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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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 and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

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 warning information systems to support preparedness and adaptation decisions in a changing climate.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate that GIDMaPS advances our drought monitoring and prediction capabilities through integration of multiple data and indicators.

Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

USGS Publications Warehouse

Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.

2017-01-01

Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the VegDRI-Canada map with the Canadian Drought Monitor (CDM), an independent drought indicator, showed that the VegDRI-Canada maps depicted key spatial drought severity patterns during the two targeted drought years consistent with the CDM. In addition, VegDRI-Canada was compared with canola yields in the Prairie Provinces at the regional scale for a period from 2000 to 2014 to evaluate the indices’ applicability for monitoring drought impacts on crop production. The result showed that VegDRI-Canada values had a relatively higher correlation (i.e., r > 0.5) with canola yield for nonirrigated croplands in the Canadian Prairies region in areas where drought is typically a limiting factor on crop growth, but showed a negative relationship in the southeastern Prairie region, where water availability is less of a limiting factor and in some cases a hindrance to crop growth when waterlogging occurs. These initial results demonstrate VegDRI-Canada’s utility for monitoring drought-related vegetation conditions, particularly in drought prone areas. In general, the results indicated that the VegDRI-Canada models showed sensitivity to known agricultural drought events in Canada over the 15-year period mainly for nonirrigated areas.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

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.

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.

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 potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

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 potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

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

NASA Astrophysics Data System (ADS)

Close, S.; Simpson, C.

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

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

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 drought conditions across the United States. It has been used by policy makers to trigger relief programs, by states in their monitoring efforts, and by the media and public through coverage in newspapers and on TV. The DIR has been on-line at the NDMC since 2005; it has more than 14,000 reports and impacts of drought in six basic categories: agriculture, water/energy, environment, fire, social, and other. The most recent activity (currently underway through NOAA funding) is seen in our work with five pilot communities in Illinois, Nebraska, and Oklahoma to establish a new “Drought Ready Community” (DRC) program, developing a community-driven process for integrating place-based planning to reduce vulnerability to drought. Many of these tools have included an extensive iterative process with stakeholders around the country, through means such as workshops, listening sessions, forums, and evaluator networks. The NDMC also serves in an advisory capacity to policy makers and others by providing scientific and policy-relevant information on a variety of drought and water management issues. In moving forward toward a national climate service, the NDMC is well positioned and experienced in helping connect users globally with the latest in “drought services”.

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, NIDIS is working with existing regional and local networks to develop outlook forums as part of an integrated process that involves closer coordination of drought monitoring among federal, state, and local groups; a research component that can address gaps in understanding that are identified in the outlook forum process; a drought information portal (www.drought.gov) for improving communication; an education and outreach component that improves understanding to apply the information; and close coordination with the preparedness community that includes state and local planners for improved mainstreaming of the information into decisions and policies. These components allow for a mutual learning process that encourages critical assessment of the information, builds trust and identifies how information is used to reduce vulnerability and risk associated with the impacts of drought. This process also identifies the key contacts in the region that can maximize dissemination of the information including local media, and provides an ongoing dialogue that allows for feedback and improvement of the process.

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

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

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

Future opportunities and challenges in remote sensing of drought

USGS Publications Warehouse

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

2012-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Future Opportunities and Challenges in Remote Sensing of Drought

NASA Technical Reports Server (NTRS)

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

2011-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

A 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 for early drought warning.

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

NASA Astrophysics Data System (ADS)

Kogan, F.

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

Monitoring of Drought Events in Gorontalo Regency

NASA Astrophysics Data System (ADS)

Koem, S.; Rusiyah

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-05-01

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

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 scales, it is very difficult to improve on the use of climatological forecasts. However, results presented regionally and globally pinpoint several regions in the world where drought onset forecasting is feasible and skilful.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

Kwok Wong, Wai; Hisdal, Hege

2013-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Evaluation of the Performance of Multiple Drought Indices for Tunisia

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

Drought events are frequently described using many different terms; for example, recurring climate phenomena, creeping natural hazards, agricultural disasters, and moisture deficiencies. In addition, droughts operate at many different spatial and temporal scales and affect different societal sectors, making them quite challenging to monitor, map, and assess impacts. Because of these factors, determining drought severity often requires using a convergence of evidence assisted by an analysis of multiple drought indicators. Frequent optical and thermal observations collected by daily polar-orbiting and geostationary satellites allow for regular monitoring of the land surface. In recent decades, with the launching of more advanced sensors and the maturation of remote sensing techniques, a variety of tools have been designed for improved understanding and tracking of drought events as they are occurring. These applications are intended to provide key decision makers with timely geospatial drought information to support various drought planning and mitigation activities. Two such tools highlighted in this study, are the Vegetation Drought Response Index (VegDRI) and the Evaporative Stress Index (ESI). While both indices incorporate satellite-based inputs, they are involved in different modeling approaches and observations from different parts of the electromagnetic spectrum. The VegDRI is a hybrid remote sensing and climate based indicator of drought-induced vegetation stress that combines satellite-based vegetation index observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors with climate-based drought index data and other biophysical parameters (such as land use/land cover type and soil characteristics). VegDRI provides near real-time vegetation drought severity information at relatively higher spatial resolution (1-km2) than traditional climatic drought indices such as the Standardized Precipitation Index (SPI) or the U.S. Drought Monitor (USDM), which tend to depicted broad-scale spatial drought patterns. . The ESI is an indicator of anomalous land-surface evaporation and soil moisture deficiency. The ESI is related to the ratio of actual-to-potential evapotranspiration (ET), where actual ET is estimated with a thermal-infrared (TIR) based surface energy balance algorithm. The ESI product is generated in near-real time at 10-km2 resolution over the continental U.S. using TIR imagery from the Geostationary Operational Environmental Satellites (GOES). Because it does not use precipitation data as an input, it is a valuable complement to existing precipitation-based indices and is readily portable to data-poor regions with sparse ground-based rainfall monitoring networks. In this study, we present an intercomparison of the VegDRI and the ESI for the 2009 growing season, highlighting weekly, monthly, and seasonal patterns of moisture flux from soils and vegetation.

