Science.gov

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. 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.

  3. Drought management decisions and information requirements

    NASA Astrophysics Data System (ADS)

    Linés Díaz, Clara; Werner, Micha; Mynett, Arthur

    2015-04-01

    Droughts affect the entire water cycle producing a wide range of negative environmental, economic and social impacts to such an extent that they are considered to be the most damaging and costliest of natural hazards. The implementation of drought management plans can contribute to mitigate these negative effects by defining mitigation measures. These plans often include early detection and monitoring systems. However, drought is a complex phenomenon to monitor due to the prolonged duration of events, the difficulty to determine the onset and cessation, the spatial extent affected and the wide range of impacts. Generally drought plans rely on indicators or information systems that combine different kinds of data to produce the required information to support operational management decisions. Therefore, the availability and reliability of data sources to fulfil the information needs of the decision process is crucial for drought management. This research explores the role of data and its uncertainty within operational drought management decision processes. Different decision processes at basin level will be examined to identify their key characteristics, and in particular, the information required to support the decisions and the impact of uncertainty in triggering the implementation of adequate measures. A general framework within which drought management decision processes can be evaluated will be proposed. This will be tested for the decision process followed by the Ebro river basin authority to trigger drought mitigation measures. This decision process relies on a drought indicator based on monthly precipitation, three-month flow data and reservoir level data from measurement stations to detect drought, quantify its intensity and trigger the corresponding mitigation measures according to threshold levels defined for the basin.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Drought monitoring through parallel computing

    SciTech Connect

    Burrage, K.; Belward, J.; Lau, L.; Rezny, M.; Young, R.

    1993-12-31

    One area where high performance computing can make a significant social and economic impact in Australia (especially in view of the recent El-Nino) is in the accurate and efficient monitoring and prediction of drought conditions - both in terms of speed of calculation and in high quality visualization. As a consequence, the Queensland Department of Primary Industries (DPI) is developing a spatial model of pasture growth and utilization for monitoring, assessment and prediction of the future of the state`s rangeloads. This system incorporates soil class, pasture type, tree cover, herbivore density and meterological data. DPI`s drought research program aims to predict the occurrence of feed deficits and land condition alerts on a quarter to half shire basis over Queensland. This will provide a basis for large-scale management decisions by graziers and politicians alike.

  9. The German Drought Monitor

    NASA Astrophysics Data System (ADS)

    Marx, Andreas; Zink, Matthias; Pommerencke, Julia; Kumar, Rohini; Thober, Stephan; Samaniego, Luis

    2015-04-01

    Soil moisture droughts reduce the amount of water available to plant growth potentially leading e.g. to crop failure or increased forest fire risk. The threat of human livelihoods in developing countries and large economic losses in developed ones are severe consequences of these events. Monitoring the current state of soil water content allows to improve water management to mitigate the associated damages. Since summer 2014, the German Drought Monitor (GDM, available at: www.ufz.de/droughtmonitor) has been established using an operational hydrological modeling system, which consists of 3 steps: (1) the daily download of meteorological forcing data, consistency check and interpolation of this data, (2) running the mesoscale Hydrologic Model (mHM; Samaniego et al. 2010) and saving the state variables at the end of the model run as restart-file for the next days run, and (3) calculation of the soil moisture index (SMI, Samaniego et al. 2013, JHM) and visualization of the drought data. The hydrological model mHM was used to generate daily soil moisture fields for the period 1954-2013 over the entire area of Germany at a high spatial resolution of 4 x 4 km². The model requires daily precipitation, temperature, and potential evapotranspiration as forcing. A three-layer soil scheme was used to model the soil moisture dynamics over the entire root zone depth. Based on the 60 year simulation of soil moisture, the frequency distributions have been calculated for each grid cell to derive the soil moisture index. In this beta version, we do a monthly online update of the SMI. Furthermore, a trend analysis of drought events for 69 German subregions since 1954 was conducted. It showed that for most parts of Germany, the frequency of abnormally dry conditions increased while the stronger drought situations with SMI<0.2 decreased at the same time. For the coming year, a stakeholder consultation is planned. The aim is to clarify for whom a drought monitor would be useful, what

  10. 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

  11. 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

  12. Integrated drought monitoring approach: bringing diverse information into comprehensive drought monitoring system

    NASA Astrophysics Data System (ADS)

    Ceglar, A.; Medved-Cvikl, B.; Kajfež-Bogataj, L.

    2011-12-01

    Understanding the complexity of drought is crucial to convey improved information on drought situation to decision-makers and general public. Addressing this need by sharing drought data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. This is also a challenge for Drought management centre for South-Eastern Europe (DMCSEE). In one of the most vulnerable regions to drought, according to the IPCC projections, drought-related damages have already had large impact on the economy and welfare. Trans-national integrated approach is therefore necessary for successful tracking of drought, comparing its impacts using common methodology and assessing vulnerability of various sectors. First step in building transnational integrated approach is to combine very diverse monitoring systems from technical perspective in one comprehensive drought monitoring system. In this regard, the EuroGEOSS (European answer to GEOSS - Global Earth Observation System of Systems) portends major benefits through various sharing mechanisms and gives access to services that can be linked together to process and generate new understandable knowledge and information (figure 1). Drought monitoring systems on different spatial levels can greatly benefit from integrated approach, proposed by the EuroGEOSS project. Benefits of interoperability arrangements and integrated monitoring for DMCSEE and European Drought Observatory (EDO) are presented in the article. Established infrastructure enables the use of information on various spatial levels (continental, regional and national). Technical solution enables the inclusion of very diverse drought monitoring systems from south-eastern Europe into EDO. Integrated drought monitoring system improves information on all essential levels (timing, intensity, duration and spatial extent of a specific drought episode) in the framework of existing polices and politics. The common

  13. The drought risk atlas: Enhancing decision support for drought risk management in the United States

    NASA Astrophysics Data System (ADS)

    Svoboda, Mark D.; Fuchs, Brian A.; Poulsen, Chris C.; Nothwehr, Jeff R.

    2015-07-01

    Decision makers have continuously asked for better tools and resources to help them assess their risks related to climate variability and extremes. Drought is one of the risks they face, and the need for better drought risk tools and resources has also been expressed. With drought continuing to be one of the most problematic and costly natural disasters within the United States, and building on the work of the original National Drought Atlas (NDA) (1996), an updated and expanded Drought Risk Atlas (DRA) decision support tool for the United States was developed and is housed at the National Drought Mitigation Center. The DRA (1) provides weekly calculations of multiple indices/indicators, with more than a billion records made freely available, including the SPI, SPEI, PDSI, scPDSI, Deciles and U.S. Drought Monitor; (2) houses more than 3000 stations with data through 2012, nearly tripling the station count of the original NDA; (3) utilizes a much longer period of record, nearly double that of the NDA in most cases; (4) when fully completed, will house a cache of more than 500,000 gridded drought index maps; (5) will allow us to analyze and assess trends and various characteristics of drought, including frequency, intensity, duration and magnitude; (6) will become a resource for the National Weather Service (NWS) personnel around the country by transferring the application into the field through integration within the NWS's newly developed Local Climate Analysis Tool (LCAT); and (7) work directly with the National Integrated Drought Information System (NIDIS) program office to include the information contained in the DRA into NIDIS's regional drought early warning system pilot basins and the U.S. Drought Portal for broad dissemination to the user community and general public.

  14. 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

  15. 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.

  16. Drought monitoring: Historical and current perspectives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  17. An Interface to Drought Mitigation: Decision Support Tools from the National Drought Mitigation Center

    NASA Astrophysics Data System (ADS)

    Svoboda, M.; Fuchs, B.; Hayes, M. J.

    2012-12-01

    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 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, services and decision support applications, along with maintaining a number of operational drought-related tools and products including the U.S. Drought Monitor (USDM), Drought Impact Reporter (DIR) and Vegetation Drought Response Index (VegDRI). The NDMC's newly launched National Drought Atlas (NDA) will be the focus of this presentation. Building off the concept of the original National Electronic Drought Atlas (NEDA) developed by the United States Army Corps of Engineers (led by Hoskings, Wallis and Guttman in the early 1990s), the original NEDA consisted of approximately 1000 stations taken from the Historical Climate Network (HCN). The period of record was limited at that time with most stations only having digital data from the late 1940s to present. For the NDMC's NDA, more than 12,000 stations with precipitation and/or temperature records from the National Weather Service Cooperative data (COOP) network were analyzed through the Regional Climate Centers' (RCCs) Applied Climate Information System (ACIS). From the initial sample set of 12,000 sites considered, over 3000 stations had at least 40 years of data and over 1700 sites had over 60 years of data meeting our criteria. A unique period of record (POR) was established for each station based on the screening criteria, with each station having a unique starting date. From the final selection of 3059 stations, all have at least 40+ years of data and 827 sites contain over 80+ years of data. In essence, the new NDA tripled the size and doubled the period of record of those sites used in

  18. Monitoring vegetation responses to drought -- linking Remotely-sensed Drought Indices with Meteorological drought indices

    NASA Astrophysics Data System (ADS)

    Wang, H.; Lin, H.; Liu, D.

    2013-12-01

    Abstract: Effectively monitoring vegetation drought is of great significance in ecological conservation and agriculture irrigation at the regional scale. Combining meteorological drought indices with remotely sensed drought indices can improve tracking vegetation dynamic under the threat of drought. This study analyzes the dynamics of spatially-defined Temperature Vegetation Dryness Index (TVDI) and temporally-defined Vegetation Health Index (VHI) from remotely sensed NDVI and LST datasets in the dry spells in Southwest China. We analyzed the correlation between remotely sensed drought indices and meteorological drought index of different time scales. The results show that TVDI was limited by the spatial variations of LST and NDVI, while VHI was limited by the temporal variations of LST and NDVI. Station-based buffering analysis indicates that the extracted remotely sensed drought indices and Standard Precipitation Index (SPI) could reach stable correlation with buffering radius larger than 35 km. Three factors affect the spatiotemporal relationship between remotely sensed drought indices and SPI: i) different vegetation types; ii) the timescale of SPI; and iii) remote sensing data noise. Vegetation responds differently to meteorological drought at various time scales. The correlation between SPI6 and VHI is more significant than that between SPI6 and TVDI. Spatial consistency between VHI and TVDI varies with drought aggravation. In early drought period from October to December, VHI and TVDI show limited consistency due to the low quality of remotely sensed images. The study helps to improve monitoring vegetation drought using both meteorological drought indices and remotely sensed drought indices.

  19. Developing a European Drought Observatory for Monitoring, Assessing and Forecasting Droughts across the European Continent

    NASA Astrophysics Data System (ADS)

    Vogt, J.; Barbosa, P.; Hofer, B.; Magni, D.; Jager, A. D.; Singleton, A.; Horion, S.; Sepulcre, G.; Micale, F.; Sokolova, E.; Calcagni, L.; Marioni, M.; Antofie, T. E.

    2011-12-01

    Many European countries have repeatedly been affected by droughts, resulting in considerable ecological and economic damage. 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 national activities with a European view. As droughts affect the entire water cycle continuous monitoring of a suite of indicators is required. Drought indicators at continental scale are supplemented by indicators at national, regional and local scales, providing more detailed information. At the core of the European Drought Observatory (EDO) are a portal and a map server presenting Europe-wide up-to-date drought-relevant information to the public and to decision makers in policy and water resources management. The final portal will include access to metadata catalogues, media reports, a map server and other related resources. The current version of EDO publishes continental information based on data processed and analysed at JRC as well as more detailed information at national and river basin scale processed by the local authorities. Available drought products include monthly updated Standardized Precipitation Indices (SPI), modelled soil moisture anomalies, remote sensing observations on the state of the vegetation cover (i.e. fAPAR and NDWI) and groundwater levels. A one-week soil moisture anomaly forecast complements the picture. Access to information at the national and river basin scale is established through interoperability arrangements with local authorities, making use of a special metadata catalogue and OWS standards (especially WMS and WCS). In addition, time series of drought indices can be retrieved for grid cells and administrative regions in

  20. Monitoring groundwater drought with GRACE data assimilation

    NASA Astrophysics Data System (ADS)

    Li, B.; Rodell, M.; Beaudoing, H. K.; Getirana, A.; Zaitchik, B. F.

    2015-12-01

    Groundwater drought is a distinct class of drought, not a sub-class of meteorological, agricultural and hydrological drought and has profound impacts on natural environments and societies. Due to a deficiency of in situ measurements, we developed a groundwater drought indicator using groundwater change estimates derived by assimilating GRACE derived terrestrial water storage (TWS) anomalies into the NASA Catchment land surface model. Data assimilation enables spatial and temporal downscaling of coarse GRACE TWS observations (monthly and ~150,000 km2 effective spatial resolution) and extrapolation to near-real time. In this talk, we will present our latest progress on using GRACE satellite data for groundwater drought monitoring in the U.S. and globally. Characteristics of this groundwater drought indicator will be discussed, including its relationship with other types of drought and how they are influenced by model physics and climate conditions. Results are evaluated using in situ groundwater observations.

  1. 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

  2. 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. PMID:25977759

  3. Development and Applications of the U.S. Drought Monitor and North America Drought Monitor

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2007-05-01

    Drought is an important climatological phenomenon which has significant socioeconomic and environmental impacts. Several drought indices have been developed during the last hundred years to quantify drought, but all of them either were developed for specific applications and/or regions, or have limitations which restrict their use. In the U.S., a drought monitoring tool was developed in the late 1990s through a federal-state collaborative effort to consolidate and centralize drought monitoring activities. This tool, the U.S. Drought Monitor (USDM), consists of a weekly map and narrative product which describes current drought conditions according to a scale ranging from moderate drought (D1) to exceptional drought (D4). Conditions which are dry but not yet of drought severity are categorized as abnormally dry (D0). The USDM draws its strength from the collaborative input at the federal (USDA, NOAA), regional (NOAA Regional Climate Centers), state, and local levels and from the objective synthesis of several drought-related indices. In late 2002, the methodology of the USDM was extended internationally to develop the North America Drought Monitor (NADM), which is a monthly map and narrative product that describes drought across the U.S., Mexico, and Canada. This paper will describe the development of the USDM and NADM, and discuss examples of their applications.

  4. 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

  5. Drought Monitoring in Peru as a Climate Service

    NASA Astrophysics Data System (ADS)

    Lavado, Waldo; Felipe, Oscar; Caycho, Tania; Sosa, Jesus; Fernandez, Carlos; Endara, Sofia

    2015-04-01

    Given the need to reduce socio- economic and environmental drought in Peru as well as the vulnerability and increasing responsiveness and recovery to these events, the National Service of Meteorology and Hydrology of Peru (SENAMHI ) in conjunction with the Peru's Environment Ministry has developed a plan Drought Monitoring nationwide, which consists of two components: 1) Monitoring System and 2 ) Dissemination System . The first component consists of calculating drought indicators at national level; and for that purpose we have selected the following indexes: Normal Precipitation Index (NPI), Standardized Precipitation Index (SPI) , Precipitation Concentration Index (PCI) , Vegetation Condition Index (VCI ) , Temperature Condition Index ( TCI) , Healthy Vegetation Index (VHI ) and Streamflow Drought Index (SDI). In order to estimate these index observed climatological and hydrological data of SENAMHI network is used as well as remote sensing data of precipitation, temperature and vegetation (TRMM, CHIRPS and MODIS). The second component is the spread of these indicators and a compilation thereof to a summary document that integrates all indicators (Monthly Bulletin). This will be done through newsletters and a website (www.senamhi.gob.pe/serviciosclimaticos); in the case of exceptional drought events special notes will be made. A date has launched the first newsletter in September 2014. This drought monitoring system will be used as an instrument of climate service and we intend to make it a useful tool for decision makers and the general population .

  6. Overview and Update of the North America Drought Monitor and North America Climate Extremes Monitoring System

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2006-12-01

    The North America Drought Monitor (NADM) is a joint operational drought monitoring activity between scientists and other specialists in the United States, Mexico, and Canada. Like all weather phenomena, drought occurs irrespective of political and international boundaries. The monthly map and narrative product created by this first-of-its-kind effort provides an integrated continental-scale drought assessment tool for decision-makers in all three countries involved in drought monitoring, drought mitigation, and related climate services. The product is prepared by a rotating primary author who utilizes drought indicators which are computed using standard methodologies for stations across the continent, plus national drought monitoring products and feedback from local experts in each of the three countries. The participants include, within the United States: the NOAA National Climatic Data Center, NOAA Climate Prediction Center, USDA Joint Agricultural Weather Facility, and National Drought Mitigation Center; within Mexico: Servicio Meteorologico Nacional/Comision Nacional del Agua; and within Canada: Agriculture and Agrifood Canada and the Meteorological Service of Canada. The NADM is part of a North America Climate Extremes Monitoring (NACEM) system which will monitor and assess climate extremes across the continent. Several climate indicators are currently computed from station daily data to measure (in addition to drought) heavy precipitation, heat waves, and cold waves. Future efforts will add indicators to monitor storm severity and severe weather, including the creation of a North America Climate Extremes Index (NACEI) patterned after the U.S. Climate Extremes Index (USCEI). This presentation will review the history of the NADM/NACEM effort, the data utilized, the indicators computed, and the product preparation and peer review process.

  7. Drought monitoring using remote sensing of evapotranspiration

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. The drought calculator: decision support tool for predicting forage growth during drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Drought Calculator (DC), a spreadsheet-based decision support system, was developed to help ranchers and range managers predict reductions in forage production due to drought. Forage growth potential (FGP) is predicted as a weighted average of monthly precipitation during the spring. Precipita...

  9. 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

  10. 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

  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. NOAA Drought Task Force: A Coordinated Research Initiative to Advance Drought Understanding, Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Mariotti, A.; Barrie, D.

    2014-12-01

    The NOAA's Drought Task Force was first established in October 2011 and renewed in October 2014 with the goal of achieving significant new advances in the ability to understand, monitor and predict drought over North America. The Task Force is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in support of the National Integrated Drought Information System NIDIS. The Drought Task Force also represents an important research contribution to efforts to develop an international Global Drought Information System (GDIS). The Drought Task Force brings together leading drought scientists research laboratories and/or operational centers from NOAA, other U.S. agencies laboratories and academia. Their concerted research effort builds on individual MAPP research projects and related drought-research sector developments. The projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those evaluating new drought monitoring and prediction tools for operational and service purposes. This contribution will present an overview of Drought Task Force activities and plans to date, including highlights of research activities and how the group has been working in partnership with NIDIS and synergy with GDIS to advance the science underpinning the development, assessment and provision of drought information.

  13. Drought monitoring and analysis in China based on the Integrated Surface Drought Index (ISDI)

    NASA Astrophysics Data System (ADS)

    Wu, Jianjun; Zhou, Lei; Mo, Xinyu; Zhou, Hongkui; Zhang, Jie; Jia, Ruijing

    2015-09-01

    Timely and accurate monitoring of the onset and evolution of drought in China are important to reduce losses from drought. The Integrated Surface Drought Index (ISDI) which originally established in mideast China shows a large potential for real-time regional drought monitoring. However, ISDI is still at the developmental stage, and the applicability of the index requires further examination especially for China with vast area, climatic conditions, complex topography, and land cover. Furthermore, ISDI model depends on the historical training data corresponding to the study area. ISDI application in China must be remodeled using the historical training data over China. In this paper, we remodeled ISDI over China based on previous work and evaluated its capability for near real-time drought monitoring. Using the Palmer Drought Severity Index (PDSI) as a dependent variable, ISDI integrates climate-based drought indices, satellite-based Vegetation Index (VI) and land surface temperature (LST) with other biophysical and elevation data to produce a 1-km regional drought condition map at 16-day intervals. Strong relationships were determined between the calculated ISDI and PDSI for spring, summer and autumn, and all of the correlation coefficients exceeded 0.8. The initial ISDI results demonstrated a good performance for monitoring droughts in southwestern China from 2009 to 2010, high temperatures and droughts in southern China in 2013, and floods in northeastern China in 2013. The higher spatial resolution and near real-time capability of ISDI can provide important inputs for drought management and mitigation in China.

  14. 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

  15. Monitoring the 1996 Drought Using the Standardized Precipitation Index.

    NASA Astrophysics Data System (ADS)

    Hayes, Michael J.; Svoboda, Mark. D.; Wilhite, Donald A.; Vanyarkho, Olga V.

    1999-03-01

    Droughts are difficult to detect and monitor. Drought indices, most commonly the Palmer Drought Severity Index (PDSI), have been used with limited success as operational drought monitoring tools and triggers for policy responses. Recently, a new index, the Standardized Precipitation Index (SPI), was developed to improve drought detection and monitoring capabilities. The SPI has several characteristics that are an improvement over previous indices, including its simplicity and temporal flexibility, that allow its application for water resources on all timescales. In this article, the 1996 drought in the southern plains and southwestern United States is examined using the SPI. A series of maps are used to illustrate how the SPI would have assisted in being able to detect the onset of the drought and monitor its progression. A case study investigating the drought in greater detail for Texas is also given. The SPI demonstrated that it is a tool that should be used operationally as part of a state, regional, or national drought watch system in the United States. During the 1996 drought, the SPI detected the onset of the drought at least 1 month in advance of the PDSI. This timeliness will be invaluable for improving mitigation and response actions of state and federal government to drought-affected regions in the future.

  16. A comprehensive drought monitoring method integrating MODIS and TRMM data

    NASA Astrophysics Data System (ADS)

    Du, Lingtong; Tian, Qingjiu; Yu, Tao; Meng, Qingyan; Jancso, Tamas; Udvardy, Peter; Huang, Yan

    2013-08-01

    Drought is a complex hazard caused by the breaking of water balance and it has always an impact on agricultural, ecological and socio-economic spheres. Although the drought indices deriving from remote sensing data have been used to monitor meteorological or agricultural drought, there are no indices that can suitably reflect the comprehensive information of drought from meteorological to agricultural aspects. In this paper, the synthesized drought index (SDI) is defined as a principal component of vegetation condition index (VCI), temperature condition index (TCI) and precipitation condition index (PCI). SDI integrates multi-source remote sensing data from moderate resolution imaging spectroradiometer (MODIS) and tropical rainfall measuring mission (TRMM) and it synthesizes precipitation deficits, soil thermal stress and vegetation growth status in drought process. Therefore, this method is favorable to monitor the comprehensive drought. In our research, a heavy drought process was accurately explored using SDI in Shandong province, China from 2010 to 2011. Finally, a validation was implemented and its results show that SDI is not only strongly correlated with 3-month scales standardized precipitation index (SPI3), but also with variation of crop yield and drought-affected crop areas. It was proved that this index is a comprehensive drought monitoring indicator and it can contain not only the meteorological drought information but also it can reflect the drought influence on agriculture.

  17. Assessing the Remotely Sensed Drought Severity Index for Agricultural Drought Monitoring in North China

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Huang, J.; Mu, Q.

    2014-12-01

    With a warming climate, the world has experienced frequent droughts during the past few decades. A remotely sensed Drought Severity Index (DSI), which integrates both vegetation growth condition and evapotranspiration, has been recently proposed for drought monitoring at the global scale. However, there has been little research on its utility for regional application, especially on agricultural drought. As an important winter wheat producing region, the North China has suffered from frequent droughts in recent years. In this study, the capability of the DSI for drought monitoring and impact analysis in five wheat producing provinces of North China was investigated. First, the DSI was compared with precipitation and soil moisture to show its ability for characterizing moisture status. Then specifically for agricultural drought, the DSI was evaluated against agricultural drought severity and the impacts of drought on crop yield during the growing season were also explored using the 8-day DSI data. The main conclusions are: (1) The DSI shows generally good ability for characterizing moisture conditions at the province level with varying ability during winter wheat main growing season (March-June), and the best relationship was found in April. (2) Despite varying capability, the DSI is quite effective in characterizing agricultural drought severity at the province level. (3) Drought shows generally increasing agricultural impacts during winter wheat main growing season (March-June), with little impacts in March (green-up stage), emerging impacts in April (jointing and booting stages) and significant drought impacts in May (heading and filling stages). (4) Based on the spatial pattern of agricultural drought impacts, densely winter wheat planted areas such as South Hebei, Central/West Shandong and North/East Henan are identified as drought vulnerable regions and comprehensive monitoring in these hotspots is highly recommended.

  18. A Remote Sensing-based Global Agricultural Drought Monitoring and Forecasting System for Supporting GEOSS (Invited)

    NASA Astrophysics Data System (ADS)

    di, L.; Yu, G.; Han, W.; Deng, M.

    2010-12-01

    Group on Earth Observations (GEO) is a voluntary partnership of governments and international organizations. GEO is coordinating the implementation of the Global Earth Observation System of Systems (GEOSS), a worldwide effort to make Earth observation resources more useful to the society. As one of the important technical contributors to GEOSS, the Center for Spatial Information Science and Systems (CSISS), George Mason University, is implementing a remote sensing-based global agricultural drought monitoring and forecasting system (GADMFS) as a GEOSS societal benefit areas (agriculture and water) prototype. The goals of the project are 1) to establish a system as a component of GEOSS for providing global on-demand and systematic agriculture drought information to users worldwide, and 2) to support decision-making with improved monitoring, forecasting, and analyses of agriculture drought. GADMFS has adopted the service-oriented architecture and is based on standard-compliant interoperable geospatial Web services to provide online on-demand drought conditions and forecasting at ~1 km spatial and daily and weekly temporal resolutions for any part of the world to world-wide users through the Internet. Applicable GEOSS recommended open standards are followed in the system implementation. The system’s drought monitoring relies on drought-related parameters, such as surface and root-zone soil moisture and NDVI time series derived from remote sensing data, to provide the current conditions of agricultural drought. The system links to near real-time satellite remote sensing data sources from NASA and NOAA for the monitoring purpose. For drought forecasting, the system utilizes a neural-network based modeling algorithm. The algorithm is trained with inputs of current and historic vegetation-based and climate-based drought index data, biophysical characteristics of the environment, and time-series weather data. The trained algorithm will establish per-pixel model for

  19. Monitoring agricultural drought with climate-based drought indices in China

    NASA Astrophysics Data System (ADS)

    Wang, H.; Zhang, C., Sr.; Jeffery, R. C.

    2015-12-01

    Agricultural drought monitoring significantly influences food security in recent decades. Soil moisture shortages adversely affecting agriculture is one important indicator for agricultural drought monitoring. Because of limited soil moisture observations, characterizing soil moisture using climate-based drought indices has great practical meaning. The agricultural area in China was identified by crop identification from remotely sensed data. Drought indices of multiple timescale or from two-layer bucket model were analyzed. In most agricultural areas of China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer time scales. In general, multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0-5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90-100-cm depth than the Z index. Soil moisture-drought indices relationship was significantly affected by soil organic carbon density. Effective agriculture drought monitoring can be conducted with climate-based drought indices from widely available climatic data and crop area identification from remote sensing. Authors:Hongshuo wang1, Chao Zhang1, Jeffery C Rogers2 1 China agricultural university 2 Ohio state University Key words: Agricultural drought, SPI, SPEI, PDSI, Z index, crop identification

  20. 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.

  1. Enhanced Drought Monitoring in the Upper Colorado River Basin

    NASA Astrophysics Data System (ADS)

    Doesken, N.; Smith, R.; Ryan, W.; Schwalbe, Z.; Verdin, J. P.

    2012-12-01

    As a part of the National Integrated Drought Information System's Upper Colorado River Basin pilot project, an aggressive collaborative drought monitoring and communication process was initiated in 2010. Weekly climate, drought and water supply assessments were begun which included webinars during critical times of the year -- primarily late January through mid summer. A diverse set of stakeholders ranging from ski area operators, river commissioners, state and federal agency representatives, public land managers, municipal water providers, agricultural interests and media from a 3-state area were invited to participate along with National Weather Service forecast office personal, state climate office representatives and other information providers. The process evolved to become a weekly drought monitoring "committee" providing detailed input to the U.S. Drought Monitor national author. In 2012 this new system was put to the test as dry winter conditions exploded into extreme and widespread drought as the normal spring storms failed to materialize and instead long-duration above average temperatures added evaporative stress to the already limited water supplies. This presentation examines this effort with an emphasis on stakeholder engagement. The overall impact of the 2012 drought appears, so far, to be less than what was experienced in 2002 although measured stream flow appears tp be similar. To what extent this could be attributed to the enhanced drought monitoring and communication will be discussed. The sustainability of this aggressive monitoring effort will also be assessed.

  2. 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

  3. 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.

  4. Drought monitoring in the Northwestern United States

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Drought along the US Pacific Coast has grabbed headlines this year. During this past spring and summer, California has continued to experience a multi-year drought with water restrictions imposed by the state; the governor of Washington has declared a statewide drought emergency; and the governor of Oregon has issued a drought declaration for most of the counties in Oregon. The region relies on winter precipitation, and especially snow, for most of its water supply during the summer. This past winter has been anomalously warm, leading to record low snow in many places, providing what many have called a preview of snow conditions that may become common by the middle of this century. This talk will review the development of the drought in the Northwest, put the past winter in a historic context, and provide a summary of drought projections under climate change.

  5. 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

  6. Statistical Analysis of Drought Indices and Drought Monitoring for Alberta, Canada

    NASA Astrophysics Data System (ADS)

    Shen, S.; Dai, Q.; Yin, H.; Howard, A.

    2006-12-01

    This presentation discusses a statistical analysis of six drought indices for monitoring Alberta drought events from 1901 to 2000. The data used are the interpolated daily precipitation data on the 149 ecodistrict polygons over Alberta. The analyzed indices are standardized precipitation index, rainfall anomaly index, rainfall decile index, standardized anomaly index, principal component index, and optimal index. The historically documented drought records of five sites (Beaver Lodge, Lacombe, Lethbridge, Vegreville, and Swift Current [in Saskatchwan]) are classified into drought categories D4, D3, ?, D0, and wet categories D1, -D2, and D3. The thresholds of the drought categories for different indices are calculated. The wheat drought of Canada's Palliser Triangle was used as a validation analysis of the drought indices. The transitional probability of drought categories from one week to the next is calculated. Some discussions on the theory of calculating SPI are included. It has been found that the while all the drought indices are highly correlated with precipitation, the PCI has the highest correlation. The transitional probability analysis for the south Alberta agricultural region shows that the chance of transition from normal to extremely dry is highest in the mid May, hence this region's spring seeding is extremely vulnerable to precipitation and an effective irrigation system is of great importance to the early stages of crop development.

  7. 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

  8. 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.

  9. Drought Monitoring Using Satellite Data: Application to Karoon Basin

    NASA Astrophysics Data System (ADS)

    Maleki, M.; Moridnejad, A.; Kavehi, R.

    2011-12-01

    Development of a reliable drought monitoring system is fundamental to water resources engineering and management. In this regard, input data sets (e.g., precipitation, soil moisture, snow cover) play a major role in the proper assessment of droughts. Precipitation, for example, is a key input to drought models. Traditionally, drought analysis has been based on long-term rain-gauge measurements. However, rain gauges are sparsely spatially distributed and suffer from lack of areal representation of precipitation, which can be quite limiting for various drought-related analyses such as deriving the spatial extent of drought. Given inherent advantages of remote sensing data in terms of spatiotemporal resolution and large area coverage in comparison with traditional in-situ observations, satellite-based data have been widely used for monitoring hydrological and land use change variables, such as precipitation, soil moisture, and vegetation coverage. In this study, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) satellite precipitation algorithm is used as input to monitor meteorological drought condition using the Standardized Precipitation Index (SPI). Furthermore, the remotely sensed precipitation estimates are used as input in a soil accounting model to simulate the soil moisture condition. With the combination of SPI and soil moisture condition for different crops (wet and dry condition for various types of crops and vegetation), the drought condition is monitored over the Karoon basin in northern Iran. Other data sets used in this study include Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation condition and evapotranspiration data. This study presents an example implication of the remote sensing data for drought monitoring and analysis across a data sparse region. The results are validated with the available rain gauge measurements and they show a very good agreement, indicating that remote

  10. The Global Drought Monitor Portal - The Foundation for a Global Drought Early Warning System

    NASA Astrophysics Data System (ADS)

    Brewer, M.; Heim, R. R.; Pozzi, W.; Vogt, J.; Sheffield, J.

    2011-12-01

    Drought monitoring, assessment, response, mitigation, adaptation, and early warning systems have been created in a number of countries around the world, and some regional and continental efforts have been successful. However, the creation of a Global Drought Early Warning System (GDEWS) remains elusive. A GDEWS incorporates forecasting and research improvements, in addition to monitoring, impact, planning, mitigation and adaptation and recovery information. At a series of workshops in 2010, the US National Integrated Drought Information System (NIDIS) agreed to take the first step toward a GDEWS, the formation of a Global Drought Monitoring Portal (GDMP). This effort currently covers three continents - North America, Europe, and Africa - and provides global drought indicator information through satellite products and Global Historical Climate Network locations. The GDMP has benefited from coordination with the World Meteorological Organization (WMO) and Group on Earth Observations (GEO). Other nations have expressed interest in contributing and new regional and continental information should be online shortly. This paper presents the capabilities of the GDMP to link the monitoring, forecasting, research, and impacts aspects of international drought as well as the advantages of using common architecture through GEO to facilitate transfer and interoperability of GDEWS-related information.

  11. Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.

    2015-12-01

    This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. We argue that satellite observations not currently used for operational drought monitoring, such as near-surface air relative humidity data from the Atmospheric Infrared Sounder (AIRS) mission, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. While there are immense opportunities, there are major challenges including data continuity, unquantified uncertainty, sensor changes, and community acceptability. One of the major limitations of many of the currently available satellite observations is their short length of record. A number of relevant satellite missions and sensors (e.g., the Gravity Recovery and Climate Experiment, GRACE) provide only a decade of data, which may not be sufficient to study droughts from a climate perspective. However, they still provide valuable information about relevant hydrologic and ecological processes linked to this natural hazard. Therefore, there is a need for models and algorithms that combine multiple datasets and/or assimilate satellite observations into model simulations to generate long-term climate data records. Finally, the study identifies a major gap in indicators for describing drought impacts on the carbon and nitrogen cycle, which are fundamental to assessing drought impacts on ecosystems.

  12. 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

  13. A framework for developing an impact-oriented agricultural drought monitoring system from remote sensing

    NASA Astrophysics Data System (ADS)

    Zhang, Jie

    2016-04-01

    With a changing climate, drought has become more intensified, of which agriculture is the major affected sector. Satellite observations have proven great utilities for real-time drought monitoring as well as crop yield estimation, and many remotely sensed indicators have been developed for drought monitoring based on vegetation growth conditions, surface temperature and evapotranspiration information. However, those current drought indicators typically don't take into account the different responses of various input information and the drought impacts during the growing season, revealing some limitations for effective agricultural drought monitoring and impact analysis. Therefore, the goal of this research is to build a framework for the development of an impact-oriented and remote sensing based agricultural drought indicator. Firstly, the global agricultural drought risk was characterized to provide an overview of the agricultural drought prone areas in the world. Then, the responses of different remotely sensed indicators to drought and the impacts of drought on crop yield from the remote sensing perspective during the growing season were explored. Based on previous works on drought risk, drought indicator response and drought impact analysis, an impact-oriented drought indicator will be prototyped from the integration of the drought responses of different indicators and the drought impacts during the growing season. This research can inform an impact-oriented agricultural drought indicator, help prototype an impact-oriented agricultural drought monitoring system, and thus provide valuable inputs for effective agricultural management.

  14. 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.

  15. Application of Assimilated GRACE Data for Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Rodell, M.; Li, B.; Beaudoing, H. K.; Zaitchik, B. F.; Famiglietti, J. S.

