Sample records for drought monitor decision

  1. Building Gateway Tools for Informed Decision Making: The Drought Risk Atlas and U.S. Drought Monitor

    NASA Astrophysics Data System (ADS)

    Svoboda, M.; Fuchs, B.; Poulsen, C.; Nothwehr, J.; Owen, S.

    2014-12-01

    The National Drought Mitigation Center (NDMC) (http://drought.unl.edu) has been working with the National Integrated Drought Information System (NIDIS) (http://drought.gov;) and other partners with a goal of developing tools to enhance drought risk management activities in the U.S. and around the world. The NDMC is a national center founded in 1995 and located at the University of Nebraska-Lincoln. The NDMC conducts basic and applied research, provides a variety of services and produces decision support applications. In addition, the NDMC is involved heavily in education, outreach and planning activities and maintains a number of operational drought-related tools and products including the U.S. Drought Monitor (USDM), Drought Impact Reporter (DIR), Vegetation Drought Response Index (VegDRI) and the Drought Risk Atlas (DRA). The NDMC's recently launched Drought Risk Atlas (DRA) (http://droughtatlas.unl.edu) and the continually evolving U.S. Drought Monitor (http://droughtmonitor.unl.edu;) will be the focus of this presentation. The DRA was launched in 2014 in order to help better answer the common questions of "How does this drought compare to the Dust Bowl years or some other regional drought of record?", or "How often do we see a drought as severe as this?", and "Are we seeing trends in drought frequency?". Access to new digital data sources, geospatial tools and analyses, and dissemination through a web-based interface has allowed us to triple the original National Drought Atlas station sample size and roughly double the period of record in standing up the new DRA. Building off of feedback from the user community, the SPI, SPEI, PDSI, self-calibrated PDSI, Deciles and other climatology (to also include hydrology) products are included. It is anticipated that this tool will heighten awareness and enhance decision support activities with regards to drought risk for policy makers, resource managers, producers, planners, media and the public. Examples of the DRA

  2. 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.

  3. Drought: A comprehensive R package for drought monitoring, prediction and analysis

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Cheng, Hongguang

    2015-04-01

    Drought may impose serious challenges to human societies and ecosystems. Due to complicated causing effects and wide impacts, a universally accepted definition of drought does not exist. The drought indicator is commonly used to characterize drought properties such as duration or severity. Various drought indicators have been developed in the past few decades for the monitoring of a certain aspect of drought condition along with the development of multivariate drought indices for drought characterizations from multiple sources or hydro-climatic variables. Reliable drought prediction with suitable drought indicators is critical to the drought preparedness plan to reduce potential drought impacts. In addition, drought analysis to quantify the risk of drought properties would provide useful information for operation drought managements. The drought monitoring, prediction and risk analysis are important components in drought modeling and assessments. In this study, a comprehensive R package "drought" is developed to aid the drought monitoring, prediction and risk analysis (available from R-Forge and CRAN soon). The computation of a suite of univariate and multivariate drought indices that integrate drought information from various sources such as precipitation, temperature, soil moisture, and runoff is available in the drought monitoring component in the package. The drought prediction/forecasting component consists of statistical drought predictions to enhance the drought early warning for decision makings. Analysis of drought properties such as duration and severity is also provided in this package for drought risk assessments. Based on this package, a drought monitoring and prediction/forecasting system is under development as a decision supporting tool. The package will be provided freely to the public to aid the drought modeling and assessment for researchers and practitioners.

  4. 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.

  5. Drought Monitoring with VegDRI

    USGS Publications Warehouse

    Brown, Jesslyn F.

    2010-01-01

    Drought strikes somewhere in the United States every year, turning green landscapes brown as precipitation falls below normal levels and water supplies dwindle. Drought is typically a temporary climatic aberration, but it is also an insidious natural hazard. It might last for weeks, months, or years and may have many negative effects. Drought can threaten crops, livestock, and livelihoods, stress wildlife and habitats, and increase wildfire risks and threats to human health. Drought conditions can vary tremendously from place to place and week to week. Accurate drought monitoring is essential to understand a drought's progression and potential effects, and to provide information necessary to support drought mitigation decisions. It is also crucial in light of climate change where droughts could become more frequent, severe, and persistent.

  6. Agricultural Productivity Forecasts for Improved Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Limaye, Ashutosh; McNider, Richard; Moss, Donald; Alhamdan, Mohammad

    2010-01-01

    Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop

  7. 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

    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.

  8. 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.

  9. Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

    NASA Technical Reports Server (NTRS)

    Ly, Vickie; Gao, Michael; Cary, Cheryl; Turnbull-Appell, Sophie; Surunis, Anton

    2016-01-01

    The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

  10. Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Advanced Microwave Scanning Radiometer Data Products for National Drought Monitor Decision Support

    NASA Technical Reports Server (NTRS)

    Estep, Leland

    2007-01-01

    Drought effects are either direct or indirect depending on location, population, and regional economic vitality. Common direct effects of drought are reduced crop, rangeland, and forest productivity; increased fire hazard; reduced water levels; increased livestock and wildlife mortality rates; and damage to wildlife and fish habitat. Indirect impacts follow on the heels of direct impacts. For example, a reduction in crop, rangeland, and forest productivity may result in reduced income for farmers and agribusiness, increased prices for food and timber, unemployment, reduced tax revenues, increased crime, foreclosures on bank loans to farmers and businesses, migration, and disaster relief programs. In the United States alone, drought is estimated to result in annual losses of between $6 - 8 billion. Recent sustained drought in the United States has made decision-makers aware of the impacts of climate change on society and environment. The eight major droughts that occurred in the United States between 1980 and 1999 accounted for the largest percentage of weather-related monetary losses. Monitoring drought and its impact that occurs at a variety of scales is an important government activity -- not only nationally but internationally as well. The NDMC (National Drought Mitigation Center) and the USDA (U.S. Department of Agriculture) RMA (Risk Management Agency) have partnered together to develop a DM-DSS (Drought Monitoring Decision Support System). This monitoring system will be an interactive portal that will provide users the ability to visualize and assess drought at all levels. This candidate solution incorporates atmospherically corrected VIIRS data products, such as NDVI (Normalized Difference Vegetation Index) and Ocean SST (sea surface temperature), and AMSR-E soil moisture data products into two NDMC vegetation indices -- VegDRI (Vegetation Drought Response Index) and VegOUT (Vegetation Outlook) -- which are then input into the DM-DSS.

  11. Agricultural drought risk monitoring and yield loss forecast with remote sensing data

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

    The World Meteorological Organization (WMO) and Global Water Partnership (GWP) have launched a joint Integrated Drought Management Programme (IDMP) to improve monitoring and prevention of droughts. In the frame of this project this study focuses on identification of agricultural drought characteristics and elaborates a monitoring method (with application of remote sensing data), which could result in appropriate early warning of droughts before irreversible yield loss and/or quality degradation occur. The spatial decision supporting system to be developed will help the farmers in reducing drought risk of the different regions by plant specific calibrated drought indexes. The study area was the Tisza River Basin, which is located in Central Europe within the Carpathian Basin. For the investigations normalized difference vegetation index (NDVI) was used calculated from 16 day moving average chlorophyll intensity and biomass quantity data. The results offer concrete identification of remote sensing and GIS data tools for agricultural drought monitoring and forecast, which eventually provides information on physical implementation of drought risk levels. In the first step, we statistically normalized the crop yield maps and the MODIS satellite data. Then the drought-induced crop yield loss values were classified. The crop yield loss data were validated against the regional meteorological drought index values (SPI), the water management and soil physical data. The objective of this method was to determine the congruency of data derived from spectral data and from field measurements. As a result, five drought risk levels were developed to identify the effect of drought on yields: Watch, Early Warning, Warning, Alert and Catastrophe. In the frame of this innovation such a data link and integration, missing from decision process of IDMP, are established, which can facilitate the rapid spatial and temporal monitoring of meteorological, agricultural drought phenomena and its

  12. The Global Drought Information System - A Decision Support Tool with Global Applications

    NASA Astrophysics Data System (ADS)

    Heim, R. R.; Brewer, M.

    2012-12-01

    Drought is a natural hazard which can cause famine in developing countries and severe economic hardship in developed countries. Given current concerns with the increasing frequency and magnitude of droughts in many regions of the world, especially in the light of expected climate change, drought monitoring and dissemination of early warning information in a timely fashion on a global scale is a critical concern as an important adaptation and mitigation strategy. While a number of nations, and a few continental-scale activities have developed drought information system activities, a global drought early warning system (GDEWS) remains elusive, despite the benefits highlighted by ministers to the Global Earth Observation System of System in 2008. In an effort to begin a process of drought monitoring with international collaboration, the National Integrated Drought Information System's (NIDIS) U.S. Drought Portal, a web-based information system created to address drought services and early warning in the United States, including drought monitoring, forecasting, impacts, mitigation, research, and education, volunteered to develop a prototype Global Drought Monitoring Portal (GDMP). Through integration of data and information at the global level, and with four continental-level partners, the GDMP has proven successful as a tool to monitor drought around the globe. At a recent meeting between NIDIS, the World Meteorological Organization, and the Global Earth Observation System of Systems, it was recommended that the GDMP form the basis for a Global Drought Information System (GDIS). Currently, GDIS activities are focused around incorporating additional drought monitoring information, especially from those areas without regional or continental-scale input, and incorporating drought-specific climate forecast information from the World Climate Research Programme. Additional GDIS pilot activities are underway with an emphasis on information and decision making, and how to

  13. 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

  14. The Global Drought Information System - A Decision Support Tool with Global Applications

    NASA Astrophysics Data System (ADS)

    Arndt, D. S.; Brewer, M.; Heim, R. R., Jr.

    2014-12-01

    underway with an emphasis on information and decision making, and how to effectively provide drought early warning. This talk will provide an update on the status of GDIS and its role in international drought monitoring.

  15. DroughtView: Satellite Based Drought Monitoring and Assessment

    NASA Astrophysics Data System (ADS)

    Hartfield, K. A.; Van Leeuwen, W. J. D.; Crimmins, M.; Marsh, S. E.; Torrey, Y.; Rahr, M.; Orr, B. J.

    2014-12-01

    Drought is an ever growing concern within the United States and Mexico. Extended periods of below-average precipitation can adversely affect agricultural production and ecosystems, impact local water resources and create conditions prime for wildfire. DroughtView (www.droughtview.arizona.edu) is a new on-line resource for scientists, natural resource managers, and the public that brings a new perspective to remote-sensing based drought impact assessment that is not currently available. DroughtView allows users to monitor the impact of drought on vegetation cover for the entire continental United States and the northern regions of Mexico. As a spatially and temporally dynamic geospatial decision support tool, DroughtView is an excellent educational introduction to the relationship between remotely sensed vegetation condition and drought. The system serves up Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data generated from 250 meter 16-day composite Moderate-resolution Imaging Spectroradiometer (MODIS) imagery from 2000 to the present. Calculation of difference from average, previous period and previous year greenness products provide the user with a proxy for drought conditions and insight on the secondary impacts of drought, such as wildfire. The various image products and overlays are served up via the ArcGIS Server platform. DroughtView serves as a useful tool to introduce and teach vegetation time series analysis to those unfamiliar with the science. High spatial resolution imagery is available as a reference layer to locate points of interest, zoom in and export images for implementation in reports and presentations. Animation of vegetation time series allows users to examine ecosystem disturbances and climate data is also available to examine the relationship between precipitation, temperature and vegetation. The tool is mobile friendly allowing users to access the system while in the field. The systems capabilities and

  16. Monitoring and seasonal forecasting of meteorological droughts

    NASA Astrophysics Data System (ADS)

    Dutra, Emanuel; Pozzi, Will; Wetterhall, Fredrik; Di Giuseppe, Francesca; Magnusson, Linus; Naumann, Gustavo; Barbosa, Paulo; Vogt, Jurgen; Pappenberger, Florian

    2015-04-01

    Near-real time drought monitoring can provide decision makers valuable information for use in several areas, such as water resources management, or international aid. Unfortunately, a major constraint in current drought outlooks is the lack of reliable monitoring capability for observed precipitation globally in near-real time. Furthermore, drought monitoring systems requires a long record of past observations to provide mean climatological conditions. We address these constraints by developing a novel drought monitoring approach in which monthly mean precipitation is derived from short-range using ECMWF probabilistic forecasts and then merged with the long term precipitation climatology of the Global Precipitation Climatology Centre (GPCC) dataset. Merging the two makes available a real-time global precipitation product out of which the Standardized Precipitation Index (SPI) can be estimated and used for global or regional drought monitoring work. This approach provides stability in that by-passes problems of latency (lags) in having local rain-gauge measurements available in real time or lags in satellite precipitation products. Seasonal drought forecasts can also be prepared using the common methodology and based upon two data sources used to provide initial conditions (GPCC and the ECMWF ERA-Interim reanalysis (ERAI) combined with either the current ECMWF seasonal forecast or a climatology based upon ensemble forecasts. Verification of the forecasts as a function of lead time revealed a reduced impact on skill for: (i) long lead times using different initial conditions, and (ii) short lead times using different precipitation forecasts. The memory effect of initial conditions was found to be 1 month lead time for the SPI-3, 3 to 4 months for the SPI-6 and 5 months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value, a skill similar to or better than climatological forecasts. In some cases, particularly for long SPI time

  17. 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.

  18. 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 Veg

  19. The Drought Monitor.

    NASA Astrophysics Data System (ADS)

    Svoboda, Mark; Lecomte, Doug; Hayes, Mike; Heim, Richard; Gleason, Karin; Angel, Jim; Rippey, Brad; Tinker, Rich; Palecki, Mike; Stooksbury, David; Miskus, David; Stephens, Scott

    2002-08-01

    information about drought and to receive regional and local input that is in turn incorporated into the product. This paper describes the Drought Monitor and the interactive process through which it is created.

  20. Utilizing multisource remotely sensed data to dynamically monitor drought in China

    NASA Astrophysics Data System (ADS)

    Liu, Sanchao; Li, Wenbo

    2011-12-01

    Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

  1. Monitoring of Drought Events in Gorontalo Regency

    NASA Astrophysics Data System (ADS)

    Koem, S.; Rusiyah

    2017-12-01

    Gorontalo Regency is a region vulnerable to drought. Drought is one of meteorological disaster because it tends to bring negative impact on various sectors. This study used rainfall data from 1981 to 2016 (35 years). The research employed Standardized Precipitation Index (SPI) to monitor and calculate the level of drought from the duration, intensity, and frequency in different time scales. The SPI value was calculated using the DrinC and ArcGIS software is used to create drought spatial distribution maps. The mean intensity of drought simultaneously followed the drought magnitude in Bilato station. The peak of drought in SPI-3 occurs in 1982, 2009 and 2016. In 1982, about 76.5% of the stations showed that the peak of drought events for SPI-3 in October to December. Moreover, 94% of the stations reveals that the peak of drought events for SPI-6 occur in July to December 1982. This shows that drought in 1982 was more severe than other years in the last three decades. Linear trends of drought for the period of 1981 to 2016 in most stations show an increasing trend, hence, it can be concluded that Gorontalo Regency experienced an increase in the wet period. Changes in time-scale caused the tendency for a high number of dry period frequencies. Drought spatial distribution could be used to determine the priority plans in finding the solutions due to droughts that occur in drought-vulnerable areas. Drought analysis using SPI could contribute to the decision-making in the future as an effort to minimize the impact of drought.

  2. Integrated Drought Monitoring and Forecasts for Decision Making in Water and Agricultural Sectors over the Southeastern US under Changing Climate

    NASA Astrophysics Data System (ADS)

    Arumugam, S.; Mazrooei, A.; Ward, R.

    2017-12-01

    Changing climate arising from structured oscillations such as ENSO and rising temperature poses challenging issues in meeting the increasing water demand (due to population growth) for public supply and agriculture over the Southeast US. This together with infrastructural (e.g., most reservoirs being within-year systems) and operational (e.g., static rule curves) constraints requires an integrated approach that seamlessly monitors and forecasts water and soil moisture conditions to support adaptive decision making in water and agricultural sectors. In this talk, we discuss the utility of an integrated drought management portal that both monitors and forecasts streamflow and soil moisture over the southeast US. The forecasts are continuously developed and updated by forcing monthly-to-seasonal climate forecasts with a land surface model for various target basins. The portal also houses a reservoir allocation model that allows water managers to explore different release policies in meeting the system constraints and target storages conditioned on the forecasts. The talk will also demonstrate how past events (e.g., 2007-2008 drought) could be proactively monitored and managed to improve decision making in water and agricultural sectors over the Southeast US. Challenges in utilizing the portal information from institutional and operational perspectives will also be presented.

  3. 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.

  4. Localizing drought monitoring products to support agricultural climate service advisories in South Asia

    NASA Astrophysics Data System (ADS)

    Qamer, F. M.; Matin, M. A.; Yadav, N. K.; Bajracharya, B.; Zaitchik, B. F.; Ellenburg, W. L.; Krupnik, T. J.; Hussain, G.

    2017-12-01

    The Fifth Assessment Report of the Intergovernmental Panel on Climate Change identifies drought as one of the major climate risks in South Asia. During past two decades, a large amount of climate data have been made available by the scientific community, but the deployment of climate information for local level and agricultural decision making remains less than optimal. The provisioning of locally calibrated, easily accessible, decision-relevant and user-oriented information, in the form of drought advisory service could help to prepare communities to reduce climate vulnerability and increase resilience. A collaborative effort is now underway to strengthen existing and/or establish new drought monitoring and early warning systems in Afghanistan, Bangladesh, Nepal and Pakistan by incorporating standard ground-based observations, earth observation datasets, and numerical forecast models. ICT-based agriculture drought monitoring platforms, hosted at national agricultural and meteorological institutions, are being developed and coupled with communications and information deployment strategies to enable the rapid and efficient deployment of information that farmers can understand, interpret, and act on to adapt to anticipated droughts. Particular emphasis is being placed on the calibration and validation of data products through retrospective analysis of time series data, in addition to the installation of automatic weather station networks. In order to contextualize monitoring products to that they may be relevant for farmers' primary cropping systems, district level farming practices calendars are being compiled and validated through focus groups and surveys to identify the most important times and situations during which farmers can adapt to drought. High-resolution satellite crop distribution maps are under development and validation to add value to these efforts. This programme also aims to enhance capacity of agricultural extension staff to better understand

  5. The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

    2013-12-01

    Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. 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. 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 based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. 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 results indicate

  6. Advancing Drought Understanding, Monitoring and Prediction

    NASA Technical Reports Server (NTRS)

    Mariotti, Annarita; Schubert, Siegfried D.; Mo, Kingtse; Peters-Lidard, Christa; Wood, Andy; Pulwarty, Roger; Huang, Jin; Barrie, Dan

    2013-01-01

    Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem

  7. 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.

  8. The German drought monitor

    NASA Astrophysics Data System (ADS)

    Zink, Matthias; Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Mai, Juliane; Schäfer, David; Marx, Andreas

    2016-07-01

    The 2003 drought event in Europe had major implications on many societal sectors, including energy production, health, forestry and agriculture. The reduced availability of water accompanied by high temperatures led to substantial economic losses on the order of 1.5 Billion Euros, in agriculture alone. Furthermore, soil droughts have considerable impacts on ecosystems, forest fires and water management. Monitoring soil water availability in near real-time and at high-resolution, i.e., 4 × 4 km2, enables water managers to mitigate the impact of these extreme events. The German drought monitor was established in 2014 as an online platform. It uses an operational modeling system that consists of four steps: (1) a daily update of observed meteorological data by the German Weather Service, with consistency checks and interpolation; (2) an estimation of current soil moisture using the mesoscale hydrological model; (3) calculation of a quantile-based soil moisture index (SMI) based on a 60 year data record; and (4) classification of the SMI into five drought classes ranging from abnormally dry to exceptional drought. Finally, an easy to understand map is produced and published on a daily basis on www.ufz.de/droughtmonitor. Analysis of the ongoing 2015 drought event, which garnered broad media attention, shows that 75% of the German territory underwent drought conditions in July 2015. Regions such as Northern Bavaria and Eastern Saxony, however, have been particularly prone to drought conditions since autumn 2014. Comparisons with historical droughts show that the 2015 event is amongst the ten most severe drought events observed in Germany since 1954 in terms of its spatial extent, magnitude and duration.

  9. High-resolution near real-time drought monitoring in South Asia

    NASA Astrophysics Data System (ADS)

    Aadhar, Saran; Mishra, Vimal

    2017-10-01

    Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

  10. High-Resolution Near Real-Time Drought Monitoring in South Asia

    NASA Astrophysics Data System (ADS)

    Aadhar, S.; Mishra, V.

    2017-12-01

    Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

  11. 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.

  12. Application of a hybrid association rules/decision tree model for drought monitoring

    NASA Astrophysics Data System (ADS)

    Nourani, Vahid; Molajou, Amir

    2017-12-01

    The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.

  13. Global integrated drought monitoring and prediction system

    PubMed Central

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe. PMID:25977759

  14. Global integrated drought monitoring and prediction system.

    PubMed

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe.

  15. 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

  16. 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.

  17. The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

    NASA Technical Reports Server (NTRS)

    White, Kristopher D.; Case, Jonathan L.

    2013-01-01

    Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring

  18. Remote sensing techniques for monitoring drought hazards: an intercomparison (Invited)

    NASA Astrophysics Data System (ADS)

    Brown, J. F.; Anderson, M. C.; Wardlow, B. D.; Svoboda, M. D.

    2009-12-01

    Drought events are frequently described using many different terms; for example, recurring climate phenomena, creeping natural hazards, agricultural disasters, and moisture deficiencies. In addition, droughts operate at many different spatial and temporal scales and affect different societal sectors, making them quite challenging to monitor, map, and assess impacts. Because of these factors, determining drought severity often requires using a convergence of evidence assisted by an analysis of multiple drought indicators. Frequent optical and thermal observations collected by daily polar-orbiting and geostationary satellites allow for regular monitoring of the land surface. In recent decades, with the launching of more advanced sensors and the maturation of remote sensing techniques, a variety of tools have been designed for improved understanding and tracking of drought events as they are occurring. These applications are intended to provide key decision makers with timely geospatial drought information to support various drought planning and mitigation activities. Two such tools highlighted in this study, are the Vegetation Drought Response Index (VegDRI) and the Evaporative Stress Index (ESI). While both indices incorporate satellite-based inputs, they are involved in different modeling approaches and observations from different parts of the electromagnetic spectrum. The VegDRI is a hybrid remote sensing and climate based indicator of drought-induced vegetation stress that combines satellite-based vegetation index observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors with climate-based drought index data and other biophysical parameters (such as land use/land cover type and soil characteristics). VegDRI provides near real-time vegetation drought severity information at relatively higher spatial resolution (1-km2) than traditional climatic drought indices such as the Standardized

  19. 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.

  20. 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

  1. 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.

  2. The Drought Task Force and Research on Understanding, Predicting, and Monitoring Drought

    NASA Astrophysics Data System (ADS)

    Barrie, D.; Mariotti, A.; Archambault, H. M.; Hoerling, M. P.; Wood, E. F.; Koster, R. D.; Svoboda, M.

    2016-12-01

    Drought has caused serious social and economic impacts throughout the history of the United States. All Americans are susceptible to the direct and indirect threats drought poses to the Nation. Drought challenges agricultural productivity and reduces the quantity and quality of drinking water supplies upon which communities and industries depend. Drought jeopardizes the integrity of critical infrastructure, causes extensive economic and health impacts, harms ecosystems, and increases energy costs. Ensuring the availability of clean, sufficient, and reliable water resources is a top national and NOAA priority. The Climate Program Office's Modeling, Analysis, Predictions, and Projections (MAPP) program, in partnership with the NOAA-led National Integrated Drought Information System (NIDIS), is focused on improving our understanding of drought causes, evolution, amelioration, and impacts as well as improving our capability to monitor and predict drought. These capabilities and knowledge are critical to providing communities with actionable, reliable information to increase drought preparedness and resilience. This poster will present information on the MAPP-organized Drought Task Force, a consortium of investigators funded by the MAPP program in partnership with NIDIS to advance drought understanding, monitoring, and prediction. Information on Task Force activities, products, and MAPP drought initiatives will be described in the poster, including the Task Force's ongoing focus on the California drought, its predictability, and its causes.

  3. Advancements in satellite remote sensing for drought monitoring

    USDA-ARS?s Scientific Manuscript database

    Drought monitoring is a key component for effective drought preparedness strategies, providing critical information on current conditions that can be used to trigger mitigation actions to lessen the impact of this natural hazard. However, drought can be both complex and challenging to monitor becau...

  4. Drought monitoring: Historical and current perspectives

    USDA-ARS?s Scientific Manuscript database

    Given the complex dimensions of drought and the challenges they pose for routine drought monitoring, it is essential that we continue to find innovative and robust ways to quantify and more effectively communicate the impacts of this hazard as part of an operational Drought Early Warning System. Th...

  5. 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

  6. Development of an operational African Drought Monitor prototype

    NASA Astrophysics Data System (ADS)

    Chaney, N.; Sheffield, J.; Wood, E. F.; Lettenmaier, D. P.

    2011-12-01

    Droughts have severe economic, environmental, and social impacts. However, timely detection and monitoring can minimize these effects. Based on previous drought monitoring over the continental US, a drought monitor has been developed for Africa. Monitoring drought in data sparse regions such as Africa is difficult due to a lack of historical or real-time observational data at a high spatial and temporal resolution. As a result, a land surface model is used to estimate hydrologic variables, which are used as surrogate observations for monitoring drought. The drought monitoring system consists of two stages: the first is to create long-term historical background simulations against which current conditions can be compared. The second is the real-time estimation of current hydrological conditions that results in an estimated drought index value. For the first step, a hybrid meteorological forcing dataset was created that assimilates reanalysis and observational datasets from 1950 up to real-time. Furthermore, the land surface model (currently the VIC land surface model is being used) was recalibrated against spatially disaggregated runoff fields derived from over 500 GRDC stream gauge measurements over Africa. The final result includes a retrospective database from 1950 to real-time of soil moisture, evapotranspiration, river discharge at the GRDC gauged sites (etc.) at a 1/4 degree spatial resolution, and daily temporal resolution. These observation-forced simulations are analyzed to detect and track historical drought events according to a drought index that is calculated from the soil moisture fields and river discharge relative to their seasonal climatology. The real-time monitoring requires the use of remotely sensed and weather-model analysis estimates of hydrological model forcings. For the current system, NOAA's Global Forecast System (GFS) is used along with remotely sensed precipitation from the NASA TMPA system. The historical archive of these data is

  7. Real-time monitoring and short-term forecasting of drought in Norway

    NASA Astrophysics Data System (ADS)

    Kwok Wong, Wai; Hisdal, Hege

    2013-04-01

    Drought is considered to be one of the most costly natural disasters. Drought monitoring and forecasting are thus important for sound water management. In this study hydrological drought characteristics applicable for real-time monitoring and short-term forecasting of drought in Norway were developed. A spatially distributed hydrological model (HBV) implemented in a Web-based GIS framework provides a platform for drought analyses and visualizations. A number of national drought maps can be produced, which is a simple and effective way to communicate drought conditions to decision makers and the public. The HBV model is driven by precipitation and air temperature data. On a daily time step it calculates the water balance for 1 x 1 km2 grid cells characterized by their elevation and land use. Drought duration and areal drought coverage for runoff and subsurface storage (sum of soil moisture and groundwater) were derived. The threshold level method was used to specify drought conditions on a grid cell basis. The daily 10th percentile thresholds were derived from seven-day windows centered on that calendar day from the reference period 1981-2010 (threshold not exceeded 10% of the time). Each individual grid cell was examined to determine if it was below its respective threshold level. Daily drought-stricken areas can then be easily identified when visualized on a map. The drought duration can also be tracked and calculated by a retrospective analysis. Real-time observations from synoptic stations interpolated to a regular grid of 1 km resolution constituted the forcing data for the current situation. 9-day meteorological forecasts were used as input to the HBV model to obtain short-term hydrological drought forecasts. Downscaled precipitation and temperature fields from two different atmospheric models were applied. The first two days of the forecast period adopted the forecasts from Unified Model (UM4) while the following seven days were based on the 9-day forecasts

  8. Flooding During Drought: Learning from Stakeholder Engagement & Partner Coordination in the California-Nevada Drought Early Warning System (DEWS)

    NASA Astrophysics Data System (ADS)

    Sheffield, A. M.

    2017-12-01

    After more than 5 years of drought, extreme precipitation brought drought relief in California and Nevada and presents an opportunity to reflect upon lessons learned while planning for the future. NOAA's National Integrated Drought Information System (NIDIS) California-Nevada Drought Early Warning System (DEWS) in June 2017 convened a regional coordination workshop to provide a forum to discuss and build upon past drought efforts in the region and increase coordination, collaboration and information sharing across the region as a whole. Participants included federal, tribal, state, academic, and local partners who provided a post-mortem on the recent drought and impacts as well as recent innovations in drought monitoring, forecasts, and decision support tools in response to the historic drought. This presentation will highlight lessons learned from stakeholder outreach and engagement around flooding during drought, and pathways for moving forward coordination and collaboration in the region. Additional focus will be on the potential opportunities from examining California decision making calendars from this drought. Identified gaps and challenges will also be shared, such as the need to connect observations with social impacts, capacity building around available tools and resources, and future drought monitoring needs. Drought will continue to impact California and Nevada, and the CA-NV DEWS works to make climate and drought science readily available, easily understandable and usable for decision makers; and to improve the capacity of stakeholders to better monitor, forecast, plan for and cope with the impacts of drought.

  9. A new multi-sensor integrated index for drought monitoring

    NASA Astrophysics Data System (ADS)

    Jiao, W.; Wang, L.; Tian, C.

    2017-12-01

    Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for

  10. The U.S./Canadian GEO Bilateral Drought Indices and Definitions Study: Implications for the Canadian Drought Monitor and a Global Drought Early Warning System

    NASA Astrophysics Data System (ADS)

    Hadwen, T.; Heim, R. R.; Howard, A.

    2011-12-01

    Drought is a difficult phenomenon to define; the way in which it is monitored, measured, assessed and even the very definition of drought vary from location to location based on the regional climate and the potential impacts. Drought is not an absolute condition but an evolving state brought on by relatively dry weather, growing more severe over time. There are many factors that define a drought and many more that define its impacts. Many definitions and indices are based solely on meteorological characteristics. Although this approach has merit, it is often necessary to go further to define those meteorological conditions in a way that is relevant to the land and water use in a region. A Drought Indices and Definitions Study was initiated in 2010 as part of a GEO Bilateral effort to examine drought across the U.S. and Canada. The Study's deliverables will include a survey of the drought indices used to monitor drought, and a bibliography of research addressing the nature of drought, across the diverse climates of the continent. With an increasing pressure to utilize drought monitoring as a primary indicator of need for disaster assistance, the reliability of drought indices must be validated and utilized in appropriate in various regions. In 2009, following over five years of participation in the North American Drought Monitor (NA-DM), the National Agroclimate Information Service of Agriculture and Agri-Food Canada initiated a project to develop a Canadian Drought Monitor (Can-DM), based on primary principles used in the NA-DM and the US Drought Monitor (US-DM). The process of developing an operational monitoring tool and using drought indices in a vast and environmentally diverse country has been challenging. in Canada, many of the commonly used indices are not appropriate in certain regions or data densities do not allow for proper use. This paper will discuss the experiences that the Can-DM team has had dealing with these challenges, how these experiences

  11. Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

    NASA Astrophysics Data System (ADS)

    Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

    2014-05-01

    Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety

  12. 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.

  13. 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.

  14. 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

  15. Research on the remote sensing methods of drought monitoring in Chongqing

    NASA Astrophysics Data System (ADS)

    Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

    2011-12-01

    There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.

  16. 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

  17. Building Better Drought Resilience Through Improved Monitoring and Early Warning: Learning From Stakeholders in Europe, the USA, and Australia

    NASA Astrophysics Data System (ADS)

    Stahl, K.; Hannaford, J.; Bachmair, S.; Tijdeman, E.; Collins, K.; Svoboda, M.; Knutson, C. L.; Wall, N.; Smith, K. H.; Bernadt, T.; Crossman, N. D.; Overton, I. C.; Barker, L. J.; Acreman, M. C.

    2016-12-01

    With climate projections suggesting that droughts will intensify in many regions in future, improved drought risk management may reduce potential threats to freshwater security across the globe. One aspect that has been called for in this respect is an improvement of the linkage of drought monitoring and early warning, which currently focuses largely on indicators from meteorology and hydrology, to drought impacts on environment and society. However, a survey of existing monitoring and early warning systems globally, that we report on in this contribution, demonstrates that although impacts are being monitored, there is limited work, and certainly little consensus, on how to best achieve this linkage. The Belmont Forum project DrIVER (Drought impacts: Vulnerability thresholds in monitoring and early-warning research) carried out a number of stakeholder workshops in North America, Europe and Australia to elaborate on options for such improvements. A first round of workshops explored current drought management practices among a very diverse range of stakeholders, and their expectations from monitoring and early warning systems (particularly regarding impact characterization). The workshops revealed some disconnects between the indices used in the public early warning systems and those used by local decision-makers, e.g. to trigger drought measures. Follow-up workshops then explored how the links between information at these different scales can be bridged and applied. Impact information plays a key role in this task. This contribution draws on the lessons learned from the transdisciplinary interactions in DrIVER, to enhance the usability of drought monitoring and early-warning systems and other risk management strategies.

  18. 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

  19. 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

  20. Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

    NASA Astrophysics Data System (ADS)

    Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

    2012-12-01

    Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate

  1. Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China

    NASA Astrophysics Data System (ADS)

    Chen, Hui; Wu, Wei; Liu, Hong-Bin

    2018-04-01

    Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.

  2. Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

    NASA Astrophysics Data System (ADS)

    Aghakouchak, Amir; Tourian, Mohammad J.

    2015-04-01

    Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

  3. The Crop Risk Zones Monitoring System for resilience to drought in the Sahel

    NASA Astrophysics Data System (ADS)

    Vignaroli, Patrizio; Rocchi, Leandro; De Filippis, Tiziana; Tarchiani, Vieri; Bacci, Maurizio; Toscano, Piero; Pasqui, Massimiliano; Rapisardi, Elena

    2016-04-01

    Food security is still one of the major concerns that Sahelian populations have to face. In the Sahel, agriculture is primarily based on rainfed crops and it is often structurally inadequate to manage the climatic variability. The predominantly rainfed cropping system of Sahel region is dependent on season quality on a year-to-year basis, and susceptible to weather extremes of droughts and extreme temperatures. Low water-storage capacity and high dependence on rainfed agriculture leave the agriculture sector even more vulnerable to climate risks. Crop yields may suffer significantly with either a late onset or early cessation of the rainy season, as well as with a high frequency of damaging dry spells. Early rains at the beginning of the season are frequently followed by dry spells which may last a week or longer. As the amount of water stored in the soil at this time of the year is negligible, early planted crops can suffer water shortage stresses during a prolonged dry spell. Therefore, the choice of the sowing date is of fundamental importance for farmers. The ability to estimate effectively the onset of the season and potentially dangerous dry spells becomes therefore vital for planning rainfed agriculture practices aiming to minimize risks and maximize yields. In this context, advices to farmers are key drivers for prevention allowing a better adaptation of traditional crop calendar to climatic variability. In the Sahel, particularly in CILSS (Permanent Interstates Committee for Drought Control in the Sahel) countries, national Early Warning System (EWS) for food security are underpinned by Multidisciplinary Working Groups (MWGs) lead by National Meteorological Services (NMS). The EWSs are mainly based on tools and models utilizing numeric forecasts and satellite data to outlook and monitor the growing season. This approach is focused on the early identification of risks and on the production of information within the prescribed time period for decision

  4. The economic value of drought information: Application to water resources management decisions in Spain

    NASA Astrophysics Data System (ADS)

    Garrote, Luis; Sordo, Alvaro; Iglesias, Ana

    2016-04-01

    Information is valuable when it improves decision-making (e.g., actions can be adjusted to better suit the situation at hand) and enables the mitigation of damage. However, quantifying the value of information is often difficult. Here we explore a general approach to understand the economic value of drought information for water managers framing our approach in the precautionary principle that reminds us that uncertainty is not a reason to postpone or avoid action. We explore how decision making can disregard uncertain effects, taking a short-term approach and focusing instead on the certain costs and benefits of taking action. Two main questions arise: How do we know that advanced drought information is actually helping decisions?; and What is the value of information in the decision process? The approach is applied to several regulated water resources systems in Spain. It first views drought information as a factor in the decision process which can be used by water managers to reduce uncertainty. Second, the value of drought information is the expected gain in a decision outcome (utility) from using additional information. Finally, the gains of improved information are compared with the information collection costs. Here we estimate the value by taking into account the accuracy of the drought information, the subjective probabilities about the value, analyzed as Bayesian probabilities, and the ability or skill of the stakeholders to apply the drought information to modify their actions. Since information may be considered a public good (non-rivalry and non-excludability), it may justify public policy in the provision of information, considering social costs and benefits. The application of the framework to the Spanish case studies shows that information benefits exceeds to costs when drought frequency is 20-40% above normal values; below these values uncertainty in the decisions dominate the results; above these values, the management decisions are limited even

  5. 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

  6. 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.

  7. 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. 

  8. Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

    NASA Astrophysics Data System (ADS)

    Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

    2014-12-01

    Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and

  9. Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

    NASA Astrophysics Data System (ADS)

    Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

    2015-12-01

    Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and

  10. Timescale differences between SC-PDSI and SPEI for drought monitoring in China

    NASA Astrophysics Data System (ADS)

    Zhao, Haiyan; Gao, Ge; An, Wei; Zou, Xukai; Li, Haitao; Hou, Meiting

    2017-12-01

    The Palmer Drought Severity Index (PDSI) has been widely used to monitor drought. Its characteristics are more suitable for measuring droughts of longer timescales, and this fact has not received much attention. The Standardized Precipitation Evapotranspiration Index (SPEI) can better reflect the climatic water balance, owing to its combination of precipitation and potential evapotranspiration. In this study, we selected monthly average air temperature and precipitation data from 589 meteorological stations of China's National Meteorological Information Center, to compare the effects of applying a self-calibrating PDSI (SC-PDSI) and SPEI to monitor drought events in the station regions, with a special focus on differences of event timescale. The results show the following. 1) Comparative analysis using SC-PDSI and SPEI for drought years and characters of three dry periods from 1961 to 2011 in the Beijing region showed that durations of SC-PDSI-based dry spells were longer than those of 3-month and 6-month SPEIs, but equal to those of 12-month or longer timescale SPEIs. 2) For monitoring evolution of the fall 2009 to spring 2010 Southwest China drought and spring 2000 Huang-Huai drought, 3-month SPEI could better monitor the initiation, aggravation, alleviation and relief of drought in the two regions, whereas the SC-PDSI was insensitive to drought recovery because of its long-term memory of previous climate conditions. 3) Analysis of the relationship between SC-PDSI for different regions and SPEI for different timescales showed that correlation of the two indexes changed with region, and SC-PDSI was maximally correlated with SPEI of 9-19 months in China. Therefore, SC-PDSI is only suitable for monitoring mid- and long-term droughts, owing to the strong lagged autocorrelation such as 0.4786 for 12-month lagged ones in Beijing, whereas SPEI is suitable for both short- and long-term drought-monitoring and should have greater application prospects in China.

  11. Assessment of TRMM 3B43 product for drought monitoring in Singapore

    NASA Astrophysics Data System (ADS)

    Tan, Mou Leong; Chua, Vivien P.; Tan, Kok Chooi; Brindha, K.

    2017-10-01

    Drought is one of the most hazardous natural disasters for human beings and the environment. Using only rain gauge is insufficient to monitor the drought pattern effectively as it impacts large areas. This situation is more critical on small island countries, with limited rain gauges for monitoring drought pattern over the ocean regions. This study aims to assess the capability of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B43 product in monitoring drought in Singapore from 1998 to 2014. The Standardized Precipitation Index (SPI) at various time-scales is used for identifying drought patterns. Results show moderate to good correlations between TMPA- 3B43 and rain gauges in the SPI estimations. Besides that, TMPA-3B43 exhibits a similar temporal drought behavior as the rain gauges. These findings indicate the TMPA 3B43 product as a very useful tool to study drought pattern over Singapore.

  12. 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

  13. 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.

  14. 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.

  15. Use of decision support systems as a drought management tool

    USGS Publications Warehouse

    Frevert, D.; Lins, H.; ,

    2005-01-01

    Droughts present a unique challenge to water managers throughout the world and the current drought in the western United States is taxing facilities to the limit. Coping with this severe drought requires state of the art decision support systems including efficient and accurate hydrologic process models, detailed hydrologic data bases and effective river systems management modeling frameworks. This paper will outline a system of models developed by the Bureau of Reclamation, the US Geological Survey, the University of Colorado and a number of other governmental and university partners. The application of the technology to drought management in several key western river basins will be discussed.

  16. Making the Case for a Water Monitor: A Potential Complement to the U.S. Drought Monitor within a Water Management Context

    NASA Astrophysics Data System (ADS)

    Svoboda, M. D.; Fuchs, B.; Poulsen, C.; Nothwehr, J.; Swigart, J.

    2017-12-01

    Launched in 1999, the weekly U.S. Drought Monitor (USDM) is now approaching its twentieth year of existence. Over that time, it has built up an expert validation community that has grown into a network of nearly 450 persons. From the very beginning, questions from the user community have been centered on how we can do a better job of addressing and depicting short- vs. long-term conditions on a single map such as the U.S. Drought Monitor. Early efforts to fill the water supply/demand/forecast void have simply utilized existing hydrological websites and products from a variety of sources across a variety of spatial and temporal scales. The question being asked repeatedly has been "Why not develop two separate maps?" Can such an approach strengthen our capacity to assess both the supply and demand side of the equation when it comes to balancing drought and water supply? This presentation will describe in more detail the evolution of the USDM and how the need for a complementary sister product such as a Water Monitor has emerged. We will explore how such a tool could better capture and collectively assess key hydroclimatic parameters (e.g., in situ, modeled and remotely sensed products), better integrate streamflow forecasts, and reflect surface and groundwater resources and snow water equivalent. In essence, the goal is to develop a more usable decision support tool that has the potential to better facilitate water management and markets in the United States. Ultimately, there are vast differences between the USDM and Water Monitor products that we must address in order to better reflect how drought affects both managed and unmanaged systems.

  17. Informing Drought Preparedness and Response with the South Asia Land Data Assimilation System

    NASA Astrophysics Data System (ADS)

    Zaitchik, B. F.; Ghatak, D.; Matin, M. A.; Qamer, F. M.; Adhikary, B.; Bajracharya, B.; Nelson, J.; Pulla, S. T.; Ellenburg, W. L.

    2017-12-01

    Decision-relevant drought monitoring in South Asia is a challenge from both a scientific and an institutional perspective. Scientifically, climatic diversity, inconsistent in situ monitoring, complex hydrology, and incomplete knowledge of atmospheric processes mean that monitoring and prediction are fraught with uncertainty. Institutionally, drought monitoring efforts need to align with the information needs and decision-making processes of relevant agencies at national and subnational levels. Here we present first results from an emerging operational drought monitoring and forecast system developed and supported by the NASA SERVIR Hindu-Kush Himalaya hub. The system has been designed in consultation with end users from multiple sectors in South Asian countries to maximize decision-relevant information content in the monitoring and forecast products. Monitoring of meteorological, agricultural, and hydrological drought is accomplished using the South Asia Land Data Assimilation System, a platform that supports multiple land surface models and meteorological forcing datasets to characterize uncertainty, and subseasonal to seasonal hydrological forecasts are produced by driving South Asia LDAS with downscaled meteorological fields drawn from an ensemble of global dynamically-based forecast systems. Results are disseminated to end users through a Tethys online visualization platform and custom communications that provide user oriented, easily accessible, timely, and decision-relevant scientific information.

