data System (ADS)

Jiao, T.; Williams, C. A.

2016-12-01

During the period from 1997 to 2009, Australia experienced one of the most severe and persistent drought known as the Millennium Drought (MD). Major water shortages were reported across the Australian continent as well as a great many tree mortality during and post this drought event. Given the projection of hotter and drier conditions for much of the continent, it is critical to analyze the impacts of climate extremes like MD as an indicator of possible impacts of future trends. Despite many field investigation, large-area monitoring of vegetation decline from MD remains lacking. Here, multi-source remote sensing datasets and novel methods were employed to assess the impacts of MD on vegetation in Australia in terms of the magnitude and sensitivity. Vegetation variables examined include fraction of photosynthetically absorbed radiation (fPar), vegetation optical depth (VOD) and aboveground biomass (AGB). Drought indicators are calculated based on precipitation and potential evapotranspiration from meteorological data. We found consistent spatial patterns in drought-induced declines among fPar, VOD and AGB. Common declines were observed in the east of New South Wales (NSW), the southeast of Queensland, the center and east of Victoria, and Tasmania. Severe declines (>0.2) in fPar concentrate in open forests and shrub lands while regions with more than 0.1 of decline in VOD are found widely across biome types. The net decrease in AGB could reach more than 20 Mg C per ha in the west of Victoria and the southwest of NSW. Sensitivity analysis shows that forests followed by herbaceous are more sensitive to drought than shrubs in terms of declines in fPar and VOD. In addition, vegetation tends to have larger sensitivity in semi-arid or semi-mesic regions than in areas that are either too dry or too wet.

NDVI statistical distribution of pasture areas at different times in the Community of Madrid (Spain)

NASA Astrophysics Data System (ADS)

Martín-Sotoca, Juan J.; Saa-Requejo, Antonio; Díaz-Ambrona, Carlos G. H.; Tarquis, Ana M.

2015-04-01

The severity of drought has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. However, its impacts on rain-fed agriculture are especially direct. Because of the importance of drought, there have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). 'Biomass index' based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in countries like United States of America, Canada and Spain for pasture and forage crops for some years (Rao, 2010). This type of agricultural insurance is named as 'index-based insurance' (IBI). IBI is perceived to be substantially less costly to operate and manage than multiple peril insurance. IBI contracts pay indemnities based not on the actual yield (or revenue) losses experienced by the insurance purchaser but rather based on realized NDVI values (historical data) that is correlated with farm-level losses (Xiaohui Deng et al., 2008). Definition of when drought event occurs is defined on NDVI threshold values mainly based in statistical parameters, average and standard deviation that characterize a normal distribution. In this work a pasture area at the north of Community of Madrid (Spain) has been delimited. Then, NDVI historical data was reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. A statistical analysis of the NDVI histograms at consecutives 46 intervals of that area was applied to search for the best statistical distribution based on the maximum likelihood criteria. The results show that the normal distribution is not the optimal representation when IBI is available; the implications in the context of crop insurance are discussed (Martín-Sotoca, 2014). References Kolli N Rao. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish). Niemeyer, S., 2008: New drought indices. First Int. Conf. on Drought Management: Scientific and Technological Innovations, Zaragoza, Spain, Joint Research Centre of the European Commission. [Available online at http://www.iamz.ciheam.org/medroplan/zaragoza2008/Sequia2008/Session3/S.Niemeyer.pdf.] Xiaohui Deng, Barry J. Barnett, Gerrit Hoogenboom, Yingzhuo Yu and Axel Garcia y Garcia 2008. Alternative Crop Insurance Indexes. Journal of Agricultural and Applied Economics, 40(1), 223-237. Acknowledgements First author acknowledges the Research Grant obtained from CEIGRAM in 2014

Indicators to measure risk of disaster associated with drought: Implications for the health sector.

PubMed

Sena, Aderita; Ebi, Kristie L; Freitas, Carlos; Corvalan, Carlos; Barcellos, Christovam

2017-01-01

Brazil has a large semiarid region, which covers part of 9 states, over 20% of the 5565 municipalities in the country and at 22.5 million persons, 12% of the country's population. This region experiences recurrent and extended droughts and is characterized by low economic development, scarcity of natural resources including water, and difficult agricultural and livestock production. Local governments and communities need easily obtainable tools to aid their decision making process in managing risks associated with drought. To inform decision-making at the level of municipalities, we investigated factors contributing to the health risks of drought. We used education and poverty indicators to measure vulnerability, number of drought damage evaluations and historical drought occurrences as indicators of hazard, and access to water as an indicator of exposure, to derive a drought disaster risk index. Indicators such as access to piped water, illiteracy and poverty show marked differences in most states and, in nearly all states, the living conditions of communities in the semiarid region are worse than in the rest of each state. There are municipalities at high drought disaster risk in every state and there are a larger number of municipalities at higher risks from the center to the north of the semiarid region. Understanding local hazards, exposures and vulnerabilities provides the means to understand local communities' risks and develop interventions to reduce them. In addition, communities in these regions need to be empowered to add their traditional knowledge to scientific tools, and to identify the actions most relevant to their needs and realities.

Indicators to measure risk of disaster associated with drought: Implications for the health sector

PubMed Central

Ebi, Kristie L.; Freitas, Carlos; Corvalan, Carlos; Barcellos, Christovam

2017-01-01

Introduction Brazil has a large semiarid region, which covers part of 9 states, over 20% of the 5565 municipalities in the country and at 22.5 million persons, 12% of the country’s population. This region experiences recurrent and extended droughts and is characterized by low economic development, scarcity of natural resources including water, and difficult agricultural and livestock production. Local governments and communities need easily obtainable tools to aid their decision making process in managing risks associated with drought. Methods To inform decision-making at the level of municipalities, we investigated factors contributing to the health risks of drought. We used education and poverty indicators to measure vulnerability, number of drought damage evaluations and historical drought occurrences as indicators of hazard, and access to water as an indicator of exposure, to derive a drought disaster risk index. Results Indicators such as access to piped water, illiteracy and poverty show marked differences in most states and, in nearly all states, the living conditions of communities in the semiarid region are worse than in the rest of each state. There are municipalities at high drought disaster risk in every state and there are a larger number of municipalities at higher risks from the center to the north of the semiarid region. Conclusions Understanding local hazards, exposures and vulnerabilities provides the means to understand local communities’ risks and develop interventions to reduce them. In addition, communities in these regions need to be empowered to add their traditional knowledge to scientific tools, and to identify the actions most relevant to their needs and realities. PMID:28742848

Toward Seasonal Forecasting of Global Droughts: Evaluation over USA and Africa

NASA Astrophysics Data System (ADS)

Wood, Eric; Yuan, Xing; Roundy, Joshua; Sheffield, Justin; Pan, Ming

2013-04-01

Extreme hydrologic events in the form of droughts are significant sources of social and economic damage. In the United States according to the National Climatic Data Center, the losses from drought exceed US210 billion during 1980-2011, and account for about 24% of all losses from major weather disasters. Internationally, especially for the developing world, drought has had devastating impacts on local populations through food insecurity and famine. Providing reliable drought forecasts with sufficient early warning will help the governments to move from the management of drought crises to the management of drought risk. After working on drought monitoring and forecasting over the USA for over 10 years, the Princeton land surface hydrology group is now developing a global drought monitoring and forecasting system using a dynamical seasonal climate-hydrologic LSM-model (CHM) approach. Currently there is an active debate on the merits of the CHM-based seasonal hydrologic forecasts as compared to Ensemble Streamflow Prediction (ESP). We use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2) and its previous version CFSv1, to investigate the value of seasonal climate model forecasts by conducting a set of 27-year seasonal hydrologic hindcasts over the USA. Through Bayesian downscaling, climate models have higher squared correlation (R2) and smaller error than ESP for monthly precipitation averaged over major river basins across the USA, and the forecasts conditional on ENSO show further improvements (out to four months) over river basins in the southern USA. All three approaches have plausible predictions of soil moisture drought frequency over central USA out to six months because of strong soil moisture memory, and seasonal climate models provide better results over central and eastern USA. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur in different seasons for different basins. The R2 of drought severity accumulated over USA is higher during winter, and climate models present added value especially at long leads. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the realtime data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for estimating a climatology against which current conditions can be compared. Based on our established experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML), we use the downscaled CFSv2 climate forcings to drive the re-calibrated VIC model and produce 6-month, 20-member ensemble hydrologic forecasts over Africa starting on the 1st of each calendar month during 1982-2007. Our CHM-based seasonal hydrologic forecasts are now being analyzed for its skill in predicting short-term soil moisture droughts over Africa. Besides relying on a single seasonal climate model or a single drought index, preliminary forecast results will be presented using multiple seasonal climate models based on the NOAA-supported National Multi-Model Ensemble (NMME) project, and with multiple drought indices. Results will be presented for the USA NIDIS test beds such as Southeast US and Colorado NIDIS (National Integrated Drought Information System) test beds, and potentially for other regions of the globe.

Impact of Drought on Groundwater and Soil Moisture - A Geospatial Tool for Water Resource Management

NASA Astrophysics Data System (ADS)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

For many decades, recurring droughts in different regions in the US have been negatively impacting ecosystems and economic sectors. Oklahoma and Texas have been suffering from exceptional and extreme droughts in 2011-2014, with almost 95% of the state areas being affected (Drought Monitor, 2015). Accordingly, in 2011 alone, around 1.6 billion were lost in the agricultural sector alone as a result of drought in Oklahoma (Stotts 2011), and 7.6 billion in Texas agriculture (Fannin 2012). While surface water is among the instant indicators of drought conditions, it does not translate directly to groundwater resources that are the main source of irrigation water. Both surface water and groundwater are susceptible to drought, while groundwater depletion is a long-term process and might not show immediately. However, understanding groundwater availability is crucial for designing water management strategies and sustainable water use in the agricultural sector and other economic sectors. This paper presents an interactive geospatially weighted evaluation model and a tool at the same time to analyze groundwater resources that can be used for decision support in water management. The tool combines both groundwater and soil moisture changes in Oklahoma and Texas in 2003-2014, thus representing the most important indicators of agricultural and hydrological drought. The model allows for analyzing temporal and geospatial long-term drought at the county level. It can be expanded to other regions in the US and the world. The model has been validated with the Palmer Drought Index Severity Index to account for other indicators of meteorological drought. It can serve as a basis for an upcoming socio-economic and environmental analysis of drought events in the short and long-term in different geographic regions.

Non-linear effects of drought under shade: reconciling physiological and ecological models in plant communities.

PubMed

Holmgren, Milena; Gómez-Aparicio, Lorena; Quero, José Luis; Valladares, Fernando

2012-06-01

The combined effects of shade and drought on plant performance and the implications for species interactions are highly debated in plant ecology. Empirical evidence for positive and negative effects of shade on the performance of plants under dry conditions supports two contrasting theoretical models about the role of shade under dry conditions: the trade-off and the facilitation hypotheses. We performed a meta-analysis of field and greenhouse studies evaluating the effects of drought at two or more irradiance levels on nine response variables describing plant physiological condition, growth, and survival. We explored differences in plant response across plant functional types, ecosystem types and methodological approaches. The data were best fit using quadratic models indicating a humped-back shape response to drought along an irradiance gradient for survival, whole plant biomass, maximum photosynthetic capacity, stomatal conductance and maximal photochemical efficiency. Drought effects were ameliorated at intermediate irradiance, becoming more severe at higher or lower light levels. This general pattern was maintained when controlling for potential variations in the strength of the drought treatment among light levels. Our quantitative meta-analysis indicates that dense shade ameliorates drought especially among drought-intolerant and shade-tolerant species. Wet tropical species showed larger negative effects of drought with increasing irradiance than semiarid and cold temperate species. Non-linear responses to irradiance were stronger under field conditions than under controlled greenhouse conditions. Non-linear responses to drought along the irradiance gradient reconciliate opposing views in plant ecology, indicating that facilitation is more likely within certain range of environmental conditions, fading under deep shade, especially for drought-tolerant species.

Drought variability and change across the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Coll, Joan Ramon; Aguilar, Enric

2015-04-01

Drought variability and change is assessed in this study across the Iberian Peninsula along the 20th century and the first decade of the 21st century using state of the art drought indices: the Sc-PDSI, the SPI and the SPEI. Daily temperature and precipitation data from 24 time-series regularly spread over Iberian Peninsula are quality controlled and also homogenized in a monthly scale to create the Monthly Iberian Temperature and Precipitation Series (MITPS) for the period 1906-2010. The Sc-PDSI, the 12-month SPI and 12-month SPEI are computed on a monthly basis using the newly MITPS dataset to identify dry and wet conditions across time. Precipitation data is only required to compute SPI, but potential evapotranspiration (PET) is also needed to perform the Sc-PDSI and SPEI, which is estimated using the Tornthwaite's method. The analysis conducted in this study confirms that drought conditions are worsening for most of the Iberian Peninsula across time strongly induced by global warming especially during the last three decades. All drought indices have found a drying trend in the Pyrenees, Ebro basin, central Iberia and in the south and south-eastern area while a wetting trend is identified in the western and in the north-western region. Future projections also indicate a clear increase in hydrological drought conditions along the 21st century, thus, water saving and the application of effective water management strategies will be crucial to minimize the impact of hydrological droughts over the Iberian Peninsula into the near future. KEY WORDS: Drought, climate change, Iberian Peninsula, drought indices.

Quantitative variation in water-use efficiency across water regimes and its relationship with circadian, vegetative, reproductive, and leaf gas-exchange traits.

PubMed

Edwards, Christine E; Ewers, Brent E; McClung, C Robertson; Lou, Ping; Weinig, Cynthia

2012-05-01

Drought limits light harvesting, resulting in lower plant growth and reproduction. One trait important for plant drought response is water-use efficiency (WUE). We investigated (1) how the joint genetic architecture of WUE, reproductive characters, and vegetative traits changed across drought and well-watered conditions, (2) whether traits with distinct developmental bases (e.g. leaf gas exchange versus reproduction) differed in the environmental sensitivity of their genetic architecture, and (3) whether quantitative variation in circadian period was related to drought response in Brassica rapa. Overall, WUE increased in drought, primarily because stomatal conductance, and thus water loss, declined more than carbon fixation. Genotypes with the highest WUE in drought expressed the lowest WUE in well-watered conditions, and had the largest vegetative and floral organs in both treatments. Thus, large changes in WUE enabled some genotypes to approach vegetative and reproductive trait optima across environments. The genetic architecture differed for gas-exchange and vegetative traits across drought and well-watered conditions, but not for floral traits. Correlations between circadian and leaf gas-exchange traits were significant but did not vary across treatments, indicating that circadian period affects physiological function regardless of water availability. These results suggest that WUE is important for drought tolerance in Brassica rapa and that artificial selection for increased WUE in drought will not result in maladaptive expression of other traits that are correlated with WUE.

(How) Can We Use Satellite Data to Estimate Effects of Extreme Drought on Photosynthesis?

NASA Astrophysics Data System (ADS)

Vicca, S.; Balzarolo, M.; Filella, I.; Granier, A.; Herbst, M.; Knohl, A.; Longdoz, B.; Mund, M.; Nagy, Z.; Pintér, K.; Rambal, S.; Verbesselt, J.; Verger, A.; Zeileis, A.; Zhang, C.; Penuelas, J.

2017-12-01

Severe droughts can strongly impact photosynthesis (GPP), but the tool best suited for large-scale and long-term monitoring, satellite imagery, has yet to prove its ability to detect drought effects on GPP. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect effect of a strong drought (that started during the European heatwave of 2003) on GPP in a beech forest in France (Hesse). While vegetation state remained largely unaffected by the drought, Eddy Covariance data revealed a substantial decrease in GPP and GPP recovered only after about three years. This three-year reduction in GPP was, however not detected by severaly commonly used reflectance indices (like NDVI and FAPAR) or by MODIS GPP product. Only he Enhanced Vegetation Index (EVI) and the Photochemical Reflectance Index (PRI) detected the drought effect, but the PRI only after normalization for absorbed light. These results were compared to a two other forests where a severe drought event had affected GPP and these data confirmed that especially the PRI normalized for absorbed light provides useful information about vegetation functioning that is not captured by other remote sensing indicators under test.

Analysis of potential future droughts limiting maize production, in the Luvuvhu River catchment area, South Africa

NASA Astrophysics Data System (ADS)

Masupha, Teboho Elisa; Moeletsi, Mokhele Edmond

2018-06-01

Recurring droughts associated with global warming have raised major concern for the agricultural sector, particularly vulnerable small-scale farmers who rely on rain-fed farming such as in the Luvuvhu River catchment. The Standardized Precipitation Evapotranspiration Index (SPEI) and Water Requirement Satisfaction Index (WRSI) were calculated to assess drought on a 120-day maturing maize crop based on outputs of the CSIRO-Mk3.6.0 under RCP 4.5 emission scenario, for the period 1980/81-2089/90. Results by SPEI show that 40-54% of the agricultural seasons during the base period experienced mild drought conditions (SPEI 0 to -0.99), equivalent to a recurrence of once in two seasons. However, WRSI results clearly indicated that stations in the drier regions (annual rainfall <600 mm) of the catchment experienced mild drought (WRSI 70 - 79) corresponding to satisfactory crop performance every season. Results further showed overall mild to moderate droughts in the beginning of the near-future climate period (2020/21-2036/37) with SPEI values not decreasing below -1.5. These conditions are then expected to change during the far-future climate period (2055/56-2089/90), whereby results on the expected crop performance predicted significantly drier conditions (p < 0.05). This study provided information on how farmers in the area can prepare for future agricultural seasons, while there is sufficient time to implement strategies to reduce drought risk potential. Thus, integrated interventions could provide best options for improving livelihoods and building the capability of farmers to manage climate change-related stresses.

Drought causes reduced growth of trembling aspen in western Canada.

PubMed

Chen, Lei; Huang, Jian-Guo; Alam, Syed Ashraful; Zhai, Lihong; Dawson, Andria; Stadt, Kenneth J; Comeau, Philip G

2017-07-01

Adequate and advance knowledge of the response of forest ecosystems to temperature-induced drought is critical for a comprehensive understanding of the impacts of global climate change on forest ecosystem structure and function. Recent massive decline in aspen-dominated forests and an increased aspen mortality in boreal forests have been associated with global warming, but it is still uncertain whether the decline and mortality are driven by drought. We used a series of ring-width chronologies from 40 trembling aspen (Populus tremuloides Michx.) sites along a latitudinal gradient (from 52° to 58°N) in western Canada, in an attempt to clarify the impacts of drought on aspen growth by using Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Results indicated that prolonged and large-scale droughts had a strong negative impact on trembling aspen growth. Furthermore, the spatiotemporal variability of drought indices is useful for explaining the spatial heterogeneity in the radial growth of trembling aspen. Due to ongoing global warming and rising temperatures, it is likely that severer droughts with a higher frequency will occur in western Canada. As trembling aspen is sensitive to drought, we suggest that drought indices could be applied to monitor the potential effects of increased drought stress on aspen trees growth, achieve classification of eco-regions and develop effective mitigation strategies to maintain western Canadian boreal forests. © 2017 John Wiley & Sons Ltd.

Differential antioxidative response of tolerant and sensitive maize (Zea mays L.) genotypes to drought stress at reproductive stage.

PubMed

Chugh, Vishal; Kaur, Narinder; Grewal, M S; Gupta, Anil K

2013-04-01

The role of oxidative stress management was evaluated in two maize (Zea mays L.) genotypes - Parkash (drought-resistant) and Paras (drought-sensitive), subjected to drought stress during reproductive stage. Alterations in their antioxidant pools - glutathione (GSH) and ascorbic acid (AsA) combined with activities of enzymes glutathione reductase (GR), ascorbate peroxidase (APX), peroxidase (POX) and catalase (CAT) involved in defense against oxidative stress and stress parameters, namely chlorophyll (Chl), hydrogen peroxide (H2O2) and malondialdehyde (MDA) were investigated in flag leaves from silk emergence till maturity. The drought caused transient increase in GR, APX, POX and CAT activities in drought-tolerant genotype (Parkash) which decreased at later stages with the extended period of drought stress. However, in Paras, drought stress caused decrease in activities of GR and CAT from initial period of stress till the end of experiment, except for POX which showed slight increase in activity. A significant increase in GSH content was observed in Parkash till 35 days after silking (DAS), whereas in Paras, GSH content remained lower than irrigated till maturity. Parkash which had higher AsA and Chl contents, also showed lower H2O2 and MDA levels than Paras under drought stress conditions. However, at the later stages, decline in antioxidant enzyme activities in Parkash due to severe drought stress led to enhanced membrane damage, as revealed by the accumulation of MDA. Our data indicated that significant activation of antioxidant system in Parkash might be responsible for its drought-tolerant behavior under drought stress and helped it to cope with the stress up to a definite period. Thus, the results indicate that antioxidant status and lipid peroxidation in flag leaves can be used as indices of drought tolerance in maize plants and also as potential biochemical targets for the crop improvement programmes to develop drought-tolerant cultivars.

Expanded spatial extent of the Medieval Climate Anomaly revealed in lake-sediment records across the boreal region in northwest Ontario.

PubMed

Laird, Kathleen R; Haig, Heather A; Ma, Susan; Kingsbury, Melanie V; Brown, Thomas A; Lewis, C F Michael; Oglesby, Robert J; Cumming, Brian F

2012-09-01

Multi-decadal to centennial-scale shifts in effective moisture over the past two millennia are inferred from sedimentary records from six lakes spanning a ~250 km region in northwest Ontario. This is the first regional application of a technique developed to reconstruct drought from drainage lakes (open lakes with surface outlets). This regional network of proxy drought records is based on individual within-lake calibration models developed using diatom assemblages collected from surface sediments across a water-depth gradient. Analysis of diatom assemblages from sediment cores collected close to the near-shore ecological boundary between benthic and planktonic diatom taxa indicated this boundary shifted over time in all lakes. These shifts are largely dependent on climate-driven influences, and can provide a sensitive record of past drought. Our lake-sediment records indicate two periods of synchronous signals, suggesting a common large-scale climate forcing. The first is a period of prolonged aridity during the Medieval Climate Anomaly (MCA, c. 900-1400 CE). Documentation of aridity across this region expands the known spatial extent of the MCA megadrought into a region that historically has not experienced extreme droughts such as those in central and western north America. The second synchronous period is the recent signal of the past ~100 years, which indicates a change to higher effective moisture that may be related to anthropogenic forcing on climate. This approach has the potential to fill regional gaps, where many previous paleo-lake depth methods (based on deeper centrally located cores) were relatively insensitive. By filling regional gaps, a better understanding of past spatial patterns in drought can be used to assess the sensitivity and realism of climate model projections of future climate change. This type of data is especially important for validating high spatial resolution, regional climate models. © 2012 Blackwell Publishing Ltd.

Breeding drought tolerant rice for shallow rainfed ecosystem of eastern India.

PubMed

Swain, Padmini; Raman, Anitha; Singh, S P; Kumar, Arvind

2017-08-01

In shallow rainfed rice agro-ecosystems, drought stress can occur at any growth stage and can cause a significant yield reduction. During recent years, some rice varieties possessing tolerance of reproductive-stage drought stress have recently been developed. Tolerance of vegetative-stage drought stress is also required to improve rice productivity in drought-prone regions. In this study, we evaluated a set of rice breeding lines for their response to a range of different types of vegetative-stage drought stress in order to propose standardized phenotyping protocols for conducting vegetative-stage drought stress screening trials and also to identify genotypes combining tolerance of vegetative- and reproductive-stage drought stress. A soil water potential threshold of -20 kPa during the vegetative stage was identified as the target for effective selection under vegetative stage with grain yield reduction of about 50% compared to irrigated control trials. Genotypes identified as showing high yield under reproductive-stage drought stress were not necessarily the genotypes showing best performance under vegetative-stage drought stress. Genotypes IR72667-16-1-B-B-3, IR78908-126-B-2-B, and IR79970-B-47-1 showed tolerance of both vegetative-stage and reproductive-stage drought stress. For most, the genotypes that were best under vegetative stage drought or even vegetative stage + reproductive stage drought were different from the genotypes that were best under reproductive stage drought. Based on the cultivar superiority measure, IR69515-6-KKN-4-UBN-4-2-1-1-1 and IR78908-126-B-1-B were the stable genotypes (indicated by low P i ) under both irrigated control and severe vegetative stress conditions, genotypes IR83614-203-B and IR78908-80-B-3-B were stable under irrigated control conditions and moderate stress, whereas IR72667-16-1-B-B-3 was stable under both moderate and severe vegetative-stage stress conditions.

Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

USGS Publications Warehouse

Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.

2017-01-01

Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the VegDRI-Canada map with the Canadian Drought Monitor (CDM), an independent drought indicator, showed that the VegDRI-Canada maps depicted key spatial drought severity patterns during the two targeted drought years consistent with the CDM. In addition, VegDRI-Canada was compared with canola yields in the Prairie Provinces at the regional scale for a period from 2000 to 2014 to evaluate the indices’ applicability for monitoring drought impacts on crop production. The result showed that VegDRI-Canada values had a relatively higher correlation (i.e., r > 0.5) with canola yield for nonirrigated croplands in the Canadian Prairies region in areas where drought is typically a limiting factor on crop growth, but showed a negative relationship in the southeastern Prairie region, where water availability is less of a limiting factor and in some cases a hindrance to crop growth when waterlogging occurs. These initial results demonstrate VegDRI-Canada’s utility for monitoring drought-related vegetation conditions, particularly in drought prone areas. In general, the results indicated that the VegDRI-Canada models showed sensitivity to known agricultural drought events in Canada over the 15-year period mainly for nonirrigated areas.

Temporal-spatial characteristics of severe drought events in Southwest China and their relationships to teleconnection indices

NASA Astrophysics Data System (ADS)

Wang, P., III; Wu, C.; Hao, Y.; Xu, K.

2017-12-01

In the process of global warming, the frequency and intensity of a series of climate events (such as, precipitation, flood disaster, climate arid) are also being changed. Even in the today of advanced science and technology, the occurrence and severity of drought in China is still devastating impact on social and economic development. We studied the spatial and temporal variability of drought in southwestern China China and its relationships to teleconnection indices. We used the Palmer Drought Severity Index (PDSI) to investigate the variation in drought in southwestern China between 1961 and 2012 using the Mann-Kendall (MK), continuous wavelet transform (CWT) and the rotated empirical orthogonal function (REOF) methods. Additionally, We analyzed the relationships between the time variability of significant patterns and teleconnection indices. The PDSI shows that there is a trend of turning dry in west Tibet; while it is remarkably drying in junction of Yunnan, Guizhou, Sichuan, Chongqing provinces, and the drought in Spring is more severe than in autumn, with a changing oscillation period of 2-7a. It's found the drought strength reducing before rising without a obvious turning point. Also, the drought frequency staggered in spatial distribution, and a larger inter-annual difference. AO and SS are the most important factors among all the drought influence factors, the others differ from the importance.

Mapping the Distribution of Potential Land Drought in Batam Island Using the Integration of Remote Sensing and Geographic Information Systems (GIS)

NASA Astrophysics Data System (ADS)

Lubis, M. Z.; Taki, H. M.; Anurogo, W.; Pamungkas, D. S.; Wicaksono, P.; Aprilliyanti, T.

2017-12-01

Potential land drought mapping on Batam is needed to determine the distribution of areas that are very potential to the physical drought of the land. It is because the drought is always threatening on the long dry season. This research integrates remote sensing science with Geographic Information System (GIS). This research aims to map the distribution of land drought potential in Batam Island. The parameters used in this research are land use, Land Surface Temperature (LST), Potential dryness of land on the Batam island. The resulting map indicates the existence of five potential drought classes on the island of Batam. The area of very low drought potential is 2629.45 ha, mostly located in the Sungai Beduk sub-district. High drought potential with an area of 7081.39 ha is located in Sekupang sub-district. The distribution of very high land drought potential is in Batam city and Nongsa sub-district with area of 15600.12 ha. The coefficient of determination (R 2) is 0.6279. This indicates a strong positive relationship between field LST and modelled LST.

Drought impact on vegetation growth and mortality

NASA Astrophysics Data System (ADS)

Xu, C.; Wang, M.; Allen, C. D.; McDowell, N. G.; Middleton, R. S.

2017-12-01

Vegetation is a key regulator of the global carbon cycle via CO2 absorption through photosynthesis and subsequent growth; however, low water availability, heat stress, and disturbances associated with droughts could substantially reduce vegetation growth and increase vegetation mortality. As far as we know, there are few studies have assessed the drought impact on vegetation growth and mortality at regional and global scales. In this study, we analyzed 13 Earth System models (ESMs) to quantify the impact of drought on GPP and linked the remote-sensing based tree mortality to observed drought indices to assess the drought impact on tree mortality in continental US (CONUS). Our analysis of 13 Earth System models (ESMs) shows that the average global gross primary production (GPP) reduction per year associated with extreme droughts over years 2075-2099 is predicted to be 3-5 times larger than that over years 1850-1999. The annual drought-associated reduction in GPP over years 2075-2099 could be 52 and 74 % of annual fossil fuel carbon emission during years 2000-2007. Increasing drought impacts on GPP are driven primarily by the increasing drought frequency. The risks of drought-associated GPP reduction are particularly high for temperate and tropical regions. The consistent prediction of higher drought-associated reduction in NPP across 13 ESMs suggests increasing impacts of drought on the global carbon cycle with atmospheric warming. Our analysis of drought impact on tree mortality showed that drought-associated carbon loss accounts for 12% of forest carbon loss in CONUS for 2000-2014, which is about one-fifth of that resulting from timber harvesting and 1.35 % of average annual fossil fuel emissions in the U.S. for the same period. The carbon stock loss from natural disturbances for 2000-2014 is approximately 75% of the total carbon loss from anthropogenic disturbance (timber harvesting), suggesting that natural disturbances play a very important role on forest carbon loss from dead trees. Our results clearly demonstrate the importance of drought impact on forest carbon stocks at the continental level and will provide critical data for future model improvement to better predict the vegetation mortality under droughts.