    2014-12-01

    A unique aspect of the Gravity Recovery and Climate Experiment (GRACE) satellites is their ability to detect changes in water stored in all levels of the soil column, including groundwater. Thus GRACE is well suited for identifying hydrological droughts, when total water storage is low. The potential for GRACE to contribute to global drought monitoring is clear, but first it is necessary to overcome GRACE's low spatial and temporal resolutions (relative to other hydrological observations) and data latency. To do so we synthesize GRACE data with other ground and space based meteorological observations within a sophisticated numerical model of land surface water and energy processes. The resulting high resolution, near real-time fields of soil moisture and groundwater storage variations are then used to generate drought indicator maps. Since 2011, such maps have been produced on a weekly basis for the continental U.S., disseminated through the University of Nebraska's National Drought Mitigation Center website, and incorporated into the U.S. and North American Drought Monitors. Expansion of these GRACE-based drought indicators to the global scale is ongoing and is expect to be completed over the next 12-18 months.

  16. Collaborative processes, research, and applications to improve drought-sensitive decision making in the Upper Colorado River Basin

    NASA Astrophysics Data System (ADS)

    Verdin, J. P.; Pulwarty, R. S.; Doesken, N. J.; Gillespie, M.; Werner, K.; Wilhelmi, O.; Lewis, M. E.; Darby, L. S.; McNutt, C. A.; Schmidt, M.; Redmond, K. T.

    2010-12-01

    The Upper Colorado River Basin (UCRB) is the focus of the first pilot regional drought early warning information system of the National Integrated Drought Information System (NIDIS). In partnership with resource managers from across the basin, a program of needs assessments, collaborative processes, research, and applications was designed and is being implemented. Priority actions involve the drought-sensitive decisions of large reservoir operators, water providers dependent on inter-basin transfers, and ecosystem managers. Identification of drought monitoring and forecasting needs has led to an ongoing UCRB drought monitoring process organized under the leadership of the Colorado state climatologist. Weekly webinars during spring runoff (monthly during the rest of the year) review the latest science, observations and forecasts for variables like streamflow, precipitation, temperature, snowpack, and reservoir storage. Research and applications projects support this collaborative process by developing new insights and tools for drought impact analyses. They include review and improvement of drought indices used in the UCRB, and new tools for making custom, locally-relevant indicators; spatial analysis of water demand in the basin; a low-flow impacts database, including environmental considerations; linkage of National Weather Service climate and hydrological modeling; a monitoring gaps assessment; and enhanced web access to drought information specific to the UCRB via the NIDIS portal. Lessons learned during 2010 will be applied during a second annual cycle in 2011 and then placed in the context of longer-term planning strategies. The findings of the pilot will provide the basis for the design of innovative and sustained practices in the UCRB, as well as expansion of the early warning system to include the Lower Colorado River Basin and to inform adaptation across multiple timescales. The UCRB effort highlights the role of pilot design and implementation as

  17. The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation

    USGS Publications Warehouse

    Brown, J.F.; Wardlow, B.D.; Tadesse, T.; Hayes, M.J.; Reed, B.C.

    2008-01-01

    The development of new tools that provide timely, detailed-spatial-resolution drought information is essential for improving drought preparedness and response. This paper presents a new method for monitoring drought-induced vegetation stress called the Vegetation Drought Response Index (VegDRI). VegDRI integrates traditional climate-based drought indicators and satellite-derived vegetation index metrics with other biophysical information to produce a I km map of drought conditions that can be produced in near-real time. The initial VegDRI map results for a 2002 case study conducted across seven states in the north-central United States illustrates the utility of VegDRI for improved large-area drought monitoring. Copyright ?? 2008 by Bellwether Publishing, Ltd. All rights reserved.

  18. Improving Agricultural Drought Monitoring in East Africa with Unbiased Rainfall Fields and Detailed Land Surface Physics

    NASA Astrophysics Data System (ADS)

    McNally, A.; Yatheendradas, S.; Peters-Lidard, C. D.; Michaelsen, J.

    2010-12-01

    Monitoring drought is particularly challenging within rainfed agricultural and pastoral systems, where it can serve the greatest need. Such locations often have sparse or non-existent ground based measurements of precipitation, evapotranspiration (ET), and soil moisture. For more effective drought monitoring with limited hydroclimate observations, we simulate land surface states using the Community Noah Land Surface Model forced with different merged rainfall products inside a Land Information System (LIS). Using model outputs we will answer the questions: How sensitive are soil moisture and ET fields to differences in rainfall forcing and model physics? What are acceptable drought-specific tradeoffs between near-real time availability and skill of rainfall data? Preliminary results with the African Rainfall Estimation Algorithm Version 2 (RFE2.0) outperformed global products, suggesting that sub-global rainfall estimates are the way forward for regional drought monitoring. Specifically, the Noah model forced with RFE2.0 better resolved the heterogeneous patterns in crop stress than the Famine Early Warning System Network (FEWS NET) operational Water Requirement Satisfaction Index (WRSI) model. To further investigate the improvement in drought monitoring while maintaining timeliness, we unbias (using Africa specific climatology) the precipitation products from CPC Merged Analysis of Precipitation (CMAP), Tropical Rainfall Measurement Mission (TRMM), and RFE2.0. The skill (relative accuracy) and reliability (average agreement) of the unbiased rainfall are calculated against an unbiased precipitation product augmented with station data from Ethiopia and Kenya. Soil moisture and ET fields from Noah are compared to the operational FEWS NET WRSI, soil water anomaly index, and the World Food Program’s Crop and Food Security Assessment Mission reports. We anticipate that the unbiased rainfall fields will improve the accuracy, spatio-temporal resolution, and

  19. Drought and vegetation stress monitoring in Portugal using satellite data

    NASA Astrophysics Data System (ADS)

    Gouveia, C.; Trigo, R. M.; Dacamara, C. C.

    2009-02-01

    Remote sensed information on vegetation and soil moisture, namely the Normalised Difference Vegetation Index (NDVI) and the Soil Water Index (SWI), is employed to monitor the spatial extent, severity and persistence of drought episodes over Continental Portugal, from 1999 to 2006. The severity of a given drought episode is assessed by evaluating the cumulative impact over time of drought conditions on vegetation. Special attention is given to the drought episodes that have occurred in the last decade, i.e., 1999, 2002 and particularly the major event of 2005. During both the 1999 and 2005 drought episodes negative anomalies of NDVI are observed over large sectors of Southern Portugal for up to nine months (out of eleven) of the vegetative cycle. On the contrary, the 2002 event was characterized by negative anomalies in the northern half of Portugal and for a shorter period (eight out of eleven months). The impact of soil moisture on vegetation dynamics is evaluated by analyzing monthly anomalies of SWI and by studying the annual cycle of SWI vs. NDVI. While in the case of the drought episode of 1999 the scarcity of water in the soil persisted until spring, in the recent episode of 2005 the deficit in greenness was already apparent at the end of summer. The impact of dry periods on vegetation is clearly observed in both arable land and forest, and it is found that arable land presents a higher sensitivity. From an operational point of view, obtained results reveal the possibility of using the developed methodology to monitor, in quasi real-time, vegetation stress and droughts in Mediterranean ecosystems.

  20. Application of terrestrial microwave remote sensing to agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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. Suc...

  1. 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

  2. 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

  3. 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

  4. Using the New Floating Month Drought Index to Monitor Extreme Moisture Spells and Assess Century-Scale Climate Change

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2009-12-01

    The evolution of drought indices over the 20th century culminated in the U.S. Drought Monitor (USDM) as a drought monitoring tool that incorporated the various existing drought indicators, drought impacts information, and input from local field experts. A set of objective blends was created to integrate appropriately-scaled indices which assessed short-term and long-term moisture conditions. Unfortunately, the objective blends provide indeterminate information when short-term conditions are wet and long-term conditions are dry, or vice versa. The new Floating Month Drought Index (FMDI) improves upon the objective blends by including a temporal component. The FMDI computes the precipitation percentile for the current month and for the current N-month dry spell, the length and starting year/month of the current dry spell, and the Dx dry spell category based on USDM categories (and similar statistics for wet spells). In this way, the FMDI provides an objective decision-support tool for integrating the multiple time scales of drought. This presentation will discuss the development of the FMDI and how it can be used to assess changes in extreme moisture conditions on regional and national scales over the 20th to 21st centuries.

  5. 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

  6. 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

  7. A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Xia, Youlong; Ouyang, Wei; Shen, Xinyi

    2016-06-01

    Drought indices have been commonly used to characterize different properties of drought and the need to combine multiple drought indices for accurate drought monitoring has been well recognized. Based on linear combinations of multiple drought indices, a variety of multivariate drought indices have recently been developed for comprehensive drought monitoring to integrate drought information from various sources. For operational drought management, it is generally required to determine thresholds of drought severity for drought classification to trigger a mitigation response during a drought event to aid stakeholders and policy makers in decision making. Though the classification of drought categories based on the univariate drought indices has been well studied, drought classification method for the multivariate drought index has been less explored mainly due to the lack of information about its distribution property. In this study, a theoretical drought classification method is proposed for the multivariate drought index, based on a linear combination of multiple indices. Based on the distribution property of the standardized drought index, a theoretical distribution of the linear combined index (LDI) is derived, which can be used for classifying drought with the percentile approach. Application of the proposed method for drought classification of LDI, based on standardized precipitation index (SPI), standardized soil moisture index (SSI), and standardized runoff index (SRI) is illustrated with climate division data from California, United States. Results from comparison with the empirical methods show a satisfactory performance of the proposed method for drought classification.

  8. 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

  9. 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

  10. 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

  11. Utilizing a Multi-sensor Satellite Time Series in Real-time Drought Monitoring Across the United States

    NASA Astrophysics Data System (ADS)

    Brown, J. F.; Miura, T.; Gu, Y.; Jenkerson, C.; Wardlow, B.

    2009-05-01

    Drought events frequently occur in the United States and result in billions of dollars of damage, often exceeding the costs of other weather-related hazards. Monitoring drought conditions is a necessary function of government agencies at State, Federal, and local levels as part of decision support for planning, risk management, and hazard mitigation activities. In partnership with the National Drought Mitigation Center, the National Aeronautics and Space Administration, the U.S. Department of Agriculture Risk Management Agency, and the High Plains Regional Climate Center, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center is developing an operational drought decision support tool with relatively higher spatial resolution (1 km2) than traditional drought monitoring maps. The Vegetation Drought Response Index (VegDRI) is a geospatial model that integrates in-situ climate, satellite, and biophysical data, providing an indicator of canopy vegetation condition (or stress). The satellite data ingested into VegDRI are collected from daily polar-orbiting earth observing systems including the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS). These instruments provide regular synoptic measurements of land surface conditions in near-real time. In VegDRI, remote sensing data provide proxy information about the vegetation status (or health) related to climate-induced changes and are integrated with traditional drought indices based on in-situ climate observations. When merged, the two complementary sources of drought-related data provide a comprehensive and detailed picture of drought impacts across the landscape. A 20-year history of AVHRR time-series data produced over the U.S. at a 1 km2 resolution provides a historical context for monitoring drought conditions. However, the MODIS instrument has improved sensor characteristics designed for land surface monitoring. To seamlessly

  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. Monitoring drought for grassland and cropland using multi-sensor microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Zhang, A.; Jia, G.

    2012-12-01

    Remote sensing drought indices derived from optical and infrared bands have been successfully used in monitoring drought throughout the world; however the application of microwave remote sensing sensor in drought monitoring has not been thoroughly investigated. In this study, we propose a microwave remote sensing drought index, the Microwave Integrated Drought Index (MIDI), especially for short-term drought monitoring over northern China. The index combined three variables: the Tropical Rainfall Measuring Mission (TRMM) precipitation, land surface temperature (LST) and soil moisture (SM) obtained by the Vrije Universiteit Amsterdam and NASA Goddard Space Flight Center (VUA-NASA) from the Advanced Microwave Scanning Radiometer (AMSR-E) on-board Aqua satellite. The microwave remotely sensed variables were linearly scaled from 0 to 1 for each pixel based on absolute minimum and maximum values for each variable over time, in order to discriminate the weather-related component from the ecosystem component. The microwave indices were evaluated with the Standardized Precipitation Index (SPI), an in-situ meteorological data based drought index. Pearson correlation analyses were performed between the remotely sensed drought indices values and different time scale SPI values for the growing season from 2003 to 2010 to assess the capability of remotely sensed drought indices in monitoring drought over three different climate regions in northern China. There was significant spatial variability in the correlations between remote sensing drought indices and SPI, generally, the Precipitation Condition Index (PCI) showed the highest correlation with 1-month SPI (r around 0.70) whether compared to remote sensing drought indices or different time scale SPI; while correlations between Soil Moisture Condition Index (SMCI), Land Surface Temperature (TCI) and SPI exhibited different trends among three climate regions. The MIDI with proper weights of three components nearly possessed the

  14. 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.

  15. Application of LANDSAT digital data for monitoring drought. [South Dakota

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

    A technique utilizing transformed LANDSAT digital data for detection of agricultural vegetative water stress was developed during the 1976 South Dakota drought, and expanded to the U.S. Great Plains the following year to evaluate its effectiveness in detecting and monitoring vegetative stress water stress over large areas. This technique, the green index number (GIN), indicated when the vegetation within a segment was undergoing stress. Segments were classified as either moisture-stressed or normal using remote sensing techniques combined with a knowledge of crop condition. The remote sensing-based information was compared to a weekly ground-based index (the crop moisture index) provided by the U.S. Dept. of Commerce. The approaches used and the results from the GIN monitoring program are presented.

  16. On the potential application of land surface models for drought monitoring in China

    NASA Astrophysics Data System (ADS)

    Zhang, Liang; Zhang, Huqiang; Zhang, Qiang; Li, Yaohui; Zhao, Jianhua

    2016-01-01

    The potential of using land surface models (LSMs) to monitor near-real-time drought has not been fully assessed in China yet. In this study, we analyze the performance of such a system with a land surface model (LSM) named the Australian Community Atmosphere Biosphere Land Exchange model (CABLE). The meteorological forcing datasets based on reanalysis products and corrected by observational data have been extended to near-real time for semi-operational trial. CABLE-simulated soil moisture (SM) anomalies are used to characterize drought spatial and temporal evolutions. One outstanding feature in our analysis is that with the same meteorological data, we have calculated a range of drought indices including Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI). We have assessed the similarity among these indices against observed SM over a number of regions in China. While precipitation is the dominant factor in the drought development, relationships between precipitation, evaporation, and soil moisture anomalies vary significantly under different climate regimes, resulting in different characteristics of droughts in China. The LSM-based trial system is further evaluated for the 1997/1998 drought in northern China and 2009/2010 drought in southwestern China. The system can capture the severities and temporal and spatial evolutions of these drought events well. The advantage of using a LSM-based drought monitoring system is further demonstrated by its potential to monitor other consequences of drought impacts in a more physically consistent manner.

  17. 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

  18. 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

  19. Monitoring southwest drought of China using HJ-1A/B and Landsat remote sensing data

    NASA Astrophysics Data System (ADS)

    Huang, He; Zhou, Hongjian; Wang, Ping; Wu, Wei; Yang, Siquan

    2012-10-01

    Drought is one major nature disaster in the world. The affected population and agriculture loss caused by drought are the largest in all natural disasters. Drought has the characteristics of wide affected areas, long duration and periodic strong feature. Remote sensing has the advantages of large coverage, frequent observation, repeatable observation, reliable information source and low cost. These advantages make remote sensing a vital contributor for drought disaster monitoring and forecasting. So, remote sensing data have been widely used and delivered significant benefits in drought prevention and reduction in China. Three drought monitor models including Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Temperature Vegetation Dryness Index (TVDI) had been used to monitor southwest drought occurred in China from 2009 to 2011 based on the small satellite constellation for environment and disaster monitoring and forecasting A/B satellites (HJ-1AB) and Landsat remote sensing data. The results shown that five regions including Sichuan province, Chongqing, Guizhou province, Yunnan province, Guangxi province in southwest of China had suffered different degrees agricultural drought disaster in 2010 and 2011. The comprehensive agricultural disaster situation of five affected areas in 2010 was more serious than drought events occurred in 2011. The many regions in Guizhou province were hardest-hit areas cased by the two consecutive year drought events in southwest China.

  20. A Drought Monitoring Tool for Customized Calculation of a Standardized Precipitation Index Value in the Navajo Nation

    NASA Astrophysics Data System (ADS)

    Cary, C.; Ly, V.; Gao, M.; Surunis, A.; Turnbull-Appell, S.; Sodergren, C.; Brooks, A. N.

    2015-12-01

    The Navajo Nation, located in the southwestern United States, has been increasingly impacted by severe drought events and regional 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 climate and drought are dependent on national-scale monthly drought maps calculated by the Western Regional Climate Center (WRCC). These maps do not provide the spatial resolution needed to examine differences in drought severity across the vast Nation. To better understand and monitor drought regime changes in the Navajo Nation, this project comprises of two main components: 1) a geodatabase of historical climate information necessary to calculate Standardized Precipitation Index (SPI) values and 2) a tool that calculates SPI values for a user-selected area within the study site. The tool and geodatabase use TRMM and GPM observed precipitation data, and Parameter-elevation Relationships on Independent Slopes Model (PRISM) modeled historical precipitation data. These products 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.

  1. Land-atmosphere coupling metrics from satellite remote sensing as a global drought-monitoring tool

    NASA Astrophysics Data System (ADS)

    Roundy, Joshua K.; Santanello, Joseph A.

    2015-04-01

    Drought causes significant economic impact to society that can be reduced through preparations made possible by monitoring and prediction. Most drought monitoring systems utilize a variety of metrics to assess and understand drought. Feedbacks induced through land-atmosphere interactions are an important mechanism of drought intensification and persistence that is often not considered in current drought monitors due to a lack of spatially consistent observations. Recent work has developed a new classification of land-atmosphere interactions that summarizes the net impact of these interactions on drought intensification and recovery through the Coupling Drought Index (CDI). One thing that makes the CDI unique is that it can be calculated based on estimates from satellite remote sensing, which makes it particularly useful for global drought monitoring. Furthermore, the persistent nature of these coupling regimes provides a means of prediction through a Markov Chain Coupling Statistical Model (CSM). Previous work has shown that the CDI based on satellite remote sensing compares well with the U.S. Drought monitor in terms of drought intensification and recovery. On the other hand, the skill of the CSM forecasts over the U.S. is limited and still needs improvement. In this work the extent to which the CDI and CSM can be extended to other areas of the globe are explored. In particular, the ability of the satellite remote sensing based CDI to capture drought intensification and recovery over Africa and Europe are assessed. The benefits and limitations of using a metric of land-atmosphere interactions for global drought monitoring are also discussed.

  2. Advancing the understanding, monitoring and prediction of North American drought in support of NIDIS

    NASA Astrophysics Data System (ADS)

    Mariotti, Annarita; Pulwarty, Roger

    2014-05-01

    The NOAA's Drought Task Force was established in October 2011 with the goal of achieving significant new advances in the ability to understand, monitor and predict drought over North America. The Task Force is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in support of the National Integrated Drought Information System NIDIS. It brings together over thirty-five leading drought scientists research laboratories and/or operational centers from NOAA, other U.S. agencies laboratories and academia. Their concerted research effort builds on individual MAPP research projects and related drought-research sector developments. The projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those evaluating new drought monitoring and prediction tools for operational and service purposes. In this presentation we will show how a coordinated, sustained multidisciplinary effort to assess understanding of both past droughts and emergent events contributes to the effectiveness of early warning systems. This contribution will present an overview of Drought Task Force activities to date, including highlights of research activities and how the group has been working in partnership with NIDIS to advance the science underpinning the development, assessment and provision of drought information.

  3. Probabilistic drought characterization in the categorical form using ordinal regression

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hong, Yang; Xia, Youlong; Singh, Vijay P.; Hao, Fanghua; Cheng, Hongguang

    2016-04-01

    Drought is an insidious natural hazard that may cause tremendous losses to different sectors, including agriculture and ecosystems. Reliable drought monitoring and early warning are of critical importance for drought preparedness planning and mitigation to reduce potential impacts. Traditional drought monitoring is generally based on drought indices, such as Standardized Precipitation Index (SPI), that are computed from hydro-climatic variables. The U.S. Drought Monitor (USDM) classifies drought conditions into different drought categories to provide composite drought information by integrating multiple drought indices, which has been commonly used to aid decision making at the federal, state, and local levels. Characterizing drought in categories similar to USDM would be important for decision making for both research and operational purposes. However, drought monitoring, based on a variety of drought indices, is challenged by the classification of drought into categories used by USDM. In this study, an ordinal regression model is proposed to characterize droughts in USDM drought categories based on several drought indices, in which the probability of each drought category can be estimated. The proposed method is assessed by comparing with USDM in Texas and a satisfactory performance for estimating drought categories is revealed.

  4. 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; Wardlow, Brian; Zaitchik, Benjamin F.

    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.

  5. 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

  6. 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

  7. 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.

  8. Assessing the sensitivity of two new indicators of vegetation response to water availability for drought monitoring

    NASA Astrophysics Data System (ADS)

    Jia, Li; Hu, Guangcheng; Zhou, Jie; Menenti, Massimo

    2012-10-01

    Two new drought indicators based on satellite observations of vegetation index and land surface temperature, i.e. the Normalized Temperature Anomaly Index (NTAI) and the Normalized Vegetation Anomaly Index (NVAI) were applied to monitor drought events in different regions in China and India. We carried out this analysis for drought events with distinct duration, intensity and surface condition in 2006 in Sichuan-Chongqing, in 2009 in Inner-Mongolia (China) and in the Ganga basin (India) using the MODIS LST and NDVI data products and TRMM rainfall data for the period 2001 - 2010. Two newly proposed drought indicators NVAI and NTAI were evaluated against widely accepted indicators such as Precipitation Anomaly Percentage (PAP), Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). The results show that NTAI and NVAI responded consistently to climate forcing. Long lasting rainfall anomalies led to severe drought and anomalies in rainfall, anomalies in NTAI appeared almost simultaneously and followed by negative anomaly in NVAI. The two new drought indicators NTAI and NVAI can distinguish the stages of drought evolution. The sensitivity of the indicators and of their anomalies to drought conditions and severity was also evaluated against drought assessments by operational drought monitoring services, documented how well the indicators meet expectations on the timely and reliable detection of environmental change.

  9. 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.

  10. Research Progress of Farmland Drought Monitoring and Prediction Based on Multi-Source Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Raffaele; Pascucci, Simone; Silvesrtro, Paolo Cosmo

    2014-11-01

    Since the Kick-off of the Dragon-3 project Farmland Drought Monitoring and Prediction Based on Multi-source Remote Sensing Data (ID: 10448), our research focuses on three points including 1) the monitoring of key biophysical variables of crop and soil in farmland drought by optical and radar remote sensing data, 2) the risk assessment of farmland drought by time series remote sensing and meteorological data, and 3) the crop loss evaluation under farmland drought mainly based on AquaCrop crop model. Our study area is mainly located in Beijing, and Shaanxi Province (semi-arid region), China. Experiment campaign and data analysis were carried out and some new methods aiming at farmland drought monitoring and prediction were developed, which highlighting the importance of ESA-NRSCC Dragon cooperation.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. Using a diagnostic soil-plant-atmosphere model for monitoring drought at field to continental scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought assessment is a complex undertaking, 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, groundwater and surface water anomalies reflect deficiencies in mo...

  16. Group on Earth Observations (GEO) Global Drought Monitor Portal: Adding Capabilities for Forecasting Hydrological Extremes and Early Warning Networking

    NASA Astrophysics Data System (ADS)

    Pozzi, W.; de Roo, A.; Vogt, J.; Lawford, R. G.; Pappenberger, F.; Heim, R. R.; Stefanski, R.

    2011-12-01

    The Intergovernmental Panel on Climate Change (IPCC 2007) has suggested the hydrometeorological extremes of both drought and flooding may increase under climate change. Drought zones can grow over large tracts of continental area and are a global-scale phenomenon (Sheffield and Wood 2011). The Group on Earth Observations Global Drought Monitor Portal (GDMP) was established as a demonstration for the 5th Earth Observation Ministerial Summit in Beijing in 2010. The European Drought Observatory, the North American Drought Monitor, the Princeton University experimental African Drought Monitor, and the University College London experimental global drought monitor were made "interoperable" through installation of Open Geospatial Consortium (OGC) Web Mapping Services (WMS) on their respective servers, allowing maps of current drought conditions to be exchanged and assembled into maps of global drought coverage on the NIDIS portal. Partners from the Republic of Argentina, the Commonwealth of Australia, China, Jordan, Brazil, and Uruguay have also joined. The GEO Global Drought Monitoring, Forecasting, and Early Warning effort involves multiple parties and institutions, including the World Meteorological Organization, the World Climate Research Program Drought Interest Group, NASA, and others. The GEO Secretariat held a launch workshop in Geneva on 4-6 May 2010 to initiate drafting the final GEO Work Plan, and, during this meeting, additional capabilities were added to the existing GDMP: 1) drought forecasting was added to drought "current conditions" monitoring, in a partnership with Joint Research Centre (and other partners) aiming at a combined platform for Hydrological Extremes (drought and flooding); 2) extending drought forecasts from the medium-range 15-day window to a 30-day window; this will be tested through pilot projects over Europe and Africa, as part of the Global Water Scarcity Information Service (GLOWASIS)and the Improved Drought Early Warning Forecasting

  17. Drought monitoring using downscaled soil moisture through machine learning approaches over North and South Korea

    NASA Astrophysics Data System (ADS)

    Park, S.; Im, J.; Rhee, J.; Park, S.

    2015-12-01

    Soil moisture is one of the most important key variables for drought monitoring. It reflects hydrological and agricultural processes because soil moisture is a function of precipitation and energy flux and crop yield is highly related to soil moisture. Many satellites including Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity sensor (SMOS), and Soil Moisture Active Passive (SMAP) provide global scale soil moisture products through microwave sensors. However, as the spatial resolution of soil moisture products is typically tens of kilometers, it is difficult to monitor drought using soil moisture at local or regional scale. In this study, AMSR-E and AMSR2 soil moisture were downscaled up to 1 km spatial resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) data—Evapotranspiration, Land Surface Temperature, Leaf Area Index, Normalized Difference Vegetation Index, Enhanced Vegetation Index and Albedo—through machine learning approaches over Korean peninsula. To monitor drought from 2003 to 2014, each pixel of the downscaled soil moisture was scaled from 0 to 1 (1 is the wettest and 0 is the driest). The soil moisture based drought maps were validated using Standardized Precipitation Index (SPI) and crop yield data. Spatial distribution of drought status was also compared with other drought indices such as Scaled Drought Condition Index (SDCI). Machine learning approaches were performed well (R=0.905) for downscaling. Downscaled soil moisture was validated using in situ Asia flux data. The Root Mean Square Errors (RMSE) improved from 0.172 (25 km AMSR2) to 0.065 (downscaled soil moisture). The correlation coefficients improved from 0.201 (25 km AMSR2) to 0.341 (downscaled soil moisture). The soil moisture based drought maps and SDCI showed similar spatial distribution that caught both extreme drought and no drought. Since the proposed drought monitoring approach based on the downscaled

  18. Hydras+ Improving Drought Monitoring by Assimilating multi-source Remote Sensing Observations into Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Rains, Dominik; Lievens, Hans; Vernieuwe, Hilde; De Baets, Bernard; Hostache, Renaud; Chini, Marco; Pfister, Laurent; Matgen, Patrick; He, Guowei; Vereecken, Harry; Han, Xujun; Montzka, Carsten; Verhoest, Niko

    2015-04-01

    Given the expected increase in extreme events due to climate change, more drought events can be expected in the future. These events have often devastating impacts on society and the environment. Adequate monitoring of these events within disaster management is therefore of utmost importance. Remote sensing can provide important information, though does not allow for a complete assessment of droughts as (1) only measurements of the surface are obtained and (2) the spatial and temporal resolutions are often too coarse. Combining remote sensing with land surface models is generally opted for, and is already in place in many drought monitoring systems. However, prediction of drought events (occurrence, intensity, frequency) can be improved by improving modelling approaches via the assimilation of multiple sources of remote sensing data. If both remote sensing observation and model reliability and accuracy can be enhanced, a more precise monitoring and modelling is expected, and therefore improved drought forecast is possible. Within the recently initiated BELSPO/FNR funded HYDRAS+ project, research on these domains is carried out demonstrating the benefits of jointly assimilating several remote sensing sources (e.g. Sentinel 1, SMOS, SMAP) in land surface models for improved drought monitoring and prediction. It furthermore aims at assessing whether conceptual models (SUPERFLEX) can be used instead of complex and computation-expensive land surface models (CLM 4.5). If such models can be used, a faster computation of droughts at very large scale becomes possible. The findings will not be used to set up a standalone drought monitoring system but rather be used to potentially improve currently existing systems. Any improvement in the currently available systems will have important positive consequences with respect to disaster management as it will allow for an improved management of resources.

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

    USGS Publications Warehouse

    Brown, J.F.; Miura, T.; Wardlow, B.; Gu, Y.

    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. 

  20. Data-Intensive Drought Monitoring, Forecasting, and Outlooks for Climate-Resilient Water Management in Western Agriculture

    NASA Astrophysics Data System (ADS)

    Ryu, J.

    2014-12-01

    Drought increasingly threatens the sustainability of regional water resources in many states in the United States. Drought has large economic impacts and significant environmental and societal effects. Although much research on drought at national, regional, and local scales has been conducted to mitigate drought impacts, still drought claims economic losses estimated at about $8.5 billion per year. One possible reason for such huge losses may be a lack of clear understanding of the characteristics of drought at local scales that the end user can relate to the particular water management constraints of their basin. Sustainable water management alternatives are explored and discussed to mitigate climate-induced drought impacts on western agriculture. Current drought monitoring, forecasting, and outlooks efforts are demonstrated along with visualization and research survey. Future direction for Big Drought research is also highlighted.

  1. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

    NASA Astrophysics Data System (ADS)

    Hao, Cui; Zhang, Jiahua; Yao, Fengmei

    2015-03-01

    Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed

  2. Monitoring drought conditions and their uncertainties in areas with sparse precipitation data. Evaluation of different precipitation datasets in Africa.

    NASA Astrophysics Data System (ADS)

    Naumann, G.; Barbosa, P.; Carrao, H.; Singleton, A.; Vogt, J.

    2012-04-01

    Merged Analysis of Precipitation (CMAP, 2.5°x2.5°). A non-parametric resampling bootstrap approach was used in order to assess the sampling uncertainties associated with SPI estimation in terms of confidence bands. Confidence bands are essential for making a qualified assessment of drought events. The comparative analysis of the four different datasets suggests that is feasible to use short time series of precipitation data with high spatial resolution (0.25°x0.25°) such as the TRMM for reliable drought monitoring over Africa. Furthermore, the bootstrap technique gives an estimate of the SPI uncertainty by providing confidence intervals. The proposed approach for drought monitoring has the potential to be used in support of decision making at continental and sub-continental scales over Africa or other regions that have a sparse distribution of rainfall measurement instruments.

  3. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status affecting evapotranspiration and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as...

  4. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status for estimating evapotranspiration and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  6. SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

    Mesoamerica is a prime example of a multi-national region with natural and human induced stresses that benefits from information provided by observation systems. The region 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 of its population to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, the University of Alabama in Huntsville and numerous SERVIR* partners are developing data products, knowledge extraction methods and decision support tools for environmental monitoring, disaster response and sustainable growth planning in Mesoamerica. The combination of space- based observations from NASA's Earth Observing Satellites with information management and knowledge extraction technologies has yielded a robust system for use by scientists, educators, environmental ministers and policy makers. These resources enhance the ability to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. Now in its fourth year SERVIR has become a partner in the International Space and Major Disasters Charter. In the past year the Charter provided commercial satellite imagery to aid in disaster response to Hurricanes Dean, Felix and Noel. Overcoming roadblocks to coordination and data sharing between countries, organizations and disciplines SERVIR is providing environmental monitoring and decision support products and applications that directly map to several Observation GEOSS societal benefit areas. This paper provides an overview of the ongoing accomplishments of the SERVIR project. *SERVIR is a Spanish verb meaning "to serve" or "be useful" is also an acronym for the Spanish name of the capability: Sistema Regional de Visualizacion y Monitero.

  7. A Decision Support System For Assisting With Stocking Rate Decisions During And Following Drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final forage production level is known. Erroneous stocking rate decisions can have...

  8. Linking Forest Carbon Monitoring with Management Decisions

    NASA Astrophysics Data System (ADS)

    Birdsey, R.; Pan, Y.; Potter, C.; Hom, J.; Clark, K.; van Tuyl, S.

    2006-12-01

    Managing forests to increase carbon stocks or reduce emissions requires knowledge of how management practices effect carbon pools over time, and inexpensive techniques to monitor activities. Here we discuss our approach to integrate the multi-tier monitoring data from the North American Carbon Program (NACP) with management decisions by linking bottom-up and top-down ecosystem models with decision-support tools. Monitoring carbon stocks and fluxes in the NACP involves a multi-tier hierarchy of observation methods: remote sensing, inventories, landscape biometrics, and flux towers. We use the GIS version of PnET-CN to scale up and map observations from flux towers, landscape biometrics, and inventories to areas of approximately 50 km2 around flux tower sites. The NASA-CASA model is used to scale down remote sensing observations from the MODIS sensor and biophysical maps to the same areas. Mapped estimates of productivity and biomass that embed consequences of land disturbances and forest age structure are used to compare and reconcile the top-down and bottom-up approaches, and to provide input to decision-support tools. Key information for the decision-support tools includes (1) estimates of carbon stocks and quantified impacts of management activity; (2) estimates of net ecosystem production (NEP) and changes in carbon pools; and (3) estimates of forest/atmosphere carbon fluxes and relevant effects from various environmental controls. To demonstrate the relevance of this work to land managers, we illustrate how this information can be used for estimating and reporting carbon stocks and changes in carbon stocks to the national greenhouse gas registry.

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

    NASA Astrophysics Data System (ADS)

    Yi, Hang; Wen, Lianxing

    2016-01-01

    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.

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

    PubMed Central

    Yi, Hang; Wen, Lianxing

    2016-01-01

    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. PMID:26813800

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

    PubMed

    Yi, Hang; Wen, Lianxing

    2016-01-01

    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. PMID:26813800

  12. Coping with Natural Hazards in a Conservation Context: Resource-Use Decisions of Maasai Households During Recent and Historical Droughts

    PubMed Central

    Leslie, Paul W.; McCabe, J. Terrence

    2014-01-01

    Analyzing people’s decisions can reveal key variables that affect their behaviors. Despite the demonstrated utility of this approach, it has not been applied to livelihood decisions in the context of conservation initiatives. We used ethnographic decision modeling in combination with qualitative comparative analysis (QCA) to examine the herding decisions of Maasai households living near Tarangire National Park (TNP) during recent and historical droughts. The effects of the establishment of TNP on herding practices during drought were different than anticipated based on the size and reliability of several prominent resource areas that are now within the park. We found little evidence of people relying on these swamps and rivers for watering cattle during historical droughts; rather, these sites were more commonly used as grazing areas for small stock and wet-season grazing areas for cattle to avoid disease carried by calving wildebeest. Yet during the 2009 drought, many herders moved their livestock – especially cattle from outside of the study area – toward TNP in search of grazing. Our analysis of herding decisions demonstrates that resource-use decisions are complex and incorporate a variety of information beyond the size or reliability of a given resource area, including contextual factors (e.g., disease, conflict, grazing) and household factors (e.g., social capital, labor, herd size). More broadly, this research illustrates that pairing decision modeling with QCA is a structured approach to identifying these factors and understanding how opportunities, constraints, and perceptions influence how people respond to changes in resource access. PMID:25506101

  13. 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.