  18. 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.

  19. 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.

  20. 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

  1. A Look into the National Drought Mitigation Center: Providing 15 Years of Drought Services (Invited)

    NASA Astrophysics Data System (ADS)

    Svoboda, M. D.; Hayes, M. J.; Knutson, C. L.; Wardlow, B. D.

    2009-12-01

    The National Drought Mitigation Center (NDMC) was formed in 1995 at the University of Nebraska-Lincoln. Over the past 15 years, the NDMC has made it a priority to work with various local, state, tribal and federal entities to provide a suite of drought/climate services, with a goal of bringing research to fruition through applications and operations. Through our research and outreach projects, the NDMC has worked to reduce risk to drought by developing several mitigation strategies, monitoring and decision making tools and other services aimed at enhancing our nation’s capacity to cope with drought. Two of the earliest NDMC activities were the creation of a website and assessing drought conditions around the United States. An electronic drought clearinghouse was built in 1995 at drought.unl.edu. The site was designed, and still concentrates, on the concepts of drought monitoring, planning, and mitigation and also serves as a repository of information from around the world. The NDMC’s electronic quarterly newsletter, DroughtScape, disseminates information about all things drought to people across the country. In addition, the NDMC has developed and is home to websites for the U.S. Drought Monitor (USDM), Drought Impact Reporter (DIR), and the Vegetation Drought Response Index (VegDRI). In an effort to inform decision makers, the NDMC continually pursues ways to raise the awareness and visibility of drought as one of the most costly hazards we face. This began in the mid-1990s with the creation of a state-based drought impact assessment map that would help lead to the formation of the USDM in 1999 and the DIR in 2005. The NDMC plays a key role in producing the weekly USDM and the monthly North American Drought Monitor (NADM). The USDM was created out of collaborations between the NDMC, United States Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) and has quickly become one of the most widely used products in assessing

  2. Ecohydrological drought monitoring and prediction using a land data assimilation system

    NASA Astrophysics Data System (ADS)

    Sawada, Y.; Koike, T.

    2017-12-01

    Despite the importance of the ecological and agricultural aspects of severe droughts, few drought monitor and prediction systems can forecast the deficit of vegetation growth. To address this issue, we have developed a land data assimilation system (LDAS) which can simultaneously simulate soil moisture and vegetation dynamics. By assimilating satellite-observed passive microwave brightness temperature, which is sensitive to both surface soil moisture and vegetation water content, we can significantly improve the skill of a land surface model to simulate surface soil moisture, root zone soil moisture, and leaf area index (LAI). We run this LDAS to generate a global ecohydrological land surface reanalysis product. In this presentation, we will demonstrate how useful this new reanalysis product is to monitor and analyze the historical mega-droughts. In addition, using the analyses of soil moistures and LAI as initial conditions, we can forecast the ecological and hydrological conditions in the middle of droughts. We will present our recent effort to develop a near real time ecohydrological drought monitoring and prediction system in Africa by combining the LDAS and the atmospheric seasonal prediction.

  3. 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; hide

    2011-01-01

    NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors 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 by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields.

  4. Satellite Gravimetry Applied to Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Rodell, Matthew

    2010-01-01

    Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes

  5. 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'.

  6. Forecasting and Monitoring Agricultural Drought in the Philippines

    NASA Astrophysics Data System (ADS)

    Perez, G. J.; Macapagal, M.; Olivares, R.; Macapagal, E. M.; Comiso, J. C.

    2016-06-01

    A monitoring and forecasting sytem is developed to assess the extent and severity of agricultural droughts in the Philippines at various spacial scales and across different time periods. Using Earth observation satellite data, drought index, hazard and vulnerability maps are created. The drought index, called Standardized Vegetation-Temperature Ratio (SVTR), is derived using the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). SVTR is evaluated by correlating its values with existing agricultural drought index, particulary Evaporative Stress Index (ESI). Moreover, the performance of SVTR in detecting drought occurrences was assessed for the 2015-2016 drought event. This period is a strong El Niño year and a large portion of the country was affected by drought at varying degrees, making it a good case study for evaluating drought indices. Satellitederived SVTR was validated through several field visits and surveys across different major agricultural areas in the country, and was found to be 73% accurate. The drought hazard and vulnerability maps are produced by utilizing the evapotranspration product of MODIS, rainfall climatology from the Tropical Rainfall Microwave Mission (TRMM) and ancillary data, including irrigation, water holding capacity and land use. Finally, we used statistical techniques to determine trends in NDVI and LST and generate a sixmonth forecast of drought index. Outputs of this study are being assessed by the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) and the Department of Agriculture Bureau of Soils and Water Management (DABSWM) for future integration in their operations.

  7. Drought monitoring in the Brazilian Semiarid region.

    PubMed

    Alvalá, Regina C S; Cunha, Ana Paula M A; Brito, Sheila S B; Seluchi, Marcelo E; Marengo, José A; Moraes, Osvaldo L L; Carvalho, Magog A

    2017-10-16

    Drought is a natural and recurrent phenomenon. It is considered 'a natural disaster' whenever it occurs in an intensive manner in highly populated regions, resulting in significant damage (material and human) and loss (socioeconomic). This paper presents the efforts developed to monitor the impact of drought in the semiarid region of Northeast Brazil. In this scope, information from different sources is compiled to support the evaluation and identification of impacted municipalities, with the main objective of supporting emergency actions to mitigate their impact. In the semiarid region of Brazil there are frequent occurrences of dry periods during the rainy season, which, depending on the intensity and duration, can cause significant damage to family-farmed crops, with a farming system characterized by low productivity indices. However, rain-fed agriculture has great economic expression and high social importance due to the region is densely occupied, and contributes to the establishment of communities in the countryside. Specifically, in the present study, the methodology adopted to monitor the impact of agricultural droughts, including an analysis of the hydrological year 2015-2016, is presented, considering different water stress indicators for the identification of the affected municipalities and assessment of the methods and tools developed.

  8. Drought Monitoring and Forecasting: Experiences from the US and Africa

    NASA Astrophysics Data System (ADS)

    Sheffield, Justin; Chaney, Nate; Yuan, Xing; Wood, Eric

    2013-04-01

    Drought has important but very different consequences regionally due to differences in vulnerability. These differences derive from variations in exposure related to climate variability and change, sensitivity of local populations, and coping capacity at all levels. Managing the risk of drought impacts relies on a variety of measures to reduce vulnerability that includes forewarning of drought development through early-warning systems. Existing systems rely on a variety of observing systems from satellites to local observers, modeling tools, and data dissemination methods. They range from sophisticated state-of-the-art systems to simple ground reports. In some regions, systems are virtually non-existent due to limited national capacity. This talk describes our experiences in developing and implementing drought monitoring and seasonal forecast systems in the US and sub-Saharan Africa as contrasting examples of the scientific challenges and user needs in developing early warning systems. In particular, early warning can help improve livelihoods based on subsistence farming in sub-Saharan Africa; whist reduction of economic impacts is generally foremost in the US. For the US, our national drought monitoring and seasonal forecast system has been operational for over 8 years and provides near real-time updates on hydrological states at ~12km resolution and hydrological forecasts out to 9 months. Output from the system contributes to national assessments such as from the NOAA Climate Prediction Center (CPC) and the US National Drought Monitor (USDM). For sub-Saharan Africa, our experimental drought monitoring system was developed as a translation of the US system but presents generally greater challenges due to, for example, lack of ground data and unique user needs. The system provides near real-time updates based on hydrological modeling and satellite based precipitation estimates, and has recently been augmented by a seasonal forecast component. We discuss the

  9. 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

  10. Development of a SMAP-Based Drought Monitoring Product

    NASA Astrophysics Data System (ADS)

    Sadri, S.; Wood, E. F.; Pan, M.; Lettenmaier, D. P.

    2016-12-01

    Agricultural drought is defined as a deficit in the amount of soil moisture over a prolonged period of time. Soil moisture information over time and space provides critical insight for agricultural management, including both water availability for crops and moisture conditions that affect management practices such as fertilizer, pesticide applications, and their impact as non-point pollution runoff. Since April of 2015, NASA's Soil Moisture Active Passive (SMAP) mission has retrieved soil moisture using L-band passive radiometric measurements at a 8 day repeat orbit with a swath of 1000 km that maps the Earth in 2-3 days depending on locations. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP soil moisture in terms of probability percentiles for dry (drought) or wet (pluvial) conditions. SMAP observations do result in retrievals that are spatially and temporally discontinuous. Additionally, the short SMAP record length provides a statistical challenge in estimating a drought index and thus drought risk evaluations. In this presentation, we describe a SMAP drought index for the CONUS region based on near-surface soil moisture percentiles. Because the length of the SMAP data record is limited, we use a Bayesian conditional probability approach to extend the SMAP record back to 1979 based on simulated soil moisture of the same period from the Variable Infiltration Capacity (VIC) Land Surface Model (LSM), simulated by Princeton University. This is feasible because the VIC top soil layer (10 cm) is highly correlated with the SMAP 36 km passive microwave during 2015-2016, with more than half the CONUS grids having a cross-correlation greater than 0.6, and over 0.9 in many regions. Given the extended SMAP record, we construct an empirical probability distribution of near-surface soil moisture drought index showing severities similar to those used by the U.S. Drought Monitor (from D0-D4), for a specific SMAP

  11. Assessing existing drought monitoring and forecasting capacities, mitigation and adaptation practices in Africa

    NASA Astrophysics Data System (ADS)

    Nyabeze, W. R.; Dlamini, L.; Lahlou, O.; Imani, Y.; Alaoui, S. B.; Vermooten, J. S. A.

    2012-04-01

    Drought is one of the major natural hazards in many parts of the world, including Africa and some regions in Europe. Drought events have resulted in extensive damages to livelihoods, environment and economy. In 2011, a consortium consisting of 19 organisations from both Africa and Europe started a project (DEWFORA) aimed at developing a framework for the provision of early warning and response through drought impact mitigation for Africa. This framework covers the whole chain from monitoring and vulnerability assessment to forecasting, warning, response and knowledge dissemination. This paper presents the first results of the capacity assessment of drought monitoring and forecasting systems in Africa, the existing institutional frameworks and drought mitigation and adaptation practices. Its focus is particularly on the historical drought mitigation and adaptation actions identified in the North Africa - Maghreb Region (Morocco, Algeria and Tunisia) and in the Southern Africa - Limpopo Basin. This is based on an extensive review of historical drought experiences. From the 1920's to 2009, the study identified 37 drought seasons in the North African - Maghreb Region and 33 drought seasons in the Southern Africa - Limpopo Basin. Existing literature tends to capture the spatial extent of drought at national and administrative scale in great detail. This is driven by the need to map drought impacts (food shortage, communities affected) in order to inform drought relief efforts (short-term drought mitigation measures). However, the mapping of drought at catchment scale (hydrological unit), required for longer-term measures, is not well documented. At regional level, both in North Africa and Southern Africa, two organisations are involved in drought monitoring and forecasting, while at national level 22 organisations are involved in North Africa and 37 in Southern Africa. Regarding drought related mitigation actions, the inventory shows that the most common actions

  12. 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.

  13. Drought monitoring using remote sensing of evapotranspiration

    USDA-ARS?s Scientific Manuscript database

    Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moist...

  14. Developing Drought Outlook Forums in Support of a Regional Drought Early Warning Information System

    NASA Astrophysics Data System (ADS)

    Mcnutt, C. A.; Pulwarty, R. S.; Darby, L. S.; Verdin, J. P.; Webb, R. S.

    2011-12-01

    The National Integrated Drought Information System (NIDIS) Act of 2006 (P.L. 109-430) charged NIDIS with developing the leadership and partnerships necessary to implement an integrated national drought monitoring and forecasting system that creates a drought "early warning system". The drought early warning information system should be capable of providing accurate, timely and integrated information on drought conditions at the relevant spatial scale to facilitate proactive decisions aimed at minimizing the economic, social and ecosystem losses associated with drought. As part of this effort, NIDIS has held Regional Drought Outlook Forums in several regions of the U.S. The purpose of the Forums is to inform practices that reduce vulnerability to drought through an interactive and collaborative process that includes the users of the information. The Forums have focused on providing detailed assessments of present conditions and impacts, comparisons with past drought events, and seasonal predictions including discussion of the state and expected evolution of the El Niño Southern Oscillation phenomena. Regional Climate Outlook Forums (RCOFs) that include close interaction between information providers and users are not a new concept, however. RCOFs started in Africa in the 1990s in response to the 1997-98 El Niño and have since expanded to South America, Asia, the Pacific islands, and the Caribbean. As a result of feedback from the RCOFs a large body of research has gone into improving seasonal forecasts and the capacity of the users to apply the information in a way that improves their decision-making. Over time, it has become clear that more is involved than just improving the interaction between the climate forecasters and decision-makers. NIDIS is using the RCOF approach as one component in a larger effort to develop Regional Drought Early Warning Information Systems (RDEWS) around the U.S. Using what has been learned over the past decade in the RCOF process

  15. 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

  16. Using Satellite Data to Build Climate Resilience: A Novel East Africa Drought Monitor

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    East Africa is affected by recurrent drought. The 2015-2016 El Niño triggered a severe drought across East Africa causing serious impacts to regional water security, health, and livelihoods. Ethiopia was the hardest hit, with the United Nations Office for the Coordination of Humanitarian Affairs calling the recent drought the worst in 50 years. Resources to monitor the severity and progression of droughts are a critical component to disaster risk reduction, but are challenging to implement in regions with sparse data collection networks such as East Africa. Satellite data is used by the United Nations Food and Agriculture Organization Global Information and Early Warning System, the USAID Famine Early Warning System, and the Africa Drought and Flood Monitor. These systems use remotely sensed vegetation, soil moisture, and meteorological data to develop drought indices. However, they do not directly monitor impacts to water resources, which is necessary to appropriately target drought mitigation efforts. The current study combines new radar data from the European Space Agency's Sentinel-1 mission with satellite imagery to perform a retrospective analysis of the impact of the 2015-2016 drought in East Africa on regional surface water. Inland water body extents during the drought are compared to historical trends to identify the most severely impacted areas. The developed tool has the potential to support on-the-ground humanitarian relief efforts and to refine predictions of water scarcity and crop impacts from existing hydrologic models and famine early warning systems.

  17. 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

  18. Global Drought Services: Collaborations Toward an Information System for Early Warning

    NASA Astrophysics Data System (ADS)

    Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.

    2014-12-01

    Drought is a hazard that lends itself well to diligent, sustained monitoring and early warning. However, unlike most hazards, the fact that droughts typically evolve slowly, can last for months or years and cover vast areas spanning multiple political boundaries/jurisdictions and economic sectors can make it a daunting task to monitor, develop plans for, and identify appropriate, proactive mitigation strategies. The National Drought Mitigation Center (NDMC) and National Integrated Drought Information System (NIDIS) have been working together to reduce societal vulnerability to drought by helping decision makers at all levels to: 1) implement drought early warning/forecasting and decision support systems; 2) support and advocate for better collection of, and understanding of drought impacts; and 3) increase long-term resilience to drought through proactive planning. The NDMC and NIDIS risk management approach has been the basis from which many partners around the world are developing a collaboration and coordination nexus with an ultimate goal of building comprehensive global drought early warning information systems (GDEWIS). The core emphasis of this model is on developing and applying useful and usable information that can be integrated and transferred freely to other regions around the globe. The High-Level Ministerial Declaration on Drought, the Integrated Drought Management Programme (IDMP) co-led by the WMO and the Global Water Partnership (GWP), and the Global Framework for Climate Services are drawing extensively from the integrated NDMC-NIDIS risk management framework. This presentation will describe, in detail, the various drought resources, tools, services, and collaborations already being provided and undertaken at the national and regional scales by the NDMC, NIDIS, and their partners. The presentation will be forward-looking, identifying improvements in existing and proposed mechanisms to help strengthen national and international drought early

  19. Advance of the Monitor of Drought for the Northern Region of Mexico

    NASA Astrophysics Data System (ADS)

    Reyes Gomez, V. M.; Nunez Lopez, D.

    2007-05-01

    In the last 13 years, the State of Chihuahua suffered a lingering drought that caused social, economical and environmental impacts hardly quantifiable. Since 2002, a monitoring system was implemented to watch the evolution of the meteorological drought in Chihuahua, recently being broadened for the states in the North of Mexico. Evaluation of the Meteorological Drought The Monitoring System on the Drought in Chihuahua includes the following steps: missing data gaps were completed basing on the statistical procedures described by Young (1992); the source code, was compiled to create a computer program, with which it can be derived a level of climatic station, historical series of values for the SPI in time scales of 1 to 48 months; under this classification scheme, it is considered that a drought event begins when the values of the SPI are inferior to -0.7 (McKee et al. 1995). The spatial distribution of the SPI was determined through spatial interpolation techniques using a reverse method of the distance between stations included in Arc/Info©. This same procedure was applied for the States of Sonora, Sinaloa, Durango and Zacatecas with the purpose of implementing this tool for the north of Mexico. Advances on the Monitoring System The monitoring system allows an analysis of the frequency, duration and intensity of the drought events that took place in several climatic regions (Núñez-López et al., 2005); un map of spatial distribution of the SPI for the northern region of Mexico, in the States of Sonora, Sinaloa, Durango and Chihuahua. The generated map will be published in a section on the CEISS web page (www.sequia.edu.mx), together with the monthly bulletin available to the public in general; it is monitoring to an annual scale, the tendencies of the deficits or surplus of the runoff volumes on three of the main dams in the State of Chihuahua Conclusions The Drought Monitoring System in Chihuahua complies with the following international rules for the

  20. NCEP/NLDAS Drought Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Xia, Y.; Ek, M.; Wood, E.; Luo, L.; Sheffield, J.; Lettenmaier, D.; Livneh, B.; Cosgrove, B.; Mocko, D.; Meng, J.; Wei, H.; Restrepo, P.; Schaake, J.; Mo, K.

    2009-05-01

    The NCEP Environmental Modeling Center (EMC) collaborated with its CPPA (Climate Prediction Program of the Americas) partners to develop a North American Land Data Assimilation System (NLDAS, http://www.emc.ncep.noaa.gov/mmb/nldas) to monitor and predict the drought over the Continental United States (CONUS). The realtime NLDAS drought monitor, executed daily at NCEP/EMC, including daily, weekly and monthly anomaly and percentile of six fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, precipitation) outputted from four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid using common hourly land surface forcing. The non-precipitation surface forcing is derived from NCEP's retrospective and realtime North American Regional Reanalysis System (NARR). The precipitation forcing is anchored to a daily gauge-only precipitation analysis over CONUS that applies a Parameter-elevation Regressions on Independent Slopes Model (PRISM) correction. This daily precipitation analysis is then temporally disaggregated to hourly precipitation amounts using radar and satellite precipitation. The NARR- based surface downward solar radiation is bias-corrected using seven years (1997-2004) of GOES satellite- derived solar radiation retrievals. The uncoupled ensemble seasonal drought prediction utilizes the following three independent approaches for generating downscaled ensemble seasonal forecasts of surface forcing: (1) Ensemble Streamflow Prediction, (2) CPC Official Seasonal Climate Outlook, and (3) NCEP CFS ensemble dynamical model prediction. For each of these three approaches, twenty ensemble members of forcing realizations are generated using a Bayesian merging algorithm developed by Princeton University. The three forcing methods are then used to drive the VIC model in seasonal prediction mode over thirteen large river basins that together span the CONUS domain. One to nine month ensemble seasonal prediction products

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Kuwayama, Y.; Bernknopf, R.; Brookshire, D.; Macauley, M.; Zaitchik, B. F.; Rodell, M.; Vail, P.; Thompson, A.

    2015-12-01

    In this project, we develop a framework to estimate the economic value of information from the Gravity and Climate Experiment (GRACE) for drought monitoring and to understand how the GRACE Data Assimilation (GRACE-DA) system can inform decision making to improve regional economic outcomes. Specifically, we consider the potential societal value of further incorporating GRACE-DA information into the U.S. Drought Monitor mapmaking process. Research activities include (a) a literature review, (b) a series of listening sessions with experts and stakeholders, (c) the development of a conceptual economic framework based on a Bayesian updating procedure, and (d) an econometric analysis and retrospective case study to understand the GRACE-DA contribution to agricultural policy and production decisions. Taken together, the results from these research activities support our conclusion that GRACE-DA has the potential to lower the variance associated with our understanding of drought and that this improved understanding has the potential to change policy decisions that lead to tangible societal benefits.

  3. Drought is Coming: Monitoring Vegetation Response to Water Scarcity through Variable Chlorophyll a Fluorescence

    NASA Astrophysics Data System (ADS)

    Guadagno, C. R.; Beverly, D.; Pleban, J. R.; Speckman, H. N.; Ewers, B. E.; Weinig, C.

    2017-12-01

    Aridity is one of the most pronounced environmental limits to plant survival, and understanding how plants respond to drought and recovery is crucial for predicting impacts on managed and natural ecosystems. Changes in soil moisture conditions induce a suite of physiological responses from the cell to ecosystem scale, complicating the assessment of drought effects. Characterizing early indicators of water scarcity across species can inform biophysical models with improved understanding of plant hydraulics. While indexes exist for drought monitoring across scales, many are unable to identify imminent vegetative drought. We explore a method of early diagnosis using leaf-level and kinetic imaging measures of variable chlorophyll a fluorescence. This is a fast and reliable tool capturing leaf physiological changes in advance of changes in NDVI or passive solar induced fluorescence. Both image and leaf level Pulse Amplitude Method (PAM) measurements illustrate the utility of variable chlorophyll a fluorescence for monitoring vegetative drought. Variable fluorescence was monitored across populations of crops, desert shrubs, montane conifers and riparian deciduous trees under variable water regimes. We found a strong correlation (R = 0.85) between the maximum efficiency of photosystem II measured using variable fluorescence (Fv'Fm') and leaf level electrolyte leakage, a proximal cause of drought stress induced by cellular damage in leaves. This association was confirmed in two gymnosperm species (Picea engelmannii and Pinus contorta) and for diverse varieties of the crop species Brassica rapa. The use of chlorophyll a fluorescence per image also allowed for early detection of drought in aspen (Populus tremuloides). These results provide evidence that variable chlorophyll fluorescence decreases between 25% and 70% in mild and severely droughted twigs with respect to ones collected from trees in wet soil conditions. While current systems for monitoring variable fluorescence

  4. 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

  5. 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.

  6. Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

    NASA Astrophysics Data System (ADS)

    Sheffield, J.; Lobell, D. B.; Wood, E. F.

    2010-12-01

    Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

  7. 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.

  8. 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.

  9. Lessons Learned from Monitoring Drought in Data Sparse Regions in the United States

    NASA Astrophysics Data System (ADS)

    Edwards, L. M.; Redmond, K. T.

    2011-12-01

    Drought monitoring in the geographic domain represented by the Western Regional Climate Center (WRCC) in the United States can serve as an example of many of the challenges that face a global drought early warning system (GDEWS). The WRCC area includes numerous climate regions, such as: the Pacific coast of the continental U.S., the lowest elevation in North America, arid and alpine environments, temperate rainforest, Alaska, Hawaii and the Pacific territories of the U.S. in the tropics. This area is quite diverse in its climatological regimes, from rainforest to high desert to tundra, and covers a large area of land and water. Drought in the WRCC domain affects a wide range of constituents and interests, and the complex interplay between "human-caused" and natural drought cannot be understated. Data to support a GDEWS, as in the WRCC region, is often non-existent or unreliable in remote locations. Even in the continental U.S., data is not as dense as the topography and climate zones demand for accurate drought assessment. Challenges and efforts to address drought monitoring at the WRCC will be presented.

  10. 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

  11. Monitoring and forecasting the 2009-2010 severe drought in Southwest China

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Tang, Q.; Liu, X.; Leng, G.; Li, Z.; Cui, H.

    2015-12-01

    From the fall of 2009 to the spring of 2010, an unprecedented drought swept across southwest China (SW) and led to a severe shortage in drinking water and a huge loss to regional economy. Monitoring and predicting the severe drought with several months in advance is of critical importance for such hydrological disaster assessment, preparation and mitigation. In this study, we attempted to carry out a model-based hydrological monitoring and seasonal forecasting framework, and assessed its skill in capturing the evolution of the SW drought in 2009-2010. Using the satellite-based meteorological forcings and the Variable Infiltration Capacity (VIC) hydrologic model, the drought conditions were assessed in a near-real-time manner based on a 62-year (1952-2013) retrospective simulation, wherein the satellite data was adjusted by a gauge-based forcing to remove systematic biases. Bias-corrected seasonal forecasting outputs from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) was tentatively applied for a seasonal hydrologic prediction and its predictive skill was overall evaluated relative to a traditional Ensemble Streamflow Prediction (ESP) method with lead time varying from 1 to 6 months. The results show that the climate model-driven hydrologic predictability is generally limited to 1-month lead time and exhibits negligible skill improvement relative to ESP during this drought event, suggesting the initial hydrologic conditions (IHCs) play a dominant role in forecasting performance. The research highlights the value of the framework in providing accurate IHCs in a real-time manner which will greatly benefit drought early-warning.

  12. G-REALM: A lake/reservoir monitoring tool for drought monitoring and water resources management.

    NASA Astrophysics Data System (ADS)

    Birkett, C. M.; Ricko, M.; Beckley, B. D.; Yang, X.; Tetrault, R. L.

    2017-12-01

    G-REALM is a NASA/USDA funded operational program offering water-level products for lakes and reservoirs and these are currently derived from the NASA/CNES Topex/Jason series of satellite radar altimeters. The main stakeholder is the USDA/Foreign Agricultural Service (FAS) though many other end-users utilize the products for a variety of interdisciplinary science and operational programs. The FAS utilize the products within their CropExplorer Decision Support System (DSS) to help assess irrigation potential, and to monitor both short-term (agricultural) and longer-term (hydrological) drought conditions. There is increasing demand for a more global monitoring service that in particular, captures the variations in the smallest (1 to 100km2) reservoirs and water holdings in arid and semi-arid regions. Here, water resources are critical to both agriculture and regional security. A recent G-REALM 10-day resolution product upgrade and expansion has allowed for more accurate lake level products to be released and for a greater number of water bodies to be monitored. The next program phase focuses on the exploration of the enhanced radar altimeter data sets from the Cryosat-2 and Sentinel-3 missions with their improved spatial resolution, and the expansion of the system to the monitoring of 1,000 water bodies across the globe. In addition, a new element, the monitoring of surface water levels in wetland zones, is also being introduced. This aims to satisfy research and stakeholder requirements with respect to programs examining the links between inland fisheries catch potential and declining water levels, and to those monitoring the delicate balance between water resources, agriculture, and fisheries management in arid basins.

  13. Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach

    Treesearch

    Steve Norman; Frank H. Koch; William W. Hargrove

    2016-01-01

    Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts  can be inferred from moisture deficits quantified using precipitation and temperature measurements. However,...

  14. Drought Monitoring and Forecasting Using the Princeton/U Washington National Hydrologic Forecasting System

    NASA Astrophysics Data System (ADS)

    Wood, E. F.; Yuan, X.; Roundy, J. K.; Lettenmaier, D. P.; Mo, K. C.; Xia, Y.; Ek, M. B.

    2011-12-01

    Extreme hydrologic events in the form of droughts or floods are a significant source of social and economic damage in many parts of the world. Having sufficient warning of extreme events allows managers to prepare for and reduce the severity of their impacts. A hydrologic forecast system can give seasonal predictions that can be used by mangers to make better decisions; however there is still much uncertainty associated with such a system. Therefore it is important to understand the forecast skill of the system before transitioning to operational usage. Seasonal reforecasts (1982 - 2010) from the NCEP Climate Forecast System (both version 1 (CFS) and version 2 (CFSv2), Climate Prediction Center (CPC) outlooks and the European Seasonal Interannual Prediction (EUROSIP) system, are assessed for forecasting skill in drought prediction across the U.S., both singularly and as a multi-model system The Princeton/U Washington national hydrologic monitoring and forecast system is being implemented at NCEP/EMC via their Climate Test Bed as the experimental hydrological forecast system to support U.S. operational drought prediction. Using our system, the seasonal forecasts are biased corrected, downscaled and used to drive the Variable Infiltration Capacity (VIC) land surface model to give seasonal forecasts of hydrologic variables with lead times of up to six months. Results are presented for a number of events, with particular focus on the Apalachicola-Chattahoochee-Flint (ACF) River Basin in the South Eastern United States, which has experienced a number of severe droughts in recent years and is a pilot study basin for the National Integrated Drought Information System (NIDIS). The performance of the VIC land surface model is evaluated using observational forcing when compared to observed streamflow. The effectiveness of the forecast system to predict streamflow and soil moisture is evaluated when compared with observed streamflow and modeled soil moisture driven by

  15. 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.

  16. Monitoring 2015 drought in West Java using Normalized Difference Water Index (NDWI)

    NASA Astrophysics Data System (ADS)

    Febrina Amalo, Luisa; Ma’rufah, Ummu; Ayu Permatasari, Prita

    2018-05-01

    Drought is a slow developing phenomenon that accumulates over period and affecting various sectors. It is one of natural hazards that occurs each year, particularly in Indonesia over Australian Monsoon period. During drought event, vegetation’s cover can be affected by water stress. Normalized Difference Water Index (NDWI) is a method for water resource assessment and known to be strongly related to the plant water content. NDWI is produced from MODIS bands Near-infrared (NIR) and Short Wave Infrared (SWIR). This research aims to monitor drought using NDWI in West Java during El Niño 2015 and its impact on rainfall variability. The result showed rainfall was decreased significantly starting from May-June, then increased in November. According to NDWI, it also showed that mostly West Java Region affected by drought during May-November. Very strong drought occurred on September-November. On December, areal extent of drought was decreasing significantly because rainfall had increased during November. Generally, areal extent of drought in West Java was dominated by strong and moderate drought. It implied that El Niño 2015, give great impact on increasing drought and decreasing rainfall in West Java. NDWI can be detected drought occurrence as it have good correlation with rainfall spatially.

  17. Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

    NASA Astrophysics Data System (ADS)

    El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

    2012-12-01

    The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary

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

    USGS Publications Warehouse

    Tadesse, T.; Haile, M.; Senay, G.; Wardlow, B.D.; Knutson, C.L.

    2008-01-01

    Reducing the impact of drought and famine remains a challenge in sub-Saharan Africa despite ongoing drought relief assistance in recent decades. This is because drought and famine are primarily addressed through a crisis management approach when a disaster occurs, rather than stressing preparedness and risk management. Moreover, drought planning and food security efforts have been hampered by a lack of integrated drought monitoring tools, inadequate early warning systems (EWS), and insufficient information flow within and between levels of government in many sub-Saharan countries. The integration of existing drought monitoring tools for sub-Saharan Africa is essential for improving food security systems to reduce the impacts of drought and famine on society in this region. A proactive approach emphasizing integration requires the collective use of multiple tools, which can be used to detect trends in food availability and provide early indicators at local, national, and regional scales on the likely occurrence of food crises. In addition, improving the ability to monitor and disseminate critical drought-related information using available modern technologies (e.g., satellites, computers, and modern communication techniques) may help trigger timely and appropriate preventive responses and, ultimately, contribute to food security and sustainable development in sub-Saharan Africa. ?? 2008 United Nations.

  19. 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

  20. 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

  1. 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

  2. Monitoring and modeling agricultural drought for famine early warning (Invited)

    NASA Astrophysics Data System (ADS)

    Verdin, J. P.; Funk, C.; Budde, M. E.; Lietzow, R.; Senay, G. B.; Smith, R.; Pedreros, D.; Rowland, J.; Artan, G. A.; Husak, G. J.; Michaelsen, J.; Adoum, A.; Galu, G.; Magadzire, T.; Rodriguez, M.

    2009-12-01

    The Famine Early Warning Systems Network (FEWS NET) makes quantitative estimates of food insecure populations, and identifies the places and periods during which action must be taken to assist them. Subsistence agriculture and pastoralism are the predominant livelihood systems being monitored, and they are especially drought-sensitive. At the same time, conventional climate observation networks in developing countries are often sparse and late in reporting. Consequently, remote sensing has played a significant role since FEWS NET began in 1985. Initially there was heavy reliance on vegetation index imagery from AVHRR to identify anomalies in landscape greenness indicative of drought. In the latter part of the 1990s, satellite rainfall estimates added a second, independent basis for identification of drought. They are used to force crop water balance models for the principal rainfed staple crops in twenty FEWS NET countries. Such models reveal seasonal moisture deficits associated with yield reduction on a spatially continuous basis. In 2002, irrigated crops in southwest Asia became a concern, and prompted the implementation of a gridded energy balance model to simulate the seasonal mountain snow pack, the main source of irrigation water. MODIS land surface temperature data are also applied in these areas to directly estimate actual seasonal evapotranspiration on the irrigated lands. The approach reveals situations of reduced irrigation water supply and crop production due to drought. The availability of MODIS data after 2000 also brought renewed interest in vegetation index imagery. MODIS NDVI data have proven to be of high quality, thanks to significant spectral and spatial resolution improvements over AVHRR. They are vital to producing rapid harvest assessments for drought-impacted countries in Africa and Asia. The global food crisis that emerged in 2008 has led to expansion of FEWS NET monitoring to over 50 additional countries. Unlike previous practice, these

  3. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  4. Predicting US Drought Monitor (USDM) states using precipitation, soil moisture, and evapotranspiration anomalies, Part I: Development of a non-discrete USDM index

    USDA-ARS?s Scientific Manuscript database

    The U.S. Drought Monitor (USDM) classifies drought into five discrete dryness/drought categories based on expert synthesis of numerous data sources. In this study, an empirical methodology is presented for creating a non-discrete U.S. Drought Monitor (USDM) index that simultaneously 1) represents th...

  5. Measures of Groundwater Drought from the Long-term Monitoring Data in Korea

    NASA Astrophysics Data System (ADS)

    Chung, E.; Park, J.; Woo, N. C.

    2017-12-01

    Recently, drought has been increased in its severity and frequency along the climate change in Korea. There are several criteria for alarming drought, for instance, based on the no-rainfall days, the amount of stream discharge, and the water levels of reservoirs. However, farmers depending on groundwater still have been suffered in preparing drought especially in the Spring. No-rainfall days continue, groundwater exploitation increases, water table declines, stream discharge decreases, and then the effects of drought become serious. Thus, the drought index based on the groundwater level is needed for the preparedness of drought disaster. Palmer et al.(1965, USGS) has proposed a method to set the threshold for the decline of the groundwater level in 5 stages based on the daily water-level data over the last 30 years. In this study, according to Peters et al.(2003), the threshold of groundwater level was estimated using the daily water-level data at five sites with significant drought experiences in Korea. Water levels and precipitations data were obtained from the national groundwater monitoring wells and the automatic weather stations, respectively, for 10 years from 2005 to 2014. From the water-level changes, the threshold was calculated when the value of the drought criterion (c), the ratio of the deficit below the threshold to the deficit below the average, is 0.3. As a result, the monthly drought days were high in 2009 and 2011 in Uiryeong, and from 2005 to 2008 in Boeun. The validity of the approach and the threshold can be evaluated by comparing calculated monthly drought days with recorded drought in the past. Through groundwater drought research, it is expected that not only surface water also groundwater resource management should be implemented more efficiently to overcome drought disaster.

  6. Advancing drought monitoring using a Small Unmanned Aerial System (sUAS) in a changing climate

    NASA Astrophysics Data System (ADS)

    Ryu, J.

    2016-12-01

    Drought as a natural hazard, increasingly threatens the sustainability of regional water resources around the world. Given current trends in climate variability and change, droughts are likely to continue and increase. One of the effective ways to mitigate drought impacts may be to use a Small Unmanned Aerial System (sUAS) to improve understanding of the factors that drive the onset and development of drought conditions at local levels would enable planners and end users to more effectively manage and meter out limited water resources. During the presentation, the author will propose a methodological approach to apply sUAS for drought monitoring along with federal regulations and policies.

  7. Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

    NASA Astrophysics Data System (ADS)

    McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

    2011-12-01

    The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the

  8. 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

  9. Building a Framework in Improving Drought Monitoring and Early Warning Systems in Africa

    NASA Astrophysics Data System (ADS)

    Tadesse, T.; Wall, N.; Haigh, T.; Shiferaw, A. S.; Beyene, S.; Demisse, G. B.; Zaitchik, B.

    2015-12-01

    Decision makers need a basic understanding of the prediction models and products of hydro-climatic extremes and their suitability in time and space for strategic resource and development planning to develop mitigation and adaptation strategies. Advances in our ability to assess and predict climate extremes (e.g., droughts and floods) under evolving climate change suggest opportunity to improve management of climatic/hydrologic risk in agriculture and water resources. In the NASA funded project entitled, "Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa (GHA) under Evolving Climate Conditions to Support Adaptation Strategies," we are attempting to develop a framework that uses dialogue between managers and scientists on how to enhance the use of models' outputs and prediction products in the GHA as well as improve the delivery of this information in ways that can be easily utilized by managers. This process is expected to help our multidisciplinary research team obtain feedback on the models and forecast products. In addition, engaging decision makers is essential in evaluating the use of drought and flood prediction models and products for decision-making processes in drought and flood management. Through this study, we plan to assess information requirements to implement a robust Early Warning Systems (EWS) by engaging decision makers in the process. This participatory process could also help the existing EWSs in Africa and to develop new local and regional EWSs. In this presentation, we report the progress made in the past two years of the NASA project.

  10. 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

  11. 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

  12. Predicting the US Drought Monitor (USDM) using precipitation, soil noisture, and evapotranspiration anomalies, Part II: Intraseasonal drought intensification forecasts

    USDA-ARS?s Scientific Manuscript database

    Probabilistic forecasts of US Drought Monitor (USDM) intensification over two, four and eight week time periods are developed based on recent anomalies in precipitation, evapotranspiration and soil moisture. These statistical forecasts are computed using logistic regression with cross validation. Wh...

  13. Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery

    NASA Astrophysics Data System (ADS)

    Ozelkan, Emre; Chen, Gang; Ustundag, Burak Berk

    2016-02-01

    Drought is a rapidly rising environmental issue that can cause hardly repaired or unrepaired damages to the nature and socio-economy. This is especially true for a region that features arid/semi-arid climate, including the Turkey's most important agricultural district - Southeast Anatolia. In this area, we examined the uncertainties of applying Landsat 8 Operational Land Imager (OLI) NDVI data to estimate meteorological drought - Standardized Precipitation Index (SPI) - measured from 31 in-situ agro-meteorological monitoring stations during spring and summer of 2013 and 2014. Our analysis was designed to address two important, yet under-examined questions: (i) how does the co-existence of rainfed and irrigated agriculture affect remote sensing drought monitoring in an arid/semi-arid region? (ii) What is the role of spatial scale in drought monitoring using a GEOBIA (geographic object-based image analysis) framework? Results show that spatial scale exerted a higher impact on drought monitoring especially in the drier year 2013, during which small scales were found to outperform large scales in general. In addition, consideration of irrigated and rainfed areas separately ensured a better performance in drought analysis. Compared to the positive correlations between SPI and NDVI over the rainfed areas, negative correlations were determined over the irrigated agricultural areas. Finally, the time lag effect was evident in the study, i.e., strong correlations between spring SPI and summer NDVI in both 2013 and 2014. This reflects the fact that spring watering is crucial for the growth and yield of the major crops (i.e., winter wheat, barley and lentil) cultivated in the region.

  14. Toward Global Drought Early Warning Capability - Expanding International Cooperation for the Development of a Framework for Monitoring and Forecasting

    NASA Technical Reports Server (NTRS)

    Pozzi, Will; Sheffield, Justin; Stefanski, Robert; Cripe, Douglas; Pulwarty, Roger; Vogt, Jurgen V.; Heim, Richard R., Jr.; Brewer, Michael J.; Svoboda, Mark; Westerhoff, Rogier; hide

    2013-01-01

    Drought has had a significant impact on civilization throughout history in terms of reductions in agricultural productivity, potable water supply, and economic activity, and in extreme cases this has led to famine. Every continent has semiarid areas, which are especially vulnerable to drought. The Intergovernmental Panel on Climate Change has noted that average annual river runoff and water availability are projected to decrease by 10 percent-13 percent over some dry and semiarid regions in mid and low latitudes, increasing the frequency, intensity, and duration of drought, along with its associated impacts. The sheer magnitude of the problem demands efforts to reduce vulnerability to drought by moving away from the reactive, crisis management approach of the past toward a more proactive, risk management approach that is centered on reducing vulnerability to drought as much as possible while providing early warning of evolving drought conditions and possible impacts. Many countries, unfortunately, do not have adequate resources to provide early warning, but require outside support to provide the necessary early warning information for risk management. Furthermore, in an interconnected world, the need for information on a global scale is crucial for understanding the prospect of declines in agricultural productivity and associated impacts on food prices, food security, and potential for civil conflict. This paper highlights the recent progress made toward a Global Drought Early Warning Monitoring Framework (GDEWF), an underlying partnership and framework, along with its Global Drought Early Warning System (GDEWS), which is its interoperable information system, and the organizations that have begun working together to make it a reality. The GDEWF aims to improve existing regional and national drought monitoring and forecasting capabilities by adding a global component, facilitating continental monitoring and forecasting (where lacking), and improving these tools at

  15. Statistical analysis of long-term hydrologic records for selection of drought-monitoring sites on Long Island, New York

    USGS Publications Warehouse

    Busciolano, Ronald J.

    2005-01-01

    Ground water is the sole source of water supply for more than 3 million people on Long Island, New York. Large-scale ground-water pumpage, sewering systems, and prolonged periods of below-normal precipitation have lowered ground-water levels and decreased stream-discharge in western and central Long Island. No method is currently (2004) available on Long Island that can assess data from the ground-water-monitoring network to enable water managers and suppliers with the ability to give timely warning of severe water-level declines.This report (1) quantifies past drought- and human-induced changes in the ground-water system underlying Long Island by applying statistical and graphical methods to precipitation, stream-discharge, and ground-water-level data from selected monitoring sites; (2) evaluates the relation between water levels in the upper glacial aquifer and those in the underlying Magothy aquifer; (3) defines trends in stream discharge and ground-water levels that might indicate the onset of drought conditions or the effects of excessive pumping; and (4) discusses the long-term records that were used to select sites for a Long Island drought-monitoring network.Long Island’s long-term hydrologic records indicated that the available data provide a basis for development of a drought-monitoring network. The data from 36 stations that were selected as possible drought-monitoring sites—8 precipitation-monitoring stations, 8 streamflow-gaging (discharge) stations, 15 monitoring wells screened in the upper glacial aquifer under water-table (unconfined) conditions, and 5 monitoring wells screened in the underlying Magothy aquifer under semi-confined conditions—indicate that water levels in western parts of Long Island have fallen and risen markedly (more than 15 ft) in response to fluctuations in pumpage, and have declined from the increased use of sanitary- and storm-sewer systems. Water levels in the central and eastern parts, in contrast, remain relatively

  16. Droughts and floods monitoring in Poland with SMOS, SEVIRI and model data

    NASA Astrophysics Data System (ADS)

    Kotarba, A. Z.; Stankiewicz, K.; Słomiński, J.; Słomińska, E.; Marczewski, W.