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.

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-making. Since the '90s, analysis tools and models based on meteorological satellites data have been developed within different regional and national initiatives to allow near-real-time monitoring of the cropping season. The software was in general stand-alone applications, transferred to MWGs without continuous user support and updates. Currently MWGs in the Sahel do not have any working operational tool for drought risk identification and forecast, because such tools are by now obsolete from the IT perspective. The challenge and the objective of this work is to provide to MWGs and local end-users an open access/source Crop Risk Zones Monitoring System (CRZ-MS) supporting decision making for drought risk reduction and resilience improvement. A first prototype has been developed for Niger and Mali NMSs, based on a coherent Open Source web-based infrastructure to treat all input and output data in a interoperable, platform-independent and uniform way. The System architecture and functions are based on a agro-meteorological model, running in two different modes: 1) diagnostic mode for the drought monitoring during the agro-pastoral campaign allowing MWGs to identify agricultural drought risk areas in order to support decision making at local and national level in agricultural drought management. This early warning information also represents an input for estimating the nutritional food insecurity, for the identification of potentially vulnerable populations and assessing food crises risks by National EWSs put in place by CILSS with EU, FAO and WFP. 2) predictive mode for "advisory-support" activities to the farmers by the Agricultural Extension Services, in order to implement the most appropriate strategies for minimizing drought risk on crops (i.e. identification of the optimal period of sowing, choice of varieties based on the expected length of the growing season, adoption of suitable cultural practices for soil water management) and to build farmers resilience. To increase the accessibility of appropriate and targeted drought risk information, it is essential to move from generic information to specific advises for end-users at different decision-making levels, bridging the gap between available technology and local users' needs. Thus, advices to farmers are a fundamental component of prevention allowing a better country's preparedness to cope with weather variability.

Introducing seasonal hydro-meteorological forecasts in local water management. First reflections from the Messara site, Crete, Greece.

NASA Astrophysics Data System (ADS)

Koutroulis, Aristeidis; Grillakis, Manolis; Tsanis, Ioannis

2017-04-01

Seasonal prediction is recently at the center of the forecasting research efforts, especially for regions that are projected to be severely affected by global warming. The value of skillful seasonal forecasts can be considerable for many sectors and especially for the agricultural in which water users and managers can benefit to better anticipate against drought conditions. Here we present the first reflections from the user/stakeholder interactions and the design of a tailored drought decision support system in an attempt to bring seasonal predictions into local practice for the Messara valley located in the central-south area of Crete, Greece. Findings from interactions with the users and stakeholders reveal that although long range and seasonal predictions are not used, there is a strong interest for this type of information. The increase in the skill of short range weather predictions is also of great interest. The drought monitoring and prediction tool under development that support local water and agricultural management will include (a) sources of skillful short to medium term forecast information, (b) tailored drought monitoring and forecasting indices for the local groundwater aquifer and rain-fed agriculture, and (c) seasonal inflow forecasts for the local dam through hydrologic simulation to support management of freshwater resources and drought impacts on irrigated agriculture.

Drought Risk Assessment based on Natural and Social Factors

NASA Astrophysics Data System (ADS)

Huang, Jing; Wang, Huimin; Han, Dawei

2015-04-01

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

77 FR 71821 - Agency Information Collection Activities: Submitted for Office of Management and Budget (OMB...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-04

... inform decision-making in a variety of contexts, including agriculture, drought monitoring, and wildfire... Affairs, Attention: Desk Officer for the Department of the Interior via email: ( [email protected] animals respond to environmental variation and changes in weather and climate. Contemporary data collected...

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

NASA Astrophysics Data System (ADS)

Prakash, P.; Harter, T.

2016-12-01

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

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.

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 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 Sonora case. The potential impact of such system is examined considering a number of actions that may be implemented in the water, agricultural and cattle ranching sectors. We conclude that there are great opportunities to reduce the negative impacts of drought if climate information is used. This proposal is part of a project to go from a response to the disaster practice to a prevention policy with the Mexican government and stakeholders. An early warning to face drought may alleviate the difficulties for several sectors in the semiarid regions of Mexico and prepare various socioeconomic sectors to face the potential impacts of climate change.

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

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Molajou, Amir

2017-12-01

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

A Global Drought Observatory for Emergency Response

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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 applications will be demonstrated live during the poster session. Expansion of DroughtView includes future plans to add snow products, phenology data and climate scenarios. Extension of the spatial coverage of the data to other parts of the world is also planned.