  14. The role of soil moisture in monitoring drought events over Europe

    NASA Astrophysics Data System (ADS)

    Cammalleri, Carmelo; Micale, Fabio; Vogt, Jürgen

    2015-04-01

    Drought is a complex phenomenon that manifests at different spatial and temporal scales. Within the European Drought Observatory (EDO, http://edo.jrc.ec.europa.eu) an integrated monitoring approach is embraced, attempting at combining various sources of drought information at European level in order to provide a set of drought monitoring tools that encompasses continental, national, regional and local scales. Each tool, ranging from precipitation-based to remotely sensed greenness indicators, aims at capturing different aspect of the heterogeneous nature of drought events. An accurate measure of the effects of drought on vegetated lands can be achieved by exploiting the capability of soil moisture to quantify plant water stress. This is commonly accomplished by either accounting for the level of the current soil moisture compared to the past history or by computing a water deficit index, based on the on the critical values of the soil water retention curve. Under the definition that a vegetated area can be considered affected by drought condition only when the soil moisture status in the root zone is simultaneously: i) unusually dry compared to the "normal" state and ii) causing severe water stress to the vegetation, it is an obvious consequence that a soil moisture-based drought indicator should capture both features. Here we describe a novel drought severity index. DSI, that accounts for the mutual occurrence of these two conditions by means of a weighted average of a water deficit factor and a dryness probability factor. The former quantifies the actual plant water stress level, whereas the latter verifies that the current water deficit condition is unusual for the specific site and period. The reliability of the estimates made by DSI is evaluated by analyzing the performance during some well-known drought events that occurred over Europe between 1995 and 2012. Overall, DSI seems to correctly distinguish the main drought events recognized in the dedicated

  15. Use of satellite-derived soil moisture to improve drought monitoring

    NASA Astrophysics Data System (ADS)

    Enenkel, Markus; Rojas, Oscar; Balint, Zoltan

    2013-04-01

    From all natural disasters droughts rank first regarding the number of people affected, severity, length of event, spatial extent, loss of life and economic consequences. Drought impacts depend not only on the severity of the impact. Regional exposure and vulnerability play a crucial role that is often hard to assess. Industrialized countries, such as the United States, have measures to mitigate consequences. In contrast, developing countries often suffer from long-term impacts on people's livelihoods due to recurring events. Decreasing uncertainties in decision-making by state-of-the-art technologies seems to be the most promising approach. Several drought indices were developed during the last decades for different applications. However, there is an obvious lack of indices that consider drought creating factors and actual user requirements in data-scarce regions. FAO SWALIM (The Somalia Water and Land Information Management Group of the UN Food and Agriculture Organization) developed the Combined Drought Index (CDI) in 2011. It originally consisted of three weighted sub-indices: rainfall and temperature (both from point measurements) and NDVI as a substitute for soil moisture. At least ten years of data are required for each sub-index to detect anomalies reliably. The CDI is calculated as a decadal or monthly product, whereas drought levels range from values >1 (no drought) to <4 (extreme drought). In order to improve operational decision-making in the long run the CDI was revised to substitute point measurements by spatial data. Precipitation and temperature were obtained from modelled (and gauge-corrected) data as well as from satellite-derived datasets. The MODIS instrument onboard Terra provided NDVI data. Soil moisture was integrated from a merged active and passive microwave remote sensing dataset that had been created within the Climate Change Initiative (CCI) of the European Space Agency (ESA) This study aims at illustrating the performance of a satellite

  16. Evaluating the Potential Use of Remotely-Sensed and Model-Simulated Soil Moisture for Agricultural Drought Risk Monitoring

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    Current two datasets provide spatial and temporal resolution of soil moisture at large-scale: the remotely-sensed soil moisture retrievals and the model-simulated soil moisture products. Drought monitoring using remotely-sensed soil moisture is emerging, and the soil moisture simulated using land surface models (LSMs) have been used operationally to monitor agriculture drought in United States. Although these two datasets yield important drought information, their drought monitoring skill still needs further quantification. This study provides a comprehensive assessment of the potential of remotely-sensed and model-simulated soil moisture data in monitoring agricultural drought over the Columbia River Basin (CRB), Pacific Northwest. Two satellite soil moisture datasets were evaluated, the LPRM-AMSR-E (unscaled, 2002-2011) and ESA-CCI (scaled, 1979-2013). The USGS Precipitation Runoff Modeling System (PRMS) is used to simulate the soil moisture from 1979-2011. The drought monitoring skill is quantified with two indices: drought area coverage (the ability of drought detection) and drought severity (according to USDM categories). The effects of satellite sensors (active, passive), multi-satellite combined, length of climatology, climate change effect, and statistical methods are also examined in this study.

  17. Comparing SMMR and AVHRR data for drought monitoring

    NASA Technical Reports Server (NTRS)

    Tucker, Compton J.

    1989-01-01

    Coincident Scanning Microwave Multi-channel Radiometer 37 GHz and Advanced Very High Resolution Radiometer normalized difference vegetation index satellite data have been compared from drought-affected regions of sub-Saharan Africa and northeastern Brazil for the time period of 1980-1985. Although the two satellite data types can be highly correlated, differences between them were found for the Sahel zone in 1985 and for northeastern Brazil from 1984-1985. These findings suggest that scattering or surface roughness contributions may be greater than previously assumed for the 37 GHz microwave data.

  18. 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

  19. [An improved method and its application for agricultural drought monitoring based on remote sensing].

    PubMed

    Zheng, You-Fei; Cheng, Jin-Xin; Wu, Rong-Jun; Guan, Fu-Lai; Yao, Shu-Ran

    2013-09-01

    From the viewpoint of land surface evapotranspiration, and by using the semi-empirical evapotranspiration model based on the Priestley-Taylor equation and the land surface temperature-vegetation index (LST-VI) triangle algorithm, the current monitoring technology of agricultural drought based on remote sensing was improved, and a simplified Evapotranspiration Stress Index (SESI) was derived. With the application of the MODIS land products from March to November in 2008 and 2009, the triangle algorithm modeling with three different schemes was constructed to calculate the SESI to monitor the agricultural drought in the plain areas of Beijing, Tianjin, and Hebei, in comparison with the Temperature Vegetation Dryness Index (TVDI). The results showed that SESI could effectively simplify the remote sensing drought monitoring method, and there was a good agreement between SESI and surface soil (10 and 20 cm depth) moisture content. Moreover, the performance of SESI was better in spring and autumn than in summer, and the SESI during different periods was more comparable than TVDI. It was feasible to apply the SESI to the continuous monitoring of a large area of agricultural drought. PMID:24417121

  20. On the utility of land surface models for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely-sensed vegetation indices (VI) is examined from January 2000 until December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strateg...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 p...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. 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).

  5. 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

  6. Drought monitoring with remote sensing based land surface phenology applications and validation

    NASA Astrophysics Data System (ADS)

    El Vilaly, Mohamed Abd salam M.

    Droughts are a recurrent part of our climate, and are still considered to be one of the most complex and least understood of all natural hazards in terms of their impact on the environment. In recent years drought has become more common and more severe across the world. For more than a decade, the US southwest has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources. The focus of this work is achieving a better understanding of the impact of drought on the lands of the Hopi Tribe and Navajo Nation, situated in the Northeastern corner of Arizona. This research explores the application of remote sensing data and geospatial tools in two studies to monitor drought impacts on vegetation productivity. In both studies we used land surface phenometrics as the data tool. In a third related study, I have compared satellite-derived land surface phenology (LSP) to field observations of crop stages at the Maricopa Agricultural Center to achieve a better understanding of the temporal sensitivity of satellite derived phenology of vegetation and understand their accuracy as a tool for monitoring change. The first study explores long-term vegetation productivity responses to drought. The paper develops a framework for drought monitoring and assessment by integrating land cover, climate, and topographical data with LSP. The objective of the framework is to detect long-term vegetation changes and trends in the Normalized Difference Vegetation Index (NDVI) related productivity. The second study examines the major driving forces of vegetation dynamics in order to provide valuable spatial information related to inter-annual variability in vegetation productivity for mitigating drought impacts. The third study tests the accuracy of remote sensing-derived LSP by comparing them to the actual seasonal phases of crop growth. This provides a way to compare and validate the various LSP algorithms, and more crucially, helps to

  7. 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.

  8. [Vegetation water content retrieval and application of drought monitoring using multi-spectral remote sensing].

    PubMed

    Wang, Li-Tao; Wang, Shi-Xin; Zhou, Yi; Liu, Wen-Liang; Wang, Fu-Tao

    2011-10-01

    The vegetation is one of main drying carriers. The change of Vegetation Water Content (VWC) reflects the spatial-temporal distribution of drought situation and the degree of drought. In the present paper, a method of retrieving the VWC based on remote sensing data is introduced and analyzed, including the monitoring theory, vegetation water content indicator and retrieving model. The application was carried out in the region of Southwest China in the spring, 2010. The VWC data was calculated from MODIS data and spatially-temporally analyzed. Combined with the meteorological data from weather stations, the relationship between the EWT and weather data shows that precipitation has impact on the change in vegetation moisture to a certain extent. However, there is a process of delay during the course of vegetation absorbing water. So precipitation has a delaying impact on VWC. Based on the above analysis, the probability of drought monitoring and evaluation based on multi-spectral VWC data was discussed. Through temporal synthesis and combined with auxiliary data (i. e. historical data), it will help overcome the limitation of data itself and enhance the application of drought monitoring and evaluation based on the multi-spectral remote sensing. PMID:22250560

  9. [Evaluating the utility of MODIS vegetation index for monitoring agricultural drought].

    PubMed

    Li, Hua-Peng; Zhang, Shu-Qing; Gao, Zi-Qiang; Sun, Yan

    2013-03-01

    The exclusive shortwave bands provided by MODIS sensors offer new opportunities for agricultural drought monitoring, since they are very sensitive to vegetation moisture. In the present work, we selected Songnen Plain in Northeast China as study area aiming at monitoring agricultural drought of dry farmland here. Four types of vegetation water indices and vegetation greenness indices were calculated from the 8-day composite MODIS product (MODO9A1) in vegetation growing season between 2001 and 2010, respectively. Multi-scale standardized precipitation index (SPI) derived from precipitation data of weather stations was used as reference data to estimate drought sensitivity of various vegetation indices, and a pixel-to-weather station paired correlation approach was used to calculate the Pearson correlation coefficient between vegetation index and SPIs. The result indicated that vegetation water indices established by near infrared and shortwave infrared bands outperformed vegetation greenness indices based on visible and near infrared bands. Of these indices, NDII7 performs the best with highest correlation coefficients across all SPIs. The authors' results demonstrated the potential of MODIS shortwave spectral bands in monitoring agricultural drought, and this provides new insights to future research. PMID:23705448

  10. 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.

  11. a Combined Approach with Smos and Modis to Monitor Agricultural Drought

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    A synergistic fusion of the Soil Moisture and Ocean Salinity (SMOS) L2 soil moisture with the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and several water/vegetation indices for agricultural drought monitoring was tested. The rationale of the calculation is based on the inverse relationship between LST and vegetation condition, related in turn with the soil moisture content. All the products were time-integrated, including the lagged response of vegetation. The product aims to detect and characterize soil moisture drought conditions and, particularly, to identify potential short-term agricultural droughts among them. The new index, so-called the Soil Moisture Agricultural Drought Index (SMADI), was retrieved at 500 m spatial resolution at the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) area from 2010 to 2014 at 8-days temporal scale. SMADI was compared with other agricultural indices in REMEDHUS through statistical correlation, affording a good agreement with them, and depicting a suitable description of the drought conditions in this area during the study period.

  12. Quantifying the reliability of four global datasets for drought monitoring over a semiarid region

    NASA Astrophysics Data System (ADS)

    Katiraie-Boroujerdy, Pari-Sima; Nasrollahi, Nasrin; Hsu, Kuo-lin; Sorooshian, Soroosh

    2016-01-01

    Drought is one of the most relevant natural disasters, especially in arid regions such as Iran. One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months' persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available.

  13. Development of satellite-based drought monitoring and warning system in Asian Pacific countries

    NASA Astrophysics Data System (ADS)

    Takeuchi, W.; Oyoshi, K.; Muraki, Y.

    2013-12-01

    This research focuses on a development of satellite-based drought monitoring warning system in Asian Pacific countries. Drought condition of cropland is evaluated by using Keeth-Byram Drought Index (KBDI) computed from rainfall measurements with GSMaP product, land surface temperature by MTSAT product and vegetation phenology by MODIS NDVI product at daily basis. The derived information is disseminated as a system for an application of space based technology (SBT) in the implementation of the Core Agriculture Support Program. The benefit of this system are to develop satellite-based drought monitoring and early warning system (DMEWS) for Asian Pacific counties using freely available data, and to develop capacity of policy makers in those countries to apply the developed system in policy making. A series of training program has been carried out in 2013 to officers and researchers of ministry of agriculture and relevant agencies in Greater Mekong Subregion countries including Cambodia, China, Myanmar, Laos, Thailand and Vietnam. This system is running as fully operational and can be accessed at http://webgms.iis.u-tokyo.ac.jp/DMEWS/.

  14. 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

  15. National Integrated Drought Information System (NIDIS), United State Drought Portal (USDP): A Window on Drought Information, Impacts and Implications

    NASA Astrophysics Data System (ADS)

    Owen, T.; Svoboda, M.; Pulwarty, R.

    2007-12-01

    The NIDIS Act of 2006 calls for an interagency approach to improve drought monitoring, forecasting and early warning. Led by NOAA, NIDIS focuses on the consolidation of physical, hydrological and socio-economic impacts data; integrated observing networks; development of a suite of drought decision support and simulation tools; and interactive delivery of standardized products through an internet portal. The vision for NIDIS is a dynamic and accessible drought risk information system that informs user decisions in preparing for and mitigating of the effects of drought. In support of this vision, the U.S. Drought Portal (USDP) will be a national resource for data, models, risk information and impacts of drought, with responsibility for integrating, archiving, and disseminating data via the internet. A portal environment, defined as a "site on the World Wide Web that typically provides personalized capabilities for their visitors," is critical, as it allows selected drought information from multiple authorities to be consolidated and interrogated, while simultaneously using metadata references to identify emerging information from the drought community. The USDP will provide reliable information on drought conditions at county, regional and national scales and serve as the primary point of entry for drought-related queries (through the already secured drought.gov URL) for a variety of user groups. Such questions include: -Where are drought conditions now and where might they develop? -Does this drought event look like other events in the past? -Will the drought continue? -How is the drought affecting me? -How can I plan for and manage the impacts of drought? The USDP will be comprised of information tailored for various user communities. The portal will work by combining NIDIS-related data and information with tools necessary to exchange and integrate data on various space and time scales, and among various formats. These portal data will incorporate a spectrum of

  16. Joint use of soil moisture and vegetation growth condition by remote sensing on the agricultural drought monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Yang, Siquan; Huang, He; He, Haixia; Li, Suju; Cui, Yan

    2015-12-01

    Remote sensing is one of important methods on the agricultural drought monitoring for its long-term and wide-area observations. The detection of soil moisture and vegetation growth condition are two widely used remote sensing methods on that. However, because of the time lag in the impact of water deficit on the crop growth, it is difficulty to indicate the severity of drought by once monitoring. It also cannot distinguish other negative impact on crop growth such as low temperature or solar radiation. In this paper, the joint use of soil moisture and vegetation growth condition detections was applied on the drought management during the summer of 2013 in Liaoning province, China, in which 84 counties were affected by agricultural drought. MODIS vegetation indices and land surface temperature (LST) were used to extract the drought index. Vegetation Condition Index (VCI), which only contain the change in vegetation index, and Vegetation Supply Water Index (VSWI), which combined the information of vegetation index and land surface temperature, were selected to compare the monitoring ability on drought during the drought period in Liaoning, China in 2014. It was found that VCI could be a good method on the loss assessment. VSWI has the information on the change in LST, which can indicate the spatial pattern of drought and can also be used as the early warning method in the study.

  17. 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.

  18. Zonal calculation for large scale drought monitoring based on MODIS data

    NASA Astrophysics Data System (ADS)

    Li, Hongjun; Zheng, Li; Li, Chunqiang; Lei, Yuping

    2006-08-01

    Temperature vegetation dryness index (TVDI) is a simple and effective methods for drought monitoring. In this study, the statistic characteristics of MODIS-EVI and MODI-NDVI at two different times were analyzed and compared. NDVI reaches saturation in well-vegetated areas while EVI has no such a shortcoming. In current study, we used MODIS-EVI as vegetation index for TVDI. The analysis of vegetation index and land surface temperature at different latitudes and different times showed that there was a zonal distribution of land surface parameters. It is therefore necessary to calculate the TVDI with a zonal distribution. Compared with TVDI calculated for the whole region, the zonal calculation of TVDI increases the accuracy of regression equations of wet and dry edge, improves the correlations of TVDI and measured soil moisture, and the effectiveness of the large scale drought monitoring using remote sensing data.

  19. 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; vanDijk, Albert I. J. M.; Lloyd-Hughes, Benjamin; Pappenberger, Florian; Werner, Micha; Dutra, Emanuel; Wetterhall, Fredrik; Wagner, Wolfgang; Schubert, Siegfried; Mo, Kingste; Nicholson, Margaret; Bettio, Lynette; Nunez, Liliana; vanBeek, Rens; Bierkens, Marc; deGoncalves, Luis Gustavo Goncalves; deMattos, Joao Gerd Zell; Lawford, Richard

    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

  20. 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.

  1. AVHRR monitoring of U.S. crops during the 1988 drought

    NASA Technical Reports Server (NTRS)

    Teng, William L.

    1990-01-01

    Effects of the 1988 drought on crops in the U.S. Corn Belt were assessed and monitored by the Foreign Crop Condition Assessment Division (FCCAD), U.S. Department of Agriculture. The primary data were vegetation index numbers (VINs), each of which was calculated as an average vegetation index of a geographically referenced cell of AVHRR pixels. Using VINs, the FCCAD was able to detect the existence of drought early in the season, monitor changing conditions, and provide objective assessments of the drought's extent and severity. Field observations confirmed the image analyses, and underlined the importance of the timing of extreme weather events with respect to crop stages for interpreting VINs. The analyses were conducted in an operational environment, providing a unique test of the AVHRR data for large area, near real-time crop monitoring. Because large area, operational remote sensing of crops is quite different from traditional, controlled, small plot research studies, more work is needed to link the two; this would improve crop assessment capabilities.

  2. Monitoring global land surface drought based on a hybrid evapotranspiration model

    NASA Astrophysics Data System (ADS)

    Yao, Yunjun; Liang, Shunlin; Qin, Qiming; Wang, Kaicun; Zhao, Shaohua

    2011-06-01

    The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from -6.72 W/m 2 to 12.95 W/m 2 and the average monthly bias is -1.73 W/m 2. Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from -12.91 W/m 2 to 10.26 W/m 2 and the average monthly bias is -3.59 W/m 2. To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with

  3. Application of HJ-1A/B and ZY-3 remote sensing data for drought monitoring in Hubei Province China

    NASA Astrophysics Data System (ADS)

    Huang, He; Fan, Yida; Yang, Siquan; Wen, Qi; Pan, Donghua; Fan, Chunbo; He, Haixia

    2013-10-01

    Drought is one kind of nature disasters in the world. It has characteristics of temporal-spatial inhomogeneity, wide affected areas and periodic happening. The economic loss and affected population caused by different droughts are the largest in all natural disasters. Remote sensing has the advantages of large coverage, frequent observation, repeatable observation, reliable information source and low cost. These advantages make remote sensing a vital contributor for drought disaster risk assessment and monitoring. In this paper, three drought monitoring models, such as Vegetation Condition Index (VCI), Temperature Vegetation Dryness Index (TVDI), and Water Supplying Vegetation Index (WSVI) had been selected to monitor the drought occurred from January 2012 to June 2012 in Hubei province, China. Two kinds of remote sensing data, including HJ-1A/B CCD/IRS and ZY-3, had been employed to assess the integrated risk of Hubei drought based on three drought monitoring models. The results shown that the risk of northwest regions and middle regions in Hubei province were higher than that in the other regions. The results also indicated that the extreme risk regions were located in Shiyan, Xiangyang, Suizhou and Jingmen.

  4. Machine Learning Approaches to Drought Monitoring and Assessment through Blending of Multi-sensor Indices for Different Climate Regions

    NASA Astrophysics Data System (ADS)

    Park, Seonyoung; Im, Jungho; Jang, Eunna; Yoon, Hyunjin; Rhee, Jinyoung

    2014-05-01

    Drought causes a water shortage problem which threats human life as well as affects agricultural resources. Unlike other natural disasters such as floods, earthquakes, and landslides, drought is a slow-moving disaster, which is hard to accurately quantify spatio-temporal starting and ending points of the process. It is also difficult to estimate the damage from drought, because such damage combines social, economic, and environmental components in multi-temporal scales. There are many definitions of drought considering its type, temporal scales and regions. Drought has been actively monitored all over the world using in situ meteorological and climate measurements and satellite remote sensing measurements. There are many drought indices that use in situ measurements collected at weather stations, including z-score, Standard Precipitation Index (SPI), and Palmer Drought Severity Index (PDSI). However, these indices are point-based and limited in covering vast areas to show spatial distribution of drought. Since spatial interpolation is required to estimate spatial distribution of drought from in-situ measurements, uncertainty of drought estimation typically increases where in situ data are limited. Drought monitoring and assessment using satellite products provide an effective way as satellite data cover vast areas at high temporal resolution (e.g., daily). Most of remote sensing-based drought studies have focused on arid regions because satellite products usually well respond to the surface condition of short-term drought in arid regions. While drought often occurs in humid regions, satellite-based drought monitoring of such regions needs further investigation. In this study, remote sensing-based drought monitoring and assessment were evaluated for both arid and humid regions in the United States between 2000 and 2012 focusing on metrological and agricultural drought. Since there is no single indicator that represents complexity and diversity of drought, a total 11

  5. Agriculture In Uruguay: New Methods For Drought Monitoring and Crop Identification Using Remotely Sensed Data

    NASA Astrophysics Data System (ADS)

    Lessel, J.; Ceccato, P.

    2014-12-01

    Agriculture is a vital resource in the country of Uruguay. Here we propose new methods using remotely sensed data for assisting ranchers, land managers, and policy makers in the country to better manage their crops. Firstly, we created a drought severity index based on the climatological anomalies of land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), precipitation data from the Tropical Rainfall Monitoring Mission (TRMM), and normalized difference water index (NDWI) data also using MODIS. The use of the climatological anomalies on the variables has improved the ability of the index to correlate with known drought indices versus previously published indices, which had not used them. We applied various coefficient schemes and vegetation indices in order to choose the model which best correlated with the drought indices across 10 sites throughout Uruguay's rangelands. The model was tested over summer months from 2009-2013. In years where drought had indeed been a problem in the country (such as 2009) the model showed intense signals of drought. Secondly, we used Landsat images to identify winter and summer crops in Uruguay. We first classified them using ENVI and then used the classifications in an ArcMap model to identify specific crop areas. We first created a polygon of the classifications for soils and vegetation for each month (omitting cloud covered images). We then used the crop growing cycle to identify the times during the year for which specific polygons should be soil and which should be vegetation. By intersecting the soil polygons with the vegetation polygons during their respective time periods during the crop growing cycle we were able to create an accurately identify crops. When compared to a shapefile of proposed crops for the year the model obtained a kappa value of 0.60 with a probability of detection of 0.79 and a false alarm ratio of 0.31 for the south-western study area over the 2013-2014 summer.

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

    USGS Publications Warehouse

    U.S. Geological Survey

    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. Assessment of the EUMETSAT LSA-SAF evapotranspiration product for drought monitoring in Europe

    NASA Astrophysics Data System (ADS)

    Sepulcre-Canto, Guadalupe; Vogt, Jürgen; Arboleda, Alirio; Antofie, Tiberiu

    2014-08-01

    Evapotranspiration is a key parameter for water stress assessment as it is directly related to the moisture status of the soil-vegetation system and describes the moisture transfer from the surface to the atmosphere. With the launch of the Meteosat Second Generation geostationary satellites and the setup of the Satellite Application Facilities, it became possible to operationally produce evapotranspiration data with high spatial and temporal evolution over the entire continents of Europe and Africa. In the frame of this study we present an evaluation of the potential of the evapotranspiration (ET) product from the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA-SAF) for drought assessment and monitoring in Europe. To assess the potential of this product, the LSA-SAF ET was used as input for the ratio of ET to reference evapotranspiration (ET0), the latter estimated from the ECMWF interim reanalysis. In the analysis two case studies were considered corresponding to the drought episodes of spring/summer 2007 and 2011. For these case studies, the ratio ET/ET0 was compared with meteorological drought indices (SPI, SPEI and Sc-PDSI for 2007 and SPI for 2011) as well as with the anomalies of the fraction of absorbed photosynthetic active radiation (fAPAR) derived from remote sensing data. The meteorological and remote sensing indicators were taken from the European Drought Observatory (EDO) and the CARPATCLIM climatological atlas. Results show the potential of ET/ET0 to characterize soil moisture variability, and to give additional information to fAPAR and to precipitation distribution for drought assessment. The main limitations of the proposed ratio for drought characterization are discussed, including options to overcome them. These options include the use of filters to discriminate areas with a low percentage vegetation cover or areas that are not in their growing period and the use of evapotranspiration without water restriction (ETwwr

  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. 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.

  10. Early-season agricultural drought: detection, assessment and monitoring using Shortwave Angle and Slope Index (SASI) data.

    PubMed

    Das, Prabir Kumar; Murthy, Srirama C; Seshasai, M V R

    2013-12-01

    Early season or crop-planting-period (ES/CPP) drought conditions have become a recurrent phenomenon in tropical countries like India, due to fluctuations in the time of onset and progression of monsoon rains. ES/CPP agricultural drought assessment is a major challenge because of the difficulties in the generation of operational products on soil moisture at larger scales. The present study analyzed the Shortwave Angle Slope Index (SASI) derived from Near Infrared and Shortwave Infrared data of Moderate Resolution Imaging Spectroradiometer, for tracking surface moisture changes and assessing the agricultural drought conditions during ES/CPP, over Andhra Pradesh state, India. It was found that in-season progression of SASI was well correlated with rainfall and crop planting patterns in different districts of the study area state in both drought and normal years. Rainfall occurrence, increase in crop planted area, and decrease in SASI were in chronological synchronization in the season. Change in SASI from positive to negative values is a unique indication of dryness to wetness shift in the season. Duration of positive SASI values indicated the persistence of agricultural drought in the crop planting period. Mean SASI values were able to discriminate an area which was planted in normal year and unplanted in drought year. SASI thresholds provide an approximate and rapid estimate of the crop planting favorable area in a region which is useful to assess the impact of drought. Thus, SASI is a potential index to strengthen the existing operational drought monitoring systems. Further work needs to be on the integration of multiple parameters-SASI, soil texture, soil depth, rainfall and cropping pattern, to evolve a geospatial product on crop planting favorable areas. Such products pave the way for quantification of drought impact on agriculture in the early part of the season, which is a major inadequacy in the current drought monitoring system. PMID:23793539

  11. 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.

  12. [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. PMID:15146625

  13. Toward a Drought Cyberinfrastructure System for Improving Water Resource Management and Policy Making

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.; Feldman, D.; Grant, S.; Farahmand, A.; Nakhjiri, N.; Momtaz, F.

    2014-12-01

    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

  14. Monitoring the Impacts of Severe Drought on Plant Species in Southern California Chaparral

    NASA Astrophysics Data System (ADS)

    Dennison, P. E.; Coates, A.; Roberts, D. A.; Roth, K. L.

    2015-12-01

    Airborne imaging spectrometer and thermal infrared image data acquired for the Hyperspectral Infrared Imager (HyspIRI) preparatory campaign were used to measure changes in green vegetation fraction and land surface temperature for twelve dominant plant species affected by drought in the Santa Barbara region of California. Relative green vegetation fraction was calculated from seasonally-acquired Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data using pre-drought 2011 AVIRIS data as a baseline. Land surface temperature was retrieved from MODIS-ASTER Simulator (MASTER) data. Deeply rooted tree species, tree species found on more mesic north-facing slopes, and tree species found in riparian areas had the least change in relative green vegetation fraction in 2013 and 2014 (e.g. QUAG and UMCA in the figure below). Coastal sage scrub and chaparral shrub species demonstrated greater variability as well as a long-term decline in relative green vegetation fraction. Three Ceanothus species (CECU, CEME, and CESP in the figure below) had more severe reductions in relative green vegetation fraction in comparison to another common chaparral shrub species, Adenostoma fasciculatum (ADFA). Species formed clusters in the space defined by land surface temperature and relative green vegetation fraction. Declining relative green vegetation fraction corresponded with increasing land surface temperature. Combined, routine acquisition of imaging spectrometer and thermal infrared imagery should provide new opportunities for monitoring drought impacts on ecosystems.

  15. 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.

  16. Extension of a drought monitoring and vegetation classification methodology to the western Sahel

    NASA Technical Reports Server (NTRS)

    Mohler, Robert R. J.; Amsbury, David L.

    1988-01-01

    Biomass of growing vegetation over large semiarid regions can be estimated by digital manipulation of data from the AVHRR on NOAA polar-orbiting satellites. Here, the African Sahel is classified using a methodology which incorporates both the normalized difference and CAUSE procedures for the monitoring of vegetation during drought conditions. Preliminary analysis of color IR photographs taken on Space Shuttle missions indicates that such photographs can be digitized, registered to maps and other images, and utilized to fill temporal gaps in the historical record of data from unmanned satellites.

  17. 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

  18. Downscaling Soil Moisture Product from SMOS for Monitoring Agricultural Droughts in South America

    NASA Astrophysics Data System (ADS)

    Nagarajan, K.; Fu, C.; Judge, J.; Fraisse, C.

    2012-12-01

    drought period of 2007-2008 were used to train the downscaling methodology. Observations obtained during the growing season of 2010, during which ESA-SMOS observations were available, was used to demonstrate the feasibility of the methodology for monitoring agricultural droughts.

  19. 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.

  20. 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.

  1. 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.

  2. Calcareous palaeosols and temples in the floodplain of Thebes, Egypt: droughts and decisions

    NASA Astrophysics Data System (ADS)

    Graham, Angus; Hunter, Morag A.; Pennington, Benjamin T.; Strutt, Kristian D.

    2014-05-01

    The Egypt Exploration Society Theban Harbours and Waterscapes Survey (THaWS) works in the area around modern Luxor (Egypt), and investigates the extent to which the Egyptians manipulated the Nile and floodplain through canal and basin construction. A current focus of the project is to understand the relationship between the floodplain and a series of temples on the West Bank. A longstanding puzzle on the West Bank is why the temple of Amenhotep III (1390-1352 BCE) is not located in the same area as all the others. While 19 kings of the Egyptian New Kingdom (1550-1070 BCE) built their temples on the toe-slope of the limestone cliffs fronting onto the edge of the modern alluvium, Amenhotep's sits entirely on the modern floodplain. Egyptologists have suggested this was done to allow the inundation of the Nile to wash into the temple, symbolising and recreating the essential Egyptian cosmogony of the primeval mound. However, was it possible that a period of low Nile discharge enabled him to build on the alluvium whilst keeping the temple dry from the Nile floods? The project is testing this hypothesis through an interdisciplinary approach which provides focussed information on the development of the floodplain over historic time periods. It combines geophysical survey (Electrical Resistivity Tomography, Ground Penetrating Radar and magnetometry) with geoarchaeology using an Eijkelkamp hand auger and gouge auger with facies being dated using the stratigraphic sequence of ceramic fragments within them. Two fieldwork seasons have been carried out to date (Graham et al. 2012, 2013). Calcareous palaeosols c. 4m below the surface have been identified in three separate augers across a distance of 3 km on the West Bank floodplain, suggesting a period of low inundation levels / drought. At one of the locations an ancient surface appears to lie 0.3-0.4m above the calcisol. Ceramic fragments from this unit tentatively indicate a New Kingdom date. The strontium isotope record from

  3. Sequential decision plans, benthic macroinvertebrates, and biological monitoring programs

    NASA Astrophysics Data System (ADS)

    Jackson, John K.; Resh, Vincent H.

    1989-07-01

    A common obstacle to the inclusion of benthic macroinvertebrates in water quality monitoring programs is that numerous sample units must be examined in order to distinguish between impacted and unimpacted conditions, which can add significantly to the total cost of a monitoring program. Sequential decision plans can be used to reduce this cost because the number of sample units needed to classify a site as impacted or unimpacted is reduced by an average of 50%. A plan is created using definitions of unimpacted and impacted conditions, a description of the mathematical distribution of the data, and definitions of acceptable risks of type I and II errors. The applicability of using sequential decision plans and benthic macroinvertebrates in water quality monitoring programs is illustrated with several examples (e.g., identifying moderate and extreme changes in species richness in response to acid mine drainage; assessing the impact of a crude oil contamination on the density of two benthic populations; monitoring the effect of geothermal effluents on species diversity). These examples use data conforming to the negative binomial, Poisson, and normal distributions and define impact as changes in population density, species richness, or species diversity based on empirical data or the economic feasibility of the sequential decision plan. All mathematical formulae and intermediate values are provided for the step-by-step calculation of each sequential decision plan.

  4. Evaluating the Performance of a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Han, E.; Crow, W. T.; Holmes, T. R.; Bolten, J. D.

    2013-12-01

    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, we evaluates a soil moisture assimilation system for agricultural drought monitoring by benchmarking each component 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 inputs/output) as the full component. Lagged soil moisture/NDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities and/or 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. First, the non-linear LPRM retrieval algorithm does not appear to add much additional predictive information for future NDVI compared to the simple linear benchmark model comprised of initial AMSR-E observations (horizontally and vertically polarized brightness temperatures and surface temperature). Second, the Palmer model performed worse than the purely linear prognostic model (Antecedent Precipitation Index model) in predicting future vegetation condition. This result points out that the saturation threshold of soil layers in the modern LSMs for runoff generation hinders maximum utilization of meteorological input information for agricultural drought monitoring. As to the assimilation algorithm, better performance of the

  5. 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. 

  6. 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.

  7. 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

  8. 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

  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. 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.

  11. Improving agricultural drought monitoring in West Africa using root zone soil moisture estimates derived from NDVI

    NASA Astrophysics Data System (ADS)

    McNally, A.; Funk, C. C.; Yatheendradas, S.; Michaelsen, J.; Cappelarere, B.; Peters-Lidard, C. D.; Verdin, J. P.