    2012-04-01

    Droughts and floods represent the extreme cases of hydrological regime. Both significantly influence ecological processes in the environment as well as socio-economic situation of human activity. Measurements of soil moisture and rainfall is being recognized as fundamental for droughts and floods monitoring. We used Soil Moisture and Ocean Salinity (SMOS) L2 soil moisture data and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) rain rate approximation to evaluate the intensity and extend of droughts/floods events in Poland in 2010 and 2011. SEVIRI Multi-Sensor Precipitation Estimate rain rates were used for calculation of monthly rain accumulation (24 SEVIRI L2 datasets per day), then projected to match SMOS spatial reference. Based on SEVIRI data, monthly sum of precipitation was estimated for each SMOS DGG cell within area of interest (the ROI covers Poland and the closest neighborhood). At the DGG level, SMOS SM and SEVIRI precipitation data were compared for each month since May 2010. Nearly two year series provided a background for droughts and floods events. Final L3 products of SMOS SM and SEVIRI precipitation were compared with operational, traditionally-developed drought risk maps, in order to evaluate the degree of agreement between remotely sensed products and models calculated with surface-based measurements only.

  17. 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

  18. Drought monitoring of Tumen river basin wetlands between 1991 and 2016 using Landsat TM/ETM+

    NASA Astrophysics Data System (ADS)

    Yu, H.; Zhu, W.; Lee, W. K.; Heo, S.

    2017-12-01

    Wetlands area described as "the kidney of earth" owing to the importance of functions for stabilizing environment, long-term protection of water sources, as well as effectively minimize sediment loss, purify surface water from industrial and agricultural pollutants, and enhancing aquifer recharge. Drought monitoring in wetlands is vital due to the condition of water supply directly affecting the growth of wetland plants and local biodiversity. In this study, Vegetation Temperature Condition Index derived from Normalized Difference Vegetation Index and Land Surface Temperature is used to observe drought status from 1991 to 2016. For doing this, Landsat TM/ETM+ data for six periods are used to analytical processing. On the other hand, soil moisture maps which are acquired from CMA Land Data Assimilation System Version 1.0 for validating reliability of drought monitoring. As a result, the study shows most of area at normal moist level (decreased 25.8%) became slightly drought (increased 29.7%) in Tumen river basin cross-border (China and North Korea) wetland. The correlation between vegetation temperature condition index and soil moisture are 0.69, 0.32 and 0.2 for the layers of 0 5cm, 0 10cm, and 10 20cm, respectively. Although climate change probably contributes to the process of drought by decreasing precipitation and increasing temperature, human activities are shown as main factor that led to the process in this wetland.

  19. Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Rodell, Matt

    2007-01-01

    Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

  20. 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

  1. Use of climate information for drought risk management in Mexico

    NASA Astrophysics Data System (ADS)

    Neri, C.; Magaña Rueda, V.

    2013-05-01

    The occurrence of meteorological droughts in Mexico has brought to light the large vulnerability of the central-northern part of the country to water shortages. This region is facing current and future water shortages due to the increased demand of water from urban growth in addition to droughts. Assessing droughts requires considering long-term losses and side effects. However, governments generally invest little resources in the creation of drought risk reduction programs, even in regions where droughts have been documented in historical records, such as in the northern region of Mexico. It is not clear until now, what is our capacity to predict droughts on seasonal time scale, and even the Drought Monitor for North America not always reflect the severity of the condition at the regional level. An analysis of strategies that focus on droughts show that one of the principal limits in the management of drought risks and preventive decision making is the use of inadequate definitions of drought predictability. In addition, the means to communicate confidence in seasonal climate forecasts has inhibited the use of climate information in the planning of various socioeconomic activities. Although some sectors such as agriculture have programs to reduce the impacts of drought, their efforts have focused in providing subsidies to get along with dry conditions. In other words, there are no actions to reduce the potential impacts of drought. The characterization of the vulnerability of water user groups, particularly in Sonora as case of study, has been useful to identifying what type of climate information decision makers needed. This information will be included in a proposal of a drought early warming for Mexico. A key element in a drought early warming for Mexico 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

  2. [Simplification of crop shortage water index and its application in drought remote sensing monitoring].

    PubMed

    Liu, Anlin; Li, Xingmin; He, Yanbo; Deng, Fengdong

    2004-02-01

    Based on the principle of energy balance, the method for calculating latent evaporation was simplified, and hence, the construction of the drought remote sensing monitoring model of crop water shortage index was also simplified. Since the modified model involved fewer parameters and reduced computing times, it was more suitable for the operation running in the routine services. After collecting the concerned meteorological elements and the NOAA/AVHRR image data, the new model was applied to monitor the spring drought in Guanzhong, Shanxi Province. The results showed that the monitoring results from the new model, which also took more considerations of the effects of the ground coverage conditions and meteorological elements such as wind speed and the water pressure, were much better than the results from the model of vegetation water supply index. From the view of the computing times, service effects and monitoring results, the simplified crop water shortage index model was more suitable for practical use. In addition, the reasons of the abnormal results of CWSI > 1 in some regions in the case studies were also discussed in this paper.

  3. Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

    USGS Publications Warehouse

    Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

    2016-01-01

    Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

  4. Lessons Learned on Effective Co-production of Drought Science and Decision Support Tools with the Wind River Reservation Tribal Water Managers

    NASA Astrophysics Data System (ADS)

    McNeeley, S.; Ojima, D. S.; Beeton, T.

    2015-12-01

    The Wind River Reservation in west-central Wyoming is home of the Eastern Shoshone and Northern Arapaho Tribes. The reservation has experienced severe drought impacts on Tribal livelihoods and cultural activities in recent years. Scientists from the North Central Climate Science Center, the National Drought Mitigation Center, the High Plains Regional Climate Center, and multiple others are working in close partnership with the tribal water managers on a reservation-wide drought preparedness project that includes a technical assessment of drought risk, capacity building to train managers on drought and climate science and indicators, and drought planning. This talk will present project activities to date along with the valuable and transferrable lessons learned on effective co-production of actionable science for decision making in a tribal context.

  5. 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

  6. 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

  7. 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.

  8. Benchmarking the performance of a land data assimilation system for agricultural drought monitoring

    USDA-ARS?s Scientific Manuscript database

    The application of land data assimilation systems to operational agricultural drought monitoring requires the development of (at least) three separate system sub-components: 1) a retrieval model to invert satellite-derived observations into soil moisture estimates, 2) a prognostic soil water balance...

  9. A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.

    2016-08-01

    Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources

  10. 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

  11. 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.

  12. High Resolution Mapping of Drought Impacts on Small Waterbodies using Sentinel 1 SAR and Landsat Observations

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

    Drought in semi-arid areas can have substantial impact on ephemeral and small water bodies, which provide critical ecological habitat and have important socio-economic value. This is particularly true in the pastoral areas of East Africa, where these ecosystems provide local communities with water for human and animal consumption and pasture for livestock. However, monitoring the impact of drought on ephemeral and small water bodies in East Africa is challenging because of sparse in situ observational systems. Satellite remote sensing observations have been shown to be a viable option for monitoring surface water change in data-poor regions. Landsat data is widely used to detect open water, but the use of Landsat data in small waterbody studies is limited by its 30-meter spatial resolution. New remote sensing-based tools are necessary to better understand the vulnerability of ephemeral and small waterbodies in semi-arid areas to drought and to monitor drought impacts. This study combines Landsat and Sentinel 1 SAR observations to create a series of monthly waterbody maps over the Awash River basin in Ethiopia depicting the change in surface water from October 2014 to March 2017. The study time period corresponds with a major drought event in the area. Waterbody maps were generated using a 10-meter resolution and utilized to monitor drought impacts on ephemeral and small waterbodies in the Awash River basin over the course of the drought event. Initial results show that surface waterbodies in the lower catchments of the Awash basin were more severely impacted by the drought event than the upper catchments. It is anticipated that the new information provided by this tool will inform decisions affecting the water, energy, agriculture and other sectors in East Africa reliant on water resources, enabling water authorities to better manage future drought events.

  13. Bill Would Expand U.S. Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Zielinski, Sarah

    2006-05-01

    The collection and dissemination of drought information would be centralized within the U.S. National Oceanic and Atmospheric Administration (NOAA) under a newly proposed bill, which received support at a 4 May hearing before the U.S. House of Representatives Science Subcommittee on Environment, Technology, and Standards. The economic costs of drought average $6 to $8 billion each year in the United States, according to NOAA. The effects of prolonged drought include extreme wildfire conditions, water restrictions, and reduced crop yields.

  14. Water security and adaptive capacity for climate: Learning lessons from drought decision making in U.S. urban contexts

    NASA Astrophysics Data System (ADS)

    Dilling, L.

    2017-12-01

    Cities in the U.S. have been adapting to drought for many years, implementing a combination of mechanisms to cope with climate and water variability and increasing population. Cities are also at the frontline for making decisions about adaptation to climate change. Are decisions made to cope with drought helping cities to build the adaptive capacity necessary for adapting to climate change? We examined this question by conducting interviews with practitioners involved in drought management at urban water utilities across the U.S. to understand responses to drought and perceptions of their effectiveness. We then drew on established criteria for evaluating successful adaptation (effectiveness, efficiency, equity and legitimacy) to analyze whether these drought policies would build adaptive capacity for climate change. We find that drought responses overall are seen as successful in helping cities balance the demand and supply of water, and maintain system reliability as well as improve water awareness, but can have unintended consequences and shift vulnerability in unexpected ways. For example, even though cities are successful at reducing water use when needed, some are concerned with the increasing difficulty of finding new water savings during a future drought. Secondly, water conservation can affect revenue, impacting the ability of cities to plan for maintenance and capital costs. Third, the social acceptability of policy options is critical and depends on perceived fairness and other factors. Water managers are also challenged by "no fail" expectations that make it difficult to experiment. Moreover some measures can shift vulnerability from one risk, such as running out of water, to another risk, such as water becoming too expensive, lowering quality, or not meeting other key infrastructure design requirements. These findings demonstrate that adaptation measures that seek to reduce exposure to water scarcity can impact aspects of adaptive capacity, and shift

  15. Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

    NASA Astrophysics Data System (ADS)

    Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

    2017-12-01

    Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

  16. Modelling crop yield in Iberia under drought conditions

    NASA Astrophysics Data System (ADS)

    Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

    2017-04-01

    The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining

  17. Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

    USDA-ARS?s Scientific Manuscript database

    Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

  18. 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.

  19. Intricacies in Drought Management Policy, Crisis Response and Preparedness: Linking the Interface

    NASA Astrophysics Data System (ADS)

    Prakash, P.; Harter, T.

    2016-12-01

    Drought per se is often misrepresented as mere water scarcity issue overlooking the complexities associated with it. In many parts of the world, the drought management policy prescriptions are often driven by crisis management rather than preventive approach. As a result, the economic, social and environmental impact of droughts continues to increase even to this day. To overcome this calamity, nations should encourage coordinated effort at both national and regional scale. An integrated approach on open data sharing, technical advancement in monitoring and robust early warning system to deliver timely information to decision makers, drought projection through high performance mathematical model and effective impact assessment procedure, implementing proactive risk management measures and preparedness with effective emergency response programs plans, will certainly increase the likelihood of drought coping capabilities. The present study focuses on knowledge augmentation for better policy framework and action for all countries that suffer from droughts. A comprehensive database at the global scale has been compiled giving information on existing drought management policies/practices and the major challenges faced by major drought distressed countries. Plausible solution is suggested towards integrating the water management policy, response and preparedness, that has been garnered through the lessons from success/failure stories of nations with effective drought management policies

  20. Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

    NASA Astrophysics Data System (ADS)

    Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

    2018-02-01

    It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

  1. An Overview of the NOAA Drought Task Force

    NASA Technical Reports Server (NTRS)

    Schubert, S.; Mo, K.; Peters-Lidard, C.; Wood, A.

    2012-01-01

    The charge of the NOAA Drought Task Force is to coordinate and facilitate the various MAPP-funded research efforts with the overall goal of achieving significant advances in understanding and in the ability to monitor and predict drought over North America. In order to achieve this, the task force has developed a Drought Test-bed that individual research groups can use to test/evaluate methods and ideas. Central to this is a focus on three high profile North American droughts (1998-2004 western US drought, 2006-2007 SE US drought, 2011- current Tex-Mex drought) to facilitate collaboration among projects, including the development of metrics to assess the quality of monitoring and prediction products, and the development of an experimental drought monitoring and prediction system that incorporates and assesses recent advances. This talk will review the progress and plans of the task force, including efforts to help advance official national drought products, and the development of early warning systems by the National Integrated Drought Information System (NIDIS). Coordination with other relevant national and international efforts such as the emerging NMME capabilities and the international effort to develop a Global Drought Information System (GDIS) will be discussed.

  2. 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

  3. Drought Risk and Adaptation in the Interior (DRAI)

    NASA Astrophysics Data System (ADS)

    McNeeley, S.; Ojima, D. S.

    2013-12-01

    Drought is part of the normal climate variability in the Great Plains and Intermountain Western United States, but recent severe droughts along with climate change projections have increased the interest and need for better understanding of drought science and decision making. The purpose of this study is to understand how the U.S. Department of the Interior's (DOI) federal land and resource managers and their stakeholders (i.e., National Park Service, Bureau of Land Management, Fish and Wildlife Service, Bureau of Reclamation, Bureau of Indian Affairs and tribes, among others) are experiencing and dealing with drought in their landscapes. The Drought Risk and Adaptation in the Interior (DRAI) project is part of a new DOI-sponsored North Central Climate Science Center (NC CSC) crosscutting science initiative on drought across the Center's three foundational science areas: 1. physical climate, 2. ecosystems impacts and responses, and 3. human adaptation and decision making. The overarching goal is to learn more about drought within the DOI public lands and resource management in order to contribute to both the NC CSC regional science as well as providing managers and other decision makers with the most salient, credible, and legitimate research to support land and resource management decisions. Here we will present the project approach along with some initial insights learned from the research to date along with its utility for climate adaptation.

  4. Space-Derived Phenology, Retrieval and Use for Drought and Food Security Monitoring

    NASA Astrophysics Data System (ADS)

    Meroni, M.; Kayitakire, F.; Rembold, F.; Urbano, F.; Schucknecht, A.; LEO, O.

    2014-12-01

    Monitoring vegetation conditions is a critical activity for assessing food security in Africa. Rural populations relying on rain-fed agriculture and livestock grazing are highly exposed to large seasonal and inter-annual fluctuations in water availability. Monitoring the state, evolution, and productivity of vegetation, crops and pastures in particular, is important to conduct food emergency responses and plan for a long-term, resilient, development strategy in this area. The timing of onset, the duration, and the intensity of vegetation growth can be retrieved from space observations and used for food security monitoring to assess seasonal vegetation development and forecast the likely seasonal outcome when the season is ongoing. In this contribution we present a set of phenology-based remote sensing studies in support to food security analysis. Key phenological indicators are retrieved using a model-fit approach applied to SOPT-VEGETATION FAPAR time series. Remote-sensing phenology is first used to estimate i) the impact of the drought in the Horn of Africa, ii) crop yield in Tunisia and, iii) rangeland biomass production in Niger. Then the impact of the start and length of vegetation growing period on the total biomass production is assessed over the Sahel. Finally, a probabilistic approach using phenological information to forecast the occurrence of an end-of-season biomass production deficit is applied over the Sahel to map hot-spots of drought-related risk.

  5. A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

    NASA Technical Reports Server (NTRS)

    Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

    2018-01-01

    The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

  6. A Customized Drought Decision Support Tool for Hsinchu Science Park

    NASA Astrophysics Data System (ADS)

    Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

    2016-04-01

    Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

  7. Frequencies of decision making and monitoring in adaptive resource management

    PubMed Central

    Johnson, Fred A.

    2017-01-01

    Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management

  8. Frequencies of decision making and monitoring in adaptive resource management

    USGS Publications Warehouse

    Williams, Byron K.; Johnson, Fred A.

    2017-01-01

    Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management

  9. A Multimodel Global Drought Information System (GDIS) for Near Real-Time Monitoring of Surface Water Conditions (Invited)

    NASA Astrophysics Data System (ADS)

    Nijssen, B.

    2013-12-01

    While the absolute magnitude of economic losses associated with weather and climate disasters such as droughts is greatest in the developed world, the relative impact is much larger in the developing world, where agriculture typically constitutes a much larger percentage of the labor force and food insecurity is a major concern. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited and long-term records of soil moisture are essentially non-existent globally The problem is particularly critical given that many of the most damaging droughts occur in parts of the world that are most deficient in terms of in situ precipitation observations. In recent years, a number of near real-time drought monitoring systems have been developed with regional or global extent. While direct observations of key variables such as moisture storage are missing, the evolution of land surface models that are globally applicable provides a means of reconstructing them. The implementation of a multi-model drought monitoring system is described, which provides near real-time estimates of surface moisture storage for the global land areas between 50S and 50N with a time lag of about one day. Near real-time forcings are derived from satellite-based precipitation estimates and modeled air temperatures. The system is distinguished from other operational systems in that it uses multiple land surface models to simulate surface moisture storage, which are then combined to derive a multi-model estimate of drought. Previous work has shown that while land surface models agree in broad context, particularly in terms of soil moisture percentiles, important differences remain, which motivates a multi-model ensemble approach. The system is an extension of similar systems developed by at the University of Washington for the Pacific Northwest and for the United States, but global application of the protocols used in the U

  10. The 2005 and 2012 major drought events in Iberia: monitoring vegetation dynamics and crop yields using satellite data.

    NASA Astrophysics Data System (ADS)

    Gouveia, Célia M.; Trigo, Ricardo M.

    2014-05-01

    The Iberian Peninsula is recurrently affected by drought episodes and therefore by the adverse effects associated that range from severe water shortages to economic losses and related social impacts. During the hydrological years of 2004/2005 and 2011/2012, Iberia was hit by two of the worst drought episodes ever recording in this semi-arid region (Garcia-Herrera at al., 2007; Trigo et al., 2013). These two drought episodes were extreme in both its magnitude and spatial extent. A tendency towards a drier Mediterranean for the period 1970-2010 in comparison with 1901-70 has been identified (Hoerling et al., 2012), reinforcing the need for a continuous monitoring of vegetation stress and reliable estimates of the drought impacts. The strong effect of water scarcity on vegetation dynamics is well documented in Mediterranean and other semi-arid regions. Despite the usual link established between the decrease of vegetation greenness and the lack of precipitation during a considerably long period, the impact on vegetation activity may be amplified by other climatic anomalies, such as high temperature, high wind, and low relative humidity. The recent availability of consistent satellite imagery covering large regions over long periods of time has progressively reinforced the role of remote sensing in environmental studies, in particular in those related to drought episodes (e.g. Gouveia et al., 2009). The aim of the present work is to assess and monitor the cumulative impact over time of drought conditions on vegetation over Iberian Peninsula. For this purpose we have used the regional fields of the Normalized Difference Vegetation Index (NDVI) as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2013. The entire 15-yr long period was analysed, but particular attention was devoted to the two extreme drought episodes of 2004-2005 and 2011-2012. During the hydrological years of 2004-2005 and 2011-2012 drought episodes negative anomalies of NDVI were observed over

  11. The Lifecycles of Drought: Informing Responses Across Timescales

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.; Schubert, S. D.

    2014-12-01

    Drought is a slow-onset hazard that is a normal part of climate. Drought onset and demise are difficult to determine. Impacts are mostly nonstructural, spread over large geographical areas, and can persist long after precipitation deficits end. These factors hinder development of accurate, timely estimates of drought severity and resultant responses. Drivers of drought range from SST anomalies and global scale atmospheric response, through regional forcing and local land-surface feedbacks. Key climatological questions related to drought risk assessment, perception and management include, "Does a drought end by a return to normal precipitation; how much moisture is required and over what period; can the end of a drought be defined by the diminishing impacts e.g. soil moisture, reservoir volumes; will precipitation patterns on which management systems rely, change in the future?" Effective early warning systems inform strategic responses that anticipate crises and crisis evolution across climate timescales. While such "early information" is critical for defining event onset, it is even more critical for identifying the potential for increases in severity. Many social and economic systems have buffers in place to respond to onset (storage, transfers and purchase of grain) but lack response capabilities as drought intensifies, as buffers are depleted. Throughout the drought lifecycle (and between events), monitoring, research and risk assessments are required to: Map decision-making processes and resource capabilities including degradation of water and ecosystems Place multiple climate and land surface indicators within a consistent triggering framework (e.g. climate and vegetation mapping) before critical thresholds are reached Identify policies and practices that impede or enable the flow of information, through policy gaming and other exercises The presentation will outline the capabilities and framework needed to ensure improved scientific inputs to preparedness

  12. 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.

  13. 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.

  14. 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.

  15. A quasi-global precipitation time series for drought monitoring

    USGS Publications Warehouse

    Funk, Chris C.; Peterson, Pete J.; Landsfeld, Martin F.; Pedreros, Diego H.; Verdin, James P.; Rowland, James D.; Romero, Bo E.; Husak, Gregory J.; Michaelsen, Joel C.; Verdin, Andrew P.

    2014-01-01

    Estimating precipitation variations in space and time is an important aspect of drought early warning and environmental monitoring. An evolving drier-than-normal season must be placed in historical context so that the severity of rainfall deficits may quickly be evaluated. To this end, scientists at the U.S. Geological Survey Earth Resources Observation and Science Center, working closely with collaborators at the University of California, Santa Barbara Climate Hazards Group, have developed a quasi-global (50°S–50°N, 180°E–180°W), 0.05° resolution, 1981 to near-present gridded precipitation time series: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data archive.

  16. Futuragua: Fostering Cross-Scale Knowledge to Inform Social-Environmental Decision Processes for Building Drought Resilience in Highly Seasonal Environments

    NASA Astrophysics Data System (ADS)

    McDaniels, T.; Steyn, D. G.; Johnson, M. S.; Small, M.; Leclerc, G.; Vignola, R.; Chan, K.; Grossmann, I.; Wong-Parodi, G.

    2014-12-01

    Improving resilience to drought in complex social-environmental systems (SES) is extraordinarily important, particularly for rural tropical locations where small changes in climate regimes can have dramatic SES impacts. Efforts to build drought resilience must necessarily be planned and implemented within SES governance systems that involve linkages in water and land use administration from local to national levels. These efforts require knowledge and understanding that links climate and weather forecasts to regional and local hydrology, to social-economic and environmental systems, and to governance processes. In order to provide structure for such complex choices and investments, we argue that a focus on structured decision processes that involve linkages among science, technological perspectives, and public values conducted with agencies and stakeholders will provide a crucial framework for comparing and building insight for pursuing alternative courses of action to build drought resilience. This paper focuses on a regional case study in the seasonally-dry northwest region of Costa Rica, in watersheds rated as most threatened in the country in terms of drought. We present the overall framework guiding the transdisciplinary efforts to link scientific and technical understanding to public values, in order to foster civil society actions that lead to improved drought resilience. Initial efforts to characterize hydrological and climate regimes will be reported along with our approach to linking natural science findings, social inventories in terms of perspectives on SES, and the psychology and patterns of reliance on forecast information that provide the basis for characterizing public understanding. The overall linkage of technical and value information is focused on creating and comparing alternative actions that can potentially build resilience in short and long time frames by building decision making processes involving stakeholders, agencies and interested

  17. Developing a user-friendly Drought Monitoring and Forecasting Tool for Doctors without Borders

    NASA Astrophysics Data System (ADS)

    Enenkel, Markus

    2015-04-01

    Humanitarian aid organizations that focus on drought-related emergency response and disaster preparedness need to take decisions under high uncertainty. Satellite-derived and modelled information can help to decrease this uncertainty. However, in order to benefit from the provided knowledge it is crucial to adapt datasets and tools to actual user requirements and existing organizational capacities. Furthermore, socio-economic vulnerabilities (e. g. current rates of malnutrition) and coping capacities (e. g. access to drought-resistant seeds) of the affected population need to be assessed to link environmental conditions (drought risk) to potential impacts (food insecurity). Forecasts with lead times up to several months are desirable from a logistic point of view, but naturally less accurate than short-term predictions. As a consequence, careful calibration is required to identify and balance forecasts with an acceptable accuracy and the risk of possible false alarms. Therefore, we calibrate modelled predictions of rainfall, temperature and soil moisture via satellite-derived observations. Field tests with Doctors without Borders in Ethiopia help to define critical thresholds, to interpret the information under real conditions and to collect the necessary additional socio-economic data via a smartphone app. The final risk maps need to be visualized in a way that is easy to interpret, but not oversimplified.

  18. Droughts in Georgia

    USGS Publications Warehouse

    Barber, Nancy L.; Stamey, Timothy C.

    2000-01-01

    Droughts do not have the immediate effects of floods, but sustained droughts can cause economic stress throughout the State. The word 'drought' has various meanings, depending on a person's perspective. To a farmer, a drought is a period of moisture deficiency that affects the crops under cultivation - even two weeks without rainfall can stress many crops during certain periods of the growing cycle. To a meteorologist, a drought is a prolonged period when precipitation is less than normal. To a water manager, a drought is a deficiency in water supply that affects water availability and water quality. To a hydrologist, a drought is an extended period of decreased precipitation and streamflow. Droughts in Georgia have severely affected municipal and industrial water supplies, agriculture, stream water quality, recreation at major reservoirs, hydropower generation, navigation, and forest resources. In Georgia, droughts have been documented at U.S. Geological Survey (USGS) streamflow gaging stations since the 1890's. From 1910 to 1940, about 20 streamflow gaging stations were in operation. Since the early 1950's through the late 1980's, about 100 streamflow gaging stations were in operation. Currently (2000), the USGS streamflow gaging network consists of more than 135 continuous-recording gages. Ground-water levels are currently monitored at 165 wells equipped with continuous recorders.

  19. 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.

  20. 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.

  1. A global drought monitoring system: insights of an approach integrating remote sensing data and vulnerability to food insecurity

    NASA Astrophysics Data System (ADS)

    Angeluccetti, Irene; Perez, Francesca; Cámaro, Walther; Demarchi, Alessandro

    2015-04-01

    Early Warning Systems (EWS) for drought are currently underdeveloped compared to those related to other natural hazards. Both forecasting and monitoring of drought events are still posing challenges to the scientific community. In fact, the multifaceted nature of drought (i.e. hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. Similarly, drought impacts are various and complex thus difficult to be univocally measured. In the present study an approach for monitoring drought in near-real time and for estimating its impacts is presented. The EWS developed runs on a global extent and is mainly based on the early detection and monitoring of vegetation stress. On the one hand the monitoring of vegetation phenological parameters, whose extraction is based on the analysis of the MODIS-derived NDVI function, allows the fortnightly assessment of the vegetation productivity which could be expected at the end of the growing season. On the other hand, the Standardized Precipitation Index (SPI), calculated adapting TRMM-derived precipitation data in a selected distribution is used, before the growing season start, in order to early detect meteorological conditions which could give rise to vegetation stress events. During the growing season the SPI is used as check information for vegetation conditions. The relationships between rainfall and vegetation dynamics have been statistically analyzed considering different types of vegetation, in order to identify the most suitable rainfall cumulating interval to be used for the proposed monitoring procedures in different areas. A simplified vulnerability model, coupled with the above-mentioned hazard data, returns food security conditions, i.e. the estimated impacts over an investigated area. The model includes a set of agricultural indicators that accounts for the diversity of cultivated crops, the percentage of irrigated area and the suitability of

  2. 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

    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).

  3. 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

    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.

  4. Monitoring And Modeling Environmental Water Quality To Support Environmental Water Purchase Decision-making

    NASA Astrophysics Data System (ADS)

    Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.

    2016-12-01

    More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.

  5. 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

  6. Hydrological extremes in the media: The 2015 drought event in Germany

    NASA Astrophysics Data System (ADS)

    Zink, Matthias; Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Mai, Juliane; Schäfer, David; Marx, Andreas

    2017-04-01

    The 2003 drought event had major implications on many societal sectors, including energy production, health, forestry and agriculture. The reduced availability of water accompanied by high temperatures led to substantial economic losses in Germany on the order of 1.5 Billion Euros, in agriculture alone. Furthermore, soil droughts have considerable impacts on ecosystems, forest fires and water management. In 2015, another drought event impacted Germany which had impacts on inland navigation, forest fire risk and agriculture among others. Due to this drought event, corn yield reduced by 22% compared to the preceding 5 years. This drought event was tracked by the 2014 implemented German Drought Monitor, a near real-time, online soil water monitoring platform (Zink et al., 2016). This platform uses an high resolution, operational modeling system which delivers easy to understand maps of soil drought conditions that are published on a daily basis on www.ufz.de/droughtmonitor. During the 2015 event, the German Drought Monitor was used by several regional to national newspapers as well as by television to inform the public about the recent status of soil moisture conditions. Next to publishing the drought maps, we were asked to comment the drought development and especially the severity of the ongoing drought event. On the one hand, this gave us the opportunity to inform the public about different types and the characterization of droughts. On the other hand, some journalists just tried to invoke statements such as "this is the most severe drought event ever recorded" to get a good headline. Further the secondmost pressing question of the journalists was, if the current event could be directly attributed to climate change. A clear answer to this question could not be given since the drought monitor is based on only a 65 year period of data. Depending on the media company, different depths of information and knowledge was finally transferred to the newsletter article and

  7. 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

  8. Steady-state chlorophyll fluorescence (Fs) as a tool to monitor plant heat and drought stress

    NASA Astrophysics Data System (ADS)

    Cendrero Mateo, M.; Carmo-Silva, A.; Salvucci, M.; Moran, S. M.; Hernandez, M.

    2012-12-01

    Crop yield decreases when photosynthesis is limited by heat or drought conditions. Yet farmers do not monitor crop photosynthesis because it is difficult to measure at the field scale in real time. Steady-state chlorophyll fluorescence (Fs) can be used at the field level as an indirect measure of photosynthetic activity in both healthy and physiologically-perturbed vegetation. In addition, Fs can be measured by satellite-based sensors on a regular basis over large agricultural regions. In this study, plants of Camelina sativa grown under controlled conditions were subjected to heat and drought stress. Gas exchange and Fs were measured simultaneously with a portable photosynthesis system under light limiting and saturating conditions. Results showed that Fs was directly correlated with net CO2 assimilation (A) and inversely correlated with non-photochemical quenching (NPQ). Analysis of the relationship between Fs and Photosynthetically Active Radiation (PAR) revealed significant differences between control and stressed plants that could be used to track the status, resilience, and recovery of photochemical processes. In summary, the results provide evidence that Fs measurements, even without normalization, are an easy means to monitor changes in plant photosynthesis, and therefore, provide a rapid assessment of plant stress to guide farmers in resource applications. Figure1. Net CO2 assimilation rate (A) of Camelina sativa plants under control conditions and after heat stress exposure for 1 or 3 days (1d-HS and 3d-HS, respectively) (right) and control, drought and re-watering conditions (left). Conditions for infra-red gas analysis were: reference CO2 = 380 μmol mol-1, PPFD = 500 μmol m-2 s-1 and Tleaf set to 25°C (control, drought and re-water) or 35°C (HS). Different letters denote significant differences at the α=0.05 level. Values are means±SEM (n=10). Figure 2. Stable chlorophyll fluorescence (Fs) of Camelina sativa plants under control conditions and

  9. Linking meteorological drivers of spring-summer drought regimes to agricultural drought risk in China

    NASA Astrophysics Data System (ADS)

    Dai, L.; Wright, J. S.; Yu, C.; Huang, W. Y.

    2017-12-01

    As a drought prone country, China has experienced frequent severe droughts in recent decades. Drought frequency and severity are projected to increase in China under climate change. An understanding of the physical processes that contribute to extreme droughts is essential for seasonal forecasting, but the dominant physical mechanisms responsible for droughts in most parts of China are still unclear. Moreover, despite numerous studies on droughts in China, there are few clear connections between the meteorological and climatological drivers of extreme droughts and the associated agricultural consequences. This knowledge gap limits the capacity for decision-making support in drought management. The objectives of this study are (1) to identify robust spring-summer drought regimes over China, (2) to investigate the physical mechanisms associated with each regime, and (3) to better clarify connections between meteorological drought regimes and agricultural drought risk. First, we identify six drought regimes over China by applying an area-weighted k-means clustering technique to spatial patterns of spring-summer Standardized Precipitation Index (SPI) obtained from the ten-member ERA-20CM ensemble for 1900-2010. Second, we project these drought regimes onto agricultural drought risk maps for the three major cereal crops (rice, maize, and wheat) in China. Taking into account historical harvest areas for these crops, we then evaluate the potential impact of each drought regime on agricultural production. Third, the physical mechanisms and meteorological context behind each drought regimes are investigated based on monthly outputs from ERA20CM. We analyze the preceding and concurrent atmospheric circulation anomalies associated with each regime, and propose mechanistic explanations for drought development. This work provides a new perspective on diagnosing the physical mechanisms behind seasonal droughts, and lays a foundation for improving seasonal drought prediction and

  10. Drought and coastal ecosystems: an assessment of decision maker needs for information

    Treesearch

    Kirsten Lackstrom; Amanda Brennan; Kirstin Dow

    2016-01-01

    The National Integrated Drought Information System (NIDIS) is in the process of developing drought early warning systems in areas of the U.S. where the development and coordination of drought information is needed. In summer 2012, NIDIS launched a pilot program in North and South Carolina, addressing the uniqueness of drought impacts on coastal ecosystems.

  11. Characterization of drought patterns through remote sensing over The Chihuahua Desert, Mexico"

    NASA Astrophysics Data System (ADS)

    Madrigal, J. M.; Lopez, A.; Garatuza, J.

    2013-12-01

    Drought is a phenomenon that has intensified during the last few decades in the arid and semi-arid zones of northern Mexico. In the Chihuahua desert, across Chihuahua, Durango and Coahuila states has caused loss of food sustainability (agriculture, livestock), an increase in human health problems, and detriment of ecosystem services as well as important economic losses. In order to understand this phenomenon, it is necessary to create tools that allow monitoring the territory's spatial heterogeneity and multi-temporality. With this purpose we propose the implementation of a drought model which includes the traditional indexes of climatic drought, such as the Palmer Drought Severity Index PDSI, the Standardized Index of Rainfall SPI, data from meteorological stations and biophysical variations obtained from the MODIS sensors product MOD13 NDVI from 2001 to 2010, as well as biophysical variables characteristic of the environment, such as land use and vegetation coverage, Eco-regions, soil moisture, digital elevation model and irrigate agriculture districts. With the MODIS images, a spatially coherent time series was created analyzing the study area's phenology (TIMESAT) created the Seasonal Greenness (SG) and Start of Season Anomaly (SOSA) for the mentioned nine years. Through this, the annual cycles were established. With a decision tree model, all the previously mentioned proposed variables were integrated. The proposed model produces a general map which characterizes the vegetation condition (extreme drought, severe drought, moderate drought, near normal). Even though different techniques have been proposed on the monitoring of droughts, most of them generate drought indexes with a spatial resolution of 1km (Wardlow, B. et. al 2008; Levent T. et al. 2013). One of the main concerns of researchers on the matter is on improving the spatial information content and on having a better representation of the phenomenon. We use the normalized difference vegetation index

  12. Droughts and water scarcity: facing challenges

    NASA Astrophysics Data System (ADS)

    Pereira, Luis S.

    2014-05-01

    Water scarcity characterizes large portions of the world, particularly the Mediterranean area. It is due to natural causes - climate aridity, which is permanent, and droughts, that are temporary - and to human causes - long term desertification and short term water shortages. Droughts aggravate water scarcity. Knowledge has well developed relative to all processes but management tools still are insufficient as well as the tools required to support appropriate planning and management. Particularly, new approaches on tools for assessing related impacts in agriculture and other economic and social activities are required. Droughts occur in all climates but their characteristics largely differ among regions both in terms frequency, duration and intensity. Research has already produced a large number of tools that allow appropriate monitoring of droughts occurrence and intensity, including dynamics of drought occurrence and time evolution. Advances in drought prediction already are available but we still are far from knowing when a drought will start, how it will evolve and when it dissipates. New developments using teleconnections and GCM are being considered. Climate change is a fact. Are droughts occurrence and severity changing with global change? Opinions are divided about this subject since driving factors and processes are varied and tools for the corresponding analysis are also various. Particularly, weather data series are often too short for obtaining appropriate answers. In a domain where research is producing improved knowledge and innovative approaches, research faces however a variety of challenges. The main ones, dealt in this keynote, refer to concepts and definitions, use of monitoring indices, prediction of drought initiation and evolution, improved assessment of drought impacts, and possible influence of climate change on drought occurrence and severity.

  13. Monitoring Transcriptomic Changes in Soil-Grown Roots and Shoots of Arabidopsis thaliana Subjected to a Progressive Drought Stress.

    PubMed

    Bashir, Khurram; Rasheed, Sultana; Matsui, Akihiro; Iida, Kei; Tanaka, Maho; Seki, Motoaki

    2018-01-01

    Numerous experiments have been performed in Arabidopsis to monitor changes in gene expression that occur in response to a variety of abiotic and biotic stresses, different growth conditions, and at various developmental stages. In addition, gene expression patterns have also been characterized among wild-type and mutant genotypes. Despite these numerous reports, transcriptional changes occurring in roots of soil-grown plants subjected to a progressive drought stress have remained undocumented. To fill this gap, we established a system that allows one to establish water-deficit conditions and to collect root and shoot samples with minimal damage to the root system. Arabidopsis plants are grown in a ceramic-based granular soil and subjected to progressive drought stress by withholding water. Root and shoot samples were collected separately, RNA was purified, and a microarray analysis of drought-stressed roots and shoots was performed at 0, 1, 3, 5, 7, and 9 days after the onset of drought stress treatment. Here, we describe the detailed protocol used to analyze the transcriptomic changes occurring in roots and shoots of soil-grown Arabidopsis subjected to a progressive drought stress.

  14. USGS integrated drought science

    USGS Publications Warehouse

    Ostroff, Andrea C.; Muhlfeld, Clint C.; Lambert, Patrick M.; Booth, Nathaniel L.; Carter, Shawn L.; Stoker, Jason M.; Focazio, Michael J.

    2017-06-05

    Project Need and OverviewDrought poses a serious threat to the resilience of human communities and ecosystems in the United States (Easterling and others, 2000). Over the past several years, many regions have experienced extreme drought conditions, fueled by prolonged periods of reduced precipitation and exceptionally warm temperatures. Extreme drought has far-reaching impacts on water supplies, ecosystems, agricultural production, critical infrastructure, energy costs, human health, and local economies (Milly and others, 2005; Wihlite, 2005; Vörösmarty and others, 2010; Choat and others, 2012; Ledger and others, 2013). As global temperatures continue to increase, the frequency, severity, extent, and duration of droughts are expected to increase across North America, affecting both humans and natural ecosystems (Parry and others, 2007).The U.S. Geological Survey (USGS) has a long, proven history of delivering science and tools to help decision-makers manage and mitigate effects of drought. That said, there is substantial capacity for improved integration and coordination in the ways that the USGS provides drought science. A USGS Drought Team was formed in August 2016 to work across USGS Mission Areas to identify current USGS drought-related research and core capabilities. This information has been used to initiate the development of an integrated science effort that will bring the full USGS capacity to bear on this national crisis.

  15. 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

  16. Results of Large Area Crop Inventory Experiment (LACIE) drought analysis (South Dakota drought 1976)

    NASA Technical Reports Server (NTRS)

    Thompson, D. R.

    1976-01-01

    LACIE using techniques developed from the southern Great Plains drought analysis indicated the potential for drought damage in South Dakota. This potential was monitored and as it became apparent that a drought was developing, LACIE implemented some of the procedures used in the southern Great Plains drought. The technical approach used in South Dakota involved the normal use of LACIE sample segments (5 x 6 nm) every 18 days. Full frame color transparencies (100 x 100 nm) were used on 9 day intervals to identify the drought area and to track overtime. The green index number (GIN) developed using the Kauth transformation was computed for all South Dakota segments and selected North Dakota segments. A scheme for classifying segments as drought affected or not affected was devised and tested on all available 1976 South Dakota data. Yield model simulations were run for all CRD's Crop Reporting District) in South Dakota.

  17. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    NASA Astrophysics Data System (ADS)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  18. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    NASA Astrophysics Data System (ADS)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30 years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and evaluate their applicability for agricultural drought evaluation when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in-situ rainfall measurements across Chile were initially compared to the satellite-based precipitation estimates. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to

  19. Drought Water Right Curtailment

    NASA Astrophysics Data System (ADS)

    Walker, W.; Tweet, A.; Magnuson-Skeels, B.; Whittington, C.; Arnold, B.; Lund, J. R.

    2016-12-01

    California's water rights system allocates water based on priority, where lower priority, "junior" rights are curtailed first in a drought. The Drought Water Rights Allocation Tool (DWRAT) was developed to integrate water right allocation models with legal objectives to suggest water rights curtailments during drought. DWRAT incorporates water right use and priorities with a flow-forecasting model to mathematically represent water law and hydrology and suggest water allocations among water rights holders. DWRAT is compiled within an Excel workbook, with an interface and an open-source solver. By implementing California water rights law as an algorithm, DWRAT provides a precise and transparent framework for the complicated and often controversial technical aspects of curtailing water rights use during drought. DWRAT models have been developed for use in the Eel, Russian, and Sacramento river basins. In this study, an initial DWRAT model has been developed for the San Joaquin watershed, which incorporates all water rights holders in the basin and reference gage flows for major tributaries. The San Joaquin DWRAT can assess water allocation reliability by determining probability of rights holders' curtailment for a range of hydrologic conditions. Forecasted flow values can be input to the model to provide decision makers with the ability to make curtailment and water supply strategy decisions. Environmental flow allocations will be further integrated into the model to protect and improve ecosystem water reliability.

  20. SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

    NASA Technical Reports Server (NTRS)

    Irwin, D. E.; Sever, T. L.; Graves, S.; Hardin, Dan

    2004-01-01

    In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica, composed of the seven Central American countries and the five southernmost states of Mexico, make up only a small fraction of the world's land surface. However, the region is home to seven to eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica's biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in

  1. SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

    NASA Technical Reports Server (NTRS)

    Irwin, Daniel E.; Sever, Tom; Graves, Sara; Hardin, Danny

    2005-01-01

    In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - make up only a small fraction of the world s land surface. However, the region is home to seven to eight percent of the planet s biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica s biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far

  2. Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

    USGS Publications Warehouse

    Funk, Christopher C.; Verdin, James; Adams Chavula,; Gregory J. Husak,; Harikishan Jayanthi,; Tamuka Magadzire,

    2013-01-01

    During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAID, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were upscaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi.

  3. 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.

  4. 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

  5. An approach to integrate spatial and climatological data as support to drought monitoring and agricultural management problems in South Sudan

    NASA Astrophysics Data System (ADS)

    Bonetto, Sabrina; Facello, Anna; Camaro, Walther; Isotta Cristofori, Elena; Demarchi, Alessandro

    2016-04-01

    Drought is a natural hazard characterized by an abnormally dry event in the hydrological cycle caused by insufficient precipitation over an extended period of time, which affects more people than any other natural disaster and results in social, economic and environmental costs. In Africa, the economic system is based primarily on natural resources for example farming. For this reason, climate variability and events such as drought are phenomena that can represent significant disturbances and threats in the agricultural systems. In particular, this study concerns the monitoring of environmental changes in the south sector of South Sudan. The climate and environment in the South Sudan have shown localised changes during the course of this century and recurrent wars and droughts in the last years determined a large food-crisis. Actually, the security situation is stabilised with sporadic fighting concentrated in Jonglei, Unity and Upper Nile States. With the stabilisation of the conflict, many refugees have returned to their regions, trying to recover the economic structure based mainly on agriculture. For this reason, it is important to monitoring and analysis the vegetation and drought trend over the last years to support agricultural development and food security, in particular in post-conflict areas. This study focuses on the analysis of the relationship between the temporal variations of state of vegetation and the precipitation patterns. A historical analysis of the vegetation behaviour (NDVI) and the drought during the year is developed. In addition, with the aim to identify the wet and dry seasons, an analysis of precipitation is performed. Based on the vegetation and precipitation trends obtained, it is possible to characterize the best areas to start an agricultural system, giving priority to certain areas in order to plan the land use for agricultural purposes and programming crop (which and where). Consequently, with the aim to identify possible

  6. 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...