An extended multivariate framework for drought monitoring in Mexico

NASA Astrophysics Data System (ADS)

Real-Rangel, Roberto; Pedrozo-Acuña, Adrián; Breña-Naranjo, Agustín; Alcocer-Yamanaka, Víctor

2017-04-01

Around the world, monitoring natural hazards, such as droughts, represents a critical task in risk assessment and management plans. A reliable drought monitoring system allows to identify regions affected by these phenomena so that early response measures can be implemented. In Mexico, this activity is performed using Mexico's Drought Monitor, which is based on a similar methodology as the United States Drought Monitor and the North American Drought Monitor. The main feature of these monitoring systems is the combination of ground-based and remote sensing observations that is ultimately validated by local experts. However, in Mexico in situ records of variables such as precipitation and streamflow are often scarce, or even null, in many regions of the country. Another issue that adds uncertainty in drought monitoring is the arbitrary weight given to each analyzed variable. This study aims at providing an operational framework for drought monitoring in Mexico, based on univariate and multivariate nonparametric standardized indexes proposed in recent studies. Furthermore, the framework has been extended by taking into account the Enhanced Vegetation Index (EVI) for the drought severity assessment. The analyzed variables used for computing the drought indexes are mainly derived from remote sensing (MODIS) and land surface models datasets (NASA MERRA-2). A qualitative evaluation of the results shows that the indexes used are capable of adequately describes the intensity and spatial distribution of past drought documented events.

A component-based system for agricultural drought monitoring by remote sensing.

PubMed

Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

A component-based system for agricultural drought monitoring by remote sensing

PubMed Central

Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China’s Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring. PMID:29236700

Measuring the Value of Earth Observation Information with the Gravity Research and Climate Experiment (GRACE) Satellite

NASA Astrophysics Data System (ADS)

Bernknopf, R.; Kuwayama, Y.; Brookshire, D.; Macauley, M.; Zaitchik, B.; Pesko, S.; Vail, P.

2014-12-01

Determining how much to invest in earth observation technology depends in part on the value of information (VOI) that can be derived from the observations. We design a framework and then evaluate the value-in-use of the NASA Gravity Research and Climate Experiment (GRACE) for regional water use and reliability in the presence of drought. As a technology that allows measurement of water storage, the GRACE Data Assimilation System (DAS) provides information that is qualitatively different from that generated by other water data sources. It provides a global, reproducible grid of changes in surface and subsurface water resources on a frequent and regular basis. Major damages from recent events such as the 2012 Midwest drought and the ongoing drought in California motivate the need to understand the VOI from remotely sensed data such as that derived from GRACE DAS. Our conceptual framework models a dynamic risk management problem in agriculture. We base the framework on information from stakeholders and subject experts. The economic case for GRACE DAS involves providing better water availability information. In the model, individuals have a "willingness to pay" (wtp) for GRACE DAS - essentially, wtp is an expression of savings in reduced agricultural input costs and for costs that are influenced by regional policy decisions. Our hypothesis is that improvements in decision making can be achieved with GRACE DAS measurements of water storage relative to data collected from groundwater monitoring wells and soil moisture monitors that would be relied on in the absence of GRACE DAS. The VOI is estimated as a comparison of outcomes. The California wine grape industry has features that allow it to be a good case study and a basis for extrapolation to other economic sectors. We model water use in this sector as a sequential decision highlighting the attributes of GRACE DAS input as information for within-season production decisions as well as for longer-term water reliability.

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.

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

NASA Astrophysics Data System (ADS)

Kuwayama, Y.; Thompson, A.

2017-12-01

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

Better to Be Active (Rather Than Passive) When Considering How Soil Moisture Can Help Decision Makers

NASA Astrophysics Data System (ADS)

Mace, R.

2016-12-01

As recent events have shown, Texas is a land of drought and flood. Texas experienced the worst one-year drought of record in 2011; the second worst statewide drought of record between 2010 and 2015; and record-breaking floods in the spring of 2015, fall of 2015, and spring of 2016 (with flash droughts occurring during the summers of 2015 and 2016). Soil moisture is one factor that links drought and flood in addressing key policy and management questions: When will soil moisture be high enough to allow groundwater recharge and runoff into reservoirs? When will soil moisture be high enough to cause flash floods with excessive rainfall? After tragic floods in Wimberley in the spring of 2015, Texas is expanding its stream-flow monitoring capabilities and is starting a statewide mesonet called TexMesonet to provide more detailed weather information to flood forecasters but also to provide baseline information on soil moisture for flood, drought, and water conservation purposes. Our hope is that the TexMesonet will help ground-truth SMAP and other remote sensing systems, help improve the National Water Model (a next generation tool for flood forecasting), and spark research into sub-basin soil moisture predictors of runoff which break water-supply droughts or lead to major floods.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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.

Advancements in satellite remote sensing for drought monitoring

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Introduction of Drought Monitoring and Forecasting System based on Real-time Water Information Using ICT

NASA Astrophysics Data System (ADS)

Lee, Y., II; Kim, H. S.; Chun, G.

2016-12-01

There were severe damages such as restriction on water supply caused by continuous drought from 2014 to 2015 in South Korea. Through this drought event, government of South Korea decided to establish National Drought Information Analysis Center in K-water(Korea Water Resources Corporation) and introduce a national drought monitoring and early warning system to mitigate those damages. Drought index such as SPI(Standard Precipitation Index), PDSI(Palmer Drought Severity Index) and SMI(Soil Moisture Index) etc. have been developed and are widely used to provide drought information in many countries. However, drought indexes are not appropriate for drought monitoring and early warning in civilized countries with high population density such as South Korea because it could not consider complicated water supply network. For the national drought monitoring and forecasting of South Korea, `Drought Information Analysis System' (D.I.A.S) which is based on the real time data(storage, flowrate, waterlevel etc.) was developed. Based on its advanced methodology, `DIAS' is changing the paradigm of drought monitoring and early warning systems. Because `D.I.A.S' contains the information of water supply network from water sources to the people across the nation and provides drought information considering the real-time hydrological conditions of each and every water source. For instance, in case the water level of a specific dam declines to predetermined level of caution, `D.I.A.S' will notify people who uses the dam as a source of residential or industrial water. It is expected to provide credible drought monitoring and forecasting information with a strong relationship between drought information and the feelings of people rely on water users by `D.I.A.S'.