    2012-12-01

    The Famine Early Warning Systems Network (FEWS NET) relies heavily on remotely sensed rainfall and vegetation data to monitor agricultural drought in Sub-Saharan Africa and other places around the world. Analysts use satellite rainfall to calculate rainy season statistics and force crop water accounting models that show how the magnitude and timing of rainfall might lead to above or below average harvest. The Normalized Difference Vegetation Index (NDVI) is also an important indicator of growing season progress and is given more weight over regions where, for example, lack of rain gauges increases error in satellite rainfall estimates. Currently, however, near-real time NDVI is not integrated into a modeling framework that informs growing season predictions. To meet this need for our drought monitoring system a land surface model (LSM) is a critical component. We are currently enhancing the FEWS NET monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System. Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following questions: What is the relationship between NDVI and in-situ soil moisture measurements over the West Africa Sahel? How can we use this relationship to improve modeled water and energy fluxes over the West Africa Sahel? We investigate soil moisture and NDVI cross-correlation in the time and frequency domain to develop a transfer function model to predict soil moisture from NDVI. This work compares sites in southwest Niger, Benin, Burkina Faso, and Mali to test the generality of the transfer function. For several sites with fallow and millet vegetation in the Wankama catchment in southwest Niger we developed a non-parametric frequency response model, using NDVI inputs and soil moisture outputs, that accurately estimates root zone soil moisture (40-70cm). We extend this analysis by developing a low order parametric transfer function

  12. Drought monitoring and warning system of rice paddy field in Asia by MTSAT and GSMaP

    NASA Astrophysics Data System (ADS)

    Takeuchi, W.; Darmawan, S.; Oyoshi, K.

    2014-12-01

    This research focuses on a development of satellite-based drought monitoring warning system in Asian Pacific country. Drought condition of cropland is evaluated by using Keeth-Byram Drought Index (KBDI) computed from rainfall measurements with GSMaP product, land surface temperature by MTSAT product and vegetation phenology by MODIS NDVI product at daily basis. The derived information is disseminated as a system for an application of space based technology (SBT) in the implementation of the Core Agriculture Support Program. The benefit of this system are to develop satellite-based drought monitoring and early warning system in Asian counties using freely available data, and to develop capacity of policy makers in those countries to apply the developed system in policy making. A series of training program has been carried out in 2013 and 2014 to officers and researchers of ministry of agriculture and relevant agencies in Greater Mekong Subregion countries including Cambodia, China, Myanmar, Laos, Thailand and Vietnam. This system is running as fully operational and can be accessed at http://webgms.iis.u-tokyo.ac.jp/DMEWS/

  13. Improved drought monitoring in the Greater Horn of Africa by combining meteorological and remote sensing based indicators

    NASA Astrophysics Data System (ADS)

    Horion, Stephanie; Kurnik, Blaz; Barbosa, Paulo; Vogt, Jürgen

    2010-05-01

    Drought is a complex and insidious natural hazard. It is hence difficult to detect in its early stages and to monitor its spatial evolution. Defining drought is already a challenge and can be done differently by meteorologists, hydrologists or socio-economists. In each one of these research areas, various indicators were already set up to depict the development of drought. However they are usually considering only one aspect of the phenomenon. The development of integrated indicators could help to detect faster/better the onset of drought, to monitor more efficiently its evolution in time and space, and therefore to better trigger timely and appropriate actions on the field. In this study, meteorological and remote sensing based drought indicators were compared over the Greater Horn of Africa in order to better understand: (i) how they depict historical drought events ; (ii) if they could be combined into an integrated drought indicator. The meteorological indicator selected for our study is the well known Standardized Precipitation Index, SPI. This statistical indicator is evaluating the lack or surplus of precipitation during a given period of time as a function of the long-term average precipitation and its distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different regions in the Greater Horn of Africa. The time window for the statistical analysis was set to the rainy season, as it is the most critical period for

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  15. Nonadjunctive Use of Continuous Glucose Monitoring for Diabetes Treatment Decisions.

    PubMed

    Castle, Jessica R; Jacobs, Peter G

    2016-09-01

    While self-monitoring of blood glucose (SMBG) is the current standard used by people with diabetes to manage glucose levels, recent improvements in accuracy of continuous glucose monitoring (CGM) technology are making it very likely that diabetes-related treatment decisions will soon be made based on CGM values alone. Nonadjunctive use of CGM will lead to a paradigm shift in how patients manage their glucose levels and will require substantial changes in how care providers educate their patients, monitor their progress, and provide feedback to help them manage their diabetes. The approval to use CGM nonadjunctively is also a critical step in the pathway toward FDA approval of an artificial pancreas system, which is further expected to transform diabetes care for people with type 1 diabetes. In this article, we discuss how nonadjunctive CGM is expected to soon replace routine SMBG and how this new usage scenario is expected to transform health outcomes and patient care. PMID:26880390

  16. 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

  17. 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.

  18. On the value of combining different modelled soil moisture products for European drought monitoring

    NASA Astrophysics Data System (ADS)

    Cammalleri, C.; Micale, F.; Vogt, J.

    2015-06-01

    In the context of evaluating the occurrence of drought events over Europe, soil moisture maps provide an invaluable resource to quantify the effects of rainfall deficits on vegetated lands. Spatially distributed models represent one of the main options, alongside satellite remote sensing, to successfully monitor this quantity over large areas in a cost effective way. This work has the double aim of: (i) intercomparing three soil moisture outputs obtained by different land-surface models (LISFOOD, CLM and TESSEL) through long (at least 6 years of data between 2001 and 2011) in-situ measured datastreams, and (ii) quantifying the added value of combining the estimates of these three models by means of a simple ensemble approach. Generally, the three models return similar soil moisture anomalies over most of Europe, with few notable exceptions during summer in Mediterranean regions. The comparison with in-situ data suggests no substantial differences among the models, with LISFLOOD slightly outperforming the other two in terms of correlation as also supported by a pairwise comparison. The combined soil moisture anomalies obtained via the ensemble-mean approach are characterized by an increase of both the correlation and the accuracy in retrieving extreme events compared to the single models; however, the number of observed extreme events actually captured by the ensemble model does not increase significantly if compared to the single models. Overall, the ensemble model results are skillful, with an all site average skill score of about 0.4.

  19. Monitoring drought using spi and z-score for different time scales for Shiraz Station in Iran

    NASA Astrophysics Data System (ADS)

    Shirvani, A.; Amin, S.; Nazemosadat, S. M. J.

    2003-04-01

    Standardized Precipitation Index (SPI) is a probability index for monitoring drought. This drought index was recently developed to detect drought and wet periods for different time scales in various regions of the world. By precipitation data transform different time scale could be made and Z-Score of the new data will be calculated to compare categories of the drought severity for a specified region. The form of Probability Density Function (PDF) which defined SPI is a very important factor because applying different PDFs will return different SPI values for the same precipitation data. In this research, thirty four years (1967 to 2001) monthly precipitation data of the agricultural weather station of Shiraz, was used to calculate SPI and Z-Score values for different time scales: 1, 3, 6, 9, 12, 24 and 36 months. The Kolmogorov-Smirinov (K-S) test was used to check the goodness of fit of every data set. The K-S statistical results showed that the data fitted Pearson type III and gamma probability density when the time scales were less than 12 months, in other cases the normal probability density best fits precipitation data and when the normal probability density was used SPI and Z-Score were in a close agreement. Therefore, the corresponding conclusion is that when the time scale is increasing a closer agreement between SPI and Z-Score of the data could be achieved. Time series plots of SPIs indicated that the time scales less than 12 months had enormous fluctuations such that identifying drought and wet periods were not so clear. However, plots of 24-months SPI and 36-months SPI plots obviously could identify drought and wet periods of the region clearly. The duration, attenuation and intensity for any particular month during our historical records were time scale depended. The results of this study also showed that long-term drought of early 1960s and last part of 1970s impacted Shiraz station. Based on our research results we recommend the agriculturist use

  20. 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

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

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

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  9. Prognostic decision support using symbolic dynamics in CTG monitoring.

    PubMed

    Cesarelli, Mario; Romano, Maria; Bifulco, Paolo; Improta, Giovanni; D'Addio, Giovanni

    2013-01-01

    Foetal heart rate variability is one of the most important parameters to monitor foetal wellbeing. Linear parameters, widely employed to study foetal heart variability, have shown some limitations in highlight dynamics potentially relevant. During the last decades, therefore, nonlinear analysis methods have gained a growing interest to analyze the chaotic nature of cardiac activity. Parameters derived by techniques investigating nonlinear can be included in computerised systems of cardiotocographic monitoring. In this work, we described an application of symbolic dynamics to analyze foetal heart rate variability in healthy foetuses and a concise index, introduced for its classification in antepartum CTG monitoring. The introduced index demonstrated to be capable to highlight differences in heart rate variability and resulted correlated with the Apgar score at birth, in particular, higher variability indexes values are associated to early greater vitality at birth. These preliminary results confirm that SD can be a helpful tool in CTG monitoring, supporting medical decisions in order to assure the maximum well-being of newborns. PMID:23542985

  10. Monitoring in the nearshore: A process for making reasoned decisions

    USGS Publications Warehouse

    Bodkin, J.L.; Dean, T.A.

    2003-01-01

    Over the past several years, a conceptual framework for the GEM nearshore monitoring program has been developed through a series of workshops. However, details of the proposed monitoring program, e.g. what to sample, where to sample, when to sample and at how many sites, have yet to be determined. In FY 03 we were funded under Project 03687 to outline a process whereby specific alternatives to monitoring are developed and presented to the EVOS Trustee Council for consideration. As part of this process, two key elements are required before reasoned decisions can be made. These are: 1) a comprehensive historical perspective of locations and types of past studies conducted in the nearshore marine communities within Gulf of Alaska, and 2) estimates of costs for each element of a proposed monitoring program. We have developed a GIS database that details available information from past studies of selected nearshore habitats and species in the Gulf of Alaska and provide a visual means of selecting sites based (in part) on the locations for which historical data of interest are available. We also provide cost estimates for specific monitoring plan alternatives and outline several alternative plans that can be accomplished within reasonable budgetary constraints. The products that we will provide are: 1) A GIS database and maps showing the location and types of information available from the nearshore in the Gulf of Alaska; 2) A list of several specific monitoring alternatives that can be conducted within reasonable budgetary constraints; and 3) Cost estimates for proposed tasks to be conducted as part of the nearshore program. Because data compilation and management will not be completed until late in FY03 we are requesting support for close-out of this project in FY 04.

  11. The role of the midcingulate cortex in monitoring others' decisions

    PubMed Central

    Apps, Matthew A. J.; Lockwood, Patricia L.; Balsters, Joshua H.

    2013-01-01

    A plethora of research has implicated the cingulate cortex in the processing of social information (i.e., processing elicited by, about, and directed toward others) and reward-related information that guides decision-making. However, it is often overlooked that there is variability in the cytoarchitectonic properties and anatomical connections across the cingulate cortex, which is indicative of functional variability. Here we review evidence from lesion, single-unit recording and functional imaging studies. Taken together, these support the claim that the processing of information that has the greatest influence on social behavior can be localized to the gyral surface of the midcingulate cortex (MCCg). We propose that the MCCg is engaged when predicting and monitoring the outcomes of decisions during social interactions. In particular, the MCCg processes statistical information that tracks the extent to which the outcomes of decisions meet goals when interacting with others. We provide a novel framework for the computational mechanisms that underpin such social information processing in the MCCg. This framework provides testable hypotheses for the social deficits displayed in autism spectrum disorders and psychopathy. PMID:24391534

  12. A Collaborative Decision Environment to Support UAV Wildfire Monitoring Missions

    NASA Astrophysics Data System (ADS)

    Frost, C. R.; Enomoto, F. Y.; D'Ortenzio, M. V.; Nguyen, Q. B.

    2006-12-01

    NASA developed the Collaborative Decision Environment (CDE), the ground-based component of its Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAVs). The CDE was used to support science mission planning and decision-making for a NASA- and U.S. Forest Service-sponsored mission to monitor wildfires in the western United States using a multi- spectral imager flown onboard the General Atomics Altair UAV in summer of 2006. The CDE is a ground-based system that provides the mission/science team with situational awareness, collaboration, and decision tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, large wildfire locations, satellite-derived fire detection data, temporarily restricted airspace, and satellite imagery. While a prototype CDE was developed as a Java-based client/server application in 2004-2005, the team investigated the use of Google Earth to take advantage of its 3-D visualization capabilities, friendly user interface, and enhanced graphics performance. External data is acquired via the Internet by leveraging established and emerging Open Geospatial Consortium (OGC) standards and is re-formatted into the Keyhole Markup Language (KML) specification used by Google Earth. Aircraft flight position and sensor data products are relayed from the instrument ground station to CDE servers where they are made available to users. An instant messaging chat server is used to facilitate real-time communication between remote users. This paper will present an overview of the CDE system architecture, and discuss how science user input was crucial to shaping and developing the system. Examples from the UAV mission will be used to illustrate the presentation. Plans for future development work to improve mission operations, such as integration with

  13. 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.

  14. 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

  15. Drought monitoring based on TIGGE and distributed hydrological model in Huaihe River Basin, China.

    PubMed

    Zhao, Junfang; Xu, Jingwen; Xie, Xingmei; Lu, Houquan

    2016-05-15

    Drought assessment is important for developing measures to reduce agricultural vulnerability and thereby secure the livelihoods of those who depend on agriculture. This study uses four global ensemble weather prediction systems: the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centres for Environmental Prediction (NCEP) in the THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE) archive from 2006 to 2010. Based on results from the XXT (the first X denotes Xinanjiang, the second X denotes hybrid, and the T denotes TOPMODEL) distributed hydrological model, as well as soil moisture observations and digital elevation model (DEM) data, synthesized drought grades were established in the Huaihe River Basin of China. To filter out the impact of short-term fluctuations on observed soil moisture, a 30-day moving average was calculated. Use of the moving average significantly improves the correlation between observed soil moisture and simulated soil water deficit depth. Finally, a linear regression model describing the relationship between observed soil moisture and simulated soil water deficit depth was constructed. The deterministic regression coefficient was 0.5872, the correlation coefficient was 0.77, and the regression coefficient was -154.23. The trends in drought grades calculated using soil moisture and soil water deficit depth were found to be the same, and the grades agreed to within one level. Our findings highlight the importance of synthesizing drought grading when assessing drought using different soil moisture indicators in order to obtain a more comprehensive forecast of drought conditions. PMID:26930309

  16. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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, ...

  18. Identifiying and evaluating a suitable index for agricultural drought monitoring in the Texas High Plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought is a highly destructive natural phenomenon that affects portions of the United States almost every year. Severe water deficiencies can become catastrophic for agriculture and crop yields, especially in the Texas High Plains where generally inadequate rainfall is augmented by irrigation for c...

  19. Evaluating the performance of a soil moisture data assimilation system for agricultural drought monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. The European Drought Observatory (EDO) - A European Contribution to a Global Drought Information System (GDIS)

    NASA Astrophysics Data System (ADS)

    Vogt, J.; Sepulcre, G.; De Jager, A.; Magni, D.; Valentini, L.; Russo, S.; Micale, F.; Barbosa, P.

    2013-12-01

    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 EDO is a portal, including a map viewer, a metadata catalogue, a media-monitor and analysis tools. Underlying data stem from ground and satellite observations as well as from distributed hydrological models and are stored in a relational database. Through the map viewer Europe-wide up-to-date information on the occurrence and severity of droughts is presented, complemented by more detailed information from regional, national and local observatories through OGC compliant web-mapping services. The continent-wide meteorological, soil moisture-related and vegetation-related indicators are then integrated into a combined indicator showing different alert levels targeted specifically to decision makers in water and land management. Finally, time series of historical maps as well as graphs of the temporal evolution of drought indices for individual grid cells in Europe can be retrieved and analysed. On-going work is focusing on developing reliable medium and long-range probabilistic as well as seasonal drought forecasts, the analysis of climate change impacts on drought occurrence, duration and severity and the assessment of current and future drought hazard and risk. In addition, remote sensing-based water-stress indicators from geostationary satellite data (e.g., MSG SEVIRI) are developed in order to complement the available information. The further development of EDO as part of a Global Drought Information

  6. A prototype platform for water resources monitoring and early recognition of critical droughts in Switzerland

    NASA Astrophysics Data System (ADS)

    Zappa, M.; Bernhard, L.; Spirig, C.; Pfaundler, M.; Stahl, K.; Kruse, S.; Seidl, I.; Stähli, M.

    2014-09-01

    In recent years Switzerland has experienced some unprecedented drought situations. At a political level solutions have been requested for early recognition of hydrological droughts. A prototype information platform has been developed to guide water resources management during situations where water resources drop below critical levels. The development was steered by stakeholders from national administrations and different economic sectors. Since June 2013 the platform has presented daily updated real-time information on several drought indicators including precipitation, streamflow, lake levels, groundwater levels, soil moisture deficit, snow resources, dryness in forests and stream temperatures. For three basins, ensemble forecasts of runoff, soil moisture, snowpack and groundwater storage have been provided. Furthermore, a nationwide operational hydrological simulation at 600 × 600 m resolution gives indications on local water resources deficits. Information for each variable has been used to create automatic "awareness maps" for nine large regions. Three levels of information with increasing detail and complexity can be accessed by over 180 registered users. The operators of the platform give interpreted comments on the content of the platform each week-day. The test phase of the platform will last until the end of 2014.

  7. In-season Drought Monitoring: Testing Instrumentation and Developing Methods of Measurement Analysis

    NASA Astrophysics Data System (ADS)

    Raper, Tyson B.

    Soil moisture sensor use in crop production systems has the potential to give inference on plant water status for the purpose of irrigation scheduling and site-drought characterization. These processed measurements could serve as the framework on which to compile trial results across locations, thereby more accurately defining varietal yield response to drought. Still, the ability to characterize drought within a given field or initiate irrigations from these data hinge upon the ability of the instrument to characterize soil moisture at the sampled point and extrapolate that information across the landscape and time. Therefore, the objectives of this research were to: (1) test the response of the Watermark 200SS (Irrometer Company, Inc., Riverside, CA) and Decagon 10HS (Decagon Devices, Inc., Pullman, WA) to changes in water content of three dissimilar soils representing common soils in row-crop production under variable environmental conditions; (2) develop a soil moisture-based index to quantify drought stress in dryland cotton cultivar trials; and (3) determine if a limited number of soil moisture sensors deployed into a dryland cultivar trial could accurately characterize the VWC at a given point within the field and if this measurement could be extrapolated out to the field scale from the very small sphere of influence characterizing the utilized soil moisture sensors. During the 2012 and 2013 growing seasons soil moisture sensors were deployed into over 14 cotton cultivar trials across the U.S. Cotton Belt and into a water-input controlled container study. Tested sensors' inability to accurately predict container VWC emphasized the relatively small quantity of soil on which these sensors rely and the variability in soil moisture within a very limited volume. Results from the drought-index studies suggested both the Accumulated Soil Moisture Stress Index (ASMSI) and the relative reduction in evapotranspiration (1-(ETc adj/ETc)) appear to have potential in

  8. 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

  9. 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

  10. 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

  11. Estimation of drought transition probabilities in Sicily making use of exogenous variables

    NASA Astrophysics Data System (ADS)

    Bonaccorso, Brunella; di Mauro, Giuseppe; Cancelliere, Antonino; Rossi, Giuseppe

    2010-05-01

    Drought monitoring and forecasting play a very important role for an effective drought management. A timely monitoring of drought features and/or forecasting of an incoming drought do make possible an effective mitigation of its impacts, more than in the case of other natural disasters (e.g. floods, earthquakes, hurricanes, etc.). An accurate selection of indices, able to monitor the main characteristics of droughts, is essential to help decision makers to implement appropriate preparedness and mitigation measures. Among the several proposed indices for drought monitoring, the Standardized Precipitation Index (SPI) has found widespread use to monitor dry and wet periods of precipitation aggregated at different time scales. Recently, some efforts have been made to analyze the role of SPI for drought forecasting, as well as to estimate transition probabilities between drought classes. In the present work, a model able to estimate transition probabilities from a current SPI drought class or from a current SPI value to future classes, corresponding to droughts of different severities, is presented and extended in order to include information provided by an exogenous variable, such as a large scale climatic index as the North Atlantic Oscillation Index (NAO). The model has been preliminarily applied and tested with reference to SPI series computed on average areal precipitation in Sicily island, Italy, making use of NAO as exogenous variable. Results seem to indicate that winter drought transition probabilities in Sicily are generally affected by NAO index. Furthermore, the statistical significance of such influence has been tested by means of a Montecarlo analysis, which indicates that the effect of NAO on drought transition in Sicily should be considered significant.

  12. Relative Spectral Mixture Analysis for monitoring natural hazards that impact vegetation cover: the importance of the nonphotosynthetic fraction in understanding landscape response to drought, fire, and hurricane damage

    NASA Astrophysics Data System (ADS)

    Okin, G. S.

    2007-12-01

    Remote sensing provides a unique ability to monitor natural hazards that impact vegetation hydrologically. Here, the use of a new multitemporal remote sensing technique that employs free, coarse multispectral remote sensing data is demonstrated in monitoring short- and long-term drought, fire occurrence and recovery, and damage to hurricane-related mangrove ecosystems and subsequent recovery of these systems. The new technique, relative spectral mixture analysis (RSMA), provides information about the nonphotosynthetic fraction (nonphotosynthetic vegetation plus litter) of ground cover in addition to the green vegetation fraction. In some cases, RSMA even provides an improved ability to monitor changes in the green fraction compared to traditional vegetation indices or standard remote sensing products. In arid and semiarid regions, the nonphotosynthetic fraction can vary on an annual basis significantly more than the green fraction and is thus perfectly suited for monitoring drought in these regions. Mortality of evergreen trees due to long-term drought also shows up strongly in the nonphotosynthetic fraction as green vegetation is replaced by dry needles and bare trunks. The response of the nonphotosynthetic fraction to fire is significantly different from that of drought because of the combustion of nonphotosynthetic material. Finally, damage to mangrove ecosystems from hurricane damage, and their subsequent recovery, is readily observable in both the green and nonphotosynthetic fractions as estimated by RSMA.

  13. Developing a Climate Service: Using Hydroclimate Monitoring and Forecasting to Aid Decision Making in Africa and Latin America

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Hydrological and water scarcity predictions have the potential to provide vital information for a variety of needs including water resources management, agricultural and urban water supply, and flood mitigation. In particular, seasonal forecasts of drought risk can enable farmers to make adaptive choices on crop varieties, labor usage, and technology investments. Forecast skill is generally derived from teleconnections with ocean variability specifically sea surface temperature (SST) anomalies and, equally important persistence in the state of the land in terms of soil moisture, snowpack, or streamflow conditions. Short term precipitation forecasts are critical in flood prediction by extending flood prediction lead times beyond the basin travel time, and thus allows for extended warnings. The Global Framework for Climate Services (GFCS) is a UN-wide initiative in which WMO Members and inter- and non- governmental, regional, national and local stakeholders work in partnership to develop targeted climate services. Thus, GFCS offers the potential for hydroclimatologists to develop products (hydroclimatic forecasts) and information services (i.e. product dissemination) to users with the expectation that GFCS will increase the resilience of the society to weather and climate events and to reduce operational costs for economic sectors and regions dependent on water. This presentation will discuss the development of a nascent climate service system focused on hydroclimatic monitoring and forecasting, and initially developed by the authors for Africa and Latin America. Central to this system is the use of satellite remote sensing and hydroclimate forecasts (from days to seasons) in the development of weather and climate information useful for water management in sectors such as flood protection (precipitation and streamflow forecasting) and agriculture (drought and crop forecasting). The elements of this system will be discussed, including the challenges of monitoring and

  14. A case study of optimization in the decision process: Siting groundwater monitoring wells

    SciTech Connect

    Cardwell, H.; Huff, D.; Douthitt, J.; Sale, M.

    1993-12-01

    Optimization is one of the tools available to assist decision makers in balancing multiple objectives and concerns. In a case study of the siting decision for groundwater monitoring wells, we look at the influence of the optimization models on the decisions made by the responsible groundwater specialist. This paper presents a multi-objective integer programming model for determining the location of monitoring wells associated with a groundwater pump-and-treat remediation. After presenting the initial optimization results, we analyze the actual decision and revise the model to incorporate elements of the problem that were later identified as important in the decision-making process. The results of a revised model are compared to the actual siting plans, the recommendations from the initial optimization runs, and the initial monitoring network proposed by the decision maker.

  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. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    NASA Astrophysics Data System (ADS)

    Gu, Yingxin; Hunt, Eric; Wardlow, Brian; Basara, Jeffrey B.; Brown, Jesslyn F.; Verdin, James P.

    2008-11-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r~0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r~0.22).

  17. Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

    USGS Publications Warehouse

    Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  18. Monitoring drought impact on Mediterranean oak savanna vegetation using remote sensing

    NASA Astrophysics Data System (ADS)

    González-Dugo, Maria P.; Carpintero, Elisabet; Andreu, Ana

    2015-04-01

    A holm oak savanna, known as dehesa in Spain and montado in Portugal, is the largest agroforest ecosystem in Europe, covering about 3 million hectares in the Iberian Peninsula and Greece (Papanastasis et al., 2004). It is considered an example of sustainable land use, supporting a large number of species and diversity of habitats and for its importance in rural development and economy (Plieninger et al., 2001). It is a combination between an agricultural and a naturally vegetated ecosystem, consisting of widely-spaced oak trees (mostly Quercus Ilex and Quercus suber) combined with a sub-canopy composed by crops, annual grassland and/or shrubs. It has a Mediterranean climate with severe periodic droughts. In the last decades, this system is being exposed to multiple threats derived from socio-economic changes and intensive agricultural use, which have caused environmental degradation, including tree decline, changes in soil properties and hydrological processes, and an increase of soil erosion (Coelho et al., 2004). Soil water dynamics plays a central role in the current decline and reduction of forested areas that jeopardizes the preservation of the system. In this work, a series of remotely sensed images since 1990 to present was used to evaluate the effect of several drought events occurred in the study area (1995, 2009, 2010/2011) on the tree density and water status. Data from satellites Landsat and field measurements have been combined in a spectral mixture model to assess separately the evolution of tree, dry grass and bare soil ground coverage. Only summer images have been used to avoid the influence of the green herbaceous layer on the analysis. Thermal data from the same sensors and meteorological information are integrated in a two source surface energy balance model to compute the Evaporative Stress Index (ESI) and evaluate the vegetation water status. The results have provided insights about the severity of each event and the spatial distribution of

  19. Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts

    NASA Astrophysics Data System (ADS)

    Szczypta, C.; Calvet, J.-C.; Maignan, F.; Dorigo, W.; Baret, F.; Ciais, P.

    2014-05-01

    Two new remotely sensed leaf area index (LAI) and surface soil moisture (SSM) satellite-derived products are compared with two sets of simulations of the ORganizing Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) land surface models. We analyse the interannual variability over the period 1991-2008. The leaf onset and the length of the vegetation growing period (LGP) are derived from both the satellite-derived LAI and modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI and LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. In order to investigate how recent droughts affected vegetation over the Euro-Mediterranean area, a case study addressing the summer 2003 drought is presented. It shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite-derived product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of the Ukraine and southern Russia.

  20. An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. drought monitor classifications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Comparison of multiple hydrologic indicators, derived from independent data sources and modeling approaches, may improve confidence in signals of emerging drought – particularly during periods of rapid onset. This paper compares the Evaporative Stress Index (ESI) - a diagnostic fast-response indica...

  1. Impact of drought on the CO2 atmospheric growth rate 2010-2012 from the NASA Carbon Monitoring System Flux (CMS-Flux) Project

    NASA Astrophysics Data System (ADS)

    Bowman, K. W.; Liu, J.; Parazoo, N.; Jiang, Z.; Bloom, A. A.; Lee, M.; Menemenlis, D.; Gierach, M.; Collatz, G. J.; Gurney, K. R.

    2015-12-01

    The La Nina between 2011-2012 led to significant droughts in the US and Northeastern Brazil while the historic drought in Amazon in 2010 was caused in part by the historic central Pacific El Nino. In order to investigate the role of drought on the atmospheric CO2 growth rate, we use satellite observations of CO2 and CO to infer spatially resolved carbon fluxes and attribute those fluxes to combustion sources correlated with drought conditions. Solar induced fluorescence in turn is used to estimate the impact of drought on productivity and its relationship to total flux. Preliminary results indicate that carbon losses in Mexico are comparable to the total fossil fuel production for that region. These in turn played an important role in the acceleration of the atmospheric growth rate from 2011-2012. These results were enabled using the NASA Carbon Monitoring System Project (CMS-Flux), which is based upon a 4D-variational assimilation system that incorporates observationally-constrained "bottom-up" estimates from the Fossil Fuel Data Assimilation System (FFDAS), the ECCO2-­Darwin physical and biogeochemical adjoint ocean state estimation system, and CASA-GFED3 land-surface biogeochemical model.

  2. 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.

  3. Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

    NASA Technical Reports Server (NTRS)

    Rochon, Gilbert L.

    1989-01-01

    Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and

  4. Metacognition in human decision-making: confidence and error monitoring

    PubMed Central

    Yeung, Nick; Summerfield, Christopher

    2012-01-01

    People are capable of robust evaluations of their decisions: they are often aware of their mistakes even without explicit feedback, and report levels of confidence in their decisions that correlate with objective performance. These metacognitive abilities help people to avoid making the same mistakes twice, and to avoid overcommitting time or resources to decisions that are based on unreliable evidence. In this review, we consider progress in characterizing the neural and mechanistic basis of these related aspects of metacognition—confidence judgements and error monitoring—and identify crucial points of convergence between methods and theories in the two fields. This convergence suggests that common principles govern metacognitive judgements of confidence and accuracy; in particular, a shared reliance on post-decisional processing within the systems responsible for the initial decision. However, research in both fields has focused rather narrowly on simple, discrete decisions—reflecting the correspondingly restricted focus of current models of the decision process itself—raising doubts about the degree to which discovered principles will scale up to explain metacognitive evaluation of real-world decisions and actions that are fluid, temporally extended, and embedded in the broader context of evolving behavioural goals. PMID:22492749

  5. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    USGS Publications Warehouse

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

    2008-01-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

  6. 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.

  7. Defensible Progress Monitoring Data for Medium- and High-Stakes Decisions

    ERIC Educational Resources Information Center

    Parker, Richard I.; Vannest, Kimberly J.; Davis, John L.; Clemens, Nathan H.

    2012-01-01

    Within a response to intervention model, educators increasingly use progress monitoring (PM) to support medium- to high-stakes decisions for individual students. For PM to serve these more demanding decisions requires more careful consideration of measurement error. That error should be calculated within a fixed linear regression model rather than…

  8. The Theil-Sen Slope for High-Stakes Decisions from Progress Monitoring

    ERIC Educational Resources Information Center

    Vannest, Kimberly J.; Parker, Richard I.; Davis, John L.; Soares, Denise A.; Smith, Stacey L.

    2012-01-01

    More and more, schools are considering the use of progress monitoring data for high-stakes decisions such as special education eligibility, program changes to more restrictive environments, and major changes in educational goals. Those high-stakes types of data-based decisions will need methodological defensibility. Current practice for…

  9. 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

  10. A Simple Drought Product and Indicator Derived from Temperature and Relative Humidity Observed by the Atmospheric InfraRed Sounder (AIRS)

    NASA Astrophysics Data System (ADS)

    Granger, S. L.; Behrangi, A.

    2015-12-01

    In the United States, drought results in agricultural losses, impacts to industry, power and energy production, natural resources, municipal water supplies and human health making it one of the costliest natural hazards in the nation. Monitoring drought is therefore critical to help local governments, resource managers, and other groups make effective decisions, yet there is no single definition of drought, and because of the complex nature of drought there is no universal best drought indicator. Remote sensing applications in drought monitoring are advantageous due to the large spatial and temporal frequency of observations, leading to a better understanding of the spatial extent of drought and its duration, and in detecting the onset of drought and its intensity. NASA Earth Observing System (EOS)-era data have potential for monitoring and assessing drought and many are already used either directly or indirectly for drought monitoring. Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor are widely used for agricultural and environmental plant-stress monitoring via the USDM, the VegDRI project and FEWSNet. However there remain underutilized sources of information from NASA satellite observations that may have promise for characterizing and understanding meteorological drought. Once such sensor is NASA's Advanced Infra-Red Sounder (AIRS) aboard the Aqua satellite. AIRS and it's sister sensor the Advanced Microwave Sounding Unit (AMSU) that together provide meteorological information of high relevance to meteorological drought, e.g., profiles of water vapor, surface air temperature, and precipitation. Recent work undertaken to develop simple indicators of drought based on temperature and relative humidity from the AIRS suite of instruments is promising. Although there are more sophisticated indicators developed through the application of a variety of

  11. Monitoring of water use, drought and yield impacts using imagery from multiple satellites

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural monitoring systems require information with continuous spatial and temporal sampling, ideally collected at daily timesteps and at spatial scales from county level down to field scale. While remote sensing data significantly improve on the spatial sampling provided by ground-based obser...

  12. 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). PMID:21411433

  13. Supervision of dynamic systems: Monitoring, decision-making and control

    NASA Technical Reports Server (NTRS)

    White, T. N.

    1982-01-01

    Effects of task variables on the performance of the human supervisor by means of modelling techniques are discussed. The task variables considered are: The dynamics of the system, the task to be performed, the environmental disturbances and the observation noise. A relationship between task variables and parameters of a supervisory model is assumed. The model consists of three parts: (1) The observer part is thought to be a full order optimal observer, (2) the decision-making part is stated as a set of decision rules, and (3) the controller part is given by a control law. The observer part generates, on the basis of the system output and the control actions, an estimate of the state of the system and its associated variance. The outputs of the observer part are then used by the decision-making part to determine the instants in time of the observation actions on the one hand and the controls actions on the other. The controller part makes use of the estimated state to derive the amplitude(s) of the control action(s).

  14. The Application of Modified Normalized Difference Water Index (MNDWI) by Leaf Area Index in the Retrieval of Regional Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Zhang, H.-w.; Chen, H.-l.

    2015-04-01

    The vegetation coverage is one of the important factors that restrict the accuracy of remote sensing retrieval of soil moisture. In order to effectively improve the accuracy of the remote sensing retrieval of soil moisture and to reduce the impact of vegetation coverage variation on the retrieval accuracy, the Leaf Area Index (LAI) is introduced to the Normalized Difference Water Index (NDWI) to greatly improve the accuracy of the soil moisture retrieval. In its application on the regional drought monitoring, the paper uses the relative LAI from two places which locate in the north and south of Henan Province respectively (Xin Xiang and Zhu Ma Dian) as indicators. It uses the days after turned-green stage to conduct difference value correction on the Relative Leaf Area Index (RLAL) of the entire province, so as to acquire the distribution of RLAI of the province's wheat producing area. After this, the local remote sensing NDWI will be Modified (MNDWI = NDWI xRLAI ) to acquire the soil moisture distribution status of the entire province's wheat producing area. The result shows that, the Modified Normalized Difference Water Index of LAI which based on the days after turned-green stage can improve the real time retrieval accuracy of soil moisture under different vegetation coverage.

  15. Environment and response monitoring on tension leg platforms: Decision support, risk reduction and design data gathering

    SciTech Connect

    Edwards, R.Y. Jr.; Leggelo, B. van; Rubin, S.; Ozakcay, L.

    1995-05-01

    The various roles which instrumentation/monitoring systems play in risk reduction, decision support, forensic engineering and enhancement of the engineering design tools are discussed. The environment and response monitoring systems on three recent Tension Leg Platforms are described. Emphasis is placed on tendon tension measuring systems. A discussion of alternate approaches to the measurement of tendon tension is offered. Suggestions for improved instrumentation are made and methods for efficiently mating performance and environment monitoring systems with the platforms` SCADA Systems are discussed.

  16. 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

  17. Tolkku - a toolbox for decision support from condition monitoring data

    NASA Astrophysics Data System (ADS)

    Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo

    2012-05-01

    This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.