Epigenetic responses to drought stress in rice (Oryza sativa L.).

PubMed

Gayacharan; Joel, A John

2013-07-01

Cytosine methylation polymorphism plays a key role in gene regulation, mainly in expression of genes in crop plants. The differential expression of cytosine methylation over drought stress response was analyzed in rice using drought susceptible but agronomically superior lines IR 20 and CO 43, and drought tolerant genotypes PL and PMK 3 and their F1 hybrids. The parents and hybrids were subjected to two moisture regimes viz., one under drought condition and another under control condition. The cytosine methylation polymorphism in genomic DNA was quantified under both the conditions at the reproductive stage of the plant using the Methylation Sensitive Amplified Polymorphism (MSAP) technique devised by Xiong et al. (261:439-446, 1999). The results depicted that under drought condition, hyper-methylation was predominant in the drought susceptible genotypes while drought tolerant genotypes presented hypo-methylation behavior. While imposing drought, spikelet sterility per cent was positively correlated to percentage of methylation whereas, panicle length, number of seed per panicle, panicle weight, 100 seed weight, and yield/plant were negatively correlated indicating the role of epigenetic regulation in yield attributing traits in response to drought. Thus, methylation can be considered as an important epigenetic regulatory mechanism in rice plants to adapt drought situation. From this study, we speculate that the hyper- methylation may be an indicator of drought susceptibility and the hypo-methylation for drought tolerance and this methylation polymorphism can be effectively used in drought screening program.

Impacts of droughts on carbon sequestration by China's terrestrial ecosystems from 2000 to 2011

NASA Astrophysics Data System (ADS)

Liu, Y. B.; Zhou, Y. L.; Ju, W. M.; Wang, S. Q.; Wu, X. C.; He, M. Z.

2013-11-01

In recent years, droughts have frequently hit China's terrestrial ecosystems. How these droughts affected carbon sequestration by China's terrestrial ecosystems is still unclear. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model, driven by remotely sensed vegetation parameters, was employed to assess the effects of droughts on net ecosystem productivity (NEP) of terrestrial ecosystems in China for the period from 2000 to 2011. Different categories of droughts, as indicated by a standard precipitation index (SPI), extensively hit terrestrial ecosystems in China, particularly in 2001, 2006, 2009 and 2011. The national total NEP exhibited a slight decline of -11.3 Tg C yr-2 during the study period, mainly due to large reductions of NEP in typical drought-hit years 2001, 2006, 2009 and 2011, ranging from 61.1 Tg C yr-1 to 168.8 Tg C yr-1. National and regional total NEP anomalies were correlated with corresponding annual mean SPI, especially in Northwest China, North China, Central China, and Southwest China. In drought years, the reductions of NEP might be caused by a larger decrease in gross primary productivity (GPP) than in respiration (RE) (2001 and 2011), a decrease in GPP and an increase in RE (2009), or a larger increase in RE than in GPP (2006). Droughts had lagged effects of up to 3-6 months on NEP due to different reactions of GPP and RE to droughts. In east humid and warm parts of China, droughts have predominant and short-term lagged influences on NEP. In western cold and arid regions, the effects of droughts on NEP were relatively weaker and might last for a longer period of time.

Comparison of spatial interpolation methods for soil moisture and its application for monitoring drought.

PubMed

Chen, Hui; Fan, Li; Wu, Wei; Liu, Hong-Bin

2017-09-26

Soil moisture data can reflect valuable information on soil properties, terrain features, and drought condition. The current study compared and assessed the performance of different interpolation methods for estimating soil moisture in an area with complex topography in southwest China. The approaches were inverse distance weighting, multifarious forms of kriging, regularized spline with tension, and thin plate spline. The 5-day soil moisture observed at 167 stations and daily temperature recorded at 33 stations during the period of 2010-2014 were used in the current work. Model performance was tested with accuracy indicators of determination coefficient (R 2 ), mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and modeling efficiency (ME). The results indicated that inverse distance weighting had the best performance with R 2 , MAPE, RMSE, RRMSE, and ME of 0.32, 14.37, 13.02%, 0.16, and 0.30, respectively. Based on the best method, a spatial database of soil moisture was developed and used to investigate drought condition over the study area. The results showed that the distribution of drought was characterized by evidently regional difference. Besides, drought mainly occurred in August and September in the 5 years and was prone to happening in the western and central parts rather than in the northeastern and southeastern areas.

How rural land use management facilitates drought risk adaptation in a changing climate - A case study in arid northern China.

PubMed

Lei, Yongdeng; Zhang, Hailin; Chen, Fu; Zhang, Linbo

2016-04-15

Under a warming climate, frequent drought and water scarcity in northern China have severely disrupted agricultural production and posed a substantial threat to farmers' livelihoods. Based on first-hand data collected through in-depth interviews with local managers and farmer households, this study evaluated the effectiveness of rural land use management in mitigating drought risk, ensuring food security and improving farmers' livelihoods. Our findings indicate that a) reforestation on low-yield cropland not only can improve the eco-environment but can also prominently mitigate the production risk to local farmers; b) replacing the traditional border irrigation with sprinkler irrigation has substantially curbed agricultural water usage and increased the per unit of output; and c) in recent years, instead of planting water-intensive grain crops, local farmers cultivated more forage crops to raise animals, which greatly diversified their income sources and reduced the drought risk of agricultural production. By performing an empirical case study in drought-prone Inner Mongolia, this study provides decision-makers with insights into how to strategically adapt to drought risk and reduce rural poverty within the broader context of climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

Drought in the Rockies

NASA Technical Reports Server (NTRS)

2002-01-01

This image shows the difference between the amount of vegetation in July 2000 and the average July vegetation for North America. Of particular interest are the dry conditions in the western United States. This spring and summer the Rocky Mountains have been relatively dry, and the brown regions stretching from the Canadian to the Mexican border, indicate the effect on the regions' forests. Western Montana and eastern Idaho are particularly parched, and appear darker brown. The dry conditions have contributed to this year's devastating fire season, during which millions of acres have burned in the west. Scientists find that during the growing season, land plants can be used to measure drought. Healthy, thriving plants reflect and absorb visible and near-infrared light differently than plants under stress. These variations in reflectance and absorption can be measured by satellites to produce maps of healthy and stressed vegetation. This image shows Normalized Difference Vegetation Index (NDVI) anomaly, which indicates where vegetation growth was above average (green pixels), below average (brown pixels), or normal (white pixels). For more images and information about measuring vegetation and drought from space visit: Drought and Vegetation Monitoring. Image courtesy NASA Goddard Space Flight Center Biospheric Sciences Branch, based on data from NOAA.

Development and assessment of Transpirative Deficit Index (D-TDI) for agricultural drought monitoring

NASA Astrophysics Data System (ADS)

Borghi, Anna; Rienzner, Michele; Gandolfi, Claudio; Facchi, Arianna

2017-04-01

Drought is a major cause of crop yield loss, both in rainfed and irrigated agroecosystems. In past decades, many approaches have been developed to assess agricultural drought, usually based on the monitoring or modelling of the soil water content condition. All these indices show weaknesses when applied for a real time drought monitoring and management at the local scale, since they do not consider explicitly crops and soil properties at an adequate spatial resolution. This work describes a newly developed agricultural drought index, called Transpirative Deficit Index (D-TDI), and assesses the results of its application over a study area of about 210 km2 within the Po River Plain (northern Italy). The index is based on transforming the interannual distribution of the transpirative deficit (potential crop transpiration minus actual transpiration), calculated daily by means of a spatially distributed conceptual hydrological model and cumulated over user-selected time-steps, to a standard normal distribution (following the approach proposed by the meteorological index SPI - Standard Precipitation Index). For the application to the study area a uniform maize crop cover (maize is the most widespread crop in the area) and 22-year (1993-2014) meteorological data series were considered. Simulation results consist in maps of the index cumulated over 10-day time steps over a mesh with cells of 250 m. A correlation analysis was carried out (1) to study the characteristics and the memory of D-TDI and to assess its intra- and inter-annual variability, (2) to assess the response of the agricultural drought (i.e., the information provided by D-TDI) to the meteorological drought computed through the SPI over different temporal steps. The D-TDI is positively auto-correlated with a persistence of 30 days, and positively cross-correlated to the SPI with a persistence of 40 days, demonstrating that D-TDI responds to meteorological forcing. Correlation analyses demonstrate that soils characterized by high available water content (AWC) can more easily compensate for a short-term variability in the precipitation pattern, while soils with low AWC are more strictly linked to the SPI variability. Since D-TDI relies both on climate and fine-resolution soil and land cover data, it provides a reliable measure of the evolution of agricultural drought over the territory with respect to that achieved through meteorological drought indices. The accumulation of the index over a 10-day period considering a mesh with cells of 250 m allows to capture the response of the territory to drought at time and spatial scales of interest for stakeholders. Modelling efforts utilizing the D-TDI have potential to shed light on the vulnerability of agricultural areas to drought; future work using the D-TDI as a tool to map drought prone areas could therefore improve the ability of farmers and irrigation district managers to cope with agricultural droughts and set up adaptation actions. Despite D-TDI was used in this study on historical data series, the index has the potential to be applied for real-time or provisional monitoring by incorporating real time or provisional meteorological data, giving the opportunity to stakeholders to promptly cope with droughts.

Asian droughts in the last millennium: a search for robust impacts of Pacific Ocean surface temperature variabilities

NASA Astrophysics Data System (ADS)

Yu, Entao; King, Martin P.; Sobolowski, Stefan; Otterå, Odd Helge; Gao, Yongqi

2018-06-01

This study investigates the robustness of hydroclimate impacts in Asia due to major drivers of climate variability in the Pacific Ocean, namely the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Composite analyses are carried out on a tree ring-based Palmer Drought Severity Index as well as on a long coupled global climate model control experiment. El Niño (La Niña) has a robust impact on wet (dry) conditions in West Asia and dry (wet) conditions in South Asia. For the PDO, impacts are found throughout the Asia domain. However, identifying the robust signals due to PDO from these analyses is more challenging due to the limited lengths of the data. Results indicate that West Asia (South and Southeast Asia) experiences wet (dry) conditions during periods of positive PDO. For East Asia, there is indication that positive (negative) PDO is associated with wet (dry) conditions around and southward of 30°N and dry (wet) conditions north of this latitude. This result is consistent with the current understanding of the role of PDO in the "southern-flood northern-drought" phenomenon in China. We suggest that specific extreme events or periods have regional impacts with strong intensities that cannot be fully explained through the composite analysis of ENSO, PDO, or any combination thereof. Two such examples are shown to illustrate this: the Strange Parallel Drought (1756-1768 CE) and the Great Drought (1876-1878 CE). Additionally, during these climate events, ENSO and PDO can be in phases which are not consistent with the required phases of these drivers that explain the concurrent drought and pluvial conditions in Asia. Therefore, not all historical drought and pluvial events in Northeast Asia and northern China can be related back to ENSO or PDO. Finally, we also examine the dynamical characteristics of the reported hydroclimatic impacts in the global climate model experiment. There is moisture transport into (out of) regions that exhibit wet (dry) conditions in a manner consistent with the various ENSO and PDO composites, thereby providing physical explanation of the index-based results.

Molecular and Morpho-Agronomical Characterization of Root Architecture at Seedling and Reproductive Stages for Drought Tolerance in Wheat

PubMed Central

Vinod; Naik, Bhojaraja K.; Chand, Suresh; Deshmukh, Rupesh; Mallick, Niharika; Singh, Sanjay; Singh, Nagendra Kumar; Tomar, S. M. S.

2016-01-01

Water availability is a major limiting factor for wheat (Triticum aestivum L.) production in rain-fed agricultural systems worldwide. Root architecture is important for water and nutrition acquisition for all crops, including wheat. A set of 158 diverse wheat genotypes of Australian (72) and Indian (86) origin were studied for morpho-agronomical traits in field under irrigated and drought stress conditions during 2010–11 and 2011-12.Out of these 31 Indian wheat genotypes comprising 28 hexaploid (Triticum aestivum L.) and 3 tetraploid (T. durum) were characterized for root traits at reproductive stage in polyvinyl chloride (PVC) pipes. Roots of drought tolerant genotypes grew upto137cm (C306) as compared to sensitive one of 63cm with a mean value of 94.8cm. Root architecture traits of four drought tolerant (C306, HW2004, HD2888 and NI5439) and drought sensitive (HD2877, HD2012, HD2851 and MACS2496) genotypes were also observed at 6 and 9 days old seedling stage. The genotypes did not show any significant variation for root traits except for longer coleoptiles and shoot and higher absorptive surface area in drought tolerant genotypes. The visible evaluation of root images using WinRhizo Tron root scanner of drought tolerant genotype HW2004 indicated compact root system with longer depth while drought sensitive genotype HD2877 exhibited higher horizontal root spread and less depth at reproductive stage. Thirty SSR markers were used to study genetic variation which ranged from 0.12 to 0.77 with an average value of 0.57. The genotypes were categorized into three subgroups as highly tolerant, sensitive, moderately sensitive and tolerant as intermediate group based on UPGMA cluster, STRUCTURE and principal coordinate analyses. The genotypic clustering was positively correlated to grouping based on root and morpho-agronomical traits. The genetic variability identified in current study demonstrated these traits can be used to improve drought tolerance and association mapping. PMID:27280445

Modeling seasonal changes in live fuel moisture and equivalent water thickness using a cumulative water balance index

Treesearch

Philip E. Dennison; Dar A. Roberts; Sommer R. Thorgusen; Jon C. Regelbrugge; David Weise; Christopher Lee

2003-01-01

Live fuel moisture, an important determinant of fire danger in Mediterranean ecosystems, exhibits seasonal changes in response to soil water availability. Both drought stress indices based on meteorological data and remote sensing indices based on vegetation water absorption can be used to monitor live fuel moisture. In this study, a cumulative water balance index (...

Analysis of Natural Variation in Bermudagrass (Cynodon dactylon) Reveals Physiological Responses Underlying Drought Tolerance

PubMed Central

Cheng, Zhangmin; Ye, Tiantian; Chan, Zhulong

2012-01-01

Bermudagrass (Cynodon dactylon) is a widely used warm-season turfgrass and one of the most drought tolerant species. Dissecting the natural variation in drought tolerance and physiological responses will bring us powerful basis and novel insight for plant breeding. In the present study, we evaluated the natural variation of drought tolerance among nine bermudagrass varieties by measuring physiological responses after drought stress treatment through withholding water. Three groups differing in drought tolerance were identified, including two tolerant, five moderately tolerant and two susceptible varieties. Under drought stress condition, drought sensitive variety (Yukon) showed relative higher water loss, more severe cell membrane damage (EL), and more accumulation of hydrogen peroxide (H2O2) and malondialdehyde (MDA), while drought tolerant variety (Tifgreen) exhibited significantly higher antioxidant enzymes activities. Further results indicated that drought induced cell injury in different varieties (Yukon, SR9554 and Tifgreen) exhibited liner correlation with leaf water content (LWC), H2O2 content, MDA content and antioxidant enzyme activities. Additionally, Tifgreen plants had significantly higher levels of osmolytes (proline level and soluble sugars) when compared with Yukon and SR9554 under drought stress condition. Taken together, our results indicated that natural variation of drought stress tolerance in bermudagrass varieties might be largely related to the induced changes of water status, osmolyte accumulation and antioxidant defense system. PMID:23285294

A component-based system for agricultural drought monitoring by remote sensing.

PubMed

Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

A component-based system for agricultural drought monitoring by remote sensing

PubMed Central

Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China’s Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring. PMID:29236700

7 CFR 759.3 - Abbreviations and definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., as a result of the natural disaster. U.S. Drought Monitor is a system for classifying drought severity according to a range of abnormally dry to exceptional drought. It is a collaborative effort..., outlooks, and drought impacts on a map and in narrative form. This synthesis of indices is reported by the...

7 CFR 759.3 - Abbreviations and definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., as a result of the natural disaster. U.S. Drought Monitor is a system for classifying drought severity according to a range of abnormally dry to exceptional drought. It is a collaborative effort..., outlooks, and drought impacts on a map and in narrative form. This synthesis of indices is reported by the...

Short-term Drought Prediction in India.

NASA Astrophysics Data System (ADS)

Shah, R.; Mishra, V.

2014-12-01

Medium range soil moisture drought forecast helps in decision making in the field of agriculture and water resources management. Part of skills in medium range drought forecast comes from precipitation. Proper evaluation and correction of precipitation forecast may improve drought predictions. Here, we evaluate skills of ensemble mean precipitation forecast from Global Ensemble Forecast System (GEFS) for medium range drought predictions over India. Climatological mean (CLIM) of historic data (OBS) are used as reference forecast to evaluate GEFS precipitation forecast. Analysis was conducted based on forecast initiated on 1st and 15th dates of each month for lead up to 7-days. Correlation and RMSE were used to estimate skill scores of accumulated GEFS precipitation forecast from lead 1 to 7-days. Volumetric indices based on the 2X2 contingency table were used to check missed and falsely predicted historic volume of daily precipitation from GEFS in different regions and at different thresholds. GEFS showed improvement in correlation of 0.44 over CLIM during the monsoon season and 0.55 during the winter season. Lower RMSE was showed by GEFS than CLIM. Ratio of RMSE in GEFS and CLIM comes out as 0.82 and 0.4 (perfect skill is at zero) during the monsoon and winter season, respectively. We finally used corrected GEFS forecast to derive the Variable Infiltration Capacity (VIC) model, which was used to develop short-term forecast of hydrologic and agricultural (soil moisture) droughts in India.

Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study

NASA Astrophysics Data System (ADS)

Mishra, Ashok K.; Ines, Amor V. M.; Das, Narendra N.; Prakash Khedun, C.; Singh, Vijay P.; Sivakumar, Bellie; Hansen, James W.

2015-07-01

Drought is of global concern for society but it originates as a local problem. It has a significant impact on water quantity and quality and influences food, water, and energy security. The consequences of drought vary in space and time, from the local scale (e.g. county level) to regional scale (e.g. state or country level) to global scale. Within the regional scale, there are multiple socio-economic impacts (i.e., agriculture, drinking water supply, and stream health) occurring individually or in combination at local scales, either in clusters or scattered. Even though the application of aggregated drought information at the regional level has been useful in drought management, the latter can be further improved by evaluating the structure and evolution of a drought at the local scale. This study addresses a local-scale agricultural drought anatomy in Story County in Iowa, USA. This complex problem was evaluated using assimilated AMSR-E soil moisture and MODIS-LAI data into a crop model to generate surface and sub-surface drought indices to explore the anatomy of an agricultural drought. Quantification of moisture supply in the root zone remains a gray area in research community, this challenge can be partly overcome by incorporating assimilation of soil moisture and leaf area index into crop modeling framework for agricultural drought quantification, as it performs better in simulating crop yield. It was noted that the persistence of subsurface droughts is in general higher than surface droughts, which can potentially improve forecast accuracy. It was found that both surface and subsurface droughts have an impact on crop yields, albeit with different magnitudes, however, the total water available in the soil profile seemed to have a greater impact on the yield. Further, agricultural drought should not be treated equal for all crops, and it should be calculated based on the root zone depth rather than a fixed soil layer depth. We envisaged that the results of this study will enhance our understanding of agricultural droughts in different parts of the world.

The hydroclimatology of UK droughts: evidence from newly recovered and reconstructed datasets from the late 19th century to present

NASA Astrophysics Data System (ADS)

Smith, K. A.; Hannaford, J.; Bloomfield, J.; McCarthy, M.; Parry, S.; Barker, L. J.; Svensson, C.; Tanguy, M.; Marchant, B.; McKenzie, A.; Legg, T.; Prudhomme, C.

2017-12-01

While the UK is regarded as a wet country, it has periodically suffered from major droughts which have caused serious environmental and societal impacts. Parts of the UK are water stressed and, in a warming world, changes to supply/demand balances could have major implications. There is a pressing need for improved tools for drought risk assessment, which is contingent on a proper understanding of past occurrence of droughts. However, our understanding of hydrological drought occurrence is grounded in the post-1960 period when most UK river flow and groundwater records commenced. As such, water resources planners would benefit from a more thorough assessment of historical drought characteristics and their variability. The multi-disciplinary `Historic Droughts' project thus aims to rigorously characterise droughts in the UK back to the 1890s to inform improved drought management. The foundation of this is a comprehensive characterisation of the hydroclimatology of UK droughts. Here, we present the results of this initiative, based on a hydrological reconstruction campaign of unparalleled scope and detail. Driven by rainfall and potential evapotranspiration data, extended in time using newly recovered observational records, hydro(geo)logical models are used to reconstruct, back to 1890, river flows for >300 catchments across the UK, and groundwater levels from >50 boreholes. The reconstructions are derived within a state-of-the-art modelling framework which allows a comprehensive assessment of uncertainty. A suite of indicators are then applied to these datasets to identify and characterise drought events, integrating precipitation, evapotranspiration, streamflow and groundwater. The work provides new insights into the spatial and temporal dynamics of hitherto poorly quantified late 19th and early 20th century droughts. Similarly, the assessment of temporal variability of drought characteristics benefits from the long timescale of the reconstructions, in turn allowing improved assessment of the large-scale climate drivers of UK droughts. The propagation of UK drought is analysed comprehensively for the first time, highlighting the differential spatio-temporal expression of meteorological, streamflow and groundwater droughts, with important implications for water resources management.

How Does Drought Change With Climate Change

NASA Astrophysics Data System (ADS)

Trenberth, K. E.

2014-12-01

Large disparities among published studies have led to considerable confusion over the question of how drought is changing and how it is expected to change with global warming. As a result the IPCC AR5 assessment has watered down statements, and failed to carry out an adequate assessment of the sources of the discrepancies. Quite aside from the different definitions of drought related to meteorological (absence of precipitation), hydrological (lack of water in lakes and rivers), and agricultural (lack of soil moisture) drought, there are many indices that measure drought. Good homogeneous datasets are essential to assess changes over time, but are often not available. Simpler indices may miss effects of certain physical processes, such as evapotranspiration (ET). The Palmer Drought Severity Index (PDSI) has been much maligned but has considerable merit because it can accommodate different ET formulations (e.g., Thornthwaite vs Penman-Monteith), it can be self calibrating to accommodate different regions, and it carries out a crude moisture balance. This is in contrast to simpler indices, such as the Standardized Precipitation Index, which provides only a measure of moisture supply, or the Standardized Precipitation Evapotranspiration Index, which also includes potential (but not actual) ET. The largest source of drought variations is ENSO: during La Niña more rain falls on land while during El Niño most precipitation is over the Pacific Ocean, exposing more land to drought conditions. It is essential to account for interannual and inter-decadal variability in assessing changes in drought with climate change. Yet drought is one time on land when effects accumulate, with huge consequences for wild fire risk. It is important to ask the right questions in dealing with drought.

Risk identification of agricultural drought for sustainable agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-04-01

Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20 year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Exploring the Components of the Palmer Drought Indices Using the Apalachicola-Chattahoochee-Flint (ACF) River Basin as a Case Study

NASA Astrophysics Data System (ADS)

Perrone, D.; Duncan, L. L.; Jacobi, J. H.; Hornberger, G.

2012-12-01

Water resources are vital to sustaining ecosystem services, energy and food supplies, and industrial processes. Competition for water resources is likely to intensify as the population increases, economy grows, and land develops. Drought events intensify water scarcity, and recent events in many countries, including the United States (US), Great Britain, and Sri Lanka, highlight how important it is to provide meaningful context to water planners and managers. Palmer's drought indices - Z Index, Palmer Drought Severity Index (PDSI), and Palmer Hydrological Drought Index (PHDI) - are widely used and accepted by scientists and policy makers in the US to understand drought and manage water resources. Drought index values at the climate division scale are available, but a transparent calculation tool at multiple spatial and temporal scales is not readily available. Moreover, a close look at the development of the indices reveals a number of subjective calculation methods and regionally biased factors. For researchers studying areas with overlapping climate divisions, performing international research, or working with limited, site-specific data, the ability to control and modify calculations is desired. This research presents a transparent tool for calculating Palmer's drought indices. We use the Apalachicola-Chattahoochee-Flint (ACF) River Basin, located in the southeastern US, as our case study to explore and evaluate the sensitivity of Palmer's indices to temperature and precipitation anomalies, calibration periods, and other index components. The ACF has suffered two major droughts (2007 and 2012) in the past five years and supports multiple demand-side sectors - agriculture in Georgia, public and recreational supply for the Atlanta metropolitan area, hydroelectric power in Alabama, tri-state navigation, and ecosystem services. We show how the PDSI varies in response to changes in precipitation, calibration period, and a number of other variables. The aim of the work is to make this easily used tool available to help professionals who work toward facilitating water management and reducing water conflicts in the future.

Droughts in the US: Modeling and Forecasting for Agriculture-Water Management and Adaptation

NASA Astrophysics Data System (ADS)

Perveen, S.; Devineni, N.; Lall, U.

2012-12-01

More than half of all US counties are currently mired in a drought that is considered the worst in decades. A persistent drought can not only lead to widespread impacts on water access with interstate implications (as has been shown in the Southeast US and Texas), chronic scarcity can emerge as a risk in regions where fossil aquifers have become the primary source of supply and are being depleted at rates much faster than recharge (e.g., Midwestern US). The standardized drought indices on which the drought declarations are made in the US so far consider only the static decision frameworks—where only the supply is the control variable and not the water consumption. If a location has low demands, drought as manifest in the usual indices does not really have "proportionate" social impact. Conversely, a modest drought as indicated by the traditional measures may have significant impacts where demand is close to the climatological mean value of precipitation. This may also lead to drought being declared too late or too soon. Against this fact, the importance of improved drought forecasting and preparedness for different sectors of the economy becomes increasingly important. The central issue we propose to address through this paper is the construction and testing of a drought index that considers regional water demands for specific purposes (e.g., crops, municipal use) and their temporal distribution over the year for continental US. Here, we have highlighted the use of the proposed index for three main sectors: (i) water management organizations, (ii) optimizing agricultural water use, and (iii) supply chain water risk. The drought index will consider day-to-day climate variability and sectoral demands to develop aggregate regional conditions or disaggregated indices for water users. For the daily temperature and precipitation data, we are using NLDAS dataset that is available from 1949 onwards. The national agricultural statistics services (NASS) online database has been accessed for the agricultural data at the county level. Preliminary analyses show that large parts of Midwest and Southern parts of Florida and California are prone to multiyear droughts. This can primarily be attributed to high agricultural and/or urban water demands coupled with high interannual variability in supply. We propose to develop season-ahead and monthly updated forecasts of the drought index for informing the drought management plans. Given the already customized (sector specific) nature of the proposed drought index and its ability to represent the variability in both supply and demand, the early warning or forecasting of the index would not only complement the drought early warning systems in place by the national integrated drought information system (NIDIS) but also help in prescribing the ameliorative measures for adaptation.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

USGS Publications Warehouse

Funk, Christopher C.; Hoell, Andrew; Shukla, Shraddhanand; Blade, Ileana; Liebmann, Brant; Roberts, Jason B.; Robertson, Franklin R.

2014-01-01

In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.

Multi-Scale Drought Analysis using Thermal Remote Sensing: A Case Study in Georgia’s Altamaha River Watershed

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Bhat, S.; Choi, M.; Mecikalski, J. R.; Anderson, M. C.

2009-12-01

The unprecedented recent droughts in the Southeast US caused reservoir levels to drop dangerously low, elevated wildfire hazard risks, reduced hydropower generation and caused severe economic hardships. Most drought indices are based on recent rainfall or changes in vegetation condition. However in heterogeneous landscapes, soils and vegetation (type and cover) combine to differentially stress regions even under similar weather conditions. This is particularly true for the heterogeneous landscapes and highly variable rainfall in the Southeastern United States. This research examines the spatiotemperal evolution of watershed scale drought using a remotely sensed stress index. Using thermal-infrared imagery, a fully automated inverse model of Atmosphere-Land Exchange (ALEXI), GIS datasets and analysis tools, modeled daily surface moisture stress is examined at a 10-km resolution grid covering central to southern Georgia. Regional results are presented for the 2000-2008 period. The ALEXI evaporative stress index (ESI) is compared to existing regional drought products and validated using local hydrologic measurements in Georgia’s Altamaha River watershed at scales from 10 to 10,000 km2.

Using the PDSI to Estimate Summer Stream Discharge in the Greater Yellowstone Ecosystem: Implications for 20th Century Riparian Habitat Variability

NASA Astrophysics Data System (ADS)

Persico, L.; Meyer, G. A.

2013-12-01

Small streams at lower elevations in the Greater Yellowstone Ecosystem (GYE) create riparian habitat in an otherwise dry environment. Riparian area can be expanded by beaver damming, which increases channel wetted area and local water tables, and allows fine-grained organic-rich sediment to accumulate. However, increases can be countered by severe drought. The loss of riparian area is potentially greatest in small basins dependent on snowpack for base flow, where prolonged severe drought may reduce base flow to zero. Discharge records are often lacking for basins < 20 km^2, making it difficult to directly examine how climate has impacted flow. The Palmer Drought Severity Index (PDSI) is a useful proxy for large-scale variations in available moisture. PDSI values for climate divisions are estimated from spatially weighted weather station measurements of temperature and precipitation. We use divisional PDSI values to estimate discharge on GYE small streams since 1900. USGS stream-gauge sites were regressed with the corresponding PDSI for each climate division. We also use a regional (2.5° by 2.5°) reconstruction of the PDSI based on 30 tree ring chronologies (Cook et al., 2004) to estimate discharge during the most severe two and ten year droughts (AD 1150-1151 and 805-796, respectively) during the Medieval Climatic Anomaly (MCA). The MCA is a period of high climate variability and widespread drought in the GYE. Significant correlations between stream discharge and the PDSI occur during the late summer and early fall and the strongest correlation between discharge and the PDSI occurs for the 3-month PDSI average centered on August. Stream-gauge records with bootstrapped correlation values greater than 0.65 were chosen for regression analyses. To estimate stream flows for ungauged stream reaches, stepwise multiple regression analyses were performed using measured stream flows and independent basin characteristics. Basin area and mean elevation are significant predictors of discharge (α < 0.05). The 1930s Dust Bowl drought was one of the most severe droughts in the past 300 years; from 1934-1935, average August discharge was reduced by 25-40% with respect to the anomalously wet early 20th century pluvial. Discharge estimates using reconstructed PDSI values for the 2- and 10-year MCA droughts (PDSI = -6 and -5, respectively) indicate that 60% of stream reaches where beaver were active in the late Holocene became ephemeral in these droughts. This analysis is supported by observations during the extreme drought of the 2000s, when ephemeral flow occurred along streams with known historical beaver activity in northern Yellowstone. Model predictions indicate that by 2030-2039 the GYE will endure persistent severe drought (mean annual PDSI = -4 to -6) (Dai, 2011), thus riparian area is likely to decrease in the coming decades. The early 20th century has been suggested to be an ideal reference for riparian habitat restoration despite anomalously wet conditions unlike current or likely future climate. Future efforts to restore riparian habitat by reducing elk browsing and increasing beaver damming will be hampered by reduced flows on small streams.