Climate related natural hazards management in the vulnerable regions of Uzbekistan - experiences in the frame of projects Climate Risk Management in Uzbekistan (CRM-Uz) and Water in Central Asia (CAWa)

NASA Astrophysics Data System (ADS)

Merkushkin, Alexander; Gafurov, Abror; Agaltseva, Natalya; Pak, Alexander; Mannig, Birgit; Paeth, Heiko; Vorogushyn, Sergiy; Unger-Shayesteh, Katy

2014-05-01

Increased frequency of natural hazards under conditions of observed climate change in Uzbekistan has become challenging concern and shows the need to develop more effective climate risk mechanisms towards improving the security of society and sustainable development. In the framework of presented study, the importance of drought monitoring and methodologies for early warning for such purposes in Uzbekistan are demonstrated. For the conditions of Uzbekistan, droughts are most dangerous climate related natural phenomenon. Therefore, the CRM-Uz Project on Climate Risk Management was established with focus on reducing climate risks, strengthening adaptive capacity for stimulating the development of early warning mechanisms, as well as to build up the basis for long-term investments. This serves to increase resilience to climate impacts in the country. In the frame of the CRM-Uz Project, Drought Early Warning System (DEWS), has been developed and implemented in one of the southern provinces of Uzbekistan (Kashkadarya). The main task of DEWS is to provide population with information on the possibility of upcoming drought season in advance. DEWS is used for the assessment, monitoring, prevention, early warning and decision making in this region. Such early warning system provides the required information to undertake appropriate measures against drought and to mitigate its adverse effects to society. It is clear that during years with expected drought the hydrological forecasts become much more important. Complex mathematical model which simulates of run-off formation as a basis of DEWS provides the seasonal hydrological forecasts that are used to inform all concerned sectors, especially the agricultural sector on water availability during the vegetation period. In the frame of cooperation with German Research Centre for Geosciences (GFZ) within the CAWa Project, the DEWS was extended through implementation of MODSNOW - the operational tool for snow cover monitoring at the Drought Monitoring Centre at UzHydromet. The upgrade of the DEWS withMODSNOW strengthens DEWS's capacity in terms of improvement the hydrological forecasting. Moreover, based on climate scenarios provided within the CAWa project by the University of Würzburg, the regional hydrological model AISHF was used to asses medium and long term water availability in the Kashkadarya River which indicates a reduction of water resources in the selected basin in the future.

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 with perfect information.

Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Huning, L. S.; Love, C. A.; Farahmand, A.

2017-12-01

This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. Satellite observations that are not currently used for operational drought monitoring, such as near-surface air relative humidity and water vapor, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. This presentation describes how different satellite observations can be combined for overall drought development and impact assessment. Finally, we provide an overview of the research gaps and challenges that are facing us ahead in the remote sensing of drought.

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

USGS Publications Warehouse

Funk, Chris; Verdin, James P.; Husak, Gregory

2007-01-01

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

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

2017-04-01

The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining vegetation and hydro-meteorological drought indices for the assessment of cereal yield. Moreover, the present study will provide some guidance on user's decision making process in agricultural practices in the IP, assisting farmers in deciding whether to purchase crop insurance. Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). Andreia Ribeiro also thanks FCT for grant PD/BD/114481/2016.

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

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.

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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 forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

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 Production (NPP)), minimum annual NDVI, maximum annual NDVI, and annual amplitude, were extracted using that new framework. A multi-linear regression has been applied to these vegetation phenology metrics as well as to the relationship between pheno-metrics and environmental variables, to detect potential vegetation changes and to examine the existing relationship between vegetation dynamics and rainfall and elevation gradients. The results suggest that vegetation behavior is foremost governed by rainfall gradients (R-square =0.74). Trend analyses confirmed that around 80 percent of pixels showed a general decline of greenness with confidence level of 95% (p< 0.05), while 4 percent showed a general greening up. Vegetation in the area showed a significant and strong relationship with elevation and precipitation gradients. This correlation was more prominent at mid-elevations, which could be explained by the snowmelt dynamics and hydrological redistribution of water at that elevation. These tools, methods and results can be used to aid in monitoring and understanding climate change and variability impacts on vegetation productivity, ecosystem services, and water resources of the region, and to inform decision-makers and range managers at Hopi Tribe and Navajo nation. Keywords: drought, remote sensing, time series, vegetation dynamics, Hopi Tribe and Navajo Nations

A new multi-sensor integrated index for drought monitoring

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

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

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

USGS Publications Warehouse

,

2012-01-01

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

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

USGS Publications Warehouse

,

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Assessment of TRMM 3B43 product for drought monitoring in Singapore

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

SERVIR-Africa: Developing an Integrated Platform for Floods Disaster Management in Africa

NASA Technical Reports Server (NTRS)

Macharia, Daniel; Korme, Tesfaye; Policelli, Fritz; Irwin, Dan; Adler, Bob; Hong, Yang

2010-01-01

SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.

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.

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 California Drought will be presented. Further Reading: Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

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 (NDVI) data acquired by MODIS instead of the Advanced Very High Resolution Radiometer (AVHRR). The results show a better drought pattern characterization over The Chihuahua Desert, Mexico". The future work will consist of making a sensibility and optimization study of the variables used in the CART model, including others such as evapotranspiration and rainfall. Additionally, this work will research on the potential of using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI).

A Seamless Framework for Global Water Cycle Monitoring and Prediction

NASA Astrophysics Data System (ADS)

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

2013-12-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Utilizing Objective Drought Thresholds to Improve Drought Monitoring with the SPI

NASA Astrophysics Data System (ADS)

Leasor, Z. T.; Quiring, S. M.