  18. 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

  19. Evaluation of soil moisture and Palmer Drought Severity Index in Brazil

    NASA Astrophysics Data System (ADS)

    Rossato, Luciana; Antônio Marengo, José; Bassi Marinho Pires, Luciana

    2016-04-01

    Soil moisture is one of the main factors for the study of drought, climate and vegetation. In the case of drought, this is a regional phenomenon and affects food security more than any other natural disaster. Therefore, monitoring of different types of drought has been based on indexes that standardize on temporal and spatial scales. Currently, the monitoring of different types of drought is based on indexes that attempt to encapsulate on temporal and regional levels allowing thereby the comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, the Palmer Drought Severity Index was estimated for the entire Brazilian territory, using meteorological (precipitation and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil) data. The data field capacity and permanent wilting point were obtained from the physical properties of the soil, while the water storage in the soil was calculated considering the water balance model. Analyses were made for the years 2000 through 2014, which includes periods with and without occurrence of drought, respectively. The results showed that the PDSI had higher negative indices for the years 2003 and 2012 in Brazil's Northeast region, and this region was strongly affected by drought during those years. These indices can serve as a basis for assessing future drought projections, considering different scenarios. The results also show that soil moisture constitutes one of the limiting factors for obtaining high agricultural productivity, in order to reduce the effects caused by drought. Therefore, these indices can serve as a basis for assessing future drought projections, considering different scenarios. It would be desirable to assist decision makers in action plans with more effective strategies, allowing farmers to live with drought without losing their livelihood.

  20. Evaluation of Soil Moisture and Palmer Drought Severity Index in Brazil

    NASA Astrophysics Data System (ADS)

    Rossato, L.

    2015-12-01

    Soil moisture is one of the main factors for the study of drought, climate and vegetation. In the case of drought, this is a regional phenomenon and affects food security more than any other natural disaster. Therefore, monitoring of different types of drought has been based on indexes that standardize on temporal and spatial scales. Currently, the monitoring of different types of drought is based on indexes that attempt to encapsulate on temporal and regional levels allowing thereby the comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, the Palmer Drought Severity Index (PDSI) was estimated for the entire Brazilian territory, using meteorological (precipitation and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil) data. The data field capacity and permanent wilting point were obtained from the physical properties of the soil, while the water storage in the soil was calculated considering the water balance model. Analyses were made for the years 2000 through 2014, which includes periods with and without occurrence of drought, respectively. The results showed that the PDSI had higher negative indices for the years 2003, 2012, 2013 and 2014 in Brazil's Northeast region, and this region was strongly affected by drought during those years. These indices can serve as a basis for assessing future drought projections, considering different scenarios. The results also show that soil moisture constitutes one of the limiting factors for obtaining high agricultural productivity, in order to reduce the effects caused by drought. Therefore, these indices can serve as a basis for assessing future drought projections, considering different scenarios. It would be desirable to assist decision makers in action plans with more effective strategies, allowing farmers to live with drought without losing their livelihood.

  1. 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.

  2. 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

    2016-01-01

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

  3. 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.

  4. 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

  5. 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

  6. Knowledge-based decision support for patient monitoring in cardioanesthesia.

    PubMed

    Schecke, T; Langen, M; Popp, H J; Rau, G; Käsmacher, H; Kalff, G

    1992-01-01

    An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia. PMID:1402299

  7. Combined monitoring, decision and control model for the human operator in a command and control desk

    NASA Technical Reports Server (NTRS)

    Muralidharan, R.; Baron, S.

    1978-01-01

    A report is given on the ongoing efforts to mode the human operator in the context of the task during the enroute/return phases in the ground based control of multiple flights of remotely piloted vehicles (RPV). The approach employed here uses models that have their analytical bases in control theory and in statistical estimation and decision theory. In particular, it draws heavily on the modes and the concepts of the optimal control model (OCM) of the human operator. The OCM is being extended into a combined monitoring, decision, and control model (DEMON) of the human operator by infusing decision theoretic notions that make it suitable for application to problems in which human control actions are infrequent and in which monitoring and decision-making are the operator's main activities. Some results obtained with a specialized version of DEMON for the RPV control problem are included.

  8. Tablet-based patient monitoring and decision support systems in hospital care.

    PubMed

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  9. Assessing potential of vertical average soil moisture (0-40cm) estimation for drought monitoring using MODIS data: a case study

    NASA Astrophysics Data System (ADS)

    Ma, Jianwei; Huang, Shifeng; Li, Jiren; Li, Xiaotao; Song, Xiaoning; Leng, Pei; Sun, Yayong

    2015-12-01

    Soil moisture is an important parameter in the research of hydrology, agriculture, and meteorology. The present study is designed to produce a near real time soil moisture estimation algorithm by linking optical/IR measurements to ground measured soil moisture, and then used to monitoring region drought. It has been found that the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) are related to surface soil moisture. Therefore, a relationship between ground measurement soil moisture and NDVI and LST can be developed. Six days' NDVI and LST data calculated from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) of Shandong province during October in 2009 to May in 2010 were combined with ground measured volumetric soil moisture in different depth (10cm, 20cm, 40cm, and mean in vertical (0-40cm)) and different soil type to determine regression relationships at a 1 km scale. Based on the regression relationships, mean volumetric soil moisture in vertical (0-40cm) at 1 km resolution can be calculated over the Shandong province, and then drought maps were obtained. The result shows that significantly relationship exists between the NDVI and LST and soil moisture at different soil depths, and regression relationships are soil type dependent. What is more, the drought monitoring results agree well with actual situation.

  10. Drought description

    USGS Publications Warehouse

    Matalas, N.C.

    1991-01-01

    What constitutes a comprehensive description of drought, a description forming a basis for answering why a drought occurred is outlined. The description entails two aspects that are "naturally" coupled, named physical and economic, and treats the set of hydrologic measures of droughts in terms of their multivariate distribution, rather than in terms of a collection of the marginal distributions. ?? 1991 Springer-Verlag.

  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. Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

    NASA Technical Reports Server (NTRS)

    Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

    2010-01-01

    Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

  13. Application of MODIS time series data for drought assessment in East China

    NASA Astrophysics Data System (ADS)

    Liu, Chaoshun; Shi, Runhe; Gao, Wei; Gao, Zhiqiang

    2010-08-01

    Drought is one of the major environmental disasters in China, so it is very important to detect and monitor drought periodically at large scale for decision making. This study focuses on combining information from visible, near infrared, and short wave infrared channels of MODIS to improve sensitivity to drought severity. Significant correlations have been found between NDVI/NMDI values and precipitation/soil moisture data in individual stations. It was confirmed that both NDVI and NMDI indices could be used to monitor drought in the study area at a regional scale. However, NMDI had a slightly higher correlation with soil moisture or precipitation than NDVI, which suggests that NMDI variations can be a good indicator of water changes and in turn, the drought conditions in individual stations in the study area. Results from analysis of time series NDVI and NDWI data over the study area also indicate that NMDI was more sensitive than NDVI to drought conditions. Future efforts are being need to more fully exploit the potential of NMDI as an active drought-monitoring tool for different geographic regions, climates, and multiple spatial scales.

  14. The Development of a Web-service-based On-demand Global Agriculture Drought Information System

    NASA Astrophysics Data System (ADS)

    Deng, M.; Di, L.; Han, W.; Yagci, A.; Peng, C.

    2011-12-01

    The growing demand on detailed and accurate assessments of agriculture drought from local to global scales has made drought monitoring and forecasting a hot research topic in recent years. However, many challenges in this area still remain. One of such challenges is to how to let world-wide decision makers obtain accurate and timely drought information. Current agriculture drought information systems in the world are limited in many aspects, such as only regional or country level coverage, very coarse spatial and temporal resolutions, no on-demand drought information product generation and download services, no online analysis tools, no interoperability with other systems, and ineffective agriculture drought monitoring and forecasting. Leveraging the latest advances in geospatial Web service, interoperability and cyber-infrastructure technologies and the availability of near real-time global remote sensing data, we aims at providing a solution to those problems by building an open, interoperable, standard-compliant, and Web-service-based global agriculture drought monitoring and forecasting system (GADMFS) (http://gis.csiss.gmu.edu/GADMFS/). GADMFS will provide world-wide users with timely, on-demand, and ready-to-use agricultural drought data and information products as well as improved global agriculture drought monitoring, prediction and analysis services. For the monitoring purpose, the system lively links to near real-time satellite remote sensing data sources from NASA and NOAA and relies on drought related remotely sensed physical and biophysical parameters, such as soil moisture and drought-related vegetation indices (VIs, e.g., NDVI) to provide the current conditions of global agricultural drought at high resolutions (up to 500m spatial and daily temporal) to world-wide users on demand. For drought prediction, the system utilizes a neural network based modeling algorithm, trained with current and historic vegetation-based and climate-based drought index

  15. 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.

  16. Integrating TRMM and MODIS satellite with socio-economic vulnerability for monitoring drought risk over a tropical region of India

    NASA Astrophysics Data System (ADS)

    Yaduvanshi, Aradhana; Srivastava, Prashant K.; Pandey, A. C.

    Drought is a recurring feature of the climate, responsible for social and economic losses in India. In the present work, attempts were made to estimate the drought hazard and risk using spatial and temporal datasets of Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS) in integration with socio-economic vulnerability. The TRMM rainfall was taken into account for trend analysis and Standardized Precipitation Index (SPI) estimation, with aim to investigate the changes in rainfall and deducing its pattern over the area. The SPI and average rainfall data derived from TRMM were interpolated to obtain the spatial and temporal pattern over the entire South Bihar of India, while the MODIS datasets were used to derive the Normalized Difference Vegetation Index (NDVI) deviation in the area. The Geographical Information System (GIS) is taken into account to integrate the drought vulnerability and hazard, in order to estimate the drought risk over entire South Bihar. The results indicated that approximately 36.90% area is facing high to very high drought risk over north-eastern and western part of South Bihar and need conservation measurements to combat this disaster.

  17. Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data

    NASA Astrophysics Data System (ADS)

    Bhuiyan, C.; Singh, R. P.; Kogan, F. N.

    2006-12-01

    The hard-rock hilly Aravalli terrain of Rajasthan province of India suffers with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. In the present study, detailed analysis of meteorological and hydrological data of the Aravalli region has been carried out for the years 1984-2003. Standardised Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardised Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) and Vegetation Health Index (VHI) have been computed using NDVI values obtained from Global Vegetation Index (GVI) and thermal channel data of NOAA AVHRR satellite. Detailed analyses of spatial and temporal drought dynamics during monsoon and non-monsoon seasons have been carried out through drought index maps generated in Geographic Information Systems (GIS) environment. Analysis and interpretation of these maps reveal that negative SPI anomalies not always correspond to drought. In the Aravalli region, aquifer-stress shifts its position time to time, and in certain pockets it is more frequent. In comparison to hydrological stress, vegetative stress in the Aravalli region is found to be slower to begin but quicker to withdraw.

  18. Attributing a Value Onto Groundwater Resources: The Impact of Environmental Cost on Monitoring Decisions

    NASA Astrophysics Data System (ADS)

    Paleologos, E.

    2009-04-01

    European and U.S. regulations mandate a minimum number of wells in order to monitor for groundwater pollution from landfills. The optimum number and location of a network of wells is assessed by conducting numerical flow and transport simulations, which account for the heterogeneity of aquifers, and a decision-making analysis, which accounts for the probability of failure, the cost of monitoring measures, and the cost of remediation. An optimal monitoring network seeks to maximize the probability of detection, minimize the extent of polluted area, and minimize the cost of a system. The current work focuses on the decision-making part and specifically on the impact of the environmental cost on the selection of an optimal network. The results of a stochastic analysis by Yenigul et al. are utilized to determine the optimal configuration of wells subject to the above three objectives. When the standard practice is followed to set the remediation cost as a substitute of the environmental cost the optimal decision on monitoring network coincides with the minimum-mandated number of wells. A broader definition of environmental cost is proposed here that considers that the full value of groundwater resources is not recovered after remediation. The lost value of groundwater is defined as the value change from drinking water, before a pollution event, to irrigation water, which is returned after remediation. When this expanded notion of environmental cost is utilized higher monitoring standards are seen to be optimal.

  19. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    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. PMID:26610496

  20. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    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. PMID:26610496

  1. Uncertainty in drought monitoring by the Standardized Precipitation Index: the case study of the Abruzzo region (central Italy)

    NASA Astrophysics Data System (ADS)

    Vergni, L.; Di Lena, B.; Todisco, F.; Mannocchi, F.

    2015-12-01

    As shown by several authors, drought monitoring by the Standardized Precipitation Index (SPI) presents some uncertainties, mainly dependent on the choice of the probability distribution used to describe the cumulative precipitation and on the characteristics (e.g., length and variability) of the dataset. In this paper, the uncertainty related to SPI estimates has been quantified and analyzed with regards to the case study of the Abruzzo region (Central Italy), by using monthly precipitation recorded at 75 stations during the period 1951-2009. First, a set of distributions suitable to describe the cumulative precipitation at the 3-, 6-, and 12-month time scales was identified by using L-moments ratio diagrams. The goodness-of-fit was evaluated by applying the Kolmogorov-Smirnov test, and the Normality test on the derived SPI series. Then the confidence intervals of SPI have been calculated by applying a bootstrap procedure. The size of the confidence intervals has been considered as a measure of uncertainty, and its dependence on several factors such as the distribution type, the time scale, the record length, and the season has been examined. Results show that the distributions Pearson type III (PE3), Weibull (WEI), Generalized Normal (GNO), Generalized Extreme Value (GEV), and Gamma (GA2) are all suitable to describe the cumulative precipitation, with a slightly better performance of the PE3 and GNO distributions. As expected, the uncertainty increases as the record length and time scale decrease. The leading source of uncertainty is the record length while the effects due to seasonality and time scale are negligible. Two-parameter distributions make it possible to obtain confidence intervals of SPI (particularly for extreme values) narrower than those obtained by three-parameter distributions. Nevertheless, due to a poorer goodness of fit, two-parameter distributions can provide less reliable estimates of the precipitation probability. In any event, independently

  2. Remote sensing of drought: progress, challenges and opportunities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This review surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. We argue that satellite observations not currently used for operational drought monitoring, such as relative humidity data from the Atmos...

  3. Probabilistic drought classification using gamma mixture models

    NASA Astrophysics Data System (ADS)

    Mallya, Ganeshchandra; Tripathi, Shivam; Govindaraju, Rao S.

    2015-07-01

    Drought severity is commonly reported using drought classes obtained by assigning pre-defined thresholds on drought indices. Current drought classification methods ignore modeling uncertainties and provide discrete drought classification. However, the users of drought classification are often interested in knowing inherent uncertainties in classification so that they can make informed decisions. Recent studies have used hidden Markov models (HMM) for quantifying uncertainties in drought classification. The HMM method conceptualizes drought classes as distinct hydrological states that are not observed (hidden) but affect observed hydrological variables. The number of drought classes or hidden states in the model is pre-specified, which can sometimes result in model over-specification problem. This study proposes an alternate method for probabilistic drought classification where the number of states in the model is determined by the data. The proposed method adapts Standard Precipitation Index (SPI) methodology of drought classification by employing gamma mixture model (Gamma-MM) in a Bayesian framework. The method alleviates the problem of choosing a suitable distribution for fitting data in SPI analysis, quantifies modeling uncertainties, and propagates them for probabilistic drought classification. The method is tested on rainfall data over India. Comparison of the results with standard SPI show important differences particularly when SPI assumptions on data distribution are violated. Further, the new method is simpler and more parsimonious than HMM based drought classification method and can be a viable alternative for probabilistic drought classification.

  4. Monitoring Ecosystem Carbon and Water Variations During a Severe Drought in the Southwest With AVIRIS and MODIS Sensor Data.

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Huete, A. R.; Didan, K.; Cobb, N.; Koch, G.

    2004-12-01

    We investigated the spatial and temporal variations in vegetation biologic activity across a wide range of ecosystems (desert shrub to conifer forest) in northern Arizona with carbon and water indices derived from fine resolution AVIRIS data and moderate resolution MODIS observations. Leaf level and canopy level surface moisture indices were computed over the range of ecosystems and drought-induced mortality sites with hyperspectral AVIRIS data in the 1240nm and 2100nm water absorption regions. The land surface moisture indices were combined with the vegetation index, carbon measures to map spatial and temporal patterns of above-ground net productivity and analyze ecosystem sensitivity to water availability and precipitation. The coupled water and carbon indices were scaled up to MODIS data for spatial extension and time series analysis over the past 5 years. Land surface moisture and carbon patterns behaved differently across the range of ecosystems and within drought impact sites. Drought impacts were observed in all ecosystems, particularly in tree mortality areas and the grassland and desert areas. Our results show that combined water and carbon indices offer improved sensitivity to ecosystem health assessment and drought detection and analysis. Remotely-sensed land surface water indices combined with the carbon products yielded important information useful in the prediction of vegetation health response to climate change and human land cover modifications.

  5. 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

  6. 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.

  7. Development of a decision-making methodology to design a water quality monitoring network.

    PubMed

    Keum, Jongho; Kaluarachchi, Jagath J

    2015-07-01

    The number of water quality monitoring stations in the USA has decreased over the past few decades. Scarcity of observations can easily produce prediction uncertainty due to unreliable model calibration. An effective water quality monitoring network is important not only for model calibration and water quality prediction but also for resources management. Redundant or improperly located monitoring stations may cause increased monitoring costs without improvement to the understanding of water quality in watersheds. In this work, a decision-making methodology is proposed to design a water quality monitoring network by providing an adequate number of monitoring stations and their approximate locations at the eight-digit hydrologic unit codes (HUC8) scale. The proposed methodology is demonstrated for an example at the Upper Colorado River Basin (UCRB), where salinity is a serious concern. The level of monitoring redundancy or scarcity is defined by an index, station ratio (SR), which represents a monitoring density based on water quality load originated within a subbasin. By comparing the number of stations from a selected target SR with the available number of stations including the actual and the potential stations, the suggested number of stations in each subbasin was decided. If monitoring stations are primarily located in the low salinity loading subbasins, the average actual SR tends to increase, and vice versa. Results indicate that the spatial distribution of monitoring locations in 2011 is concentrated on low salinity loading subbasins, and therefore, additional monitoring is required for the high salinity loading subbasins. The proposed methodology shows that the SR is a simple and a practical indicator for monitoring density. PMID:26113203

  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. Drought tolerance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought stress is a major limiting factor to crop yields, even in sub-humid regions like the Missouri Bootheel. Due to common factors such as soils with low available water holding capacities, even short-term drought can impact yield leading producers of rainfed crops to convert to irrigated product...

  10. Role of memory strength in reality monitoring decisions: evidence from source attribution biases.

    PubMed

    Hoffman, H G

    1997-03-01

    Reality monitoring of verbal memories was compared with decisions about pictorial memories in this study. Experiment 1 showed an advantage in memory for imagined over perceived words and a bias to respond "perceived" on false alarms. Experiment 2 showed the opposite pattern: an advantage in memory for perceived pictures and a bias to respond "imagined" on false alarms. Participants attribute false alarms to whichever class of memories has the weakest trace strengths. The relative strength of memories of imagined and perceived objects was manipulated in Experiments 3 and 4, yielding changes in source attribution biases that were predicted by the strength heuristic. All 4 experiments generalize the mirror effect (an inverse relationship between patterns of hits and false alarms commonly found on recognition tests) to reality monitoring decisions. Results suggest that under some conditions differences between the strength of memories for perceived and imagined events, rather than differences in qualitative characteristics, are used to infer memory source. PMID:9080009

  11. Building Decision Trees for Characteristic Ellipsoid Method to Monitor Power System Transient Behaviors

    SciTech Connect

    Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.; Etingov, Pavel V.; Zhou, Ning; Dagle, Jeffery E.

    2010-12-01

    The characteristic ellipsoid is a new method to monitor the dynamics of power systems. Decision trees (DTs) play an important role in applying the characteristic ellipsoid method to system operation and analysis. This paper presents the idea and initial results of building DTs for detecting transient dynamic events using the characteristic ellipsoid method. The objective is to determine fault types, fault locations and clearance time in the system using decision trees based on ellipsoids of system transient responses. The New England 10-machine 39-bus system is used for running dynamic simulations to generate a sufficiently large number of transient events in different system configurations. Comprehensive transient simulations considering three fault types, two fault clearance times and different fault locations were conducted in the study. Bus voltage magnitudes and monitored reactive and active power flows are recorded as the phasor measurements to calculate characteristic ellipsoids whose volume, eccentricity, center and projection of the longest axis are used as indices to build decision trees. The DT performances are tested and compared by considering different sets of PMU locations. The proposed method demonstrates that the characteristic ellipsoid method is a very efficient and promising tool to monitor power system dynamic behaviors.

  12. Model-driven decision support for monitoring network design: methods and applications

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D. R.; Mishra, P. K.; Katzman, D.

    2012-12-01

    A crucial aspect of any decision-making process for environmental management of contaminated sites and protection of groundwater resources is the identification of scientifically defensible remediation scenarios. The selected scenarios are ranked based on both their protective and cost effectiveness. The decision-making process is facilitated by implementation of site-specific data- and model-driven analyses for decision support (DS) taking into account existing uncertainties to evaluate alternative characterization and remedial activities. However, due to lack of data and/or complex interdependent uncertainties (conceptual elements, model parameters, measurement/computational errors, etc.), the DS optimization problem is ill posed (non unique) and the model-prediction uncertainties are difficult to quantify. Recently, we have developed and implemented several novel theoretical approaches and computational algorithms for model-driven decision support. New and existing DS tools have been employed for model analyses of the fate and extent of a chromium plume in the regional aquifer at Sandia Canyon Site, LANL. Since 2007, we have performed three iterations of DS analyses implementing different models, decision-making tools, and data sets providing guidance on design of a subsurface monitoring network for (1) characterization of the flow and transports processes, and (2) protection of the water users. The monitoring network is augmented by new wells at locations where acquired new data can effectively reduce uncertainty in model predicted contaminant concentrations. A key component of the DS analyses is contaminant source identification. Due to data and conceptual uncertainties, subsurface processes controlling the contaminant arrival at the top of the regional aquifer are not well defined. Nevertheless, the model-based analyses of the existing data and conceptual knowledge, including respective uncertainties, provide constrained probabilistic estimates of the

  13. Efficiency evaluation of a groundwater monitoring network using a risk-based decision- support process

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Birdsell, K.; Davis, P.; Echohawk, C.

    2006-12-01

    Efficiency evaluation of a groundwater monitoring network using a risk-based decision-support process Velimir V Vesselinov, Kay Birdsell, Paul David, Chris Echohawk A series of contaminant sources have the potential to impact the quality of regional groundwater resources beneath the Los Alamos National Laboratory (LANL). Currently, 21 areas have been identified where contaminants could possibly reach the regional aquifer at the water table. Because the temporal variability of the contaminant mass fluxes through the vadose zone is not well defined, source strength uncertainty at the regional aquifer is represented by a series of unit-mass source functions. Uncertainties in the potential contaminant pathways within the aquifer and the breakthrough curves at the potential discharge locations (receptors), which include water-supply wells and springs, are investigated. Risk-based analyses of the performance of the existing groundwater monitoring network are carried out. The network should be capable of detecting the potential contaminant plumes before they reach (1) the receptors and/or (2) the LANL boundaries at unacceptably high concentrations. Individual monitoring boreholes are ranked based on their importance for plume detection. Suggestions regarding optimal sampling frequency for the monitoring boreholes are also made. The study utilizes a risk-based decision-support process. The goal is to facilitate the decision process by means of risk-based analyses of model predictions that incorporate current data and conceptual understandings. The most important question is whether the existing knowledge is adequate and sufficient for each particular contamination source / pathway in order to select a remedy(ies) now without any further characterization. The immediate evaluation of remedy options can help prioritize our efforts and reduce the time to completion and cost of the LANL environmental program. Our study addresses fundamental questions related to building

  14. 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

  15. 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.

  16. The Ebb and Flow of Airborne Pathogens: Monitoring and Use in Disease Management Decisions.

    PubMed

    Mahaffee, Walter F; Stoll, Rob

    2016-05-01

    Perhaps the earliest form of monitoring the regional spread of plant disease was a group of growers gathering together at the market and discussing what they see in their crops. This type of reporting continues to this day through regional extension blogs, by crop consultants and more formal scouting of sentential plots in the IPM PIPE network (http://www.ipmpipe.org/). As our knowledge of plant disease epidemiology has increased, we have also increased our ability to detect and monitor the presence of pathogens and use this information to make management decisions in commercial production systems. The advent of phylogenetics, next-generation sequencing, and nucleic acid amplification technologies has allowed for development of sensitive and accurate assays for pathogen inoculum detection and quantification. The application of these tools is beginning to change how we manage diseases with airborne inoculum by allowing for the detection of pathogen movement instead of assuming it and by targeting management strategies to the early phases of the epidemic development when there is the greatest opportunity to reduce the rate of disease development. While there are numerous advantages to using data on inoculum presence to aid management decisions, there are limitations in what the data represent that are often unrecognized. In addition, our understanding of where and how to effectively monitor airborne inoculum is limited. There is a strong need to improve our knowledge of the mechanisms that influence inoculum dispersion across scales as particles move from leaf to leaf, and everything in between. PMID:27003505

  17. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    PubMed Central

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2°C) in the Salt Lake Basin area during the 28-year period (1984–2011). Analysis of air temperature data also showed increases at a rate of 1.5–2°C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin. PMID:24587709

  18. In-situ monitoring of California's drought: Impacts on key hydrologic variables in the Southern Sierra Nevada

    NASA Astrophysics Data System (ADS)

    Oroza, C.; Zheng, Z.; Zhang, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

    2015-12-01

    Like many semi-arid regions, California relies on seasonal snowmelt from the Sierra Nevada mountain range to provide freshwater allocations for multiple stakeholders throughout the year. The magnitude and timing of runoff from these regions is being altered by consecutive years of drought, affecting downstream ecosystems, hydropower operations, and deliveries to agriculture and urban water users. Understanding the long-term effect of drought on the montane water balance requires temporally continuous, in-situ measurements of key hydrologic variables across large spatial domains. We discuss a seven-year dataset from the Southern Sierra Critical Zone Observatory, which includes co-located measurements of snowpack, soil moisture, and soil temperature in the Kings River watershed. We investigate how these key hydrologic variables are affected as the region transitions from winters that have nearly continuous snow cover (2008-2011) to winters with extended snow-on, snow-off periods (2012-2014). For water year 2014, we observe a 93% decline in average snowpack, a 35% decline in average soil moisture, and a 25% increase in average soil temperature compared to a wet-year index of each variable. We discuss the effect of physiographic features, including slope, aspect, elevation, and canopy coverage on the changes observed in each variable. Finally, we use sparse inverse covariance estimation to investigate the changing conditional relationships throughout the observatory in wet and dry years.

  19. Use of Landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey.

    PubMed

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2°C) in the Salt Lake Basin area during the 28-year period (1984-2011). Analysis of air temperature data also showed increases at a rate of 1.5-2°C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin. PMID:24587709

  20. Operationalizing crop monitoring system for informed decision making related to food security in Nepal

    NASA Astrophysics Data System (ADS)

    Qamer, F. M.; Shah, S. N. Pd.; Murthy, M. S. R.; Baidar, T.; Dhonju, K.; Hari, B. G.

    2014-11-01

    In Nepal, two thirds of the total population depend on agriculture for their livelihoods and more than one third of Gross Domestic Product (GDP) comes from the agriculture sector. However, effective agriculture production across the country remains a serious challenge due to various factors, such as a high degree of spatial and temporal climate variability, irrigated and rain-fed agriculture systems, farmers' fragile social and economic fabric, and unique mountain practices. ICIMOD through SERVIR-Himalaya initiative with collaboration of Ministry of Agricultural Development (MoAD) is working on developing a comprehensive crop monitoring system which aims to provide timely information on crop growth and drought development conditions. This system analyzes historical climate and crop conditions patterns and compares this data with the current growing season to provide timely assessment of crop growth. Using remote sensing data for vegetation indices, temperature and rainfall, the system generated anomaly maps are inferred to predict the increase or shortfall in production. Comparisons can be made both spatially and in graphs and figures at district and Village Developmental Committee (VDC) levels. Timely information on possible anomaly in crop production is later used by the institutions like Ministry of Agricultural Development, Nepal and World Food Programme, Nepal to trigger appropriate management response. Future potential includes integrating data on agricultural inputs, socioeconomics, demographics, and transportation to holistically assess food security in the region served by SERVIR-Himalaya.

  1. Accesible hydrological monitoring for better decision making and modelling: a regional initiative in the Andes

    NASA Astrophysics Data System (ADS)

    De Bievre, B.; Célleri, R.; Crespo, P.; Ochoa, B.; Buytaert, W.; Tobón, C.; Villacís, M.; Villazon, M. F.; Llerena, C.; Rodriguez, M.; Viñas, P.

    2013-05-01

    The goal of the Hydrological Monitoring of Andean Ecosystems Initiative is to improve the conservation and management of High-Andean ecosystems by providing information on the hydrological response of these ecosystems and how different land-uses affect their water yield and regulation capacity. The initiative fills a gap left by widespread hydrological modeling exercises that suffer from lack of data, and by glacier monitoring under climate change. The initiative proposes a hydrological monitoring system involving precipitation, discharge and land cover monitoring in paired catchments. The methodology is accessible for non-specialist organizations, and allows for generation of evidence of land use impact on hydrology on the short term (i.e. a few years). Nevertheless, long term monitoring is pursued with the aim of identifying trends in hydrological response (as opposed to trends in climate) under global change. In this way it supports decision making on the preservation of the hydrological services of the catchment. The initiative aims at a high number of paired catchment sites along the Andes, in order to draw regional conclusions and capture variability, and is connected to more detailed hydrological research sites of several Andean universities. We present preliminary results of a dozen of sites from Venezuela to Bolivia, summarized in hydrological performance indicators that were agreed upon among hydrologists, local stakeholders, and water authorities. The success factors, as well as limitations, of the network are discussed.

  2. A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

    NASA Astrophysics Data System (ADS)

    di, L.; Yang, Z.

    2009-12-01

    Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the

  3. 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

  4. Drought in the Anthropocene

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    Drought management is inefficient because feedbacks between drought and people are not fully understood. In this human-influenced era, we need to rethink the concept of drought to include the human role in mitigating and enhancing drought.

  5. Monitoring and Assessment Science to Support Decision-Making by the United Nations Convention to Combat Desertification (UNCCD)

    NASA Astrophysics Data System (ADS)

    Winslow, M.; Akhtar-Schuster, M.; Cherlet, M.; Martius, C.; Sommer, S.; Thomas, R.; Vogt, J.

    2009-12-01

    The United Nations Convention to Combat Desertification (UNCCD) is a global treaty that emerged from the Rio Earth Summit and formally took force in 1996. It has now been ratified by 193 countries (known as Parties to the Convention). Yet the UNCCD has gained only modest support from donors, largely due to questions about the science base underlying its target issue (desertification) resulting in ambiguous definitions and quantification of the problem. The UNCCD recognizes the need to reform itself and commissioned a scientific conference in Buenos Aires, Argentina in September 2009 to discuss ways to improve the scientific underpinning of monitoring and assessment (M&A) of desertification, land degradation and drought (DLDD). Previous attempts by the UNCCD on M&A focused largely on a search for a common, simple, universal set of indicators that could be reported by country Parties to the Convention Secretariat, which would collate them into a global report. However experience found that no single set of indicators is satisfactory to all countries, because DLDD depends strongly on the local environmental and human/social context. Three preparatory Working Groups analyzed the issue of DLDD M&A and recommended the following. Parties should recognize that M&A methods must integrate human-environment parameters to capture the complexity of DLDD phenomena as defined in the Convention’s text. Traditional tendencies had been to isolate biophysical from social and economic parameters, leading to unrealistic conclusions. Parties should take advantage of a much wider range of analytical techniques than just the coarse-scale indicators that had been their main focus to date. Powerful but underutilized techniques include integrated assessment models, remote sensing, geographic information systems and mapping, participatory stakeholder assessment, hierarchical aggregation of related data, knowledge management and many others. Multiple methods could provide validation checks

  6. Sexism and beautyism effects in selection as a function of self-monitoring level of decision maker.

    PubMed

    Jawahar, I M; Mattsson, Jonny

    2005-05-01

    The authors, in two experiments, investigated the influence of the sex and attractiveness of applicants for male and female sex-typed jobs on selection decisions made by low and high self-monitors. In both experiments, attractiveness and the congruence between applicants' sex and the sex type of the job influenced selection decisions. In addition, high self-monitors were more influenced by attractiveness and sex of the applicant when hiring for sex-typed jobs than low self-monitors, but this difference in hiring pattern was not evident when the job was gender neutral. Results indicate that job applicants may encounter different employment opportunities as a function of their sex, their physical attractiveness, the sex type of the job, and the self-monitoring level of the decision maker. Implications of results are discussed and suggestions for future research are offered. PMID:15910150

  7. Anchor effects in decision making can be reduced by the interaction between goal monitoring and the level of the decision maker's executive functions.

    PubMed

    Schiebener, Johannes; Wegmann, Elisa; Pawlikowski, Mirko; Brand, Matthias

    2012-11-01

    Models of decision making postulate that interactions between contextual conditions and characteristics of the decision maker determine decision-making performance. We tested this assumption by using a possible positive contextual influence (goals) and a possible negative contextual influence (anchor) in a risky decision-making task (Game of Dice Task, GDT). In this task, making advantageous choices is well known to be closely related to a specific decision maker variable: the individual level of executive functions. One hundred subjects played the GDT in one of four conditions: with self-set goal for final balance (n = 25), with presentation of an anchor (a fictitious Top 10 list, showing high gains of other participants; n = 25), with anchor and goal definition (n = 25), and with neither anchor nor goal setting (n = 25). Subjects in the conditions with anchor made more risky decisions irrespective of the negative feedback, but this anchor effect was influenced by goal monitoring and moderated by the level of the subjects' executive functions. The findings imply that impacts of situational influences on decision making as they frequently occur in real life depend upon the individual's cognitive abilities. Anchor effects can be overcome by subjects with good cognitive abilities. PMID:22915277

  8. Managing the risk of agricultural drought in Africa

    NASA Astrophysics Data System (ADS)

    Quaife, T. L.; Black, E.; Brown, M.; Greatrex, H.; Maidment, R.; Mookerjee, A.; Tarnavsky, E.

    2015-12-01

    Farmers in Africa are highly vulnerable to variability in the weather - especially to drought. Robust and timely information on drought risk can enable farmers to take action to increase yields. Such information also forms the basis of financial instruments, such as weather index insurance. Monitoring weather conditions is, however, difficult in Africa because of the heteorogeneity of the climate, and the sparcity of the ground-observing network. Remotely sensed data (for example satellite-based rainfall estimates) are an alternative to ground observations - but only if the algorithms have skill and the data are presented in a useful form. A more fundamental issue is that the condition of the land surface is affected by factors other than rainfall. The evolving risk of agricultural drought is thus determined by the properties of the land surface, the contemporaneous soil moisture and the risk of rainfall deficits. We present a prototype agricultural decision support tool, based on the JULES land-surface model, driven with ensembles of meteorological driving data, which encompass the uncertainty in rainfall. We discuss the application of the tool for designing and implementing drought insurance in Ghana and Zambia - illustrated with real examples of weather index insurance schemes that are already active.

  9. Citizen Empowerment in Volcano Monitoring, Communication and Decision-Making at Tungurahua Volcano, Ecuador

    NASA Astrophysics Data System (ADS)

    Bartel, B.; Mothes, P. A.