Associations of multi-decadal sea-surface temperature variability with US drought

USGS Publications Warehouse

McCabe, G.J.; Betancourt, J.L.; Gray, S.T.; Palecki, M.A.; Hidalgo, H.G.

2008-01-01

Recent research suggests a link between drought occurrence in the conterminous United States (US) and sea surface temperature (SST) variability in both the tropical Pacific and North Atlantic Oceans on decadal to multidecadal (D2M) time scales. Results show that the Atlantic Multidecadal Oscillation (AMO) is the most consistent indicator of D2M drought variability in the conterminous US during the 20th century, but during the 19th century the tropical Pacific is a more consistent indicator of D2 M drought. The interaction between El Nin??o-Southern Oscillation (ENSO) and the AMO explain a large part of the D2M drought variability in the conterminous US. More modeling studies are needed to reveal possible mechanisms linking low-frequency ENSO variability and the AMO with drought in the conterminous US. ?? 2007 Elsevier Ltd and INQUA.

A return to the genetic heritage of durum wheat to cope with drought heightened by climate change.

PubMed

Slama, Amor; Mallek-Maalej, Elhem; Ben Mohamed, Hatem; Rhim, Thouraya; Radhouane, Leila

2018-01-01

The objective of this work was to perform a comparative analysis of the physiological, biochemical and agronomical parameters of recent and heritage durum wheat cultivars (Triticum durum Desf.) under water-deficit conditions. Five cultivars were grown under irrigated (control) and rainfall (stressed) conditions. Different agro-physiological and biochemical parameters were studied: electrolyte leakage, relative water content, chlorophyll fluorescence, proline, soluble sugars, specific peroxidase activity, yield and drought stress indices. It was revealed that a water deficit increased proline content, electrolyte leakage, soluble sugars and specific peroxidase activity and decreased relative water content, fluorescence and grain yield. According to these parameters and drought stress indices, our investigation indicated that old cultivars are the best-adapted to local conditions and showed characteristics of drought tolerance, while recent cultivars showed more drought susceptibility. Therefore, local cultivars of each country should be kept by farmers and plant breeders to preserve their genetic heritage.

Tree-ring based February-April precipitation reconstruction for the lower reaches of the Yangtze River, southeastern China

NASA Astrophysics Data System (ADS)

Shi, Jiangfeng; Lu, Huayu; Li, Jinbao; Shi, Shiyuan; Wu, Shuangye; Hou, Xinyuan; Li, Lingling

2015-08-01

February-April drought strongly affects agriculture and socio-economics in southeastern China, yet its long-term variability has not been assessed due to the shortness of instrumental records. In this study, we reported a 168-year tree-ring width chronology from a steep, low-elevation site with thin soil layers in the Xianxia Mountains, southeastern China. Contrary to the existing chronologies that are mostly temperature sensitive, this chronology contained a strong February-April precipitation signal, indicating great potential for tree-ring based precipitation reconstructions in southeastern China. The reconstruction explained 47.8% of the instrumental variance during 1951-2012. The full reconstruction indicated that there were 3 dry periods (1873-1896, 1924-1971, 1995-2012) and 2 wet periods (1856-1872, 1972-1994) during 1856-2013. The extreme drought in 2011 was not unprecedented for the past 168 years, and the recent severe droughts may be part of interdecadal variations in regional February-April precipitation. Our results also suggested that February-April precipitation in southeastern China was highly influenced by the tropical Pacific climate system, in particular El Niño-Southern Oscillation (ENSO).

The impact exploration of agricultural drought on winter wheat yield in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui

2017-04-01

Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive correlation (p<0.01), which may provide a way to quantitatively evaluate the winter wheat yield losses caused by drought. Key words: drought, winter wheat yield, SPEI, EPIC, the North China Plain

Evolutionary trade-offs between drought resistance mechanisms across a precipitation gradient in a seasonally dry tropical oak (Quercus oleoides).

PubMed

Ramírez-Valiente, Jose A; Cavender-Bares, Jeannine

2017-07-01

In seasonally dry tropical forest regions, drought avoidance during the dry season coupled with high assimilation rates in the wet season is hypothesized to be an advantageous strategy for forest trees in regions with severe and long dry seasons. In contrast, where dry seasons are milder, drought tolerance coupled with a conservative resource-use strategy is expected to maximize carbon assimilation throughout the year. Tests of this hypothesis, particularly at the intraspecific level, have been seldom conducted. In this study, we tested the extent to which drought resistance mechanisms and rates of carbon assimilation have evolved under climates with varying dry season length and severity within Quercus oleoidesCham. and Schlect., a tropical dry forest species that is widely distributed in Central America. For this purpose, we conducted a greenhouse experiment where seedlings originating from five populations that vary in rainfall patterns were grown under different watering treatments. Our results revealed that populations from xeric climates with more severe dry seasons exhibited large mesophyllous leaves (with high specific leaf area, SLA), and leaf abscission in response to drought, consistent with a drought-avoidance strategy. In contrast, populations from more mesic climates with less severe dry seasons had small and thick sclerophyllous leaves with low SLA and reduced water potential at the turgor loss point (πtlp), consistent with a drought-tolerance strategy. Mesic populations also showed high plasticity in πtlp in response to water availability, indicating that osmotic adjustment to drought is an important component of this strategy. However, populations with mesophyllous leaves did not have higher maximum carbon assimilation rates under well-watered conditions. Furthermore, SLA was negatively associated with mass-based photosynthetic rates, contrary to expectations of the leaf economics spectrum, indicating that drought-resistance strategies are not necessarily tightly coupled with resource-use strategies. Overall, our study demonstrates the importance of considering intraspecific variation in analyses of the vulnerability of tropical trees to climate change. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Huning, L. S.; Love, C. A.; Farahmand, A.

2017-12-01

This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. Satellite observations that are not currently used for operational drought monitoring, such as near-surface air relative humidity and water vapor, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. This presentation describes how different satellite observations can be combined for overall drought development and impact assessment. Finally, we provide an overview of the research gaps and challenges that are facing us ahead in the remote sensing of drought.

Estimation of droughts indicators in the Veguita zone, Cuba

NASA Astrophysics Data System (ADS)

Cumbrera, Ramiro; Millán Vega, Humberto; Tarquis, Ana Maria; Alcolea Naranjo, Osvaldo

2016-04-01

This work has as essential objective the evaluation and analysis of the main indicators of hydrometeorology drought in Veguita, using series of daily precipitations, daily temperature and intensity of the rain. These data were contributed by the Station Agrometeorológica of Veguitas. The estimated indexes were the concentration of precipitations (CP) and the standardized index of precipitation and evapotranspiration (SPEI). The CP was calculated by means of the calculation of the index of Gini, based on the curve of Lorentz using data from 1994 until 2013. The SPEI was calculated with the software of the same name using the data from 2001 up to 2013. The main result obtained was that the precipitations in the area are concentrating, in accordance with the index of Gini and the exponential adjustment of the curve of Lorentz. Beside it, gusts dry superiors to one month were detected and the SPEI pointed out 35 months with drought, 40 humid and 81 with normal levels of rain in the last 13 years.

Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest

USGS Publications Warehouse

Steinman, Byron A.; Abbott, Mark B.; Mann, Michael E.; Ortiz, Joseph D.; Feng, Song; Pompeani, David P.; Stansell, Nathan D.; Anderson, Lesleigh; Finney, Bruce P.; Bird, Broxton W.

2014-01-01

Reconstructing centennial timescale hydroclimate variability during the late Holocene is critically important for understanding large-scale patterns of drought and their relationship with climate dynamics. We present sediment oxygen isotope records spanning the last two millennia from 10 lakes, as well as climate model simulations, indicating that the Little Ice Age was dry relative to the Medieval Climate Anomaly in much of the Pacific Northwest of North America. This pattern is consistent with observed associations between the El Niño Southern Oscillation (ENSO), the Northern Annular Mode and drought as well as with proxy-based reconstructions of Pacific ocean-atmosphere variations over the past 1000 years. The large amplitude of centennial variability indicated by the lake data suggests that regional hydroclimate is characterized by longer-term shifts in ENSO-like dynamics, and that an improved understanding of the centennial timescale relationship between external forcing and drought conditions is necessary for projecting future hydroclimatic conditions in western North America.

Seasonal photosynthetic responses of European oaks to drought and elevated daytime temperature.

PubMed

Arend, M; Brem, A; Kuster, T M; Günthardt-Goerg, M S

2013-01-01

Oaks are commonly considered as drought- and heat-tolerant trees that might benefit from a warmer and drier climate. Their tolerance to drought has been frequently studied in the past, whereas studies dealing with elevated temperature or its combination with drought are very limited in number. In this study we investigated seasonal photosynthetic patterns in three European oak species (Quercus robur, Q. petraea, Q. pubescens) exposed in lysimeter-based open-top chambers (OTC) to elevated daytime temperature, drought and their combination. Stomatal and non-stomatal traits of photosynthesis were followed over an entire growing season and related to changes in daytime temperature, soil moisture and pre-dawn leaf water potential (Ψ(PD) ). Elevated daytime temperature enhanced net photosynthesis (P(N) ) in a season-dependent manner, with higher mid-summer rates than in controls exposed to ambient temperature. Drought imposed in early and mid-summer reduced the soil moisture content and caused a gradual decline in Ψ(PD) , stomatal conductance (g(S) ) and P(N) . Drought effects on Ψ(PD) and P(N) were exacerbated when drought was combined with elevated daytime temperature. In general, P(N) tended to be more affected by low soil moisture content or low Ψ(PD) in Q. robur than in Q. petraea and Q. pubescens. Non-stomatal limitations may have contributed to the drought-induced decline of P(N) in Q. robur, as indicated by a down-regulation of PSII photochemistry (F(V) /F(M) ) and decreased chlorophyll content. Taken together, our findings show that European oaks may benefit from elevated temperature, but detrimental effects can be expected when elevated temperature occurs simultaneously with drought. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

How Much Water Trees Access and How It Determines Forest Response to Drought

NASA Astrophysics Data System (ADS)

Berdanier, A. B.; Clark, J. S.

2015-12-01

Forests are transformed by drought as water availability drops below levels where trees of different sizes and species can maintain productivity and survive. Physiological studies have provided detailed understanding of how species differences affect drought vulnerability but they offer almost no insights about the amount of water different trees can access beyond general statements about rooting depth. While canopy architecture provides strong evidence for light availability aboveground, belowground moisture availability remains essentially unknown. For example, do larger trees always have greater access to soil moisture? In temperate mixed forests, the ability to access a large soil moisture pool could minimize damage during drought events and facilitate post-drought recovery, potentially at the expense of neighboring trees. We show that the pool of accessible soil moisture can be estimated for trees with data on whole-plant transpiration and that this data can be used to predict water availability for forest stands. We estimate soil water availability with a Bayesian state-space model based on a simple water balance, where cumulative depressions in water use below potential transpiration indicate soil resource depletion. We compare trees of different sizes and species, extend these findings to the entire stand, and connect them to our recent research showing that tree survival after drought depends on post-drought growth recovery and local moisture availability. These results can be used to predict competitive abilities for soil water, understand ecohydrological variation within stands, and identify trees that are at risk of damage from future drought events.

Precursor conditions related to Zimbabwe's summer droughts

NASA Astrophysics Data System (ADS)

Nangombe, Shingirai; Madyiwa, Simon; Wang, Jianhong

2018-01-01

Despite the increasing severity of droughts and their effects on Zimbabwe's agriculture, there are few tools available for predicting these droughts in advance. Consequently, communities and farmers are more exposed, and policy makers are always ill prepared for such. This study sought to investigate possible cycles and precursor meteorological conditions prior to drought seasons that could be used to predict impending droughts in Zimbabwe. The Single Z-Index was used to identify and grade drought years between 1951 and 2010 according to rainfall severity. Spectral analysis was used to reveal the cycles of droughts for possible use of these cycles for drought prediction. Composite analysis was used to investigate circulation and temperature anomalies associated with severe and extreme drought years. Results indicate that severe droughts are more highly correlated with circulation patterns and embedded weather systems in the Indian Ocean and equatorial Pacific Ocean than any other area. This study identified sea surface temperatures in the average period June to August, geopotential height and wind vector in July to September period, and air temperature in September to November period as precursors that can be used to predict a drought occurrence several months in advance. Therefore, in addition to sea surface temperature, which was identified through previous research for predicting Zimbabwean droughts, the other parameters identified in this study can aid in drought prediction. Drought cycles were established at 20-, 12.5-, 3.2-, and 2.7-year cycles. The spectral peaks, 12.5, 3.2, and 2.7, had a similar timescale with the luni-solar tide, El Niño Southern Oscillation and Quasi Biennial Oscillation, respectively, and hence, occurrence of these phenomena have a possibility of indicating when the next drought might be.

How well do CMIP5 climate simulations replicate historical trends and patterns of droughts?

DOE PAGES

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin; ...

2015-04-26

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Technical Reports Server (NTRS)

Rosevelt, Carolyn; Melton, Forrest S.; Johnson, Lee; Guzman, Alberto; Verdin, James P.; Thenkabail, Prasad S.; Mueller, Rick; Jones, Jeanine; Willis, Patrick

2016-01-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Guzman, A.; Verdin, J. P.; Thenkabail, P. S.; Mueller, R.; Jones, J.; Willis, P.

2015-12-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March - September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

The complex influence of ENSO on droughts in Ecuador

NASA Astrophysics Data System (ADS)

Vicente-Serrano, S. M.; Aguilar, E.; Martínez, R.; Martín-Hernández, N.; Azorin-Molina, C.; Sanchez-Lorenzo, A.; El Kenawy, A.; Tomás-Burguera, M.; Moran-Tejeda, E.; López-Moreno, J. I.; Revuelto, J.; Beguería, S.; Nieto, J. J.; Drumond, A.; Gimeno, L.; Nieto, R.

2017-01-01

In this study, we analyzed the influence of El Niño-Southern Oscillation (ENSO) on the spatio-temporal variability of droughts in Ecuador for a 48-year period (1965-2012). Droughts were quantified from 22 high-quality and homogenized time series of precipitation and air temperature by means of the Standardized Precipitation Evapotranspiration Index. In addition, the propagation of two different ENSO indices (El Niño 3.4 and El Niño 1 + 2 indices) and other atmospheric circulation processes (e.g., vertical velocity) on different time-scales of drought severity were investigated. The results showed a very complex influence of ENSO on drought behavior across Ecuador, with two regional patterns in the evolution of droughts: (1) the Andean chain with no changes in drought severity, and (2) the Western plains with less severe and frequent droughts. We also detected that drought variability in the Andes mountains is explained by the El Niño 3.4 index [sea surface temperature (SST) anomalies in the central Pacific], whereas the Western plains are much more driven by El Niño 1 + 2 index (SST anomalies in the eastern Pacific). Moreover, it was also observed that El Niño and La Niña phases enhance droughts in the Andes and Western plains regions, respectively. The results of this work could be crucial for predicting and monitoring drought variability and intensity in Ecuador.

[Physiological responses of mycorrhizal Pinus massoniana seedlings to drought stress and drought resistance evaluation].

PubMed

Wang, Yi; Ding, Gui-jie

2013-03-01

A greenhouse pot experiment was conducted to study the effects of inoculating Pisolithus tinctorius, Cenococcum geophilum, Cantharellus cibarius, and Suillus luteus on the physiological characteristics of Pinus massoniana seedlings under the conditions of drought stress and re-watering, with the drought resistance of the mycorrhizal seedlings evaluated. Under drought stress, the MDA content and membrane' s relative permeability of P. massoniana seedlings increased, but these two indices in the inoculated (mycorrhizal) seedlings were significantly lower than these in the un-inoculated (control) seedlings. After re-watering, the MDA content and membrane's relative permeability of mycorrhizal seedlings had a rapid decrease, as compared with the control. In the first 21 days of drought stress, the production rate of superoxide radical of the seedlings increased, and the SOD, POD and NR activities of mycorrhizal seedlings increased significantly. With the extending of drought stress, the seedlings after re-watering had different recovery ability. Under the re-watering after 14 days drought stress, the SOD, POD and NR activities recovered. The drought resistance of the mycorrhizal seedlings was in the order of Suillus luteus 1 > Suillus luteus 7 > Cantharellus cibarius > Cenococcum geophilum > Pisolithus tinctorius. The SOD and MDA activities had a greater correlation with the mycorrhizal seedlings drought resistance, being able to be used as the indicators to evaluate the drought resistance of mycorrhizal seedlings.

Change in hydraulic properties and leaf traits in a tall rainforest tree species subjected to long-term throughfall exclusion in the perhumid tropics

NASA Astrophysics Data System (ADS)

Schuldt, B.; Leuschner, C.; Horna, V.; Moser, G.; Köhler, M.; van Straaten, O.; Barus, H.

2011-08-01

A large-scale replicated throughfall exclusion experiment was conducted in a pre-montane perhumid rainforest in Sulawesi (Indonesia) exposing the trees for two years to pronounced soil desiccation. The lack of regularly occurring dry periods and shallow rooting patterns distinguish this experiment from similar experiments conducted in the Amazonian rainforest. We tested the hypotheses that a tree's sun canopy is more affected by soil drought than its shade crown, making tall trees particularly vulnerable even under a perhumid climate, and that extended drought periods stimulate an acclimation in the hydraulic system of the sun canopy. In the abundant and tall tree species Castanopsis acuminatissima (Fagaceae), we compared 31 morphological, anatomical, hydraulic and chemical variables of leaves, branches and the stem together with stem diameter growth between drought and control plots. There was no evidence of canopy dieback. However, the drought treatment led to a 30 % reduction in sapwood-specific hydraulic conductivity of sun canopy branches, possibly caused by the formation of smaller vessels and/or vessel filling by tyloses. Drought caused an increase in leaf size, but a decrease in leaf number, and a reduction in foliar calcium content. The δ13C and δ18O signatures of sun canopy leaves gave no indication of a permanent down-regulation of stomatal conductance during the drought, indicating that pre-senescent leaf shedding may have improved the water status of the remaining leaves. Annual stem diameter growth decreased during the drought, while the density of wood in the recently produced xylem increased in both the stem and sun canopy branches (marginally significant). The sun canopy showed a more pronounced drought response than the shade crown indicating that tall trees with a large sun canopy are more vulnerable to drought stress. We conclude that the extended drought prompted a number of medium- to long-term responses in the leaves, branches and the trunk, which may have reduced drought susceptibility. However, unlike a natural drought, our drought simulation experiment was carried out under conditions of high humidity, which may have dampened drought induced damages.

The compensation effects of physiology and yield in cotton after drought stress.

PubMed

Niu, Jing; Zhang, Siping; Liu, Shaodong; Ma, Huijuan; Chen, Jing; Shen, Qian; Ge, Changwei; Zhang, Xiaomeng; Pang, Chaoyou; Zhao, Xinhua

The objective of this study was to investigate the root growth compensatory effects and cotton yield under drought stress. The results indicate that the root dry weight, boll weight, and cotton yield increased in both the drought-resistant cultivar (CCRI-45) and the drought-sensitive cultivar (CCRI-60). Compensation effects were exhibited under the three-day drought stress treatment at a soil relative water content (SRWC) of 60% and 45% during the seedling stage, and flowering and boll-forming stage over two years. The yield of the drought-resistant cultivar (CCRI-45) was higher than the control, however, following the six-day 45% SRWC drought treatments, the yield of the drought-sensitive cultivar (CCRI-60) was lower than the control. The soluble sugar content, proline content, superoxide dismutase (SOD) activity, and peroxidase (POD) activity of the roots increased under drought stress and then decreased after re-watering, although the values remained higher than those of the controls for a short period. These physiological measures may represent stress reactions and thus may not indicate factors that result in compensation effects. However, catalase (CAT) activity and gibberellic acid (GA) content of the roots decreased under drought stress. After re-watering, the CAT activity and the GA content increased and were significantly higher than those of the controls under the six-day 60% SRWC and 45% SRWC drought treatments. The abscisic acid (ABA) content of the roots increased under drought stress. After re-watering, the ABA content decreased to a lower level under the three and six-day 60% SRWC and 45% SRWC drought treatments than in the controls. According to an analysis of various indicators, the interaction between ABA and GA signals may play an important role in root growth compensatory effects. In summary, the results demonstrate that moderate drought stress is beneficial to root growth and yield. This conclusion is of great significance to improving our understanding of the maximum utilization of limited water resources. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Tomato HsfA1a plays a critical role in plant drought tolerance by activating ATG genes and inducing autophagy

PubMed Central

Wang, Yu; Cai, Shuyu; Yin, Lingling; Shi, Kai; Xia, Xiaojian; Zhou, Yanhong; Yu, Jingquan; Zhou, Jie

2015-01-01

Autophagy plays critical roles in plant responses to stress. In contrast to the wealth of information concerning the core process of plant autophagosome assembly, our understanding of the regulation of autophagy is limited. In this study, we demonstrated that transcription factor HsfA1a played a critical role in tomato tolerance to drought stress, in part through its positive role in induction of autophagy under drought stress. HsfA1a expression was induced by drought stress. Virus-induced HsfA1a gene silencing reduced while its overexpression increased plant drought tolerance based on both symptoms and membrane integrity. HsfA1a-silenced plants were more sensitive to endogenous ABA-mediated stomatal closure, while its overexpression lines were resistant under drought stress, indicating that phytohormone ABA did not play a major role in HsfA1a-induced drought tolerance. On the other hand, HsfA1a-silenced plants increased while its overexpression decreased the levels of insoluble proteins which were highly ubiquitinated under drought stress. Furthermore, drought stress induced numerous ATGs expression and autophagosome formation in wild-type plants. The expression of ATG10 and ATG18f, and the formation of autophagosomes were compromised in HsfA1a-silenced plants but were enhanced in HsfA1a-overexpressing plants. Both electrophoretic mobility shift assay and chromatin immunoprecipitation coupled with qPCR analysis revealed that HsfA1a bound to ATG10 and ATG18f gene promoters. Silencing of ATG10 and ATG18f reduced HsfA1a-induced drought tolerance and autophagosome formation in plants overexpressing HsfA1a. These results demonstrate that HsfA1a induces drought tolerance by activating ATG genes and inducing autophagy, which may promote plant survival by degrading ubiquitinated protein aggregates under drought stress. PMID:26649940

Drought-sensitive aquifer settings in southeastern Pennsylvania

USGS Publications Warehouse

Zimmerman, Tammy M.; Risser, Dennis W.

2005-01-01

This report describes the results of a study conducted by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Conservation and Natural Resources, Bureau of Topographic and Geologic Survey, to determine drought-sensitive aquifer settings in southeastern Pennsylvania. Because all or parts of southeastern Pennsylvania have been in drought-warning or drought-emergency status during 6 of the past 10 years from 1994 through 2004, this information should aid well owners, drillers, and water-resource managers in guiding appropriate well construction and sustainable use of Pennsylvania's water resources. 'Drought-sensitive' aquifer settings are defined for this study as areas unable to supply adequate quantities of water to wells during drought. Using information from previous investigations and a knowledge of the hydrogeology and topography of the study area, drought-sensitive aquifer settings in southeastern Pennsylvania were hypothesized as being associated with two factors - a water-table decline (WTD) index and topographic setting. The WTD index is an estimate of the theoretical water-table decline at the ground-water divide for a hypothetical aquifer with idealized geometry. The index shows the magnitude of ground-water decline after cessation of recharge is a function of (1) distance from stream to divide, (2) ground-water recharge rate, (3) transmissivity, (4) specific yield, and (5) duration of the drought. WTD indices were developed for 39 aquifers that were subsequently grouped into categories of high, moderate, and low WTD index. Drought-sensitive settings determined from the hypothesized factors were compared to locations of wells known to have been affected (gone dry, replaced, or deepened) during recent droughts. Information collected from well owners, drillers, and public agencies identified 2,016 wells affected by drought during 1998-2002. Most of the available data on the location of drought-affected wells in the study area were from Chester and Montgomery Counties because those counties have well-construction regulations that identify wells that failed during drought. The locations of drought-affected wells in Chester and Montgomery Counties indicated the most highly sensitive settings are uplands and slopes in aquifers with high WTD index and uplands in aquifers with moderate WTD index. The least sensitive settings are in aquifers with low WTD index, in valleys, or on slopes. A map was developed showing the relative drought sensitivity (low, moderate, and high) of aquifers in southeastern Pennsylvania. Study results were limited by the inability to obtain much information about the location of drought-affected wells, with the exception of Montgomery and Chester Counties. Also, the construction characteristics (particularly depth) of drought-affected wells generally were not available. Well depth could be used to distinguish between problems caused by shallow well depth (generally less than 100 ft) and those caused by deficiency of the aquifer to supply water. With the exception of owner-derived information from a public survey on drought-affected wells (35 wells), depth data were not obtained. Data from the 35 drought-affected wells indicated most were drilled (not dug) and were completed to depths greater than 100 feet. This finding indicates that the affects of recent droughts in southeastern Pennsylvania were not restricted to shallow dug wells, but also affected deeper drilled wells.

A global drought climatology for the 3rd edition of the World Atlas of Desertification (WAD)

NASA Astrophysics Data System (ADS)

Spinoni, Jonathan; Carrao, Hugo; Naumann, Gustavo; Antofie, Tiberiu; Barbosa, Paulo; Vogt, Jürgen

2013-04-01

A new version of the World Atlas of Desertification (WAD) is being compiled in the framework of cooperation between the Joint Research Centre (JRC) of the European Commission and the United Nations Environment Programme (UNEP). This initiative aims at mapping the global land degradation and desertification, as well as introducing the reader with complex interactions of geo-physical, socio-economic, and political aspects that affect the environmental sustainability. Recurrent extreme events resulting from climate change, such as more severe droughts, combined with non-adapted land use practices can affect the resilience of ecosystems tipping them into a less productive state. Thus, to describe the effects of climatological hazards on land degradation and desertification processes, we computed a World drought climatology that will be part of the 3rd edition of the WAD and will replace and update to 2010 the results presented in the 2nd edition in 1997. This paper presents the methodology used to compute three parameters included in the WAD drought climatology, i.e. drought frequency, intensity and duration, and discusses their spatio-temporal patterns both at global and continental scales. Because drought is mainly driven and triggered by a rainfall deficit, we chose the Standardized Precipitation Index (SPI) as the drought indicator to estimate our climatological parameters. The SPI is a statistical precipitation-based drought indicator widely used in drought-related studies. We calculated the SPI on three different accumulation periods: 3 months (SPI-3), 6 months (SPI-6), and 12 months (SPI-12), in order to take into account meteorological, agricultural, and hydrological drought-related features. Each quantity has been calculated on a monthly basis using the baseline period between January 1951 and December 2010. As data input, we used the Full Data Reanalysis Version 6.0 (0.5˚x0.5˚) of gridded monthly precipitation provided by the Global Precipitation Climatology Center (GPCC) of the Deutscher Wetterdienst (DWD). This dataset was selected after an extensive quality check on data reliability, homogeneity, and physical consistency. We defined the drought frequency as the number of months with SPI below -1 out of all months in different periods of 10-15 years between 1951 and 2010. For the drought intensity we analyzed the drought events with at least 3 consecutive months with SPI below -1. The drought duration is defined in an operative way: a drought starts when SPI first falls below -1 and it ends when it turns back positive (i.e. >0) for at least 2 consecutive months. The results show that in the last two decades, as compared to the long-term normal conditions, the regions most affected by drought events were Congo and Central Africa, North-Eastern China, the Australian South-Eastern coast, and the Middle East. In general, an increase in duration and intensity of drought events was found for almost all the Northern Hemisphere. We also focused on some regional case studies dealing with drought events in the Mediterranean region, the Horn of Africa, and South America in the last 15 years

Monitoring Agricultural Drought Using Geographic Information Systems and Remote Sensing on the Primary Corn and Soybean Belt in the United States

NASA Astrophysics Data System (ADS)

Al-Shomrany, Adel

The study aims to evaluate various remote sensing drought indices to assess those most fitting for monitoring agricultural drought. The objectives are (1) to assess and study the impact of drought effect on (corn and soybean) crop production by crop mapping information and GIS technology; (2) to use Geographical Weighted Regression (GWR) as a technical approach to evaluate the spatial relationships between precipitation vs. irrigated and non-irrigated corn and soybean yield, using a Nebraska county-level case study; (3) to assess agricultural drought indices derived from remote sensing (NDVI, NMDI, NDWI, and NDII6); (4) to develop an optimal approach for agricultural drought detection based on remote sensing measurements to determine the relationship between US county-level yields versus relatively common variables collected. Extreme drought creates low corn and soybean production where irrigation systems are not implemented. This results in a lack of moisture in soil leading to dry land and stale crop yields. When precipitation and moisture is found across all states, corn and soybean production flourishes. For Kansas, Nebraska, and South Dakota, irrigation management methods assist in strong crop yields throughout SPI monthly averages. The data gathered on irrigation consisted of using drought indices gathered by the national agricultural statistics service website. For the SPI levels ranging between one-month and nine-months, Kansas and Nebraska performed the best out of all 12-states contained in the Midwestern primary Corn and Soybean Belt. The reasoning behind Kansas and Nebraska's results was due to a more efficient and sustainable irrigation system, where upon South Dakota lacked. South Dakota was leveled by strong correlations throughout all SPI periods for corn only. Kansas showed its strongest correlations for the two-month and three-month averages, for both corn and soybean. Precipitation regression with irrigated and non-irrigated maize (corn) and soybean levels show yields as a function of precipitation. The GWR models predicted that yields were significantly better than OLS performances for maize (corn) and soybean. The OLS regression model when used showed a general trend of correlation between observed yields and long-term mean precipitation totals, with 84% and 63% of the variability in mean yield explained by the mean annual precipitation for the non-irrigated crops. The GWR technique performance in predicting yields was significantly better than OLS performances. For instance in the months of June, July, and August precipitations had greater impacts on maize (corn) yields than soybeans under non-irrigated conditions as a result of the greater sensitivity maize (corn) had to water stress. SPI is capable of offering various time-scales enabling it to show initial warning signs of drought conditions and accompanying severity levels. SPI calculation techniques used for various locations are reflected upon the precipitation records acquired during those periods. Over the 3, 6, and 9-month periods, NDII6 performed the best out of all of the MODIS indices as shown in its results in monitoring vegetation moisture and drought detection. NDII6 performed the best due to its detection abilities. The 9-month SPI provides an indication of inter-seasonal precipitation patterns over medium timescale duration. A new approach used is to average corn and soybean yields for all counties of the study area in comparison with average anomalies of the MODIS indices for the growing season between May through September from 2006-2012. There was a strong correlation between average corn yields versus MODIS NDII6 averages for these years with R2 equaling 0.62. That means NDII6 is the best indicator to show drought conditions and vegetation moisture monitoring. There was a weak correlation with R2 = 0.16 between averages of soybean yields and averages of precipitation. Irrigation and management systems, technological improvements from hybrids, producer management techniques, and other management practices have an impact on crop yield productions. (Abstract shortened by ProQuest.).

Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Şahin, Mehmet

2015-07-01

The forecasting of drought based on cumulative influence of rainfall, temperature and evaporation is greatly beneficial for mitigating adverse consequences on water-sensitive sectors such as agriculture, ecosystems, wildlife, tourism, recreation, crop health and hydrologic engineering. Predictive models of drought indices help in assessing water scarcity situations, drought identification and severity characterization. In this paper, we tested the feasibility of the Artificial Neural Network (ANN) as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012. The predictive variables were: monthly rainfall totals, mean temperature, minimum temperature, maximum temperature and evapotranspiration, which were supplemented by large-scale climate indices (Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and Indian Ocean Dipole) and the Sea Surface Temperatures (Nino 3.0, 3.4 and 4.0). A total of 30 ANN models were developed with 3-layer ANN networks. To determine the best combination of learning algorithms, hidden transfer and output functions of the optimum model, the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton backpropagation algorithms were utilized to train the network, tangent and logarithmic sigmoid equations used as the activation functions and the linear, logarithmic and tangent sigmoid equations used as the output function. The best ANN architecture had 18 input neurons, 43 hidden neurons and 1 output neuron, trained using the Levenberg-Marquardt learning algorithm using tangent sigmoid equation as the activation and output functions. An evaluation of the model performance based on statistical rules yielded time-averaged Coefficient of Determination, Root Mean Squared Error and the Mean Absolute Error ranging from 0.9945-0.9990, 0.0466-0.1117, and 0.0013-0.0130, respectively for individual stations. Also, the Willmott's Index of Agreement and the Nash-Sutcliffe Coefficient of Efficiency were between 0.932-0.959 and 0.977-0.998, respectively. When checked for the severity (S), duration (D) and peak intensity (I) of drought events determined from the simulated and observed SPEI, differences in drought parameters ranged from - 1.41-0.64%, - 2.17-1.92% and - 3.21-1.21%, respectively. Based on performance evaluation measures, we aver that the Artificial Neural Network model is a useful data-driven tool for forecasting monthly SPEI and its drought-related properties in the region of study.

Physiological responses of somaclonal variants of triploid bermudagrass (Cynodon transvaalensis x Cynodon dactylon) to drought stress.

PubMed

Lu, Shaoyun; Chen, Chuanhao; Wang, Zhongcheng; Guo, Zhenfei; Li, Haihang

2009-03-01

Eight somaclonal variants with enhanced drought tolerance were isolated from regenerated plants of triploid bermudagrass (Cynodon dactylon x Cynodon transvaalensis cv., TifEagle). Three of them (10-17, 89-02, 117-08) with strong drought tolerance were selected for investigations of physiological responses to drought stress. Compared to the parent control, TifEagle, the somaclonal variants had higher relative water contents and relative growth, and lower ion leakages in the greenhouse tests, while no difference in evapotranspirational water losses and soil water contents was observed between the variants and TifEagle. The variants also had less leaf firing in the field tests under drought stress. Superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activities decreased gradually in responses to drought stress in all plants and exhibited negative correlations with ion leakage, indicating that the declined activities of these antioxidant enzymes were associated with drought injury in the triploid bermudagrass. However, CAT activities were significantly higher in all three variants than in TifEagle during drought stress. Two variants, 10-17 and 89-02, also had significantly higher APX activities than TifEagle before and during the first 4 days of drought treatments. These two lines also showed higher SOD activities after prolonged drought stress. Proline, total soluble sugars and sucrose were accumulated under drought stress in all plants and exhibited positive correlations with ion leakage. More proline and sugars were accumulated in TifEagle than in the variants. The results indicated that higher activities of the antioxidant enzymes in the variants during drought stress are associated with their increased drought tolerance.

Effect of Drought on Streamflow and Stream-Water Quality in Colorado, July through September 2002

USGS Publications Warehouse

Chafin, Daniel T.; Druliner, A. Douglas

2007-01-01

During 2002, Colorado experienced the State's worst drought since 1977. In 2003, the U.S. Geological Survey entered into cooperative agreement with the Colorado Department of Public Health and Environment to evaluate the general effects of drought on the water quality of streams in Colorado during summer 2002 by analyzing a water-quality data set obtained during summer 2002 in cooperation with a variety of State and local governments. Water samples were collected at 148 stream sites in Colorado and were measured or analyzed for field properties, major ions, nutrients, organic carbon, bacteria, and dissolved and total recoverable metals. Mean annual streamflow was analyzed at 134 sites in Colorado, and mean summer (July-September) streamflow for 2002 was determined for 146 sites for water years 1978-2002. Mean annual streamflow for 2002 had an average percentile of 29.4 and mean summer streamflow for 2002 had an average percentile of 7.6 relative to 1978-2002. These results indicate that streamflow in Colorado was substantially less than median streamflow for the period and that the effect of drought on streamflow was greater during summer 2002 than during water year 2002 (October 1, 2001, through September 30, 2002). Few measured constituent concentrations or values were elevated or depressed on a widespread basis during summer 2002. Specific conductance was elevated (in the upper quartile relative to historical data) in five of the seven basins that had sufficient data for characterization, indicating that specific conductance likely was affected by drought in those basins. Chloride concentrations were elevated in three of five basins with sufficient data and indicate that chloride concentration generally was affected by drought in those basins. Sulfate concentration was elevated in four of six basins with sufficient data. The widespread elevation of specific conductance and concentrations of chloride and sulfate indicates that salinity generally was affected by drought in Colorado streams during July-September 2002, likely because streamflow at most sites was dominated by base flow of ground water, which usually has substantially greater salinity compared to runoff from precipitation. Total-recoverable iron and manganese concentrations were depressed (in the lower quartile of historical data) in the Arkansas River Basin, which likely was due to reduced land-surface washoff of sediment containing oxyhydroxides of these metals. Of the 246 water samples collected at 148 sites during the summer of 2002, constituents in 115 exceeded Colorado water-quality standards. Constituents that exceeded water-quality standards were pH (all 9.0 standard unit exceedances; 9 samples), chloride (1 sample), sulfate (9 samples), dissolved ammonia (10 samples), dissolved nitrite nitrogen (3 samples), E. coli (Escherichia coli) bacteria (34 samples, 20 in Arkansas River Basin), fecal-coliform bacteria (18 samples, all in Arkansas River Basin), dissolved copper (1 sample), dissolved iron (3 samples), total-recoverable iron (3 samples), dissolved manganese (13 samples), dissolved selenium (10 samples), and dissolved zinc (1 sample). Of these 115 exceedances, historical data were sufficient to conclude that 21 probably were affected by drought, that 39 probably were not affected by drought, and that 55 were of indeterminate nature. Specific conductance indicates that the San Juan River Basin (average percentile 95.2) experienced the greatest effects of drought on water quality during summer 2002 compared to other basins in Colorado, followed by the Upper Colorado (90.0) and Dolores River (85.7) Basins. The South Platte River Basin (70.9) experienced the least effect of drought, and the Yampa and White River Basin group (73.7) had the second smallest effect. The Gunnison River (82.1) and Arkansas River (81.2) Basins had intermediate drought effects. The Rio Grande had insufficient data to rank the relative effect of drought on salinity.

A Groundwater Resource Index (GRI) for drought monitoring and forecasting in a mediterranean climate

NASA Astrophysics Data System (ADS)

Mendicino, Giuseppe; Senatore, Alfonso; Versace, Pasquale

2008-08-01

SummaryDrought indices are essential elements of an efficient drought watching system, aimed at providing a concise overall picture of drought conditions. Owing to its simplicity, time-flexibility and standardization, the Standardized Precipitation Index (SPI) has become a very widely used meteorological index, even if it is not able to account for effects of aquifers, soil, land use characteristics, canopy growth and temperature anomalies. Many other drought indices have been developed over the years, with monitoring and forecasting purposes, also with the purpose of taking advantage of the opportunities offered by remote sensing and improved general circulation models (GCMs). Moreover, some aggregated indices aimed at capturing the different features of drought have been proposed, but very few drought indices are focused on the groundwater resource status. In this paper a novel Groundwater Resource Index (GRI) is presented as a reliable tool useful in a multi-analysis approach for monitoring and forecasting drought conditions. The GRI is derived from a simple distributed water balance model, and has been tested in a Mediterranean region, characterized by different geo-lithological conditions mainly affecting the summer hydrologic response of the catchments to winter precipitation. The analysis of the GRI characteristics shows a high spatial variability and, compared to the SPI through spectral analysis, a significant sensitivity to the lithological characterization of the analyzed region. Furthermore, the GRI shows a very high auto-correlation during summer months, useful for forecasting purposes. The capability of the proposed index in forecasting summer droughts was tested analyzing the correlation of the GRI April values with the mean summer runoff values of some river basins (obtaining a mean correlation value of 0.60) and with the summer NDVI values of several forested areas, where correlation values greater than 0.77 were achieved. Moreover, its performance was evaluated in forecasting the major historic drought events, finding that the GRI is a better predictor than the SPI in order to predispose adequate actions for facing summer drought, with just one year missed and no false alarms observed.

Spatial Variations in Drought Persistence in the South-Central U.S.

NASA Astrophysics Data System (ADS)

Leasor, Z. T.; Quiring, S. M.

2016-12-01

Drought is one of the most prominent climatic hazards in the south-central United States. This study examines spatial variations in meteorological drought persistence using high-resolution PRISM gridded precipitation data from 1900-2015. The Standardized Precipitation Index (SPI) is used to represent meteorological drought conditions. The study region covers Texas, Oklahoma, and Kansas. Droughts are first divided into different severity categories using the classification employed by the U.S. National Drought Monitor. The frequency and duration of each drought event is determined and this is used to calculate drought persistence. Our results indicate that drought persistence in the south-central U.S. varies as a function of drought severity. In addition, drought persistence also varies substantially over space and time. The probability of drought termination is a function of drought severity, geographic location and time of the year. In addition, there is evidence that drought persistence is influenced by global teleconnections and land-atmosphere interactions. The results of this drought persistence climatology can benefit seasonal forecasting and the current understanding of drought recovery.

Remotely Sensed Quantitative Drought Risk Assessment in Vulnerable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.

2012-04-01

Hazard may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, economy and society. This paper deals with drought risk assessment, which the first step designed to find out what the problems are and comprises three distinct steps, namely risk identification, risk management which is not covered in this paper, there should be a fourth step to address the need for feedback and to take post-audits of all risk assessment exercises. In particular, quantitative drought risk assessment is attempted by using statistical methods. For the qualification of drought, the Reconnaissance Drought Index (RDI) is employed, which is a new index based on hydrometeorological parameters, such as precipitation and potential evapotranspiration. The remotely sensed estimation of RDI is based on NOA-AVHRR satellite data for a period of 20 years (1981-2001). The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Specifically, the undertaken drought risk assessment processes are specified as follows: 1. Risk identification: This step involves drought quantification and monitoring based on remotely sensed RDI and extraction of several features such as severity, duration, areal extent, onset and end time. Moreover, it involves a drought early warning system based on the above parameters. 2. Risk estimation: This step includes an analysis of drought severity, frequency and their relationships. 3. Risk evaluation: This step covers drought evaluation based on analysis of RDI images before and after each drought episode, which usually lasts one hydrological year (12month). The results of these three-step drought assessment processes are considered quite satisfactory in a drought-prone region such as Thessaly in central Greece. Moreover, remote sensing has proven very effective in delineating spatial variability and features in drought monitoring and assessment.

Accounting for dynamics of mean precipitation in drought projections: A case study of Brazil for the 2050 and 2070 periods.

PubMed

Mpelasoka, Freddie; Awange, Joseph L; Goncalves, Rodrigo Mikosz

2018-05-01

Changes in drought around the globe are among the most daunting potential effects of climate change. However, changes in droughts are often not well distinguished from changes in aridity levels. As drought constitutes conditions of aridity, the projected declines in mean precipitation tend to override changes in drought. This results in projections of more dire changes in drought than ever. The overestimate of changes can be attributed to the use of 'static' normal precipitation in the derivation of drought events. The failure in distinguishing drought from aridity is a conceptual problem of concern, particularly to drought policymakers. Given that the key objective of drought policies is to determine drought conditions, which are rare and so protracted that they are beyond the scope of normal risk management, for interventions. The main objective of this Case Study of Brazil is to demonstrate the differences between projections of changes in drought based on 'static' and '30-year dynamic' precipitation normal conditions. First we demonstrate that the 'static' based projections suggest 4-fold changes in the probability of drought-year occurrences against changes by the dynamic normal precipitation. The 'static-normal mean precipitation' based projections tend to be monotonically increasing in magnitude, and were arguably considered unrealistic. Based on the '30-year dynamic' normal precipitation conditions, the 13-member GCM ensemble median projection estimates of changes for 2050 under rcp4.5 1 and rcp8.5 2 suggest: (i) Significant differences between changes associated with rcp4.5 and rcp8.5, and are more noticeable for droughts at long than short timescales in the 2070; (ii) Overall, the results demonstrate more realistic projections of changes in drought characteristics over Brazil than previous projections based on 'static' normal precipitation conditions. However, the uncertainty of response of droughts to climate change in CMIP5 simulations is still large, regardless of GCMs selection and translation processes undertaken. Copyright © 2017 Elsevier B.V. All rights reserved.

Pacific and Atlantic influences on Mesoamerican climate over the past millennium

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Burnette, D. J.; Diaz, J. Villanueva; Heim, R. R.; Fye, F. K.; Paredes, J. Cerano; Soto, R. Acuna; Cleaveland, M. K.

2012-09-01

A new tree-ring reconstruction of the Palmer Drought Severity Index (PDSI) for Mesoamerica from AD 771 to 2008 identifies megadroughts more severe and sustained than any witnessed during the twentieth century. Correlation analyses indicate strong forcing of instrumental and reconstructed June PDSI over Mesoamerica from the El Niño/Southern Oscillation (ENSO). Spectral analyses of the 1,238-year reconstruction indicate significant concentrations of variance at ENSO, sub-decadal, bi-decadal, and multidecadal timescales. Instrumental and model-based analyses indicate that the Atlantic Multidecadal Oscillation is important to warm season climate variability over Mexico. Ocean-atmospheric variability in the Atlantic is not strongly correlated with the June PDSI reconstruction during the instrumental era, but may be responsible for the strong multidecadal variance detected in the reconstruction episodically over the past millennium. June drought indices in Mesoamerica are negatively correlated with gridded June PDSI over the United States from 1950 to 2005, based on both instrumental and reconstructed data. Interannual variability in this latitudinal moisture gradient is due in part to ENSO forcing, where warm events favor wet June PDSI conditions over the southern US and northern Mexico, but dryness over central and southern Mexico (Mesoamerica). Strong anti-phasing between multidecadal regimes of tree-ring reconstructed June PDSI over Mesoamerica and reconstructed summer (JJA) PDSI over the Southwest has also been detected episodically over the past millennium, including the 1950-1960s when La Niña and warm Atlantic SSTs prevailed, and the 1980-1990s when El Niño and cold Atlantic SSTs prevailed. Several Mesoamerican megadroughts are reconstructed when wetness prevailed over the Southwest, including the early tenth century Terminal Classic Drought, implicating El Niño and Atlantic SSTs in this intense and widespread drought that may have contributed to social changes in ancient Mexico.

Indices and Dynamics of Global Hydroclimate Over the Past Millennium from Data Assimilation

NASA Astrophysics Data System (ADS)

Steiger, N. J.; Smerdon, J. E.

2017-12-01

Reconstructions based on data assimilation (DA) are at the forefront of model-data syntheses in that such reconstructions optimally fuse proxy data with climate models. DA-based paleoclimate reconstructions have the benefit of being physically-consistent across the reconstructed climate variables and are capable of providing dynamical information about past climate phenomena. Here we use a new implementation of DA, that includes updated proxy system models and climate model bias correction procedures, to reconstruct global hydroclimate on seasonal and annual timescales over the last millennium. This new global hydroclimate product includes reconstructions of the Palmer Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and global surface temperature along with dynamical variables including the Nino 3.4 index, the latitudinal location of the intertropical convergence zone, and an index of the Atlantic Multidecadal Oscillation. Here we present a validation of the reconstruction product and also elucidate the causes of severe drought in North America and in equatorial Africa. Specifically, we explore the connection between droughts in North America and modes of ocean variability in the Pacific and Atlantic oceans. We also link drought over equatorial Africa to shifts of the intertropical convergence zone and modes of ocean variability.

The North American Drought Atlas: Tree-Ring Reconstructions of Drought Variability for Climate Modeling and Assessment

NASA Astrophysics Data System (ADS)

Cook, E. R.

2007-05-01

The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see http:iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html), great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of the Northern Hemisphere where sufficient tree-ring data exist. By doing so, the importance of this product to the modeling community will be significantly enhanced.

Testing a new application for TOPSIS: monitoring drought and wet periods in Iran

NASA Astrophysics Data System (ADS)

Roshan, Gholamreza; Ghanghermeh, AbdolAzim; Grab, Stefan W.

2018-01-01

Globally, droughts are a recurring major natural disaster owing to below normal precipitation, and are occasionally associated with high temperatures, which together negatively impact upon human health and social, economic, and cultural activities. Drought early warning and monitoring is thus essential for reducing such potential impacts on society. To this end, several experimental methods have previously been proposed for calculating drought, yet these are based almost entirely on precipitation alone. Here, for the first time, and in contrast to previous studies, we use seven climate parameters to establish drought/wet periods; these include: T min, T max, sunshine hours, relative humidity, average rainfall, number of rain days greater than 1 mm, and the ratio of total precipitation to number of days with precipitation, using the technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. To test the TOPSIS method for different climate zones, six sample stations representing a variety of different climate conditions were used by assigning weight changes to climate parameters, which are then applied to the model, together with multivariate regression analysis. For the six stations tested, model results indicate the lowest errors for Zabol station and maximum errors for Kermanshah. The validation techniques strongly support our proposed new method for calculating and rating drought/wet events using TOPSIS.

Drought Effects on Riparian Vegetation in the Santa Clara River Basin Using Airborne Imaging Spectroscopy

NASA Astrophysics Data System (ADS)

Schmidt, C.; Miller, D.; Roberts, D. A.

2017-12-01

Riparian forests are groundwater-dependent ecosystems that are highly sensitive to changes in the water table. As climate change continues, droughts are likely to become more frequent and severe in Southern California, threatening the persistence of these ecosystems. From 2012 to 2017, California experienced the most severe drought in the past century, providing a case study to assess drought impacts. Using imagery collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) from 2013 and 2016, we evaluated changes in riparian forest health in a central section of the Santa Clara River Basin, a multi-use river located just north of Los Angeles. We used Constrained Reference Endmember Selection (CRES) to select reference endmembers of green vegetation (GV), non-photosynthetic vegetation (NPV), and rock/soil. We used spectral mixture analysis to estimate endmember fractions. We assessed changes in green vegetation cover and canopy water content at key monitoring sites based on the Relative GV Fraction, the Normalized Difference Water Index, and the Water Band Index. Preliminary results showed a decrease in the GV fraction and an increase in the NPV fraction, indicating an overall decline in riparian forest health as a result of drought. Our results demonstrate the spatial extent of drought effects in groundwater dependent ecosystems.

An assessment of global meteorological droughts based on HAPPI experiments

NASA Astrophysics Data System (ADS)

Liu, Wenbin; Sun, Fubao; Lim, Wee Ho; Zhang, Jie

2017-04-01

Droughts caused water shortages could lead to serious consequences on the socioeconomic and environmental well-being. In the context of changing climate, droughts monitoring, attributions and impact assessments have been performed using observations (e.g., Sun et al., 2012; Zhang et al., 2016) and climate model projections (e.g., Liu et al., 2016, 2017); with expectation that such scientific knowledge would feed into long-term adaptation and mitigation plans to tackle potentially unfavorable future drought impacts in a warming world. Inspired by the 2015 Paris Agreement, the HAPPI (Half a degree Additional warming, Projections, Prognosis and Impacts) experiments were set up to better inform international policymakers about the socioeconomic and environmental impacts under less severe global warming conditions. This study aims to understand the potential shift in meteorological droughts from the past into the future on a global scale. Based on the HAPPI data, we evaluate the change in drought related indices (i.e., PET/P, PDSI) from the past to the future scenarios (1.5 and 2 degrees Celsius warming). Here we present some early results (MIROC5 as demonstration) on identified hotspots and discuss the differences in severity of droughts between these warming worlds and associated consequences. References: Liu W, and Sun F, 2017. Projecting and attributing future changes of evaporative demand over China in CMIP5 climate models, Journal of Hydrometeorology, doi: 10.1175/JHM-D-16-0204.1 Liu W, and Sun F, 2016. Assessing estimates of evaporative demand in climate models using observed pan evaporation over China. Journal of Geophysical Research-Atmosphere 121, 8329-8349 Zhang J, Sun F, Xu J, Chen Y, Sang Y, -F, and Liu C, 2016. Dependence of trends in and sensitivity of drought over China (1961-2013) on potential evaporation model. Geophysical Research Letters 43, 206-213 Sun F, Roderick M, Farquhar G, 2012. Changes in the variability of global land precipitation. Geophysical Research Letters 39, L19402

Drought in Southwestern United States

NASA Technical Reports Server (NTRS)

2007-01-01

The southwestern United States pined for water in late March and early April 2007. This image is based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite from March 22 through April 6, 2007, and it shows the Normalized Difference Vegetation Index, or NDVI, for the period. In this NDVI color scale, green indicates areas of healthier-than-usual vegetation, and only small patches of green appear in this image, near the California-Nevada border and in Utah. Larger areas of below-normal vegetation are more common, especially throughout California. Pale yellow indicates areas with generally average vegetation. Gray areas appear where no data were available, likely due to persistent clouds or snow cover. According to the April 10, 2007, update from the U.S. Drought Monitor, most of the southwestern United Sates, including Utah, Nevada, California, and Arizona, experienced moderate to extreme drought. The hardest hit areas were southeastern California and southwestern Arizona. Writing for the Drought Monitor, David Miskus of the Joint Agricultural Weather Facility reported that March 2007 had been unusually dry for the southwestern United States. While California's and Utah's reservoir storage was only slightly below normal, reservoir storage was well below normal for New Mexico and Arizona. In early April, an international research team published an online paper in Science noting that droughts could become more common for the southwestern United States and northern Mexico, as these areas were already showing signs of drying. Relying on the same computer models used in the Intergovernmental Panel on Climate Change (IPCC) report released in early 2007, the researchers who published in Science concluded that global warming could make droughts more common, not just in the American Southwest, but also in semiarid regions of southern Europe, Mediterranean northern Africa, and the Middle East.

Drought sensitivity predicts habitat size sensitivity in an aquatic ecosystem.

PubMed

Amundrud, Sarah L; Srivastava, Diane S

2015-07-01

Species and trophic richness often increase with habitat size. Although many ecological processes have been evoked to explain both patterns, the environmental stress associated with small habitats has rarely been considered. We propose that larger habitats may be species rich simply because their environmental conditions are within the fundamental niche of more species; larger habitats may also have more trophic levels if traits of predators render them vulnerable to environmental stress. We test this hypothesis using the aquatic insect larvae in water-filled bromeliads. In bromeliads, the probability of desiccation is greatest in small plants. For the 10 most common bromeliad insect taxa, we ask whether differences in drought tolerance and regional abundances between taxa predict community and trophic composition over a gradient of bromeliad size. First, we used bromeliad survey data to calculate the mean habitat size of occurrence of each taxon. Comparing the observed mean habitat size of occurrence to that expected from random species assembly based on differences in their regional abundances allowed us to obtain habitat size sensitivity indices (as Z scores) for the various insect taxa. Second, we obtained drought sensitivity indices by subjecting individual insects to drought and measuring the effects on relative growth rates in a mesocosm experiment. We found that drought sensitivity strongly, predicts habitat size sensitivity in bromeliad insects. However, an increase in trophic richness with habitat size could not be explained by an increased sensitivity of predators to drought, but rather by sampling effects, as predators were rare compared to lower trophic levels. This finding suggests that physiological tolerance to environmental stress can be relevant in explaining the universal increase in species with habitat size.

Multi-scale linkages of winter drought variability to ENSO and the Arctic Oscillation: A case study in Shaanxi, North China

NASA Astrophysics Data System (ADS)

Liu, Zhiyong; Zhang, Xin; Fang, Ruihong

2018-02-01

Understanding the potential connections between climate indices such as the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) and drought variability will be beneficial for making reasonable predictions or assumptions about future regional droughts, and provide valuable information to improve water resources planning and design for specific regions of interest. This study is to examine the multi-scale relationships between winter drought variability over Shaanxi (North China) and both ENSO and AO during the period 1960-2009. To accomplish this, we first estimated winter dryness/wetness conditions over Shaanxi based on the self-calibrating Palmer drought severity index (PDSI). Then, we identified the spatiotemporal variability of winter dryness/wetness conditions in the study area by using the empirical orthogonal function (EOF). Two primary sub-regions of winter dryness/wetness conditions across Shaanxi were identified. We further examined the periodical oscillations of dryness/wetness conditions and the multi-scale relationships between dryness/wetness conditions and both ENSO and AO in winter using wavelet analysis. The results indicate that there are inverse multi-scale relations between winter dryness/wetness conditions and ENSO (according to the wavelet coherence) for most of the study area. Moreover, positive multi-scale relations between winter dryness/wetness conditions and AO are mainly observed. The results could be beneficial for making reasonable predictions or assumptions about future regional droughts and provide valuable information to improve water resources planning and design within this study area. In addition to the current study area, this study may also offer a useful reference for other regions worldwide with similar climate conditions.

77 FR 8246 - Alabama Power Company; Notice of Application Accepted for Filing, Soliciting Motions To Intervene...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... Martin Dam Project: (1) A flood control guide; (2) an operating guide; and (3) a drought contingency.... The drought contingency plan provides an indication of impending hydrologic drought conditions. m. A...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less

Drought analysis and water resource availability using standardised precipitation evapotranspiration index

NASA Astrophysics Data System (ADS)

Hui-Mean, Foo; Yusop, Zulkifli; Yusof, Fadhilah

2018-03-01

Trend analysis for potential evapotranspiration (PET) and climatic water balance (CWB) is critical in identifying the wetness or dryness episodes with respect to the water surplus or deficit. The PET is computed based on the monthly average temperature for the entire Peninsular Malaysia using Thornthwaite parameterization. The trends and slope's magnitude for the PET and CWB were then investigated using Mann-Kendall, Spearman's rho tests and Thiel-Sen estimator. The 1-, 3-, 6- and 12-month standardised precipitation evapotranspiration index (SPEI) is applied to determine the drought episodes and the average recurrence interval are calculated based on the SPEI. The results indicate that most of the stations show an upward trend in annual and monthly PET while majority of the regions show an upward trend in annual CWB except for the Pahang state. The increasing trends detected in the CWB describe water is in excess especially during the northeast monsoons while the decreasing trends imply water insufficiency. The excess water is observed mostly in January especially in the west coast, east coast and southwest regions that suggest more water is available for crop requirement. The average recurrence interval for drought episodes is almost the same for the smaller severity with various time scale of SPEI and high probability of drought occurrence is observed for some regions. The findings are useful for policymakers and practitioners to improve water resources planning and management, in particular to minimise drought effects in the future. Future research shall address the influence of topography on drought behaviour using more meteorological stations and to include east Malaysia in the analysis.

Wildfire potential mapping over the state of Mississippi: A land surface modeling approach

Treesearch

William H. Cooke; Georgy V. Mostovoy; Valentine G. Anantharaj; W. Matt Jolly

2012-01-01

A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern part of Mississippi. The following three indices were tested and used to simulate spatial and temporal wildfire probability changes: (1) the accumulated difference between daily precipitation and potential...