2017-12-01

Drought is a prominent climatic hazard in the south-central United States. Droughts are frequently monitored using the severity categories determined by the U.S. Drought Monitor (USDM). This study uses the Standardized Precipitation Index (SPI) to conduct a drought frequency analysis across Texas, Oklahoma, and Kansas using PRISM precipitation data from 1900-2015. The SPI is shown to be spatiotemporally variant across the south-central United States. In particular, utilizing the default USDM severity thresholds may underestimate drought severity in arid regions. Objective drought thresholds were implemented by fitting a CDF to each location's SPI distribution. This approach results in a more homogeneous distribution of drought frequencies across each severity category. Results also indicate that it may be beneficial to develop objective drought thresholds for each season and SPI timescale. This research serves as a proof-of-concept and demonstrates how drought thresholds should be objectively developed so that they are appropriate for each climatic region.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The Drought Monitor.

NASA Astrophysics Data System (ADS)

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

2002-08-01

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

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.

Drought monitoring: Historical and current perspectives

USDA-ARS?s Scientific Manuscript database

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

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 of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

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.

Towards Remotely Sensed Composite Global Drought Risk Modelling

NASA Astrophysics Data System (ADS)

Dercas, Nicholas; Dalezios, Nicolas

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

Li, Xinlu; Lu, Hui; Lyu, Haobo

2017-04-01

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

7 CFR 759.5 - Secretarial disaster area determination and notification process.

Code of Federal Regulations, 2013 CFR

2013-01-01

... § 759.5 Secretarial disaster area determination and notification process. (a) U.S. Drought Monitor. With respect to drought and without requiring an LAR: (1) If any portion of a county is physically located in an area with a Drought Monitor Intensity Classification value of D3 (drought-extreme) or higher...

7 CFR 759.5 - Secretarial disaster area determination and notification process.

Code of Federal Regulations, 2014 CFR

2014-01-01

... § 759.5 Secretarial disaster area determination and notification process. (a) U.S. Drought Monitor. With respect to drought and without requiring an LAR: (1) If any portion of a county is physically located in an area with a Drought Monitor Intensity Classification value of D3 (drought-extreme) or higher...

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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, focused and coordinated research efforts are needed, drawing from excellence across the broad drought research community. To meet this challenge, National Oceanic and Atmospheric Administration (NOAA)'s Drought Task Force was established in October 2011 with the ambitious goal of achieving significant new advances in the ability to understand, monitor, and predict drought over North America. The Task Force (duration of October 2011-September 2014) is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in partnership with NIDIS. It brings together over 30 leading MAPP-funded drought scientists from multiple academic and federal institutions [involves scientists from NOAA's research laboratories and centers, the National Aeronautics and Space Administration (NASA), U.S. Department of Agriculture, National Center for Atmospheric Research (NCAR), and many universities] in a concerted research effort that builds on individual MAPP research projects. These 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 aimed at testing new drought monitoring and prediction tools for operational and service purposes (as part of NCEP's Climate Test Bed). The Drought Task Force provides focus and coordination to MAPP drought research activities and also facilitates synergies with other national and international drought research efforts, including those by the GDIS.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Use of decision support systems as a drought management tool

USGS Publications Warehouse

Frevert, D.; Lins, H.; ,

2005-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-02-25

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

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

PubMed Central

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-01-01

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

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.

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

PubMed

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

2008-08-08

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Development of an operational African Drought Monitor prototype

NASA Astrophysics Data System (ADS)

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

2011-12-01

Droughts have severe economic, environmental, and social impacts. However, timely detection and monitoring can minimize these effects. Based on previous drought monitoring over the continental US, a drought monitor has been developed for Africa. Monitoring drought in data sparse regions such as Africa is difficult due to a lack of historical or real-time observational data at a high spatial and temporal resolution. As a result, a land surface model is used to estimate hydrologic variables, which are used as surrogate observations for monitoring drought. The drought monitoring system consists of two stages: the first is to create long-term historical background simulations against which current conditions can be compared. The second is the real-time estimation of current hydrological conditions that results in an estimated drought index value. For the first step, a hybrid meteorological forcing dataset was created that assimilates reanalysis and observational datasets from 1950 up to real-time. Furthermore, the land surface model (currently the VIC land surface model is being used) was recalibrated against spatially disaggregated runoff fields derived from over 500 GRDC stream gauge measurements over Africa. The final result includes a retrospective database from 1950 to real-time of soil moisture, evapotranspiration, river discharge at the GRDC gauged sites (etc.) at a 1/4 degree spatial resolution, and daily temporal resolution. These observation-forced simulations are analyzed to detect and track historical drought events according to a drought index that is calculated from the soil moisture fields and river discharge relative to their seasonal climatology. The real-time monitoring requires the use of remotely sensed and weather-model analysis estimates of hydrological model forcings. For the current system, NOAA's Global Forecast System (GFS) is used along with remotely sensed precipitation from the NASA TMPA system. The historical archive of these data is evaluated against the data set used to create the background simulations. Real-time adjustments are used to preserve consistency between the historical and real-time data. The drought monitor will be presented together with the web-interface that has been developed for the scientific community to access and retrieve the data products. This system will be deployed for operational use at AGRHYMET in Niamey, Niger before the end of 2011.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