  7. 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.

  8. 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.

  9. Integrating environmental monitoring with cumulative effects management and decision making.

    PubMed

    Cronmiller, Joshua G; Noble, Bram F

    2018-05-01

    Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to

  10. 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

  11. 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.

  12. Low-cost sensors to monitor groundwater drought in Somalia

    NASA Astrophysics Data System (ADS)

    Buytaert, W.; Ochoa-Tocachi, B. F.; Caniglia, D.; Haibe, K.; Butler, A. P.

    2017-12-01

    Somalia is one of the poorest countries in the world, devastated by conflict and suffering from the most severe droughts in living memory. Over 6 million people are in need of assistance, and about 3 million are threatened with famine. In April 2017, the WHO estimated that more than 25,000 people have been struck by cholera or acute watery diarrhoea and this number is rising quickly. About half a million Somalis have been displaced internally, many of which in search of water. Some 3 million pastoralists have lost 70% of livestock as a result of the drought. Humanitarian organisations and government agencies invest large amounts of resources to alleviate these conditions. It is paramount to inform the design, focus, and optimisation of these interventions by monitoring and quantifying water resources. Yet, regions such as Somalia are extremely sparsely gauged as a result of a combination of lack of resources and technical expertise, as well as the harsh geographical and geopolitical conditions. Low-cost, robust, and reliable sensors may provide a potential solution to this problem. We present the results of a research project that aimed to leverage new developments in sensor, logger, and data transmission technologies to develop low-cost water level sensors to monitor hand-dug groundwater wells in real time. We tested 3 types of sensor types, i.e. pressure transducers, ultrasound-based distance sensors, and lidar, which were coupled to low-cost logging systems. The different designs were tested both in laboratory conditions, and in-situ in hand-dug wells in Somaliland. Our results show that it is technically possible to build sensors with a total cost of around US$250 each, which are fit-for-purpose for the required application. In-situ deployment over a period of 2 months highlights their robustness despite severe logistical and practical challenges, though further tests are required to understand their long-term reliability. Operating the sensors at one

  13. 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.

  14. Drought impacts and resilience on crops via evapotranspiration estimations

    NASA Astrophysics Data System (ADS)

    Timmermans, Joris; Asadollahi Dolatabad, Saeid

    2015-04-01

    Currently, the global needs for food and water is at a critical level. It has been estimated that 12.5 % of the global population suffers from malnutrition and 768 million people still do not have access to clean drinking water. This need is increasing because of population growth but also by climate change. Changes in precipitation patterns will result either in flooding or droughts. Consequently availability, usability and affordability of water is becoming challenge and efficient use of water and water management is becoming more important, particularly during severe drought events. Drought monitoring for agricultural purposes is very hard. While meteorological drought can accurately be monitored using precipitation only, estimating agricultural drought is more difficult. This is because agricultural drought is dependent on the meteorological drought, the impacts on the vegetation, and the resilience of the crops. As such not only precipitation estimates are required but also evapotranspiration at plant/plot scale. Evapotranspiration (ET) describes the amount of water evaporated from soil and vegetation. As 65% of precipitation is lost by ET, drought severity is highly linked with this variable. In drought research, the precise quantification of ET and its spatio-temporal variability is therefore essential. In this view, remote sensing based models to estimate ET, such as SEBAL and SEBS, are of high value. However the resolution of current evapotranspiration products are not good enough for monitoring the impact of the droughts on the specific crops. This limitation originates because plot scales are in general smaller than the resolution of the available satellite ET products. As such remote sensing estimates of evapotranspiration are always a combination of different land surface types and cannot be used for plant health and drought resilience studies. The goal of this research is therefore to enable adequate resolutions of daily evapotranspiration estimates

  15. 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.

  16. 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.

  17. 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

    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.

  18. 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.

  19. Strengthening Agricultural Decisions in Countries at Risk of Food Insecurity: The GEOGLAM Crop Monitor for Early Warning

    NASA Astrophysics Data System (ADS)

    Becker-Reshef, I.; Barker, B.; McGaughey, K.; Humber, M. L.; Sanchez, A.; Justice, C. O.; Rembold, F.; Verdin, J. P.

    2016-12-01

    Timely, reliable information on crop conditions, and prospects at the subnational scale, is critical for making informed policy and agricultural decisions for ensuring food security, particularly for the most vulnerable countries. However, such information is often incomplete or lacking. As such, the Crop Monitor for Early Warning (CM for EW) was developed with the goal to reduce uncertainty and strengthen decision support by providing actionable information on a monthly basis to national, regional and global food security agencies through timely consensus assessments of crop conditions. This information is especially critical in recent years, given the extreme weather conditions impacting food supplies including the most recent El Nino event. This initiative brings together the main international food security monitoring agencies and organizations to develop monthly crop assessments based on satellite observations, meteorological information, field observations and ground reports, which reflect an international consensus. This activity grew out of the successful Crop Monitor for the G20 Agricultural Market Information System (AMIS), which provides operational monthly crop assessments of the main producing countries of the world. The CM for EW was launched in February 2016 and has already become a trusted source of information internationally and regionally. Its assessments have been featured in a large number of news articles, reports, and press releases, including a joint statement by the USAID's FEWS NET, UN World Food Program, European Commission Joint Research Center, and the UN Food and Agriculture Organziation, on the devastating impacts of the southern African drought due to El Nino. One of the main priorities for this activity going forward is to expand its partnership with regional and national monitoring agencies, and strengthen capacity for national crop condition assessments.

  20. Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

    NASA Astrophysics Data System (ADS)

    Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

    2017-12-01

    Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The

  1. 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.

  2. Visualizing Earth Science Data for Environmental Monitoring and Decision Support in Mesoamerica: The SERVIR Project

    NASA Astrophysics Data System (ADS)

    Hardin, D.; Graves, S.; Sever, T.; Irwin, D.

    2005-05-01

    In 2002 and 2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - makes up only a small fraction of the world's land surface. However, the region is home to approximately eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Mesoamerica's biological and cultural diversity are severely threatened by human impact and natural disasters including extensive deforestation, illegal logging, water pollution, slash and burn agriculture, earthquakes, hurricanes, drought, and volcanic eruption. NASA Marshall Space Flight Center (NASA/MSFC), together with the University of Alabama in Huntsville (UAH) and the SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters, and better understand both natural and human induced effects. The decision support and environmental monitoring data products are typically formatted as conventional two-dimensional, static and animated imagery. However, in addition to conventional data products and as a major portion of our research, we are employing commercial applications that generate three-dimensional interactive visualizations that allow data products to be viewed from multiple angles and at

  3. 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.

  4. Automated Monitoring of Carbon Fluxes in a Northern Rocky Mountain Forest Indicates Above-Average Net Primary Productivity During the 2015 Western U.S. Drought

    NASA Astrophysics Data System (ADS)

    Stenzel, J.; Hudiburg, T. W.

    2016-12-01

    As global temperatures rise in the 21st century, "hotter" droughts will become more intense and persistent, particularly in areas which already experience seasonal drought. Because forests represent a large and persistent terrestrial carbon sink which has previously offset a significant proportion of anthropogenic carbon emissions, forest carbon cycle responses to drought have become a prominent research concern. However, robust mechanistic modeling of carbon balance responses to projected drought effects requires improved observation-driven representations of carbon cycle processes; many such component processes are rarely monitored in complex terrain, are modeled or unrepresented quantities at eddy covariance sites, or are monitored at course temporal scales that are not conducive to elucidating process responses at process time scales. In the present study, we demonstrate the use of newly available and affordable automated dendrometers for the estimation of intra-seasonal Net Primary Productivity (NPP) in a Northern Rocky Mountain conifer forest which is impacted by seasonal drought. Results from our pilot study suggest that NPP was restricted by mid-summer moisture deficit under the extraordinary 2015 Western U.S. drought, with greater than 90% off stand growth occurring prior to August. Examination of growth on an inter-annual scale, however, suggests that the study site experienced above-average NPP during this exceptionally hot year. Taken together, these findings indicate that intensifying mid-summer drought in regional forests has affected the timing but has not diminished the magnitude of this carbon flux. By employing automated instrumentation for the intra-annual assessment of NPP, we reveal that annual NPP in regional forests is largely determined before mid-summer and is therefore surprisingly resilient to intensities of seasonal drought that exceed normal conditions of the 20th century.

  5. Monitoring as a partially observable decision problem

    Treesearch

    Paul L. Fackler; Robert G. Haight

    2014-01-01

    Monitoring is an important and costly activity in resource man-agement problems such as containing invasive species, protectingendangered species, preventing soil erosion, and regulating con-tracts for environmental services. Recent studies have viewedoptimal monitoring as a Partially Observable Markov Decision Pro-cess (POMDP), which provides a framework for...

  6. 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

  7. 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.

  8. 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

  9. Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

    2014-01-01

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

  10. Multi-year strongest California drought from 500 m SNPP/VIIRS

    NASA Astrophysics Data System (ADS)

    Guo, W.; Kogan, F.

    2016-12-01

    Starting in 2006, the western United States was affected by a 10-year long mega-drought. Among 17 western states, California was the most severely drought-affected, especially in 2012-2015, when the area of stronger than moderate vegetation stress reached 70%. This drought had considerable impacts on California's environmental, economy and society. Currently, drought in the USA is monitored by the US Drought Monitor (USDM), which estimates drought area and intensity on an area with an effective resolution of around 30-by-30 km. California produces more than 90% of US fruits, vegetables, berries and nuts, which are grown on relatively small areas (200-500 acres, or 0.5 to 2 km²). Since most of these crops are irrigated, it is important to estimate crop conditions on the area comparable to the size of the planted crop. This paper demonstrates how the new 0.5-by-0.5 km Vegetation health (VH) technology (VH-500) developed from the data collected by the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite launched in 2011, monitors the current mega-drought in California, distinguishing drought-affected area with and without irrigation and estimating drought start/end, intensity, duration and impacts. The VH-500 method and data showed that California's vegetation was under medium-to-exceptional stress, especially in 2013 and 2014. However, in the middle of such intensive stress, in some of the 500-m areas of the Central Valley where principal crops are growing, vegetation experienced favorable conditions because some of these crops were irrigated. The VH-500 drought estimates showed general similarities with the assessed economic drought impacts (crop fallowing, employment loss and crop revenue change) in California.

  11. How 21st century droughts affect food and environmental security

    NASA Astrophysics Data System (ADS)

    Kogan, Felix

    The first 13th years of the 21st century has begun with a series of widespread, long and intensive droughts around the world. Extreme and severe-to-extreme intensity droughts covered 2-6% and 7-16% of the world land, respectively, affecting environment, economies and humans. These droughts reduced agricultural production, leading to food shortages, human health deterioration, poverty, regional disturbances, population migration and death. This presentation is a travelogue of the 21st century global and regional droughts during the warmest years of the past 100 years. These droughts were identified and monitored with the NOAA operational space technology, called Vegetation Health (VH), which has the longest period of observation and provide good data quality. The VH method was used for assessment of vegetation condition or health, including drought early detection and monitoring. The VH method is based on operational satellites data estimating both land surface greenness (NDVI) and thermal conditions. The 21st century droughts in the USA, Russia, Australia Argentina, Brazil, China, India and other principal grain producing countries were intensive, long, covered large areas and caused huge losses in agricultural production, which affected food and environmental security and led to food riots in some countries. This presentation investigate how droughts affect food and environmental security, if they can be detected earlier, how to monitor their area, intensity, duration and impacts and also their dynamics during the climate warming era with satellite-based vegetation health technology.

  12. Strategic Planning for Drought Mitigation Under Climate Change

    NASA Astrophysics Data System (ADS)

    Cai, X.; Zeng, R.; Valocchi, A. J.; Song, J.

    2012-12-01

    Droughts continue to be a major natural hazard and mounting evidence of global warming confronts society with a pressing question: Will climate change aggravate the risk of drought at local scale? It is important to explore what additional risk will be imposed by climate change and what level of strategic measures should be undertaken now to avoid vulnerable situations in the future, given that tactical measures may not avoid large damage. This study addresses the following key questions on strategic planning for drought mitigation under climate change: What combination of strategic and tactical measures will move the societal system response from a vulnerable situation to a resilient one with minimum cost? Are current infrastructures and their operation enough to mitigate the damage of future drought, or do we need in-advance infrastructure expansion for future drought preparedness? To address these questions, this study presents a decision support framework based on a coupled simulation and optimization model. A quasi-physically based watershed model is established for the Frenchman Creek Basin (FCB), part of the Republic River Basin, where groundwater based irrigation plays a significant role in agriculture production and local hydrological cycle. The physical model is used to train a statistical surrogate model, which predicts the watershed responses under future climate conditions. The statistical model replaces the complex physical model in the simulation-optimization framework, which makes the models computationally tractable. Decisions for drought preparedness include traditional short-term tactical measures (e.g. facility operation) and long-term or in-advance strategic measures, which require capital investment. A scenario based three-stage stochastic optimization model assesses the roles of strategic measures and tactical measures in drought preparedness and mitigation. Two benchmark climate prediction horizons, 2040s and 2090s, represent mid-term and

  13. Transcriptomic Changes of Drought-Tolerant and Sensitive Banana Cultivars Exposed to Drought Stress

    PubMed Central

    Muthusamy, Muthusamy; Uma, Subbaraya; Backiyarani, Suthanthiram; Saraswathi, Marimuthu Somasundaram; Chandrasekar, Arumugam

    2016-01-01

    In banana, drought responsive gene expression profiles of drought-tolerant and sensitive genotypes remain largely unexplored. In this research, the transcriptome of drought-tolerant banana cultivar (Saba, ABB genome) and sensitive cultivar (Grand Naine, AAA genome) was monitored using mRNA-Seq under control and drought stress condition. A total of 162.36 million reads from tolerant and 126.58 million reads from sensitive libraries were produced and mapped onto the Musa acuminata genome sequence and assembled into 23,096 and 23,079 unigenes. Differential gene expression between two conditions (control and drought) showed that at least 2268 and 2963 statistically significant, functionally known, non-redundant differentially expressed genes (DEGs) from tolerant and sensitive libraries. Drought has up-regulated 991 and 1378 DEGs and down-regulated 1104 and 1585 DEGs respectively in tolerant and sensitive libraries. Among DEGs, 15.9% are coding for transcription factors (TFs) comprising 46 families and 9.5% of DEGs are constituted by protein kinases from 82 families. Most enriched DEGs are mainly involved in protein modifications, lipid metabolism, alkaloid biosynthesis, carbohydrate degradation, glycan metabolism, and biosynthesis of amino acid, cofactor, nucleotide-sugar, hormone, terpenoids and other secondary metabolites. Several, specific genotype-dependent gene expression pattern was observed for drought stress in both cultivars. A subset of 9 DEGs was confirmed using quantitative reverse transcription-PCR. These results will provide necessary information for developing drought-resilient banana plants. PMID:27867388

  14. 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.

  15. 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.

  16. A water resources simulation gaming model for the Invitational Drought Tournament.

    PubMed

    Wang, K; Davies, E G R

    2015-09-01

    A system dynamics-based simulation gaming model, developed as a component of Agriculture and Agri-Food Canada's Invitational Drought Tournament (IDT; Hill et al., 2014), is introduced in this paper as a decision support tool for drought management at the river-basin scale. This IDT Model provides a comprehensive and integrated overview of drought conditions, and illustrates the broad effects of socio-economic drought and mitigation strategies. It is intended to provide a safe, user-friendly experimental environment with fast run-times for testing management options, and to promote collaborative decision-making and consensus building. Examples of model results from several recent IDT events demonstrate potential effects of drought and the short-to longer-term effectiveness of policies selected by IDT teams; such results have also improved teams' understanding of the complexity of water resources systems and their management trade-offs. The IDT Model structure and framework can also be reconfigured quickly for application to different river basins. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Remote Sensing of Agro-droughts in Guangdong Province of China Using MODIS Satellite Data.

    PubMed

    Gao, Maofang; Qin, Zhihao; Zhang, Hong'ou; Lu, Liping; Zhou, Xia; Yang, Xiuchun

    2008-08-08

    A practical approach was developed in the study for drought monitoring in Guangdong province of China on the basis of vegetation supply water index (VSWI) and precipitation distance index (PDI). A comprehensive index for assessment of agro-drought severity (SADI) was then established from the normalized VSWI and PDI. Using MODIS satellite images and precipitation data from ground-observed meteorological stations, we applied the approach to Guangdong for drought monitoring in 2006. The monitoring results showed that the drought severity on average was very low in the province during the main growing season from May to September in 2006. However, seasonal variation of the severity was also obvious in difference counties of the province. Higher severity of drought could be seen in the periods of late-June (In China each month is traditionally divided into 3 periods. Each is with 10 days and has different names. This division system is mainly with consideration of farming seasons hence has been widely used as the basis of drought monitoring periods in China. In order to keep this tradition, we define, for example, for June, the early-June as the period from 1 st to 10 th of June, the mid-June as the period from 11 th to 20 th , and the late-June as the period from 21 st to 30 th . So mid-August denotes the period from 11 th to 20 th of August, and early-July the period from 1 st to 10th of July, and so on.), early-July, mid-August and late-September. Regionally, Leizhou Peninsula in the west had the most serious drought before mid-May. Validation indicated that our monitoring results were generally consistent with the drought statistics data and the results from Chinese National Satellite Meteorological Center (CNSMC), which used only remote sensing data. This consistence confirmed the applicability of our approach for drought monitoring. Our better identification of drought severity in Leizhou Peninsula of western Guangdong than that of CNSMC might suggest that the

  18. GROUND WATER QUALITY SURROUNDING LAKE TEXOMA DURING SHORT-TERM DROUGHT CONDITIONS

    EPA Science Inventory

    Water quality data from 55 monitoring wells during drought conditions surrounding Lake Texoma, located on the border of Oklahoma and Texas, was compared to assess the influence of drought on groundwater quality. During the drought month of October, water table levels were three ...

  19. Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

    NASA Astrophysics Data System (ADS)

    Van Loon, Anne; Laaha, Gregor; Van Lanen, Henny; Parajka, Juraj; Fleig, Anne; Ploum, Stefan

    2016-04-01

    reservoir levels and, consequently, on drinking water and electricity production. Snow storage therefore, is an important factor to consider in drought monitoring, prediction and management.

  20. Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

    NASA Astrophysics Data System (ADS)

    Van Loon, A.; Laaha, G.; Van Lanen, H.; Parajka, J.; Fleig, A. K.; Ploum, S.

    2015-12-01

    reservoir levels and, consequently, on drinking water and electricity production. Snow storage therefore, is an important factor to consider in drought monitoring, prediction and management.

  1. 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

  2. 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

  3. In Situ Stem Psychrometry: toward a Physiologically-Based Drought Monitoring Network

    NASA Astrophysics Data System (ADS)

    KOCH, G. W.; Williams, C.; Ambrose, A.

    2012-12-01

    Plant water potential is a synoptic variable that integrates soil and atmospheric moisture stress and interacts with plant-internal factors to regulate gas exchange and determine vulnerability to drought-induced hydraulic dysfunction. Despite its importance, methods for measuring water potential are labor intensive. This limitation reduces measurement frequency, likely causes important transient events to be overlooked, and restricts development of a richer understanding of the impacts of integrated water stress on plant and ecosystem function. Recent technological advances have enabled in-situ, automated measurement of branch water potential over periods of weeks to months using stem psychrometers. We evaluated this technology through laboratory and field comparisons to standard pressure chamber measurements and with field installations in temperate forest, semi-arid woodland, and chaparral ecosystems. Performance was highly sensitive to installation procedures. With proper sealing, insulation, and radiation shielding, psychrometers typically differed from pressure chamber measurements by less than 0.2 MPa down to water potentials as low as -7 MPa. Measurements in tall trees reaffirmed the influence of gravity on water potential as previously documented with the pressure chamber. Psychrometer performance in situ was stable for periods of several weeks to months, with tissue wound response degrading sensor operation over time. We conclude that stem psychrometer technology is now suitable to serve as the foundation for a physiologically-based drought monitoring network that can anticipate important ecosystem impacts including changes in whole-system fluxes and mortality events.

  4. 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

  5. Assessment of tree response to drought: validation of a methodology to identify and test proxies for monitoring past environmental changes in trees.

    PubMed

    Tene, A; Tobin, B; Dyckmans, J; Ray, D; Black, K; Nieuwenhuis, M

    2011-03-01

    A thinning experiment stand at Avoca, Ballinvalley, on the east coast of the Republic of Ireland was used to test a developed methodology aimed at monitoring drought stress, based on the analysis of growth rings obtained by coring. The stand incorporated six plots representing three thinning regimes (light, moderate and heavy) and was planted in the spring of 1943 on a brown earth soil. Radial growth (early- and latewood) was measured for the purpose of this study. A multidisciplinary approach was used to assess historic tree response to climate: specifically, the application of statistical tools such as principal component and canonical correlation analysis to dendrochronology, stable isotopes, ring density proxy, blue reflectance and forest biometrics. Results showed that radial growth was a good proxy for monitoring changes to moisture deficit, while maximum density and blue reflectance were appropriate for assessing changes in accumulated temperature for the growing season. Rainfall also influenced radial growth changes but not significantly, and was a major factor in stable carbon and oxygen discrimination, mostly in the latewood formation phase. Stable oxygen isotope analysis was more accurate than radial growth analysis in drought detection, as it helped detect drought signals in both early- and latewood while radial growth analysis only detected the drought signal in earlywood. Many studies have shown that tree rings provide vital information for marking past climatic events. This work provides a methodology to better identify and understand how commonly measured tree proxies relate to environmental parameters, and can best be used to characterize and pinpoint drought events (variously described using parameters such as like moisture deficit, accumulated temperature, rainfall and potential evaporation).

  6. 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.

  7. Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

    USDA-ARS?s Scientific Manuscript database

    Agricultural drought is defined as a shortage of moisture in the root zone of plants. Recently available satellite-based remote sensing data have accelerated development of drought early warning system by providing spatially continuous soil moisture information repeatedly at short-term interval. Non...

  8. 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.

  9. Drought monitoring of Shandong province in late 2010 using data acquired by Terra MODIS

    NASA Astrophysics Data System (ADS)

    Wang, Mingzhi; Huang, He; Liu, Suihua; Yan, Lei

    2011-12-01

    Drought has been a frequently happened type of disaster in China, and it has caused massive losses to people's lives. Especially the drought happened in Shandong province in the late 2010, which was recognized as the severest in the past five hundred years in some areas. Evaluation must be done in order to make proper rescue plans. Instead of collecting data site by site, remote sensing is an efficient way to acquire data in a large area, which is very helpful for drought identification. Some normal ways in remote sensing for drought analysis are explained and compared in this paper, and then the VSWI method is chosen to evaluation the drought in Shandong province. Because of its free data policy and wide availability, the data sets acquired by Terra-MODIS are chosen to identify the drought severity in Shandong province. From the drought severity level images we can see that almost the whole area of Shandong province was lack of water except the Weishan Lake and eastern coastline regions where large area of water exists. The southwest region, including Heze and Jining, is in moderate drought condition, where it is used to be an important grain-producing area. This drought condition will inevitably put a negative effect on its grain production. The central and southern areas were in severe drought condition, but fortunately these areas are of hills and mountains, so the drought will only affect the lives of residents. The northern parts, including Dezhou and Bingzhou areas, were also in severe drought condition, and these regions are also important for grain-producing, so the severe drought disaster will lead to a sharp grain output cut. This analysis results will not only shed light on the rescue process, but also give the government some clues on how to maintain the grain supply safety.

  10. 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

  11. The European 2015 drought from a groundwater perspective

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    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.

  12. 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

  13. Decision-Making Accuracy of CBM Progress-Monitoring Data

    ERIC Educational Resources Information Center

    Hintze, John M.; Wells, Craig S.; Marcotte, Amanda M.; Solomon, Benjamin G.

    2018-01-01

    This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading…

  14. The role of conservation programs in drought risk adaptation

    Treesearch

    Steven Wallander; Marcel Aillery; Daniel Hellerstein; Michael Hand

    2013-01-01

    This report evaluates the extent to which farms facing higher levels of drought risk are more likely to participate in conservation programs, and fi nds a strong link between drought risk and program participation. Prior research has shown that climate-related risk exposure infl uences production decisions such as crop choice; our research shows that adaptation also...

  15. Remotely Sensed Hydrometeorological and Agrometeorological Drought Risk Identification for Sustainable Agriculture.

    NASA Astrophysics Data System (ADS)

    Dalezios, Nicolas R.; Blanta, Anna; Spyropoulos, Nicos

    2013-04-01

    Drought is considered as one of the major environmental hazards with significant impacts to agriculture, environment, economy and society. This paper addresses drought as a hazard within the risk management framework. Indeed, hazards 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. Besides, risk management consists of risk assessment and feedback of the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. In order to ensure sustainability in agricultural production a better understanding of the natural disasters, in particular droughts, that impact agriculture is essential. Droughts may result in environmental degradation of an area, which is one of the factors contributing to the vulnerability of agriculture, because it directly magnifies the risk of natural disasters. This paper deals with drought risk identification, which involves hazard quantification, event monitoring including early warning systems and statistical inference. For drought quantification the Reconnaissance Drought Index (RDI) combined with Vegetation Health Index (VHI) is employed. RDI is a new index based on hydrometeorological parameters, and in particular precipitation and potential evapotranspiration, which has been recently modified to incorporate monthly satellite (NOAA/AVHAA) data for a period of 20 years (1981-2001). VHI is based on NDVI. The study area is Thessaly in central Greece, which is one of the major agricultural areas of the country occasionally facing droughts. Drought monitoring is conducted by monthly remotely sensed RID and VHI images and several drought features are extracted such as severity, duration, areal extent, onset and end time. Drought early warning is developed using empirical relationships of the above mentioned features. In particular, two second-order polynomials

  16. 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.

  17. GROUND WATER QUALITY SURROUNDING LAKE TEXOMA DURING DROUGHT CONDITIONS

    EPA Science Inventory

    Water quality data from 55 producing monitoring wells during drought conditions surrounding Lake Texoma, located on the border of Oklahoma and Texas, was compared to assess the influence of drought on groundwater quality. The main water quality parameter measured was nitrate, an...

  18. Monitoring in the context of structured decision-making and adaptive management

    USGS Publications Warehouse

    Lyons, J.E.; Runge, M.C.; Laskowski, H.P.; Kendall, W.L.

    2008-01-01

    In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play >3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill >1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring

  19. On-line confidence monitoring during decision making.

    PubMed

    Dotan, Dror; Meyniel, Florent; Dehaene, Stanislas

    2018-02-01

    Humans can readily assess their degree of confidence in their decisions. Two models of confidence computation have been proposed: post hoc computation using post-decision variables and heuristics, versus online computation using continuous assessment of evidence throughout the decision-making process. Here, we arbitrate between these theories by continuously monitoring finger movements during a manual sequential decision-making task. Analysis of finger kinematics indicated that subjects kept separate online records of evidence and confidence: finger deviation continuously reflected the ongoing accumulation of evidence, whereas finger speed continuously reflected the momentary degree of confidence. Furthermore, end-of-trial finger speed predicted the post-decisional subjective confidence rating. These data indicate that confidence is computed on-line, throughout the decision process. Speed-confidence correlations were previously interpreted as a post-decision heuristics, whereby slow decisions decrease subjective confidence, but our results suggest an adaptive mechanism that involves the opposite causality: by slowing down when unconfident, participants gain time to improve their decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Coping with historic drought in California rangelands: Developing a more effective institutional response

    USGS Publications Warehouse

    Brown, Joel R.; Alvarez, Pelayo; Byrd, Kristin B.; Deswood, Helena; Elias, Emile; Spiegal, Sheri

    2017-01-01

    Drought response is widely varied depending on both the characteristics of the drought and the ability of individual ranchers to respond.Assistance from institutions during drought has not typically considered preemptive, during, and post-drought response as a strategic approach, which recognizes biophysical, sociological, and economic complexities of drought.A USDA Southwest Climate Hub-sponsored workshop brought together a range of representatives from public and private institutions with drought response responsibilities to examine how those institutions could better support drought decision-making.Institutions can greatly improve their support for individual land managers by doing more systematic collecting and organizing of drought-related information as a basis for programs, and by collaborating to enhance both institutional and individual learning.

  1. Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Bolten, J. D.

    2014-12-01

    Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

  2. 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

  3. 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

  4. Hydrologic monitoring using open-source Arduino logging platforms in a socio-hydrological system of the drought-prone tropics, Guanacaste, Costa Rica

    NASA Astrophysics Data System (ADS)

    Hund, S. V.; Johnson, M. S.; Steyn, D. G.; Keddie, T.; Morillas, L.

    2015-12-01

    Water supply is highly disputed in the tropics of northwestern Costa Rica where rainfall exhibits high seasonal variability and long annual dry seasons. Water shortages are common during the dry season, and water conflicts emerge between domestic water users, intensively irrigated agriculture, the tourism industry, and ecological flows. Climate change may further increase the variability of precipitation and the risk for droughts, and pose challenges for small rural agricultural communities experiencing water stress. To adapt to seasonal droughts and improve resilience of communities to future changes, it is essential to increase understanding of interactions between components of the coupled hydrological-social system. Yet, hydrological monitoring and data on water use within developing countries of the humid tropics is limited. To address these challenges and contribute to extended monitoring networks, low-cost and open-source monitoring platforms were developed based off Arduino microelectronic boards and software and combined with hydrological sensors to monitor river stage and groundwater levels in two watersheds of Guanacaste, Costa Rica. Hydrologic monitoring stations are located in remote locations and powered by solar panels. Monitoring efforts were made possible through collaboration with local rural communities, and complemented with a mix of digitized water extraction data and community water use narratives to increase understanding of water use and challenges. We will present the development of the Arduino logging system, results of water supply in relation to water use for both the wet and dry season, and discuss these results within a socio-hydrological system context.

  5. Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

    NASA Astrophysics Data System (ADS)

    Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

    2012-06-01

    It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

  6. Exploring the link between meteorological drought and streamflow to inform water resource management

    NASA Astrophysics Data System (ADS)

    Lennard, Amy; Macdonald, Neil; Hooke, Janet

    2015-04-01

    Drought indicators are an under-used metric in UK drought management. Standardised drought indicators offer a potential monitoring and management tool for operational water resource management. However, the use of these metrics needs further investigation. This work uses statistical analysis of the climatological drought signal based on meteorological drought indicators and observed streamflow data to explore the link between meteorological drought and hydrological drought to inform water resource management for a single water resource region. The region, covering 21,000 km2 of the English Midlands and central Wales, includes a variety of landscapes and climatological conditions. Analysis of the links between meteorological drought and hydrological drought performed using streamflow data from 'natural' catchments indicates a close positive relationship between meteorological drought indicators and streamflow, enhancing confidence in the application of drought indicators for monitoring and management. However, many of the catchments in the region are subject to modification through impoundments, abstractions and discharge. Therefore, it is beneficial to explore how climatological drought signal propagates into managed hydrological systems. Using a longitudinal study of catchments and sub-catchments that include natural and modified river reaches the relationship between meteorological and hydrological drought is explored. Initial statistical analysis of meteorological drought indicators and streamflow data from modified catchments shows a significantly weakened statistical relationship and reveals how anthropogenic activities may alter hydrological drought characteristics in modified catchments. Exploring how meteorological drought indicators link to streamflow across the water supply region helps build an understanding of their utility for operational water resource management.

  7. 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.

  8. Workshop on the Development of an Experimental Global Drought Information System (GDIS): Overview of Workshop Goals

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried

    2012-01-01

    Among the key recommendations of a recent WCRP Workshop on Drought Predictability and Prediction in a Changing Climate is the development of an experimental global drought information system (GDIS). The timeliness of such an effort is evidenced by the wide aITay of relevant ongoing national and international (as well as regional and continental scale) efforts to provide drought information, including the US and North American drought monitors, and various integrating activities such as GEO and the Global Drought Portal. The workshop will review current capabilities and needs, and focus on the steps necessary to develop a GDIS that will build upon the extensive worldwide investments that have already been made in developing drought monitoring (including new space-based observations), drought risk management, and climate prediction capahilities.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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

  14. Drought Analysis for Kuwait Using Standardized Precipitation Index

    PubMed Central

    2014-01-01

    Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of monthly total precipitation data from January 1967 to December 2009 is used for the assessment. The computation of the SPI series is performed for intermediate- and long-time scales of 3, 6, 12, and 24 months. The drought severity and duration are also estimated. The bivariate probability distribution for these two drought characteristics is constructed by using Clayton copula. It has been shown that the drought SPI series for the time scales examined have no systematic trend component but a seasonal pattern related to rainfall data. The results are used to perform univariate and bivariate frequency analyses for the drought events. The study will help evaluating the risk of future droughts in the region, assessing their consequences on economy, environment, and society, and adopting measures for mitigating the effect of droughts. PMID:25386598

  15. Risk indicators for water supply systems for a drought Decision Support System in central Tuscany (Italy)

    NASA Astrophysics Data System (ADS)

    Rossi, Giuseppe; Garrote, Luis; Caporali, Enrica

    2010-05-01

    Identifying the occurrence, the extent and the magnitude of a drought can be delicate, requiring detection of depletions of supplies and increases in demand. Drought indices, particularly the meteorological ones, can describe the onset and the persistency of droughts, especially in natural systems. However they have to be used cautiously when applied to water supply systems. They show little correlation with water shortage situations, since water storage, as well as demand fluctuation, play an important role in water resources management. For that reason a more dynamic indicator relating supply and demand is required in order to identify situations when there is risk of water shortages. In water supply systems there is great variability on the natural water resources and also on the demands. These quantities can only be defined probabilistically. This great variability is faced defining some threshold values, expressed in probabilistic terms, that measure the hydrologic state of the system. They can identify specific actions in an operational context in different levels of severity, like the normal, pre-alert, alert and emergency scenarios. They can simplify the decision-making required during stressful periods and can help mitigate the impacts of drought by clearly defining the conditions requiring actions. The threshold values are defined considering the probability to satisfy a given fraction of the demand in a certain time horizon, and are calibrated through discussion with water managers. A simplified model of the water resources system is built to evaluate the threshold values and the management rules. The threshold values are validated with a long term simulation that takes into account the characteristics of the evaluated system. The levels and volumes in the different reservoirs are simulated using 20-30 years time series. The critical situations are assessed month by month in order to evaluate optimal management rules during the year and avoid conditions

  16. 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.

  17. Drought

    Treesearch

    John W. Coulston

    2009-01-01

    Drought occurrence is a function of temperature, moisture, and soil characteristics. In some regions, such as much of the Western United States, drought is a regular occurrence, while in others, such as the Northeastern United States, drought occurs on an irregular basis. Moderate drought stress tends to slow plant growth while severe drought stress also reduces...

  18. 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

  19. Avoiding Drought Risks and Social Conflict Under Climate Change

    NASA Astrophysics Data System (ADS)

    Towler, E.; Lazrus, H.; Paimazumder, D.

    2014-12-01

    Traditional drought research has mainly focused on physical drought risks and less on the cultural processes that also contribute to how drought risks are perceived and managed. However, as society becomes more vulnerable to drought and climate change threatens to increase water scarcity, it is clear that drought research would benefit from a more interdisciplinary approach. To assess avoided drought impacts from reduced climate change, drought risks need to be assessed in the context of both climate prediction as well as improved understanding of socio-cultural processes. To this end, this study explores a risk-based framework to combine physical drought likelihoods with perceived risks from stakeholder interviews. Results are presented from a case study on how stakeholders in south-central Oklahoma perceive drought risks given diverse cultural beliefs, water uses, and uncertainties in future drought prediction. Stakeholder interviews (n=38) were conducted in 2012 to understand drought risks to various uses of water, as well as to measure worldviews from the cultural theory of risk - a theory that explains why people perceive risks differently, potentially leading to conflict over management decisions. For physical drought risk, drought projections are derived from a large ensemble of future climates generated from two RCPs that represent higher and lower emissions trajectories (i.e., RCP8.5 and RCP4.5). These are used to develop a Combined Drought Risk Matrix (CDRM) that characterizes drought risks for different water uses as the products of both physical likelihood (from the climate ensemble) and risk perception (from the interviews). We use the CRDM to explore the avoided drought risks posed to various water uses, as well as to investigate the potential for reduction of conflict over water management.

  20. Groundwater quality surrounding Lake Texoma during short-term drought conditions

    USGS Publications Warehouse

    Kampbell, D.H.; An, Y.-J.; Jewell, K.P.; Masoner, J.R.

    2003-01-01

    Water quality data from 55 monitoring wells during drought conditions surrounding Lake Texoma, located on the border of Oklahoma and Texas, was compared to assess the influence of drought on groundwater quality. During the drought month of October, water table levels were three feet (0.9 m) lower compared with several months earlier under predrought climate conditions. Detection frequencies of nitrate (> 0.1 mg/l), orthophosphates (> 0.1 mg/l), chlorides (> MCL), and sulfates (> MCL) all increased during drought. Orthophosphate level was higher during drought. Largest increases in concentration were nitrate under both agriculture lands and in septic tank areas. An increase in ammonium-nitrogen was only detected in the septic tank area. The study showed that stressors such as nitrate and total salts could potentially become a health or environmental problem during drought.

  1. Using FRET for Drought Mitigation

    NASA Astrophysics Data System (ADS)

    Osborne, H. D.; Palmer, C. K.; Hobbins, M.

    2016-12-01

    With the ongoing drought plaguing California and much of the Western United States, water agencies and the general public have a heightened need for short term forecasts of evapotranspiration. The National Weather Service's (NWS) Forecast Reference Evapotranspiration (FRET) product suite can fill this need. The FRET product suite uses the Penman - Monteith Reference Evapotranspiration (ETrc) equation for a short canopy (12 cm grasses), adopted by the Environmental Water Resources Institute of the American Society of Civil Engineers. FRET is calculated across the contiguous U.S. using temperatures, humidity, winds, and sky cover from Numerical Weather Prediction (NPW) models and adjusted by NWS forecasters with local expertise of terrain and weather patterns. The Weekly ETrc product is easily incorporated into drought-planning strategies, allowing water managers, the agricultural community, and the public to make better informed water-use decisions. FRET can assist with the decision making process for scheduling irrigation (e.g., farms, golf courses, vineyards) and timing of fertilizers. The California Department of Water Resources (CA DWR) also ingests the FRET into their soil moisture models, and uses FRET to assist in determining the reservoir releases for the Feather River. The United States Bureau of Reclamation (USBR) also uses FRET in determining reservoir releases and assessing water temperature along the Sacramento and American Rivers. FRET is now operational on the National Digital Forecast Database (NDFD), permitting other agencies easy access to this nationwide data for all drought mitigation and planning purposes.

  2. Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

    NASA Technical Reports Server (NTRS)

    White, Kristopher D.; Case, Jonathan L.

    2014-01-01

    The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

  3. Research on Applicability Analysis of Drought Index in Liaoning Area

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Ding, Hua; Shuang Sun, Li; Li, Ru Ren; Liu, Yu Mei

    2018-05-01

    Based on brightness temperature data of AMSR-E (advanced microwave scanning radiometer — earth observing system) in 2009 and 2011, the inversion on 8 brightness temperature ratios is performed as alternative drought indexes in this paper. The correlation analysis is made through the soil moisture extracted from inversion drought index and data itself, and 3 kinds of alternative drought that relatively coincide with soil moisture of AMSR-E data itself are selected. And then on this basis, the analysis on the change situation of 3 kinds of microwave moisture indexes in 10 pixel × 10 pixel rectangular region of Shenyang and Chaoyang is made, and the evaluation on the monitoring advantages and disadvantages of 3 kinds of indexes on soil moisture is performed, so as to obtain the optimal index PIv6.9 for drought monitoring. In the end, in order to further study PIv6.9 on soil moisture monitoring situation within the range of Liaoning province, four days with relatively large precipitation are selected according to meteorological station data in 2009, the precipitation data of 51 meteorological stations in Liaoning province are interpolated within the range of the whole province by utilizing Kriging method, and the contrastive analysis on the spatial distribution of precipitation and PIv6.9 index is made. The results show that PIv6.9 can best reflect the spatial distribution characteristics of drought status in Liaoning province.

  4. Decision-making contexts involving Earth observations in federal and state government agencies

    NASA Astrophysics Data System (ADS)

    Kuwayama, Y.; Thompson, A.

    2017-12-01

    National and international organizations are placing greater emphasis on the societal and economic benefits that can be derived from applications of Earth observations, yet improvements are needed to connect to the decision processes that produce actions with direct societal benefits. The Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES), a cooperative agreement between Resources for the Future (RFF) and the National Aeronautics and Space Administration (NASA), has the goal of advancing methods for the valuation and communication of the applied benefits linked with Earth observations. One of the Consortium's activities is a set of Policy Briefs that document the use of Earth observations for decision making in federal and state government agencies. In developing these Policy Briefs, we pay special attention to documenting the entire information value chain associated with the use of Earth observations in government decision making, namely (a) the specific data product, modeling capability, or information system used by the agency, (b) the decision context that employs the Earth observation information and translates it into an agency action, (c) the outcomes that are realized as a result of the action, and (d) the beneficiaries associated with the outcomes of the decision. Two key examples include the use of satellite data for informing the US Drought Monitor (USDM), which is used to determine the eligibility of agricultural communities for drought disaster assistance programs housed at the US Department of Agriculture (USDA), and the use of satellite data by the Florida Department of Environmental Protection to develop numeric nutrient water quality standards and monitoring methods for chlorophyll-a, which is codified in Florida state code (62-302.532).

  5. Groundwater vulnerability to drought in agricultural watersheds, S. Korea

    NASA Astrophysics Data System (ADS)

    Song, Sung-Ho; Kim, Jin-Sung; Lee, Byungsun

    2017-04-01

    Drought can be generally defined by a considerable decrease in water availability due to a deficit in precipitation during a significant period over a large area. In South Korea, the severe drought occurred over late spring to early summer during from 2012 to 2015. In this period, precipitation decreased up to 10-40% compared with a normal one, resulting in reduction of stream flow and reservoir water over the country. It led to a shortage of irrigation water that caused great damage to grow rice plants on early stage. Furthermore, drought resulted in a negative effect on groundwater system with decline of its level. Change of the levels significantly reflects intrinsic characteristics of aquifer system. Identifying drought effects on groundwater system is very difficult because change of groundwater level after hydrological events tends to be delayed. Therefore, quantitative assessment on decline of groundwater level in agricultural watersheds plays an essential role to make customized policies for water shortage since groundwater system is directly affected by drought. Furthermore, it is common to analyze the time-series groundwater data from monitoring wells including hydrogeological characteristics in company with meteorological data because drought effects on groundwater system is site-specific. Currently, a total of 364 groundwater monitoring wells including 210 wells for rural groundwater management network(RGMN) and 154 wells for seawater intrusion monitoring network (SIMN) have been operating in agricultural watersheds in S. Korea. To estimate the effect of drought on groundwater system, monthly mean groundwater level data were obtained from RGMN and SIMN during the periods of 2012 to 2015. These data were compared to their past data in company with rainfall data obtained from adjacent weather stations. In 2012 and 2014, mean groundwater level data in the northern part of the country during irrigation season(April to June), when precipitation was recorded

  6. Water monitoring to support the State of Illinois Governor's Drought Response Task Force -August 7, 2012

    USGS Publications Warehouse

    ,

    2012-01-01

    The U.S. Geological Survey (USGS) collects streamflow, groundwater level, and water-quality data for the State of Illinois and the Nation. Much of these data are collected every 15 minutes (real-time) as a part of the national network, so that water-resource managers can make decisions in a timely and reliable manner. Coupled with modeling and other water-resource investigations, the USGS provides data to the State during droughts and other hydrologic events. The types of data, capabilities, and presentation of these materials are described in this document as USGS Real-Time Data, Supplementary Data Collection and Analysis, and National Resources Available.