Projected changes in the evolution of drought assessed with the SPEI over the Czech Republic

NASA Astrophysics Data System (ADS)

Potop, V.; Boroneana, C.; Stepanek, P.; Skalak, P.; Mozny, M.

2012-04-01

In previous studies the spatial and temporal evolution of drought events in the Czech Republic were extensively analyzed by comparing results from the most advanced drought indices (e.g. the SPI and SPEI), which take into account the role of antecedent conditions in quantifying drought severity. In the present study, the Standardized Precipitation Evapotranspiration Index (SPEI) was adopted to assess and project drought characteristics in the Czech Republic based on the regional climate model ALADIN-Climate/CZ simulated data. The simulations were conducted at high resolution (10km) for the current (1961-2000) and two future climates (2021-2050 and 2071-2100). First, the observed data of air temperature and precipitation totals was transferred into a regular grid of ALADIN-Climate/CZ model. The bias correction was applied on the scenario runs. The bias correction method is based on variable correction using individual percentiles whose relationship is derived from observations and control RCM simulation. The SPEI was calculated based on observed monthly data of mean temperature and precipitation totals for the period 1961-1990, as reference period, and for the periods 2021-2050 and 2071-2100, as future climates under A1B SRES scenario. The SPEI were calculated with various lags, 1, 3, 6, 12 and 24 months because the drought at these time scales is relevant for agricultural, hydrological and socio-economic impact, respectively. The study refers at the warm season of the year (April to September). As in the case of observational study, we have identified three climatically homogeneous regions, corresponding to the altitudes below 400 m, between 401 and 700 m and, above 700 m. For these three regions the frequency distribution of the SPEI values in 7 classes of drought category (%) were calculated based on grid point data falling in each region, both for the observed data and scenario runs. The paper presents the projected changes in frequency distribution of SPEI at various time scales, in intensity, duration and spatial distribution of drought over the territory of the Czech Republic under A1B scenario for the middle and the end of 21st century. We gratefully acknowledge the support of the Ministry of Education, Youth and Sports for projects OC10010.

Reconstructed droughts for the southeastern Tibetan Plateau over the past 568 years and its linkages to the Pacific and Atlantic Ocean climate variability

NASA Astrophysics Data System (ADS)

Fang, Keyan; Gou, Xiaohua; Chen, Fahu; Li, Jinbao; D'Arrigo, Rosanne; Cook, Edward; Yang, Tao; Davi, Nicole

2010-09-01

We present a Palmer Drought Severity Index reconstruction ( r = 0.61, P < 0.01) from 1440 to 2007 for the southeastern Tibetan Plateau, based on tree rings of the forest fir ( Abies forrestii). Persistent decadal dry intervals were found in the 1440s-1460s, 1560s-1580s, 1700s, 1770s, 1810s, 1860s and 1980s, and the extreme wet epochs were the 1480s-1490s, 1510s-1520s, 1590s, 1610s-1630s, 1720s-1730s, 1800s, 1830s, 1870s, 1930s, 1950s and after the 1990s. Comparisons of our record with those identified in other moisture related reconstructions for nearby regions showed that our reconstructed droughts were relatively consistent with those found in other regions of Indochina, suggesting similar drought regimes. Spectral peaks of 2.3-5.5 years may be indicative of ENSO activity, as also suggested by negative correlations with SSTs in the eastern equatorial and southeastern Pacific Ocean. Significant multidecadal spectral peaks of 29.2-40.9 and 56.8-60.2 years were identified. As indicated by the spatial correlation patterns, the decadal-scale variability may be linked to SST variations in the northern Pacific and Atlantic Oceans.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE PAGES

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.; ...

2018-09-01

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Mean annual precipitation predicts primary production resistance and resilience to extreme drought.

PubMed

Stuart-Haëntjens, Ellen; De Boeck, Hans J; Lemoine, Nathan P; Mänd, Pille; Kröel-Dulay, György; Schmidt, Inger K; Jentsch, Anke; Stampfli, Andreas; Anderegg, William R L; Bahn, Michael; Kreyling, Juergen; Wohlgemuth, Thomas; Lloret, Francisco; Classen, Aimée T; Gough, Christopher M; Smith, Melinda D

2018-04-27

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future. Copyright © 2018. Published by Elsevier B.V.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Co-occurring woody species have diverse hydraulic strategies and mortality rates during an extreme drought.

PubMed

Johnson, Daniel M; Domec, Jean-Christophe; Carter Berry, Z; Schwantes, Amanda M; McCulloh, Katherine A; Woodruff, David R; Wayne Polley, H; Wortemann, Remí; Swenson, Jennifer J; Scott Mackay, D; McDowell, Nate G; Jackson, Robert B

2018-03-01

From 2011 to 2013, Texas experienced its worst drought in recorded history. This event provided a unique natural experiment to assess species-specific responses to extreme drought and mortality of four co-occurring woody species: Quercus fusiformis, Diospyros texana, Prosopis glandulosa, and Juniperus ashei. We examined hypothesized mechanisms that could promote these species' diverse mortality patterns using postdrought measurements on surviving trees coupled to retrospective process modelling. The species exhibited a wide range of gas exchange responses, hydraulic strategies, and mortality rates. Multiple proposed indices of mortality mechanisms were inconsistent with the observed mortality patterns across species, including measures of the degree of iso/anisohydry, photosynthesis, carbohydrate depletion, and hydraulic safety margins. Large losses of spring and summer whole-tree conductance (driven by belowground losses of conductance) and shallower rooting depths were associated with species that exhibited greater mortality. Based on this retrospective analysis, we suggest that species more vulnerable to drought were more likely to have succumbed to hydraulic failure belowground. © 2018 John Wiley & Sons Ltd.

Global Assessment of Groundwater Sustainability Based On Storage Anomalies

NASA Astrophysics Data System (ADS)

Thomas, Brian F.; Caineta, Júlio; Nanteza, Jamiat

2017-11-01

The world's largest aquifers are a fundamental source of freshwater used for agricultural irrigation and to meet human water needs. Therefore, their stored volume of groundwater is linked with water security, which becomes more relevant during periods of drought. This work focuses on understanding large-scale groundwater changes, where we introduce an approach to evaluate groundwater sustainability at a global scale. We employ a groundwater drought index to assess performance metrics (reliability, resilience, vulnerability, and a combined sustainability index) for the largest and most productive global aquifers. Spatiotemporal changes in total water storage are derived from remote sensing observations of gravity anomalies, from which the groundwater drought index is inferred. The results reveal a complex relationship between the indicators, while considering monthly variability in groundwater storage. Combining the drought and sustainability indexes, as presented in this work, constitutes a measure for quantifying groundwater sustainability. This framework integrates changes in groundwater resources due to human influences and climate changes, thus opening a path to assess progress toward sustainable use and water security.

A cross-scale approach to understand drought-induced variability of sagebrush ecosystem productivity

NASA Astrophysics Data System (ADS)

Assal, T.; Anderson, P. J.

2016-12-01

Sagebrush (Artemisia spp.) mortality has recently been reported in the Upper Green River Basin (Wyoming, USA) of the sagebrush steppe of western North America. Numerous causes have been suggested, but recent drought (2012-13) is the likely mechanism of mortality in this water-limited ecosystem which provides critical habitat for many species of wildlife. An understanding of the variability in patterns of productivity with respect to climate is essential to exploit landscape scale remote sensing for detection of subtle changes associated with mortality in this sparse, uniformly vegetated ecosystem. We used the standardized precipitation index to characterize drought conditions and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery (250-m resolution) to characterize broad characteristics of growing season productivity. We calculated per-pixel growing season anomalies over a 16-year period (2000-2015) to identify the spatial and temporal variability in productivity. Metrics derived from Landsat satellite imagery (30-m resolution) were used to further investigate trends within anomalous areas at local scales. We found evidence to support an initial hypothesis that antecedent winter drought was most important in explaining reduced productivity. The results indicate drought effects were inconsistent over space and time. MODIS derived productivity deviated by more than four standard deviations in heavily impacted areas, but was well within the interannual variability in other areas. Growing season anomalies highlighted dramatic declines in productivity during the 2012 and 2013 growing seasons. However, large negative anomalies persisted in other areas during the 2014 growing season, indicating lag effects of drought. We are further investigating if the reduction in productivity is mediated by local biophysical properties. Our analysis identified spatially explicit patterns of ecosystem properties altered by severe drought which are consistent with field observations of sagebrush mortality. The results provide a theoretical framework for future field based investigation at multiple spatiotemporal scales.

Significant and unique changes in phosphorylation levels of four phosphoproteins in two apple rootstock genotypes under drought stress.

PubMed

Ren, Jing; Mao, Juan; Zuo, Cunwu; Calderón-Urrea, Alejandro; Dawuda, Mohammed Mujitaba; Zhao, Xin; Li, Xinwen; Chen, Baihong

2017-12-01

Drought stress is a major problem around the world and there is still little molecular mechanism about how fruit crops deal with moderate drought stress. Here, the physiological and phosphoproteomic responses of drought-sensitive genotype (M26) and drought-tolerant genotype (MBB) under moderate drought stress were investigated. Our results of the physiology analysis indicated that the MBB genotype could produce more osmosis-regulating substances. Furthermore, phosphoproteins from leaves of both genotypes under moderate drought stress were analyzed using the isobaric tags for relative and absolute quantification technology. A total of 595 unique phosphopeptides, 682 phosphorylated sites, and 446 phosphoproteins were quantitatively analyzed in the two genotypes. Five and thirty-five phosphoproteins with the phosphorylation levels significantly changed (PLSC) were identified in M26 and MBB, respectively. Among these, four PLSC phosphoproteins were common to both genotypes, perhaps indicating a partial overlap of the mechanisms to moderate drought stress. Gene ontology analyses revealed that the PLSC phosphoproteins represent a unique combination of metabolism, transcription, translation, and protein processing, suggesting that the response in apple to moderate drought stress encompasses a new and unique homeostasis of major cellular processes. The basic trend was an increase in protein and organic molecules abundance related to drought. These increases were higher in MBB than in M26. Our study is the first to address the phosphoproteome of apple rootstocks in response to moderate drought stress, and provide insights into the molecular regulation mechanisms of apple rootstock under moderate drought stress.

Improved short-term drought response of transgenic rice over-expressing maize C4 phosphoenolpyruvate carboxylase via calcium signal cascade.

PubMed

Liu, Xiaolong; Li, Xia; Dai, Chuanchao; Zhou, Jiayu; Yan, Ting; Zhang, Jinfei

2017-11-01

To understand the link between long-term drought tolerance and short-term drought responses in plants, transgenic rice (Oryza sativa L.) plants over-expressing the maize C 4- pepc gene encoding phosphoenolpyruvate carboxylase (PC) and wild-type (WT) rice plants were subjected to PEG 6000 treatments to simulate drought stress. Compared with WT, PC had the higher survival rate and net photosynthetic rate after 16days of drought treatment, and had higher relative water content in leaves after 2h of drought treatment as well, conferring drought tolerance. WT accumulated higher amounts of malondialdehyde, superoxide radicals, and H 2 O 2 than PC under the 2-h PEG 6000 treatment, indicating greater damages in WT. Results from pretreatments with a Ca 2+ chelator and/or antagonist showed that the regulation of the early drought response in PC was Ca 2+ -dependent. The NO and H 2 O 2 levels in PC lines were also up-regulated via Ca 2+ signals, indicating that Ca 2+ in PC lines also reacted upstream of NO and H 2 O 2 . 2-h drought treatment increased the transcripts of CPK9 and CPK4 in PC via positive up-regulation of Ca 2+ . The transcripts of NAC6 [NACs (NAM, ATAF1, ATAF2, and CUC2)] and bZIP60 (basic leucine zipper, bZIP) were up-regulated, but those of DREB2B (dehydration-responsive element-binding protein, DREB) were down-regulated, both via Ca 2+ signals in PC. PEPC activity, expressions of C 4 -pepc, and the antioxidant enzyme activities in PC lines were up-regulated via Ca 2+ . These results indicated that Ca 2+ signals in PC lines can up-regulate the NAC6 and bZIP60 and the downstream targets for early drought responses, conferring drought tolerance for the long term. Copyright © 2017 Elsevier GmbH. All rights reserved.

Evaluation of groundwater droughts in Austria

NASA Astrophysics Data System (ADS)

Haas, Johannes Christoph; Birk, Steffen

2015-04-01

Droughts are abnormally dry periods that affect various aspects of human life on earth, ranging from negative impacts on agriculture or industry, to being the cause for conflict and loss of human life. The changing climate reinforces the importance of investigations into this phenomenon. Various methods to analyze and classify droughts have been developed. These include drought indices such as the Standard Precipitation Index SPI, the Palmer Drought Severity Index PDSI or the Crop Moisture Index CMI. These and other indices consider meteorological parameters and/or their effects on soil moisture. A depletion of soil moisture triggered by low precipitation and high evapotranspiration may also cause reduced groundwater recharge and thus decreasing groundwater levels and reduced groundwater flow to springs, streams, and wetlands. However, the existing indices were generally not designed to address such drought effects on groundwater. Thus, a Standardized Groundwater level Index has recently been proposed by Bloomfied and Marchant (2013). Yet, to our knowledge, this approach has only been applied to consolidated aquifers in the UK. This work analyzes time series of groundwater levels from various, mostly unconsolidated aquifers in Austria in order to characterize the effects of droughts on aquifers in different hydrogeologic and climatic settings as well as under different usage scenarios. In particular, comparisons are made between the water rich Alpine parts of Austria, and the dryer parts situated in the East. The time series of groundwater levels are compared to other data, such as meteorological time series and written weather records about generally accepted phenomena, such as the 2003 European drought and heat wave. Thus, valuable insight is gained into the propagation of meteorological droughts through the soil and the aquifer in different types of hydrogeologic and climatic settings, which provides a prerequisite for the assessment of the aquifers' drought susceptibility in a changing climate. References: Bloomfield, J. P. & Marchant, B. P. Analysis of groundwater drought building on the standardised precipitation index approach Hydrology and Earth System Sciences, 2013, 17, 4769-4787

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2003-01-01

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

Risk identification of agricultural drought for sustainable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-09-01

Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote-sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Drought Impact Is Alleviated in Sugar Beets (Beta vulgaris L.) by Foliar Application of Fullerenol Nanoparticles

PubMed Central

Borišev, Milan; Borišev, Ivana; Župunski, Milan; Arsenov, Danijela; Pajević, Slobodanka; Ćurčić, Živko; Vasin, Jovica; Djordjevic, Aleksandar

2016-01-01

Over the past few years, significant efforts have been made to decrease the effects of drought stress on plant productivity and quality. We propose that fullerenol nanoparticles (FNPs, molecular formula C60(OH)24) may help alleviate drought stress by serving as an additional intercellular water supply. Specifically, FNPs are able to penetrate plant leaf and root tissues, where they bind water in various cell compartments. This hydroscopic activity suggests that FNPs could be beneficial in plants. The aim of the present study was to analyse the influence of FNPs on sugar beet plants exposed to drought stress. Our results indicate that intracellular water metabolism can be modified by foliar application of FNPs in drought exposed plants. Drought stress induced a significant increase in the compatible osmolyte proline in both the leaves and roots of control plants, but not in FNP treated plants. These results indicate that FNPs could act as intracellular binders of water, creating an additional water reserve, and enabling adaptation to drought stress. Moreover, analysis of plant antioxidant enzyme activities (CAT, APx and GPx), MDA and GSH content indicate that fullerenol foliar application could have some beneficial effect on alleviating oxidative effects of drought stress, depending on the concentration of nanoparticles applied. Although further studies are necessary to elucidate the biochemical impact of FNPs on plants; the present results could directly impact agricultural practice, where available water supplies are often a limiting factor in plant bioproductivity. PMID:27832171

Impacts of droughts on carbon sequestration by China's terrestrial ecosystems from 2000 to 2011

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, Y.; Ju, W.; Wang, S.; Wu, X.; He, M.; Zhu, G.

2014-05-01

In recent years, China's terrestrial ecosystems have experienced frequent droughts. How these droughts have affected carbon sequestration by the terrestrial ecosystems is still unclear. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model, driven by remotely sensed vegetation parameters, was employed to assess the effects of droughts on net ecosystem productivity (NEP) of terrestrial ecosystems in China from 2000 to 2011. Droughts of differing severity, as indicated by a standard precipitation index (SPI), hit terrestrial ecosystems in China extensively in 2001, 2006, 2009, and 2011. The national total annual NEP exhibited the slight decline of -11.3 Tg C yr-2 during the aforementioned years of extensive droughts. The NEP reduction ranged from 61.1 Tg C yr-1 to 168.8 Tg C yr-1. National and regional total NEP anomalies were correlated with the annual mean SPI, especially in Northwest China, North China, Central China, and Southwest China. The reductions in annual NEP in 2001 and 2011 might have been caused by a larger decrease in annual gross primary productivity (GPP) than in annual ecosystem respiration (ER). The reductions experienced in 2009 might be due to a decrease in annual GPP and an increase in annual ER, while reductions in 2006 could stem from a larger increase in ER than in GPP. The effects of droughts on NEP lagged up to 3-6 months, due to different responses of GPP and ER. In eastern China, where is humid and warm, droughts have predominant and short-term lagged influences on NEP. In western regions, cold and arid, the drought effects on NEP were relatively weaker but prone to lasting longer.

The 8th Century Megadrought Across North America

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Therrell, M. D.; Cleaveland, M. K.; Fye, F. K.; Cook, E. R.; Grissino-Mayer, H. D.; Acuna-Soto, R.

2002-12-01

Tree-ring data suggest that the 8th and 16th century megadroughts may have been the most severe and sustained droughts to impact North America in the past 1500 years. The 16th century megadrought may have persisted for up to 40 years, and extended from the tropics to the boreal forest and from the Pacific to Atlantic coasts. Evidence for the 8th century drought is sparse, but tree-ring and lake sediment data indicate that this drought extended from the northern Great Plains, across the southwestern United States, and into central Mexico and the Yucatan peninsula. Tree-ring data from Colorado and New Mexico document severe drought from A.D. 735-765, and may provide accurate and precise dating for the onset of the epic droughts reconstructed during the late first millennium A.D. with sedimentary data from Elk Lake, Minnesota; Moon Lake, South Dakota; La Piscina de Yuriria, Guanajuato; and Lake Chichancanab, Yucatan. If these chronological refinements are correct, then the sedimentary records suggest much greater persistence to the 8th century megadrought than indicated by the very high resolution tree-ring data, and a strong second pulse of prolonged drought late in the first millennium. Analyses of instrumental precipitation and drought indices during the 20th century, along with tree-ring reconstructions of climate in Mexico and the Southwest, indicate that annual and decadal droughts can both simultaneously impact the entire region from New Mexico and Texas down into central Mexico. The intensity and large-scale impact of drought across this region seem to be greatest when La Nina conditions and the low phase of the North Pacific oscillation prevail. The tree-ring dated 8th century megadrought occurred near the decline of the Classic Period civilizations at Teotihuacan in central Mexico and in the Mayan region of the Yucatan. The 8th century megadrought may have interacted with anthropogenic environmental degradation, epidemic disease, and social upheaval to contribute to the collapse of the Classic Period in Mesoamerica.

Response of Main Maize Varieties to Water Stress and Comprehensive Evaluation in Hebei Province

NASA Astrophysics Data System (ADS)

Yue, Haiwang; Chen, Shuping; Bu, Junzhou; Wei, Jianwei; Peng, Haicheng; Li, Yuan; Li, Chunjie; Xie, Junliang

2018-01-01

Drought is a serious threat to maize production in Hebei province. Planting drought resistant maize varieties is an effective measure to solve drought in arid and less rain areas. Drought resistance in maize is controlled by many genes, and multiple indexes should be used for comprehensive evaluation (Campos H et al.2004). In the arid rain shed, using 34 maize varieties to promote crop production compared to the drought resistance test. The experiment was conducted with two treatments of drought stress (irrigation only at seedling stage) and normal irrigation, and 12 agronomic traits related to drought resistance of maize were determined. The results showed that drought had significant effects on maize yield and main agronomic characters. Under drought stress, plant height, ear length, bare tip, ear row number, row grains, 1000-kernel weight, ASI index can be used as identification index of drought resistance of maize in different period. The results indicated that the variety with strong drought resistance is Zhongdi175, the worst drought resistance is Woyu964.

Genotypically Identifying Wheat Mesophyll Conductance Regulation under Progressive Drought Stress

PubMed Central

Olsovska, Katarina; Kovar, Marek; Brestic, Marian; Zivcak, Marek; Slamka, Pavol; Shao, Hong Bo

2016-01-01

Photosynthesis limitation by CO2 flow constraints from sub-stomatal cavities to carboxylation sites in chloroplasts under drought stress conditions is, at least in some plant species or crops not fully understood, yet. Leaf mesophyll conductance for CO2 (gm) may considerably affect both photosynthesis and water use efficiency (WUE) in plants under drought conditions. The aim of our study was to detect the responses of gm in leaves of four winter wheat (Triticum aestivum L.) genotypes from different origins under long-term progressive drought. Based on the measurement of gas-exchange parameters the variability of genotypic responses was analyzed at stomatal (stomata closure) and non-stomatal (diffusional and biochemical) limits of net CO2 assimilation rate (AN). In general, progressive drought caused an increasing leaf diffusion resistance against CO2 flow leading to the decrease of AN, gm and stomatal conductance (gs), respectively. Reduction of gm also led to inhibition of carboxylation efficiency (Vcmax). On the basis of achieved results a strong positive relationship between gm and gs was found out indicating a co-regulation and mutual independence of the relationship under the drought conditions. In severely stressed plants, the stomatal limitation of the CO2 assimilation rate was progressively increased, but to a less extent in comparison to gm, while a non-stomatal limitation became more dominant due to the prolonged drought. Mesophyll conductance (gm) seems to be a suitable mechanism and parameter for selection of improved diffusional properties and photosynthetic carbon assimilation in C3 plants, thus explaining their better photosynthetic performance at a whole plant level during periods of drought. PMID:27551283

Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators

NASA Astrophysics Data System (ADS)

Gouveia, C. M.; Trigo, R. M.; Beguería, S.; Vicente-Serrano, S. M.

2017-04-01

The present work analyzes the drought impacts on vegetation over the entire Mediterranean basin, with the purpose of determining the vegetation communities, regions and seasons at which vegetation is driven by drought. Our approach is based on the use of remote sensing data and a multi-scalar drought index. Correlation maps between fields of monthly Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at different time scales (1-24 months) were computed for representative months of winter (Feb), spring (May), summer (Aug) and fall (Nov). Results for the period from 1982 to 2006 show large areas highly controlled by drought, although presenting high spatial and seasonal differences, with a maximum influence in August and a minimum in February. The highest correlation values are observed in February for 3 months' time scale and in May for 6 and 12 months. The higher control of drought on vegetation in February and May is obtained mainly over the drier vegetation communities (Mediterranean Dry and Desertic) at shorter time scales (3 to 9 months). Additionally, in February the impact of drought on vegetation is lower for Temperate Oceanic and Continental vegetation types and takes place at longer time scales (18-24). The dependence of drought time-scale response with water balance, as obtained through a simple difference between precipitation and reference evapotranspiration, varies with vegetation communities. During February and November low water balance values correspond to shorter time scales over dry vegetation communities, whereas high water balance values implies longer time scales over Temperate Oceanic and Continental areas. The strong control of drought on vegetation observed for Mediterranean Dry and Desertic vegetation types located over areas with high negative values of water balance emphasizes the need for an early warning drought system covering the entire Mediterranean basin. We are confident that these results will provide a useful tool for drought management plans and play a relevant role in mitigating the impact of drought episodes.

Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

Ecological and meteorological drought monitoring in East Asia

NASA Astrophysics Data System (ADS)

Kim, J. B.; Um, M. J.; Kim, Y.; Chae, Y.

2016-12-01

This study aims to how well the ecological drought index can capture the drought status in the East Asia. We estimated the drought severe index (DSI), which uses the evapotranspiration, potential evapotranspiration and the normalized difference vegetation index (NDVI), suggested by Mu et al. (2013) to define the ecological drought. In addition, the meteorological drought index, which is standardized precipitation and evapotranspiration index (SPEI), are estimated and compared to the DSI. The satellite data by moderate resolution imaging spectroradiometer (MODIS) and advanced very-high-resolution radiometer (AVHRR) are used to analyze the DSI and the monthly precipitation and temperature data in the climate research unit (CRU) are applied to estimate the SPEI for 2000-2013 in the East Asia. We conducted the statistical analyses to investigate the drought characteristics of the ecological and meteorological drought indices (i.e. the DSI and SPEI, respectively) and then compared those characteristics drought indices depending on the drought status. We found the DSI did not well captured the drought status when the categories originally suggested by Mu et al. (2013) are applied to divide the drought status in the study area. Consequently, the modified categories for the DSI in this study is suggested and then applied to define the drought status. The modified categories in this study show the great improvement to capture the drought status in the East Asia even though the results cannot be acquired around Taklamakan desert due to the lack of the satellite data. These results illustrate the ecological drought index, such as the DSI, can be applied for the monitoring of the drought in the East Asia and then can give the detailed information of drought status because the satellite data have the relatively high spatial resolutions compared to the observations such as the CRU data. Reference Mu Q, Zhao M, Kimball JS, McDowell NG, Running SW (2013) A remotely sensed global terrestrial drought severity index. Bulletin of the American Meteorological Society 94(1): 83-98. Acknowledgement This study was supported by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. Corresponding Author: yeonjoo.kim@yonsei.ac.kr

Implications of vegetation hydraulic capacitance as an indicator of water stress and drought recovery

NASA Astrophysics Data System (ADS)

Matheny, A. M.; Bohrer, G.

2017-12-01

Above-ground water storage in vegetation plays an integral role in the avoidance of hydraulic impairment to transpiration. New high temporal resolution measurements of dynamic changes in tree hydraulic capacitance are facilitating insights into vegetation water use strategies. Diurnal withdrawal from water storage in leaves, branches, stems, and roots significantly impacts sap flow, stomatal conductance, and transpiration. The ability to store and use water varies based on soil- and root-water availability, tree size, wood vessel anatomy and density, and stomatal response strategy (i.e. isohydricity). We present results from a three-year long study of stem capacitance dynamics in five species in a mixed deciduous forest in Michigan. The site receives 800mm of rainfall annually, but water potential in the well-drained sandy soil nears the permanent wilting point several times annually. We demonstrate radical differences in stored water use between drought tolerant and intolerant species. Red maple, a drought intolerant, isohydric species, showed a strong dependence on stem capacitance for transpiration during both wet and dry periods. Red oak, a more drought hearty, deep rooted, anisohydric species, was much less reliant on withdrawal from water storage during all conditions. During well-watered conditions, withdrawal from storage by red maple was 10 kg day-1, yet storage withdrawal from similarly sized red oaks was 1 kg day-1. Red oaks only drew strongly upon stored water during the driest extremes. Metrics of hydration status derived from capacitance provide a means to explore drought response and recovery. Declines in consecutive days' maximum capacitance indicate an inability to restore lost water and can be used to mark the onset of water stress. Drought recovery can be quantified as the time required for stem water content to return to pre-drought volumes. Capacitance withdrawal and depletion exhibit a clear threshold response to declining soil water availability. These new measurement technologies will also improve our understanding of trees' water status regulation in response to drying soil and drought, and could improve plant hydrodynamic modeling.

Drought assessment in the Dongliao River basin: traditional approaches vs. generalized drought assessment index based on water resources systems

NASA Astrophysics Data System (ADS)

Weng, B. S.; Yan, D. H.; Wang, H.; Liu, J. H.; Yang, Z. Y.; Qin, T. L.; Yin, J.

2015-08-01

Drought is firstly a resource issue, and with its development it evolves into a disaster issue. Drought events usually occur in a determinate but a random manner. Drought has become one of the major factors to affect sustainable socioeconomic development. In this paper, we propose the generalized drought assessment index (GDAI) based on water resources systems for assessing drought events. The GDAI considers water supply and water demand using a distributed hydrological model. We demonstrate the use of the proposed index in the Dongliao River basin in northeastern China. The results simulated by the GDAI are compared to observed drought disaster records in the Dongliao River basin. In addition, the temporal distribution of drought events and the spatial distribution of drought frequency from the GDAI are compared with the traditional approaches in general (i.e., standard precipitation index, Palmer drought severity index and rate of water deficit index). Then, generalized drought times, generalized drought duration, and generalized drought severity were calculated by theory of runs. Application of said runs at various drought levels (i.e., mild drought, moderate drought, severe drought, and extreme drought) during the period 1960-2010 shows that the centers of gravity of them all distribute in the middle reaches of Dongliao River basin, and change with time. The proposed methodology may help water managers in water-stressed regions to quantify the impact of drought, and consequently, to make decisions for coping with drought.

Drought Characteristics Based on the Retrieved Paleoprecipitation in Indus and Ganges River Basins

NASA Astrophysics Data System (ADS)

Davtalabsabet, R.; Wang, D.; Zhu, T.; Ringler, C.

2014-12-01

Indus and Ganges River basins (IGRB), which cover the major parts of India, Nepal, Bangladesh and Pakistan, are considered as the most important socio-economic regions in South Asia. IGRB support the food security of hundreds of millions people in South Asia. The food production in IGRB strictly relies on the magnitude and spatiotemporal pattern of monsoon precipitation. Due to severe drought during the last decades and food production failure in IGRB, several studies have focused on understanding the main drivers for south Asia monsoon failures and drought characteristics based on the historical data. However, the period of available historical data is not enough to address the full characteristic of drought under a changing climate. In this study, an inverse Palmer Drought Severity Index (PDSI) model is developed to retrieve the paleoprecipitation back to 700 years in the region, taking the inputs of available soil water capacity, temperature, and previous reconstructed PDSI based on tree-ring analysis at 2.5 degree resolution. Based on the retrieved paleoprecipitation, drought frequency and intensity are quantified for two periods of 1300-1899 (the reconstruction period) and 1900-2010 (the instrumental period). Previous studies have shown that in IGRB, a severe drought occurs when the annual precipitation deficit, compared with the long-term average precipitation, is greater than 10%. Climatic drought frequency is calculated as the percentage of years with predefined severe droughts. Drought intensity is defined as the average precipitation deficit during all of the years identified as severe droughts. Results show that the drought frequency, as well as the spatial extent, has significantly increased from the reconstruction period to the instrumental period. The drought frequency in the Indus River basin is higher than that in the Ganges River basin. Several mega-droughts are identified during the reconstruction period.