Irrigation in California's Central Valley (USA) has decreased significantly due to water shortages resulting from the current drought, which began in 2010. In particular, fallow fields in the west side of the San Joaquin Valley (WSJV), which is the southwest portion of the Central Valley, increased from around 12% in the years before the drought (2007-2010) to 20-25% in the following years (2011-2015). We monitored and mapped drought-induced edaphic changes in salinity at two scales: (i) field scale (32.4-ha field in Kings County) and (ii) water district scale (2400 ha at -former- Broadview Water District in Fresno County). At both scales drought-induced land-use changes (i.e., shift from irrigated agriculture to fallow) drastically decreased soil quality by increasing salinity (and sodicity), especially in the root-zone (top 1.2 m). The field study monitors the spatial (three dimensions) changes of soil salinity (and sodicity) in the root-zone during 10 years of irrigation with drainage water followed by 4 years of no applied irrigation water (only rainfall) due to drought conditions. Changes of salinity (and other edaphic properties), through the soil profile (down to 1.2 m, at 0.3-m increments), were monitored and modeled using geospatial apparent electrical conductivity measurements and extensive soil sampling in 1999, 2002, 2004, 2009, 2011, and 2013. Results indicate that when irrigation was applied, salts were leached from the root-zone causing a remarkable improvement in soil quality. However, in less than two years after termination of irrigation, salinity in the soil profile returned to original levels or higher across the field. At larger spatial scales the effect of drought-induced land-use change on root-zone salinity is also evident. Up to spring 2006, lands in Broadview Water District (BWD) were used for irrigated agriculture. Water rights were then sold and the farmland was retired. Soil quality decreased since land retirement, especially during the drought years. Root-zone soil salinity was mapped in 1991 using geospatial apparent electrical conductivity measurements and extensive soil sampling and in 2013 using recent root-zone remote sensing salinity map for the WSJV (developed and published by the U.S. Salinity Laboratory, USDA-ARS), which was calibrated and (independently) validated, including fields from the BWD. Results reveal dramatic increases in soil salinity for all the fields that were originally non-saline and slightly-saline in 1991. Additionally, time-series analysis of very-high resolution ortho-imagery (from Google Earth and USGS) suggests that surface soil quality drastically decreased especially during the drought years. Our research shows how terminating irrigation in California's Central Valley can lead to substantial soil salinization in a very short time. Salinization in WSJV due to the termination of irrigation is a consequence of the complex multi-scale interaction of geomorphologic, topographic, and anthropogenic factors requiring yearly monitoring to adequately assess the impacts of drought for use in field- and basin-scale water management decisions. Among other concerns, increased salinity and sodicity affect vegetation growth and may lead to increased soil erosion and very-fine dust formation creating health and environmental hazards.

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

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

Sun, Ying; Fu, Rong; Dickinson, Robert

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

DOE PAGES

Sun, Ying; Fu, Rong; Dickinson, Robert; ...

2015-11-02

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Towards the construction of a Drought Early Warning System in México

NASA Astrophysics Data System (ADS)

Neri, C.; Magaña, V. O.

2011-12-01

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

The Challenges of Developing a Framework for Global Water Cycle Monitoring and Prediction (Alfred Wegener Medal Lecture)

NASA Astrophysics Data System (ADS)

Wood, Eric F.

2014-05-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ("From Observations to Decisions") recognizes that "water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity", and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the developments at Princeton University towards a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. At every step there are scientific challenges whose solutions are only partially being solved. In addition there are challenges in delivering such systems as "climate services", especially to societies with low technical capacity such as rural agriculturalists in sub-Saharan Africa, but whose needs for such information are great. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

An Evaluation of Drought Indices in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Shahabfar, A.; Eitzinger, J.

2009-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

Agricultural activity can exacerbate or buffer the impact of climate variability, especially droughts, on the hydrologic and socioeconomic conditions of rural areas. Potential negative regional impacts of droughts include impoverishment of agricultural regions, deterioration or overuse of water resources, risk of monoculture, and regional dependence on external food markets. Policies that encourage adequate management practices in the face of adverse climatic events are critical to preserve rural livelihoods and to ensure a sustainable future for agriculture. Diagnosing and managing drought effects on agricultural production, on the social and natural environment, and on limited water resources, is highly complex and interdisciplinary. The challenges that decision-makers face to mitigate the impact of water shortage are social, agronomic, economic and environmental in nature and therefore must be approached from an integrated multidisciplinary point of view. Existing observation technologies, in conjunction with models and assimilation methods open the opportunity for novel interdisciplinary analysis tools to support policy and decision making. We present an integrated modeling and observation framework driven by satellite remote sensing and other ancillary information from regional monitoring networks to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, management decisions and socioeconomic policy. The core of this framework is a hydroeconomic model of agricultural production that assimilates remote sensing inputs to quantify the amount of land, water, fertilizer and labor farmers allocate for each crop they choose to grow on a seasonal basis in response to changing climatic conditions, including drought. A regional hydroclimatologic model provides biophysical constraints to an economic model of agricultural production based on a class of models referred to as positive mathematical programming (PMP). A recursive Bayesian update method is used to adjust the model parameters by assimilating information on crop acreage, production, and crop evapotranspiration estimated from high-spatial resolution satellite remote sensing. We are developing new land parameter records adapted for agricultural application by merging relatively fine scale, calibrated spectral reflectance time series with similar spectral information from coarser scale and more temporally continuous global satellite data records. These new products will be used to generate field scale estimates of LAI and FPAR, which will be used with regional surface meteorology and biophysical data to estimate crop production including C4 crop types. This integrated framework provides an operational means to monitor and forecast what crops will be grown and how farmers will allocate land, water and other agricultural resources under expected adverse conditions, and the resulting consequences for other water users. It will also permit evaluation of impacts of water policy and changes in food prices on rural community livelihoods. The Bayesian update framework constitutes an efficient method for the identification of the production function parameters and provides valuable information on the associated uncertainty of the forecasts.