    2013-05-01

    Trained citizen volunteers called vigías have worked to help monitor and communicate warnings about Tungurahua volcano, in Ecuador, since the volcano reawoke in 1999. The network, organized by the scientists of Ecuacor's Instituto Geofísico de la Escuela Politécnica Nacional (Geophysical Institute) and the personnel from the Secretaría Nacional de Gestión de Riesgos (Risk Management, initially the Civil Defense), has grown to well over 20 observers living around the volcano who communicate regularly via handheld two-way radios. Interviews with participants in 2010 indicate that the network enables direct communication between communities and authorities, engenders trust in scientists and emergency response personnel, builds community, and empowers communities to make decisions in times of crisis.

  10. Citizen empowerment in volcano monitoring, communication and decision-making at Tungurahua volcano, Ecuador

    NASA Astrophysics Data System (ADS)

    Bartel, B. A.; Mothes, P. A.

    2013-12-01

    Trained citizen volunteers called vigías have worked to help monitor and communicate warnings about Tungurahua volcano, in Ecuador, since the volcano reawoke in 1999. The network, organized by the scientists of Ecuador's Instituto Geofísico de la Escuela Politécnica Nacional (Geophysical Institute) and the personnel from the Secretaría Nacional de Gestión de Riesgos (Risk Management, initially the Civil Defense), has grown to more than 20 observers living around the volcano who communicate regularly via handheld two-way radios. Interviews with participants conducted in 2010 indicate that the network enables direct communication between communities and authorities; engenders trust in scientists and emergency response personnel; builds community; and empowers communities to make decisions in times of crisis.

  11. Applications of neural networks to monitoring and decision making in the operation of nuclear power plants

    SciTech Connect

    Uhrig, R.E. Oak Ridge National Lab., TN )

    1990-01-01

    Application of neural networks to monitoring and decision making in the operation of nuclear power plants is being investigated under a US Department of Energy sponsored program at the University of Tennessee. Projects include the feasibility of using neural networks for the following tasks: (1) diagnosing specific abnormal conditions or problems in nuclear power plants, (2) detection of the change of mode of operation of the plant, (3) validating signals coming from detectors, (4) review of noise'' data from TVA's Sequoyah Nuclear Power Plant, and (5) examination of the NRC's database of Letter Event Reports'' for correlation of sequences of events in the reported incidents. Each of these projects and its status are described briefly in this paper. This broad based program has as its objective the definition of the state-of-the-art in using neural networks to enhance the performance of commercial nuclear power plants.

  12. A haptic-inspired audio approach for structural health monitoring decision-making

    NASA Astrophysics Data System (ADS)

    Mao, Zhu; Todd, Michael; Mascareñas, David

    2015-03-01

    Haptics is the field at the interface of human touch (tactile sensation) and classification, whereby tactile feedback is used to train and inform a decision-making process. In structural health monitoring (SHM) applications, haptic devices have been introduced and applied in a simplified laboratory scale scenario, in which nonlinearity, representing the presence of damage, was encoded into a vibratory manual interface. In this paper, the "spirit" of haptics is adopted, but here ultrasonic guided wave scattering information is transformed into audio (rather than tactile) range signals. After sufficient training, the structural damage condition, including occurrence and location, can be identified through the encoded audio waveforms. Different algorithms are employed in this paper to generate the transformed audio signals and the performance of each encoding algorithms is compared, and also compared with standard machine learning classifiers. In the long run, the haptic decision-making is aiming to detect and classify structural damages in a more rigorous environment, and approaching a baseline-free fashion with embedded temperature compensation.

  13. On the utility of in situ soil moisture observations for flash drought early warning in Oklahoma, USA

    NASA Astrophysics Data System (ADS)

    Ford, Trent W.; McRoberts, D. Brent; Quiring, Steven M.; Hall, Ryann E.

    2015-11-01

    Drought early warning systems are a vital component of drought monitoring and require information at submonthly time scales because of the rapidly evolving nature of drought. This study evaluates the utility of in situ soil moisture observations for drought early warning in Oklahoma. Soil moisture was used to identify drought events, and the results were compared with the U.S. Drought Monitor with respect to the identification of drought onset. Soil moisture observations consistently identify rapid-onset (flash) drought events earlier than the U.S. Drought Monitor. Our results show that soil moisture percentiles provide a 2-3 week lead time over the U.S. Drought Monitor based on five flash drought events that occurred in Oklahoma between 2000 and 2013. We conclude that in situ soil moisture observations are an important source of information for early warning of flash drought events in the Oklahoma.

  14. Evaluation of corn genotypes for drought and heat stress tolerance using physiological measurements and a microcontroller-based monitoring system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Moisture deficit accompanied by high temperature are major abiotic stress factors that affect corn production in the southern United States, particularly during the reproductive stage of the plant. In evaluating plants for environmental stress tolerance, it is important to monitor changes in their ...

  15. 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.

  16. Big Data Architectures for Operationalized Seismic and Subsurface Monitoring and Decision Support Workflows

    NASA Astrophysics Data System (ADS)

    Irving, D. H.; Rasheed, M.; Hillman, C.; O'Doherty, N.

    2012-12-01

    Oilfield management is moving to a more operational footing with near-realtime seismic and sensor monitoring governing drilling, fluid injection and hydrocarbon extraction workflows within safety, productivity and profitability constraints. To date, the geoscientific analytical architectures employed are configured for large volumes of data, computational power or analytical latency and compromises in system design must be made to achieve all three aspects. These challenges are encapsulated by the phrase 'Big Data' which has been employed for over a decade in the IT industry to describe the challenges presented by data sets that are too large, volatile and diverse for existing computational architectures and paradigms. We present a data-centric architecture developed to support a geoscientific and geotechnical workflow whereby: ●scientific insight is continuously applied to fresh data ●insights and derived information are incorporated into engineering and operational decisions ●data governance and provenance are routine within a broader data management framework Strategic decision support systems in large infrastructure projects such as oilfields are typically relational data environments; data modelling is pervasive across analytical functions. However, subsurface data and models are typically non-relational (i.e. file-based) in the form of large volumes of seismic imaging data or rapid streams of sensor feeds and are analysed and interpreted using niche applications. The key architectural challenge is to move data and insight from a non-relational to a relational, or structured, data environment for faster and more integrated analytics. We describe how a blend of MapReduce and relational database technologies can be applied in geoscientific decision support, and the strengths and weaknesses of each in such an analytical ecosystem. In addition we discuss hybrid technologies that use aspects of both and translational technologies for moving data and analytics

  17. 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. PMID:27251219

  18. A case study on the early warning of agricultural drought

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyu; Fan, Jinlong; Yang, Xiaoguang; Han, Yinjuan; Wei, Jianguo

    2010-10-01

    In general, agricultural drought always occurs under the circumstance of the comprehensive interactions among the factors of nature, economy and society. The loss due to agricultural drought in China is huge every year. Therefore the timely monitoring of agricultural drought is critical to help reduce the loss. The information of agricultural drought early warning is helpful for local governmental officials and farmers in preparation for coping with the likely happening drought. The paper presents an approach and findings of an early warning of agricultural drought which has been successfully conducted in the semiarid and rainfed farming area in Ningxia autonomous region in the northwest of China.

  19. Evaluation and application of the SPDI-JDI for droughts in Texas, USA

    NASA Astrophysics Data System (ADS)

    Ma, Mingwei; Ren, Liliang; Singh, Vijay P.; Tu, Xinjun; Jiang, Shanhu; Liu, Yi

    2015-02-01

    The lack of a system/model for integration of drought-related information has been an important obstacle in efforts for accurate and reliable drought monitoring and prediction. This study proposes an integrated multivariate standardized drought index (i.e. standardized Palmer drought index-based joint drought index, SPDI-JDI), where the Palmer scheme/model is accepted as a multivariate multi-index conceptual framework that integrates multiple drought-related indicators for characterizing drought. Using the meteorological data of ten climate divisions from Texas, the computed SPDI-JDI index is first compared to various ground observations (e.g. streamflow, lake/reservoir water level, soil moisture content and groundwater level) for the reflection of drought/wetness conditions. Moreover, the SPDI-JDI is also evaluated against Palmer drought indices and US Drought Monitor for drought detection. Results indicate that the SPDI-JDI is in good/acceptable agreements with surface and subsurface water anomalies and performs well with respect to the integrated use of Palmer drought severity index, Palmer modified drought index, Palmer hydrologic drought index and Palmer Z index as well as to the US Drought Monitor observations. Potential implications are that the SPDI-JDI allows for insights into different impacts of drought and leads to high probability of drought detection versus multi-source drought information, implying attractive properties originating from its physically inclusive and multivariate joint probabilistic combined nature.

  20. Decision analyses for optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D.

    2011-12-01

    Model-based decision making related to environmental management problems is a challenging problem. There has been substantial theoretical research and practical applications related to this problem. However, there are very few cases in which the actual decision analyses have been tested in the field to evaluate their adequacy. Over the last several years, we have performed a series of decision analyses to support optimization of a monitoring network at the Los Alamos National Laboratory (LANL) site. The problem deals with contaminant transport in the regional aquifer beneath the LANL site. At three separate stages, the existing monitoring network was augmented based on analyses of the existing uncertainties; in total, five new monitoring wells were proposed. At each stage, the data collected at the new monitoring wells demonstrated the adequacy of the prior uncertainty and decision analyses. The decision analyses required a detailed estimation of uncertainties in model predictions. Various uncertainties, including measurement errors and uncertainties in the conceptualization and model parameters, contributed to the uncertainties in the model predictions. The decision analyses were computationally intensive requiring on the order of one million model simulations; computational efficiency is achieved using (1) high-performance computing (LANL multiprocessor clusters), (2) novel computational techniques for model analysis, and (3) a simple analytical 3D simulator to simulate contaminant transport. Decision support related to optimal design of monitoring networks required optimization of the proposed new monitoring well locations in order to reduce existing model-prediction uncertainties and environmental risk. An important aspect of the analysis is the application of novel techniques for optimization (SQUADS based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods; Vesselinov & Harp, 2011) and uncertainty quantification (ABAGUS: Agent

  1. A love story about forest drought detection: the relationship between MODIS data and Climate time series.

    NASA Astrophysics Data System (ADS)

    Domingo, Cristina; Ninyerola, Miquel; Pons, Xavier; Cristóbal, Jordi

    2015-04-01

    The scientific community recognizes drought as an important phenomenon with important implications over many Social Benefit Areas (SBA) that GEOSS addresses and which impacts need to be managed and assessed through policy decisions. The traditional assessment of drought has been often based on both precipitation shortages and differences between actual and potential evapotranspiration, among others. During the last fifteen years, new advances on drought indices, integrating time-scales and effortless computing, have concluded with many drought indices such the Standardized Precipitation Evapotranspiration Index (SPEI). The SPEI uses precipitation data and potential evapotranspiration to emphasize climatic anomalies along different time frames. However, a non-traditional point of view based not only on climatic variables but also on biological data is evaluated here as an encouraging tool for drought detection analysis. Therefore, the real physiological state of the vegetation will be introduced as a new variable required in order to understand the vulnerabilities of forest ecosystems to drought, considering the existing time lag between meteorological events and biological responses. Invaluable Earth Observation satellites provide the research community with a big data of imagery which processed as a Vegetation Indices (VI) time series, such as Normalized Difference Vegetation Index (NDVI), the Vegetation Condition Index (VCI), the Normalized Difference Water Index (NDWI), the Normalized Difference Drought Index (NDDI) and the Temperature Vegetation Dryness Index (TVDI), offer large possibilities on forest applications. This research is focused on the global affection of droughts on forests given the invaluable ecosystem services they provide to society. In this study remote sensing and climate data to characterize drought on forests, supporting the idea that SPEI and MODIS VI clearly respond to drought situations on forests, is used. Results from the analysis of

  2. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) v2.0 Dataset: 35 year Quasi-Global Precipitation Estimates for Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Peterson, P.; Funk, C. C.; Landsfeld, M. F.; Pedreros, D. H.; Shukla, S.; Husak, G. J.; Harrison, L.; Verdin, J. P.

    2015-12-01

    A high quality, long-term, high-resolution precipitation dataset is a key requirement for supporting drought monitoring and long term trend analysis. In this presentation we introduce a new dataset: the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) v2.0, developed by scientists at the University of California, Santa Barbara and the U.S. Geological Survey Earth Resources Observation and Science Center. This new quasi-global precipitation product is available at daily to seasonal time scales, with a spatial resolution of 0.05°, and a 1981 to near real-time period of record. The three main types of information used in the CHIRPS are: (1) global 0.05° precipitation climatologies, (2) gridded precipitation estimates derived from time-varying cold cloud duration, and (3) in situ precipitation observations. The Climate Hazards Group (CHG) has developed an extensive database of in situ daily, pentadal, and monthly precipitation totals with over a billion daily observations worldwide. A screening procedure was developed to flag and remove potential false zeros from the daily GTS and GSOD data. These potentially spurious data can artificially suppress CHIRPS rainfall totals. Using GPCC v7 as the best-available standard, we compare CHIRPS with ARC2, CFS-Reanalysis, CHIRP, CMORPH, CPC-Unified, ECMWF, PERSIANNE, RFE2, TAMSAT, TRMM-RT7, and TRMM-V7. The CHIRPS is shown to have higher correlation, and lower systematic errors (bias) and mean absolute errors with GPCC v7 than the other datasets. Comparison with independent validation data suggests that the CHIRPS performance is similar to research quality products like the GPCC and GPCP, but with higher resolution and lower latency. We conclude by looking at the change in availability of station data within a monitoring time frame, contrasting countries with and without near real time data.

  3. Ground-water availability in part of the Borough of Carroll Valley, Adams County, Pennsylvania, and the establishment of a drought-monitor well

    USGS Publications Warehouse

    Low, Dennis J.; Conger, Randall W.

    2002-01-01

    Continued population growth in the Borough of Carroll Valley (Borough) coupled with the drought of 2001 have increased the demand for ground water in the Borough. This demand has led Borough officials to undertake an effort to evaluate the capability of the crystalline-bedrock aquifers to meet future, projected growth and to establish a drought-monitor well within and for the use of the Borough. As part of this effort, this report summarizes ground-water data available from selected sections within the Borough and provides geohydrologic information needed to evaluate ground-water availability and recharge sources within part of the Borough. The availability of ground water in the Borough is limited by the physical characteristics of the underlying bedrock, and its upland topographic setting. The crystalline rocks (metabasalt, metarhyolite, greenstone schist) that underlie most of the study area are among the lowest yielding aquifers in the Commonwealth. More than 25 percent of the wells drilled in the metabasalt, the largest bedrock aquifer in the study area, have driller reported yields less than 1.25 gallons per minute. Driller reports indicate also that water-producing zones are shallow and few in number. In general, 50 percent of the water-producing zones reported by drillers are penetrated at depths of 200 feet or less and 90 percent at depths of 370 feet or less. Borehole geophysical data indicate that most of the water-producing zones are at lithologic contacts, but such contacts are penetrated infrequently and commonly do not intersect areas of ground-water recharge. Single-well aquifer tests and slug tests indicate that the bedrock aquifers also do not readily transmit large amounts of water. The median hydraulic conductivity and transmissivity of the bedrock aquifers are 0.01 foot per dayand 2.75 feet squared per day, respectively. The crystalline and siliciclastic (Weverton and Loudoun Formations) bedrock aquifers are moderately to highly resistant to

  4. Rational risk-based decision support for drinking water well managers by optimized monitoring designs

    NASA Astrophysics Data System (ADS)

    Enzenhöfer, R.; Geiges, A.; Nowak, W.

    2011-12-01

    Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill

  5. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    PubMed

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. PMID:27586069

  6. 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.

  7. 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

  8. 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.

  9. Distributed multisensor processing, decision making, and control under constrained resources for remote health and environmental monitoring

    NASA Astrophysics Data System (ADS)

    Talukder, Ashit; Sheikh, Tanwir; Chandramouli, Lavanya

    2004-04-01

    Previous field-deployable distributed sensing systems for health/biomedical applications and environmental sensing have been designed for data collection and data transmission at pre-set intervals, rather than for on-board processing These previous sensing systems lack autonomous capabilities, and have limited lifespans. We propose the use of an integrated machine learning architecture, with automated planning-scheduling and resource management capabilities that can be used for a variety of autonomous sensing applications with very limited computing, power, and bandwidth resources. We lay out general solutions for efficient processing in a multi-tiered (three-tier) machine learning framework that is suited for remote, mobile sensing systems. Novel dimensionality reduction techniques that are designed for classification are used to compress each individual sensor data and pass only relevant information to the mobile multisensor fusion module (second-tier). Statistical classifiers that are capable of handling missing/partial sensory data due to sensor failure or power loss are used to detect critical events and pass the information to the third tier (central server) for manual analysis and/or analysis by advanced pattern recognition techniques. Genetic optimisation algorithms are used to control the system in the presence of dynamic events, and also ensure that system requirements (i.e. minimum life of the system) are met. This tight integration of control optimisation and machine learning algorithms results in a highly efficient sensor network with intelligent decision making capabilities. The applicability of our technology in remote health monitoring and environmental monitoring is shown. Other uses of our solution are also discussed.

  10. Large Aquatic Ecosystem Restoration Monitoring for Decision Makers: Monitoring to Target and Evaluate Success of Ecosystem Restoration

    EPA Science Inventory

    Monitoring ecosystem restoration at various scales in LAEs can be challenging, frustrating and rewarding. Some of the major ecosystem restoration monitoring occurring in LAEs include: seagrass expansion/contraction; dead zone sizes; oyster reefs; sea turtle nesting; toxic and nu...

  11. 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.

  12. High-resolution monitoring of catchment nutrient response to the end of the 2011-2012 drought in England, captured by the demonstration test catchments

    NASA Astrophysics Data System (ADS)

    Outram, F. N.; Lloyd, C.; Jonczyk, J.; Benskin, C. McW. H.; Grant, F.; Dorling, S. R.; Steele, C. J.; Collins, A. L.; Freer, J.; Haygarth, P. M.; Hiscock, K. M.; Johnes, P. J.; Lovett, A. L.

    2013-12-01

    The Demonstration Test Catchments (DTC) project is a UK Government funded initiative to test the effectiveness of on-farm mitigation measures designed to reduce agricultural pollution without compromising farm productivity. Three distinct catchments in England have been chosen to test the efficacy of mitigation measures on working farms in small tributary sub-catchments equipped with continuous water quality monitoring stations. The Hampshire Avon in the south is a mixed livestock and arable farming catchment, the River Wensum in the east is a lowland catchment with predominantly arable farming and land use in the River Eden catchment in the north-west is predominantly livestock farming. One of the many strengths of the DTC as a national research platform is that it provides the ability to investigate catchment hydrology and biogeochemical response across different landscapes and geoclimatic characteristics, with a range of differing flow behaviours, geochemistries and nutrient chemistries. Although numerous authors present studies of individual catchment responses to storms, no studies exist of multiple catchment responses to the same rainfall event captured with in situ high-resolution nutrient monitoring at a national scale. This paper brings together findings from all three DTC research groups to compare the response of the catchments to a major storm event in April 2012. This was one of the first weather fronts to track across the country following a prolonged drought period affecting much of the UK through 2011-2012, marking an unusual meteorological transition when a rapid shift from drought to flood risk occurred. The effects of the weather front on discharge and water chemistry parameters, including nitrogen species (NO3-N and NH4-N) and phosphorus fractions (total P (TP) and total reactive P (TRP)), measured at a half-hourly time step are examined. When considered in the context of one hydrological year, flow and concentration duration curves reveal that

  13. Water uptake patterns and root system architecture of Zea mays in a natural soil under influence of drought stress monitored by MRI

    NASA Astrophysics Data System (ADS)

    Merz, Steffen; Pohlmeier, Andreas; Seidler, Christina; van Dusschoten, Dagmar; Vereecken, Harry

    2012-04-01

    The interface between roots and soil plays a key role in water transport in the Soil-Plant-Atmosphere-Continuum (SPAC). The transport which changes with the degree of dehydration is influenced by both the hydraulic conductivity of roots and the soil. One important factor in plant growth is the amount of available water in the soil, which correlates directly with soil texture. Water uptake of plant roots and water uptake patterns in soil can be monitored using non-invasive 1H Nuclear Magnetic Resonance Imaging (MRI). In a preceding study the effect of root water uptake and uniform desiccation patterns under drought conditions were observed for Ricinus communis grown in a model medium (Pohlmeier et al. 2008). Continuing these studies, the new aspect is the determination of water uptake patterns and root system architecture in a natural soil. The general challenge of MRI in soils are the inherent fast relaxation times T2* and T2 of the soil matrix. With the use of conventional sequences only water in macropores can be determined. The loss of sensitivity can be overcome by MRI sequences with sufficiently short detection times. In this work we employed and assessed two methods: SPI (Single Point Imaging) detects the T2* relaxation with a dead time of < 0.05 ms and SE3D (Spin Echo 3D) probes T2,eff with an echo time of about 0.8 ms. Zea mays, planted in a cylindrical container filled with a natural soil was completely sealed after 4 weeks of growth to avoid evaporation, so water loss took place via transpiration only. The water content of the soil was determined gravimetrically and by means of MRI each 2nd day over a period of 14 days. Furthermore a SEMS (Spin Echo Multi Slice) sequence was used to visualize the growth of root system architecture. This study shows that SPI3D and SE3D are feasible for the determination of water content in a natural soil up to a certain detection limit. We observed quite uniform water uptake patterns during drying of the soil until water

  14. 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

  15. 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.

  16. 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.

  17. Generalized drought assessment in Dongliao river basin based on water resources system

    NASA Astrophysics Data System (ADS)

    Weng, B. S.; Yan, D. H.; Wang, H.; Qin, T. L.; Yin, J.

    2014-11-01

    Drought is firstly a resource issue, and with its development it transforms into a disaster issue. The occurrences of drought events usually feature determinacy and randomness. Drought issue has become one of the major factors to affect sustainable economic and social development. In this paper, we propose the generalized drought assessment index (GDAI) based on water resources system 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 (DRB) in the northeast China. The results simulated by the GDAI are then compared to observed drought disaster records in DRB. As second, the temporal distribution of drought events and the spatial distribution of drought frequency from the GDAI are compared with the traditional approach (i.e. the SPI, the PDSI, and the RWD). Then, generalized drought times (GDT), generalized drought duration (GDD), and generalized drought severity (GDS) were calculated by theory of runs. Application of the GDT, the GDD, and the GDS of various drought levels (i.e. mild drought, moderate drought, severe drought, and extreme drought) to the period 1960-2010 shows that the centers of gravity of them are all distributed in the middle reached of DRB, and change with time. The proposed methodology helps water managers in water-stressed regions to quantify the impact of drought, consequently, to make decisions regarding coping with drought issue.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Uncertainty Quantification in Vibration-Based Structural Health Monitoring for Enhanced Decision-Making Capability

    NASA Astrophysics Data System (ADS)

    Mao, Zhu

    This dissertation aims to augment current structural health monitoring (SHM) practice with an approach to model and quantify uncertainty to enable confidence-based decision-making. The SHM application domain is vibration data-based system identification, and more specifically, transmissibility and frequency response function (FRF) estimations are considered, as these are the primary forms of transfer function estimation in the frequency domain. A finite element (FE) model is established in order to supply a benchmark of transmissibility evaluations, and by tuning the FE model, structural damages can be simulated. Two SHM features are proposed to detect and localize defects by analyzing the features calculated at certain interest point arrays. Considering a realistic test condition, all of the model parameters and data are subject to uncertainty from various sources leading to ambiguous system identification results that cause false alarms (Type-I error) when evaluating hypothesis testing for damage. Based upon stationary Gaussian random process, this dissertation statistically establishes uncertainty quantification (UQ) models for different estimators, and uncertainties of transmissibility and FRF are therefore quantified. A perturbation approach is implemented ending up with standard deviation and bias coefficient of transmissibility magnitude estimations. Probability density functions (PDFs) of transmissibility and FRF estimation are derived, for both magnitude and phase, via different methods, namely Chi-square and Gaussian bivariate approach. The proposed statistical models are validated by Monte-Carlo test on both FE simulation model and real lab-scale structure. To obtain a more stringent validation condition, extraneous artificial noise is added onto the raw measurements. Compared to the pre-set confidence interval, validation results are illustrated via outlier percentage, which is the observed outlier amount, at each frequency line, normalized by the

  5. Real-time Monitor Quality of WMS to Support Service Choosing Decision

    NASA Astrophysics Data System (ADS)

    Wu, H.; Li, Z.; Yang, C.

    2009-12-01

    The past decade achievement in geospatial interoperability includes thousands of map layers deployed on the Internet and are persistently served for the community through standard interfaces, such as WMS, WFS, and WCS. Our empirical study reveals that the status of the services is not satisfactory and it is often true that a predefined map application is unable to compose because some published map servers simply do not work. When a map composes several layers from different servers, it becomes a serious problem. The request of each map layer takes time and even in the most optimistic expectation, the total time for composing a map is longer than the longest response time. While these services are geographically distributed and maintained by various hosts, it is not possible to solve this problem by improving these services at the host sides. We propose an approach to solve this problem by providing a mechanism that allows map composition to select the best map layers in run time based on real-time monitoring of the quality of services. Service Oriented Architecture (SOA) is extended in this approach to include quality elements in the process of registration, search and binding. OGC capability document is extended to describe quality of service. Techniques, such as online and automatic substitution of second-best layer, local cache, and virtual tile system, are designed and implemented in this approach to enable map composition by requesting map layers from various service providers. A prototype system based on this approach will be demonstrated in our presentation to prove that this approach significantly improves users’ experience of web map composition and is one of the most desired method to make service suitable for decision support.

  6. Global Drought Watch from Space.

    NASA Astrophysics Data System (ADS)

    Kogan, Felix N.

    1997-04-01

    Drought is the most damaging environmental phenomenon. During 1967-91, droughts affected 50% of the 2.8 billion people who suffered from weather-related disasters. Since droughts cover large areas, it is difficult to monitor them using conventional systems. In recent years the National Oceanic and Atmospheric Administration has designed a new Advanced Very High Resolution Radiometer- (AVHRR) based Vegetation Condition Index (VCI) and Temperature Condition Index (TCI), which have been useful in detecting and monitoring large area, drought-related vegetation stress. The VCI was derived from the Normalized Difference Vegetation Index (NDVI), which is the ratio of the difference between AVHRR-measured near-infrared and visible reflectance to their sum. The TCI was derived from the 10.3-11.3-mm AVHRR-measured radiances, converted to brightness temperature (BT). Algorithms were developed to reduce the noise and to adjust NDVI and BT for land surface nonhomogeneity. The VCI and TCI are used to determine the water- and temperature-related vegetation stress occuring during drought. This paper provides the principles of these indices, describes data processing, and gives examples of VCI-TCI applications in different ecological environments of the world. The results presented here are the first attempt to use both NDVI and thermal channels on a large area with very diversified ecological resources. The application of VCI and TCI are illustrated and validated by in situ measurements. These indices were also used for assessment of drought impact on regional agricultural production in South America, Africa, Asia, North America, and Europe. For this purpose, the average VCI-TCI values for a given region and for each week of the growing season were calculated and compared with yields of agricultural crops. The results showed a very strong correlation between these indices and yield, particularly during the critical periods of crop growth.

  7. 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.

  8. Advances in European drought research efforts and related research networks

    NASA Astrophysics Data System (ADS)

    Tallaksen, Lena; van Lanen, Henny

    2010-05-01

    Drought is a complex phenomenon with wide-ranging socio-economic and environmental impacts; still drought research and operational applications like drought monitoring and forecasting, have been lagging behind the development in flood-related research. However, recently several drought research projects and networks have emerged in Europe, partly in response to the occurrence of a series of dry and hot summers in the 21st century, notable the record breaking 2003 event covering large part of central Europe. These events were a strong reminder of Europe's vulnerability to drought and neither were forecasted. Meteorological drought is caused by regional or meso- (synoptic) scale spatial and temporal anomalies in the climatic system, which control the natural short- and long term variability in drought occurrence. However, climate forcing by synoptic scale conditions is not the only cause of drought, also various regional land-surface feedbacks through soil moisture and vegetation, concur to amplify dry weather and high summer temperatures. A deficit in the climatic water balance may affect all components of the hydrological cycle through a reduction in soil moisture, groundwater and surface water and subsequently, reduced water availability. Understanding how a climate water deficiency propagates through the hydrological system and its feedbacks to the atmosphere is crucial to develop drought mitigation and adaptation plans. Moreover, it is the basis for early warning and forecasting of hydrological drought (groundwater and surface water). A review of drought studies from the 20th century suggests that drought in Europe has occurred more frequently in the latter part of the century, partly enhanced by higher temperatures. However, the scientific understanding of the driving forces behind large-scale droughts is incomplete and further complicated by insufficient knowledge about long-term (decadal and millennial) natural variability. Moreover, the role of the physical

  9. A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

    NASA Astrophysics Data System (ADS)

    Khader, A.; Rosenberg, D.; McKee, M.

    2012-12-01

    Nitrate pollution poses a health risk for infants whose freshwater drinking source is groundwater. This risk creates a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision maker and the expected outcomes from these alternatives. The alternatives include: (i) ignore the health risk of nitrate contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, pollution transport processes, and climate (Khader and McKee, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine where methemoglobinemia is the main health problem associated with the principal pollutant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not-use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs include healthcare for methemoglobinemia, purchase of bottled water, and installation and maintenance of the groundwater monitoring system. At current

  10. A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

    NASA Astrophysics Data System (ADS)

    Khader, A. I.; Rosenberg, D. E.; McKee, M.

    2013-05-01

    Groundwater contaminated with nitrate poses a serious health risk to infants when this contaminated water is used for culinary purposes. To avoid this health risk, people need to know whether their culinary water is contaminated or not. Therefore, there is a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management options. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision-maker and the expected outcomes from these alternatives. The alternatives include (i) ignore the health risk of nitrate-contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, contaminant transport processes, and climate (Khader, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine, where methemoglobinemia (blue baby syndrome) is the main health problem associated with the principal contaminant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs

  11. The SfM-monitored rill experiment, a tool to detect decisive processes?

    NASA Astrophysics Data System (ADS)

    Remke, Alexander-André; Wirtz, Stefan; Brings, Christine; Gronz, Oliver; Seeger, Manuel; Ries, Johannes B.

    2016-04-01

    The initiation of rill erosion marks the transition from sheet to linear erosion. With this transition, the relevant processes change and therefore, the observation method needs to be changed too: from observing rainfall induced drop impacts to hydraulic observations. For us, the investigation of the decisive processes in eroding rills resulted in a constantly revised and updated rill erosion experiment, that has been used for several years. Within this experiment the sediment transport behavior of rills is simulated and examined. To make the experiment repeatable and replicable, several key-variables have to be kept constant, i.e. water quantity (1000 L), test duration (approx. 4 min.) and the length of the tested rill section (20 m). For each tested rill, the topographic background is determined i.e. catchment area, aspect, slope, position and height of existing knick-points and three cross-sections. After the initial assessment, the rill is flushed with water (250 L min -1) twice in order to determine the modifications of the rill caused by the flowing water. Within these approx. 4 minutes of "controlled destruction" the velocity of the turbulently flowing water at the beginning of the erosional event and after one and two minutes is determined and the corresponding water depth is recorded using three gauges at selected measuring points. At the end of the tested rill segment, the discharge is constantly monitored. Unfortunately, the results of this rill experiment do not directly show the modifications caused by the artificial waterflow. A way out of this knowledge gap is offered by combining this experimental measurement method with a technique already used in different scientific disciplines in more large-scale applications. Structure-from-Motion technology offers the opportunity to get a different, more detailed view inside the erosion rills. A static multi-camera-array and a dynamically moved digital video-frame camera are now used to obtain three

  12. CropEx Web-Based Agricultural Monitoring and Decision Support

    NASA Technical Reports Server (NTRS)

    Harvey. Craig; Lawhead, Joel

    2011-01-01

    CropEx is a Web-based agricultural Decision Support System (DSS) that monitors changes in crop health over time. It is designed to be used by a wide range of both public and private organizations, including individual producers and regional government offices with a vested interest in tracking vegetation health. The database and data management system automatically retrieve and ingest data for the area of interest. Another stores results of the processing and supports the DSS. The processing engine will allow server-side analysis of imagery with support for image sub-setting and a set of core raster operations for image classification, creation of vegetation indices, and change detection. The system includes the Web-based (CropEx) interface, data ingestion system, server-side processing engine, and a database processing engine. It contains a Web-based interface that has multi-tiered security profiles for multiple users. The interface provides the ability to identify areas of interest to specific users, user profiles, and methods of processing and data types for selected or created areas of interest. A compilation of programs is used to ingest available data into the system, classify that data, profile that data for quality, and make data available for the processing engine immediately upon the data s availability to the system (near real time). The processing engine consists of methods and algorithms used to process the data in a real-time fashion without copying, storing, or moving the raw data. The engine makes results available to the database processing engine for storage and further manipulation. The database processing engine ingests data from the image processing engine, distills those results into numerical indices, and stores each index for an area of interest. This process happens each time new data is ingested and processed for the area of interest, and upon subsequent database entries, the database processing engine qualifies each value for each area of

  13. 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.

  14. 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.

  15. From meteorological to hydrological drought in the Upper Niger Basin: trend and uncertainty analysis in the monitoring and the modeling of rainfall deficits and low flow responses

    NASA Astrophysics Data System (ADS)

    Fournet, S.; Aich, V.; Liersch, S.; Hattermann, F. F.

    2012-04-01

    From 1970 to 2002, the Sahel experienced a fairly abrupt, severe and continuous dry episode. The main reason is the oceanic forcing ruling the West African monsoon dynamic. Also, a combinative effect of climate and anthropogenic changes (demographic pressure on land associated to inappropriate land-use practices) initiates and supports the interactive processes of drying and land cover degradation forming a complex land atmosphere feedback convection. The Great Drought in Mali largely affected the regional food security, the human societies and economic development and the conservation of wet and semi-arid ecosystems. It results in an increasing competition and conflicts for water access between vulnerable local stakeholders (rainfed and controlled irrigation farming, nomad pastoralism, traditional fishing) and steers national investments with the construction of dams and diversion channels for development of hydropower energy and fully governed irrigated agriculture. To support drought adaptations in regional development strategies, climate and hydrological forecasting are thus of paramount importance. Whilst climate change is typically associated with an increase in mean global surface temperature, what matters regionally and still remains uncertain is the change in rainfall, discharge and drought patterns from daily intensity to large inter-annual and multi-decadal variability. Different climate data sources exist for investigation of climate variability and change: daily measurements, reanalysis data and climate scenarios using Global and Regional Circulation Models (GCMs and RCMs). This study aims at analyzing the suitability of the different data sources for drought investigation in the target area, the Upper Niger Basin. First, the performance of meteorological data sets based on climate reanalysis is assessed in comparison of data of synoptic stations. Second, one statistical (STAR) and two dynamical regional RCMs (CCLM, REMO) are compared to IPCC-GCM data

  16. The characteristics of global droughts and ENSO teleconnections

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Xu, C.; Chen, X.; Hong, Y.