  7. Protection of agriculture against drought in Slovenia based on vulnerability and risk assessment

    NASA Astrophysics Data System (ADS)

    Dovžak, M.; Stanič, S.; Bergant, K.; Gregorič, G.

    2012-04-01

    Past and recent extreme events, like earthquakes, extreme droughts, heat waves, flash floods and volcanic eruptions continuously remind us that natural hazards are an integral component of the global environment. Despite rapid improvement of detection techniques many of these events evade long-term or even mid-term prediction and can thus have disastrous impacts on affected communities and environment. Effective mitigation and preparedness strategies will be possible to develop only after gaining the understanding on how and where such hazards may occur, what causes them, what circumstances increase their severity, and what their impacts may be and their study has the recent years emerged as under the common title of natural hazard management. The first step in natural risk management is risk identification, which includes hazard analysis and monitoring, vulnerability analysis and determination of the risk level. The presented research focuses on drought, which is at the present already the most widespread as well as still unpredictable natural hazard. Its primary aim was to assess the frequency and the consequences of droughts in Slovenia based on drought events in the past, to develop methodology for drought vulnerability and risk assessment that can be applied in Slovenia and wider in South-Eastern Europe, to prepare maps of drought risk and crop vulnerability and to guidelines to reduce the vulnerability of the crops. Using the amounts of plant available water in the soil, slope inclination, solar radiation, land use and irrigation infrastructure data sets as inputs, we obtained vulnerability maps for Slovenia using GIS-based multi-criteria decision analysis with a weighted linear combination of the input parameters. The weight configuration was optimized by comparing the modelled crop damage to the assessed actual damage, which was available for the extensive drought case in 2006. Drought risk was obtained quantitatively as a function of hazard and

  8. Soil degradation in farmlands of California's San Joaquin Valley resulting from drought-induced land-use changes

    NASA Astrophysics Data System (ADS)

    Scudiero, Elia; Skaggs, Todd; Anderson, Ray; Corwin, Dennis

    2016-04-01

    drought years. Root-zone soil salinity was mapped in 1991 using geospatial apparent electrical conductivity measurements and extensive soil sampling and in 2013 using recent root-zone remote sensing salinity map for the WSJV (developed and published by the U.S. Salinity Laboratory, USDA-ARS), which was calibrated and (independently) validated, including fields from the BWD. Results reveal dramatic increases in soil salinity for all the fields that were originally non-saline and slightly-saline in 1991. Additionally, time-series analysis of very-high resolution ortho-imagery (from Google Earth and USGS) suggests that surface soil quality drastically decreased especially during the drought years. Our research shows how terminating irrigation in California's Central Valley can lead to substantial soil salinization in a very short time. Salinization in WSJV due to the termination of irrigation is a consequence of the complex multi-scale interaction of geomorphologic, topographic, and anthropogenic factors requiring yearly monitoring to adequately assess the impacts of drought for use in field- and basin-scale water management decisions. Among other concerns, increased salinity and sodicity affect vegetation growth and may lead to increased soil erosion and very-fine dust formation creating health and environmental hazards.

  9. Climate Change, Drought and Human Health in Canada

    PubMed Central

    Yusa, Anna; Berry, Peter; Cheng, June J.; Ogden, Nicholas; Bonsal, Barrie; Stewart, Ronald; Waldick, Ruth

    2015-01-01

    Droughts have been recorded all across Canada and have had significant impacts on individuals and communities. With climate change, projections suggest an increasing risk of drought in Canada, particularly in the south and interior. However, there has been little research on the impacts of drought on human health and the implications of a changing climate. A review of the Canadian, U.S. and international literature relevant to the Canadian context was conducted to better define these impacts and adaptations available to protect health. Drought can impact respiratory health, mental health, illnesses related to exposure to toxins, food/water security, rates of injury and infectious diseases (including food-, water- and vector-borne diseases). A range of direct and indirect adaptation (e.g., agricultural adaptation) options exist to cope with drought. Many have already been employed by public health officials, such as communicable disease monitoring and surveillance and public education and outreach. However, gaps exist in our understanding of the impacts of short-term vs. prolonged drought on the health of Canadians, projections of drought and its characteristics at the regional level and the effectiveness of current adaptations. Further research will be critical to inform adaptation planning to reduce future drought-related risks to health. PMID:26193300

  10. Climate Change, Drought and Human Health in Canada.

    PubMed

    Yusa, Anna; Berry, Peter; J Cheng, June; Ogden, Nicholas; Bonsal, Barrie; Stewart, Ronald; Waldick, Ruth

    2015-07-17

    Droughts have been recorded all across Canada and have had significant impacts on individuals and communities. With climate change, projections suggest an increasing risk of drought in Canada, particularly in the south and interior. However, there has been little research on the impacts of drought on human health and the implications of a changing climate. A review of the Canadian, U.S. and international literature relevant to the Canadian context was conducted to better define these impacts and adaptations available to protect health. Drought can impact respiratory health, mental health, illnesses related to exposure to toxins, food/water security, rates of injury and infectious diseases (including food-, water- and vector-borne diseases). A range of direct and indirect adaptation (e.g., agricultural adaptation) options exist to cope with drought. Many have already been employed by public health officials, such as communicable disease monitoring and surveillance and public education and outreach. However, gaps exist in our understanding of the impacts of short-term vs. prolonged drought on the health of Canadians, projections of drought and its characteristics at the regional level and the effectiveness of current adaptations. Further research will be critical to inform adaptation planning to reduce future drought-related risks to health.

  11. 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.

  12. The evaporative demand drought index: Part II – CONUS-wide assessment against common drought indicators

    USDA-ARS?s Scientific Manuscript database

    Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought, however other climatic factors such as solar radiation, wind speed, and specific humidity can be important drivers in the depletion of soil moisture and evolution and persistence of dro...

  13. Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.

    PubMed

    Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

    2013-05-01

    Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.

  14. Hyperspectral remote sensing for monitoring species-specific drought impacts in southern California

    NASA Astrophysics Data System (ADS)

    Coates, Austin Reece

    A drought persisting since the winter of 2011-2012 has resulted in severe impacts on shrublands and forests in southern California, USA. Effects of drought on vegetation include leaf wilting, leaf abscission, and potential plant mortality. These impacts vary across plant species, depending on differences in species' adaptations to drought, rooting depth, and edaphic factors. During 2013 and 2014, Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data were acquired seasonally over the Santa Ynez Mountains and Santa Ynez Valley north of Santa Barbara, California. To determine the impacts of drought on individual plant species, spectral mixture analysis was used to model a relative green vegetation fraction (RGVF) for each image date in 2013 and 2014. A July 2011 AVIRIS image acquired during the last nondrought year was used to determine a reference green vegetation (GV) endmember for each pixel. For each image date in 2013 and 2014, a three-endmember model using the 2011 pixel spectrum as GV, a lab nonphotosynthetic vegetation (NPV) spectrum, and a photometric shade spectrum was applied. The resulting RGVF provided a change in green vegetation cover relative to 2011. Reference polygons collected for 14 plant species and land cover classes were used to extract the RGVF values from each date. The deeply rooted tree species and tree species found in mesic areas appeared to be the least affected by the drought, whereas the evergreen chaparral showed the most extreme signs of distress. Coastal sage scrub had large seasonal variability; however, each year, it returned to an RGVF value only slightly below the previous year. By binning all the RGVF values together, a general decreasing trend was observed from the spring of 2013 to the fall of 2014. This study intends to lay the groundwork for future research in the area of multitemporal, hyperspectral remote sensing. With proposed plans for a hyperspectral sensor in space (HyspIRI), this type of research will prove to

  15. 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

  16. 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.

  17. 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.

  18. Monitoring the expression of maize genes in developing kernels under drought stress using oligo-microarray

    USDA-ARS?s Scientific Manuscript database

    Preharvest A. flavus infection is usually exacerbated when maize plants suffer drought stress in the late grain-fill stage. However, the field observation suggests that drought-tolerant maize lines displayed less aflatoxin contamination under the stress in comparison with the drought-sensitive maize...

  19. 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; hide

    2014-01-01

    The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture

  20. 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

  1. Land-atmosphere interaction and disaster-causing process of drought in northern China: observation and experiment (DroughtPEX_China)

    NASA Astrophysics Data System (ADS)

    Li, Yaohui

    2017-04-01

    aims to establish a complete observation &experiment system for droughts particularly over the arid and semi-arid regions in northern China. Relying on the existing meteorological observation network and experimental bases, the DroughtPEX_China implemented interdisciplinary, comprehensive and systemic drought-scientific experiment including the routine observation, intensive and special observation, and the artificially field control test for the drought forming and reducing. Such large observation &experiment will promote a large step or theoretical breakthrough on the knowledge of the complex dynamic process for the formation and development of drought disasters, the mechanism of the water-energy cycle in the atmosphere-soil-vegetation on multi-scales, and the interrelationship in the atmosphere, agriculture and hydrological droughts. The ultimate purpose of DroughtPEX_China is to make great progress on the technology of accurate drought monitoring, risk assessment and early warning. This paper will introduce the Drought PEX_China with the scientific goal, experiment design and layout, preliminary results, information sharing, and its promoting role on international cooperation of drought scientific research. Key words: Disaster-causing process of drought; Observation & experiment; Northern China

  2. 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.

  3. High resolution multi-scalar drought indices for Iberia

    NASA Astrophysics Data System (ADS)

    Russo, Ana; Gouveia, Célia; Trigo, Ricardo; Jerez, Sonia

    2014-05-01

    human resources. The understanding of the present-day underlying mechanisms together with the necessary contextualization within a wider past, is essential to understand future projections, and should lastly rebound on the adequacy of the management decision making. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAG-GLO/4155/2012) Gouveia C., Trigo R.M., DaCamara C.C. (2009) Drought and Vegetation Stress Monitoring in Portugal using Satellite Data, Natural Hazards and Earth System Sciences, 9, 1-11. Giorgi, F. and Lionello, P.; Climate change projections for the Mediterranean region. Global and Planetary Change, 63 (2-3): 90-104, 2008. Vicente-Serrano, Sergio M., Santiago Beguería, Juan I. López-Moreno, 2010: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. Jerez, S., R.M. Trigo, S.M. Vicente-Serrano, D. Pozo-Vázquez, R. Lorente-Plazas, J. Lorenzo-Lacruz, F. Santos-Alamillos and J.P. Montávez (2013). The impact of the North Atlantic Oscillation on the renewable energy resources in south-western Europe. Journal of Applied Meteorology and Climatology, DOI 10.1175/JAMC-D-12-0257.1.

  4. 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

  5. A model of human decision making in multiple process monitoring situations

    NASA Technical Reports Server (NTRS)

    Greenstein, J. S.; Rouse, W. B.

    1982-01-01

    Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.

  6. 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

  7. 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

  8. Monitoring and decision making by people in man machine systems

    NASA Technical Reports Server (NTRS)

    Johannsen, G.

    1979-01-01

    The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

  9. 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.

  10. 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.

  11. 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

  12. Spatio-temporal drought characteristics of the tropical Paraiba do Sul River Basin and responses to the Mega Drought in 2014-2016

    NASA Astrophysics Data System (ADS)

    Nauditt, Alexandra; Metzke, Daniel; Ribbe, Lars

    2017-04-01

    The Paraiba do Sul River Basin (56.000 km2) supplies water to the Brazilian states Sao Paulo and Rio de Janeiro. Their large metropolitan areas were strongly affected by a Mega drought during the years 2014 and 2015 with severe implications for domestic water supply, the hydropower sector as well as for rural agricultural downstream regions. Longer drought periods are expected to become more frequent in the future. However, drought characteristics, low flow hydrology and the reasons for the recurrent water scarcity in this water abundant tropical region are still poorly understood. In order to separate the impact of human abstractions from hydro-climatic and catchment storage related hydrological drought propagation, we assessed the spatio-temporal distribution of drought severity and duration establishing relationships between SPI, SRI and discharge threshold drought anomalies for all subcatchments of the PdS based on a comprehensive hydro-meteorological data set of the Brazilian National Water Agency ANA. The water allocation model "Water Evaluation and Planning System (WEAP)" was established on a monthly basis for the entire Paraiba do Sul river basin incorporating human modifications of the hydrological system as major (hydropower) reservoirs and their operational rules, water diversions and major abstractions. It simulates reasonable discharges and reservoir levels comparable to the observed values. To evaluate the role of climate variability and drought responses for hydrological drought events, scenarios were developed to simulate discharge and reservoir level the impact of 1. Varying meteorological drought frequencies and durations and 2. Implementing operational rules as a response to drought. Uncertainties related to the drought assessment, modelling, parameter and input data were assessed. The outcome of this study for the first time provides an overview on the heterogeneous spatio-temporal drought characteristics of the Paraiba do Sul river basin and

  13. Satellite-guided hydro-economic analysis for integrated management and prediction of the impact of droughts on agricultural regions

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Howitt, R.; Kimball, J. S.

    2013-12-01

    Agricultural activity can exacerbate or buffer the impact of climate variability, especially droughts, on the hydrologic and socioeconomic conditions of rural areas. Potential negative regional impacts of droughts include impoverishment of agricultural regions, deterioration or overuse of water resources, risk of monoculture, and regional dependence on external food markets. Policies that encourage adequate management practices in the face of adverse climatic events are critical to preserve rural livelihoods and to ensure a sustainable future for agriculture. Diagnosing and managing drought effects on agricultural production, on the social and natural environment, and on limited water resources, is highly complex and interdisciplinary. The challenges that decision-makers face to mitigate the impact of water shortage are social, agronomic, economic and environmental in nature and therefore must be approached from an integrated multidisciplinary point of view. Existing observation technologies, in conjunction with models and assimilation methods open the opportunity for novel interdisciplinary analysis tools to support policy and decision making. We present an integrated modeling and observation framework driven by satellite remote sensing and other ancillary information from regional monitoring networks to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, management decisions and socioeconomic policy. The core of this framework is a hydroeconomic model of agricultural production that assimilates remote sensing inputs to quantify the amount of land, water, fertilizer and labor farmers allocate for each crop they choose to grow on a seasonal basis in response to changing climatic conditions, including drought. A regional hydroclimatologic model provides biophysical constraints to an economic model of agricultural production based on a class of models referred to as positive mathematical programming (PMP

  14. 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.

  15. Relationship between crown dieback and drought in the southeastern United States

    Treesearch

    Michael K. Crosby; Zhaofei Fan; Martin A. Spetich; Theodor D. Leininger; Xingang Fan

    2012-01-01

    Forest Health and Monitoring (FHM) and Palmer's Drought Severity Index (PDSI) data were obtained for 11 states in the southeastern United States to assess the relationship between drought and crown dieback. Correlation analyses were performed at the species group and ecoregion levels within the study area. The results indicate a negative correlation between...

  16. 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.

  17. 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.

  18. 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

    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.

  19. Assessing vulnerability to drought: identifying underlying factors across Europe

    NASA Astrophysics Data System (ADS)

    Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia

    2015-04-01

    data from the European Drought Impact Report Inventory. For specific hotpots vulnerability factors are presented also through spider diagrams in order to allow policy and decision makers to identify underlying sources of vulnerability in the European context. This assessment offers an overall picture at a European level that strives to contribute to enhance the understanding of drought vulnerability across Europe.

  20. A Seamless Framework for Global Water Cycle Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

    2013-12-01

    The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions

  1. Home monitoring and decision support for international liver transplant children.

    PubMed

    Song, Bianying; Schulze, Mareike; Goldschmidt, Imeke; Haux, Reinhold; Baumann, Ulrich; Marschollek, Michael

    2013-01-01

    Complications may occur after a liver transplantation, therefore proper monitoring and care in the post-operation phase plays a very important role. Sometimes, monitoring and care for patients from abroad is difficult due to a variety of reasons, e.g., different care facilities. The objective of our research for this paper is to design, implement and evaluate a home monitoring and decision support infrastructure for international children who underwent liver transplant operation. A point-of-care device and the PedsQL questionnaire were used in patients' home environment for measuring the blood parameters and assessing quality of life. By using a tablet PC and a specially developed software, the measured results were able to be transmitted to the health care providers via internet. So far, the developed infrastructure has been evaluated with four international patients/families transferring 38 records of blood test. The evaluation showed that the home monitoring and decision support infrastructure is technically feasible and is able to give timely alarm in case of abnormal situation as well as may increase parent's feeling of safety for their children.

  2. 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

  3. Exploring the linkage between drought, high temperatures, and hydrologic sensitivities: A case study of the 2012 Great Plains drought.

    NASA Astrophysics Data System (ADS)

    Livneh, B.; Hoerling, M. P.

    2014-12-01

    The occurrence of drought is associated with agricultural loss, water supply shortfalls, and other economic impacts. Here we explore the physical relationships between precipitation deficits, high temperatures, and hydrologic responses as a pathway to better anticipate drought impacts. Current methodologies to predict hydrologic scarcity include local monitoring of river flows, remote sensing of land-surface wetness, drought indices, expert judgment, climate indices (e.g. SST-relationships) and the application of hydrologic models. At longer lead times, predictions of drought have most frequently been made on the basis of GCM ensembles, with subsequent downscaling of those to scales over which hydrologic predictions can be made. This study focuses on two important aspects of drought. First, we explore the causal hydro-climatic timeline of a drought event, namely (a) the lack of precipitation, which serves to reduce soil moisture and produce (b) a skewed Bowen ratio, i.e. comparatively more sensible heating (warming) with less ET, resulting in (c) anomalously warm conditions. We seek to assess the extent to which the lack of precipitation contributes to warming temperatures, and the further effects of that warming on hydrology and the severity of drought impacts. An ensemble of GCM simulations will be used to explore the evolution of the land surface energy budget during a recent Great Plains drought event, which will subsequently be used to drive a hydrologic model. Second, we examine the impacts of the critical assumptions relating climatic variables with water demand, specifically the relationship between potential evapotranspiration (PET) and temperature. The common oversimplification in relating PET to temperature is explored against a more physically consistent energy balance estimate of PET, using the Penman-Monteith approach and the hydrologic impacts are presented. Results from this work are anticipated to have broad relevance for future water management

  4. An Updated Decision Support Interface: A Tool for Remote Monitoring of Crop Growing Conditions

    NASA Astrophysics Data System (ADS)

    Husak, G. J.; Budde, M. E.; Rowland, J.; Verdin, J. P.; Funk, C. C.; Landsfeld, M. F.

    2014-12-01

    Remote sensing of agroclimatological variables to monitor food production conditions is a critical component of the Famine Early Warning Systems Network portfolio of tools for assessing food security in the developing world. The Decision Support Interface (DSI) seeks to integrate a number of remotely sensed and modeled variables to create a single, simplified portal for analysis of crop growing conditions. The DSI has been reformulated to incorporate more variables and give the user more freedom in exploring the available data. This refinement seeks to transition the DSI from a "first glance" agroclimatic indicator to one better suited for the differentiation of drought events. The DSI performs analysis of variables over primary agricultural zones at the first sub-national administrative level. It uses the spatially averaged rainfall, normalized difference vegetation index (NDVI), water requirement satisfaction index (WRSI), and actual evapotranspiration (ETa) to identify potential hazards to food security. Presenting this information in a web-based client gives food security analysts and decision makers a lightweight portal for information on crop growing conditions in the region. The crop zones used for the aggregation contain timing information which is critical to the DSI presentation. Rainfall and ETa are accumulated from different points in the crop phenology to identify season-long deficits in rainfall or transpiration that adversely affect the crop-growing conditions. Furthermore, the NDVI and WRSI serve as their own seasonal accumulated measures of growing conditions by capturing vegetation vigor or actual evapotranspiration deficits. The DSI is currently active for major growing regions of sub-Saharan Africa, with intention of expanding to other areas over the coming years.

  5. On the Use of NASA Earth Observations to Characterize the 2012 US Drought

    NASA Technical Reports Server (NTRS)

    Lawford, Richard; Toll, David; Doorn, Bradley; Entin, Jared; Mocko, David; Svoboda, Mark; Rodell, Matthew; Koster, Randy; Schubert, Siegried; Liang, Xin-Zhong; hide

    2013-01-01

    As the harvest season approached in August 2012, much of the United States remained in the grip of a major drought. According to the United States Drought Monitor (USDM), 52 percent of the United States and Puerto Rico was in moderate drought conditions or worse by August 7, 2012 (see Figure 1a). Drought areas were concentrated in the agricultural states in the central U.S.A. The drought threatened global food prices and US biofuel feedstocks. Although areas east of the Mississippi River experienced some relief due to Hurricane Isaac, the drought persisted west of the Mississippi River Basin. The USDA Economic Research Service reports about 80 percent of the US agriculture experienced drought in 2012 making it the most extensive drought since the 1950's. The Financial Times reported 2012 losses at roughly $30 billion dollars. NASA maintains satellite and modelling capabilities that enable the assessment of drought severity and extent on a national and global basis.

  6. A description of nurses' decision-making in managing electrocardiographic monitor alarms.

    PubMed

    Gazarian, Priscilla K; Carrier, Natalie; Cohen, Rachel; Schram, Haley; Shiromani, Samara

    2015-01-01

    To describe the cues and factors that nurses use in their decision-making when responding to clinical alarms. Alarms are designed to be very sensitive, and as a result, they are not very specific. Lack of adherence to the practice standards for electrocardiographic monitoring in hospital settings has been observed, resulting in overuse of the electrocardiographic monitoring. Monitoring without consideration of clinical indicators uses scarce healthcare resources and may even produce untoward circumstances because of alarm fatigue. With so many false alarms, alarm fatigue represents a symptom of a larger problem. It cannot be fixed until all of the factors that contribute to its existence have been examined. This was a qualitative descriptive study. This study was conducted at an academic medical centre located in the Northeast United States. Eight participants were enrolled using purposive sampling. Nurses were observed for two three-hour periods. Following each observation, the nurse was interviewed using the critical decision method to describe the cognitive processes related to the alarm activities. Qualitative data from the conducted interviews were analysed via an a priori framework founded in the critical decision method. This study reveals information, experience, guidance and decision-making as the four prominent categories contributing to nurses' decision-making in relation to alarm management. Managing technology was a category not identified a priori that emerged in the data analysis. Nurses revealed a breadth of information needed to adequately identify and interpret monitor alarms, and how they used that information to put the alarms into the particular context of an individual patient's situations. Understanding the cues and factors nurses use when responding to cardiac alarms will guide the development of learning experiences and inform policies to guide practice. © 2014 John Wiley & Sons Ltd.

  7. Remote Sensing Technologies Mitigate Drought

    NASA Technical Reports Server (NTRS)

    2015-01-01

    Ames Research Center has partnered with the California Department of Water Resources to develop satellite-based technologies to mitigate drought conditions. One project aims to help water managers adjust their irrigation to match the biological needs of each crop, and another involves monitoring areas where land is fallow so emergency relief can more quickly aid affected communities.

  8. Designing basin-customized combined drought indices via feature extraction

    NASA Astrophysics Data System (ADS)

    Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

    2017-04-01

    The socio-economic costs of drought are progressively increasing worldwide due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and how to combine them, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). The W-QEISS algorithm relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables (cardinality) and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of a pre-defined model (i.e., an extreme learning machine) of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The proposed methodology is tested in the case study of Lake Como in northern Italy, a regulated lake mainly operated for irrigation supply to four downstream agricultural districts. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as the most common drought indicators at multiple time aggregations. The soil

  9. Drought, Agriculture, and Labor: Understanding Drought Impacts and Vulnerability in California

    NASA Astrophysics Data System (ADS)

    Greene, C.

    2015-12-01

    Hazardous drought impacts are a product of not only the physical intensity of drought, but also the economic, social, and environmental characteristics of the region exposed to drought. Drought risk management requires understanding the complex links between the physical and human dimensions of drought. Yet, there is a research gap in identifying and explaining the socio-economic complexities of drought in the context of the first world, especially for economic and socially marginal groups who rely on seasonal and temporary jobs. This research uses the current drought in California as a case study to identify the socioeconomic impacts of drought on farmworker communities in California's San Joaquin Valley, with a specific focus on the relationship between drought and agricultural labor. Through both a narrative analysis of drought coverage in newspaper media, drought policy documents, and interviews with farmworkers, farmers, community based organizations, and government officials in the San Joaquin Valley, this research aims to highlight the different understandings and experiences of the human impacts of drought and drought vulnerability in order to better inform drought risk planning and policy.

  10. Evaluation of strategies for nature-based solutions to drought: a decision support model at the national scale

    NASA Astrophysics Data System (ADS)

    Simpson, Mike; Ives, Matthew; Hall, Jim

    2016-04-01

    There is an increasing body of evidence in support of the use of nature based solutions as a strategy to mitigate drought. Restored or constructed wetlands, grasslands and in some cases forests have been used with success in numerous case studies. Such solutions remain underused in the UK, where they are not considered as part of long-term plans for supply by water companies. An important step is the translation of knowledge on the benefits of nature based solutions at the upland/catchment scale into a model of the impact of these solutions on national water resource planning in terms of financial costs, carbon benefits and robustness to drought. Our project, 'A National Scale Model of Green Infrastructure for Water Resources', addresses this issue through development of a model that can show the costs and benefits associated with a broad roll-out of nature based solutions for water supply. We have developed generalised models of both the hydrological effects of various classes and implementations of nature-based approaches and their economic impacts in terms of construction costs, running costs, time to maturity, land use and carbon benefits. Our next step will be to compare this work with our recent evaluation of conventional water infrastructure, allowing a case to be made in financial terms and in terms of security of water supply. By demonstrating the benefits of nature based solutions under multiple possible climate and population scenarios we aim to demonstrate the potential value of using nature based solutions as a component of future long-term water resource plans. Strategies for decision making regarding the selection of nature based and conventional approaches, developed through discussion with government and industry, will be applied to the final model. Our focus is on keeping our work relevant to the requirements of decision-makers involved in conventional water planning. We propose to present the outcomes of our model for the evaluation of nature

  11. Extreme Droughts In Sydney And Melbourne Since The 1850s

    NASA Astrophysics Data System (ADS)

    Dogan, Selim

    2014-05-01

    Sydney and Melbourne are the two highly populated and very well known Australian cities. Population is over 4 million for each. These cities are subject to extreme droughts which affect regional water resources and cause substantial agricultural and economic losses. This study presents a drought analysis of Sydney and Melbourne for the period of 1850s to date by using Effective Drought Index (EDI) and Standardized Precipitation Index (SPI). EDI is a function of precipitation needed for return to normal conditions, the amount of precipitation necessary for recovery from the accumulated deficit since the beginning of a drought. SPI is the most popular and widely used drought index for the last decades. According to the results of EDI analysis; 8 different extreme drought events identified in Sydney, and 5 events in Melbourne since 1850s. The characterization of these extreme drought events were investigated in terms of magnitude, duration, intensity and interarrival time between previous drought event. EDI results were compared with the results of SPI and the similarities and differences were then discussed in more detail. The most severe drought event was identified for the period of July 1979 to February 1981 (lasted 19 months) for Sydney, while the most severe drought took longer in Melbourne for the period of March 2006 to February 2010 (47 months). This study focuses on the benefits of the use of EDI and SPI methods in order to monitor droughts beside presenting the extreme drought case study of Sydney and Melbourne.

  12. 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.

  13. 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

  14. 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

  15. Water monitoring to support the State of Illinois Governor’s Drought Response Task Force – August 24, 2012

    USGS Publications Warehouse

    ,

    2012-01-01

    The U.S. Geological Survey (USGS) collects streamflow, groundwater levels, and water-quality data for the State of Illinois and the Nation. Much of these data are collected every 15 minutes (real-time) as a part of the national network, so that water-resource managers can make decisions in a timely and reliable manner. Coupled with modeling and other water-resource investigations, the USGS provides data to the State during droughts and other hydrologic events. The types of data, capabilities, and presentation of these materials are described in this document as USGS Real-Time Data, Supplementary Data Collection and Analysis, and National Resources Available.

  16. Perception of drought by surface and groundwater farmers: a perspective from Júcar river basin, Spain

    NASA Astrophysics Data System (ADS)

    Urquijo, Julia; De Stefano, Lucia

    2015-04-01

    Irrigation farmers play a key role in water management at all levels and their role becomes even more relevant during droughts, when water systems are under increased pressure. The analysis of farmers' drought perception and of their strategies to reduce vulnerability can contribute to better understand their behavior and concerns, and to better inform decision-making regarding drought management at different scales. This study focuses on the analysis of perception of and response to drought of surface and groundwater irrigation farmers in two areas of the Jucar River Basin (Spain). The results show that the dependence on surface water or groundwater for irrigation highly influences farmers' perception of drought. For surface water farmers, non-climatic factors (e.g. level of reservoirs or impacts on production) are used to describe drought situations more often that precipitation shortfalls, while groundwater irrigators barely feel affected by rainfall variability. Local strategies are highly adapted to local conditions and usually require collective agreements to coordinate individual actions and make them effective. The vulnerability factors differ depending on the source of water used to support irrigation, e.g. being water quality and the cost of water reasons of concern for groundwater farmers while irrigators using surface water are concerned with temporal water shortages and the economic viability of their agricultural activity. The analysis of how farmers relate to and face drought appears also to catch the main water management issues in the River Basin. The results of the study highlight that local knowledge can inform policy makers on the way farmers cope with drought and it can also support decision-making in enhancing drought and water resource management.

  17. Assessing the impacts of droughts on net primary productivity in China.

    PubMed

    Pei, Fengsong; Li, Xia; Liu, Xiaoping; Lao, Chunhua

    2013-01-15

    Frequency and severity of droughts were projected to increase in many regions. However, their effects of temporal dynamics on the terrestrial carbon cycle remain uncertain, and hence deserve further investigation. In this paper, the droughts that occurred in China during 2001-2010 were identified by using the standardized precipitation index (SPI). Standardized anomaly index (SAI), which has been widely employed in reflecting precipitation, was extended to evaluate the anomalies of net primary productivity (NPP). In addition, influences of the droughts on vegetation were explored by examining the temporal dynamics of SAI-NPP along with area-weighted drought intensity at different time scales (1, 3, 6, 9 and 12 months). Year-to-year variability of NPP with several factors, including droughts, NDVI, radiation and temperature, was analyzed as well. Consequently, the droughts in the years 2001, 2006 and 2009 were well reconstructed. This indicates that SPI could be applied to the monitoring of the droughts in China during the past decade (2001-2010) effectively. Moreover, strongest correlations between droughts and NPP anomalies were found during or after the drought intensities reached their peak values. In addition, some droughts substantially reduced the countrywide NPP, whereas the others did not. These phenomena can be explained by the regional diversities of drought intensity, drought duration, areal extents of the droughts, as well as the cumulative and lag responses of vegetation to the precipitation deficits. Besides the drought conditions, normalized difference vegetation index (NDVI), radiation and temperature also contribute to the interannual variability of NPP. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Mapping Regional Drought Vulnerability: a Case Study

    NASA Astrophysics Data System (ADS)

    Karamouz, M.; Zeynolabedin, A.; Olyaei, M. A.

    2015-12-01

    are ranked in 5 intervals and for each parameter vulnerability maps are prepared in GIS environment. Selection of theses parameters are based on factors such as regional features and availability of data. Considering the fact that the aforementioned parameters have different level of importance in vulnerability maps, different weights are assigned to the parameters considering how critical each parameter is in the overall drought analysis. Expert's opinion is selected in assigning weights. A multi-criteria decision making (MCDM) framework is used to check the consistency of the provided information. Then the weighted maps are overlaid to find the overall vulnerability map. The map shows very low, low, medium, intense and very intense regional vulnerabilities. According to the results, the west part of East Azarbaijan province is the most vulnerable region to drought which is expected due to the vicinity of this part to Urumia Lake that has been lost most of its water during the last decades. The least vulnerable part seems to be the Eastern part of the province with longer lasting resources. Taking into consideration that Caspian Sea is near this part with high precipitation record, the outcome of this study is in line with the general expectations. The result of this study can be used for preparedness planning and for allocating resources for facing droughts in this region.

  19. Drought occurence

    Treesearch

    John W. Coulston

    2007-01-01

    Why Is Drought Important? Drought is an important forest disturbance that occurs regularly in the Western United States and irregularly in the Eastern United States (Dale and others 2001). Moderate drought stress tends to slow plant growth while severedrought stress can also reduce photosynthesis (Kareiva and others 1993). Drought can also interact with...

  20. Vulnerability analysis for a drought Early Warning System

    NASA Astrophysics Data System (ADS)

    Angeluccetti, Irene; Demarchi, Alessandro; Perez, Francesca

    2014-05-01

    Early Warning Systems (EWS) for drought are often based on risk models that do not, or marginally, take into account the vulnerability factor. The multifaceted nature of drought (hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. The latter, together with the complexity of impacts generated by this hazard, causes the current underdevelopment of drought EWS compared to other hazards. In Least Developed Countries, where drought events causes the highest numbers of affected people, the importance of correct monitoring and forecasting is considered essential. Existing early warning and monitoring systems for drought produced at different geographic levels, provide only in a few cases an actual spatial model that tries to describe the cause-effect link between where the hazard is detected and where impacts occur. Integrate vulnerability information in such systems would permit to better estimate affected zones and livelihoods, improving the effectiveness of produced hazard-related datasets and maps. In fact, the need of simplification and, in general, of a direct applicability of scientific outputs is still a matter of concern for field experts and early warning products end-users. Even if the surplus of hazard related information produced right after catastrophic events has, in some cases, led to the creation of specific data-sharing platforms, the conveyed meaning and usefulness of each product has not yet been addressed. The present work is an attempt to fill this gap which is still an open issue for the scientific community as well as for the humanitarian aid world. The study aims at conceiving a simplified vulnerability model to embed into an existing EWS for drought, which is based on the monitoring of vegetation phenological parameters and the Standardized Precipitation Index, both produced using free satellite derived datasets. The proposed vulnerability model includes (i) a

  1. Towards an integrated soil moisture drought monitor for East Africa

    USDA-ARS?s Scientific Manuscript database

    Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived mo...

  2. Short-term droughts forecast using Markov chain model in Victoria, Australia

    NASA Astrophysics Data System (ADS)

    Rahmat, Siti Nazahiyah; Jayasuriya, Niranjali; Bhuiyan, Muhammed A.

    2017-07-01

    A comprehensive risk management strategy for dealing with drought should include both short-term and long-term planning. The objective of this paper is to present an early warning method to forecast drought using the Standardised Precipitation Index (SPI) and a non-homogeneous Markov chain model. A model such as this is useful for short-term planning. The developed method has been used to forecast droughts at a number of meteorological monitoring stations that have been regionalised into six (6) homogenous clusters with similar drought characteristics based on SPI. The non-homogeneous Markov chain model was used to estimate drought probabilities and drought predictions up to 3 months ahead. The drought severity classes defined using the SPI were computed at a 12-month time scale. The drought probabilities and the predictions were computed for six clusters that depict similar drought characteristics in Victoria, Australia. Overall, the drought severity class predicted was quite similar for all the clusters, with the non-drought class probabilities ranging from 49 to 57 %. For all clusters, the near normal class had a probability of occurrence varying from 27 to 38 %. For the more moderate and severe classes, the probabilities ranged from 2 to 13 % and 3 to 1 %, respectively. The developed model predicted drought situations 1 month ahead reasonably well. However, 2 and 3 months ahead predictions should be used with caution until the models are developed further.

  3. Impacts of drought on grape yields in Western Cape, South Africa

    NASA Astrophysics Data System (ADS)

    Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

    2016-01-01

    Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on

  4. 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.

  5. 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

  6. Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

    NASA Technical Reports Server (NTRS)

    Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae; hide

    2015-01-01

    As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles

  7. 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.

  8. New drought indices from the assimilation of satellite data

    NASA Astrophysics Data System (ADS)

    Calvet, Jean-Christophe; Barbu, Alina; Fairbairn, David

    2016-04-01

    The current agricultural drought indicators produced by Meteo-France are derived from digital simulations of soil moisture produced by the SURFEX modelling platform. In the framework of the IMAGINES European project, a research was conducted in order to assess the impact on the monitoring of agricultural droughts of the integration of satellite data into SURFEX. A data assimilation system was implemented to this end. It provides simulations of the biomass and leaf area index of straw cereals and grasslands over France. It is shown that these simulations can be improved through the assimilation of satellite products distributed in near-real-time by the Copernicus Global Land service (http://land.copernicus.eu/global/). Reference in situ observations of the agricultural yields show that using satellite data, a significant correlation between the maximum annual above-ground biomass simulated by SURFEX and the agricultural yield at the scale of administrative units (départements) can be achieved. Without satellite data, very low correlations are observed. It is also shown that new 10-day drought indicators, complementary to soil moisture, can be derived from the leaf area index and from the above-ground biomass of vegetation. These demonstration drought monitoring products for the 2008-2013 period are freely available on the project web site (http://fp7-imagines.eu/) for 45 administrative units for cereals and for 48 administrative units for grasslands.

  9. Water Decisions for Sustainability of the Arbuckle-Simpson Aquifer

    NASA Astrophysics Data System (ADS)

    Lazrus, H.; Mcpherson, R. A.; Morss, R. E.; PaiMazumder, D.; Silvis, V.; Towler, E.

    2012-12-01

    The Arbuckle-Simpson Aquifer in south-central Oklahoma, situated in the heart of the Chickasaw Nation, is the state's only sole-source groundwater basin and sustains the Blue River, the state's only freeflowing river. The recent comprehensive hydrological studies of the aquifer indicate the need for sustainable management of the amount of water extracted. However, the question of how to deal with that management in the face of increasing drought vulnerability, diverse demands, and climate variability and change remains. Water management carries a further imperative to be inclusive of tribal and non-tribal interests. To address these issues, this interdisciplinary project takes an integrated approach to understanding risk perceptions and water decisions for sustainability of the Arbuckle-Simpson Aquifer. Our interdisciplinary research asks: How do stakeholders in the Arbuckle-Simpson Aquifer perceive drought risks across weather and climate scales, and how do these perceptions guide water management decisions given (i) diverse cultural beliefs, (ii) valued hydrologic services, (iii) past drought experience, and (iv) uncertainties in future projection of precipitation and drought? We will use ethnographic methods to diagnose how cultural values and beliefs inform risk perceptions, and how this in turn guides decision making or ignites conflict across different sectors and stakeholder groups. Further, the characterization of drought risk will be examined in the context of historic meteorological and hydrologic events, as well as climate variability and change. This will identify which risks are prioritized, and under what conditions, in regional decision making or water-related conflicts.

  10. Design and Application of Drought Indexes in Highly Regulated Mediterranean Water Systems

    NASA Astrophysics Data System (ADS)

    Castelletti, A.; Zaniolo, M.; Giuliani, M.

    2017-12-01

    Costs of drought are progressively increasing due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and combinatione thereof, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). W-QEISS relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of an extreme learning machine of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The approach is tested on Lake Como, Italy, a regulated lake mainly operated for irrigation supply. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that

  11. Identification of drought in Dhalai river watershed using MCDM and ANN models

    NASA Astrophysics Data System (ADS)

    Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

    2017-03-01

    An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

  12. Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

    2015-12-01

    A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

  13. 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.

  14. Atmospheric Infrared Sounder on NASA's Aqua Satellite: Applications for Volcano Rapid Response, Influenza Outbreak Prediction, and Drought Onset Prediction

    NASA Astrophysics Data System (ADS)

    Ray, S. E.; Fetzer, E. J.; Lambrigtsen, B.; Olsen, E. T.; Licata, S. J.; Hall, J. R.; Penteado, P. F.; Realmuto, V. J.; Thrastarson, H. T.; Teixeira, J.; Granger, S. L.; Behrangi, A.; Farahmand, A.

    2017-12-01

    The Atmospheric Infrared Sounder (AIRS) has been returning daily global observations of Earth's atmospheric constituents and properties since 2002. With its 15-year data record and near real-time capability, AIRS data are being used in the development of applications that fall within many of the NASA Applied Science focus areas. An automated alert system for volcanic plumes has been developed that triggers on threshold breaches of SO2, ash and dust in granules of AIRS data. The system generates a suite of granule-scale maps that depict both plume and clouds, all accessible from the AIRS web site. Alerts are sent to a curated list of volcano community members, and links to views in NASA Worldview and Google Earth are also available. Seasonal influenza epidemics are major public health concern with millions of cases of severe illness and large economic impact. Recent studies have highlighted the role of absolute or specific humidity as a likely player in the seasonal nature of these outbreaks. A quasi-operational influenza outbreak prediction system has been developed based on the SIRS model which uses AIRS and NCEP humidity data, Center for Disease Control reports on flu and flu-like illnesses, and results from Google Flu Trends. Work is underway to account for diffusion (spatial) in addition to the temporal spreading of influenza. The US Drought Monitor (USDM) is generated weekly by the National Drought Mitigation Center (NDMC) and is used by policymakers for drought decision-making. AIRS data have demonstrated utility in monitoring the development and detection of meteorological drought with both AIRS-derived standardized vapor pressure deficit and standardized relative humidity, showing early detection lead times of up to two months. An agreement was secured with the NDMC to begin a trial period using AIRS products in the production of the USDM, and in July of 2017 the operational delivery of weekly CONUS AIRS images of Relative Humidity, Surface Air Temperature

  15. 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.

  16. Characterizing Drought Events from a Hydrological Model Ensemble

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    detection and characterization. This ensemble approach allows for uncertainty estimates and confidence intervals to be explored in simulations of drought event characteristics, such as duration and severity, which would not otherwise be available from a deterministic approach. The acquired understanding of uncertainty in drought events may then be applied to historic drought reconstructions, supplying evidence which could prove vital in decision making scenarios.

  17. 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

  18. 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

  19. Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

    USGS Publications Warehouse

    Austin, Samuel H.; Nelms, David L.

    2017-01-01

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

  20. Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment

    NASA Astrophysics Data System (ADS)

    Ahmadalipour, Ali; Moradkhani, Hamid

    2017-12-01

    Hydrologic modeling is one of the primary tools utilized for drought monitoring and drought early warning systems. Several sources of uncertainty in hydrologic modeling have been addressed in the literature. However, few studies have assessed the uncertainty of gridded observation datasets from a drought monitoring perspective. This study provides a hydrologic modeling oriented analysis of the gridded observation data uncertainties over the Pacific Northwest (PNW) and its implications on drought assessment. We utilized a recently developed 100-member ensemble-based observed forcing data to simulate hydrologic fluxes at 1/8° spatial resolution using Variable Infiltration Capacity (VIC) model, and compared the results with a deterministic observation. Meteorological and hydrological droughts are studied at multiple timescales over the basin, and seasonal long-term trends and variations of drought extent is investigated for each case. Results reveal large uncertainty of observed datasets at monthly timescale, with systematic differences for temperature records, mainly due to different lapse rates. The uncertainty eventuates in large disparities of drought characteristics. In general, an increasing trend is found for winter drought extent across the PNW. Furthermore, a ∼3% decrease per decade is detected for snow water equivalent (SWE) over the PNW, with the region being more susceptible to SWE variations of the northern Rockies than the western Cascades. The agricultural areas of southern Idaho demonstrate decreasing trend of natural soil moisture as a result of precipitation decline, which implies higher appeal for anthropogenic water storage and irrigation systems.