Anticipating U.S. severe droughts - A NASA NEWS initiative on extremes

NASA Astrophysics Data System (ADS)

Wang, S.; Oglesby, R. J.; Hilburn, K. A.; Barandiaran, D.; Pan, M.; Pinker, R. T.; Wang, H.; Santanello, J. A.

2013-12-01

The 2012-2013 drought may not have been predictable as based on current schemes employed for such purposes, but it may have been anticipatable due to knowledge of key precursors such as favorable (remote) SST patterns, and reduced regional soil moisture and winter snow packs. A working group was assembled under the NASA Energy and Water cycle Study (NEWS) to examine the extent to which the 2012 drought could be anticipated and to put recent severe droughts in perspective. A recent NOAA report analyzing the drought of 2012 in the central US has concluded that the drought was not inherently predictable, representing a very anomalous atmospheric circulation pattern. This ';predictability' is based on what happened in the atmosphere, and further, depends on the capabilities of the predictive schemes currently employed. The current prediction schemes emphasize the role of the large-scale atmospheric circulation, but the extent to which the long wave patterns and subsequent short wave effects can be predicted in advance remains unclear. These schemes generally lack full consideration of the local surface state, especially the effect of precursor anomalies in key elements such as soil moisture and snow pack. It is also not clear how well they account for the effects of either interannual or lower-frequency oceanic anomaly patterns. The role of the aforesaid precursors, combined with knowledge of their state, allow some assessment of the ';likelihood' of drought that is not currently being considered. For example, by late winter of 2012 much of the central US was already experiencing dry conditions, including reduced soil moisture, and the snowpack in the Rockies was well below normal. SST patterns appear to have been largely neutral. While the manifestation of the resultant drought also critically dependent on the large-scale atmospheric circulation that subsequently developed, it is clear that the region was preconditioned towards being dry. The other factor about precursors of drought in the previous year. The Drought Monitor data indicated that the 2011 drought remains stronger than the 2012 one in the ';exceptional' category. This feature reflects the different scales in the atmospheric teleconnection pattern and the comparison of the two events can help determine the soil moisture (or lack of) impact on 2012's widespread drought that persisted into 2013. Our hypothesis is that even if one cannot predict the future atmospheric circulation patterns with much certainty for a given year, we may still be able to make some assessment of whether or not a drought may be likely to occur. We refer to this as anticipating drought. As precursors such as soil moisture and snowpack become important in potentially enhancing and prolonging the drought as it occurs, the actual drought that does subsequently occur will depend closely in magnitude and duration on the atmospheric circulation that unfolds.

Drought evolution characteristics and precipitation intensity changes during alternating dry-wet changes in the Huang-Huai-Hai River basin

NASA Astrophysics Data System (ADS)

Yan, D. H.; Wu, D.; Huang, R.; Wang, L. N.; Yang, G. Y.

2013-07-01

Abrupt drought-flood change events caused by atmospheric circulation anomalies have occurred frequently and widely in recent years, which has caused great losses and casualties in China. In this paper, we focus on investigating whether there will be a rainfall occurrence with higher intensity after a drought period in the Huang-Huai-Hai River basin. Combined with the Chinese climate divisions and the basin's DEM (digital elevation model), the basin is divided into seven sub-regions by means of cluster analysis of the basin meteorological stations using the self-organizing map (SOM) neural network method. Based on the daily precipitation data of 171 stations for the years 1961-2011, the changes of drought times with different magnitudes are analyzed, and the number of consecutive days without precipitation is used to identify the drought magnitudes. The first precipitation intensity after a drought period is analyzed with the Pearson-III frequency curve, then the relationship between rainfall intensity and different drought magnitudes is observed, as are the changes of drought times for different years. The results of the study indicated that the occurrence times of different drought levels show an overall increasing trend; there is no clear interdecadal change shown, but the spatial difference is significant. (2) As the drought level increases, the probability of extraordinary rainstorm becomes lower, and the frequency of occurrence of spatial changes in different precipitation intensities vary. In the areas I and II, as the drought level increases, the occurrence frequency of different precipitation intensities first shows a decreasing trend, which becomes an increasing trend when extraordinary drought occurs. In the area III, IV and V, the probability of the different precipitation intensities shows an overall decreasing trend. The areas VI and VII are located at the mountains with high altitudes where the variation of different precipitation intensities with the increase in drought level is relatively complex. (3) As the drought times increase, areas I, II and V, which are located on the coastal and in the valley or basin, are vulnerable to extreme precipitation processes; areas III, IV, VI and VII are located in the inland area, where heavier precipitation is not likely to occur. (4) The local rainfall affected by multiple factors is closely related with drought occurrence. The characteristics between the first rainfall intensity after a drought period and different drought magnitudes (or drought occurrence times) are preliminarily examined in this paper, but its formation mechanism still requires further research.

Description of historical crop calendar data bases developed to support foreign commodity production forecasting project experiments

NASA Technical Reports Server (NTRS)

West, W. L., III (Principal Investigator)

1981-01-01

The content, format, and storage of data bases developed for the Foreign Commodity Production Forecasting project and used to produce normal crop calendars are described. In addition, the data bases may be used for agricultural meteorology, modeling of stage sequences and planting dates, and as indicators of possible drought and famine.

Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions

PubMed Central

Jiang, Yiwei

2013-01-01

Drought is a major environmental stress limiting growth of perennial grasses in temperate regions. Plant drought tolerance is a complex trait that is controlled by multiple genes. Candidate gene association mapping provides a powerful tool for dissection of complex traits. Candidate gene association mapping of drought tolerance traits was conducted in 192 diverse perennial ryegrass (Lolium perenne L.) accessions from 43 countries. The panel showed significant variations in leaf wilting, leaf water content, canopy and air temperature difference, and chlorophyll fluorescence under well-watered and drought conditions across six environments. Analysis of 109 simple sequence repeat markers revealed five population structures in the mapping panel. A total of 2520 expression-based sequence readings were obtained for a set of candidate genes involved in antioxidant metabolism, dehydration, water movement across membranes, and signal transduction, from which 346 single nucleotide polymorphisms were identified. Significant associations were identified between a putative LpLEA3 encoding late embryogenesis abundant group 3 protein and a putative LpFeSOD encoding iron superoxide dismutase and leaf water content, as well as between a putative LpCyt Cu-ZnSOD encoding cytosolic copper-zinc superoxide dismutase and chlorophyll fluorescence under drought conditions. Four of these identified significantly associated single nucleotide polymorphisms from these three genes were also translated to amino acid substitutions in different genotypes. These results indicate that allelic variation in these genes may affect whole-plant response to drought stress in perennial ryegrass. PMID:23386684

Semi-High Throughput Screening for Potential Drought-tolerance in Lettuce (Lactuca sativa) Germplasm Collections

PubMed Central

Knepper, Caleb; Mou, Beiquan

2015-01-01

This protocol describes a method by which a large collection of the leafy green vegetable lettuce (Lactuca sativa L.) germplasm was screened for likely drought-tolerance traits. Fresh water availability for agricultural use is a growing concern across the United States as well as many regions of the world. Short-term drought events along with regulatory intervention in the regulation of water availability coupled with the looming threat of long-term climate shifts that may lead to reduced precipitation in many important agricultural regions has increased the need to hasten the development of crops adapted for improved water use efficiency in order to maintain or expand production in the coming years. This protocol is not meant as a step-by-step guide to identifying at either the physiological or molecular level drought-tolerance traits in lettuce, but rather is a method developed and refined through the screening of thousands of different lettuce varieties. The nature of this screen is based in part on the streamlined measurements focusing on only three water-stress indicators: leaf relative water content, wilt, and differential plant growth following drought-stress. The purpose of rapidly screening a large germplasm collection is to narrow the candidate pool to a point in which more intensive physiological, molecular, and genetic methods can be applied to identify specific drought-tolerant traits in either the lab or field. Candidates can also be directly incorporated into breeding programs as a source of drought-tolerance traits. PMID:25938876

Semi-High Throughput Screening for Potential Drought-tolerance in Lettuce (Lactuca sativa) Germplasm Collections.

PubMed

Knepper, Caleb; Mou, Beiquan

2015-04-17

This protocol describes a method by which a large collection of the leafy green vegetable lettuce (Lactuca sativa L.) germplasm was screened for likely drought-tolerance traits. Fresh water availability for agricultural use is a growing concern across the United States as well as many regions of the world. Short-term drought events along with regulatory intervention in the regulation of water availability coupled with the looming threat of long-term climate shifts that may lead to reduced precipitation in many important agricultural regions has increased the need to hasten the development of crops adapted for improved water use efficiency in order to maintain or expand production in the coming years. This protocol is not meant as a step-by-step guide to identifying at either the physiological or molecular level drought-tolerance traits in lettuce, but rather is a method developed and refined through the screening of thousands of different lettuce varieties. The nature of this screen is based in part on the streamlined measurements focusing on only three water-stress indicators: leaf relative water content, wilt, and differential plant growth following drought-stress. The purpose of rapidly screening a large germplasm collection is to narrow the candidate pool to a point in which more intensive physiological, molecular, and genetic methods can be applied to identify specific drought-tolerant traits in either the lab or field. Candidates can also be directly incorporated into breeding programs as a source of drought-tolerance traits.

Spatiotemporal characterization of current and future droughts in the High Atlas basins (Morocco)

NASA Astrophysics Data System (ADS)

Zkhiri, Wiam; Tramblay, Yves; Hanich, Lahoucine; Jarlan, Lionel; Ruelland, Denis

2018-02-01

Over the past decades, drought has become a major concern in Morocco due to the importance of agriculture in the economy of the country. In the present work, the standardized precipitation index (SPI) is used to monitor the evolution, frequency, and severity of droughts in the High Atlas basins (N'Fis, Ourika, Rhéraya, Zat, and R'dat), located south of Marrakech city. The spatiotemporal characterization of drought in these basins is performed by computing the SPI with precipitation spatially interpolated over the catchments. The Haouz plain, located downstream of these basins, is strongly dependent on water provided by the mountain ranges, as shown by the positive correlations between the normalized difference vegetation index (NDVI) in the plain and the 3, 6, and 12-month SPI in the High Atlas catchments. On the opposite, no significant correlations are found with piezometric levels of the Haouz groundwater due to intensified pumping for irrigation in the recent decades. A relative SPI index was computed to evaluate the climate change impacts on drought occurrence, based on the projected precipitation (2006-2100) from five high-resolution CORDEX regional climate simulations, under two emission scenarios (RCP 4.5 and RCP 8.5). These models show a decrease in precipitation towards the future up to - 65% compared to the historical period. In terms of drought events, the future projections indicate a strong increase in the frequency of SPI events below - 2, considered as severe drought condition.

Assessment of the 1998–2001 drought impact on forest health in southeastern forests: an analysis of drought severity using FHM data

Treesearch

R. J. Klos; G. G. Wang; W. L. Bauerle

2010-01-01

Analyses of forest health indicators monitored through the Forest Health and Monitoring (FHM) program suggested that weather was the most important cause of tree mortality. Drought is of particular importance among weather variables because several global climate change scenarios predicted more frequent and/or intense drought in the Southeastern United States. During...

Development of a drought forecasting model for the Asia-Pacific region using remote sensing and climate data: Focusing on Indonesia

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Kim, Gayoung; Im, Jungho

2017-04-01

Three regions of Indonesia with different rainfall characteristics were chosen to develop drought forecast models based on machine learning. The 6-month Standardized Precipitation Index (SPI6) was selected as the target variable. The models' forecast skill was compared to the skill of long-range climate forecast models in terms of drought accuracy and regression mean absolute error (MAE). Indonesian droughts are known to be related to El Nino Southern Oscillation (ENSO) variability despite of regional differences as well as monsoon, local sea surface temperature (SST), other large-scale atmosphere-ocean interactions such as Indian Ocean Dipole (IOD) and Southern Pacific Convergence Zone (SPCZ), and local factors including topography and elevation. Machine learning models are thus to enhance drought forecast skill by combining local and remote SST and remote sensing information reflecting initial drought conditions to the long-range climate forecast model results. A total of 126 machine learning models were developed for the three regions of West Java (JB), West Sumatra (SB), and Gorontalo (GO) and six long-range climate forecast models of MSC_CanCM3, MSC_CanCM4, NCEP, NASA, PNU, POAMA as well as one climatology model based on remote sensing precipitation data, and 1 to 6-month lead times. When compared the results between the machine learning models and the long-range climate forecast models, West Java and Gorontalo regions showed similar characteristics in terms of drought accuracy. Drought accuracy of the long-range climate forecast models were generally higher than the machine learning models with short lead times but the opposite appeared for longer lead times. For West Sumatra, however, the machine learning models and the long-range climate forecast models showed similar drought accuracy. The machine learning models showed smaller regression errors for all three regions especially with longer lead times. Among the three regions, the machine learning models developed for Gorontalo showed the highest drought accuracy and the lowest regression error. West Java showed higher drought accuracy compared to West Sumatra, while West Sumatra showed lower regression error compared to West Java. The lower error in West Sumatra may be because of the smaller sample size used for training and evaluation for the region. Regional differences of forecast skill are determined by the effect of ENSO and the following forecast skill of the long-range climate forecast models. While shown somewhat high in West Sumatra, relative importance of remote sensing variables was mostly low in most cases. High importance of the variables based on long-range climate forecast models indicates that the forecast skill of the machine learning models are mostly determined by the forecast skill of the climate models.

Meteorological contribution to the mitigation and adaptation of the 'extreme water events' of Hungarian Great Plain

NASA Astrophysics Data System (ADS)

Dunkel, Z.; Vincze, E.; Moring, A.

2012-04-01

The lack of water is a traditional problem of Hungarian agriculture. Two big rivers cross the territory of Hungary and times to times they produce huge floods. In the Carpathian basin a flood and a drought can occur in the same year. The general problem of Hungarian agriculture is the 'water' in two contexts, in lack of water and in surplus. Not only of the next year but of the next decades the basic question of the Hungarian planning is how the national economy can handle the increasing numbers of unexpected negative events of climate change because the growing numbers of sometimes catastrophic floods and droughts seems to be connected with global warming. Beside the 'normal floods' in the last few years the numbers of so called flash floods show increasing tendency too. The presentation summarises the 'extreme water events' of Hungarian Great Plain, and the forecast problems of Hungarian meteorology together with the National strategy in mitigation and adaptation in connection with climate change. From meteorological point of view the handling of flood and drought problem is totally different. In case of flood the stress is on the forecast, in case of drought mainly of the evaluation of the historical data mainly the short and long term evaluation of drought indices. Drought indices seem to be the simplest tools in drought analysis. The more or less well known and popular indices have been collected and compared not only with the well known simple but more complicated water balance and so called 'recursive' indices beside few ones use remotely sensed data, mainly satellite born information. The indices are classified into five groups, namely 'precipitation', 'water balance', 'soil moisture', 'recursive' and 'remote sensing' indices. For every group typical expressions are given and the possible use in the decision making and hazard risk evaluation and compensation of the farmers after the events. The meteorological elements of new Hungarian agricultural risk strategy will be shown.

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

NASA Astrophysics Data System (ADS)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

The influence of oceanic basins on drought and ecosystem dynamics in Northeast Brazil

NASA Astrophysics Data System (ADS)

Santos Pereira, Marcos Paulo; Justino, Flavio; Mendes Malhado, Ana Claudia; Barbosa, Humberto; Marengo, José

2014-12-01

The 2012 drought in Northeast Brazil was the harshest in decades, with potentially significant impacts on the vegetation of the unique semi-arid caatinga biome and on local livelihoods. Here, we use a coupled climate-vegetation model (CCM3-IBIS) to: (1) investigate the role of the Pacific and Atlantic oceans in the 2012 drought, and; (2) evaluate the response of the caatinga vegetation to the 2012 climate extreme. Our results indicate that anomalous sea surface temperatures (SSTs) in the Atlantic Ocean were the primary factor forcing the 2012 drought, with Pacific Ocean SST having a larger role in sustaining typical climatic conditions in the region. The drought strongly influenced net primary production in the caatinga, causing a reduction in annual net ecosystem exchange indicating a reduction in amount of CO2 released to the atmosphere.

Drought responses of flood-tolerant trees in Amazonian floodplains

PubMed Central

Parolin, Pia; Lucas, Christine; Piedade, Maria Teresa F.; Wittmann, Florian

2010-01-01

Background Flood-tolerant tree species of the Amazonian floodplain forests are subjected to an annual dry period of variable severity imposed when low river-water levels coincide with minimal precipitation. Although the responses of these species to flooding have been examined extensively, their responses to drought, in terms of phenology, growth and physiology, have been neglected hitherto, although some information is found in publications that focus on flooding. Scope The present review examines the dry phase of the annual flooding cycle. It consolidates existing knowledge regarding responses to drought among adult trees and seedlings of many Amazonian floodplain species. Main Findings Flood-tolerant species display variable physiological responses to dry periods and drought that indicate desiccation avoidance, such as reduced photosynthetic activity and reduced root respiration. However, tolerance and avoidance strategies for drought vary markedly among species. Drought can substantially decrease growth, biomass and photosynthetic activity among seedlings in field and laboratory studies. When compared with the responses to flooding, drought can impose higher seedling mortality and slower growth rates, especially among evergreen species. Results indicate that tolerance and avoidance strategies for drought vary markedly between species. Both seedling recruitment and photosynthetic activity are affected by drought, Conclusions For many species, the effects of drought can be as important as flooding for survival and growth, particularly at the seedling phase of establishment, ultimately influencing species composition. In the context of climate change and predicted decreases in precipitation in the Amazon Basin, the effects of drought on plant physiology and species distribution in tropical floodplain forest ecosystems should not be overlooked. PMID:19880423

Utilizing Objective Drought Thresholds to Improve Drought Monitoring with the SPI

NASA Astrophysics Data System (ADS)

Leasor, Z. T.; Quiring, S. M.

2017-12-01

Drought is a prominent climatic hazard in the south-central United States. Droughts are frequently monitored using the severity categories determined by the U.S. Drought Monitor (USDM). This study uses the Standardized Precipitation Index (SPI) to conduct a drought frequency analysis across Texas, Oklahoma, and Kansas using PRISM precipitation data from 1900-2015. The SPI is shown to be spatiotemporally variant across the south-central United States. In particular, utilizing the default USDM severity thresholds may underestimate drought severity in arid regions. Objective drought thresholds were implemented by fitting a CDF to each location's SPI distribution. This approach results in a more homogeneous distribution of drought frequencies across each severity category. Results also indicate that it may be beneficial to develop objective drought thresholds for each season and SPI timescale. This research serves as a proof-of-concept and demonstrates how drought thresholds should be objectively developed so that they are appropriate for each climatic region.

Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought.

PubMed

Frolking, Steve; Hagen, Stephen; Braswell, Bobby; Milliman, Tom; Herrick, Christina; Peterson, Seth; Roberts, Dar; Keller, Michael; Palace, Michael

2017-01-01

Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon's vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999-2009, and low morning backscatter persisted for 2006-2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts.

Drought resistance across California ecosystems: Evaluating changes in carbon dynamics using satellite imagery

USGS Publications Warehouse

Malone, Sparkle; Tulbure, Mirela; Pérez-Luque, Antonio J.; Assal, Timothy J.; Bremer, Leah; Drucker, Debora; Hillis, Vicken; Varela, Sara; Goulden, Michael

2016-01-01

Drought is a global issue that is exacerbated by climate change and increasing anthropogenic water demands. The recent occurrence of drought in California provides an important opportunity to examine drought response across ecosystem classes (forests, shrublands, grasslands, and wetlands), which is essential to understand how climate influences ecosystem structure and function. We quantified ecosystem resistance to drought by comparing changes in satellite-derived estimates of water-use efficiency (WUE = net primary productivity [NPP]/evapotranspiration [ET]) under normal (i.e., baseline) and drought conditions (ΔWUE = WUE2014 − baseline WUE). With this method, areas with increasing WUE under drought conditions are considered more resilient than systems with declining WUE. Baseline WUE varied across California (0.08 to 3.85 g C/mm H2O) and WUE generally increased under severe drought conditions in 2014. Strong correlations between ΔWUE, precipitation, and leaf area index (LAI) indicate that ecosystems with a lower average LAI (i.e., grasslands) also had greater C-uptake rates when water was limiting and higher rates of carbon-uptake efficiency (CUE = NPP/LAI) under drought conditions. We also found that systems with a baseline WUE ≤ 0.4 exhibited a decline in WUE under drought conditions, suggesting that a baseline WUE ≤ 0.4 might be indicative of low drought resistance. Drought severity, precipitation, and WUE were identified as important drivers of shifts in ecosystem classes over the study period. These findings have important implications for understanding climate change effects on primary productivity and C sequestration across ecosystems and how this may influence ecosystem resistance in the future.

Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought

PubMed Central

Hagen, Stephen; Braswell, Bobby; Milliman, Tom; Herrick, Christina; Peterson, Seth; Roberts, Dar; Keller, Michael; Palace, Michael

2017-01-01

Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon’s vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999–2009, and low morning backscatter persisted for 2006–2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts. PMID:28873422

Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches

PubMed Central

Kumar, Arvind; Dixit, Shalabh; Ram, T.; Yadaw, R. B.; Mishra, K. K.; Mandal, N. P.

2014-01-01

The increased occurrence and severity of drought stress have led to a high yield decline in rice in recent years in drought-affected areas. Drought research at the International Rice Research Institute (IRRI) over the past decade has concentrated on direct selection for grain yield under drought. This approach has led to the successful development and release of 17 high-yielding drought-tolerant rice varieties in South Asia, Southeast Asia, and Africa. In addition to this, 14 quantitative trait loci (QTLs) showing a large effect against high-yielding drought-susceptible popular varieties were identified using grain yield as a selection criterion. Six of these (qDTY 1.1, qDTY 2.2, qDTY 3.1, qDTY 3.2, qDTY 6.1, and qDTY 12.1) showed an effect against two or more high-yielding genetic backgrounds in both the lowland and upland ecosystem, indicating their usefulness in increasing the grain yield of rice under drought. The yield of popular rice varieties IR64 and Vandana has been successfully improved through a well-planned marker-assisted backcross breeding approach, and QTL introgression in several other popular varieties is in progress. The identification of large-effect QTLs for grain yield under drought and the higher yield increase under drought obtained through the use of these QTLs (which has not been reported in other cereals) indicate that rice, because of its continuous cultivation in two diverse ecosystems (upland, drought tolerant, and lowland, drought susceptible), has benefited from the existence of larger genetic variability than in other cereals. This can be successfully exploited using marker-assisted breeding. PMID:25205576

Contrasting Changes Caused by Drought and Submergence Stresses in Bermudagrass (Cynodon dactylon)

PubMed Central

Ye, Tiantian; Shi, Haitao; Wang, Yanping; Chan, Zhulong

2015-01-01

In this study, we investigated the mechanisms by which bermudagrass withstands the drought and submergence stresses through physiological, proteomic and metabolomic approaches. The results showed that significant physiological changes were observed after drought treatment, while only slight changes after submergence treatment, including compatible solute contents, ROS levels and antioxidant enzyme activities. Proteomics results showed that 81 proteins regulated by drought or submergence treatment were identified by MALDI-TOF-MS. Among them, 76 proteins were modulated by drought stress with 46 increased abundance and 30 decreased abundance. Forty-five showed abundance changes after submergence treatment with 10 increased and 35 decreased. Pathway enrichment analysis revealed that pathways of amino acid metabolism and mitochondrial electron transport/ATP synthesis were only enriched by drought treatment, while other pathways including photosynthesis, biodegradation of xenobiotics, oxidative pentose phosphate, glycolysis and redox were commonly over-represented after both drought and submergence treatments. Metabolomic analysis indicated that most of the metabolites were up-regulated by drought stress, while 34 of 40 metabolites contents exhibited down-regulation or no significant changes when exposed to submergence stress, including sugars and sugar alcohols. These data indicated that drought stress extensively promoted photosynthesis and redox metabolisms while submergence stress caused declined metabolisms and dormancy in Cynodon dactylon. Taken together, the quiescence strategy with retarded growth might allow bermudagrass to be adaptive to long-term submerged environment, while activation of photosynthesis and redox, and accumulation of compatible solutes and molecular chaperones increased bermudagrass tolerance to drought stress. PMID:26617615

Introduction of Drought Monitoring and Forecasting System based on Real-time Water Information Using ICT

NASA Astrophysics Data System (ADS)

Lee, Y., II; Kim, H. S.; Chun, G.

2016-12-01

There were severe damages such as restriction on water supply caused by continuous drought from 2014 to 2015 in South Korea. Through this drought event, government of South Korea decided to establish National Drought Information Analysis Center in K-water(Korea Water Resources Corporation) and introduce a national drought monitoring and early warning system to mitigate those damages. Drought index such as SPI(Standard Precipitation Index), PDSI(Palmer Drought Severity Index) and SMI(Soil Moisture Index) etc. have been developed and are widely used to provide drought information in many countries. However, drought indexes are not appropriate for drought monitoring and early warning in civilized countries with high population density such as South Korea because it could not consider complicated water supply network. For the national drought monitoring and forecasting of South Korea, `Drought Information Analysis System' (D.I.A.S) which is based on the real time data(storage, flowrate, waterlevel etc.) was developed. Based on its advanced methodology, `DIAS' is changing the paradigm of drought monitoring and early warning systems. Because `D.I.A.S' contains the information of water supply network from water sources to the people across the nation and provides drought information considering the real-time hydrological conditions of each and every water source. For instance, in case the water level of a specific dam declines to predetermined level of caution, `D.I.A.S' will notify people who uses the dam as a source of residential or industrial water. It is expected to provide credible drought monitoring and forecasting information with a strong relationship between drought information and the feelings of people rely on water users by `D.I.A.S'.

Understanding the Central Equatorial African long-term drought using AMIP-type simulations

NASA Astrophysics Data System (ADS)

Hua, Wenjian; Zhou, Liming; Chen, Haishan; Nicholson, Sharon E.; Jiang, Yan; Raghavendra, Ajay

2018-02-01

Previous studies show that Indo-Pacific sea surface temperature (SST) variations may help to explain the observed long-term drought during April-May-June (AMJ) since the 1990s over Central equatorial Africa (CEA). However, the underlying physical mechanisms for this drought are still not clear due to observation limitations. Here we use the AMIP-type simulations with 24 ensemble members forced by observed SSTs from the ECHAM4.5 model to explore the likely physical processes that determine the rainfall variations over CEA. We not only examine the ensemble mean (EM), but also compare the "good" and "poor" ensemble members to understand the intra-ensemble variability. In general, EM and the "good" ensemble member can simulate the drought and associated reduced vertical velocity and anomalous anti-cyclonic circulation in the lower troposphere. However, the "poor" ensemble members cannot simulate the drought and associated circulation patterns. These contrasts indicate that the drought is tightly associated with the tropical Walker circulation and atmospheric teleconnection patterns. If the observational circulation patterns cannot be reproduced, the CEA drought will not be captured. Despite the large intra-ensemble spread, the model simulations indicate an essential role of SST forcing in causing the drought. These results suggest that the long-term drought may result from tropical Indo-Pacific SST variations associated with the enhanced and westward extended tropical Walker circulation.

Measuring the invisible: Analysis of the Sustainable Development Goals in relation to populations exposed to drought.

PubMed

Sena, Aderita; de Freitas, Carlos Machado; Barcellos, Christovam; Ramalho, Walter; Corvalan, Carlos

2016-03-01

Brazil, together with all the member countries of the United Nations, is in a process of adoption of a group of Sustainable Development Goals, including targets and indicators. This article considers the implications of these goals and their proposed targets, for the Semi-Arid region of Brazil. This region has recurring droughts which may worsen with climate change, further weakening the situation of access of water for human consumption in sufficient quantity and quality, and as a result, the health conditions of the exposed populations. This study identifies the relationship between drought and health, in an effort to measure progress in this region (1,135 municipalities), comparing relevant indicators with the other 4,430 municipalities in Brazil, based on census data from 1991, 2000 and 2010. Important inequalities between the municipalities of this region and the municipalities of the rest of Brazil are identified, and discussed in the context of what is necessary for achieving the Sustainable Development Goals in the Semi-arid Region, principally in relation to the measures for adaptation to achieve universal and equitable access to drinking water.

Middle-term metropolitan water availability index assessment based on synergistic potentials of multi-sensor data

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Yang, Y. Jeffrey; Daranpob, Ammarin

2010-03-01

The impact of recent drought and water pollution episodes results in an acute need to project future water availability to assist water managers in water utility infrastructure management within many metropolitan regions. Separate drought and water quality indices previously developed might not be sufficient for the purpose of such an assessment. This paper describes the development of the "Metropolitan Water Availability Index (MWAI)" and its potential applications in assessing the middle-term water availability at the watershed scale in a fast growing metropolitan region - the Manatee County near Tampa Bay, Florida, U.S.A. The MWAI framework is based on a statistical approach that seeks to reflect the continuous spatial and temporal variations of both water quantity and quality using a simple numerical index. Such a trend analysis will surely result in the final MWAI values for regional water management systems within a specified range. By using remote sensing technologies and data processing techniques, continuous monitoring of spatial and temporal distributions of key water availability variables, such as evapotranspiration (ET) and precipitation, is made achievable. These remote sensing technologies can be ground-based (e.g., radar estimates of rainfall), or based on remote sensing data gathered by aircraft or satellites. Using a middle term historical record, the MWAI was applied to the Manatee County water supplies. The findings clearly indicate that only eight out of twelve months in 2008 had positive MWAI values during the year. Such numerical findings are consistent with the observational evidence of statewide drought events in 2006-2008, which implies the time delay between the ending of severe drought period and the recovery of water availability in MWAI. It is expected that this forward-looking novel water availability forecasting platform will help provide a linkage in methodology between strategic planning, master planning, and the plant operation and adaptations in response to the MWAI implications.