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.

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

Treesearch

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

2016-01-01

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

A new comprehensive index for drought monitoring with TM data

NASA Astrophysics Data System (ADS)

Wang, Yuanyuan

2017-10-01

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

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;

Research and Development initiative of Satellite Technology Application for Environmental Issues in Asia Region

NASA Astrophysics Data System (ADS)

Hamamoto, K.; Kaneko, Y.; Sobue, S.; Oyoshi, K.

2016-12-01

Climate change and human activities are directly or indirectly influence the acceleration of environmental problems and natural hazards such as forest fires, drought and floods in the Asia-Pacific countries. Satellite technology has become one of the key information sources in assessment, monitoring and mitigation of these hazards and related phenomenon. However, there are still gaps between science and application of space technology in practical usage. Asia-Pacific Regional Space Agency Forum (APRSAF) recommended to initiate the Space Applications for Environment (SAFE) proposal providing opportunity to potential user agencies in the Asia Pacific region to develop prototype applications of space technology for number of key issues including forest resources management, coastal monitoring and management, agriculture and food security, water resource management and development user-friendly tools for application of space technology. The main activity of SAFE is SAFE prototyping. SAFE prototyping is a demonstration for end users and decision makers to apply space technology applications for solving environmental issues in Asia-Pacific region. By utilizing space technology and getting technical support by experts, prototype executers can develop the application system, which could support decision making activities. SAFE holds a workshop once a year. In the workshop, new prototypes are approved and the progress of on-going prototypes are confirmed. Every prototype is limited for two years period and all activities are operated by volunteer manner. As of 2016, 20 prototypes are completed and 6 prototypes are on-going. Some of the completed prototypes, for example drought monitoring in Indonesia were applied to operational use by a local official organization.

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 implemented in Africa in the past include food aid, drought relief programs, growing of drought tolerate crops, saving livestock, water efficiency and construction or rehabilitation of boreholes, wells and small dams. In the North Africa - Maghreb Region and in the Southern Africa - Limpopo Basin, respectively 73 and 39 organisations involved in drought mitigation, are identified, dealing with agriculture extension services (28), food aid (11), policy (11), advocacy (10) and water supply (3). The most common adaptation actions identified are water harvesting, construction of water infrastructure, rehabilitation of traditional/cultural practices or implementation of technologies, water conservation, crop monitoring and crop diversification. Regarding involvement of organisations in drought adaptation, 18 organisations in the North Africa - Maghreb Region and 20 in Southern Africa - Limpopo Basin are identified. These organisations are involved in water infrastructure development or management (7), agriculture extension services (7) and policy development (13). The paper clearly shows that there is need to improve the existing monitoring and early warning systems at continental, regional, national and local scales. It also shows that a lot of organisations emerge when there is a drought and are involved in drought mitigation but only a few are involved in drought adaptation.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Assessment of the 1998–2001 drought impact on forest health in southeastern forests: an analysis of drought severity using FHM data

Treesearch

R. J. Klos; G. G. Wang; W. L. Bauerle

2010-01-01

Analyses of forest health indicators monitored through the Forest Health and Monitoring (FHM) program suggested that weather was the most important cause of tree mortality. Drought is of particular importance among weather variables because several global climate change scenarios predicted more frequent and/or intense drought in the Southeastern United States. During...

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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 and adaptation. Lessons will be drawn from recent and ongoing events in California, the Midwest, and globally.

Assessing changes in drought characteristics with standardized indices

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Use of NDVI and land surface temperature for assessing vegetation health: merits and limitations

USDA-ARS?s Scientific Manuscript database

To date, most drought indices used in drought monitoring are based on precipitation and meteorological data collected on the ground from distributed monitoring networks. Few satellite-based drought indices are currently in production, although these afford better spatial and temporal coverage and r...

Integrating NASA Earth Science Enterprise (ESE) Data Into Global Agricultural Decision Support Systems

NASA Astrophysics Data System (ADS)

Teng, W.; Kempler, S.; Chiu, L.; Doraiswamy, P.; Liu, Z.; Milich, L.; Tetrault, R.

2003-12-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of U.S. agricultural products and for global food security. Two major operational users of satellite remote sensing for global crop monitoring are the USDA Foreign Agricultural Service (FAS) and the U.N. World Food Programme (WFP). The primary goal of FAS is to improve foreign market access for U.S. agricultural products. The WFP uses food to meet emergency needs and to support economic and social development. Both use global agricultural decision support systems that can integrate and synthesize a variety of data sources to provide accurate and timely information on global crop conditions. The Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (GES DAAC) has begun a project to provide operational solutions to FAS and WFP, by fully leveraging results from previous work, as well as from existing capabilities of the users. The GES DAAC has effectively used its recently developed prototype TRMM Online Visualization and Analysis System (TOVAS) to provide ESE data and information to the WFP for its agricultural drought monitoring efforts. This prototype system will be evolved into an Agricultural Information System (AIS), which will operationally provide ESE and other data products (e.g., rainfall, land productivity) and services, to be integrated into and thus enhance the existing GIS-based, decision support systems of FAS and WFP. Agriculture-oriented, ESE data products (e.g., MODIS-based, crop condition assessment product; TRMM derived, drought index product) will be input to a crop growth model in collaboration with the USDA Agricultural Research Service, to generate crop condition and yield prediction maps. The AIS will have the capability for remotely accessing distributed data, by being compliant with community-based interoperability standards, enabling easy access to agriculture-related products from other data producers. The AIS? system approach will provide a generic mechanism for easily incorporating new products and making them accessible to users.

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

PubMed

Yi, Hang; Wen, Lianxing

2016-01-27

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

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.