  1. Environmental change challenges decision-making during post-market environmental monitoring of transgenic crops.

    PubMed

    Sanvido, Olivier; Romeis, Jörg; Bigler, Franz

    2011-12-01

    The ability to decide what kind of environmental changes observed during post-market environmental monitoring of genetically modified (GM) crops represent environmental harm is an essential part of most legal frameworks regulating the commercial release of GM crops into the environment. Among others, such decisions are necessary to initiate remedial measures or to sustain claims of redress linked to environmental liability. Given that consensus on criteria to evaluate 'environmental harm' has not yet been found, there are a number of challenges for risk managers when interpreting GM crop monitoring data for environmental decision-making. In the present paper, we argue that the challenges in decision-making have four main causes. The first three causes relate to scientific data collection and analysis, which have methodological limits. The forth cause concerns scientific data evaluation, which is controversial among the different stakeholders involved in the debate on potential impacts of GM crops on the environment. This results in controversy how the effects of GM crops should be valued and what constitutes environmental harm. This controversy may influence decision-making about triggering corrective actions by regulators. We analyse all four challenges and propose potential strategies for addressing them. We conclude that environmental monitoring has its limits in reducing uncertainties remaining from the environmental risk assessment prior to market approval. We argue that remaining uncertainties related to adverse environmental effects of GM crops would probably be assessed in a more efficient and rigorous way during pre-market risk assessment. Risk managers should acknowledge the limits of environmental monitoring programmes as a tool for decision-making.

  2. Drought and the water-energy nexus in Texas

    NASA Astrophysics Data System (ADS)

    Scanlon, Bridget R.; Duncan, Ian; Reedy, Robert C.

    2013-12-01

    Texas experienced the most extreme drought on record in 2011 with up to 100 days of triple digit temperatures resulting in record electricity demand and historically low reservoir levels. We quantified water and electricity demand and supply for each power plant during the drought relative to 2010 (baseline). Drought raised electricity demands/generation by 6%, increasing water demands/consumption for electricity by 9%. Reductions in monitored reservoir storage <50% of capacity in 2011 would suggest drought vulnerability, but data show that the power plants were flexible enough at the plant level to adapt by switching to less water-intensive technologies. Natural gas, now ˜50% of power generation in Texas, enhances drought resilience by increasing the flexibility of power plant generators, including gas combustion turbines to complement increasing wind generation and combined cycle generators with ˜30% of cooling water requirements of traditional steam turbine plants. These reductions in water use are projected to continue to 2030 with increased use of natural gas and renewables. Although water use for gas production is controversial, these data show that water saved by using natural gas combined cycle plants relative to coal steam turbine plants is 25-50 times greater than the amount of water used in hydraulic fracturing to extract the gas.

  3. Environmental and physiological effects on grouping of drought-tolerant and susceptible rice varieties related to rice (Oryza sativa) root hydraulics under drought

    PubMed Central

    Henry, Amelia; Wehler, Regina; Grondin, Alexandre; Franke, Rochus; Quintana, Marinell

    2016-01-01

    Background and Aims Root hydraulic limitations (i.e. intra-plant restrictions to water movement) may be related to crop performance under drought, and groupings in the hydraulic function of drought-tolerant and drought-susceptible rice (Oryza sativa) varieties have been previously reported. This study aimed to better understand the environmental and physiological relationships with rice root hydraulics under drought. Methods Xylem sap bleeding rates in the field (gsap g–1 shoot) were measured on seasonal and diurnal time frames, during which time environmental conditions were monitored and physiological measurements were conducted. Complementary experiments on the effects of vapour pressure deficit (VPD) on root hydraulic conductivity and on transpiration rates of de-rooted tillers were conducted in growth chambers. Key Results The diurnal effects on bleeding rate were more closely related to irradiance than VPD, and VPD effects on root hydraulic conductivity measured on 21-day-old plants were due to effects on plant growth including root surface area, maximum root depth and root:shoot ratio. Leaf osmotic potential was related to the grouping of drought-tolerant and drought-susceptible varieties in rice root hydraulics, and these groupings were independent of differences in phenology. Low single-tiller bleeding rates were observed under high evapo-transpirational demand, higher bleeding rates were observed at more negative leaf osmotic potentials in drought-susceptible varieties, and drought-tolerant and susceptible varieties differed in the VPD-induced increase in transpiration rates of de-rooted tillers. Low root suberin amounts in some of the drought-susceptible varieties may have resulted in higher ion transport, as evidenced by higher sap K+ concentration and higher bleeding rates in those varieties. Conclusions These results provide evidence of the environmental effects on shoots that can influence root hydraulics. The consistent groupings of drought

  4. Environmental and physiological effects on grouping of drought-tolerant and susceptible rice varieties related to rice (Oryza sativa) root hydraulics under drought.

    PubMed

    Henry, Amelia; Wehler, Regina; Grondin, Alexandre; Franke, Rochus; Quintana, Marinell

    2016-05-02

    Root hydraulic limitations (i.e. intra-plant restrictions to water movement) may be related to crop performance under drought, and groupings in the hydraulic function of drought-tolerant and drought-susceptible rice (Oryza sativa) varieties have been previously reported. This study aimed to better understand the environmental and physiological relationships with rice root hydraulics under drought. Xylem sap bleeding rates in the field (g sap g -1 shoot ) were measured on seasonal and diurnal time frames, during which time environmental conditions were monitored and physiological measurements were conducted. Complementary experiments on the effects of vapour pressure deficit (VPD) on root hydraulic conductivity and on transpiration rates of de-rooted tillers were conducted in growth chambers. The diurnal effects on bleeding rate were more closely related to irradiance than VPD, and VPD effects on root hydraulic conductivity measured on 21-day-old plants were due to effects on plant growth including root surface area, maximum root depth and root:shoot ratio. Leaf osmotic potential was related to the grouping of drought-tolerant and drought-susceptible varieties in rice root hydraulics, and these groupings were independent of differences in phenology. Low single-tiller bleeding rates were observed under high evapo-transpirational demand, higher bleeding rates were observed at more negative leaf osmotic potentials in drought-susceptible varieties, and drought-tolerant and susceptible varieties differed in the VPD-induced increase in transpiration rates of de-rooted tillers. Low root suberin amounts in some of the drought-susceptible varieties may have resulted in higher ion transport, as evidenced by higher sap K + concentration and higher bleeding rates in those varieties. These results provide evidence of the environmental effects on shoots that can influence root hydraulics. The consistent groupings of drought-tolerant and susceptible varieties suggest that traits

  5. An approach to drought data web-dissemination

    NASA Astrophysics Data System (ADS)

    Angeluccetti, Irene; Perez, Francesca; Balbo, Simone; Cámaro, Walther; Boccardo, Piero

    2017-04-01

    Drought data dissemination has always been a challenge for the scientific community. Firstly, a variety of widely known datasets is currently being used to describe different aspects of this same phenomenon. Secondly, new indexes are constantly being produced by scientists trying to better capture drought events. The present work aims at presenting how the drought monitoring communication issue was addressed by the ITHACA team. The ITHACA drought monitoring system makes use of two indicators: the Standardized Precipitation Index (SPI) and the Seasonal Small Integral Deviation (SSID). The first one is obtained considering the 3-months cumulating interval of the rainfall derived from the TRMM dataset; the second one is the percent deviation from the historical average value of the integral of the NDVI function describing the vegetation season. The SPI and the SSID are 30 and 5 km gridded respectively. The whole time-series of these two indicators (since year 2000 onwards), covering the whole Africa, are published by a WebGIS platform (http://drought.ithacaweb.org). On the one hand, although the SPI has been used for decades in different contexts and little explanation is due when presenting this indicator to an audience with a scientific background, the WebGIS platform shows a guide for its correct interpretation. On the other hand, being the SSID not commonly used in the field of vegetation analysis, the guide shown on the WebGIS platform is essential for the visitor to understand the data. Recently a new index has been created in order to synthesize, for a non-expert audience, the information provided by the indicators. It is aggregated per second order administrative levels and is calculated as follows: (i) a meteorological drought warning is issued when negative SPI and no vegetative season is detected (a blue palette is used); (ii) a warning value is assigned if SSID, SPI, or both, are negative (amber to brown palette is used) i.e., where the vegetative season

  6. 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

  7. Impact of advanced monitoring variables on intraoperative clinical decision-making: an international survey.

    PubMed

    Joosten, Alexandre; Desebbe, Olivier; Suehiro, Koichi; Essiet, Mfonobong; Alexander, Brenton; Ricks, Cameron; Rinehart, Joseph; Faraoni, David; Cecconi, Maurizio; Van der Linden, Philippe; Cannesson, Maxime

    2017-02-01

    To assess the relationship between the addition of advanced monitoring variables and changes in clinical decision-making. A 15-questions survey was anonymously emailed to international experts and physician members of five anesthesia societies which focused on assessing treatment decisions of clinicians during three realistic clinical scenarios measured at two distinct time points. The first is when typical case information and basic monitoring (T1) were provided, and then once again after the addition of advanced monitoring variables (T2). We hypothesized that the addition of advanced variables would increase the incidence of an optimal therapeutic decision (a priori defined as the answer with the highest percentage of expert agreement) and decrease the variability among the physician's suggested treatments. The survey was completed by 18 experts and 839 physicians. Overall, adding advanced monitoring did not significantly increase physician response accuracy, with the least substantial changes noted on questions related to volume expansion or vasopressor administration. Moreover, advanced monitoring data did not significantly decrease the high level of initial practice variability in physician suggested treatments (P = 0.13), in contrast to the low variability observed within the expert group (P = 0.039). Additionally, 5-10 years of practice (P < 0.0001) and a cardiovascular subspecialty (P = 0.048) were both physician characteristics associated with a higher rate of optimal therapeutic decisions. The addition of advanced variables was of limited benefit for most physicians, further indicating the need for more in depth education on the clinical value and technical understanding of such variables.

  8. 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.

  9. Hydraulic Function in Australian Tree Species during Drought-Induced Mortality

    NASA Astrophysics Data System (ADS)

    Tissue, D.; Maier, C.; Creek, D.; Choat, B.

    2016-12-01

    Drought induced tree mortality and decline are key issues facing forest ecology and management. Here, we primarily investigated the hydraulic limitations underpinning drought-induced mortality in three Australian tree species. Using field-based large rainout shelters, three angiosperm species (Casuarina cunninghamiana, Eucalyptus sideroxylon, Eucalyptus tereticornis) were subjected to two successive drought and recovery cycles, prior to a subsequent long and extreme drought to mortality; total duration of experiment was 2.5 years. Leaf gas exchange, leaf and stem hydraulics, and carbon reserves were monitored during the experiment. Trees died as a result of failure in the hydraulic transport system, primarily related to water stress induced embolism. Stomatal closure occurred prior to the induction of significant embolism in the stem xylem of all species. Nonetheless, trees suffered a rapid decline in xylem water potential and increase in embolism during the severe drought treatment. Trees died at water potentials causing greater than 90% loss of hydraulic conductivity in the stem, providing support for the theory that lethal water potential is correlated with complete loss of hydraulic function in the stem xylem of angiosperms.

  10. Drought in Northeast Brazil—past, present, and future

    NASA Astrophysics Data System (ADS)

    Marengo, Jose A.; Torres, Roger Rodrigues; Alves, Lincoln Muniz

    2017-08-01

    This study provides an overview of the drought situation in Northeast Brazil for the past, present, and future. Droughts affect more people than any other natural hazard owing to their large scale and long-lasting nature. They are recurrent in the region and while some measures have been taken by the governments to mitigate their impacts, there is still a perception that residents, mainly in rural areas, are not yet adapted to these hazards. The drought affecting the Northeast from 2012 to 2015, however, has had an intensity and impact not seen in several decades and has already destroyed large swaths of cropland, affecting hundreds of cities and towns across the region, and leaving ranchers struggling to feed and water cattle. Future climate projections for the area show large temperature increases and rainfall reductions, which, together with a tendency for longer periods with consecutive dry days, suggest the occurrence of more frequent/intense dry spells and droughts and a tendency toward aridification in the region. All these conditions lead to an increase in evaporation from reservoirs and lakes, affecting irrigation and agriculture as well as key water uses including hydropower and industry, and thus, the welfare of the residents. Integrating drought monitoring and seasonal forecasting provides efficient means of assessing impacts of climate variability and change, identifying vulnerabilities, and allowing for better adaptation measures not only for medium- and long-term climate change but also for extremes of the interannual climate variability, particularly droughts.

  11. Spatiotemporal drought forecasting using nonlinear models

    NASA Astrophysics Data System (ADS)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    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. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. 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. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  12. Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

    NASA Astrophysics Data System (ADS)

    Van Loon, Anne F.; Stahl, Kerstin; Di Baldassarre, Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko; Gleeson, Tom; Van Dijk, Albert I. J. M.; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Adriaan J.; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; Wagener, Thorsten; Van Lanen, Henny A. J.

    2016-09-01

    In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include

    • (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to

    • Fuzzy rule-based forecast of meteorological drought in western Niger

      NASA Astrophysics Data System (ADS)

      Abdourahamane, Zakari Seybou; Acar, Reşat

      2018-01-01

      Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R 2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α < 0.05 level) to the SPI-3. Moreover, the implemented fuzzy model compared to decision tree-based forecast model shows better forecast skills.

    • An online tool for Operational Probabilistic Drought Forecasting System (OPDFS): a Statistical-Dynamical Framework

      NASA Astrophysics Data System (ADS)

      Zarekarizi, M.; Moradkhani, H.; Yan, H.

      2017-12-01

      The Operational Probabilistic Drought Forecasting System (OPDFS) is an online tool recently developed at Portland State University for operational agricultural drought forecasting. This is an integrated statistical-dynamical framework issuing probabilistic drought forecasts monthly for the lead times of 1, 2, and 3 months. The statistical drought forecasting method utilizes copula functions in order to condition the future soil moisture values on the antecedent states. Due to stochastic nature of land surface properties, the antecedent soil moisture states are uncertain; therefore, data assimilation system based on Particle Filtering (PF) is employed to quantify the uncertainties associated with the initial condition of the land state, i.e. soil moisture. PF assimilates the satellite soil moisture data to Variable Infiltration Capacity (VIC) land surface model and ultimately updates the simulated soil moisture. The OPDFS builds on the NOAA's seasonal drought outlook by offering drought probabilities instead of qualitative ordinal categories and provides the user with the probability maps associated with a particular drought category. A retrospective assessment of the OPDFS showed that the forecasting of the 2012 Great Plains and 2014 California droughts were possible at least one month in advance. The OPDFS offers a timely assistance to water managers, stakeholders and decision-makers to develop resilience against uncertain upcoming droughts.

    • 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

    • System robustness analysis for drought risk management in South Florida

      NASA Astrophysics Data System (ADS)

      Eilander, D.; Bouwer, L.; Barnes, J.; Mens, M.; Obeysekera, J.

      2015-12-01

      Drought is a frequently returning natural hazard in Florida, with at least one severe drought to be expected every decade. These droughts have had many impacts such as loss of agricultural products, inadequate public water supply and salt water intrusion into freshwater aquifers. Furthermore, climate change projections for South Florida suggest that dry spells are likely to be more frequent and prolonged, with negative impacts on water supply management for all users. In this study a System Robustness Analysis was conducted in order to analyse the effectiveness of strategies to limit the socio-economic impact of droughts under climate change. System Robustness Analysis (SRA) aims to support decision making by quantifying how well a system, with and without additional measures, can remain functioning under a range of external disturbances. Two system characteristics add up to system robustness: Resistance is the ability to withstand disturbances without responding (zero impact), and resilience is the ability to recover from the response to a disturbance. SRA can help to provide insight into the sensitivity of a system to changing magnitudes of extreme weather events. A regional-scale hydrologic and water management model is used to simulate the effect of changing precipitation and evaporation forcing on agricultural and urban water supply and demand in South Florida. The complex water management operational rules including water use restrictions are simulated in the model. Based on model runs with a various climate scenarios, drought events with a wide range of severity are identified and for each event the socio-economic impacts are determined. Here, a drought is defined as a reduced streamflow in the upstream Kissimmee basin, which contributes most to Lake Okeechobee, the major surface water storage in the system. The drought severity is characterized by the maximum drought deficit volume. Drought impacts are analyzed for several users in Miami Dade County. From

    • The relative influence of climate and catchment properties on hydrological drought

      NASA Astrophysics Data System (ADS)

      Van Loon, Anne; Laaha, Gregor; Koffler, Daniel

      2014-05-01

      Studying hydrological drought (a below-normal water availability in groundwater, lakes and streams) is important to society and the ecosystem, but can also reveal interesting information about catchment functioning. This information can later be used for predicting drought in ungauged basins and to inform water management decisions. In this study, we used an extensive Austrian dataset of discharge measurements in clusters of catchments and combine this dataset with thematic information on climate and catchment properties. Our aim was to study the relative effects of climate and catchment characteristics on drought duration and deficit and on hydrological drought typology. Because the climate of the region is roughly uniform, our hypothesis was that the effect of differences of catchment properties would stand out. From time series of precipitation and discharge we identified droughts with the widely-used threshold level approach, defining a drought when a variable falls below a pre-defined threshold representing the regime. Drought characteristics that were analysed are drought duration and deficit. We also applied the typology of Van Loon & Van Lanen (2012). To explain differences in drought characteristics between catchments we did a correlation analysis with climate and catchment characteristics, based on Pearson correlation. We found very interesting patterns in the correlations of drought characteristics with climate and catchment properties: 1) Droughts with long duration (mean and maximum) and composite droughts are related to catchments with a high BFI (high baseflow) and a high percentage of shallow groundwater tables. 2) The deficit (mean and maximum) of both meteorological droughts and hydrological droughts is strongly related to catchment humidity, in this case quantified by average annual precipitation. 3) The hydrological drought types that are related to snow, i.e. cold snow season drought and snow melt drought, occur in catchments that are have a

    • Multi-index time series monitoring of drought and fire effects on desert grasslands

      USGS Publications Warehouse

      Villarreal, Miguel; Norman, Laura M.; Buckley, Steven; Wallace, Cynthia S.A.; Coe, Michelle A.

      2016-01-01

      The Western United States is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change and it is important to understand how these disturbances will interact and affect recovery and composition of plant communities in the future. In this research paper we describe the temporal response of grassland communities to drought and fire in southern Arizona, where land managers are using repeated, prescribed fire as a habitat restoration tool. Using a 25-year atlas of fire locations, we paired sites with multiple fires to unburned control areas and compare satellite and field-based estimates of vegetation cover over time. Two hundred and fifty Landsat TM images, dating from 1985–2011, were used to derive estimates of Total Vegetation Fractional Cover (TVFC) of live and senescent grass using the Soil-Adjusted Total Vegetation Index (SATVI) and post-fire vegetation greenness using the Normalized Difference Vegetation Index (NDVI). We also implemented a Greenness to Cover Index that is the difference of time-standardized SATVI-TVFC and NDVI values at a given time and location to identify post-fire shifts in native, non-native, and annual plant cover. The results highlight anomalous greening and browning during drought periods related to amounts of annual and non-native plant cover present. Results suggest that aggressive application of prescribed fire may encourage spread of non-native perennial grasses and annual plants, particularly during droughts.

    • Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

      USGS Publications Warehouse

      Husak, Gregory J.; Michaelsen, Joel C.; Funk, Christopher C.

      2007-01-01

      Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov–Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa. 

    • 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

  1. Hydrologic Droughts in Kansas - Are They Becoming Worse?

    USGS Publications Warehouse

    Putnam, James E.; Perry, Charles A.; Wolock, David M.

    2008-01-01

    Multi-year droughts have been a recurrent feature of the climate and hydrology of Kansas since at least the 1930s. Streamflow records collected by the U.S. Geological Survey (USGS) indicate that water years 2000 to 2006 (October 1, 1999, through September 30, 2006) represent the sixth hydrologic drought during the past eight decades, and that corresponding streamflow levels in some parts of Kansas were lower than those during historic droughts of the 1930s and 1950s, even though the precipitation deficit was not as severe. Record-low streamflows in water year 2006 were recorded at USGS streamgages on the Republican, Smoky Hill, Solomon, Saline, upper Kansas, middle Arkansas, and Little Arkansas Rivers, as well as many tributary sites, and one tributary site of the Neosho River (fig. 1, table 1). Low streamflows during the hydrologic drought also resulted in record low levels at three Federal reservoirs in Kansas (fig. 1, table 2). An unprecedented number of administrative decisions were made by the Division of Water Resources, Kansas Department of Agriculture to curtail water diversions from rivers to maintain minimum desirable streamflows, and low flows on the lower Republican River in Kansas created concerns that Colorado and Nebraska were not complying with the terms of the 1943 Republican River Compact.

  2. Towards a Seamless Framework for Drought Analysis and Prediction from Seasonal to Climate Change Time Scales (Plinius Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Sheffield, Justin

    2013-04-01

    Droughts arguably cause the most impacts of all natural hazards in terms of the number of people affected and the long-term economic costs and ecosystem stresses. Recent droughts worldwide have caused humanitarian and economic problems such as food insecurity across the Horn of Africa, agricultural economic losses across the central US and loss of livelihoods in rural western India. The prospect of future increases in drought severity and duration driven by projected changes in precipitation patterns and increasing temperatures is worrisome. Some evidence for climate change impacts on drought is already being seen for some regions, such as the Mediterranean and east Africa. Mitigation of the impacts of drought requires advance warning of developing conditions and enactment of drought plans to reduce vulnerability. A key element of this is a drought early warning system that at its heart is the capability to monitor evolving hydrological conditions and water resources storage, and provide reliable and robust predictions out to several months, as well as the capacity to act on this information. At longer time scales, planning and policy-making need to consider the potential impacts of climate change and its impact on drought risk, and do this within the context of natural climate variability, which is likely to dominate any climate change signal over the next few decades. There are several challenges that need to be met to advance our capability to provide both early warning at seasonal time scales and risk assessment under climate change, regionally and globally. Advancing our understanding of drought predictability and risk requires knowledge of drought at all time scales. This includes understanding of past drought occurrence, from the paleoclimate record to the recent past, and understanding of drought mechanisms, from initiation, through persistence to recovery and translation of this understanding to predictive models. Current approaches to monitoring and

  3. Drought Information Supported by Citizen Scientists (DISCS)

    NASA Astrophysics Data System (ADS)

    Molthan, A.; Maskey, M.; Hain, C.; Meyer, P.; Nair, U. S.; Handyside, C. T.; White, K.; Amin, M.

    2017-12-01

    Each year, drought impacts various regions of the United States on time scales of weeks, months, seasons, or years, which in turn leads to a need to document these impacts and inform key decisions on land management, use of water resources, and disaster response. Mapping impacts allows decision-makers to understand potential damage to agriculture and loss of production, to communicate and document drought impacts on crop yields, and to inform water management decisions. Current efforts to collect this information includes parsing of media reports, collaborations with local extension offices, and partnerships with the National Weather Service cooperative observer network. As part of a NASA Citizen Science for Earth Systems proposal award, a research and applications team from Marshall Space Flight Center, the University of Alabama in Huntsville, and collaborators within the NWS have developed a prototype smartphone application focused on the collection of citizen science observations of crop health and drought impacts, along with development of innovative low-cost soil moisture sensors to supplement subjective assessments of local soil moisture conditions. Observations provided by citizen scientists include crop type and health, phase of growth, soil moisture conditions, irrigation status, along with an optional photo and comment to provide visual confirmation and other details. In exchange for their participation, users of the app also have access to unique land surface modeling data sets produced at MSFC such as the NASA Land Information System soil moisture and climatology/percentile products from the Short-term Prediction Research and Transition (SPoRT) Center, assessments of vegetation health and stress from NASA and NOAA remote sensing platforms (e.g. MODIS/VIIRS), outputs from a crop stress model developed at the University of Alabama in Huntsville, recent rainfall estimates from the NOAA/NWS network of ground-based weather radars, and other observations made

  4. Drought allocations using the Systems Impact Assessment Model: Klamath River

    USGS Publications Warehouse

    Flug, M.; Campbell, S.G.

    2005-01-01

    Water supply and allocation scenarios for the Klamath River, Ore. and Calif., were evaluated using the Systems Impact Assessment Model (SIAM), a decision support system developed by the U.S. Geological Survey. SIAM is a set of models with a graphical user interface that simulates water supply and delivery in a managed river system, water quality, and fish production. Simulation results are presented for drought conditions, one aspect of Klamath River water operations. The Klamath River Basin has experienced critically dry conditions in 1992, 1994, and 2001. Drought simulations are useful to estimate the impacts of specific legal or institutional flow constraints. In addition, simulations help to identify potential adverse water quality consequences including evaluating the potential for reducing adverse temperature impacts on anadromous fish. In all drought simulations, water supply was insufficient to fully meet upstream and downstream targets for endangered species.

  5. Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

    USDA-ARS?s Scientific Manuscript database

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this ...

  6. Using mobile health technology to deliver decision support for self-monitoring after lung transplantation.

    PubMed

    Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A

    2016-10-01

    Lung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH(®), a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators. To examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation. A cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support. Of the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n=23) were less likely to follow technology decision support than the high (odds ratio [OR]=0.11, p=0.02) and low (OR=0.04, p=0.02) use groups. The odds of following decision

  7. Social influences on reality-monitoring decisions.

    PubMed

    Hoffman, H G; Granhag, P A; Kwong See, S T; Loftus, E F

    2001-04-01

    A modified Asch (1951) conformity paradigm was used to study the impact of social influence on reality-monitoring decisions about new items. Subjects studied pictures of some objects and imagined others. In a later test phase, they judged whether items had been perceived in the study phase, had been imagined, or were new. Critically, for some items, the subjects were informed of a confederate's response before rendering a judgment. Although the confederate was always correct when they responded to old items, for new items, the confederate responded perceived, imagined, or new, or did not respond (baseline). In two experiments, we show that memory for new items was influenced by an erroneous response of the confederate. Social conformity was reduced by undermining the credibility of the confederate (Experiments 1A and 1B), and the confederate's influence was evident even after there was only a 20-min delay between study and test (Experiment 2), when the subjects were 87% accurate on new baseline items. These experiments reveal the power of social influence on reality-monitoring accuracy and confidence.

  8. 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

  9. Experimental evidence for drought induced alternative stable states of soil moisture

    NASA Astrophysics Data System (ADS)

    Robinson, David. A.; Jones, Scott B.; Lebron, Inma; Reinsch, Sabine; Domínguez, María T.; Smith, Andrew R.; Jones, Davey L.; Marshall, Miles R.; Emmett, Bridget A.

    2016-01-01

    Ecosystems may exhibit alternative stable states (ASS) in response to environmental change. Modelling and observational data broadly support the theory of ASS, however evidence from manipulation experiments supporting this theory is limited. Here, we provide long-term manipulation and observation data supporting the existence of drought induced alternative stable soil moisture states (irreversible soil wetting) in upland Atlantic heath, dominated by Calluna vulgaris (L.) Hull. Manipulated repeated moderate summer drought, and intense natural summer drought both lowered resilience resulting in shifts in soil moisture dynamics. The repeated moderate summer drought decreased winter soil moisture retention by ~10%. However, intense summer drought, superimposed on the experiment, that began in 2003 and peaked in 2005 caused an unexpected erosion of resilience and a shift to an ASS; both for the experimental drought manipulation and control plots, impairing the soil from rewetting in winter. Measurements outside plots, with vegetation removal, showed no evidence of moisture shifts. Further independent evidence supports our findings from historical soil moisture monitoring at a long-term upland hydrological observatory. The results herald the need for a new paradigm regarding our understanding of soil structure, hydraulics and climate interaction.

  10. Experimental evidence for drought induced alternative stable states of soil moisture

    PubMed Central

    Robinson, David. A.; Jones, Scott B.; Lebron, Inma; Reinsch, Sabine; Domínguez, María T.; Smith, Andrew R.; Jones, Davey L.; Marshall, Miles R.; Emmett, Bridget A.

    2016-01-01

    Ecosystems may exhibit alternative stable states (ASS) in response to environmental change. Modelling and observational data broadly support the theory of ASS, however evidence from manipulation experiments supporting this theory is limited. Here, we provide long-term manipulation and observation data supporting the existence of drought induced alternative stable soil moisture states (irreversible soil wetting) in upland Atlantic heath, dominated by Calluna vulgaris (L.) Hull. Manipulated repeated moderate summer drought, and intense natural summer drought both lowered resilience resulting in shifts in soil moisture dynamics. The repeated moderate summer drought decreased winter soil moisture retention by ~10%. However, intense summer drought, superimposed on the experiment, that began in 2003 and peaked in 2005 caused an unexpected erosion of resilience and a shift to an ASS; both for the experimental drought manipulation and control plots, impairing the soil from rewetting in winter. Measurements outside plots, with vegetation removal, showed no evidence of moisture shifts. Further independent evidence supports our findings from historical soil moisture monitoring at a long-term upland hydrological observatory. The results herald the need for a new paradigm regarding our understanding of soil structure, hydraulics and climate interaction. PMID:26804897

  11. An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

    PubMed

    Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

    2017-08-11

    We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision

  12. Hydrologic and human aspects of the 1976-77 drought

    USGS Publications Warehouse

    Matthai, Howard F.

    1979-01-01

    The drought of 1976-77 was the most severe in at least 50 years in many parts of the United States. Record low amounts of rainfall, snowfall, and runoff, and increased withdrawals of ground water were prevalent. The use of carry-over storage in reservoirs during 1976 maintained streamflow at near normal levels, but some reservoirs went dry or dropped below the outlet works in 1977. Carry-over storage in the fall of 1977 was very low. Ground-water levels were at or near record low levels in many aquifers, hundreds of wells went dry, and thousands of wells were drilled. Yet no wide-spread deterioration of ground-water quality was reported. Water-quality problems arose in some streams and lakes, but most were localized and of short duration. Water rationing became a way of life in numerous areas , and water was hauled in many rural areas and to a few towns. Water use was affected by legal agreements or decisions, some of which were modified for the duration of the drought, and by the inability of water managers to efficiently manage surface and ground waters as one resource under existing law. There are still many drought related problems to solve and many challenges to be met before the next drought occurs. The advancement of techniques in many fields of endeavor in recent years plus ongoing, planned, and proposed research on drought and the risks involved are promising thrusts that should make it easier to cope with the next drought. (Kosco-USGS)

  13. Integrating an agent-based model into a large-scale hydrological model for evaluating drought management in California

    NASA Astrophysics Data System (ADS)

    Sheffield, J.; He, X.; Wada, Y.; Burek, P.; Kahil, M.; Wood, E. F.; Oppenheimer, M.

    2017-12-01

    California has endured record-breaking drought since winter 2011 and will likely experience more severe and persistent drought in the coming decades under changing climate. At the same time, human water management practices can also affect drought frequency and intensity, which underscores the importance of human behaviour in effective drought adaptation and mitigation. Currently, although a few large-scale hydrological and water resources models (e.g., PCR-GLOBWB) consider human water use and management practices (e.g., irrigation, reservoir operation, groundwater pumping), none of them includes the dynamic feedback between local human behaviors/decisions and the natural hydrological system. It is, therefore, vital to integrate social and behavioral dimensions into current hydrological modeling frameworks. This study applies the agent-based modeling (ABM) approach and couples it with a large-scale hydrological model (i.e., Community Water Model, CWatM) in order to have a balanced representation of social, environmental and economic factors and a more realistic representation of the bi-directional interactions and feedbacks in coupled human and natural systems. In this study, we focus on drought management in California and considers two types of agents, which are (groups of) farmers and state management authorities, and assumed that their corresponding objectives are to maximize the net crop profit and to maintain sufficient water supply, respectively. Farmers' behaviors are linked with local agricultural practices such as cropping patterns and deficit irrigation. More precisely, farmers' decisions are incorporated into CWatM across different time scales in terms of daily irrigation amount, seasonal/annual decisions on crop types and irrigated area as well as the long-term investment of irrigation infrastructure. This simulation-based optimization framework is further applied by performing different sets of scenarios to investigate and evaluate the effectiveness

  14. Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

    NASA Technical Reports Server (NTRS)

    Li, Bailing; Rodell, Matthew; Zaitchik, Benjamin F.; Reichle, Rolf H.; Koster, Randal D.; van Dam, Tonie M.

    2012-01-01

    A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

  15. Comparative proteome analysis of drought-sensitive and drought-tolerant rapeseed roots and their hybrid F1 line under drought stress.

    PubMed

    Mohammadi, Payam Pour; Moieni, Ahmad; Komatsu, Setsuko

    2012-11-01

    Rapeseed (Brassica napus L.), which is the third leading source of vegetable oil, is sensitive to drought stress during the early vegetative growth stage. To investigate the initial response of rapeseed to drought stress, changes in the protein expression profiles of drought-sensitive (RGS-003) and drought-tolerant lines (SLM-003), and their F1 hybrid, were analyzed using a proteomics approach. Seven-day-old rapeseed seedlings were treated with drought stress by restricting water for 7 days, and proteins were extracted from roots and separated by two-dimensional polyacrylamide gel electrophoresis. In the sensitive rapeseed line, 35 protein spots were differentially expressed under drought stress, and proteins related to metabolism, energy, disease/defense, and transport were decreased. In the tolerant line, 32 protein spots were differentially expressed under drought stress, and proteins involved in metabolism, disease/defense, and transport were increased, while energy-related proteins were decreased. Six protein spots in F1 hybrid were common among expressed proteins in the drought-sensitive and -tolerant lines. Notably, tubulin beta-2 and heat shock protein 70 were decreased in the drought-sensitive line and hybrid F1 plants, while jasmonate-inducible protein and 20S proteasome subunit PAF1 were increased in the F1 hybrids and drought-tolerant line. These results indicate that (1) V-type H(+) ATPase, plasma-membrane associated cation-binding protein, HSP 90, and elongation factor EF-2 have a role in the drought tolerance of rapeseed; (2) The decreased levels of heat shock protein 70 and tubulin beta-2 in the drought-sensitive and hybrid F1 lines might explain the reduced growth of these lines in drought conditions.

  16. Informing Decisions with a Climate Synthesis Product: Implications for Regional Climate Services

    NASA Astrophysics Data System (ADS)

    Guido, Z.; Hill, D.; Crimmins, M.; Ferguson, D. B.

    2012-12-01

    The demand for regional climate information is increasing and spurring efforts to provide a broad slate of climate services that inform policy and resource management and elevate general knowledge. Routine syntheses of existing climate-related information may be an effective strategy for connecting climate information to decision making, but few studies have formally assessed their contribution to informing decisions. During the 2010-2011 winter, drought conditions expanded and intensified in Arizona and New Mexico, creating an opportunity to develop and evaluate a pithy, monthly regional climate communication product—La Niña Drought Tracker—that synthesized and interpreted drought and climate information. Six issues were published and subsequently evaluated through an online survey. On average, 417 people consulted the publication each month. Many of the survey respondents indicated that they made at least one drought-related decision, and the product at least moderately influenced the majority of those decisions, some of which helped mitigate economic losses and reduce climate vulnerability. The product also improved understanding of climate and drought for more than 90 percent of the respondents and helped the majority of them better prepare for drought. These, and other results demonstrate that routine interpretation and synthesis of existing climate information can help enhance access to and understanding and use of climate information in decision-making. Moreover, developing regional, contextual knowledge within climate service programs can facilitate the implementation of activities like the Tracker that enhance the use of climate information without engaging in time-consuming collaborative processes that can prevent the timely production of the services. We present results from the case study of the Tracker and place it within the context of the challenges and opportunities associated with providing climate services, particularly those services that

  17. Tropical river suspended sediment and solute dynamics in storms during an extreme drought

    NASA Astrophysics Data System (ADS)

    Clark, Kathryn E.; Shanley, James B.; Scholl, Martha A.; Perdrial, Nicolas; Perdrial, Julia N.; Plante, Alain F.; McDowell, William H.

    2017-05-01

    Droughts, which can strongly affect both hydrologic and biogeochemical systems, are projected to become more prevalent in the tropics in the future. We assessed the effects of an extreme drought during 2015 on stream water composition in the Luquillo Mountains of Puerto Rico. We demonstrated that drought base flow in the months leading up to the study was sourced from trade-wind orographic rainfall, suggesting a resistance to the effects of an otherwise extreme drought. In two catchments (Mameyes and Icacos), we sampled a series of four rewetting events that partially alleviated the drought. We collected and analyzed dissolved constituents (major cations and anions, organic carbon, and nitrogen) and suspended sediment (inorganic and organic matter (particulate organic carbon and particulate nitrogen)). The rivers appeared to be resistant to extreme drought, recovering quickly upon rewetting, as (1) the concentration-discharge (C-Q) relationships deviated little from the long-term patterns; (2) "new water" dominated streamflow during the latter events; (3) suspended sediment sources had accumulated in the channel during the drought flushed out during the initial events; and (4) the severity of the drought, as measured by the US drought monitor, was reduced dramatically after the rewetting events. Through this interdisciplinary study, we were able to investigate the impact of extreme drought through rewetting events on the river biogeochemistry.

  18. Tropical river suspended sediment and solute dynamics in storms during an extreme drought

    USGS Publications Warehouse

    Clark, Kathryn E.; Shanley, James B.; Scholl, Martha A.; Perdrial, Nicolas; Perdrial, Julia N.; Plante, Alain F.; McDowell, William H.

    2017-01-01

    Droughts, which can strongly affect both hydrologic and biogeochemical systems, are projected to become more prevalent in the tropics in the future. We assessed the effects of an extreme drought during 2015 on stream water composition in the Luquillo Mountains of Puerto Rico. We demonstrated that drought base flow in the months leading up to the study was sourced from trade-wind orographic rainfall, suggesting a resistance to the effects of an otherwise extreme drought. In two catchments (Mameyes and Icacos), we sampled a series of four rewetting events that partially alleviated the drought. We collected and analyzed dissolved constituents (major cations and anions, organic carbon, and nitrogen) and suspended sediment (inorganic and organic matter (particulate organic carbon and particulate nitrogen)). The rivers appeared to be resistant to extreme drought, recovering quickly upon rewetting, as (1) the concentration-discharge (C-Q) relationships deviated little from the long-term patterns; (2) “new water” dominated streamflow during the latter events; (3) suspended sediment sources had accumulated in the channel during the drought flushed out during the initial events; and (4) the severity of the drought, as measured by the US drought monitor, was reduced dramatically after the rewetting events. Through this interdisciplinary study, we were able to investigate the impact of extreme drought through rewetting events on the river biogeochemistry.

  19. Response of surface and groundwater on meteorological drought in Topla River catchment, Slovakia

    NASA Astrophysics Data System (ADS)

    Fendekova, Miriam; Fendek, Marian; Vrablikova, Dana; Blaskovicova, Lotta; Slivova, Valeria; Horvat, Oliver

    2016-04-01

    upper gauging station in Bardejov lasts usually longer than in Hanusovce nad Toplou station being located downstream. Higher number of short-term droughts was estimated for groundwater head in one monitoring well with the smallest depth of groundwater head below the surface. In this case, the influence of evapotranspiration could be the reason. More long-term droughts were estimated by TLM method for groundwater heads in other seven monitoring wells. Those droughts lasted for tens of weeks since summer until the spring of the next year. No regularity in temporal groundwater head drought propagation downstream the Topla River was discovered. However, results of the cluster analysis showed some common features of long-term drought periods (more than 100 days) occurrence for two groups of wells. Different hydrogeological conditions in two evaluated wells were also reflected in drought periods number and severity. The research was financially supported by APVV-0089-12 project (principal investigator Miriam Fendekova).

  20. A national-scale analysis of the impacts of drought on water quality in UK rivers

    NASA Astrophysics Data System (ADS)

    Coxon, G.; Howden, N. J. K.; Freer, J. E.; Whitehead, P. G.; Bussi, G.

    2015-12-01

    Impacts of droughts on water quality qre difficult to quanitify but are essential to manage ecosystems and maintain public water supply. During drought, river water quality is significantly changed by increased residence times, reduced dilution and enhanced biogeochemical processes. But, the impact severity varies between catchments and depends on multiple factors including the sensitivity of the river to drought conditions, anthropogenic influences in the catchment and different delivery patterns of key nutrient, contaminant and mineral sources. A key constraint is data availability for key water quality parameters such that impacts of drought periods on certain determinands can be identified. We use national-scale water quality monitoring data to investigate the impacts of drought periods on water quality in the United Kingdom (UK). The UK Water Quality Sampling Harmonised Monitoring Scheme (HMS) dataset consists of >200 UK sites with weekly to monthly sampling of many water quality variables over the past 40 years. This covers several major UK droughts in 1975-1976, 1983-1984,1989-1992, 1995 and 2003, which cover severity, spatial and temporal extent, and how this affects the temporal impact of the drought on water quality. Several key water quality parameters, including water temperature, nitrate, dissolved organic carbon, orthophosphate, chlorophyll and pesticides, are selected from the database. These were chosen based on their availability for many of the sites, high sampling resolution and importance to the drinking water function and ecological status of the river. The water quality time series were then analysed to investigate whether water quality during droughts deviated significantly from non-drought periods and examined how the results varied spatially, for different drought periods and for different water quality parameters. Our results show that there is no simple conclusion as to the effects of drought on water quality in UK rivers; impacts are

  1. 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

  2. A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

    PubMed

    Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

    2016-10-07

    Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

  3. A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

    PubMed Central

    Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

    2016-01-01

    Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. PMID:27713530

  4. Reconstruction of droughts in India using multiple land-surface models (1951-2015)

    NASA Astrophysics Data System (ADS)

    Mishra, Vimal; Shah, Reepal; Azhar, Syed; Shah, Harsh; Modi, Parth; Kumar, Rohini

    2018-04-01

    India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socio-economic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of

  5. 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.

  6. Pulse-drought atop press-drought: unexpected plant responses and implications for dryland ecosystems.

    PubMed

    Hoover, David L; Duniway, Michael C; Belnap, Jayne

    2015-12-01

    In drylands, climate change is predicted to cause chronic reductions in water availability (press-droughts) through reduced precipitation and increased temperatures as well as increase the frequency and intensity of short-term extreme droughts (pulse-droughts). These changes in precipitation patterns may have profound ecosystem effects, depending on the sensitivities of the dominant plant functional types (PFTs). Here we present the responses of four Colorado Plateau PFTs to an experimentally imposed, 4-year, press-drought during which a natural pulse-drought occurred. Our objectives were to (1) identify the drought sensitivities of the PFTs, (2) assess the additive effects of the press- and pulse-drought, and (3) examine the interactive effects of soils and drought. Our results revealed that the C3 grasses were the most sensitive PFT to drought, the C3 shrubs were the most resistant, and the C4 grasses and shrubs had intermediate drought sensitivities. Although we expected the C3 grasses would have the greatest response to drought, the higher resistance of C3 shrubs relative to the C4 shrubs was contrary to our predictions based on the higher water use efficiency of C4 photosynthesis. Also, the additive effects of press- and pulse-droughts caused high morality in C3 grasses, which has large ecological and economic ramifications for this region. Furthermore, despite predictions based on the inverse texture hypothesis, we observed no interactive effects of soils with the drought treatment on cover or mortality. These results suggest that plant responses to droughts in drylands may differ from expectations and have large ecological effects if press- and pulse-droughts push species beyond physiological and mortality thresholds.

  7. Improved tolerance to post-anthesis drought stress by pre-drought priming at vegetative stages in drought-tolerant and -sensitive wheat cultivars.