    2012-04-01

    Drought is among world's most serious natural disasters which have profound effects on human and environmental activity globally. In recent years, the increase of the frequency and intensity of droughts has aroused wide concern. More intense and longer droughts have been observed over wider areas, particularly in the tropics and subtropics since the 1970s. The SPI (Standard Precipitation Index) based on monthly precipitation is one of the most prominent indices of meteorological drought and soil moisture is a useful indicator of drought because it provides an aggregate estimate of available water from the balance of precipitation, evaporation, and runoff fluxes. Many studies have been conducted aiming to increase the understanding of the drought properties and underlying causes; however, the causes of droughts are complex. Some research has revealed that there is a strong relation between ENSO and drought and flood disasters. In this paper, the global monthly precipitation and soil moisture data are used to monitor the global drought, in particular, we devote ourselves to analyze the relationship between the variation of global drought and ENSO with the main objectives of exploring the spatial distribution and long-term trends of global drought and investigating the influences of ENSO on the occurrence of drought in different areas in the world. The monthly precipitation and soil moisture data during the period of 1948-2009 are derived from CRU and CPC soil moisture data set, respectively. The results show that the droughts have significantly increasing trends in the world during the past several decades. An obvious drying trend can be found in East Asia, South Asia, North Africa, northern South America, south and central Europe et al. The trends of drought in most areas in the world are correlated well with the variation of ENSO. This research has the potential to help to improve our understanding of changes of global droughts and thus to enhance human mitigation

  17. 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

  18. Social capacities for drought risk management in Switzerland

    NASA Astrophysics Data System (ADS)

    Kruse, S.; Seidl, I.

    2013-04-01

    This paper analyses the social capacities for drought risk management and gaps from the perspective of national and regional water users and policy and decision makers in Switzerland. The analysis follows five dimensions of social capacities as prerequisites for drought risk management. Regarding information and knowledge (1), basic data is available, however not assembled for an integrated drought information system. As to technology and infrastructure (2), little pro-active capacities are available with exception to few drought-prone regions; in emergency response to drought though, provisional capacities are put together. Regarding organisation and management (3) most regions have enough personnel and effective cooperation in case of acute drought; long-term strategies though are largely missing. Economic resources (4) have been considered as sufficient if drought remains rare. Finally, institutions and policies (5) are not sufficient for pro-active drought risk management, but have been suitable in the drought of 2003. Starting points for building social capacities are first to draw back upon the extensive experiences with the management of other natural hazards, second to build an integrated drought information system, including social and economic impacts and third to improve the institutional framework through consistent regulations and coordination for pro-active drought risk management.

  19. Social capacities for drought risk management in Switzerland

    NASA Astrophysics Data System (ADS)

    Kruse, S.; Seidl, I.

    2013-12-01

    This paper analyses the social capacities for drought risk management from the perspective of national and regional water users and policy- and decision-makers in Switzerland. The analysis follows five dimensions of social capacities as prerequisites for drought risk management. Regarding information and knowledge (1), basic data is available, however not assembled for an integrated drought information system. As for technology and infrastructure (2), limited proactive capacities are available with the exception of a few of the drought-prone regions; in emergency response to drought however, provisional capacities are put together. Regarding organisation and management (3) most regions have enough personnel and effective cooperation in the case of acute and sporadic drought; long-term strategies though are largely missing. Economic resources (4) are sufficient if droughts remain rare. Finally, institutions and policies (5) are not sufficient for proactive drought risk management, but have been suitable in the drought of 2003. Starting points for building social capacities are first, to draw on the extensive experiences with the management of other natural hazards, second to build an integrated drought information system, including social and economic impacts, and third to improve the institutional framework through consistent regulations and coordination for proactive drought risk management.

  20. 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.

  1. Understanding the phenomenon of drought

    SciTech Connect

    Wilhite, D.A. )

    1993-08-01

    As the demands placed on water resources increase, society and industry become more vulnerable to the effects of drought. Having a better understanding of drought can enable hydroelectric project owners, operators, and developers to improve their planning for future drought risks. This article describes drought in general as part of the climate, causes and predictability of drought, and the effects of drought.

  2. Plant Stress Indicates Drought

    NASA Video Gallery

    Farmers across America rely on early drought warning systems to manage their crops. Americans everywhere rely on those farmers to provide food. A new drought tracking system called ESI helps by mon...

  3. 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.

  4. Geoelectric monitoring as an innovative landslide monitoring tool to improve decision finding in early warning and emergency applications

    NASA Astrophysics Data System (ADS)

    Supper, R.; Ottowitz, D.; Jochum, B.; Kim, J.; Gruber, S.; Pfeiler, S.; Römer, A.

    2013-12-01

    The evaluation of actual landslide hazards and the warning of people before a catastrophic event require a good knowledge about structure, dynamics, triggers, history and possible magnitude of such high-risk landslides. However research showed that he triggering factor of almost all recent major landslides in Austria was correlated with precipitation events or snow melt. Since changes of the electrical resistivity of the subsurface with time are in most cases expected to result from variations in soil water content of the subsurface, the geoelectric method is supposed to have a high potential as an additional method to investigate subsurface processes leading to the triggering of a landslide. Therefore a geoelectric monitoring system (GEOMON4D) was developed by the Geological Survey of Austria, specifically adapted for the requirements of landslide monitoring. Starting in 2009 several GEOMON4D systems, combined with other permanently recording sensors to measure displacement (DMSTM) and hydrological parameters were installed at several active landslides in Central Europe. At the moment this TEMPLE monitoring network consists of 6 active stations (Pechgraben (A), Gschliefgraben (A), Kitzsteinhorn (A), Rosano (I), Bagnaschino (I) and La Valette (F); the stations of Hausruck (A), Laakirchen (A) and Ancona (I) were recently finalised), delivering high resolution data on a daily basis. For processing of the data a new 4D inversion algorithm was developed. In this presentation we mainly refer to the results from the Bagnaschino, Laakirchen and Pechgraben site. Although displacement measurements registered on hourly to 10 minutes basis made it possible to raise early warnings, only the analysis and inversion of geoelectrical monitoring data allowed analysing in detail the subsurface hydrological processes, which finally lead to the triggering of the respective landslides. Therefore geoelectric monitoring proved to be an essential tool to understand the prevailing

  5. The Drought Impact Reporter: A Web-Based National Drought Impacts Reporting Tool

    NASA Astrophysics Data System (ADS)

    Hayes, M. J.; Svoboda, M.; Higgins, M.; Wilhite, D.; Wood, D.

    2005-12-01

    Although drought is a major natural hazard worldwide, very few quantitative assessments and economic estimates of drought impacts have been done. In the United States, the Federal Emergency Management Agency (FEMA) estimated in 1995 that droughts in the United States cause an average annual economic loss of $6-8 billion (FEMA 1995). This number is a very rough estimate. Overall, estimates of the economic losses associated with drought are extremely incomplete at local, regional, and national scales and also by sector. In addition, many of the impacts associated with drought are social and environmental, and they are difficult to quantify. Although the National Drought Mitigation Center (NDMC) receives numerous requests each year for information on the magnitude of drought impacts for current or historical events, no systematic, standardized data collection effort exists in the United States. For this reason, the NDMC is establishing a methodology and reporting/dissemination tool under an overarching National Drought Impact Reporting Strategy (NDIRS). This tool, the Drought Impact Reporter, consists of a web-based package of products and interactive features that is also designed to assimilate user-supplied information, giving decision makers at all levels the ability to report or assess the impacts due to drought in near real-time down to the county level. An archival database is also being built and maintained, allowing for queries based on location, time, and impact category. The ultimate goal of this NDIRS effort is to develop methodologies that are comprehensive and consistent in quantifying the economic losses associated with drought, as well as social and environmental impacts at all levels.

  6. Drought risk on a pan European scale: integrating the missing piece

    NASA Astrophysics Data System (ADS)

    Blauhut, Veit; Stahl, Kerstin

    2015-04-01

    The effects of drought on the environment and socio- economic sectors are indisputably linked to each other. Nevertheless, past drought research suffered from an evident lack of ground truth in form of past observed impacts. Consequently most drought indicators are missing the link to a drought's effects on natural and human systems, and the majority of drought risk analyses are based on non-sector-specific, epistemic approaches. Hence, the science and application demands an integration of the missing piece: past drought impacts. Furthermore, for the case of Europe, drought risk analyses are mainly done for country scale or smaller units, even though the effects of the drought hazard are transboundary and long term measures are initiated through the European governance mechanism. This contribution faces drought risk on a pan European scale. A spatio-temporal clustering of drought impact occurrences from the European Drought Impact report Inventory divides Europe into macro regions with similar drought impact characteristics. To link drought impacts to indicators and vulnerability factors, multivariate logistic regression is applied to predict the likelihood of impact occurrence as a proxy for drought risk. As predictive variables we used a selection of common drought indicators and drought vulnerability analysis factors. The final results are displayed as drought risk maps, presenting drought risk for different levels of hazard severity, showing distinct differences in drought risk depending on location and impact sector. With this work, we contribute to the understanding of feedbacks between drought and society. The knowledge of this relation is essential for drought impact predictions and will improve resilience to this hazard. Furthermore, this information may become an essential tool for policy and decision makers on a European level.

  7. Drought resistant sugar beets

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Technical Abstract: Increased water demands and drought have resulted in a need to indentify crop hybrids that are drought tolerant, requiring less irrigation to sustain yields. This study was conducted to assess differences in drought tolerance among a group of genetically diverse sugarbeet hybrids...

  8. Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

    USGS Publications Warehouse

    Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

    2010-01-01

    This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

  9. Development of Decision Support System for Remote Monitoring of PIP Corn

    EPA Science Inventory

    The EPA is developing a multi-level approach that utilizes satellite and airborne remote sensing to locate and monitor genetically modified corn in the agricultural landscape and pest infestation. The current status of the EPA IRM monitoring program based on remote sensed imager...

  10. A Regional Monitoring and Visualization System for Decision Support and Disaster Management Applications for the Mesoamerican Biological Corridor and Beyond

    NASA Technical Reports Server (NTRS)

    Irwin, Daniel

    2002-01-01

    The Mesoamerican Biological Corridor (MBC)-a network of managed and protected areas extending from Mexico to Columbia-is a crucial initiative for the Mesoamerican region, with a central development concept of integrating conservation and sustainable use of biodiversity within the framework of sustainable economic development. The MBC is of particular importance to the Central American Commission for Environment and Development (CCAD), which is comprised of the environmental ministers from the seven Central American countries. Responsible for determining priority areas for action in the corridor, CCAD decision makers require current and accurate information, and access to the dynamic knowledge of the changes in the MBC such as deforestation hotspots, fires, and the effects of natural disasters. Currently this information is not integrated and in disparate locations throughout the region and the world. Leveraging NASA technology, satellite data, and capability, we propose to team with the World Bank and the CCAD to develop a regional monitoring and visualization system-with central nodes at the NASA/Marshall Space Flight Center and at CCAD headquarters. This system will assimilate NASA spatial datasets (e.g. MODIS, Landsat, etc.), spatial data from other sources (commercial and public-domain), and ancillary data developed in each of the seven Central American countries (soils, transportation networks, biodiversity indicator maps, etc.). The system will function as a "virtual dashboard" for monitoring the MBC and provide the critical decision support tools for CCAD decision makers. The CCAD central node will also serve as a high-tech showcase for the corridor among the international community, other decision-makers, the media, and students.

  11. Evaluation of drought regimes and impacts in the Limpopo basin

    NASA Astrophysics Data System (ADS)

    Alemaw, B. F.; Kileshye-Onema, J.-M.

    2014-01-01

    regional sustainable water resources development strategies. This study is exciting in the manner that the variations in the sub-basin drought severities are revealed and are used to suggest the corresponding drought monitoring and management strategies. This will have an overall effect in developing a basin-wide framework for integrated drought management as well as water resources development and management, which requires cooperative efforts among the riparian countries of the Limpopo basin.

  12. Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

    NASA Astrophysics Data System (ADS)

    A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

    2015-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

  13. Assessing Urban Droughts in a Smart City Framework

    NASA Astrophysics Data System (ADS)

    Obringer, R.; Zhang, X.; Mallick, K.; Alemohammad, S. H.; Niyogi, D.

    2016-06-01

    This study aims to integrate environmental data for drought monitoring to reduce uncertainty in urban drought characterization as part of the smart city framework. Currently, drought monitoring in urban areas is a challenge. This is due, in part, to a lack of knowledge on the subject of urban droughts and urban drought vulnerability. A critical part to assessing urban drought and implementing the necessary policies is determining drought conditions. Often the timing and severity of the drought can leave cities to enforce water restrictions, so accuracy of this determination has socioeconomic implications. To determine drought conditions, we need to know the water balance over the urban landscape, of which evapotranspiration (ET) is a key variable. However, ET data and models have high uncertainty when compared to other hydrological variables (i.e., precipitation). This is largely due to ill-defined empirical models for characterizing the urban surface resistance parameter (rs) that is used in ET calculations. We propose a method to estimate rs values using a combination of the Surface Temperature Initiated Closure (STIC) method that calculates regional evapotranspiration data and an inverted version of the Penman-Monteith equation. We use this approach across the region surrounding Indianapolis, IN (USA) from 2010-2014. We discuss the potential for this method to be integrated in to smart city framework to improve urban drought assessment.

  14. Drought-mortality relationships for tropical forests.

    PubMed

    Phillips, Oliver L; van der Heijden, Geertje; Lewis, Simon L; López-González, Gabriela; Aragão, Luiz E O C; Lloyd, Jon; Malhi, Yadvinder; Monteagudo, Abel; Almeida, Samuel; Dávila, Esteban Alvarez; Amaral, Iêda; Andelman, Sandy; Andrade, Ana; Arroyo, Luzmila; Aymard, Gerardo; Baker, Tim R; Blanc, Lilian; Bonal, Damien; de Oliveira, Atila Cristina Alves; Chao, Kuo-Jung; Cardozo, Nallaret Dávila; da Costa, Lola; Feldpausch, Ted R; Fisher, Joshua B; Fyllas, Nikolaos M; Freitas, Maria Aparecida; Galbraith, David; Gloor, Emanuel; Higuchi, Niro; Honorio, Eurídice; Jiménez, Eliana; Keeling, Helen; Killeen, Tim J; Lovett, Jon C; Meir, Patrick; Mendoza, Casimiro; Morel, Alexandra; Vargas, Percy Núñez; Patiño, Sandra; Peh, Kelvin S-H; Cruz, Antonio Peña; Prieto, Adriana; Quesada, Carlos A; Ramírez, Fredy; Ramírez, Hirma; Rudas, Agustín; Salamão, Rafael; Schwarz, Michael; Silva, Javier; Silveira, Marcos; Slik, J W Ferry; Sonké, Bonaventure; Thomas, Anne Sota; Stropp, Juliana; Taplin, James R D; Vásquez, Rodolfo; Vilanova, Emilio

    2010-08-01

    *The rich ecology of tropical forests is intimately tied to their moisture status. Multi-site syntheses can provide a macro-scale view of these linkages and their susceptibility to changing climates. Here, we report pan-tropical and regional-scale analyses of tree vulnerability to drought. *We assembled available data on tropical forest tree stem mortality before, during, and after recent drought events, from 119 monitoring plots in 10 countries concentrated in Amazonia and Borneo. *In most sites, larger trees are disproportionately at risk. At least within Amazonia, low wood density trees are also at greater risk of drought-associated mortality, independent of size. For comparable drought intensities, trees in Borneo are more vulnerable than trees in the Amazon. There is some evidence for lagged impacts of drought, with mortality rates remaining elevated 2 yr after the meteorological event is over. *These findings indicate that repeated droughts would shift the functional composition of tropical forests toward smaller, denser-wooded trees. At very high drought intensities, the linear relationship between tree mortality and moisture stress apparently breaks down, suggesting the existence of moisture stress thresholds beyond which some tropical forests would suffer catastrophic tree mortality. PMID:20659252

  15. 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.

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

    PubMed

    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

  17. 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

  18. Microwave remote sensing of flash droughts during crop growing seasons

    NASA Astrophysics Data System (ADS)

    Yuan, Xing; Ma, Zhuguo; Pan, Ming; Shi, Chunxiang

    2015-04-01

    Severe short-term droughts frequently occurred over China in recent years, with devastating impacts on crop production. Short-term droughts during the crop growing seasons sometimes occur together with abnormally high temperature, and positive feedbacks between the land and atmosphere often intensify the drought conditions. These droughts are recently termed as "flash droughts" due to their rapid development, unusual intensity and devastating impacts. This study assesses the capability of microwave remote sensing in detecting soil moisture droughts over China and in providing early warnings. The 22-year (1992-2013) satellite surface soil moisture retrievals produced by the European Space Agency Climate Change Initiative (ESA CCI) are compared against the in-situ observations at 312 stations in China, the ERA Interim and GLDAS soil moisture reanalysis, and the observed rainfall deficit. Both the reanalysis and remote sensing products can only detect less than 60% of drought months over most in-situ stations, but they capture the responses of inter-annual drought variations to ENSO at river basin scales quite well. As compared with reanalysis, the satellite products provide independent drought information over sparsely observed regions such as northwestern China, and the active microwave product with better vegetation penetration works the best in southern China. This study suggests that the microwave remote sensing data is useful for soil moisture drought monitor as well as verification for drought modeling or forecasting.

  19. Applying Generalizability Theory for Making Quantitative RTI Progress-Monitoring Decisions

    ERIC Educational Resources Information Center

    Fan, Chung-Hau; Hansmann, Paul R.

    2015-01-01

    Language in the Individuals With Disabilities Education Improvement Act (IDEIA) allows the use of response-to-intervention (RTI) methodology in the identification of specific learning disabilities. However, there is no consensus on decision rules using curriculum-based measurement of oral reading fluency (CBM-R) for defining responsiveness. The…

  20. Drought Frequency Index

    NASA Astrophysics Data System (ADS)

    Gonzalez, J.; Valdes, J. B.

    2003-04-01

    Droughts are related with prolonged time periods during moisture is significantly below normal situation. Drought indexes try to scale the main drought features based on similar definitions. The Standard Precipitation Index (SPI) is a well-known index, which for a given aggregation-time measures the deviation from the normality of the precipitation. One of the SPI weak points in the representation of drought phenomenon is that drought duration should be analyzed by using different aggregation-times. In this work, a new index is presented, which simultaneously characterize droughts based on the deviation from the normal precipitation regime and the drought persistence, both from the statistical point of view. The new index does not require aggregation at different time-lengths. Instead droughts are treated as multivariate events, whose dimensionality depends on the duration. Probabilistic events with different dimensionalities are compared on a common dimension of interest. In this case the dimension chosen is the mean frequency of recurrence. The derived index, named Drought Frequency Index (DFI) may be used to characterize historical droughts or current situation. It can be apply not only over precipitation but also over flows or other hydroclimatic variables. The new index was applied to several places in USA and Spain both for precipitation and flow historical sequences, and compared with SPI. The DFI allows the representation of the main drought characteristics in a single value, based on the stochastic feature of the phenomenon, and scaled on the mean frequency of recurrence.

  1. Dissociating source memory decisions in the prefrontal cortex: fMRI of diagnostic and disqualifying monitoring.

    PubMed

    Gallo, David A; McDonough, Ian M; Scimeca, Jason

    2010-05-01

    We used event-related fMRI to study two types of retrieval monitoring that regulate episodic memory accuracy: diagnostic and disqualifying monitoring. Diagnostic monitoring relies on expectations, whereby the failure to retrieve expected recollections prevents source memory misattributions (sometimes called the distinctiveness heuristic). Disqualifying monitoring relies on corroborative evidence, whereby the successful recollection of accurate source information prevents misattribution to an alternative source (sometimes called recall to reject). Using criterial recollection tests, we found that orienting retrieval toward distinctive recollections (colored pictures) reduced source memory misattributions compared with a control test in which retrieval was oriented toward less distinctive recollections (colored font). However, the corresponding neural activity depended on the type of monitoring engaged on these tests. Rejecting items based on the absence of picture recollections (i.e., the distinctiveness heuristic) decreased activity in dorsolateral prefrontal cortex relative to the control test, whereas rejecting items based on successful picture recollections (i.e., a recall-to-reject strategy) increased activity in dorsolateral prefrontal cortex. There also was some evidence that these effects were differentially lateralized. This study provides the first neuroimaging comparison of these two recollection-based monitoring processes and advances theories of prefrontal involvement in memory retrieval. PMID:19413478

  2. 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.

  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. Bayesian decision analysis as a tool for defining monitoring needs in the field of effects of CSOs on receiving waters.

    PubMed

    Korving, H; Clemens, F

    2002-01-01

    In recent years, decision analysis has become an important technique in many disciplines. It provides a methodology for rational decision-making allowing for uncertainties in the outcome of several possible actions to be undertaken. An example in urban drainage is the situation in which an engineer has to decide upon a major reconstruction of a system in order to prevent pollution of receiving waters due to CSOs. This paper describes the possibilities of Bayesian decision-making in urban drainage. In particular, the utility of monitoring prior to deciding on the reconstruction of a sewer system to reduce CSO emissions is studied. Our concern is with deciding whether a price should be paid for new information and which source of information is the best choice given the expected uncertainties in the outcome. The influence of specific uncertainties (sewer system data and model parameters) on the probability of CSO volumes is shown to be significant. Using Bayes' rule, to combine prior impressions with new observations, reduces the risks linked with the planning of sewer system reconstructions. PMID:11902469

  5. Drought Definitions Revisited

    NASA Astrophysics Data System (ADS)

    Van Loon, A.; Van Lanen, H.; Gleeson, T.

    2014-12-01

    Drought is commonly defined as a temporary lack of water compared to normal conditions. In the traditional definition used in the natural sciences (climate science, hydrology, earth science) only natural drivers are included and the human effect on water resources is excluded. Drought impact studies, however, using observed crop yields, wildfire data, reservoir information, etc., can hardy make this division. The interdisciplinarity of drought asks for a broader definition that considers the interplay between the hazard, impacts and management. In the IPCC-SREX report definitional issues are mentioned as one of the reasons that no clear conclusions can be drawn about historic and future changes in drought. Human activities related to drought are mentioned by IPCC, but not included in their definition of drought. In the anthropocene the human aspects of drought can no longer be neglected. The IAHS Panta Rhei initiative, for example, urges hydrologists to include the connection with human systems. We propose a paradigm shift in the definition of drought, namely to expand it to include the effects of human action. For attribution we can then distinguish between climate-induced drought and human-induced drought. In this presentation, we will present a conceptual diagram that will do justice to the interdisciplinarity of drought. We will discuss issues of variability and change, scale (both temporal and spatial scales), feedbacks, and direct and indirect anthropogenic effects. The revised definition provides recognition and a common ground to researchers in all fields of research and is better aligned with drought impacts and with stakeholders' and policy maker's views on drought.

  6. Informed Decision Making for In-Home Use of Motion Sensor-Based Monitoring Technologies

    ERIC Educational Resources Information Center

    Bruce, Courtenay R.

    2012-01-01

    Motion sensor-based monitoring technologies are designed to maintain independence and safety of older individuals living alone. These technologies use motion sensors that are placed throughout older individuals' homes in order to derive information about eating, sleeping, and leaving/returning home habits. Deviations from normal behavioral…

  7. The ebb and flow of airborne pathogens: Monitoring and use in disease management decisions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Perhaps the earliest form of monitoring the regional spread of plant disease was a group of growers gathering together at the market and discussing what they see in their crops. This type of reporting continues to this day through regional extension blogs, by crop consultants and more formal scoutin...

  8. Monitoring Classroom Behavior in Early Childhood: Using Group Observation Data to Make Decisions

    ERIC Educational Resources Information Center

    Krasch, Delilah; Carter, Deborah Russell

    2009-01-01

    Monitoring and evaluating classroom behavior in early childhood for the purpose of improving teaching and learning is critical. There is a clear link between social behavior and academic learning. Classrooms where students are following expectations, engaging academically, and transitioning effectively between activities are classrooms where…

  9. The ebb and flow of airborne pathogens: monitoring and use in disease management decisions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Perhaps the earliest form of monitoring the regional spread of plant disease was a group of growers gathering together at the market and discussing what they see in their crops. This type of reporting continues to this day through regional extension blogs, by crop consultants and more formal scoutin...

  10. 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

  11. 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

  12. Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

    PubMed

    Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

    2015-01-01

    This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning. PMID:26262410

  13. 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 ...

  14. Exploration of drought evolution using numerical simulations over the Xijiang (West River) basin in South China

    NASA Astrophysics Data System (ADS)

    Niu, Jun; Chen, Ji; Sun, Liqun

    2015-07-01

    The knowledge of drought evolution characteristics may aid the decision making process in mitigating drought impacts. This study uses a macro-scale hydrological model, Variable Infiltration Capacity (VIC) model, to simulate terrestrial hydrological processes over the Xijiang (West River) basin in South China. Three drought indices, namely standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture anomaly index (SMAI), are employed to examine the spatio-temporal and evolution features of drought events. SPI, SRI and SMAI represent meteorological drought, hydrological drought and agricultural drought, respectively. The results reveal that the drought severity depicted by SPI and SRI is similar with increasing timescales; SRI is close to that of SPI in the wet season for the Liu River basin as the high-frequency precipitation is conserved more by runoff; the time lags appear between SPI and SRI due to the delay response of runoff to precipitation variability for the You River basin. The case study in 2010 spring drought further shows that the spatio-temporal evolutions are modulated by the basin-scale topography. There is more consistency between meteorological and hydrological droughts for the fan-like basin with a converged river network. For the west area of the Xijiang basin with the high elevation, the hydrological drought severity is less than meteorological drought during the developing stage. The recovery of hydrological and agricultural droughts is slower than that of meteorological drought for basins with a longer mainstream.

  15. 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; Cai, Ximing; Wardlow, Brian; Xia, Youlong; Verdin, Jim; Ek, Michael

    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.

  16. Research on the quantitative diagnosis of drought hazard degree of winter wheat using multi-source remote sensing data

    NASA Astrophysics Data System (ADS)

    He, Haixia

    2015-12-01

    The purpose of this study is to perform the quantitative diagnosis of drought hazard degree using multi-source remote sensing data. Hazard degree is the basic function for disaster risk assessment and loss assessment. Quantitative diagnosis of drought hazard degree is essential to decision-making of drought early warning and emergency relief in practice. The currently used diagnosis methods are based on disaster loss and drought indices. The response process and impacts of drought in different crop growth stages were ignored in these methods. So, the instructions were not dynamic and real time. This study investigated the drought hazard degree diagnosing of winter wheat based on continuous multi-source remote sensing imagery and comprehensive ground-based observations. The resulted indicated that the correlation is high and drought hazard degree is suitable and sensitive to reveal drought disaster-forming environment evolution, drought formation mechanism and drought influence.

  17. Design of a decision-support architecture for management of remotely monitored patients.

    PubMed

    Basilakis, Jim; Lovell, Nigel H; Redmond, Stephen J; Celler, Branko G

    2010-09-01

    Telehealth is the provision of health services at a distance. Typically, this occurs in unsupervised or remote environments, such as a patient's home. We describe one such telehealth system and the integration of extracted clinical measurement parameters with a decision-support system (DSS). An enterprise application-server framework, combined with a rules engine and statistical analysis tools, is used to analyze the acquired telehealth data, searching for trends and shifts in parameter values, as well as identifying individual measurements that exceed predetermined or adaptive thresholds. An overarching business process engine is used to manage the core DSS knowledge base and coordinate workflow outputs of the DSS. The primary role for such a DSS is to provide an effective means to reduce the data overload and to provide a means of health risk stratification to allow appropriate targeting of clinical resources to best manage the health of the patient. In this way, the system may ultimately influence changes in workflow by targeting scarce clinical resources to patients of most need. A single case study extracted from an initial pilot trial of the system, in patients with chronic obstructive pulmonary disease and chronic heart failure, will be reviewed to illustrate the potential benefit of integrating telehealth and decision support in the management of both acute and chronic disease. PMID:20615815

  18. 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.

    2016-03-01

    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.

  19. Bayesian decision and mixture models for AE monitoring of steel-concrete composite shear walls

    NASA Astrophysics Data System (ADS)

    Farhidzadeh, Alireza; Epackachi, Siamak; Salamone, Salvatore; Whittaker, Andrew S.

    2015-11-01

    This paper presents an approach based on an acoustic emission technique for the health monitoring of steel-concrete (SC) composite shear walls. SC composite walls consist of plain (unreinforced) concrete sandwiched between steel faceplates. Although the use of SC system construction has been studied extensively for nearly 20 years, little-to-no attention has been devoted to the development of structural health monitoring techniques for the inspection of damage of the concrete behind the steel plates. In this work an unsupervised pattern recognition algorithm based on probability theory is proposed to assess the soundness of the concrete infill, and eventually provide a diagnosis of the SC wall’s health. The approach is validated through an experimental study on a large-scale SC shear wall subjected to a displacement controlled reversed cyclic loading.

  20. Decision analysis for continuous cover gas monitoring of Ferrocyanide Watch List tanks

    SciTech Connect

    Fowler, K.D.; Graves, R.D.

    1994-07-01

    This document pertains to underground waste storage tanks at the Hanford Site that have been identified to potentially contain a significant amount of ferrocyanide compounds. This document evaluates the need for continuously monitoring the headspace vapors in Ferrocyanide Watch List tanks to detect flammable gases or gases that could indicate the occurrence of a propagating ferrocyanide-nitrate/nitrite reaction. The results of modeling studies and gas monitoring, and sludge sample analyses of actual ferrocyanide tank wastes have indicated no need to continuously monitor the vapor spaces in ferrocyanide tanks. This conclusion is based in part on the following factors: (1) a study performance on waste aging suggests that the ferrocyanide has degraded in the tanks during the more than 35 years of storage; therefore, the ferrocyanide is not present in concentrations that could support an exothermic reaction, also, the moisture present in the waste is sufficient to preclude a self-sustaining (propagating) ferrocyanide-nitrate reaction; (2) evaluation of core sample results from Tank 241-C-109 and Tank 241-C-112 support laboratory studies showing that ferrocyanide has degraded and the fuel concentration in the tanks is considerably lower than postulated by flowsheet simulants; (3) no gases have been identified that would indicate the occurrence of a ferrocyanide nitrate/nitrite reaction; additionally, a self-sustaining ferrocyanide nitrate/nitrite reaction is not possible under current and future planned storage conditions. After reviewing the available information, it is evident that there would be little safety benefit from continuous in-tank vapor monitoring, and the time and commitment of operations schedule and equipment funds are not justified in the face of competing needs.

  1. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    NASA Astrophysics Data System (ADS)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives

  2. Satellite Observations of the Epic California Drought

    NASA Astrophysics Data System (ADS)

    Famiglietti, J. S.; Thomas, B. F.; Reager, J. T., II; Castle, S. L.; David, C. H.; Thomas, A. C.; Andreadis, K.; Argus, D. F.; Behrangi, A.; Farr, T.; Fisher, J. B.; Landerer, F. W.; Lo, M. H.; Molotch, N. P.; Painter, T. H.; Rodell, M.; Schimel, D.; Swenson, S. C.; Watkins, M. M.

    2014-12-01

    As California enters its third year of drought, questions of future water sustainability are inevitable. Snowpack, soil moisture, streamflow, reservoir and groundwater levels are at record lows. Mandatory water restrictions are being implemented, statewide fines for wasting water have been authorized, and billions of dollars and tens of thousands of jobs have been lost. Enhanced monitoring and modeling of the state's dwindling water supplies can help manage what remains while looking forward to a post-drought, sustainable water future. Here we demonstrate the role of satellite observations in comprehensive drought characterization and monitoring. In particular we highlight changing water supply, declining groundwater and reservoir levels, agricultural and urban stress. Potential contributions to water management will be discussed.

  3. Reducing societal vulnerability to drought: A methodology

    SciTech Connect

    Wilhite, D.A.

    1995-12-31

    Given worldwide experience with drought during the past several decades and the magnitude of associated impacts, it is apparent that vulnerability to extended periods of water shortage is escalating. Developing a national or provincial drought policy and preparedness plan is a complicated but essential first step toward reducing societal vulnerability. Until recently, nations had devoted little effort to drought preparedness, preferring instead the reactive or crisis management approach. Presently, an increasing number of nations are pursuing a more proactive approach that emphasizes the principles of risk management and sustainable development. Because of the multitude of impacts associated with drought and the numerous governmental agencies that have responsibility for some aspect of monitoring, assessment, mitigation, and planning, developing a policy and plan must be an integrated process within and between levels of government. This paper outlines a generic process that can be adopted by governments that desire to develop a more comprehensive and long-term approach to drought management and planning. Countries and states or provincial authorities that have adopted this approach is presented as case studies. This process is timely, given the declaration of the 1990s as the International Decade for Natural Disaster Reduction and the recent International Convention to Combat Desertification and Drought (June, 1994), an offshoot of deliberations at the United Nations Conference on Environment and Development.

  4. Evaluation, modification, and application of the Effective Drought Index to 200-Year drought climatology of Seoul, Korea

    NASA Astrophysics Data System (ADS)

    Kim, Do-Woo; Byun, Hi-Ryong; Choi, Ki-Seon

    2009-11-01

    SummaryIn this paper, progressive methods for assessing drought severity from diverse points of view were conceived. To select a fundamental drought index, the performances of the Effective Drought Index (EDI) and 1-, 3-, 6-, 9-, 12-, and 24-month Standardized Precipitation Indices (SPIs) were compared for drought monitoring data accumulated over 200-year period from 1807 to 2006 for Seoul, Korea. The results confirmed that the EDI was more efficient than the SPIs in assessing both short and long-term droughts. We then proposed the following methods for modifying and supplementing the EDI: (1) CEDI, a corrected EDI that considers the rapid runoff of water resources after heavy rainfall; (2) AEDI, an accumulated EDI that considers the drought severity and duration of individual drought events; and (3) YAEDI, a year-accumulated negative EDI representing annual drought severity. In addition to these indices, to more accurately measure and diagnose droughts, we proposed the utilization of (4) the Available Water Resources Index (AWRI), an existing index that expresses the actual amount of available water. Using the improved methods above, we assessed and summarized important droughts that have occurred in Seoul over the 200 years from 1807 to 2006.

  5. Assessment of Surface Water at the Sobradinho Reservoir Under the Effects of Drought Using Multi-Temporal Landsat Images

    NASA Astrophysics Data System (ADS)

    Silva, E. A.; Pedrosa, M. M.; Azevedo, S. C.; Cardim, G. P.; Carvalho, F. P. S.

    2016-06-01

    The matrix of energy generation in Brazil is predominantly hydroelectric power. Consequently, the reservoirs need constant monitoring due to the large volume of artificially dammed water. Images from remote sensing can provide reliable information concerning water bodies. In this paper, we use remote sensing imagery to monitor the Sobradinho dam in three different epochs. The objective was to verify quantitatively the area of the dam's surface reduced due to the drought of 2015, which was considered the worst in history. The approach used water surface area estimations from bands of Landsat5 and Landsat8 satellites which highlight water bodies better from other features present on surface of the Earth. Through the techniques of growth region and normalized difference water index (NDWI), we determined the surface area of the reservoir in 2011 and calculated the decrease caused by the drought. By analyzing the numbers provided by the results it is possible to estimate how the Sobradinho reservoir has been affected by the drastic drought. The results show that the Landsat images enable the monitoring of large reservoirs. Bearing in mind that monitoring is a primary and indispensable tool, not only for technical study, but also for economic and environmental research, it can help establish planning projects and water administration strategies for future decisions about the hydrical resource priority.

  6. Exploring the link between drought indicators and impacts

    NASA Astrophysics Data System (ADS)

    Bachmair, S.; Kohn, I.; Stahl, K.