The European Drought Observatory (EDO): Current State and Future Directions

NASA Astrophysics Data System (ADS)

Vogt, J.; Singleton, A.; Sepulcre, G.; Micale, F.; Barbosa, P.

2012-12-01

Europe has repeatedly been affected by droughts, resulting in considerable ecological and economic damage and climate change studies indicate a trend towards increasing climate variability most likely resulting in more frequent drought occurrences also in Europe. Against this background, the European Commission's Joint Research Centre (JRC) is developing methods and tools for assessing, monitoring and forecasting droughts in Europe and develops a European Drought Observatory (EDO) to complement and integrate national activities with a European view. At the core of the European Drought Observatory (EDO) is a portal, including a map server, a metadata catalogue, a media-monitor and analysis tools. The map server presents Europe-wide up-to-date information on the occurrence and severity of droughts, which is complemented by more detailed information provided by regional, national and local observatories through OGC compliant web mapping and web coverage services. In addition, time series of historical maps as well as graphs of the temporal evolution of drought indices for individual grid cells and administrative regions in Europe can be retrieved and analysed. Current work is focusing on validating the available products, improving the functionalities, extending the linkage to additional national and regional drought information systems and improving medium to long-range probabilistic drought forecasting products. Probabilistic forecasts are attractive in that they provide an estimate of the range of uncertainty in a particular forecast. Longer-term goals include the development of long-range drought forecasting products, the analysis of drought hazard and risk, the monitoring of drought impact and the integration of EDO in a global drought information system. The talk will provide an overview on the development and state of EDO, the different products, and the ways to include a wide range of stakeholders (i.e. European, national river basin, and local authorities) in the development of the system as well as an outlook on the future developments.

The role of mountain precipitation as a drought buffer in Puerto Rico: Assessing natural systems' resilience to change

NASA Astrophysics Data System (ADS)

Scholl, M. A.; Clark, K. E.; Van Beusekom, A.; Shanley, J. B.; Torres-Sanchez, A.; Murphy, S. F.; Gonzalez, G.

2017-12-01

Like many island and coastal areas, the Luquillo Mountains of Puerto Rico receive orographic precipitation (rain and cloud water), maintaining headwater streamflow and allowing diverse forest ecosystems to thrive. Although rainfall from regional-scale convective systems is greater in volume, multiple lines of evidence (stable isotope tracers; precipitation amount, frequency, and intensity; cloud immersion; regional cloud dynamics; weather analysis) show that trade-wind orographic precipitation contributes significantly to streamflow, soil water, and shallow groundwater. Ceilometer data and time-lapse photography of cloud-immersed conditions at the mountain indicated a seasonally invariant, sustained overnight regime of cloud water precipitation, in addition to the abundant rainfall in the mountains. Rising ocean temperatures and a warming tropical climate lead to questions about persistence of the trade-wind associated orographic precipitation and the resilience of similar mountain ecosystems to change. Projections for Caribbean climate change include amplification of trade winds; less frequent, more intense large convective systems; and a warming ocean. These may have opposing effects on mountain precipitation, increasing uncertainty about processes that mitigate drought. Field studies provide insights regarding these questions. Ceilometer and satellite observations showed cloud base is higher over the mountains than in the surrounding Caribbean region; with the trade-wind inversion cap, further rise in cloud base may produce shallower clouds and reduced precipitation. We analyzed the February-October 2015 drought, characterized by strong El Niño conditions, an absence of tropical storm systems, and reduced convection in easterly waves. Combined δ2H, δ18O and d-excess signatures of streamflow indicated precipitation was derived from shallow convective systems, trade-wind showers and cloud water. During severe drought on the island, streamflow-sustaining rainfall at the mountain station at 640 m persisted, albeit with 19% lower frequency and 52% fewer large (>10 mm) rain events than the 20-year average. Clearly, resilience of the mountain forest ecosystem and of streamflow to drought periods depends on orographic precipitation.

Exploring standardized precipitation evapotranspiration index for drought assessment in Bangladesh.

PubMed

Miah, Md Giashuddin; Abdullah, Hasan Muhammad; Jeong, Changyoon

2017-10-09

Drought is a critical issue, and it has a pressing, negative impact on agriculture, ecosystems, livelihoods, food security, and sustainability. The problem has been studied globally, but its regional or even local dimension is sometimes overlooked. Local-level drought assessment is necessary for developing adaptation and mitigation strategies for that particular region. Keeping this in understanding, an attempt was made to create a detailed assessment of drought characteristics at the local scale in Bangladesh. Standardized precipitation evapotranspiration (SPEI) is a new drought index that mainly considers the rainfall and evapotranspiration data set. Globally, SPEI has become a useful drought index, but its local scale application is not common. SPEI base (0.5° grid data) for 110 years (1901-2011) was utilized to overcome the lack of long-term climate data in Bangladesh. Available weather data (1955-2011) from Bangladesh Meteorology Department (BMD) were analyzed to calculate SPEI weather station using the SPEI calculator. The drivers for climate change-induced droughts were characterized by residual temperature and residual rainfall data from different BMD stations. Grid data (SPEI base ) of 26 stations of BMD were used for drought mapping. The findings revealed that the frequency and intensity of drought are higher in the northwestern part of the country which makes it vulnerable to both extreme and severe droughts. Based on the results, the SPEI-based drought intensity and frequency analyses were carried out, emphasizing Rangpur (northwest region) as a hot spot, to get an insight of drought assessment in Bangladesh. The findings of this study revealed that SPEI could be a valuable tool to understand the evolution and evaluation of the drought induced by climate change in the country. The study also justified the immediate need for drought risk reduction strategies that should lead to relevant policy formulations and agricultural innovations for developing drought adaptation, mitigation, and resilience mechanisms in Bangladesh.

Habitat-specific AMF symbioses enhance drought tolerance of a native Kenyan grass

NASA Astrophysics Data System (ADS)

Petipas, Renee H.; González, Jonathan B.; Palmer, Todd M.; Brody, Alison K.

2017-01-01

The role of arbuscular mycorrhizal fungi (AMF) in enhancing plant tolerance to drought is well known. However, the degree to which AMF-plant symbioses are locally adapted has been suggested but is less well understood, especially at small spatial scales. Here, we examined the effects of two arbuscular mycorrhizal fungal communities on drought tolerance of Themeda triandra, a native African perennial bunchgrass. In our study area, mound building activities of Odontotermes sp. termites produce heterogeneous habitat, particularly with respect to water availability, and do so over small spatial scales (<50 m). Thus, plants and their AMF symbionts may experience identical climatic conditions but very different edaphic conditions. We hypothesized that AMF from off-mound areas, where plants experience drought more intensely than on termite mounds, would confer greater protection from drought conditions than AMF from termite mound soils. To test this, we conducted a greenhouse experiment in which we grew plants in soils that we inoculated with fungi from on or off termite mounds, or with a sterilized control inoculum. Our results reveal habitat-specific AMF effects on host stomatal functioning and growth. Contrary to our expectations, drought stressed grasses inoculated with AMF from termite mounds closed stomata less, and produced 60% more leaves than those inoculated with off-mound AMF, thus exhibiting higher levels of tolerance. Mound-inoculated plants that were drought stressed also produced more than twice as many leaves as non-inoculated plants. Longer-term productivity measurements indicate both on- and off-mound inoculated plants were able to recover to a greater extent than non-inoculated plants, indicating that AMF associations in general help plants recover from drought. These findings highlight the important role that AMF play in mitigating drought stress and indicate that AMF affect how plants experience drought in a small scale, habitat-specific manner.

Assessment of 21st century drought conditions at Shasta Dam based on dynamically projected water supply conditions by a regional climate model coupled with a physically-based hydrology model.

PubMed

Trinh, T; Ishida, K; Kavvas, M L; Ercan, A; Carr, K

2017-05-15

Along with socioeconomic developments, and population increase, natural disasters around the world have recently increased the awareness of harmful impacts they cause. Among natural disasters, drought is of great interest to scientists due to the extraordinary diversity of their severity and duration. Motivated by the development of a potential approach to investigate future possible droughts in a probabilistic framework based on climate change projections, a methodology to consider thirteen future climate projections based on four emission scenarios to characterize droughts is presented. The proposed approach uses a regional climate model coupled with a physically-based hydrology model (Watershed Environmental Hydrology Hydro-Climate Model; WEHY-HCM) to generate thirteen equally likely future water supply projections. The water supply projections were compared to the current water demand for the detection of drought events and estimation of drought properties. The procedure was applied to Shasta Dam watershed to analyze drought conditions at the watershed outlet, Shasta Dam. The results suggest an increasing water scarcity at Shasta Dam with more severe and longer future drought events in some future scenarios. An important advantage of the proposed approach to the probabilistic analysis of future droughts is that it provides the drought properties of the 100-year and 200-year return periods without resorting to any extrapolation of the frequency curve. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of physiological and anatomical changes of C3 (Oryza sativa [L.]) and C4 (Echinochloa crusgalli [L.]) leaves in response to drought stress

NASA Astrophysics Data System (ADS)

Hamim, Hamim; Banon, Sri; Dorly, Dorly

2016-01-01

The experiment aimed to analyse the different response of C3 (Oryza sativa L.) and C4 (Echinochloa crusgalli L.) species to drought stress based on physiological and anatomical properties. Seeds of rice (Oryza sativa) and Echinochloa (Echinochloa crusgalli) were grown in 15 cm (D) pot for 6 weeks under well-watered conditions. After 6 weeks the plants were divided into two groups, (1) well-watered which were watered daily, and (2) drought stress which were withheld from watering for 6 days. After 6 days of drought, the plants were then re-watered to analyse plant recovery. During drought period, the plants were analysed for growth, leaf relative water content (RWC), photosynthesis, and leaf anatomy. Drought stress significantly reduced leaf RWC of both species, but the reduction was bigger in rice than in Echinochloa. The maximum efficiency of photosynthesis (Fv/Fm) was decrease significantly in response to drought stress by about 48.04% in rice, while it was only 34.40% in Echinochloa. Anatomical analysis showed drought treatment tended to reduce leaf thickness in the area of bulliform cell, major- as well as intervein and xylem diameter, more in Echinochloa than in rice, suggesting that the decrease of vein and xylem diameter is among the anatomical parameters that is important to overcome from drought stress in Echinochloa. The number of chloroplast in the mesophyll cell and bundle sheath cell (BSC) was different between these two species, where in Echinochloa chloroplast was found in both mesophyll as well as BSC, while in rice it was only found in mesophyll cell, confirmed that Echinochloa is a C4 and rice is a C3 species. Interestingly, in Echinochloa, the number of chloroplast was significantly increased due to drought stress in BSC, but not in mesophyll cell. The number of starch granules also dramatically increased in response to drought in the mesophyll cells of rice and Echinochloa, and in the bundle sheath cell of Echinochloa which indicate that C3 cycle may be occurred in C4 species, at least in Echinochloa, especially during drought stress.

a New Framework for Characterising Simulated Droughts for Future Climates

NASA Astrophysics Data System (ADS)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross-Dependence across Multiple Time Scales: Implications for Downscaling, Journal of Climate, 29(10), 3519-3539. Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 50, 650-660, doi:10.1002/2013WR013845.

Short- and long-term efficacy of forest thinning to mitigate drought impacts in mountain forests in the European Alps.

PubMed

Elkin, Ché; Giuggiola, Arnaud; Rigling, Andreas; Bugmann, Harald

2015-06-01

In many regions of the world, drought is projected to increase under climate change, with potential negative consequences for forests and their ecosystem services (ES). Forest thinning has been proposed as a method for at least temporarily mitigating drought impacts, but its general applicability and longer-term impacts are unclear. We use a process-based forest model to upscale experimental data for evaluating the impacts of forest thinning in a drought-susceptible valley in the interior of the European Alps, with the specific aim of assessing (1) when and where thinning may be most effective and (2) the longer-term implications for forest dynamics. Simulations indicate that forests will be impacted by climate-induced increases in drought across a broad elevation range. At lower elevations, where drought is currently prevalent, thinning is projected to temporarily reduce tree mortality, but to have minor impacts on forest dynamics in the longer term. Thinning may be particularly useful at intermediate and higher elevations as a means of temporarily reducing mortality in drought-sensitive species such as Norway spruce and larch, which currently dominate these elevations. However, in the longer term, even intense thinning will likely not be sufficient to prevent a climate change induced dieback of these species, which is projected to occur under even moderate climate change. Thinning is also projected to have the largest impact on long-term forest dynamics at intermediate elevations, with the magnitude of the impact depending on the timing and intensity of thinning. More intense thinning that is done later is projected to more strongly promote a transition to more drought-tolerant species. We conclude that thinning is a viable option for temporarily reducing the negative drought impacts on forests, but that efficient implementation of thinning should be contingent on a site-specific evaluation of the near term risk of significant drought, and how thinning will impact the rate and direction of climate driven forest conversion.

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

Assessing the add value of ensemble forecast in a drought early warning

NASA Astrophysics Data System (ADS)

Calmanti, Sandro; Bosi, Lorenzo; Fernandez, Jesus; De Felice, Matteo

2015-04-01

The EU-FP7 project EUPORIAS is developing a prototype climate service to enhance the existing food security drought early warning system in Ethiopia. The Livelihoods, Early Assessment and Protection (LEAP) system is the Government of Ethiopia's national food security early warning system, established with the support of WFP and the World Bank in 2008. LEAP was designed to increase the predictability and timeliness of response to drought-related food crises in Ethiopia. It combines early warning with contingency planning and contingency funding, to allow the government, WFP and other partners to provide early assistance in anticipation of an impending catastrophes. Currently, LEAP uses satellite based rainfall estimates to monitor drought conditions and to compute needs. The main aim of the prototype is to use seasonal hindcast data to assess the added value of using ensemble climate rainfall forecasts to estimate the cost of assistance of population hit by major droughts. We outline the decision making process that is informed by the prototype climate service, and we discuss the analysis of the expected and skill of the available rainfall forecast data over Ethiopia. One critical outcome of this analysis is the strong dependence of the expected skill on the observational estimate assumed as reference. A preliminary evaluation of the full prototype products (drought indices and needs estimated) using hindcasts data will also be presented.

The Physiology and Proteomics of Drought Tolerance in Maize: Early Stomatal Closure as a Cause of Lower Tolerance to Short-Term Dehydration?

PubMed Central

Benešová, Monika; Holá, Dana; Fischer, Lukáš; Jedelský, Petr L.; Hnilička, František; Wilhelmová, Naďa; Rothová, Olga; Kočová, Marie; Procházková, Dagmar; Honnerová, Jana; Fridrichová, Lenka; Hniličková, Helena

2012-01-01

Understanding the response of a crop to drought is the first step in the breeding of tolerant genotypes. In our study, two maize (Zea mays L.) genotypes with contrasting sensitivity to dehydration were subjected to moderate drought conditions. The subsequent analysis of their physiological parameters revealed a decreased stomatal conductance accompanied by a slighter decrease in the relative water content in the sensitive genotype. In contrast, the tolerant genotype maintained open stomata and active photosynthesis, even under dehydration conditions. Drought-induced changes in the leaf proteome were analyzed by two independent approaches, 2D gel electrophoresis and iTRAQ analysis, which provided compatible but only partially overlapping results. Drought caused the up-regulation of protective and stress-related proteins (mainly chaperones and dehydrins) in both genotypes. The differences in the levels of various detoxification proteins corresponded well with the observed changes in the activities of antioxidant enzymes. The number and levels of up-regulated protective proteins were generally lower in the sensitive genotype, implying a reduced level of proteosynthesis, which was also indicated by specific changes in the components of the translation machinery. Based on these results, we propose that the hypersensitive early stomatal closure in the sensitive genotype leads to the inhibition of photosynthesis and, subsequently, to a less efficient synthesis of the protective/detoxification proteins that are associated with drought tolerance. PMID:22719860

The physiology and proteomics of drought tolerance in maize: early stomatal closure as a cause of lower tolerance to short-term dehydration?

PubMed

Benešová, Monika; Holá, Dana; Fischer, Lukáš; Jedelský, Petr L; Hnilička, František; Wilhelmová, Naďa; Rothová, Olga; Kočová, Marie; Procházková, Dagmar; Honnerová, Jana; Fridrichová, Lenka; Hniličková, Helena

2012-01-01

Understanding the response of a crop to drought is the first step in the breeding of tolerant genotypes. In our study, two maize (Zea mays L.) genotypes with contrasting sensitivity to dehydration were subjected to moderate drought conditions. The subsequent analysis of their physiological parameters revealed a decreased stomatal conductance accompanied by a slighter decrease in the relative water content in the sensitive genotype. In contrast, the tolerant genotype maintained open stomata and active photosynthesis, even under dehydration conditions. Drought-induced changes in the leaf proteome were analyzed by two independent approaches, 2D gel electrophoresis and iTRAQ analysis, which provided compatible but only partially overlapping results. Drought caused the up-regulation of protective and stress-related proteins (mainly chaperones and dehydrins) in both genotypes. The differences in the levels of various detoxification proteins corresponded well with the observed changes in the activities of antioxidant enzymes. The number and levels of up-regulated protective proteins were generally lower in the sensitive genotype, implying a reduced level of proteosynthesis, which was also indicated by specific changes in the components of the translation machinery. Based on these results, we propose that the hypersensitive early stomatal closure in the sensitive genotype leads to the inhibition of photosynthesis and, subsequently, to a less efficient synthesis of the protective/detoxification proteins that are associated with drought tolerance.

RNA-Seq Analysis Reveals MAPKKK Family Members Related to Drought Tolerance in Maize

PubMed Central

Ren, Wen; Yang, Fengling; He, Hang; Zhao, Jiuran

2015-01-01

The mitogen-activated protein kinase (MAPK) cascade is an evolutionarily conserved signal transduction pathway that is involved in plant development and stress responses. As the first component of this phosphorelay cascade, mitogen-activated protein kinase kinase kinases (MAPKKKs) act as adaptors linking upstream signaling steps to the core MAPK cascade to promote the appropriate cellular responses; however, the functions of MAPKKKs in maize are unclear. Here, we identified 71 MAPKKK genes, of which 14 were novel, based on a computational analysis of the maize (Zea mays L.) genome. Using an RNA-seq analysis in the leaf, stem and root of maize under well-watered and drought-stress conditions, we identified 5,866 differentially expressed genes (DEGs), including 8 MAPKKK genes responsive to drought stress. Many of the DEGs were enriched in processes such as drought stress, abiotic stimulus, oxidation-reduction, and metabolic processes. The other way round, DEGs involved in processes such as oxidation, photosynthesis, and starch, proline, ethylene, and salicylic acid metabolism were clearly co-expressed with the MAPKKK genes. Furthermore, a quantitative real-time PCR (qRT-PCR) analysis was performed to assess the relative expression levels of MAPKKKs. Correlation analysis revealed that there was a significant correlation between expression levels of two MAPKKKs and relative biomass responsive to drought in 8 inbred lines. Our results indicate that MAPKKKs may have important regulatory functions in drought tolerance in maize. PMID:26599013

Quercitol and osmotic adaptation of field-grown Eucalyptus under seasonal drought stress.

PubMed

Arndt, Stefan K; Livesley, Stephen J; Merchant, Andrew; Bleby, Timothy M; Grierson, Pauline F

2008-07-01

This study investigated the role of quercitol in osmotic adjustment in field-grown Eucalyptus astringens Maiden subject to seasonal drought stress over the course of 1 year. The trees grew in a native woodland and a farm plantation in the semi-arid wheatbelt region of south Western Australia. Plantation trees allocated relatively more biomass to leaves than woodland trees, but they suffered greater drought stress over summer, as indicated by lower water potentials, CO(2)assimilation rates and stomatal conductances. In contrast, woodland trees had relatively fewer leaves and suffered less drought stress. Plantation trees under drought stress engaged in osmotic adjustment, but woodland trees did not. Quercitol made a significant contribution to osmotic adjustment in drought-stressed trees (25% of total solutes), and substantially more quercitol was measured in the leaves of plantation trees (5% dry matter) than in the leaves of woodland trees (2% dry matter). We found no evidence that quercitol was used as a carbon storage compound while starch reserves were depleted under drought stress. Differences in stomatal conductance, biomass allocation and quercitol production clearly indicate that E. astringens is both morphologically and physiologically 'plastic' in response to growth environment, and that osmotic adjustment is only one part of a complex strategy employed by this species to tolerate drought.

Spatiotemporal analysis of hydro-meteorological drought in the Johor River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Chua, Vivien P.; Li, Cheng; Brindha, K.

2018-02-01

Assessment of historical hydro-meteorological drought is important to develop a robust drought monitoring and prediction system. This study aims to assess the historical hydro-meteorological drought of the Johor River Basin (JRB) from 1975 to 2010, an important basin for the population of southern Peninsular Malaysia and Singapore. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were selected to represent the meteorological and hydrological droughts, respectively. Four absolute homogeneity tests were used to assess the rainfall data from 20 stations, and two stations were flagged by these tests. Results indicate the SPI duration to be comparatively low (3 months), and drier conditions occur over the upper JRB. The annual SSI had a strong decreasing trend at 95% significance level, showing that human activities such as reservoir construction and agriculture (oil palm) have a major influence on streamflow in the middle and lower basin. In addition, moderate response rate of SSI to SPI was found, indicating that hydrological drought could also have occurred in normal climate condition. Generally, the El Niño-Southern Oscillation and Madden Julian Oscillation have greater impacts on drought events in the basin. Findings of this study could be beneficial for future drought projection and water resources management.

Assessing Climate Risk on Agricultural Production: Insights Using Retrospective Analysis of Crop Insurance and Climatic Trends

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Elias, E.; Eischens, A.; Shilts, M.; Rango, A.; Steele, R.

2017-12-01

The collaborative synthesis of existing datasets, such as long-term climate observations and farmers' crop insurance payments, can increase their overall collective value and societal application. The U.S. Department of Agriculture (USDA) Climate Hubs were created to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this mission, Hubs work across USDA and other climate service agencies to synthesize existing information. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program which currently insures over $100 billion in crops annually. RMA hosts data describing the cause for loss (e.g. drought, wind, irrigation failure) and indemnity amount (i.e. total cost of loss) at multiple spatio-temporal scales (i.e. state, county, year, month). The objective of this paper is to link climate information with indemnities, and their associated cause of loss, to assess climate risk on agricultural production and provide regionally-relevant information to stakeholders to promote resilient working landscapes. We performed a retrospective trend analysis at the state-level for the American Southwest (SW). First, we assessed indemnity-only trends by cause of loss and crop type at varying temporal scales. Historical monthly weather data (i.e. precipitation and temperature) and long-term drought indices (e.g. Palmer Drought Severity Index) were then linked with indemnities and grouped by different causes of loss. Climatological ranks were used to integrate historical comparative intensity of acute and long-term climatic events. Heat and drought as causes of loss were most correlated with temperature and drought indicators, respectively. Across all SW states increasing indemnities were correlated with warmer conditions. Multiple statistical trend analyses suggest a framework is necessary to appropriately measure the biophysical signals in crop insurance trends taking into account spatio-temporal characteristics. Based on stakeholder feedback, we also developed a web-based information browser to visualize and assess indemnity trends providing useful and usable knowledge to support informed land management decisions and ecosystem resilience.

Sensitive indicators of Stipa bungeana response to precipitation under ambient and elevated CO2 concentration

NASA Astrophysics Data System (ADS)

Shi, Yaohui; Zhou, Guangsheng; Jiang, Yanling; Wang, Hui; Xu, Zhenzhu

2018-02-01

Precipitation is a primary environmental factor in the semiarid grasslands of northern China. With increased concentrations of atmospheric greenhouse gases, precipitation regimes will change, and high-impact weather events may be more common. Currently, many ecophysiological indicators are known to reflect drought conditions, but these indicators vary greatly among species, and few studies focus on the applicability of these drought indicators under high CO2 conditions. In this study, five precipitation levels (- 30%, - 15%, control, + 15%, and + 30%) were used to simulate the effects of precipitation change on 18 ecophysiological characteristics in Stipa bungeana, including leaf area, plant height, leaf nitrogen (N), and chlorophyll content, among others. Two levels of CO2 concentration (ambient, 390 ppm; 550 ppm) were used to simulate the effects of elevated CO2 on these drought indicators. Using gray relational analysis and phenotypic plasticity analysis, we found that total leaf area or leaf number (morphology), leaf water potential or leaf water content (physiology), and aboveground biomass better reflected the water status of S. bungeana under ambient and elevated CO2 than the 13 other analyzed variables. The sensitivity of drought indicators changed under the elevated CO2 condition. By quantifying the relationship between precipitation and the five most sensitive indicators, we found that the thresholds of precipitation decreased under elevated CO2 concentration. These results will be useful for objective monitoring and assessment of the occurrence and development of drought events in S. bungeana grasslands.

Future opportunities and challenges in remote sensing of drought

USGS Publications Warehouse

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

2012-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Future Opportunities and Challenges in Remote Sensing of Drought

NASA Technical Reports Server (NTRS)

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

2011-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

A Study on the Response of Non-photosynthetic Vegetation (NPV) towards the Anomalies of Climate in the Southwestern U.S.

NASA Astrophysics Data System (ADS)

Jia, S.; Okin, G. S.

2014-12-01

Non-photosynthetic vegetation (NPV), including the standing dead leaves and trunks of plants, is not only a crucial component of aboveground biomass in the dry ecosystems but also an effective indicator of drought, since the photosynthetic plants (PV) usually degrade to NPV after drought. With the multiple-endmember spectral mixture (MESMA) analysis, it is possible to extract the NPV coverage to a selected baseline date from MODIS MOD43 NBAR data. In this study, we used a baseline image derived based on JHU Spectral Library to obtain the NPV, PV and bare soil of southwest U.S. from 2000 to 2012. To investigate the response of NPV, we then calculated the lagged and non-lagged correlation between the anomalies of land cover and climate variables. The major land use categories are also employed to investigate the spatial pattern of the response. The more significant correlation between NPV or PV and precipitation than temperature indicates the importance of moisture in the study site. In addition, there is an asymmetric response between NPV to the drought and the increased precipitation. In drier inland, the most significant response of NPV after a deficit of precipitation occurs later than after an increase. The increase of temperature, especially under the deficits of moisture, facilitates the presence of NPV with lag, which is due to the response time of detectable withering of PV. The response of NPV also varies between the different land cover categories. In southwest U.S., the NPV from shrubs and grassland have more sensitive feedbacks on the dynamics of climate than wetter region. The nature of the ecosystems can partly explain the difference, but finer scale studies are necessary for further investigation of specific regions. Considering the increase of drought in southwest U.S., obtaining a better understanding on the response of vegetation is crucial to further evaluate its impacts on the dry ecosystems. This study provides a perspective by examining NPV, another direct indicator of drought. For further studies, temporal and spatial patterns of NPV response to the climate need more scrutiny, such as the spatial pattern of the lags, hotspots of change, and regional-specific feedbacks. Different indicators of extreme events, such as the U.S. Drought Monitor may also be employed to provide more direct evaluation.

Characterizing changes in drought risk for the United States from climate change

EPA Science Inventory

The effect of climate change on the frequency and intensity of droughts across the contiguous United States over the next century is assessed by applying Standardized Precipitation Indices and the Palmer Drought Severity Index to the full suite of 22 Intergovernmental Panel on Cl...

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies and its application to four recent severe regional drought events in China

NASA Astrophysics Data System (ADS)

Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.

2017-12-01

Reliable drought prediction is fundamental for seasonal water management. Considering that drought development is closely related to the spatio-temporal evolution of large-scale circulation patterns, we develop a conceptual prediction model of seasonal drought processes based on atmospheric/oceanic Standardized Anomalies (SA). It is essentially the synchronous stepwise regression relationship between 90-day-accumulated atmospheric/oceanic SA-based predictors and 3-month SPI updated daily (SPI3). It is forced with forecasted atmospheric and oceanic variables retrieved from seasonal climate forecast systems, and it can make seamless drought prediction for operational use after a year-to-year calibration. Simulation and prediction of four severe seasonal regional drought processes in China were forced with the NCEP/NCAR reanalysis datasets and the NCEP Climate Forecast System Version 2 (CFSv2) operationally forecasted datasets, respectively. With the help of real-time correction for operational application, model application during four recent severe regional drought events in China revealed that the model is good at development prediction but weak in severity prediction. In addition to weakness in prediction of drought peak, the prediction of drought relief is possible to be predicted as drought recession. This weak performance may be associated with precipitation-causing weather patterns during drought relief. Based on initial virtual analysis on predicted 90-day prospective SPI3 curves, it shows that the 2009/2010 drought in Southwest China and 2014 drought in North China can be predicted and simulated well even for the prospective 1-75 day. In comparison, the prospective 1-45 day may be a feasible and acceptable lead time for simulation and prediction of the 2011 droughts in Southwest China and East China, after which the simulated and predicted developments clearly change.

Stakeholder Theory and Rangeland Management: The Importance of Ranch Income Dependence

NASA Astrophysics Data System (ADS)

Elias, S.; Roche, L. M.; Elias, E.