    PubMed

    Abid, Muhammad; Tian, Zhongwei; Ata-Ul-Karim, Syed Tahir; Liu, Yang; Cui, Yakun; Zahoor, Rizwan; Jiang, Dong; Dai, Tingbo

    2016-09-01

    Wheat crop endures a considerable penalty of yield reduction to escape the drought events during post-anthesis period. Drought priming under a pre-drought stress can enhance the crop potential to tolerate the subsequent drought stress by triggering a faster and stronger defense mechanism. Towards these understandings, a set of controlled moderate drought stress at 55-60% field capacity (FC) was developed to prime the plants of two wheat cultivars namely Luhan-7 (drought tolerant) and Yangmai-16 (drought sensitive) during tillering (Feekes 2 stage) and jointing (Feekes 6 stage), respectively. The comparative response of primed and non-primed plants, cultivars and priming stages was evaluated by applying a subsequent severe drought stress at 7 days after anthesis. The results showed that primed plants of both cultivars showed higher potential to tolerate the post-anthesis drought stress through improved leaf water potential, more chlorophyll, and ribulose-1, 5-bisphosphate carboxylase/oxygenase contents, enhanced photosynthesis, better photoprotection and efficient enzymatic antioxidant system leading to less yield reductions. The primed plants of Luhan-7 showed higher capability to adapt the drought stress events than Yangmai-16. The positive effects of drought priming to sustain higher grain yield were pronounced in plants primed at tillering than those primed at jointing. In consequence, upregulated functioning of photosynthetic apparatus and efficient enzymatic antioxidant activities in primed plants indicated their superior potential to alleviate a subsequently occurring drought stress, which contributed to lower yield reductions than non-primed plants. However, genotypic and priming stages differences in response to drought stress also contributed to affect the capability of primed plants to tolerate the post-anthesis drought stress conditions in wheat. Copyright © 2016. Published by Elsevier Masson SAS.

  8. Pinus sylvestris switches respiration substrates under shading but not during drought

    NASA Astrophysics Data System (ADS)

    Hartmann, Henrik; Fischer, Sarah; Hanf, Stefan; Frosch, Torsten; Poppp, Jürgen; Trumbore, Susan

    2015-04-01

    Reduced carbon assimilation during prolonged drought forces trees to rely on stored carbon to maintain vital processes like respiration. It has been shown, however, that the use of carbohydrates, a major carbon storage pool and main respiratory substrate in plants, strongly declines with deceasing plant hydration. Yet, no empirical evidence has been produced to what degree other carbon storage compounds like lipids and proteins may fuel respiration during drought. We exposed young scots pine trees to carbon limitation using either drought or shading and assessed respiratory substrate use by monitoring the respiratory quotient, δ13C of respired CO2and concentrations of the major storage compounds, i.e. carbohydrates (COH), lipids and amino acids. Generally, respiration was dominated by the most abundant substrate. Only shaded trees shifted from carbohydrate-dominated to lipid-dominated respiration and showed progressive carbohydrate depletion. In drought trees respiration was strongly reduced and fueled with carbohydrates from also strongly reduced carbon assimilation. Initial COH content was maintained during drought probably due to reduced COH mobilization and use and the maintained COH content may have prevented lipid catabolism via sugar signaling. Our results suggest that respiratory substrates other than carbohydrates are used under carbohydrate limitation but not during drought. Thus, respiratory substrate change cannot provide an efficient means to counterbalance carbon limitation under natural drought.

  9. Quantifying the Impact of the 2015-2016 El Niño Event on California's Historic Drought to Improve Water Resource Management

    NASA Astrophysics Data System (ADS)

    Zajic, B. N.; Lawrence, J.; Gutowski, L.; Rousseau, N. J.; Reager, J. T., II; Jackson, M. E.; Laber, J. L.; Dumas, J. L.

    2016-12-01

    2015 marked the arrival of the strongest El Niño ever recorded, surpassing the 1997-1998 event that brought significant precipitation to the southwestern United States. As sea surface temperatures in the Central Pacific increased, it was forecasted that the 2015 event may have similar effects and alleviate what the US Drought Monitor classified as "exceptional" drought across the majority of the state of California. However, the impacts of the drought, now in its fifth year, continue to strain California water supplies. This study utilized data from NASA's Gravity Recovery and Climate Experiment (GRACE) Earth Observation, meteorological ground observations from the National Oceanic and Atmospheric Administration (NOAA), reservoir levels from the California Department of Water Resources (DWR), and the Oceanic Niño Index (ONI) to better quantify impacts of the 2015-16 El Niño event in the state of California. Specifically, monthly measurements of terrestrial water storage (TWS) from GRACE allowed for a more complete estimate of drought recovery throughout the state over the course of the 2016 water year. TWS was correlated with NOAA precipitation data (nClimDiv) in order to quantify the total current water deficit across the state. This relationship also permits the projection of future drought in California under various possible ENSO-driven precipitation scenarios. While analysis shows that ONI is not a sufficient metric for forecasting precipitation on a statewide basis, the various scenarios provide insight into the potential future of California's aggregated water resources. With drought in the Southwestern US projected to increase in general intensity, frequency, and duration, quantitative assessments of statewide water resources are becoming increasingly important. NASA GRACE TWS hydrological data presents a uniquely integrated measure to inform resource managers and decision makers.

  10. Limitations on gas exchange recovery following natural drought in Californian oak woodlands.

    NASA Astrophysics Data System (ADS)

    Ackerly, D.; Skelton, R. P.; Dawson, T.; Thompson, S.; Feng, X.; Weitz, A.; McLaughlin, B.

    2017-12-01

    Abstract Background/Question/Methods Drought can cause major damage to plant communities, but species damage thresholds and post-drought recovery of forest productivity are not yet predictable. We asked the question how should forest net primary productivity recover following exposure to severe drought? We used a natural drought period to investigate whether drought responses and post-drought recovery of canopy health could be predicted by properties of the water transport system. We aimed to test the hypothesis that recovery of gas exchange and canopy health would be most severely limited by xylem embolism in stems. To do this we monitored leaf level gas exchange and water status for multiple individuals of two deciduous and two evergreen species for four years spanning a severe drought event and following subsequent rehydration. Results/Discussion Severe drought caused major declines in leaf water potential, reduced stomatal conductance and assimilation rates and increased canopy bareness in our four canopy species. Water potential surpassed levels associated with incipient embolism in leaves of most trees. In contrast, due to hydraulic segmentation, water potential only rarely surpassed critical thresholds in the stems of the study trees. Individuals that surpassed critical thresholds of embolism in the stem displayed significant canopy dieback and mortality. Thus, recovery of plant gas exchange and canopy health was predicted by xylem safety margin in stems, but not leaves, providing strong support for stem cavitation vulnerability as an index of damage under natural drought conditions.

  11. An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

    PubMed

    Fan, Bi; Li, Han-Xiong; Hu, Yong

    2016-02-01

    Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

  12. 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.

  13. Pulse-drought atop press-drought: unexpected plant responses and implications for dryland ecosystems

    USGS Publications Warehouse

    Hoover, David L.; Duniway, Michael C.; Belnap, Jayne

    2015-01-01

    In drylands, climate change is predicted to cause chronic reductions in water availability (press-droughts) through reduced precipitation and increased temperatures as well as increase the frequency and intensity of short-term extreme droughts (pulse-droughts). These changes in precipitation patterns may have profound ecosystem effects, depending on the sensitivities of the dominant plant functional types (PFTs). Here we present the responses of four Colorado Plateau PFTs to an experimentally imposed, 4-year, press-drought during which a natural pulse-drought occurred. Our objectives were to (1) identify the drought sensitivities of the PFTs, (2) assess the additive effects of the press- and pulse-drought, and (3) examine the interactive effects of soils and drought. Our results revealed that the C3 grasses were the most sensitive PFT to drought, the C3shrubs were the most resistant, and the C4 grasses and shrubs had intermediate drought sensitivities. Although we expected the C3 grasses would have the greatest response to drought, the higher resistance of C3 shrubs relative to the C4 shrubs was contrary to our predictions based on the higher water use efficiency of C4 photosynthesis. Also, the additive effects of press- and pulse-droughts caused high morality in C3 grasses, which has large ecological and economic ramifications for this region. Furthermore, despite predictions based on the inverse texture hypothesis, we observed no interactive effects of soils with the drought treatment on cover or mortality. These results suggest that plant responses to droughts in drylands may differ from expectations and have large ecological effects if press- and pulse-droughts push species beyond physiological and mortality thresholds.

  14. Probabilistic estimates of drought impacts on agricultural production

    NASA Astrophysics Data System (ADS)

    Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

    2017-08-01

    Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

  15. 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

  16. CreativeDrought: An interdisciplinary approach to building resilience to drought

    NASA Astrophysics Data System (ADS)

    Rangecroft, Sally; Van Loon, Anne; Rohse, Melanie; Day, Rosie; Birkinshaw, Stephen; Makaya, Eugine

    2017-04-01

    Drought events cause severe water and food insecurities in many developing countries where resilience to natural hazards and change is low due to a number of reasons (including poverty, social and political inequality, and limited access to information). Furthermore, with climate change and increasing pressures from population and societal change, populations are expected to experience future droughts outside of their historic range. Integrated water resources management is an established tool combining natural science, engineering and management to help address drought and associated impacts. However, it often lacks a strong social and cultural aspect, leading to poor implementation on the ground. For a more holistic approach to building resilience to future drought, a stronger interdisciplinary approach is required which can incorporate the local cultural context and perspectives into drought and water management, and communicate information effectively to communities. In this pilot project 'CreativeDrought', we use a novel interdisciplinary approach aimed at building resilience to future drought in rural Africa by combining hydrological modelling with rich local information and engaging communicative approaches from social sciences. The work is conducted through a series of steps in which we i) engage with local rural communities to collect narratives on drought experiences; ii) generate hydrological modelling scenarios based on IPCC projections, existing data and the collected narratives; iii) feed these back to the local community to gather their responses to these scenarios; iv) iteratively adapt them to obtain hypothetical future drought scenarios; v) engage the community with the scenarios to formulate new future drought narratives; and vi) use this new data to enhance local water resource management. Here we present some of the indigenous knowledge gathered through narratives and the hydrological modelling scenarios for a rural community in Southern Africa

  17. Drought impacts on cereal yields in Iberia

    NASA Astrophysics Data System (ADS)

    Gouveia, Célia; Liberato, Margarida L. R.; Russo, Ana; Montero, Irene

    2014-05-01

    Spain in both considered drought events, however slightly less severe for 2012 than for 2005. In conclusion, and from an operational point of view, our results reveal the ability of the developed methodology to monitor droughts' impacts on crops productions and yields in Iberia. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAG-GLO/4155/2012) Garcia-Herrera R., Paredes D., Trigo R. M., Trigo I. F., Hernandez E., Barriopedro D. and Mendes M. A., 2007: The Outstanding 2004/05 Drought in the Iberian Peninsula: Associated Atmospheric Circulation, J. Hydrometeorol., 8, 483-498. Vicente-Serrano, Sergio M., Santiago Beguería, Juan I. López-Moreno, 2010: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. Trigo R.M., Añel J., Barriopedro D., García-Herrera R., Gimeno L., Nieto R., Castillo R., Allen M.R., Massey N. (2013), The record Winter drought of 2011-12 in the Iberian Peninsula [in "Explaining Extreme Events of 2012 from a Climate Perspective". [Peterson, T. C., M. P. Hoerling, P.A. Stott and S. Herring, Eds.] Bulletin of the American Meteorological Society, 94 (9), S41-S45.

  18. Assessing the skill of seasonal meteorological forecast products for predicting droughts and water scarcity in highly regulated basins

    NASA Astrophysics Data System (ADS)

    Squeri, Marika; Giuliani, Matteo; Castelletti, Andrea; Pulido-Velazquez, Manuel; Marcos-Garcia, Patricia; Macian-Sorribes, Hector

    2017-04-01

    Drought and water scarcity are important issues in Southern Europe and many predictions suggest that their frequency and severity will increase over the next years, potentially leading to negative environmental and socio-economic impacts. This work focuses on the Jucar river basin, located in the hinterland of Valencia (Eastern Spain), which is historically affected by long and severe dry periods that negatively impact several economic sectors, with irrigated agriculture representing the main consumptive demand in the basin (79%). Monitoring drought and water scarcity is crucial to activate timely drought management strategies in the basin. However, most traditional drought indexes fail in detecting critical events due to the large presence of human regulation supporting the irrigated agriculture. Over the last 20 years, a sophisticated drought monitoring system has been set up to properly capture the status of the catchment by means of the state index, a weighted linear combination of twelve indicators that depends on observations of precipitation, streamflow, reservoirs' storages and groundwater levels in representative locations at the basin. In this work, we explore the possibility of predicting the state index, which is currently used only as a monitoring tool, in order to prompt anticipatory actions before the drought/water scarcity event starts. In particular, we test the forecasting skill of retrospective seasonal meteorological predictions from the European Centre for Medium-range Weather Forecasts (ECMWF) System 4. The 7-months lead time of these products allows predicting in February the values of the state index until September, thus covering the entire agricultural season. Preliminary results suggest that the Sys4-ECMWF products are skillful in predicting the state index, potentially supporting the design of anticipatory drought management actions.

  19. Monitoring Natural World Heritage Sites: optimization of the monitoring system in Bogda with GIS-based multi-criteria decision analysis.

    PubMed

    Wang, Zhaoguo; Du, Xishihui

    2016-07-01

    Natural World Heritage Sites (NWHSs) are invaluable treasure due to the uniqueness of each site. Proper monitoring and management can guarantee their protection from multiple threats. In this study, geographic information system (GIS)-based multi-criteria decision analysis (GIS-MCDA) was used to assess criteria layers acquired from the data available in the literature. A conceptual model for determining the priority area for monitoring in Bogda, China, was created based on outstanding universal values (OUV) and expert knowledge. Weights were assigned to each layer using the analytic hierarchy process (AHP) based on group decisions, encompassing three experts: one being a heritage site expert, another a forest ranger, and the other a heritage site manager. Subsequently, evaluation layers and constraint layers were used to generate a priority map and to determine the feasibility of monitoring in Bogda. Finally, a monitoring suitability map of Bogda was obtained by referencing priority and feasibility maps.The high-priority monitoring area is located in the montane forest belt, which exhibits high biodiversity and is the main tourist area of Bogda. The northern buffer zone of Bogda comprises the concentrated feasible monitoring areas, and the area closest to roads and monitoring facilities is highly feasible for NWHS monitoring. The suitability of an area in terms of monitoring is largely determined by the monitoring priority in that particular area. The majority of planned monitoring facilities are well distributed in both suitable and less suitable areas. Analysis results indicate that the protection of Bogda will be more scientifically based due to its effective and all-around planned monitoring system proposed by the declaration text of Xinjiang Tianshan, which is the essential file submitted to World Heritage Centre to inscribe as a NWHS.

  20. 43 CFR 4190.1 - Effect of wildfire management decisions.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Effect of wildfire management decisions... ALASKA Effect of Wildfire Management Decisions § 4190.1 Effect of wildfire management decisions. (a... on the public lands are at substantial risk of wildfire due to drought, fuels buildup, or other...

  1. 43 CFR 4190.1 - Effect of wildfire management decisions.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Effect of wildfire management decisions... ALASKA Effect of Wildfire Management Decisions § 4190.1 Effect of wildfire management decisions. (a... on the public lands are at substantial risk of wildfire due to drought, fuels buildup, or other...

  2. 43 CFR 4190.1 - Effect of wildfire management decisions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Effect of wildfire management decisions... ALASKA Effect of Wildfire Management Decisions § 4190.1 Effect of wildfire management decisions. (a... on the public lands are at substantial risk of wildfire due to drought, fuels buildup, or other...

  3. 43 CFR 4190.1 - Effect of wildfire management decisions.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Effect of wildfire management decisions... ALASKA Effect of Wildfire Management Decisions § 4190.1 Effect of wildfire management decisions. (a... on the public lands are at substantial risk of wildfire due to drought, fuels buildup, or other...

  4. 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.

  5. 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.

  6. 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.

  7. Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

    PubMed

    Peterson, James T; Freeman, Mary C

    2016-12-01

    Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

  8. 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

  9. Optimization of Evaporative Demand Models for Seasonal Drought Forecasting

    NASA Astrophysics Data System (ADS)

    McEvoy, D.; Huntington, J. L.; Hobbins, M.

    2015-12-01

    Providing reliable seasonal drought forecasts continues to pose a major challenge for scientists, end-users, and the water resources and agricultural communities. Precipitation (Prcp) forecasts beyond weather time scales are largely unreliable, so exploring new avenues to improve seasonal drought prediction is necessary to move towards applications and decision-making based on seasonal forecasts. A recent study has shown that evaporative demand (E0) anomaly forecasts from the Climate Forecast System Version 2 (CFSv2) are consistently more skillful than Prcp anomaly forecasts during drought events over CONUS, and E0 drought forecasts may be particularly useful during the growing season in the farming belts of the central and Midwestern CONUS. For this recent study, we used CFSv2 reforecasts to assess the skill of E0 and of its individual drivers (temperature, humidity, wind speed, and solar radiation), using the American Society for Civil Engineers Standardized Reference Evapotranspiration (ET0) Equation. Moderate skill was found in ET0, temperature, and humidity, with lesser skill in solar radiation, and no skill in wind. Therefore, forecasts of E0 based on models with no wind or solar radiation inputs may prove to be more skillful than the ASCE ET0. For this presentation we evaluate CFSv2 E0 reforecasts (1982-2009) from three different E0 models: (1) ASCE ET0; (2) Hargreaves and Samani (ET-HS), which is estimated from maximum and minimum temperature alone; and (3) Valiantzas (ET-V), which is a modified version of the Penman method for use when wind speed data are not available (or of poor quality) and is driven only by temperature, humidity, and solar radiation. The University of Idaho's gridded meteorological data (METDATA) were used as observations to evaluate CFSv2 and also to determine if ET0, ET-HS, and ET-V identify similar historical drought periods. We focus specifically on CFSv2 lead times of one, two, and three months, and season one forecasts; which are

  10. Past and Future Drought Regimes in Turkey

    NASA Astrophysics Data System (ADS)

    Sen, Burak; Topcu, Sevilay; Turkes, Murat; Sen, Baha

    2010-05-01

    Climate variability in the 20th century was characterized by apparent precipitation variability at both temporal and spatial scales. In addition to the well-known characteristic seasonal and year-to-year variability, some marked and long-term changes in precipitation occurred in Turkey, particularly after the early 1970s. Drought, originating from a deficiency of precipitation over an extended time period (which is usually a season or more) has become a recurring phenomenon in Turkey in the past few decades. Spatially coherent with the significant drought events since early 1970s, water stress and shortages for all water user sectors have also reached their critical points in Turkey. Analyzing the historical occurrence of drought provides an understanding of the range of climate possibilities for a country, resulting in more informed management decision-making. However, future projections about spatial and temporal changes in drought characteristics such as frequency, intensity and duration can be challenging for developing appropriate mitigation and adaptation strategies. Hence, the objectives of this study are (i) to analyze the spatial and temporal dimensions of historical droughts in Turkey, (2) to predict potential intensity, frequency and duration of droughts in Turkey for the future (2070-2100). The Standardized Precipitation Index (SPI) and the Percent to Normal Index (PNI) have been used to assess the drought characteristics. Rainfall datasets for the reference period, 1960-1990, were acquired from 52 stations (representative of all kinds of regions with different rainfall regimes in the country) of the Turkish State Meteorological Service (TSMS). The future rainfall series for the 2070-2100 period were simulated using a regional climate model (RegCM3) for IPCC's SRESS-A2 scenario conditions. For verification of RegCM3 simulations, the model was performed for the reference period and simulated rainfall data were used for computing two drought indices (SPI

  11. Transcriptome analysis of Pinus halepensis under drought stress and during recovery.

    PubMed

    Fox, Hagar; Doron-Faigenboim, Adi; Kelly, Gilor; Bourstein, Ronny; Attia, Ziv; Zhou, Jing; Moshe, Yosef; Moshelion, Menachem; David-Schwartz, Rakefet

    2018-03-01

    Forest trees use various strategies to cope with drought stress and these strategies involve complex molecular mechanisms. Pinus halepensis Miller (Aleppo pine) is found throughout the Mediterranean basin and is one of the most drought-tolerant pine species. In order to decipher the molecular mechanisms that P. halepensis uses to withstand drought, we performed large-scale physiological and transcriptome analyses. We selected a mature tree from a semi-arid area with suboptimal growth conditions for clonal propagation through cuttings. We then used a high-throughput experimental system to continuously monitor whole-plant transpiration rates, stomatal conductance and the vapor pressure deficit. The transcriptomes of plants were examined at six physiological stages: pre-stomatal response, partial stomatal closure, minimum transpiration, post-irrigation, partial recovery and full recovery. At each stage, data from plants exposed to the drought treatment were compared with data collected from well-irrigated control plants. A drought-stressed P. halepensis transcriptome was created using paired-end RNA-seq. In total, ~6000 differentially expressed, non-redundant transcripts were identified between drought-treated and control trees. Cluster analysis has revealed stress-induced down-regulation of transcripts related to photosynthesis, reactive oxygen species (ROS)-scavenging through the ascorbic acid (AsA)-glutathione cycle, fatty acid and cell wall biosynthesis, stomatal activity, and the biosynthesis of flavonoids and terpenoids. Up-regulated processes included chlorophyll degradation, ROS-scavenging through AsA-independent thiol-mediated pathways, abscisic acid response and accumulation of heat shock proteins, thaumatin and exordium. Recovery from drought induced strong transcription of retrotransposons, especially the retrovirus-related transposon Tnt1-94. The drought-related transcriptome illustrates this species' dynamic response to drought and recovery and unravels

  12. FPGA-based smart sensor for drought stress detection in tomato plants using novel physiological variables and discrete wavelet transform.

    PubMed

    Duarte-Galvan, Carlos; Romero-Troncoso, Rene de J; Torres-Pacheco, Irineo; Guevara-Gonzalez, Ramon G; Fernandez-Jaramillo, Arturo A; Contreras-Medina, Luis M; Carrillo-Serrano, Roberto V; Millan-Almaraz, Jesus R

    2014-10-09

    Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions.

  13. 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

  14. Association of information satisfaction, psychological distress and monitoring coping style with post-decision regret following breast reconstruction.

    PubMed

    Sheehan, Joanne; Sherman, Kerry A; Lam, Thomas; Boyages, John

    2007-04-01

    Little is known of the psychosocial factors associated with decision regret in the context of breast reconstruction following mastectomy for breast cancer treatment. Moreover, there is a paucity of theoretically-based research in the area of post-decision regret. Adopting the theoretical framework of the Monitoring Process Model (Cancer 1995;76(1):167-177), the current study assessed the role of information satisfaction, current psychological distress and the moderating effect of monitoring coping style to the experience of regret over the decision to undergo reconstructive surgery. Women (N=123) diagnosed with breast cancer who had undergone immediate or delayed breast reconstruction following mastectomy participated in the study. The majority of participants (52.8%, n=65) experienced no decision regret, 27.6% experienced mild regret and 19.5% moderate to strong regret. Bivariate analyses indicated that decision regret was associated with low satisfaction with preparatory information, depression, anxiety and stress. Multinominal logistic regression analysis showed, controlling for mood state and time since last reconstructive procedure, that lower satisfaction with information and increased depression were associated with increased likelihood of experiencing regret. Monitoring coping style moderated the association between anxiety and regret (beta=-0.10, OR=0.91, p=0.01), whereby low monitors who were highly anxious had a greater likelihood of experiencing regret than highly anxious high monitors. Copyright (c) 2006 John Wiley & Sons, Ltd.

  15. 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

  16. Advancing place-based transboundary climate services: Lessons from the 2016 North American drought, wildfire, and climate services forum

    USDA-ARS?s Scientific Manuscript database

    In June 2016, nearly 50 climate science and services experts representing the North American Climate Services Partnership, North American Drought Monitor Forum, and North American Fire Forecasting Workshop joined together for an integrated workshop on drought, wildfire, and climate services across N...

  17. Did Climate Change Cause the 2012-2014 California Drought?

    NASA Astrophysics Data System (ADS)

    Mao, Y.; Clark, E.; Xiao, M.; Nijssen, B.; Lettenmaier, D. P.

    2014-12-01

    California has experienced severe drought over the last three years, with especially deficient winter precipitation and mountain snowpack in 2013-2014. While the severity of California's water crisis this year is not in question, the causes of the drought are less clear, and there has been debate as to whether human-induced climate change is at least in part a cause of anomalously low winter precipitation (P) and snow water equivalent (SWE) this year, or whether the conditions are simply the result of natural variability that has been manifested in previous severe droughts in California. To provide more scientific insight to this question, we reconstructed, using the Variable Infiltration Capacity (VIC) hydrologic model, SWE and runoff from 1920 to 2014 at a spatial resolution of 1/16 degree over the Sierra Nevada range of California. We forced the VIC model with a temporally consistent set of index precipitation and temperature stations that are also used in the University of Washington's Drought Monitoring System for the West Coast Region (http://www.hydro.washington.edu/forecast/monitor_cali/index.shtml). We carried out trend analysis and examined cumulative probability for accumulated winter precipitation, SWE on Apr 1, annual, spring and winter runoff, average winter temperature (T) and SWE/P fraction. We also did correlation analysis between SWE and P as well as SWE and T. In addition, we used detrended temperature data to force the VIC model in order to analyze the role of climate change in SWE and runoff. Our results show that while the decreasing trend in SWE and earlier runoff peak in the year are related to long-term warming climate, there is no significant trend in winter P and there are lots of variability in the record of all variables. While this year's anomalously warm weather might have exacerbated the ongoing 3-year drought (and winter 2013-14 in particular), we conclude that natural variability is the main cause.

  18. Modeling Drought Impact Occurrence Based on Climatological Drought Indices for Europe

    NASA Astrophysics Data System (ADS)

    Stagge, J. H.; Kohn, I.; Tallaksen, L. M.; Stahl, K.

    2014-12-01

    Meteorological drought indices are often assumed to accurately characterize the severity of a drought event; however, these indices do not necessarily reflect the likelihood or severity of a particular type of drought impact experienced on the ground. In previous research, this link between index and impact was often estimated based on thresholds found by experience, measured using composite indices with assumed weighting schemes, or defined based on very narrow impact measures, using either a narrow spatial extent or very specific impacts. This study expands on earlier work by demonstrating the feasibility of relating user-provided impact reports to the climatological drought indices SPI and SPEI by logistic regression. The user-provided drought impact reports are based on the European Drought Impact Inventory (EDII, www.geo.uio.no/edc/droughtdb/), a newly developed online database that allows both public report submission and querying the more than 4,000 reported impacts spanning 33 European countries. This new tool is used to quantify the link between meteorological drought indices and impacts focusing on four primary impact types, spanning agriculture, energy and industry, public water supply, and freshwater ecosystem across five European countries. Statistically significant climate indices are retained as predictors using step-wise regression and used to compare the most relevant drought indices and accumulation periods for different impact types and regions. Agricultural impacts are explained best by 2-12 month anomalies, with 2-3 month anomalies found in predominantly rain-fed agricultural regions, and anomalies greater than 3 months related to agricultural management practices. Energy and industry impacts, related to hydropower and energy cooling water in these countries, respond to longer accumulated precipitation anomalies (6-12 months). Public water supply and freshwater ecosystem impacts are explained by a more complex combination of short (1-3 month

  19. Drought and flood effects on macrobenthic communities in the estuary of Australia's largest river system

    NASA Astrophysics Data System (ADS)

    Dittmann, Sabine; Baring, Ryan; Baggalley, Stephanie; Cantin, Agnes; Earl, Jason; Gannon, Ruan; Keuning, Justine; Mayo, Angela; Navong, Nathavong; Nelson, Matt; Noble, Warwick; Ramsdale, Tanith

    2015-11-01

    Estuaries are prone to drought and flood events, which can vary in frequency and intensity depending on water management and climate change. We investigated effects of two different drought and flow situations, including a four year long drought (referred to as Millennium drought) and a major flood event, on the macrobenthic community in the estuary and coastal lagoon of the Murray Mouth and Coorong, where freshwater inflows are strictly regulated. The analysis is based on ten years of annual monitoring of benthic communities and environmental conditions in sediment and water. The objectives were to identify changes in diversity, abundance, biomass and distribution, as well as community shifts and environmental drivers for the respective responses. The Millennium drought led to decreased taxonomic richness, abundance and biomass of macrobenthos as hypersaline conditions developed and water levels dropped. More taxa were found under very high salinities than predicted from the Remane diagram. When a flood event broke the Millennium drought, recovery took longer than from a shorter drought followed by small flows. A flow index was developed to assess the biological response subject to the duration of the preceding drought and flow volumes. The index showed higher taxonomic richness, abundance and biomass at intermediate and more continuous flow conditions. Abundance increased quickly after flows were restored, but the benthic community was initially composed of small bodied organisms and biomass increased only after several years once larger organisms became more abundant. Individual densities and constancy of distribution dropped during the drought for almost all macrobenthic taxa, but recoveries after the flood were taxon specific. Distinct benthic communities were detected over time before and after the drought and flood events, and spatially, as the benthic community in the hypersaline Coorong was split off with a salinity threshold of 64 identified by LINKTREE

  20. 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.

  1. Dual Assimilation of Microwave and Thermal-Infrared Satellite Observations of Soil Moisture into NLDAS for Improved Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Hain, C.; Crow, W. T.; Anderson, M. C.; Zhan, X.; Wardlow, B.; Svoboda, M. D.; Mecikalski, J. R.

    2011-12-01

    Our research group is currently developing an operational data assimilation (DA) system for the optimal assimilation of thermal infrared (TIR) and microwave (MV) soil moisture (SM) and insertion of near real-time green vegetation fraction (GVF) into the Noah land-surface model component of the National Land Data Assimilation System (NLDAS). NLDAS produces the hydrologic products (e.g. soil moisture, evapotranspiration, and runoff) used by NCEP for operational drought monitoring, but these products are sensitive to model input errors in soil texture (affecting infiltration rates) and prescribed precipitation rates. Periodic updates of SM state variables in LSMs achieved by assimilating diagnostic moisture information retrieved using satellite remote sensing have been shown to compensate for model errors and result in improved hydrologic output. The work proposed here will build on a project currently funded under the Climate Test Bed Program entitled "A GOES Thermal-Based Drought Early Warning Index for NIDIS", which is developing an operational TIR SM index (Evaporative Stress Index; ESI) based on maps of the ratio of actual to potential ET (fPET) generated with the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm. The research team has demonstrated that diagnostic information about SM and evapotranspiration (ET) from MW and TIR remote sensing can significantly reduce SM drifts in LSMs such as Noah. The two different SM retrievals have been shown to be quite complementary: TIR provides relatively high spatial (down to 100 m) and low temporal resolution (due to cloud cover) retrievals over a wide range of GVF, while MW provides relatively low spatial (25 to 60 km) and high temporal resolution (can retrieve through cloud cover), but only over areas with low GVF. Furthermore, MW retrievals are sensitive to SM only in the first few centimeters of the soil profile, while TIR provides information about SM conditions integrated over the full root

  2. 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

  3. Seaweed extract improve drought tolerance of soybean by regulating stress-response genes.

    PubMed

    Shukla, Pushp S; Shotton, Katy; Norman, Erin; Neily, Will; Critchley, Alan T; Prithiviraj, Balakrishnan

    2018-02-01

    There is an increasing global concern about the availability of water for agricultural use. Drought stress negatively impacts plant physiology and crop productivity. Soybean ( Glycine max ) is one of the important oilseed crops, and its productivity is often reduced by drought. In this study, a commercial extract of Ascophyllum nodosum (ANE) was evaluated for its potential to alleviate drought stress in soybean. The aim of this study was to determine the effects of ANE on the response of soybean plants to drought stress by monitoring stomatal conductance, relative leaf water content, antioxidant activity and expression of stress-responsive genes. Plants treated with ANE had higher relative water content and higher stomatal conductance under drought stress. During early recovery in the post-drought phase, ANE treated plants had significantly higher stomatal conductance. The antioxidant activity was also found higher in the plants treated with ANE. In addition, ANE-treatment led to changes in the expression of stress-responsive genes: GmCYP707A1a , GmCYP707A3b , GmRD22 , GmRD20 , GmDREB1B , GmERD1 , GmNFYA3 , FIB1a , GmPIP1b , GmGST , GmBIP and GmTp55 . Taken together, these results suggest that applications of ANE improve the drought tolerance of soybean by changing physiology and gene expression.

  4. Seaweed extract improve drought tolerance of soybean by regulating stress-response genes

    PubMed Central

    Shukla, Pushp S; Shotton, Katy; Norman, Erin; Neily, Will; Critchley, Alan T

    2018-01-01

    Abstract There is an increasing global concern about the availability of water for agricultural use. Drought stress negatively impacts plant physiology and crop productivity. Soybean (Glycine max) is one of the important oilseed crops, and its productivity is often reduced by drought. In this study, a commercial extract of Ascophyllum nodosum (ANE) was evaluated for its potential to alleviate drought stress in soybean. The aim of this study was to determine the effects of ANE on the response of soybean plants to drought stress by monitoring stomatal conductance, relative leaf water content, antioxidant activity and expression of stress-responsive genes. Plants treated with ANE had higher relative water content and higher stomatal conductance under drought stress. During early recovery in the post-drought phase, ANE treated plants had significantly higher stomatal conductance. The antioxidant activity was also found higher in the plants treated with ANE. In addition, ANE-treatment led to changes in the expression of stress-responsive genes: GmCYP707A1a, GmCYP707A3b, GmRD22, GmRD20, GmDREB1B, GmERD1, GmNFYA3, FIB1a, GmPIP1b, GmGST, GmBIP and GmTp55. Taken together, these results suggest that applications of ANE improve the drought tolerance of soybean by changing physiology and gene expression. PMID:29308122

  5. 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.

  6. Remote monitoring of heart failure: benefits for therapeutic decision making.

    PubMed

    Martirosyan, Mihran; Caliskan, Kadir; Theuns, Dominic A M J; Szili-Torok, Tamas

    2017-07-01

    Chronic heart failure is a cardiovascular disorder with high prevalence and incidence worldwide. The course of heart failure is characterized by periods of stability and instability. Decompensation of heart failure is associated with frequent and prolonged hospitalizations and it worsens the prognosis for the disease and increases cardiovascular mortality among affected patients. It is therefore important to monitor these patients carefully to reveal changes in their condition. Remote monitoring has been designed to facilitate an early detection of adverse events and to minimize regular follow-up visits for heart failure patients. Several new devices have been developed and introduced to the daily practice of cardiology departments worldwide. Areas covered: Currently, special tools and techniques are available to perform remote monitoring. Concurrently there are a number of modern cardiac implantable electronic devices that incorporate a remote monitoring function. All the techniques that have a remote monitoring function are discussed in this paper in detail. All the major studies on this subject have been selected for review of the recent data on remote monitoring of HF patients and demonstrate the role of remote monitoring in the therapeutic decision making for heart failure patients. Expert commentary: Remote monitoring represents a novel intensified follow-up strategy of heart failure management. Overall, theoretically, remote monitoring may play a crucial role in the early detection of heart failure progression and may improve the outcome of patients.

  7. Transcriptome analysis of Pinus halepensis under drought stress and during recovery

    PubMed Central

    Fox, Hagar; Doron-Faigenboim, Adi; Kelly, Gilor; Bourstein, Ronny; Attia, Ziv; Zhou, Jing; Moshe, Yosef; Moshelion, Menachem; David-Schwartz, Rakefet

    2018-01-01

    Abstract Forest trees use various strategies to cope with drought stress and these strategies involve complex molecular mechanisms. Pinus halepensis Miller (Aleppo pine) is found throughout the Mediterranean basin and is one of the most drought-tolerant pine species. In order to decipher the molecular mechanisms that P. halepensis uses to withstand drought, we performed large-scale physiological and transcriptome analyses. We selected a mature tree from a semi-arid area with suboptimal growth conditions for clonal propagation through cuttings. We then used a high-throughput experimental system to continuously monitor whole-plant transpiration rates, stomatal conductance and the vapor pressure deficit. The transcriptomes of plants were examined at six physiological stages: pre-stomatal response, partial stomatal closure, minimum transpiration, post-irrigation, partial recovery and full recovery. At each stage, data from plants exposed to the drought treatment were compared with data collected from well-irrigated control plants. A drought-stressed P. halepensis transcriptome was created using paired-end RNA-seq. In total, ~6000 differentially expressed, non-redundant transcripts were identified between drought-treated and control trees. Cluster analysis has revealed stress-induced down-regulation of transcripts related to photosynthesis, reactive oxygen species (ROS)-scavenging through the ascorbic acid (AsA)-glutathione cycle, fatty acid and cell wall biosynthesis, stomatal activity, and the biosynthesis of flavonoids and terpenoids. Up-regulated processes included chlorophyll degradation, ROS-scavenging through AsA-independent thiol-mediated pathways, abscisic acid response and accumulation of heat shock proteins, thaumatin and exordium. Recovery from drought induced strong transcription of retrotransposons, especially the retrovirus-related transposon Tnt1-94. The drought-related transcriptome illustrates this species’ dynamic response to drought and recovery

  8. Pinus sylvestris switches respiration substrates under shading but not during drought.

    PubMed

    Fischer, Sarah; Hanf, Stefan; Frosch, Torsten; Gleixner, Gerd; Popp, Jürgen; Trumbore, Susan; Hartmann, Henrik

    2015-08-01

    Reduced carbon (C) assimilation during prolonged drought forces trees to rely on stored C to maintain vital processes like respiration. It has been shown, however, that the use of carbohydrates, a major C storage pool and apparently the main respiratory substrate in plants, strongly declines with decreasing plant hydration. Yet no empirical evidence has been produced to what degree other C storage compounds like lipids and proteins may fuel respiration during drought. We exposed young scots pine trees to C limitation using either drought or shading and assessed respiratory substrate use by monitoring the respiratory quotient, δ(13) C of respired CO2 and concentrations of the major storage compounds, that is, carbohydrates, lipids and amino acids. Only shaded trees shifted from carbohydrate-dominated to lipid-dominated respiration and showed progressive carbohydrate depletion. In drought trees, the fraction of carbohydrates used in respiration did not decline but respiration rates were strongly reduced. The lower consumption and potentially allocation from other organs may have caused initial carbohydrate content to remain constant during the experiment. Our results suggest that respiratory substrates other than carbohydrates are used under carbohydrate limitation but not during drought. Thus, respiratory substrate shift cannot provide an efficient means to counterbalance C limitation under natural drought. © 2015 The Authors New Phytologist © 2015 New Phytologist Trust.

  9. Quantitative analysis of proteome extracted from barley crowns grown under different drought conditions

    PubMed Central

    Vítámvás, Pavel; Urban, Milan O.; Škodáček, Zbynek; Kosová, Klára; Pitelková, Iva; Vítámvás, Jan; Renaut, Jenny; Prášil, Ilja T.

    2015-01-01

    Barley cultivar Amulet was used to study the quantitative proteome changes through different drought conditions utilizing two-dimensional difference gel electrophoresis (2D-DIGE). Plants were cultivated for 10 days under different drought conditions. To obtain control and differentially drought-treated plants, the soil water content was kept at 65, 35, and 30% of soil water capacity (SWC), respectively. Osmotic potential, water saturation deficit, 13C discrimination, and dehydrin accumulation were monitored during sampling of the crowns for proteome analysis. Analysis of the 2D-DIGE gels revealed 105 differentially abundant spots; most were differentially abundant between the controls and drought-treated plants, and 25 spots displayed changes between both drought conditions. Seventy-six protein spots were successfully identified by tandem mass spectrometry. The most frequent functional categories of the identified proteins can be put into the groups of: stress-associated proteins, amino acid metabolism, carbohydrate metabolism, as well as DNA and RNA regulation and processing. Their possible role in the response of barley to drought stress is discussed. Our study has shown that under drought conditions barley cv. Amulet decreased its growth and developmental rates, displayed a shift from aerobic to anaerobic metabolism, and exhibited increased levels of several protective proteins. Comparison of the two drought treatments revealed plant acclimation to milder drought (35% SWC); but plant damage under more severe drought treatment (30% SWC). The results obtained revealed that cv. Amulet is sensitive to drought stress. Additionally, four spots revealing a continuous and significant increase with decreasing SWC (UDP-glucose 6-dehydrogenase, glutathione peroxidase, and two non-identified) could be good candidates for testing of their protein phenotyping capacity together with proteins that were significantly distinguished in both drought treatments. PMID:26175745

  10. Multi-basin, Multi-sector Drought Economic Impact Model in Python: Development and Applications

    NASA Astrophysics Data System (ADS)

    Gutenson, J. L.; Zhu, L.; Ernest, A. N. S.; Oubeidillah, A.; Bearden, B.; Johnson, T. G.

    2015-12-01

    Drought is one of the most economically disastrous natural hazards, one whose impacts are exacerbated by the lack of abrupt onset and offset that define tornados and hurricanes. In the United States, about 30 billion dollars losses is caused by drought in 2012, resulting in widespread economic impacts for societies, industries, agriculture, and recreation. And in California, the drought cost statewide economic losses about 2.2 billion, with a total loss of 17,100 seasonal and part-time jobs. Driven by a variety of factors including climate change, population growth, increased water demands, alteration to land cover, drought occurs widely all over the world. Drought economic consequence assessment tool are greatly needed to allow decision makers and stakeholders to anticipate and manage effectively. In this study, current drought economic impact modeling methods were reviewed. Most of these models only deal with the impact in the agricultural sector with a focus on a single basin; few of these models analyze long term impact. However, drought impacts are rarely restricted to basin boundaries, and cascading economic impacts are likely to be significant. A holistic approach to multi-basin, multi-sector drought economic impact assessment is needed.In this work, we developed a new model for drought economic impact assessment, Drought Economic Impact Model in Python (PyDEM). This model classified all business establishments into thirteen categories based on NAICS, and using a continuous dynamic social accounting matrix approach, coupled with calculation of the indirect consequences for the local and regional economies and the various resilience. In addition, Environmental Policy Integrated Climate model was combined for analyzing drought caused soil erosion together with agriculture production, and then the long term impacts of drought were achieved. A visible output of this model was presented in GIS. In this presentation, Choctawhatchee-Pea-Yellow River Basins, Alabama

  11. Global patterns of drought recovery

    DOE PAGES

    Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; ...

    2017-08-09

    Drought has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, 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 factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivitymore » to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.« less

  12. 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 has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, 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 factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivitymore » to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.« less

  13. Global patterns of drought recovery.

    PubMed

    Schwalm, Christopher R; Anderegg, William R L; Michalak, Anna M; Fisher, Joshua B; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D; Wolf, Adam; Huntzinger, Deborah N; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

    2017-08-09

    Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

  14. Global patterns of drought recovery

    NASA Astrophysics Data System (ADS)

    Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

    2017-08-01

    Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time—how long an ecosystem requires to revert to its pre-drought functional state—is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth’s climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

  15. Cooperative drought adaptation: Integrating infrastructure development, conservation, and water transfers into adaptive policy pathways

    NASA Astrophysics Data System (ADS)

    Zeff, Harrison B.; Herman, Jonathan D.; Reed, Patrick M.; Characklis, Gregory W.