    2015-06-01

    Current drought monitoring and early warning systems use different indicators for monitoring drought conditions and apply different indicator thresholds and rules for assigning drought intensity classes or issue warnings or alerts. Nevertheless, there is little knowledge on the meaning of different hydro-meteorologic indicators for impact occurrence on the ground. To date, there have been very few attempts to systematically characterize the indicator-impact relationship owing to sparse and patchy data on drought impacts. The newly established European Drought Impact report Inventory (EDII) offers the possibility to investigate this linkage. The aim of this study was to explore the link between hydro-meteorologic indicators and drought impacts for the case study area Germany and thus to test the potential of qualitative impact data for evaluating the performance of drought indicators. As drought indicators two climatological drought indices - the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) - as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis between monthly time series of indicator and impact data at the federal state level, and between spatial patterns for selected drought events. The analysis clearly revealed a significant moderate to strong correlation for some states and drought events allowing for an intercomparison of the performance of different drought indicators. Important findings were strongest correlation for intermediate accumulation periods of SPI and SPEI, a slightly better performance of SPEI versus SPI, and a similar performance of streamflow percentiles to SPI in many cases. Apart from these commonalities, the analysis also exposed differences among federal states and drought events, suggesting that the linkage is time variant and

  7. 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.

  8. Applications of neural networks to monitoring and decision making in the operation of nuclear power plants. Summary

    SciTech Connect

    Uhrig, R.E. |

    1990-12-31

    Application of neural networks to monitoring and decision making in the operation of nuclear power plants is being investigated under a US Department of Energy sponsored program at the University of Tennessee. Projects include the feasibility of using neural networks for the following tasks: (1) diagnosing specific abnormal conditions or problems in nuclear power plants, (2) detection of the change of mode of operation of the plant, (3) validating signals coming from detectors, (4) review of ``noise`` data from TVA`s Sequoyah Nuclear Power Plant, and (5) examination of the NRC`s database of ``Letter Event Reports`` for correlation of sequences of events in the reported incidents. Each of these projects and its status are described briefly in this paper. This broad based program has as its objective the definition of the state-of-the-art in using neural networks to enhance the performance of commercial nuclear power plants.

  9. 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

  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. Improved monitoring framework for local planning in the water, sanitation and hygiene sector: From data to decision-making.

    PubMed

    Garriga, Ricard Giné; de Palencia, Alejandro Jiménez Fdez; Foguet, Agustí Pérez

    2015-09-01

    Today, a vast proportion of people still lack a simple pit latrine and a source of safe drinking water. To help end this appalling state of affairs, there is a pressing need to provide policymakers with evidences which may be the basis of effective planning, targeting and prioritization. Two major challenges often hinder this process: i) lack of reliable data to identify which areas are most in need; and ii) inadequate instruments for decision-making support. In tackling previous shortcomings, this paper proposes a monitoring framework to compile, analyze, interpret and disseminate water, sanitation and hygiene information. In an era of decentralization, where decision-making moves to local governments, we apply such framework at the local level. The ultimate goal is to develop appropriate tools for decentralized planning support. To this end, the study first implements a methodology for primary data collection, which combines the household and the waterpoint as information sources. In doing so, we provide a complete picture of the context in which domestic WASH services are delivered. Second, the collected data are analyzed to underline the emerging development challenges. The use of simple planning indicators serves as the basis to i) reveal which areas require policy attention, and to ii) identify the neediest. Third, a classification process is proposed to prioritize among various populations. Three different case studies from East and Southern African countries are presented. Results indicate that accurate and comprehensive data, if adequately exploited through simple instruments, may be the basis of effective targeting and prioritization, which are central to sector planning. The application of the proposed framework in the real world, however, is to a certain extent elusive; and we point out to conclude two specific challenges that remain unaddressed, namely the upgrade of existing decision-making processes to enhance transparency and inclusiveness, and the

  12. Routine Outcome Monitoring and Clinical Decision-Making in Forensic Psychiatry Based on the Instrument for Forensic Treatment Evaluation

    PubMed Central

    van der Veeken, Frida C. A.

    2016-01-01

    Background Rehabilitation in forensic psychiatry is achieved gradually with different leave modules, in line with the Risk Need Responsivity model. A forensic routine outcome monitoring tool should measure treatment progress based on the rehabilitation theory, and it should be predictive of important treatment outcomes in order to be usable in decision-making. Therefore, this study assesses the predictive validity for both positive (i.e., leave) and negative (i.e., inpatient incidents) treatment outcomes with the Instrument for Forensic Treatment Evaluation (IFTE). Methods Two-hundred and twenty-four patients were included in this study. ROC analyses were conducted with the IFTE factors and items for three leave modules: guided, unguided and transmural leave for the whole group of patients. Predictive validity of the IFTE for aggression in general, physical aggression specifically, and urine drug screening (UDS) violations was assessed for patients with the main diagnoses in Dutch forensic psychiatry, patients with personality disorders and the most frequently occurring co-morbid disorders: those with combined personality and substance use disorders. Results and Conclusions Results tentatively imply that the IFTE has a reasonable to good predictive validity for inpatient aggression and a marginal to reasonable predictive value for leave approvals and UDS violations. The IFTE can be used for information purposes in treatment decision-making, but reports should be interpreted with care and acknowledge patients’ personal risk factors, strengths and other information sources. PMID:27517721

  13. Development of a new composite drought index for multivariate drought assessment

    NASA Astrophysics Data System (ADS)

    Waseem, Muhammad; Ajmal, Muhammad; Kim, Tae-Woong

    2015-08-01

    Comprehensibly considering all physical forms of agricultural, hydrological, and meteorological drought is essential to develop reliable monitoring and prediction indices for the proper assessment of drought. This consideration encouraged to develop and evaluate a multivariate composite drought index (CDI) that considers all possible variables related to individual types of drought. The proposed CDI was primarily based on the weighted similarity measure (entropy weighted Euclidian distance) and the anomaly from the possible wettest and driest conditions of the selected study region (sub basin of Han River, South Korea). The CDI time series identified 2008-2009 as the driest year, while May 2008 was the driest month within the selected period (2003-2011). The comparative analysis revealed that the CDI monthly time series had a significant correlation with the aggregate drought index (ADI). In addition, in comparison with the single variable-based indices i.e., the standardized precipitation index (SPI) and the streamflow drought index (SDI), the CDI comprehensively responded to variability embedded in the individual drought attributes. Moreover, it was concluded that the developed CDI provided a physically sound, temporally flexible and unbiased index that can be directly associated with all possible variants and linked to the climate conditions of the study region without considering any feature extraction technique.

  14. The 25 years long drought in Sahel and its impacts on ecosystems: Long term vegetation monitoring from the sky and on the ground

    NASA Astrophysics Data System (ADS)

    Dardel, Cecile; Kergoat, Laurent; Hiernaux, Pierre; Mougin, Eric; Grippa, Manuela; Tucker, Compton Jim

    2013-04-01

    The Sahel region is known to be very sensitive to climatic fluctuations. Precipitation interannual variability has immediate and strong consequences on water resources, vegetation production, all affecting human populations. All along its history, Sahel had to face extreme climatic events. In the recent past, a 25 years period of persistent drought jeopardized the ecosystems equilibrium. Indeed, from the 1970's to the mid 1990's, precipitations were strongly and repeatedly below average. A debate has grown for years in the scientific community about the evolving trend of ecosystem in Sahel: is there desertification, or rehabilitation indicated by a "re-greening" taking place since the 1980's, as observed on satellite data by many scientists? To answer these questions, NDVI (Normalized Difference Vegetation Index) time series derived from NOAA/AVHRR are analyzed and compared to field measurements of the herbaceous aboveground mass, tree inventory and crop phytomass collected in Mali and Niger, from 1984 to 2011 and 1994 to 2011 respectively. The GIMMS-3g NDVI trends analysis from 1981 to 2011 show positive and significant slope values over almost every part of the Sahel, except for western Niger and central Sudan, thus reinforcing the "re-greening" hypothesis. Field observations are in good agreement with satellite data. A positive trend is observed over the Gourma in Mali, particularly for periods beginning in the 1980's, showing the ecosystem resilience to drought. A similar recovery is observed in western Niger, but only up to the mid 1990's, then the trend turns negative without being explained by rainfall. While the Gourma is mainly a pastoral land, western Niger is an agro-pastoral region in which cropped surfaces expanded widely over the last decades. For both regions, the re-greening trends are mainly observed on sandy soils, while erosion processes have been observed on shallow soil surfaces, inducing increased run-off and decrease in vegetation cover to

  15. Decision deadlines and uncertainty monitoring: the effect of time constraints on uncertainty and perceptual responses.

    PubMed

    Zakrzewski, Alexandria C; Coutinho, Mariana V C; Boomer, Joseph; Church, Barbara A; Smith, J David

    2014-06-01

    The behavioral uncertainty response has grounded the study of animal metacognition and influenced the study of human psychophysics. However, the interpretation of this response is debated--especially whether it is a behavioral index of metacognition. The authors advanced this interpretation using the dissociative technique of response deadlines. Uncertainty responding, if it is higher level or metacognitive, should depend on a slower, more controlled decisional process and be more vulnerable to time constraints. Humans performed sparse-uncertain-dense or sparse-middle-dense discriminations in which, respectively, they could decline difficult trials or positively identify middle stimuli. Uncertainty responses were sharply and selectively reduced under a decision deadline, as compared to primary perceptual responses (i.e., "sparse," "middle," and "dense" responses). This dissociation suggests that the uncertainty response does reflect a higher-level, decisional response. It grants the uncertainty response a distinctive psychological role in its task and encourages an interpretation of this response as an elemental behavioral index of uncertainty that deserves continuing research. PMID:24072596

  16. Decision Deadlines and Uncertainty Monitoring: The effect of time constraints on uncertainty and perceptual responses

    PubMed Central

    Zakrzewski, Alexandria C.; Coutinho, Mariana V. C.; Boomer, Joseph; Church, Barbara A.; Smith, J. David

    2013-01-01

    The behavioral uncertainty response has grounded the study of animal metacognition and influenced the study of human psychophysics. However, the interpretation of this response is debated—especially whether it is a behavioral index of metacognition. The authors advanced this interpretation using the dissociative technique of response deadlines. Uncertainty responding, if higher level or metacognitive, should depend on a slower, more controlled decisional process and be more vulnerable to time constraints. Humans performed sparse-uncertain-dense or sparse-middle-dense discriminations within which, respectively, they could decline difficult trials or positively identify middle stimuli. Uncertainty responses were sharply and selectively reduced under a decision deadline compared to primary perceptual responses (i.e., sparse, middle, and dense responses). This dissociation suggests that the uncertainty response does reflect a higher-level, decisional response. It grants the uncertainty response a distinctive psychological role in its task and encourages its interpretation as an elemental behavioral index of uncertainty that deserves continuing research. PMID:24072596

  17. Drought Tolerance in Wheat

    PubMed Central

    Prodhan, Zakaria Hossain; Faruq, Golam

    2013-01-01

    Drought is one of the most important phenomena which limit crops' production and yield. Crops demonstrate various morphological, physiological, biochemical, and molecular responses to tackle drought stress. Plants' vegetative and reproductive stages are intensively influenced by drought stress. Drought tolerance is a complicated trait which is controlled by polygenes and their expressions are influenced by various environmental elements. This means that breeding for this trait is so difficult and new molecular methods such as molecular markers, quantitative trait loci (QTL) mapping strategies, and expression patterns of genes should be applied to produce drought tolerant genotypes. In wheat, there are several genes which are responsible for drought stress tolerance and produce different types of enzymes and proteins for instance, late embryogenesis abundant (lea), responsive to abscisic acid (Rab), rubisco, helicase, proline, glutathione-S-transferase (GST), and carbohydrates during drought stress. This review paper has concentrated on the study of water limitation and its effects on morphological, physiological, biochemical, and molecular responses of wheat with the possible losses caused by drought stress. PMID:24319376

  18. Drought and pasture management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought is a common feature of every landscape and can last from a few months to several years. According to the Federal Emergency Management Agency (FEMA), droughts are the most costly natural hazard affecting the United States costing 6 to 8 billion dollars annually. Mitigating the impacts of dr...

  19. Drought tolerance in wheat.

    PubMed

    Nezhadahmadi, Arash; Prodhan, Zakaria Hossain; Faruq, Golam

    2013-01-01

    Drought is one of the most important phenomena which limit crops' production and yield. Crops demonstrate various morphological, physiological, biochemical, and molecular responses to tackle drought stress. Plants' vegetative and reproductive stages are intensively influenced by drought stress. Drought tolerance is a complicated trait which is controlled by polygenes and their expressions are influenced by various environmental elements. This means that breeding for this trait is so difficult and new molecular methods such as molecular markers, quantitative trait loci (QTL) mapping strategies, and expression patterns of genes should be applied to produce drought tolerant genotypes. In wheat, there are several genes which are responsible for drought stress tolerance and produce different types of enzymes and proteins for instance, late embryogenesis abundant (lea), responsive to abscisic acid (Rab), rubisco, helicase, proline, glutathione-S-transferase (GST), and carbohydrates during drought stress. This review paper has concentrated on the study of water limitation and its effects on morphological, physiological, biochemical, and molecular responses of wheat with the possible losses caused by drought stress. PMID:24319376

  20. 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.

  1. 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.

  2. Combined use of meteorological drought indices at multi-time scales for improving hydrological drought detection.

    PubMed

    Zhu, Ye; Wang, Wen; Singh, Vijay P; Liu, Yi

    2016-11-15

    Prediction of hydrological drought in the absence of hydrological records is of great significance for water resources management and risk assessment. In this study, two meteorological drought indices, including standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) calculated at different time scales (1 to 12months), were analyzed for their capabilities in detecting hydrological droughts. The predictive skills of meteorological drought indices were assessed through correlation analysis, and two skill scores, i.e. probability of detection (POD) and false alarm rate (FAR). When used independently, indices of short time scales generally performed better than did those of long time scales. However, at least 31% of hydrological droughts were still missed in view of the peak POD score (0.69) of a single meteorological drought index. Considering the distinguished roles of different time scales in explaining hydrological droughts with disparate features, an optimization approach of blending SPI/SPEI at multiple time scales was proposed. To examine the robustness of the proposed method, data of 1964-1990 was used to establish the multiscalar index, then validate during 2000-2010. Results showed that POD exhibited a significant increase when more than two time scales were used, and the best performances were found when blending 8 time scales of SPI and 9 for SPEI, with the corresponding values of 0.82 and 0.85 for POD, 0.205 and 0.21 for FAR, in the calibration period, and even better performance in the validation period. These results far exceeded the performance of any single meteorological drought index. This suggests that when there is lack of streamflow measurements, blending climatic information of multiple time scales to jointly monitor hydrological droughts could be an alternative solution. PMID:27450249

  3. Drought prediction using GRACE observation and NOAH model simulation

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Wu, J.; Castle, E.

    2012-12-01

    Drought causes severe impacts on agricultural production, economics and society, with annual loss about $6-8 billion in US alone. It is critical to develop drought predicting capability because drought develops more slowly than other disasters like floods and hurricanes and it is hard to recognize drought until it becomes severe. Gravity Recovery and Climate Experiment (GRACE) measures changes in the Earth's gravity. One product derived from GRACE data is the monthly terrestrial water storage over large scale, which has been used for drought monitoring. NOAH model, as a part of GLDAS land surface modeling system, integrates satellite and ground base observations to simulate a variety of geophysical variables. NOAH derived soil moisture estimates have also been used in drought monitoring. A new drought prediction method was developed with to forecast drought occurrence one month in advance. The prediction method combines two water indices, Total Storage Deficit Index (TSDI) from GRACE terrestrial water storage estimates and Soil Moisture Deficit Index (SMDI) from NOAH modeled soil moisture content. Because the two indices react differently to the same climatic forcing, with a delay in TSDI typically observed, confirmation between each other could indicate a high probability of occurring. Drought condition is predicted by comparing the combined index with the historical monthly water surplus/deficit. Evaluation over the Red River Valley of the North showed that the method was able to predict a severe drought occurring during 2006-2008 and the current drought that we are experiencing now. Currently, we are evaluating the method over a much larger scale.

  4. Under which conditions, additional monitoring data are worth gathering for improving decision making? Application of the VOI theory in the Bayesian Event Tree eruption forecasting framework

    NASA Astrophysics Data System (ADS)

    Loschetter, Annick; Rohmer, Jérémy

    2016-04-01

    Standard and new generation of monitoring observations provide in almost real-time important information about the evolution of the volcanic system. These observations are used to update the model and contribute to a better hazard assessment and to support decision making concerning potential evacuation. The framework BET_EF (based on Bayesian Event Tree) developed by INGV enables dealing with the integration of information from monitoring with the prospect of decision making. Using this framework, the objectives of the present work are i. to propose a method to assess the added value of information (within the Value Of Information (VOI) theory) from monitoring; ii. to perform sensitivity analysis on the different parameters that influence the VOI from monitoring. VOI consists in assessing the possible increase in expected value provided by gathering information, for instance through monitoring. Basically, the VOI is the difference between the value with information and the value without additional information in a Cost-Benefit approach. This theory is well suited to deal with situations that can be represented in the form of a decision tree such as the BET_EF tool. Reference values and ranges of variation (for sensitivity analysis) were defined for input parameters, based on data from the MESIMEX exercise (performed at Vesuvio volcano in 2006). Complementary methods for sensitivity analyses were implemented: local, global using Sobol' indices and regional using Contribution to Sample Mean and Variance plots. The results (specific to the case considered) obtained with the different techniques are in good agreement and enable answering the following questions: i. Which characteristics of monitoring are important for early warning (reliability)? ii. How do experts' opinions influence the hazard assessment and thus the decision? Concerning the characteristics of monitoring, the more influent parameters are the means rather than the variances for the case considered

  5. 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.

  6. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    NASA Astrophysics Data System (ADS)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2013-01-01

    Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

  7. Drought and resprouting plants

    SciTech Connect

    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.

    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 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. 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.

  8. Drought and resprouting plants

    DOE PAGESBeta

    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; et al

    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 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 ecosystemsmore » 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

  9. Drought - A Global Assessment

    NASA Astrophysics Data System (ADS)

    Lackner, S.; Barnwal, P.; von der Goltz, J.

    2013-12-01

    We investigate the lasting effects of early childhood exposure to drought on economic and health outcomes in a large multi-country dataset. By pooling all Demographic and Health Survey rounds for which household geocodes are available, we obtain an individual-level dataset covering 47 developing countries. Among other impact measures, we collect infant and child mortality data from 3.3m live births and data on stunting and wasting for 1.2m individuals, along with data on education, employment, wealth, marriage and childbearing later in life for similarly large numbers of respondents. Birth years vary from 1893 to 2012. We seek to improve upon existing work on the socio-economic impact of drought in a number of ways. First, we introduce from the hydrological literature a drought measure, the Standardized Precipitation Index (SPI), that has been shown to closely proxy the Palmer drought index, but has far less demanding data requirements, and can be obtained globally and for long time periods. We estimate the SPI for 110 years on a global 0.5° grid, which allows us to assign drought histories to the geocoded individual data. Additionally, we leverage our large sample size to explicitly investigate both how drought impacts have changed over time as adaptation occurred at a varying pace in different locations, and the role of the regional extent of drought in determining impacts.

  10. 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

  11. 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.

    2015-09-01

    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 which 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 ("random forest"), using Germany and the UK (the most data-rich countries in the EDII) as a testbed. As candidate indicators we chose two meteorological indicators (Standardized Precipitation Index (SPI) and Standardized Precipitation Evaporation Index (SPEI)) and two hydrological indicators. The analysis revealed that accumulation periods of SPI and SPEI best linked to impact occurrence are longer for the UK compared with Germany, but there is variability within each country, among impact categories and, to some degree, seasons. The median of regression tree splitting values, which we regard as estimates of thresholds of impact occurrence, was around -1 for SPI and SPEI in the UK; distinct differences between northern/northeastern vs. southern/central regions were found for Germany. Predictions with the ensemble regression tree approach yielded reasonable results for regions with good impact data coverage. The predictions

  12. What does drought look like?

    NASA Astrophysics Data System (ADS)

    Lloyd-Hughes, Benjamin

    2013-04-01

    Drought is commonly portrayed using images of cracked earth, dry dams and empty river beds. However, these 2-dimensional representations illustrate the impact of drought rather than drought itself and ignore the rich 4-dimensional spatio-temporal variablity which characterises drought as a natural hazard. Improved visualisations of drought are needed to increase public understanding and assist the research community in understanding its drivers. WebGL is explored as a medium for contructing interactive drought graphics that go beyond displaying drought impacts and address the multi-dimensionality of the problem.

  13. Discussion of GPS/RTK in fighting drought

    NASA Astrophysics Data System (ADS)

    Wang, Qinglin; Fang, Liwei; Li, Kezhao; Zang, Pengzhan

    2009-07-01

    In this spring, the worst drought to hit China's northern wheat-growing belt in half a century. How to make proper decision to fight drought is a vital problem to Chinese government. Of course, this is a complicated problem for many factors involved. But for surveyor, we must provide the drought area, different drought levels and position information quickly. Real Time Kinematic (RTK) satellite navigation is a technique used in land survey and in hydrographic survey based on the use of carrier phase measurements of the GPS, GLONASS and/or Galileo signals where a single reference station provides the real-time corrections of even to a centimetre level of accuracy. In this paper, we discuss the application of GPS technology in fighting drought. Firstly, we introduce the RTK technology and its applications in other field. Secondly, according to the requirement of fighting drought, we give the scheme of how to get the information of drought area, different drought levels rapidly. Thirdly, we discuss the technology of real-time positioning to artificial rainfall using aeroplane.

  14. [Temporal and spatial distribution of rice drought in Southwest China].

    PubMed

    Zhang, Jian-ping; Liu, Zong-yuan; He, Yong-kun; Luo, Hong-xia; Wang, Jing

    2015-10-01

    Considering the characteristics of rice production and climate conditions in Southwest China, an agricultural drought monitoring model based on wetness index anomaly rate (Mp) by calculating the variation of deviation from average values of relative humid index was established, and was used to analyze the spatial-temporal distribution characteristics of the rice drought during the growth season in Southwest China in the past 50 years (1961-2010). The applicability of the Mp model in Southwest China was verified by using this model to monitor the rice drought. The result showed there was a decreasing trend in the frequency of rice drought in term of the decadal variability. The areas with high drought risk mainly concentrated in northwestern and mid-eastern Yunnan Province, eastern Sichuan Basin, northeastern Chongqing City, and southeastern Guizhou Province. The drought frequency was highest at the stage from transplanting to tasseling, followed by the stage from grain filling to maturity, and was lowest at the stage from tasseling to grain filling. Mp was suitable for monitoring the rice drought in Southwest China, and could be used as a reference for the rice planting areas without irrigation data. PMID:26995919

  15. 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.

  16. Drought Characterisation and the Application of Indices in UK Water Resource Management

    NASA Astrophysics Data System (ADS)

    Lennard, Amy; Macdonald, Neil

    2016-04-01

    Drought is a complex phenomenon, occurring in most climatic zones, including both high and low rainfall regions. Recent drought events (2004-2006 & 2010-2012) in the UK have highlighted a continued vulnerability to this hazard. The period 2010-2012 was characterised by departures from typical seasonal climatic conditions, resulting in a severe drought, which had a significant impact on water resources in parts of the UK. Recent droughts highlight the need for better understanding of extreme drought events, particularly from a water resource perspective. The UK has a wealth of long climate series that are under used for water resource management planning. Standardised drought indicators offer a potential monitoring and management tool for operational water resource management. However, the application of these metrics for operational water resource management needs further investigation, particularly links between meteorological drought indices, streamflow, groundwater and water supply systems. This work uses standardised drought indices to investigate the propagation from meteorological drought to hydrological drought using observed data from rivers, aquifers and reservoirs 2013 within a 21,000km2 water supply region serving 7.4 million people. In order to develop a better understanding of the links between drought indices and observed drought impacts. Exploring how meteorological drought indicators link to the water supply region helps build an understanding of their utility for water resource management.

  17. From meteorological to hydrological drought using standardised indicators

    NASA Astrophysics Data System (ADS)

    Barker, Lucy J.; Hannaford, Jamie; Chiverton, Andrew; Svensson, Cecilia

    2016-06-01

    Drought monitoring and early warning (M & EW) systems are a crucial component of drought preparedness. M & EW systems typically make use of drought indicators such as the Standardised Precipitation Index (SPI), but such indicators are not widely used in the UK. More generally, such tools have not been well developed for hydrological (i.e. streamflow) drought. To fill these research gaps, this paper characterises meteorological and hydrological droughts, and the propagation from one to the other, using the SPI and the related Standardised Streamflow Index (SSI), with the objective of improving understanding of the drought hazard in the UK. SPI and SSI time series were calculated for 121 near-natural catchments in the UK for accumulation periods of 1-24 months. From these time series, drought events were identified and for each event, the duration and severity were calculated. The relationship between meteorological and hydrological drought was examined by cross-correlating the 1-month SSI with various SPI accumulation periods. Finally, the influence of climate and catchment properties on the hydrological drought characteristics and propagation was investigated. Results showed that at short accumulation periods meteorological drought characteristics showed little spatial variability, whilst hydrological drought characteristics showed fewer but longer and more severe droughts in the south and east than in the north and west of the UK. Propagation characteristics showed a similar spatial pattern with catchments underlain by productive aquifers, mostly in the south and east, having longer SPI accumulation periods strongly correlated with the 1-month SSI. For catchments in the north and west of the UK, which typically have little catchment storage, standard-period average annual rainfall was strongly correlated with hydrological drought and propagation characteristics. However, in the south and east, catchment properties describing storage (such as base flow

  18. Contributions to uncertainty in projections of future drought under climate change scenarios

    NASA Astrophysics Data System (ADS)

    Taylor, I. H.; Burke, E.; McColl, L.; Falloon, P.; Harris, G. R.; McNeall, D.

    2012-11-01

    Drought is a cumulative event, often difficult to define and involving wide reaching consequences for agriculture, ecosystems, water availability, and society. Understanding how the occurrence of drought may change in the future and which sources of uncertainty are dominant can inform appropriate decisions to guide drought impacts assessments. Uncertainties in future projections of drought arise from several sources and our aim is to understand how these sources of uncertainty contribute to future projections of drought. We consider four sources of uncertainty; climate model uncertainty associated with future climate projections, future emissions of greenhouse gases (future scenario uncertainty), type of drought (drought index uncertainty) and drought event definition (threshold uncertainty). Three drought indices (the Standardised Precipitation Index (SPI), Soil Moisture Anomaly (SMA) and Palmer Drought Severity Index (PDSI)) are calculated for the A1B and RCP2.6 future emissions scenarios using monthly model output from a 57 member perturbed parameter ensemble of climate simulations of the HadCM3C Earth system model, for the baseline period, 1961-1990, and the period 2070-2099 (representing the 2080s). We consider where there are significant increases or decreases in the proportion of time spent in drought in the 2080s compared to the baseline and compare the effects from the four sources of uncertainty. Our results suggest that, of the included uncertainty sources, choice of drought index is the most important factor influencing uncertainty in future projections of drought (60%-85% of total included uncertainty). There is a greater range of uncertainty between drought indices than that between the mitigation scenario RCP2.6 and the A1B emissions scenario (5%-6% in the 2050s to 17%-18% in the 2080s) and across the different model variants in the ensemble (9%-17%). Choice of drought threshold has the least influence on uncertainty in future drought projections (0

  19. High-frequency monitoring of nitrogen and phosphorus response in three rural catchments to the end of the 2011-2012 drought in England

    NASA Astrophysics Data System (ADS)

    Outram, F. N.; Lloyd, C. E. M.; Jonczyk, J.; Benskin, C. McW. H.; Grant, F.; Perks, M. T.; Deasy, C.; Burke, S. P.; Collins, A. L.; Freer, J.; Haygarth, P. M.; Hiscock, K. M.; Johnes, P. J.; Lovett, A. L.

    2014-09-01

    This paper uses high-frequency bankside measurements from three catchments selected as part of the UK government-funded Demonstration Test Catchments (DTC) project. We compare the hydrological and hydrochemical patterns during the water year 2011-2012 from the Wylye tributary of the River Avon with mixed land use, the Blackwater tributary of the River Wensum with arable land use and the Newby Beck tributary of the River Eden with grassland land use. The beginning of the hydrological year was unusually dry and all three catchments were in states of drought. A sudden change to a wet summer occurred in April 2012 when a heavy rainfall event affected all three catchments. The year-long time series and the individual storm responses captured by in situ nutrient measurements of nitrate and phosphorus (total phosphorus and total reactive phosphorus) concentrations at each site reveal different pollutant sources and pathways operating in each catchment. Large storm-induced nutrient transfers of nitrogen and or phosphorus to each stream were recorded at all three sites during the late April rainfall event. Hysteresis loops suggested transport-limited delivery of nitrate in the Blackwater and of total phosphorus in the Wylye and Newby Beck, which was thought to be exacerbated by the dry antecedent conditions prior to the storm. The high rate of nutrient transport in each system highlights the scale of the challenges faced by environmental managers when designing mitigation measures to reduce the flux of nutrients to rivers from diffuse agricultural sources. It also highlights the scale of the challenge in adapting to future extreme weather events under a changing climate.

  20. North American Drought Projections

    NASA Video Gallery

    Droughts in the Southwest and Central Plains of the United States in the second half of the 21st century could be drier and longer than anything humans have seen in those regions in the last 1,000 ...

  1. Hydroclimatological influences on recently increased droughts in China's largest freshwater lake

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Wu, G.

    2016-01-01

    Lake droughts are the consequence of climatic, hydrologic and anthropogenic influences. Quantification of droughts and estimation of the contributions from the individual factors are essential for understanding drought features and their causation structure. This is also important for policymakers to make effective adaption decisions, especially under changing climate. This study examines Poyang Lake, China's largest freshwater lake, which has been undergoing drastic hydrological alternation in the past decade. Standardized lake stage is used to identify and quantify the lake droughts, and hydroclimatic contributions are determined with a water budget analysis, in which absolute deficiency is defined in reference to normal hydrologic conditions. Our analyses demonstrate that in the past decade the lake droughts worsened in terms of duration, frequency, intensity and severity. Hydroclimatic contributions to each individual drought varied between droughts, and the overall contribution to the lake droughts in the past decade came from decreased inflow, increased outflow, and reduced precipitation and increased evapotranspiration in the lake region. The decreased inflow resulted mainly from reduced precipitation and less from increased evapotranspiration over the Poyang Lake basin. The increased outflow was attributable to the weakened blocking effects of the Yangtze River, which the Three Gorges Dam (TGD) established upstream. The TGD impoundments were not responsible for the increased number of drought events, but they may have intensified the droughts and changed the frequency of classified droughts. However, the TGD contribution is limited in comparison with hydroclimatic influences. Hence, the recently increased droughts were due to hydroclimatic effects, with a less important contribution from anthropogenic influences.

  2. The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

    NASA Technical Reports Server (NTRS)

    Cacas, Joseph; Glaser, John; Copenhaver, Kenneth; May, George; Stephens, Karen

    2008-01-01

    The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

  3. Assessing and monitoring the risk of desertification in Dobrogea, Romania, using Landsat data and decision tree classifier.

    PubMed

    Vorovencii, Iosif

    2015-04-01

    The risk of the desertification of a part of Romania is increasingly evident, constituting a serious problem for the environment and the society. This article attempts to assess and monitor the risk of desertification in Dobrogea using Landsat Thematic Mapper (TM) satellite images acquired in 1987, 1994, 2000, 2007 and 2011. In order to assess the risk of desertification, we used as indicators the Modified Soil Adjustment Vegetation Index 1 (MSAVI1), the Moving Standard Deviation Index (MSDI) and the albedo, indices relating to the vegetation conditions, the landscape pattern and micrometeorology. The decision tree classifier (DTC) was also used on the basis of pre-established rules, and maps displaying six grades of desertification risk were obtained: non, very low, low, medium, high and severe. Land surface temperature (LST) was also used for the analysis. The results indicate that, according to pre-established rules for the period of 1987-2011, there are two grades of desertification risk that have an ascending trend in Dobrogea, namely very low and medium desertification. An investigation into the causes of the desertification risk revealed that high temperature is the main factor, accompanied by the destruction of forest shelterbelts and of the irrigation system and, to a smaller extent, by the fragmentation of agricultural land and the deforestation in the study area. PMID:25800368

  4. A new indicator in early drought diagnosis of cucumber with chlorophyll fluorescence imaging

    NASA Astrophysics Data System (ADS)

    Wang, Heng; Li, Haifeng; Xu, Liang; Liu, Xu

    2015-05-01

    Crop population growth information can more fully reflect the state of crop growth, eliminate individual differences, and reduce error in judgment. We have built a suitable plant population growth information online monitoring system with the plant chlorophyll fluorescence and spectral scanning imaging to get the crop growth status. On the basis of the fluorescence image detection, we have studied the early drought diagnosis of cucumber. The typical chlorophyll fluorescence parameters can not reflect the drought degree significantly. We define a new indication parameter (DI). With the drought deepening, DI declines. DI can enlarge the early manifestation of cucumber drought (3-5 days), indicate more significantly in the early drought diagnosis of cucumber.

  5. 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.

  6. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. 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.

  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

    2015-07-01

    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

  11. Developing system robustness analysis for drought risk management: an application on a water supply reservoir

    NASA Astrophysics Data System (ADS)

    Mens, M. J. P.; Gilroy, K.; Williams, D.

    2015-08-01

    Droughts will likely become more frequent, greater in magnitude and longer in duration in the future due to climate change. Already in the present climate, a variety of drought events may occur with different exceedance frequencies. These frequencies are becoming more uncertain due to climate change. Many methods in support of drought risk management focus on providing insight into changing drought frequencies, and use water supply reliability as a key decision criterion. In contrast, robustness analysis focuses on providing insight into the full range of drought events and their impact on a system's functionality. This method has been developed for flood risk systems, but applications on drought risk systems are lacking. This paper aims to develop robustness analysis for drought risk systems, and illustrates the approach through a case study with a water supply reservoir and its users. We explore drought characterization and the assessment of a system's ability to deal with drought events, by quantifying the severity and socio-economic impact of a variety of drought events, both frequent and rare ones. Furthermore, we show the effect of three common drought management strategies (increasing supply, reducing demand and implementing hedging rules) on the robustness of the coupled water supply and socio-economic system. The case is inspired by Oologah Lake, a multipurpose reservoir in Oklahoma, United States. Results demonstrate that although demand reduction and supply increase may have a comparable effect on the supply reliability, demand reduction may be preferred from a robustness perspective. To prepare drought management plans for dealing with current and future droughts, it is thus recommended to test how alternative drought strategies contribute to a system's robustness rather than relying solely on water reliability as the decision criterion.

  12. Developing system robustness analysis for drought risk management: an application on a water supply reservoir

    NASA Astrophysics Data System (ADS)

    Mens, M. J. P.; Gilroy, K.; Williams, D.

    2015-01-01

    Droughts will likely become more frequent, of greater magnitude and of longer duration in the future due to climate change. Already in the present climate, a variety of drought events may occur with different exceedance frequencies. These frequencies are becoming more uncertain due to climate change. Many methods in support of drought risk management focus on providing insight into changing drought frequencies, and use water supply reliability as key decision criterion. In contrast, robustness analysis focuses on providing insight into the full range of drought events and their impact on a system's functioning. This method has been developed for flood risk systems, but applications on drought risk systems are lacking. This paper aims to develop robustness analysis for drought risk systems, and illus