2016-12-01

The California drought beginning in 2012 has been driven by reduced precipitation and record high temperatures. Hydrologic drought in the Southwest United States is projected to become the new climatology of the region. While ranchers are considered naturally adaptive, often adeptly altering management based upon conditions, the projected increased aridity may challenge rangeland management. Certain rancher characteristics are likely to impact how well ranchers adapt. Based on Stakeholder Theory (ST), we hypothesize that the extent to which ranchers are dependent on their ranches as a source of income would serve as a predictor of several key variables related to ranching adaptation and success. Data were obtained from 507 ranchers throughout the State of California via the Rangeland Decision-Making Survey implemented by University of California, Davis in 2010, just prior to the unprecedented California drought. Consistent with the ST urgency facet, results of linear regression analyses indicate the more dependent ranchers are on their ranches for their income, the more aware they are of USDA ranching initiatives (β = 0.19, p < .001) and state ranching initiatives (β = 0.10, p < .05). In addition, more dependent ranchers are more likely to use multiple and diverse sources of information about ranching (β = 0.18, p < .001), are more likely to realize the severity and extent of the most recent drought's impacts (β = 0.18, p < .001), and were more likely to have a drought management plan in place during the most recent drought (β = 0.18, p < .001). These findings are important in relation to both outreach/extension efforts and rangeland research. Outreach/extension efforts should take into account that people less dependent on their ranches are less aware of resources, as well as, less prepared to adapt to drought. Researchers should control for the extent to which ranchers are dependent on their ranches for income in order to ensure more accurate findings.

Public Participation, Education, and Engagement in Drought Planning

NASA Astrophysics Data System (ADS)

Bathke, D. J.; Wall, N.; Haigh, T.; Smith, K. H.; Bernadt, T.

2014-12-01

Drought is a complex problem that typically goes beyond the capacity, resources, and jurisdiction of any single person, program, organization, political boundary, or sector. Thus, by nature, monitoring, planning for, and reducing drought risk must be a collaborative process. The National Drought Mitigation Center, in partnership with the National Integrated Drought Information System (NIDIS) Program Office and others, provides active engagement and education drought professionals, stakeholders, and the general public about managing drought-related risks through resilience planning, monitoring, and education. Using case studies, we discuss recruitment processes, network building, participation techniques, and educational methods as they pertain to a variety of unique audiences with distinct objectives. Examples include collaborative decision-making at a World Meteorological Organization conference; planning, and peer-learning among drought professionals in a community of practice; drought condition monitoring through citizen science networks; research and education dissemination with stakeholder groups; and informal learning activities for all ages. Finally, we conclude with evaluation methods, indicators of success, and lessons learned for increasing the effectiveness of our programs in increasing drought resilience.

Global patterns of drought recovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.

Drought is a recurring multi-factor phenomenon with major impacts on natural and human systems1-3. Drought is especially important for land carbon sink variability, influencing climate regulation of the terrestrial biosphere4. While 20th Century trends in drought regime are ambiguous, “more extreme extremes” as well as more frequent and severe droughts3,7 are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the spatiotemporal patterning and controls of drought recovery are largely unknown. Here we use three distinct global datasets of grossmore » primary productivity to show that across diverse terrestrial ecosystems drought recovery times are driven by biological productivity and biodiversity, with drought length and severity of secondary importance. Recovery time, especially for extreme droughts, and the areal extent of ecosystems in recovery from drought generally increase over the 20th Century, supporting an increase globally in drought impact8. Our results indicate that if future Anthropocene droughts become more widespread as expected, that droughts will become more frequent relative to recovery time. This increases the risk of entering a new regime where vegetation never recovers to its original state and widespread degradation of the land carbon sink ensues.« less

Defining Drought Characteristics for Natural Resource Management

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Senay, G. B.; McNeeley, S.; Morisette, J. T.

2016-12-01

In the north central region of the US, on-going drought studies are investigating factors determining how drought impacts various ecosystem services and challenge natural resource management decisions. The effort reported here stems from research sponsored by the USGS North Central Climate Science Center, to deal with ecosystem response to drought with the goal to see if there are indicators of drought emerging from the ecosystem interactions with various weather patterns, soil moisture dynamics, and the structural aspects of the ecosystem in question. The North Central domain covers a region from the headwaters of the Missouri River Basin to the northern Great Plains. Using spatial and temporal analysis of remote sensing products and mechanistic daily time-step ecosystem model simulations across the northern Great Plains and northern Rockies, analysis of recent drought conditions over the region will be provided. Drought characteristics will be analyzed related to resource management targets, such as water supply, landscape productivity, or habitat needs for key species. Analysis of ecosystem and landscape patterns of drought relative to net primary productivity, surface temperatures, soil moisture content, evaporation, transpiration, and water use efficiency from 2000 through 2014 will be analyzed for different drought and non-drought events. Comparisons between satellite-derived ET and NPP of different Great Plains ecosystems related to simulated ET and NPP will be presented. These comparisons provide indications of the role that soil moisture dynamics, groundwater recharge and rooting depth of different ecosystems have on determining the sensitivity to water stress due to seasonal warming and reduced precipitation across the region. In addition, indications that average annual rainfall levels over certain ecosystems may result in reduced production due to higher rates of water demand under the observed warmer temperatures and the prolonged warming in the spring and fall affecting soil moisture conditions. These results are being used to inform managers in our region about recent climate trends regarding drought impacts and provide a basis for further co-design efforts of research to action strategies with resource managers and stakeholders in the region.

Major Mesoamerican droughts of the past millennium

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Diaz, J. Villanueva; Burnette, D. J.; Paredes, J. Cerano; Heim, R. R., Jr.; Fye, F. K.; Acuna Soto, R.; Therrell, M. D.; Cleaveland, M. K.; Stahle, D. K.

2011-03-01

Ancient Montezuma baldcypress (Taxodium mucronatum) trees found in Barranca de Amealco, Queretaro, have been used to develop a 1,238-year tree-ring chronology that is correlated with precipitation, temperature, drought indices, and crop yields in central Mexico. This chronology has been used to reconstruct the spring-early summer soil moisture balance over the heartland of the Mesoamerican cultural province, and is the first exactly dated, annually resolved paleoclimatic record for Mesoamerica spanning the Late Classic, Post Classic, Colonial, and modern eras. The reconstruction indicates that the Terminal Classic drought extended into central Mexico, supporting other sedimentary and speleothem evidence for this early 10th century drought in Mesoamerica. The reconstruction also documents severe and sustained drought during the decline of the Toltec state (1149-1167) and during the Spanish conquest of the Aztec state (1514-1539), providing a new precisely dated climate framework for Mesoamerican cultural change.

Climate and drought

NASA Astrophysics Data System (ADS)

McNab, Alan L.

Drought is a complex phenomenon that can be defined from several perspectives [Wilhite and Glantz, 1987]. The common characteristic and central idea of these perspectives is the straightforward notion of a water deficit. Complexity arises because of the need to specify the part of the hydrologic cycle experiencing the deficit and the associated time period. For example, a long-term deficit in deep groundwater storage can occur simultaneously with a short-term surplus of root zone soil water.Figure 1 [Changnon, 1987] illustrates how the definitions of drought are related to specific components of the hydrologic cycle. The dashed lines indicate the delayed translation of two hypothetical precipitation deficits with respect to runoff, soil moisture, streamflow and groundwater. From this perspective, precipitation can be considered as the carrier of the drought signal, and hydrological processes are among the final indicators that reveal the presence of drought [Hare, 1987; Klemes, 1987].

Response of water use efficiency to summer drought in a boreal Scots pine forest in Finland

NASA Astrophysics Data System (ADS)

Gao, Yao; Markkanen, Tiina; Aurela, Mika; Mammarella, Ivan; Thum, Tea; Tsuruta, Aki; Yang, Huiyi; Aalto, Tuula

2017-09-01

The influence of drought on plant functioning has received considerable attention in recent years, however our understanding of the response of carbon and water coupling to drought in terrestrial ecosystems still needs to be improved. A severe soil moisture drought occurred in southern Finland in the late summer of 2006. In this study, we investigated the response of water use efficiency to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using eddy covariance flux data from the Hyytiälä (southern Finland) flux site. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Based on observed data, the ecosystem level water use efficiency (EWUE; the ratio of gross primary production, GPP, to evapotranspiration, ET) showed a decrease during the severe soil moisture drought, while the inherent water use efficiency (IWUE; a quantity defined as EWUE multiplied with mean daytime vapour pressure deficit, VPD) increased and the underlying water use efficiency (uWUE, a metric based on IWUE and a simple stomatal model, is the ratio of GPP multiplied with a square root of VPD to ET) was unchanged during the drought. The decrease in EWUE was due to the stronger decline in GPP than in ET. The increase in IWUE was because of the decreased stomatal conductance under increased VPD. The unchanged uWUE indicates that the trade-off between carbon assimilation and transpiration of the boreal Scots pine forest was not disturbed by this drought event at the site. The JSBACH simulation showed declines of both GPP and ET under the severe soil moisture drought, but to a smaller extent compared to the observed GPP and ET. Simulated GPP and ET led to a smaller decrease in EWUE but a larger increase in IWUE because of the severe soil moisture drought in comparison to observations. As in the observations, the simulated uWUE showed no changes in the drought event. The model deficiencies exist mainly due to the lack of the limiting effect of increased VPD on stomatal conductance during the low soil moisture condition. Our study provides a deeper understanding of the coupling of carbon and water cycles in the boreal Scots pine forest ecosystem and suggests possible improvements to land surface models, which play an important role in the prediction of biosphere-atmosphere feedbacks in the climate system.

A introduction of a Scientific Research Program on Chinese Drought

NASA Astrophysics Data System (ADS)

Li, Y.

2014-12-01

Drought is one of the major meteorological disasters, with high frequencies, wide distributions and serious conditions. It is one of the biggest impacts on global agricultural productions, ecological environment and socioeconomic sustainable developments. China is particularly one of the countries in the world with serious drought disasters. The goal of this project is improving the capabilities in drought monitoring and forecasting based on an in-depth theories of drought. The project will be implemented in the typical extreme drought area based on comprehensive and systemic observation network and numerical experiments It will show a complete feedback mechanism among the atmospheric, water, biological and other spheres for forming drought. First, the atmospheric droughts that leads to agriculture and hydrologic drought and the possible causes for these disasters will be explored using our observation data sets. Second, the capability of monitoring, forecasting and early warning for drought will be developed with numerical model (regional climate model and land surface model, etc.). Last but not the least, evaluation approaches for the risk of drought and the strategy of predicting/prohibiting the drought at regional scale will be proposed. Meanwhile, service system and information sharing platform of drought monitoring and early warning will be established to improve the technical level of drought disaster preparedness and response in China.

High-resolution spatio-temporal analyses of drought episodes in the western Mediterranean basin (Spanish mainland, Iberian Peninsula)

NASA Astrophysics Data System (ADS)

González-Hidalgo, J. C.; Vicente-Serrano, S. M.; Peña-Angulo, D.; Salinas, C.; Tomas-Burguera, M.; Beguería, S.

2018-04-01

The purpose of this research was to identify major drought events on the Spanish mainland between 1961 and 2014 by means of two drought indices, and analyze the spatial propagation of drought conditions. The indices applied were the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). The first was calculated as standardized anomalies of precipitation at various temporal intervals, while the second examined the climatic balance normalized at monthly scale, incorporating the relationship between precipitation and the atmospheric water demand. The daily meteorological data from Spanish Meteorological Archives (AEMet) were used in performing the analyses. Within the framework of the DESEMON project, original data were converted into a high spatial resolution grid (1.1 km2) following exhaustive quality control. Values of both indices were calculated on a weekly scale and different timescales (12, 24 and 36 months). The results show that during the first half of the study period, the SPI usually returned a higher identification of drought areas, while the reverse was true from the 1990s, suggesting that the effect from atmospheric evaporative demand could have increased. The temporal propagation from 12- to 24-month and 36-month timescales analyzed in the paper seems to be a far from straightforward phenomenon that does not follow a simple rule of time lag, because events at different temporal scales can overlap in time and space. Spatially, the propagation of drought events affecting more than 25% of the total land indicates the existence of various spatial gradients of drought propagation, mostly east-west or west-east, but also north-south have been found. No generalized episodes were found with a radial pattern, i.e., from inland to the coast.

WRF added value to capture the spatio-temporal drought variability

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Ying; Fu, Rong; Dickinson, Robert

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Contrasting physiological responses of two co-occurring eucalypts to seasonal drought at restored bauxite mine sites.

PubMed

Szota, Christopher; Farrell, Claire; Koch, John M; Lambers, Hans; Veneklaas, Erik J

2011-10-01

This study describes the physiological response of two co-occurring tree species (Eucalyptus marginata and Corymbia calophylla) to seasonal drought at low- and high-quality restored bauxite mine sites in south-western Australia. Seasonal changes in photosynthesis (A), stomatal conductance (g(s)), leaf water potential (ψ), leaf osmotic potential (ψ), leaf relative water content (RWC) and pressure-volume analysis were captured over an 18-month field study to (i) determine the nature and severity of physiological stress in relation to site quality and (ii) identify any physiological differences between the two species. Root system restriction at the low-quality site reduced maximum rates of gas exchange (g(s) and A) and increased water stress (midday ψ and daily RWC) in both species during drought. Both species showed high stomatal sensitivity during drought; however, E. marginata demonstrated a higher dehydration tolerance where ψ and RWC fell to -3.2 MPa and 73% compared with -2.4 MPa and 80% for C. calophylla. Corymbia calophylla showed lower g(s) and higher ψ and RWC during drought, indicating higher drought tolerance. Pressure-volume curves showed that cell-wall elasticity of E. marginata leaves increased in response to drought, while C. calophylla leaves showed lower osmotic potential at zero turgor in summer than in winter, indicating osmotic adjustment. Both species are clearly able to tolerate seasonal drought at hostile sites; however, by C. calophylla closing stomata earlier in the drought cycle, maintaining a higher water status during drought and having the additional mechanism of osmotic adjustment, it may have a greater capacity to survive extended periods of drought.

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

DOE PAGES

Sun, Ying; Fu, Rong; Dickinson, Robert; ...

2015-11-02

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Drought Events and Their Impacts on Food Production in New Zealand: Historical Analysis and Outlook Model Development

NASA Astrophysics Data System (ADS)

Li, Y.; Yin, C.; Urich, P.; Hill, R.

2012-12-01

Given the importance of the primary production sector, climatic conditions have always been a significant driver of food production in New Zealand. The country has experienced a number of severe droughts throughout its history, where a number of extended periods of low rainfall have severely impacted primary production. The characteristics of historical drought and their impacts on the primary production sector are analysed, including the economic losses in the 1998-1999 and 2007-2009 events. We include the analysis of a set of national standardised drought monitoring indices: Standardised Precipitation Index (SPI), Standardised Precipitation Evapotranspiration Index (SPEI), Soil moisture Index (SMI), and Standardised Pasture Growth Index (SPGI). Since the drought events in New Zealand are clearly linked with ENSO, the SST anomalies in the key regions can be good predictors of drought events. Artificial Neural Network (ANN) information processing technics have been applied to build local drought outlook models, the predictors are the SST anomaly of eight key regions that impact New Zealand climate produced by the Climate Forecasting System v2(CFSv2) of NCEP, and the local NIWA derived observed precipitation and soil moisture data. SST is a variable that CFSv2 can forecast with high skill and after bias correction, can be applied as a climate predictor for New Zealand. Inclusion of local data and the persistent nature of drought leads to good predictors therefore one to three month ensemble drought outlooks can be produced for New Zealand. The potential changes of drought intensity and frequency over the medium to long term future are investigated using downscaled data from 12 GCMs and multiple scenarios. The results indicate that New Zealand may experience more severe drought in many areas, therefore adaptation should be planned and implemented.

Representation of physiological drought at ecosystem level based on model and eddy covariance measurements

NASA Astrophysics Data System (ADS)

Zhang, Y.; Novick, K. A.; Song, C.; Zhang, Q.; Hwang, T.

2017-12-01

Drought and heat waves are expected to increase both in frequency and amplitude, exhibiting a major disturbance to global carbon and water cycles under future climate change. However, how these climate anomalies translate into physiological drought, or ecosystem moisture stress are still not clear, especially under the co-limitations from soil moisture supply and atmospheric demand for water. In this study, we characterized the ecosystem-level moisture stress in a deciduous forest in the southeastern United States using the Coupled Carbon and Water (CCW) model and in-situ eddy covariance measurements. Physiologically, vapor pressure deficit (VPD) as an atmospheric water demand indicator largely controls the openness of leaf stomata, and regulates atmospheric carbon and water exchanges during periods of hydrological stress. Here, we tested three forms of VPD-related moisture scalars, i.e. exponent (K2), hyperbola (K3), and logarithm (K4) to quantify the sensitivity of light-use efficiency to VPD along different soil moisture conditions. The sensitivity indicators of K values were calibrated based on the framework of CCW using Monte Carlo simulations on the hourly scale, in which VPD and soil water content (SWC) are largely decoupled and the full carbon and water exchanging information are held. We found that three K values show similar performances in the predictions of ecosystem-level photosynthesis and transpiration after calibration. However, all K values show consistent gradient changes along SWC, indicating that this deciduous forest is less responsive to VPD as soil moisture decreases, a phenomena of isohydricity in which plants tend to close stomata to keep the leaf water potential constant and reduce the risk of hydraulic failure. Our study suggests that accounting for such isohydric information, or spectrum of moisture stress along different soil moisture conditions in models can significantly improve our ability to predict ecosystem responses to future drought.

Statistical trends of some meteorological drought indices in Europe

NASA Astrophysics Data System (ADS)

Diaz Loaiza, Andres; Roper, Aaron; Guimarães, Gabriela; Ward, Philip; Aerts, Jeroen

2017-04-01

Out of all the natural phenomena that afflict human society, droughts are one of the most damaging. Droughts have been estimated to cost an average of 6 to 8 billion dollars in damages per year, yet they are often overlooked in comparison to other natural disasters, because they are invisible to the naked eye, and quite difficult to measure. The presented research display a developed methodology to assess the behavior of different meteorological drought indices on a continental scale in Europe. Firstly, is assessed the behavior on varying temporal scales, and secondly, it is determine whether or not droughts have become more frequent and/or intense in recent decades. Results over the analyzed period (1950 to 2014), shows that the frequency of meteorological drought events are slightly increasing (in the SPEI index). Instead for the SPI index, this trend is not patent probably because of his own definition. About the intensity, in contrast, it seems the events are become more intense. A plausible conclusion is that the quantity of annually events of drought over Europe are conserved, but the same are becoming longer and intense. The findings of this research emphasize the impacts that climate change and increasing temperatures will have on drought impacts and the need for water management sectors to incorporate that knowledge into the consumption and protection of water resources. The advantage of using geospatial techniques into the drought monitoring, like the kriging interpolation used in the present model, allow us to comprehensively analyze drought events in different time and spatial scales.

Patterns of drought tolerance in major European temperate forest trees: climatic drivers and levels of variability.

PubMed

Zang, Christian; Hartl-Meier, Claudia; Dittmar, Christoph; Rothe, Andreas; Menzel, Annette

2014-12-01

The future performance of native tree species under climate change conditions is frequently discussed, since increasingly severe and more frequent drought events are expected to become a major risk for forest ecosystems. To improve our understanding of the drought tolerance of the three common European temperate forest tree species Norway spruce, silver fir and common beech, we tested the influence of climate and tree-specific traits on the inter and intrasite variability in drought responses of these species. Basal area increment data from a large tree-ring network in Southern Germany and Alpine Austria along a climatic cline from warm-dry to cool-wet conditions were used to calculate indices of tolerance to drought events and their variability at the level of individual trees and populations. General patterns of tolerance indicated a high vulnerability of Norway spruce in comparison to fir and beech and a strong influence of bioclimatic conditions on drought response for all species. On the level of individual trees, low-growth rates prior to drought events, high competitive status and low age favored resilience in growth response to drought. Consequently, drought events led to heterogeneous and variable response patterns in forests stands. These findings may support the idea of deliberately using spontaneous selection and adaption effects as a passive strategy of forest management under climate change conditions, especially a strong directional selection for more tolerant individuals when frequency and intensity of summer droughts will increase in the course of global climate change. © 2014 John Wiley & Sons Ltd.

Late Holocene Drought Variability in Eastern North America: Evidence From the Peatland Archive

NASA Astrophysics Data System (ADS)

Booth, R. K.; Jackson, S. T.

2006-12-01

Tree-ring based drought chronologies from semi-arid regions of western North America have revealed substantial variability in water balance during the past 1000 years, including episodes of persistent drought more severe than any observed during historical times. Delimitation of regional and continental-scale footprints of these past drought events, including their spatial patterning in humid regions where moisture-sensitive paleoclimate records are scarce, is critical to understanding their dynamics and potential causes. Ombrotrophic peatlands are scattered throughout humid regions of North America at mid-latitudes and represent an underutilized source of multidecadal-scale information on past moisture variations. We are developing a spatial network of peatland-derived paleoclimate and paleoecological records in eastern North America, in an effort to 1) determine whether large, decadal to multidecadal droughts of the past several thousand years were spatially and temporally coherent, 2) assess whether the magnitude of past drought events was sufficient to force ecological change in terrestrial ecosystems, and 3) assess the underlying mechanisms and dynamics of widespread drought in North America. We have completed water-level reconstructions based on testate-amoeba assemblages from two ombrotrophic peatlands in mid-continental North America, Hole in the Bog (NC Minnesota) and Minden Bog (SE Michgian). We also have developed reconstructions from three Sphagnum-dominated kettle peatlands, South Rhody Peatland (NC Michigan), Hornet Peatland (NW Wisconsin), and Irwin Smith Peatland (NE Michigan). Although these kettle peatlands are not truly ombrotrophic, high-magnitude water-table fluctuations should still be attributable to climate variability, and we use these records to supplement our interpretation of regional climate history. Our results indicate that all high-magnitude fluctuations in water balance were spatially extensive, affecting bog-surface moisture conditions throughout the western Great Lakes region. These include a large drought event during the late 16th century and a series of widespread drought events between 1900-1600 BP and 1100- 700 BP. The highest magnitude droughts of the last 2000 years occurred during an interval roughly consistent with the Medieval Warm Period (MWP), with individual drought events centered on 1000 BP, 800 BP, and 700 BP. These droughts were associated with major ecological changes, including abrupt changes in vegetation and fire regime. Tree-ring records from the western United States also document a series of extensive and high-magnitude drought events during this time period, suggesting these droughts affected a large portion of mid-latitude North America. Similarly widespread drought during the last 100 years has been linked to sea surface temperature (SST) anomalies in the adjacent ocean basins, particularly an anomalously warm North Atlantic and mid-latitude Pacific, and an anomalously cold Tropical Pacific. We hypothesize that the widespread droughts apparent in our bog records were related to amplification of a similar spatial mode of moisture variability. Comparison with available proxy SST records provides some support for this hypothesis, although a more extensive network of terrestrial hydroclimate records, derived using consistent methods and proxies, needs to be used in conjunction with the developing network of proxy SST records to fully test this hypothesis.

[Seed vigor evaluation based on adversity resistance index of wheat seed germination under stress conditions.

PubMed

Chen, Lei Tai; Sun, Ai Qing; Yang, Min; Chen, Lu Lu; Ma, Xue Li; Li, Mei Ling; Yin, Yan Ping

2016-09-01

A total of 16 wheat cultivars were selected to detect seed vigor of different genotypes using standard germination test, seed germination test under stress conditions and field emergence test. The adversity resistance indices of seed vigor indices and field emergence percentage under different germination conditions were used as the indices to evaluate adversity resistance. Principal component analysis and cluster analysis were used for the comprehensive evaluation of seed vigor. Results showed that drought stress, artificial aging and cold soaking treatments affected seed vigor to some extent. The adversity resistance indices of the artificial aging and cold soaking tests were significantly positively correlated with the field emergence percentage, while the adversity resistance index of drought stress test had no significant correlation with the field emergence percentage. 16 wheat cultivars were classified as three groups based on the principal component analysis and cluster analysis. Yunong 949, Yumai 49-198, Luyuan 502, Zhengyumai 9987, Shimai 21, Shannong 23, and Shixin 828 belonged to high vigor seeds. Xunong 5, Yunong 982, Tangmai 8, Jimai 20, Jimai 22, Jinan 17, and Shannong 20 belonged to medium vigor seeds. The other two cultivars, Chang 4738 and Lunxuan 061, belonged to low vigor seeds.

Possible impacts of early-11th-, middle-12th-, and late-13th-century droughts on western Native Americans and the Mississippian Cahokians

USGS Publications Warehouse

Benson, L.V.; Berry, M.S.; Jolie, E.A.; Spangler, J.D.; Stahle, D.W.; Hattori, E.M.

2007-01-01

One or more of three intense and persistent droughts impacted some Native American cultures in the early-11th, middle-12th and late-13th centuries, including the Anasazi, Fremont, Lovelock, and Mississippian (Cahokian) prehistorical cultures. Tree-ring-based reconstructions of precipitation and temperature indicate that warm drought periods occurred between AD 990 and 1060, AD 1135 and 1170, and AD 1276 and 1297. These droughts occurred during minima in the Pacific Decadal Oscillation and may have been associated with positive values of the Atlantic Multidecadal Oscillation. Each of the Native American cultures was supported, to a greater or lesser degree, by precipitation-dependent resources. Both the Four Corners region and Cahokia were sites of intense growth between about AD 1050 and 1130, and by AD 1150, cultures in both regions were undergoing stress. By AD 1300 the Anasazi and Fremont cultures had collapsed and their residual populations had either left their homelands or withered. In the case of Fremont populations, the AD 990-1060 drought may have had the greatest impact. This drought also may have affected the Anasazi, for it was at the end of this drought that some people from Chaco migrated to the San Juan River valley and founded the Salmon Ruin great house. Detailed data do not exist on the number of Lovelock habitation sites or populations over time; however, Lovelock populations appear to have retreated from the western Great Basin to California by AD 1300 or shortly thereafter.

Favorable Alleles for Stem Water-Soluble Carbohydrates Identified by Association Analysis Contribute to Grain Weight under Drought Stress Conditions in Wheat

PubMed Central

Li, Runzhi; Chang, Xiaoping; Jing, Ruilian

2015-01-01

Drought is a major environmental constraint to crop distribution and productivity. Stem water-soluble carbohydrates (WSC) buffer wheat grain yield against conditions unfavorable for photosynthesis during the grain filling stage. In this study, 262 winter wheat accessions and 209 genome-wide SSR markers were collected and used to undertake association analysis based on a mixed linear model (MLM). The WSC in different internodes at three growth stages and 1000-grain weight (TGW) were investigated under four environmental regimes (well-watered, drought stress during the whole growth period, and two levels of terminal drought stress imposed by chemical desiccation under the well-watered and drought stress during the whole growth period conditions). Under diverse drought stress conditions, WSC in lower internodes showed significant positive correlations with TGW, especially at the flowering stage under well-watered conditions and at grain filling under drought stress. Sixteen novel WSC-favorable alleles were identified, and five of them contributed to significantly higher TGW. In addition, pyramiding WSC favorable alleles was not only effective for obtaining accessions with higher WSC, but also for enhancing TGW under different water regimes. During the past fifty years of wheat breeding, WSC was selected incidentally. The average number of favorable WSC alleles increased from 1.13 in the pre-1960 period to 4.41 in the post-2000 period. The results indicate a high potential for using marker-assisted selection to pyramid WSC favorable alleles in improving WSC and TGW in wheat. PMID:25768726

The drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment

NASA Astrophysics Data System (ADS)

Wang, Zhiqiang; Jiang, Jingyi; Ma, Qing

2016-12-01

Climate change is affecting every aspect of human activities, especially the agriculture. In China, extreme drought events caused by climate change have posed a great threat to food safety. In this work we aimed to study the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment. The physical vulnerability curve was constructed from the relationship between drought hazard intensity index and yield loss rate. The risk assessment of agricultural drought was conducted from the drought hazard intensity index and physical vulnerability curve. The probability distribution of drought hazard intensity index decreased from south-west to north-east and increased from south-east to north-west along the rainfall isoline. The physical vulnerability curve had a reduction effect in three parts of the farming-pastoral ecotone in Northern China, which helped to reduce drought hazard vulnerability on spring maize. The risk of yield loss ratio calculated based on physical vulnerability curve was lower compared with the drought hazard intensity index, which suggested that the capacity of spring maize to resist and adapt to drought is increasing. In conclusion, the farming-pastoral ecotone in Northern China is greatly sensitive to climate change and has a high probability of severe drought hazard. Risk assessment of physical vulnerability can help better understand the physical vulnerability to agricultural drought and can also promote measurements to adapt to climate change.

An extended multivariate framework for drought monitoring in Mexico

NASA Astrophysics Data System (ADS)

Real-Rangel, Roberto; Pedrozo-Acuña, Adrián; Breña-Naranjo, Agustín; Alcocer-Yamanaka, Víctor

2017-04-01

Around the world, monitoring natural hazards, such as droughts, represents a critical task in risk assessment and management plans. A reliable drought monitoring system allows to identify regions affected by these phenomena so that early response measures can be implemented. In Mexico, this activity is performed using Mexico's Drought Monitor, which is based on a similar methodology as the United States Drought Monitor and the North American Drought Monitor. The main feature of these monitoring systems is the combination of ground-based and remote sensing observations that is ultimately validated by local experts. However, in Mexico in situ records of variables such as precipitation and streamflow are often scarce, or even null, in many regions of the country. Another issue that adds uncertainty in drought monitoring is the arbitrary weight given to each analyzed variable. This study aims at providing an operational framework for drought monitoring in Mexico, based on univariate and multivariate nonparametric standardized indexes proposed in recent studies. Furthermore, the framework has been extended by taking into account the Enhanced Vegetation Index (EVI) for the drought severity assessment. The analyzed variables used for computing the drought indexes are mainly derived from remote sensing (MODIS) and land surface models datasets (NASA MERRA-2). A qualitative evaluation of the results shows that the indexes used are capable of adequately describes the intensity and spatial distribution of past drought documented events.

Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

NASA Astrophysics Data System (ADS)

Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

2016-08-01

This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS in the climatic region of Birjand.