    2016-09-01

    A considerable fraction of urban water supply capacity serves primarily as a hedge against drought. Water utilities can reduce their dependence on firm capacity and forestall the development of new supplies using short-term drought management actions, such as conservation and transfers. Nevertheless, new supplies will often be needed, especially as demands rise due to population growth and economic development. Planning decisions regarding when and how to integrate new supply projects are fundamentally shaped by the way in which short-term adaptive drought management strategies are employed. To date, the challenges posed by long-term infrastructure sequencing and adaptive short-term drought management are treated independently, neglecting important feedbacks between planning and management actions. This work contributes a risk-based framework that uses continuously updating risk-of-failure (ROF) triggers to capture the feedbacks between short-term drought management actions (e.g., conservation and water transfers) and the selection and sequencing of a set of regional supply infrastructure options over the long term. Probabilistic regional water supply pathways are discovered for four water utilities in the "Research Triangle" region of North Carolina. Furthermore, this study distinguishes the status-quo planning path of independent action (encompassing utility-specific conservation and new supply infrastructure only) from two cooperative formulations: "weak" cooperation, which combines utility-specific conservation and infrastructure development with regional transfers, and "strong" cooperation, which also includes jointly developed regional infrastructure to support transfers. Results suggest that strong cooperation aids utilities in meeting their individual objectives at substantially lower costs and with less overall development. These benefits demonstrate how an adaptive, rule-based decision framework can coordinate integrated solutions that would not be

  16. Ethnobotanical study of traditional edible plants used by the Naxi people during droughts.

    PubMed

    Zhang, Lingling; Chai, Zhenzhen; Zhang, Yu; Geng, Yanfei; Wang, Yuahua

    2016-09-12

    Since 2009, millions of people have been forced to live under food shortage by the continuous drought in Southwestern China. The market was the primary source of aid grains, and fears that the market will be unable to provide sufficient food make safeguarding food security in the face of climate change crucial. Traditional adaptive strategies of pre-market indigenous people are a potential source of innovation. We studied three questions among the Naxi people: 1) What edible plants did they consume during droughts? 2) How did they produce enough food? 3) How did they consume these plants? This study investigates and documents traditional Naxi food knowledge to safeguard food security during drought and facilitate Chinese policy decisions. Ethnobotanical investigation was conducted through literature review, semi-structured interviews, collaborative fieldwork and group discussions in three Naxi villages. 89 informants (including 35 key informants) were surveyed from 2012 to 2013. Significant Index (SI) was adopted to evaluate each edible plant's food supply significance. Voucher specimens were collected for taxonomic identification. 1) In total, 141 edible plants (38 cultivated and 103 wild) were consumed-primarily landrace crops, supplementary edible plants and famine plants. 2) Naxi people produced sufficient food through widespread food production systems, strong landrace crop resilience, and diversity in wild edible plants. 3) Through a diverse diet and consuming almost all edible parts of the plant, the Naxi used edible plants fully to meet food and nutrition needs during drought. Edible plant diversity is a cornerstone of drought food security. Cultivated crops (especially landrace plants) and wild edible plants were both important. Naxi people protect edible plant diversity through ecological morality and traditional ecological knowledge (TEK). National inventories of edible plant diversity and studies of the TEK of other Chinese indigenous peoples should be

  17. Monitoring Drought along the Gulf of Mexico and the Southeastern Atlantic Ocean Using the Coastal Salinity Index

    NASA Astrophysics Data System (ADS)

    Conrads, P. A.; Rouen, L.; Lackstrom, K.; McCloskey, B.

    2017-12-01

    Coastal droughts have a different dynamic than upland droughts, which are typically characterized by agricultural, hydrologic, meteorological, and (or) socio-economic impacts. Drought uniquely affects coastal ecosystems due to changes in salinity conditions of estuarine creeks and rivers. The location of the freshwater-saltwater interface in surface-water bodies is an important factor in the ecological and socio-economic dynamics of coastal communities. The location of the interface determines the freshwater and saltwater aquatic communities, fisheries spawning habitat, and the freshwater availability for municipal and industrial water intakes. The severity of coastal drought may explain changes in Vibrio bacteria impacts on shellfish harvesting and occurrence of wound infection, fish kills, harmful algal blooms, hypoxia, and beach closures. To address the data and information gap for characterizing coastal drought, a coastal salinity index (CSI) was developed using salinity data. The CSI uses a computational approach similar to the Standardized Precipitation Index (SPI). The CSI is computed for unique time intervals (for example 1-, 6-, 12-, and 24-month) that can characterize the onset and recovery of short- and long-term drought. Evaluation of the CSI indicates that the index can be used for different estuary types (for example: brackish, oligohaline, or mesohaline), for regional comparison between estuaries, and as an index of wet conditions (high freshwater inflow) in addition to drought (saline) conditions. In 2017, three activities in 2017 will be presented that enhance the use and application of the CSI. One, a software package was developed for the consistent computation of the CSI that includes preprocessing of salinity data, filling missing data, computing the CSI, post-processing, and generating the supporting metadata. Two, the CSI has been computed at sites along the Gulf of Mexico (Texas to Florida) and the Southeastern Atlantic Ocean (Florida to

  18. Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

    USGS Publications Warehouse

    Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

    2015-01-01

    Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

  19. Impacts of the Midwestern Drought Forecasts of 2000.

    NASA Astrophysics Data System (ADS)

    Changnon, Stanley A.

    2002-10-01

    In March of 2000 (and again in April and May) NOAA issued long-range forecasts indicating that an existing Midwestern drought would continue and intensify through the upcoming summer. These forecasts received extensive media coverage and wide public attention. If the drought persisted and intensified during the summer of 2000, significant agricultural and water supply problems would occur. However, in late May, June, and July heavy rains fell throughout most of the Midwest, ending the drought in most areas and revealing that the forecast was incorrect for most of the Midwest. Significant media coverage was devoted to the `failed' forecast, with considerable speculation that major economic hardship had resulted from the forecast. This study assesses the effects of the failed drought forecast on agricultural and water agency actions in the Midwest. Assessment of the agricultural and water management sectors revealed notable commonalities. Most people surveyed were aware of the drought forecasts, and the information sources were diverse. One-third of those surveyed indicated they did nothing as a result of the forecasts. The decisions and actions taken by others as a result of the forecasts provided mixed impacts. The water resource actions such as conserving water, seeking new sources, and convening state drought groups resulted in little cost and were considered to be beneficial. However, in the three areas of agricultural impacts (crop production shifts, crop insurance purchases, and grain market choices), mainly negative outcomes occurred. The 13 March issuance of the forecast was too late for producers to make sizable changes in production practices or to alter insurance coverage greatly, and most forecast-based actions taken in these two areas were considered to be negative but financially minor losses. However, 48% of the 1017 producers sampled altered their normal crop marketing practices, which in 84% of the cases led to sizable losses in revenue. This loss

  20. Characterization of extreme flood and drought events in Singapore and investigation of their relationships with ENSO

    NASA Astrophysics Data System (ADS)

    Li, Xin; Babovic, Vladan

    2016-04-01

    Flood and drought are hydrologic extreme events that have significant impact on human and natural systems. Characterization of flood and drought in terms of their start, duration and strength, and investigation of the impact of natural climate variability (i.e., ENSO) and anthropogenic climate change on them can help decision makers to facilitate adaptions to mitigate potential enormous economic costs. To date, numerous studies in this area have been conducted, however, they are primarily focused on extra-tropical regions. Therefore, this study presented a detailed framework to characterize flood and drought events in a tropical urban city-state (i.e., Singapore), based on daily data from 26 precipitation stations. Flood and drought events are extracted from standardized precipitation anomalies from monthly to seasonal time scales. Frequency, duration and magnitude of flood and drought at all the stations are analyzed based on crossing theory. In addition, spatial variation of flood and drought characteristics in Singapore is investigated using ordinary kriging method. Lastly, the impact of ENSO condition on flood and drought characteristics is analyzed using regional regression method. The results show that Singapore can be prone to extreme flood and drought events at both monthly and seasonal time scales. ENSO has significant influence on flood and drought characteristics in Singapore, but mainly during the South West Monsoon season. During the El Niño phase, drought can become more extreme. The results have implications for water management practices in Singapore.

  1. Sure I'm Sure: Prefrontal Oscillations Support Metacognitive Monitoring of Decision Making.

    PubMed

    Wokke, Martijn E; Cleeremans, Axel; Ridderinkhof, K Richard

    2017-01-25

    Successful decision making critically involves metacognitive processes such as monitoring and control of our decision process. Metacognition enables agents to modify ongoing behavior adaptively and determine what to do next in situations in which external feedback is not (immediately) available. Despite the importance of metacognition for many aspects of life, little is known about how our metacognitive system operates or about what kind of information is used for metacognitive (second-order) judgments. In particular, it remains an open question whether metacognitive judgments are based on the same information as first-order decisions. Here, we investigated the relationship between metacognitive performance and first-order task performance by recording EEG signals while participants were asked to make a "diagnosis" after seeing a sample of fictitious patient data (a complex pattern of colored moving dots of different sizes). To assess metacognitive performance, participants provided an estimate about the quality of their diagnosis on each trial. Results demonstrate that the information that contributes to first-order decisions differs from the information that supports metacognitive judgments. Further, time-frequency analyses of EEG signals reveal that metacognitive performance is associated specifically with prefrontal theta-band activity. Together, our findings are consistent with a hierarchical model of metacognition and suggest a crucial role for prefrontal oscillations in metacognitive performance. Monitoring and control of our decision process (metacognition) is a crucial aspect of adaptive decision making. Crucially, metacognitive skills enable us to adjust ongoing behavior and determine future decision making when immediate feedback is not available. In the present study, we constructed a "diagnosis task" that allowed us to assess in what way first-order task performance and metacognition are related to each other. Results demonstrate that the contribution

  2. Hydrological change: Towards a consistent approach to assess changes on both floods and droughts

    NASA Astrophysics Data System (ADS)

    Quesada-Montano, Beatriz; Di Baldassarre, Giuliano; Rangecroft, Sally; Van Loon, Anne F.

    2018-01-01

    Several studies have found that the frequency, magnitude and spatio-temporal distribution of droughts and floods have significantly increased in many regions of the world. Yet, most of the methods used in detecting trends in hydrological extremes 1) focus on either floods or droughts, and/or 2) base their assessment on characteristics that, even though useful for trend identification, cannot be directly used in decision making, e.g. integrated water resources management and disaster risk reduction. In this paper, we first discuss the need for a consistent approach to assess changes on both floods and droughts, and then propose a method based on the theory of runs and threshold levels. Flood and drought changes were assessed in terms of frequency, length and surplus/deficit volumes. This paper also presents an example application using streamflow data from two hydrometric stations along the Po River basin (Italy), Piacenza and Pontelagoscuro, and then discuss opportunities and challenges of the proposed method.

  3. Use of Land Surface Temperature Observations in a Two-Source Energy Balance Model Towards Improved Monitoring of Evapotranspiration and Drought

    NASA Astrophysics Data System (ADS)

    Hain, C.; Anderson, M. C.; Otkin, J.; Semmens, K. A.; Zhan, X.; Fang, L.; Li, Z.

    2014-12-01

    As the world's water resources come under increasing tension due to the dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. However, direct validation of ET models is challenging due to lack of available observations that are sufficiently representative at the model grid scale (10-100 km). Prognostic land-surface models require accurate information about observed precipitation, soil moisture storage, groundwater, and artificial controls on water supply (e.g., irrigation, dams, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared remote sensing of land-surface temperature (LST) as a boundary condition. One such method, the Atmosphere Land Exchange Inverse (ALEXI) model provides estimates of surface energy fluxes through the use of mid-morning change in LST and radiation inputs. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil evaporation and canopy transpiration. Additionally, the Evaporative Stress Index (ESI) representing anomalies in the ratio of actual-to-potential ET has shown to be a reliable indicator of drought. ESI maps over the continental US show good correspondence with standard drought metrics and with patterns of precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Furthermore, 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, it provides an independent assessment of drought conditions and has particular utility for real-time monitoring in regions with sparse rainfall data or

  4. 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.

  5. Drought impacts on phloem transport

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

    Sevanto, Sanna Annika

    We report drought impacts on phloem transport have attracted attention only recently, despite the well-established, and empirically verified theories on drought impacts on water transport in plants in general. This is because studying phloem transport is challenging. Phloem tissue is relatively small and delicate, and it has often been assumed not to be impacted by drought, or having insignificant impact on plant function or survival compared to the xylem. New evidence, however, suggests that drought responses of the phloem might hold the key for predicting plant survival time during drought or revival capacity after drought. Lastly, this review summarizes currentmore » theories and empirical evidence on how drought might impact phloem transport, and evaluates these findings in relation to plant survival during drought.« less

  6. Drought impacts on phloem transport

    DOE PAGES

    Sevanto, Sanna Annika

    2018-02-12

    We report drought impacts on phloem transport have attracted attention only recently, despite the well-established, and empirically verified theories on drought impacts on water transport in plants in general. This is because studying phloem transport is challenging. Phloem tissue is relatively small and delicate, and it has often been assumed not to be impacted by drought, or having insignificant impact on plant function or survival compared to the xylem. New evidence, however, suggests that drought responses of the phloem might hold the key for predicting plant survival time during drought or revival capacity after drought. Lastly, this review summarizes currentmore » theories and empirical evidence on how drought might impact phloem transport, and evaluates these findings in relation to plant survival during drought.« less

  7. Drought sensitivity of the Amazon rainforest.

    PubMed

    Phillips, Oliver L; Aragão, Luiz E O C; Lewis, Simon L; Fisher, Joshua B; Lloyd, Jon; López-González, Gabriela; Malhi, Yadvinder; Monteagudo, Abel; Peacock, Julie; Quesada, Carlos A; van der Heijden, Geertje; Almeida, Samuel; Amaral, Iêda; Arroyo, Luzmila; Aymard, Gerardo; Baker, Tim R; Bánki, Olaf; Blanc, Lilian; Bonal, Damien; Brando, Paulo; Chave, Jerome; de Oliveira, Atila Cristina Alves; Cardozo, Nallaret Dávila; Czimczik, Claudia I; Feldpausch, Ted R; Freitas, Maria Aparecida; Gloor, Emanuel; Higuchi, Niro; Jiménez, Eliana; Lloyd, Gareth; Meir, Patrick; Mendoza, Casimiro; Morel, Alexandra; Neill, David A; Nepstad, Daniel; Patiño, Sandra; Peñuela, Maria Cristina; Prieto, Adriana; Ramírez, Fredy; Schwarz, Michael; Silva, Javier; Silveira, Marcos; Thomas, Anne Sota; Steege, Hans Ter; Stropp, Juliana; Vásquez, Rodolfo; Zelazowski, Przemyslaw; Alvarez Dávila, Esteban; Andelman, Sandy; Andrade, Ana; Chao, Kuo-Jung; Erwin, Terry; Di Fiore, Anthony; Honorio C, Eurídice; Keeling, Helen; Killeen, Tim J; Laurance, William F; Peña Cruz, Antonio; Pitman, Nigel C A; Núñez Vargas, Percy; Ramírez-Angulo, Hirma; Rudas, Agustín; Salamão, Rafael; Silva, Natalino; Terborgh, John; Torres-Lezama, Armando

    2009-03-06

    Amazon forests are a key but poorly understood component of the global carbon cycle. If, as anticipated, they dry this century, they might accelerate climate change through carbon losses and changed surface energy balances. We used records from multiple long-term monitoring plots across Amazonia to assess forest responses to the intense 2005 drought, a possible analog of future events. Affected forest lost biomass, reversing a large long-term carbon sink, with the greatest impacts observed where the dry season was unusually intense. Relative to pre-2005 conditions, forest subjected to a 100-millimeter increase in water deficit lost 5.3 megagrams of aboveground biomass of carbon per hectare. The drought had a total biomass carbon impact of 1.2 to 1.6 petagrams (1.2 x 10(15) to 1.6 x 10(15) grams). Amazon forests therefore appear vulnerable to increasing moisture stress, with the potential for large carbon losses to exert feedback on climate change.

  8. 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

  9. 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

  10. 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

  11. The ambiguity of drought events, a bottleneck for Amazon forest drought response modelling

    NASA Astrophysics Data System (ADS)

    De Deurwaerder, Hannes; Verbeeck, Hans; Baker, Timothy; Christoffersen, Bradley; Ciais, Philippe; Galbraith, David; Guimberteau, Matthieu; Kruijt, Bart; Langerwisch, Fanny; Meir, Patrick; Rammig, Anja; Thonicke, Kirsten; Von Randow, Celso; Zhang, Ke

    2016-04-01

    Considering the important role of the Amazon forest in the global water and carbon cycle, the prognosis of altered hydrological patterns resulting from climate change provides strong incentive for apprehending the direct implications of drought on the vegetation of this ecosystem. Dynamic global vegetation models have the potential of providing a useful tool to study drought impacts on various spatial and temporal scales. This however assumes the models being able to properly represent drought impact mechanisms. But how well do the models succeed in meeting this assumption? Within this study meteorological driver data and model output data of 4 different DGVMs, i.e. ORCHIDEE, JULES, INLAND and LPGmL, are studied. Using the palmer drought severity index (PDSI) and the mean cumulative water deficit (MWD), temporal and spatial representation of drought events are studied in the driver data and are referenced to historical extreme drought events in the Amazon. Subsequently, within the resulting temporal and spatial frame, we studied the drought impact on the above ground biomass (AGB) and gross primary production (GPP) fluxes. Flux tower data, field inventory data and the JUNG data-driven GPP product for the Amazon region are used for validation. Our findings not only suggest that the current state of the studied DGVMs is inadequate in representing Amazon droughts in general, but also highlights strong inter-model differences in drought responses. Using scatterplot-studies and input-output correlations, we provide insight in the origin of these encountered inter-model differences. In addition, we present directives of model development and improvement in scope of Amazon forest drought response modelling.

  12. The response of drought in Beiluo River Basin of China based on the comprehensive method of Pa, SPI and fuzzy

    NASA Astrophysics Data System (ADS)

    Zhang, L. P.; Liu, D. F.; Zhang, H. X.; Huang, Q.; Chang, J. X.

    2017-08-01

    The meteorological drought is threatening the agricultural economic development with the change of the climate. In order to analyze the characteristics of drought spatiotemporal change, the precipitation data of eight meteorological stations in the Beiluo River Basin of Shaanxi Province of China have been collected, and the drought index of Pa, SPI and FSE have been selected to analyze the drought in Shaanxi Province for the last 55 years. The results of Pa, SPI and FSE test show that the droughts happened in the Beiluo River Basin are 149, 215 and 203 times in the past 55 years, respectively. Overall, the Beiluo River has a tendency to dry out. The main type of drought is low-grade drought, followed by the mediumgrade drought, and the specially-grade drought happened least. The average rainfall decreases in the Beiluo River Basin from the southeast to the northwest, and the change of the number of drought is just opposite to that of precipitation trend, which increases from southeast to northwest. The results will provide the scientific basis for the monitoring, evaluation, early warning and drought relief.

  13. Neural mechanisms underlying conflict monitoring over risky decision alternatives: evidence from ERP in a Go/Nogo task.

    PubMed

    Wang, Shuzhen; Hui, Ning; Zhou, Xinsheng; He, Kaifeng; Yu, Yuanyuan; Shuai, Jing

    2014-09-01

    This study assessed conflict monitoring during presentation of risky decision alternatives, as indexed by the Nogo-N2, Nogo-P3, N2d and P3d event-related potentials (ERP). Decision-makers were tested on a Go/Nogo gambling task in which gain/loss outcomes as well as stimulus type (Go/Nogo) were equiprobable. Frontal-central Nogo-N2 and Nogo-P3 did not significantly differ across risky decision alternatives, whereas N2d and P3d amplitudes were more sensitive to the nature of risky decision alternatives. Frontal-central N2d was moderated by the magnitude of alternatives, with N2d amplitude greater for large than small alternatives, a result that suggests a greater degree of conflict monitoring for the former. Central P3d was associated with alternative valence, such that P3d amplitude was greater for loss than gain valences, again suggestive of more conflict monitoring for the former. The N2d and P3d potentials in risky decision alternatives are discussed in terms of the functional significance of the N2/P3 complex.

  14. Genome-assisted Breeding For Drought Resistance

    PubMed Central

    Khan, Awais; Sovero, Valpuri; Gemenet, Dorcus

    2016-01-01

    Drought stress caused by unpredictable precipitation poses a major threat to food production worldwide, and its impact is only expected to increase with the further onset of climate change. Understanding the effect of drought stress on crops and plants' response is critical for developing improved varieties with stable high yield to fill a growing food gap from an increasing population depending on decreasing land and water resources. When a plant encounters drought stress, it may use multiple response types, depending on environmental conditions, drought stress intensity and duration, and the physiological stage of the plant. Drought stress responses can be divided into four broad types: drought escape, drought avoidance, drought tolerance, and drought recovery, each characterized by interacting mechanisms, which may together be referred to as drought resistance mechanisms. The complex nature of drought resistance requires a multi-pronged approach to breed new varieties with stable and enhanced yield under drought stress conditions. High throughput genomics and phenomics allow marker-assisted selection (MAS) and genomic selection (GS), which offer rapid and targeted improvement of populations and identification of parents for rapid genetic gains and improved drought-resistant varieties. Using these approaches together with appropriate genetic diversity, databases, analytical tools, and well-characterized drought stress scenarios, weather and soil data, new varieties with improved drought resistance corresponding to grower preferences can be introduced into target regions rapidly. PMID:27499682

  15. Irrigated Agriculture in Morocco: An Agent-Based Model of Adaptation and Decision Making Amid Increasingly Frequent Drought Events

    NASA Astrophysics Data System (ADS)

    Norton, M.

    2015-12-01

    In the past 100 years, Morocco has undertaken a heavy investment in developing water infrastructure that has led to a dramatic expansion of irrigated agriculture. Irrigated agriculture is the primary user of water in many arid countries, often accounting for 80-90% of total water usage. Irrigation is adopted by farmers not only because it leads to increased production, but also because it improves resilience to an uncertain climate. However, the Mediterranean region as a whole has also seen an increase in the frequency and severity of drought events. These droughts have had a dramatic impact on farmer livelihoods and have led to a number of coping strategies, including the adoption or disadoption of irrigation. In this study, we use a record of the annual extent of irrigated agriculture in Morocco to model the effect of drought on the extent of irrigated agriculture. Using an agent-based socioeconomic model, we seek to answer the following questions: 1) Do farmers expand irrigated agriculture in response to droughts? 2) Do drought events entail the removal of perennial crops like orchards? 3) Can we detect the retreat of irrigated agriculture in the more fragile watersheds of Morocco? Understanding the determinants of irrigated crop expansion and contractions will help us understand how agro-ecological systems transition from 20th century paradigms of expansion of water supply to a 21st century paradigm of water use efficiency. The answers will become important as countries learn how to manage water in new climate regimes characterized by less reliable and available precipitation.

  16. Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA

    NASA Astrophysics Data System (ADS)

    El-Vilaly, Mohamed Abd Salam; Didan, Kamel; Marsh, Stuart E.; van Leeuwen, Willem J. D.; Crimmins, Michael A.; Munoz, Armando Barreto

    2018-03-01

    For more than a decade, the Four Corners Region has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. These persistent droughts threaten ecosystem services, agriculture, and livestock activities, and expose the hypersensitivity of this region to inter-annual climate variability and change. Much of the intermountainWestern United States has sparse climate and vegetation monitoring stations, making fine-scale drought assessments difficult. Remote sensing data offers the opportunity to assess the impacts of the recent droughts on vegetation productivity across these areas. Here, we propose a drought assessment approach that integrates climate and topographical data with remote sensing vegetation index time series. Multisensor Normalized Difference Vegetation Index (NDVI) time series data from 1989 to 2010 at 5.6 km were analyzed to characterize the vegetation productivity changes and responses to the ongoing drought. A multi-linear regression was applied to metrics of vegetation productivity derived from the NDVI time series to detect vegetation productivity, an ecosystem service proxy, and changes. The results show that around 60.13% of the study area is observing a general decline of greenness ( p<0.05), while 3.87% show an unexpected green up, with the remaining areas showing no consistent change. Vegetation in the area show a significant positive correlation with elevation and precipitation gradients. These results, while, confirming the region's vegetation decline due to drought, shed further light on the future directions and challenges to the region's already stressed ecosystems. Whereas the results provide additional insights into this isolated and vulnerable region, the drought assessment approach used in this study may be adapted for application in other regions where surface-based climate and vegetation monitoring record is spatially and temporally limited.

  17. 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.

  18. A soil water based index as a suitable agricultural drought indicator

    NASA Astrophysics Data System (ADS)

    Martínez-Fernández, J.; González-Zamora, A.; Sánchez, N.; Gumuzzio, A.

    2015-03-01

    Currently, the availability of soil water databases is increasing worldwide. The presence of a growing number of long-term soil moisture networks around the world and the impressive progress of remote sensing in recent years has allowed the scientific community and, in the very next future, a diverse group of users to obtain precise and frequent soil water measurements. Therefore, it is reasonable to consider soil water observations as a potential approach for monitoring agricultural drought. In the present work, a new approach to define the soil water deficit index (SWDI) is analyzed to use a soil water series for drought monitoring. In addition, simple and accurate methods using a soil moisture series solely to obtain soil water parameters (field capacity and wilting point) needed for calculating the index are evaluated. The application of the SWDI in an agricultural area of Spain presented good results at both daily and weekly time scales when compared to two climatic water deficit indicators (average correlation coefficient, R, 0.6) and to agricultural production. The long-term minimum, the growing season minimum and the 5th percentile of the soil moisture series are good estimators (coefficient of determination, R2, 0.81) for the wilting point. The minimum of the maximum value of the growing season is the best estimator (R2, 0.91) for field capacity. The use of these types of tools for drought monitoring can aid the better management of agricultural lands and water resources, mainly under the current scenario of climate uncertainty.

  19. Experimental droughts: Are precipitation variability and methodological trends hindering our understanding of ecological sensitivities to drought?

    NASA Astrophysics Data System (ADS)

    Hoover, D. L.; Wilcox, K.; Young, K. E.

    2017-12-01

    Droughts are projected to increase in frequency and intensity with climate change, which may have dramatic and prolonged effects on ecosystem structure and function. There are currently hundreds of published, ongoing, and new drought experiments worldwide aimed to assess ecosystem sensitivities to drought and identify the mechanisms governing ecological resistance and resilience. However, to date, the results from these experiments have varied widely, and thus patterns of drought sensitivities have been difficult to discern. This lack of consensus at the field scale, limits the abilities of experiments to help improve land surface models, which often fail to realistically simulate ecological responses to extreme events. This is unfortunate because models offer an alternative, yet complementary approach to increase the spatial and temporal assessment of ecological sensitivities to drought that are not possible in the field due to logistical and financial constraints. Here we examined 89 published drought experiments, along with their associated historical precipitation records to (1) identify where and how drought experiments have been imposed, (2) determine the extremity of drought treatments in the context of historical climate, and (3) assess the influence of precipitation variability on drought experiments. We found an overall bias in drought experiments towards short-term, extreme experiments in water-limited ecosystems. When placed in the context of local historical precipitation, most experimental droughts were extreme, with 61% below the 5th, and 43% below the 1st percentile. Furthermore, we found that interannual precipitation variability had a large and potentially underappreciated effect on drought experiments due to the co-varying nature of control and drought treatments. Thus detecting ecological effects in experimental droughts is strongly influenced by the interaction between drought treatment magnitude, precipitation variability, and key

  20. Using a water-food-energy nexus approach for optimal irrigation management during drought events in Nebraska

    NASA Astrophysics Data System (ADS)

    Campana, P. E.; Zhang, J.; Yao, T.; Melton, F. S.; Yan, J.

    2017-12-01

    Climate change and drought have severe impacts on the agricultural sector affecting crop yields, water availability, and energy consumption for irrigation. Monitoring, assessing and mitigating the effects of climate change and drought on the agricultural and energy sectors are fundamental challenges that require investigation for water, food, and energy security issues. Using an integrated water-food-energy nexus approach, this study is developing a comprehensive drought management system through integration of real-time drought monitoring with real-time irrigation management. The spatially explicit model developed, GIS-OptiCE, can be used for simulation, multi-criteria optimization and generation of forecasts to support irrigation management. To demonstrate the value of the approach, the model has been applied to one major corn region in Nebraska to study the effects of the 2012 drought on crop yield and irrigation water/energy requirements as compared to a wet year such as 2009. The water-food-energy interrelationships evaluated show that significant water volumes and energy are required to halt the negative effects of drought on the crop yield. The multi-criteria optimization problem applied in this study indicates that the optimal solutions of irrigation do not necessarily correspond to those that would produce the maximum crop yields, depending on both water and economic constraints. In particular, crop pricing forecasts are extremely important to define the optimal irrigation management strategy. The model developed shows great potential in precision agriculture by providing near real-time data products including information on evapotranspiration, irrigation volumes, energy requirements, predicted crop growth, and nutrient requirements.

  1. Investigation of drought-vulnerable regions in North Korea using remote sensing and cloud computing climate data.

    PubMed

    Yu, Jinhang; Lim, Joongbin; Lee, Kyoo-Seock

    2018-02-08

    Drought is one of the most severe natural disasters in the world and leads to serious challenges that affect both the natural environment and human societies. North Korea (NK) has frequently suffered from severe and prolonged droughts since the second half of the twentieth century. These droughts affect the growing conditions of agricultural crops, which have led to food shortages in NK. However, it is not easy to obtain ground data because NK is one of the most closed-off societies in the world. In this situation, remote sensing (RS) techniques and cloud computing climate data (CCCD) can be used for drought monitoring in NK. RS-derived drought indices and CCCD were used to determine the drought-vulnerable regions in the spring season in NK. After the results were compared and discussed, the following conclusions were derived: (1) 10.0% of the total area of NK is estimated to be a drought-vulnerable region. The most susceptible regions to drought appear in the eastern and western coastal regions, far from BaekDu-DaeGan (BDDG), while fewer drought regions are found near BDDG and the Nahngrim Mountains. The drought-vulnerable regions are the coastal regions of South Hamgyong Province, North Hamgyong Province, South Pyongan Province, and South Hwanghae Province. The latter region is the food basket of NK. (2) In terms of land cover, the drought-vulnerable regions mainly consisted of croplands and mixed forest.

  2. Use of monitoring data to support conservation management and policy decisions in Micronesia.

    PubMed

    Montambault, Jensen Reitz; Wongbusarakum, Supin; Leberer, Trina; Joseph, Eugene; Andrew, Wayne; Castro, Fran; Nevitt, Brooke; Golbuu, Yimnang; Oldiais, Noelle W; Groves, Craig R; Kostka, Willy; Houk, Peter

    2015-10-01

    Adaptive management implies a continuous knowledge-based decision-making process in conservation. Yet, the coupling of scientific monitoring and management frameworks remains rare in practice because formal and informal communication pathways are lacking. We examined 4 cases in Micronesia where conservation practitioners are using new knowledge in the form of monitoring data to advance marine conservation. These cases were drawn from projects in Micronesia Challenge jurisdictions that received funding for coupled monitoring-to-management frameworks and encompassed all segments of adaptive management. Monitoring in Helen Reef, Republic of Palau, was catalyzed by coral bleaching and revealed evidence of overfishing that led to increased enforcement and outreach. In Nimpal Channel, Yap, Federated States of Micronesia (FSM), monitoring the recovery of marine food resources after customary restrictions were put in place led to new, more effective enforcement approaches. Monitoring in Laolao Bay, Saipan, Commonwealth of the Northern Mariana Islands, was catalyzed by observable sediment loads from poor land-use practices and resulted in actions that reduced land-based threats, particularly littering and illegal burning, and revealed additional threats from overfishing. Pohnpei (FSM) began monitoring after observed declines in grouper spawning aggregations. This data led to adjusting marine conservation area boundaries and implementing market-based size class restrictions. Two themes emerged from these cases. First, in each case monitoring was conducted in a manner relevant to the social and ecological systems and integrated into the decision-making process. Second, conservation practitioners and scientists in these cases integrated culturally appropriate stakeholder engagement throughout all phases of the adaptive management cycle. More broadly, our study suggests, when describing adaptive management, providing more details on how monitoring and management activities are

  3. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-11-19

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

  4. 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

  5. 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.

  6. 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.

  7. Effect of drought on productivity in a Costa Rican tropical dry forest

    NASA Astrophysics Data System (ADS)

    Castro, S. M.; Sanchez-Azofeifa, G. A.; Sato, H.

    2018-04-01

    Climate models predict that precipitation patterns in tropical dry forests (TDFs) will change, with an overall reduction in rainfall amount and intensification of dry intervals, leading to greater susceptibility to drought. In this paper, we explore the effect of drought on phenology and carbon dynamics of a secondary TDF located in the Santa Rosa National Park (SRNP), Costa Rica. Through the use of optical sensors and an eddy covariance flux tower, seasonal phenology and carbon fluxes were monitored over a four-year period (2013-2016). Over this time frame, annual precipitation varied considerably. Total precipitation amounts for the 2013-2016 seasons equaled 1591.8 mm (+14.4 mm SD), 1112.9 mm (+9.9 mm SD), 600.8 mm (+7.6 mm SD), and 1762.2 mm (+13.9 mm SD), respectively. The 2014 and 2015 (ENSO) seasonal precipitation amounts represent a 30% and 63% reduction in precipitation, respectively, and were designated as drought seasons. Phenology was affected by precipitation patterns and availability. The onset of green-up was closely associated with pre-seasonal rains. Drought events lead to seasonal NDVI minimums and changes in phenologic cycle length. Carbon fluxes, assimilation, and photosynthetic light use efficiency were negatively affected by drought. Seasonal minimums in photosynthetic rates and light use efficiency were observed during drought events, and gross primary productivity was reduced by 13% and 42% during drought seasons 2014 and 2015, respectively. However, all four growth seasons were net carbon sinks. Results from this study contribute towards a deeper understanding of the impact of drought on TDF phenology and carbon dynamics.

  8. 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.

  9. Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

    PubMed

    D'Orangeville, Loïc; Maxwell, Justin; Kneeshaw, Daniel; Pederson, Neil; Duchesne, Louis; Logan, Travis; Houle, Daniel; Arseneault, Dominique; Beier, Colin M; Bishop, Daniel A; Druckenbrod, Daniel; Fraver, Shawn; Girard, François; Halman, Joshua; Hansen, Chris; Hart, Justin L; Hartmann, Henrik; Kaye, Margot; Leblanc, David; Manzoni, Stefano; Ouimet, Rock; Rayback, Shelly; Rollinson, Christine R; Phillips, Richard P

    2018-06-01

    Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ 50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors. © 2018 John Wiley & Sons Ltd.

  10. Plant Water Content is the Best Predictor of Drought-induced Mortality

    NASA Astrophysics Data System (ADS)

    Sapes, G.; Roskilly, B.; Dobrowski, S.; Sala, A.

    2017-12-01

    Predicting drought-induced forest mortality remains extremely challenging. Recent research has shown that both plant hydraulics and stored non-structural carbohydrates (NSC) interact during drought-induced mortality. The strong interaction between these two variables and the fact that they are both difficult to measure render drought-induced plant mortality extremely difficult to monitor and predict. A variable that is easier to measure and that integrates hydraulic transport and carbohydrate dynamics may, therefore, improve our ability to monitor and predict mortality. Here, we tested whether plant water content is such an integrator variable and, therefore, a better predictor of mortality under drought. We subjected 250 two-year-old ponderosa pine seedlings to drought until they died in a greenhouse experiment. Periodically during the dry down, we measured percent loss of hydraulic conductivity (PLC), NSC concentration (starch and soluble sugars), and tissue volumetric water content (VWC) in roots, stems and leaves. At each measurement time, a separate set of seedlings were re-watered to estimate the probability of mortality at the population level. Linear models were used to explore whether PLC and NSC were linked to VWC and to determine which of the three variables predicted mortality the best. As expected, plants lost hydraulic conductivity in stems and roots during the dry down. Starch concentrations also decreased in all organs as the drought proceeded. In contrast, soluble sugars increased in stems and roots, consistent with the conversion of stored NSCs into osmotically active compounds. Models containing both PLC and NSC concentrations as predictors of VWC were highly significant in all organs and at the whole plant level, indicating that water content is influenced by both PLC and NSCs. PLC, NSC, and VWC explained mortality across organs and at the whole plant level, but VWC was the best predictor (R2 = 0.99). Our results indicate that plant water

  11. Towards a geophysical decision-support system for monitoring and managing unstable slopes

    NASA Astrophysics Data System (ADS)

    Chambers, J. E.; Meldrum, P.; Wilkinson, P. B.; Uhlemann, S.; Swift, R. T.; Inauen, C.; Gunn, D.; Kuras, O.; Whiteley, J.; Kendall, J. M.

    2017-12-01

    Conventional approaches for condition monitoring, such as walk over surveys, remote sensing or intrusive sampling, are often inadequate for predicting instabilities in natural and engineered slopes. Surface observations cannot detect the subsurface precursors to failure events; instead they can only identify failure once it has begun. On the other hand, intrusive investigations using boreholes only sample a very small volume of ground and hence small scale deterioration process in heterogeneous ground conditions can easily be missed. It is increasingly being recognised that geophysical techniques can complement conventional approaches by providing spatial subsurface information. Here we describe the development and testing of a new geophysical slope monitoring system. It is built around low-cost electrical resistivity tomography instrumentation, combined with integrated geotechnical logging capability, and coupled with data telemetry. An automated data processing and analysis workflow is being developed to streamline information delivery. The development of this approach has provided the basis of a decision-support tool for monitoring and managing unstable slopes. The hardware component of the system has been operational at a number of field sites associated with a range of natural and engineered slopes for up to two years. We report on the monitoring results from these sites, discuss the practicalities of installing and maintaining long-term geophysical monitoring infrastructure, and consider the requirements of a fully automated data processing and analysis workflow. We propose that the result of this development work is a practical decision-support tool that can provide near-real-time information relating to the internal condition of problematic slopes.

  12. Drought and resprouting plants

    DOE PAGES

    Zeppel, Melanie J. B.; Harrison, Sandy P.; Adams, Henry D.; ...

    2014-12-17

    Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21 st century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly thanmore » ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. Furthermore, the strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented.« less

  13. Drought and resprouting plants.

    PubMed

    Zeppel, Melanie J B; Harrison, Sandy P; Adams, Henry D; Kelley, Douglas I; Li, Guangqi; Tissue, David T; Dawson, Todd E; Fensham, Rod; Medlyn, Belinda E; Palmer, Anthony; West, Adam G; McDowell, Nate G

    2015-04-01

    Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21st Century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly than ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. The strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

  14. Drought-responsive protein profiles reveal diverse defense pathways in corn kernels under field drought atress

    USDA-ARS?s Scientific Manuscript database

    Drought stress is a major factor which contributes to disease susceptibility and yield loss in agricultural crops. To identify drought responsive proteins and explore metabolic pathways involved in maize tolerance to drought stress, two lines (B73 and Lo964) with contrasting drought sensitivity were...

  15. 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, ...

  16. 33 Years of Near-Global Daily Precipitation from Multisatellite Observations and its Application to Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Ashouri, H.; Hsu, K.; Sorooshian, S.; Braithwaite, D.; Knapp, K. R.; Cecil, L. D.

    2013-12-01

    PERSIANN Climate Data Record (PERSIANN-CDR) is a new retrospective satellite-based precipitation data set that is constructed for long-term hydrological and climate studies. The PERSIANN-CDR is a near-global (60°S-60°N) long-term (1980-2012), multi-satellite, high-resolution precipitation product that provides rain rate estimates at 0.25° and daily spatiotemporal resolution. PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high resolution precipitation data set for studying the spatial and temporal variations and changes of precipitation patterns, particularly in a scale relevant to climate extremes at the global scale. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data from the International Satellite Cloud Climatology Project (ISCCP). PERSIANN-CDR is adjusted using the Global Precipitation Climatology Project (GPCP) monthly precipitation to maintain consistency of two data sets at 2.5° monthly scale throughout the entire reconstruction period. PERSIANN-CDR daily precipitation data demonstrates considerable consistency with both GPCP monthly and GPCP 1DD precipitation products. Verification studies over Hurricane Katrina show that PERSIANN-CDR has a good agreement with NCEP Stage IV radar data, noting that PERSIANN-CDR has better spatial coverage. In addition, the Probability Density Function (PDF) of PERSIANN-CDR over the contiguous United States was compared with the PDFs extracted from CPC gauge data and the TMPA precipitation product. The experiment also shows good agreement of the PDF of PERSIANN-CDR with the PDFs of TMPA and CPC gauge data. The application of PERSIANN-CDR in regional and global drought monitoring is investigated. Consisting of more than three decades of high-resolution precipitation data, PERSIANN-CDR makes us capable of long-term assessment of droughts at a higher resolution (0.25°) than previously possible. The results will be presented at the meeting.

  17. 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.

  18. 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

  19. Drivers of atmospheric evaporative demand during African droughts

    NASA Astrophysics Data System (ADS)

    Blakeley, S. L.; Harrison, L.; Hobbins, M.; Dewes, C.; Funk, C. C.; Shukla, S.; Husak, G. J.

    2017-12-01

    Seeking to advance the practice of famine early warning across sub-Saharan Africa we illuminate past drivers of high-impact droughts to gain a better understanding of the evaporative processes involved in drought dynamics. Atmospheric evaporative demand (ETo) is often used to estimate plant water balance and drought impacts to vegetation, and previously demonstrated linkages between precipitation, temperature, and ETo need to be better understood. This work is timely as new data streams will enable near-real-time monitoring of ETo and incorporation of ETo forecasts into seasonal outlooks for African growing seasons. For historical droughts during major growing seasons in sub-Saharan Africa, we evaluate ETo and identify main drivers for drought cases-identified based on below-normal precipitation during the wettest three months of the growing season-and contrast these with the ETo drivers that dominate in wetter years (we also consider droughts triggered by above normal ETo). Our focus is on regions of Africa where adequate precipitation is important for productive agriculture and pastoral activities and where evaporative demand might exacerbate moisture limitations. It is expected that important ETo drivers are partly connected with precipitation-related processes but that there are variations between regions and events. The goal here is to provide a generalized understanding of what aspects of evaporative demand historically have posed an additional hazard to plant stress and how precipitation outcomes are responsible for the ETo drivers. In addition, we explore whether there have been discernible changes through time in regard to ETo drivers during below-normal precipitation seasons. Upper and lower terciles of CHIRPS precipitation are used to identify anomalous dry and wet cases. The ETo dataset spans the 1980-near present period and is calculated following ASCE's formulation of Penman-Monteith method driven by daily temperature, humidity, wind speed, and solar

  20. Predicting and adapting to the agricultural impacts of large-scale drought (Invited)

    NASA Astrophysics Data System (ADS)

    Elliott, J. W.; Glotter, M.; Best, N.; Ruane, A. C.; Boote, K.; Hatfield, J.; Jones, J.; Rosenzweig, C.; Smith, L. A.; Foster, I.

    2013-12-01

    The impact of drought on agriculture is an important socioeconomic consequence of climate extremes. Drought affects millions of people globally each year, causing an average of 6-8 billion of damage annually in the U.S. alone. The 1988 U.S. drought is estimated to have cost 79 billion in 2013 dollars, behind only Hurricane Katrina as the most costly U.S. climate-related disaster in recent decades. The 2012 U.S. drought is expected to cost about 30 billion. Droughts and heat waves accounted for 12% of all billion-dollar disaster events in the U.S. from 1980-2011 but almost one quarter of total monetary damages. To make matters worse, the frequency and severity of large-scale droughts in important agricultural regions is expected to increase as temperatures rise and precipitation patterns shift, leading some researchers to suggest that extended drought will harm more people than any other climate-related impact, specifically in the area of food security. Improved understanding and forecasts of drought would have both immediate and long-term implications for the global economy and food security. We show that mechanistic agricultural models, applied in novel ways, can reproduce historical crop yield anomalies, especially in seasons for which drought is the overriding factor. With more accurate observations and forecasts for temperature and precipitation, the accuracy and lead times of drought impact predictions could be improved further. We provide evidence that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production in recent decades, adaptations that could be applied elsewhere. This work suggests a new approach to modeling, monitoring, and forecasting drought impacts on agriculture. Simulated (dashed line), observed (solid line), and observed linear trend (dashed straight green line) of national average maize yield in tonnes per hectare from 1979-2012. The red dot indicates the USDA estimate for 2012