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 observed atmospheric forcing. The forecast skills from the dynamical seasonal models (CFSv1, CFSv2, EUROSIP) and CPC are also compared with forecasts based on the Ensemble Streamflow Prediction (ESP) method, which uses initial conditions and historical forcings to generate seasonal forecasts. The skill of the system to predict drought, drought recovery and related hydrological conditions such as low-flows is assessed, along with quantified uncertainty.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

USGS Publications Warehouse

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-01-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

NASA Astrophysics Data System (ADS)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-08-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

Treesearch

Kirsten Lackstrom; Amanda Brennan; Kirstin Dow

2016-01-01

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

Ecohydrological drought monitoring and prediction using a land data assimilation system

NASA Astrophysics Data System (ADS)

Sawada, Y.; Koike, T.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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;

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.

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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

NASA Astrophysics Data System (ADS)

Ryu, J.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

13 CFR 123.3 - How are disaster declarations made?

Code of Federal Regulations, 2010 CFR

2010-01-01

... the disaster occurrence. When a Governor certifies with respect to a drought or to below average water... period meet or exceed the U.S. Drought Monitor (USDM) standard of “severe” (Intensity level D-2 to D-4). The USDM may be found at http://drought.unl.edu/dm/monitor. With respect to below average water levels...

13 CFR 123.3 - How are disaster declarations made?

Code of Federal Regulations, 2014 CFR

2014-01-01

... the disaster occurrence. When a Governor certifies with respect to a drought or to below average water... period meet or exceed the U.S. Drought Monitor (USDM) standard of “severe” (Intensity level D-2 to D-4). The USDM may be found at http://drought.unl.edu/dm/monitor. With respect to below average water levels...

13 CFR 123.3 - How are disaster declarations made?

Code of Federal Regulations, 2011 CFR

2011-01-01

... the disaster occurrence. When a Governor certifies with respect to a drought or to below average water... period meet or exceed the U.S. Drought Monitor (USDM) standard of “severe” (Intensity level D-2 to D-4). The USDM may be found at http://drought.unl.edu/dm/monitor. With respect to below average water levels...

13 CFR 123.3 - How are disaster declarations made?

Code of Federal Regulations, 2013 CFR

2013-01-01

... the disaster occurrence. When a Governor certifies with respect to a drought or to below average water... period meet or exceed the U.S. Drought Monitor (USDM) standard of “severe” (Intensity level D-2 to D-4). The USDM may be found at http://drought.unl.edu/dm/monitor. With respect to below average water levels...

13 CFR 123.3 - How are disaster declarations made?

Code of Federal Regulations, 2012 CFR

2012-01-01

... the disaster occurrence. When a Governor certifies with respect to a drought or to below average water... period meet or exceed the U.S. Drought Monitor (USDM) standard of “severe” (Intensity level D-2 to D-4). The USDM may be found at http://drought.unl.edu/dm/monitor. With respect to below average water levels...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

NASA Technical Reports Server (NTRS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Water Decisions for Sustainability of the Arbuckle-Simpson Aquifer

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

Wang, K; Davies, E G R

2015-09-01

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

Multivariate Drought Characterization in India for Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sreekumaran Unnithan, P.; Mondal, A.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

The demand for regional climate information is increasing and spurring efforts to provide a broad slate of climate services that inform policy and resource management and elevate general knowledge. Routine syntheses of existing climate-related information may be an effective strategy for connecting climate information to decision making, but few studies have formally assessed their contribution to informing decisions. During the 2010-2011 winter, drought conditions expanded and intensified in Arizona and New Mexico, creating an opportunity to develop and evaluate a pithy, monthly regional climate communication product—La Niña Drought Tracker—that synthesized and interpreted drought and climate information. Six issues were published and subsequently evaluated through an online survey. On average, 417 people consulted the publication each month. Many of the survey respondents indicated that they made at least one drought-related decision, and the product at least moderately influenced the majority of those decisions, some of which helped mitigate economic losses and reduce climate vulnerability. The product also improved understanding of climate and drought for more than 90 percent of the respondents and helped the majority of them better prepare for drought. These, and other results demonstrate that routine interpretation and synthesis of existing climate information can help enhance access to and understanding and use of climate information in decision-making. Moreover, developing regional, contextual knowledge within climate service programs can facilitate the implementation of activities like the Tracker that enhance the use of climate information without engaging in time-consuming collaborative processes that can prevent the timely production of the services. We present results from the case study of the Tracker and place it within the context of the challenges and opportunities associated with providing climate services, particularly those services that require several-to-many months of work but often do not generate substantial financial sponsorship. These medium-term climate services, like the Tracker, present formidable challenges. However, we argue, they are vital to satisfying stakeholder demand, creating new and strengthening existing partnerships, aiding decisions, advancing climate literacy, and fostering future projects—main goals of climate services.

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

NASA Astrophysics Data System (ADS)

Linés, Clara; Werner, Micha; Bastiaanssen, Wim

2017-09-01

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

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

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

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

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

NASA Astrophysics Data System (ADS)

Guo, W.; Kogan, F.

2016-12-01

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

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 vulnerability and presented in the same way as the vulnerability, as a GIS-based map. Risk maps show geographic regions in Slovenia where droughts pose a major threat to the agriculture and together with the vulnerability maps provide the basis for drought management, in particular for the appropriate mitigation and response actions in specific regions. The developed methodology is expected to be applied to the entire region of South-Eastern Europe within the initiative of the Drought Management Centre for Southeastern Europe.

Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA

NASA Astrophysics Data System (ADS)

Fraisse, C.

2014-12-01

AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.

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

USGS Publications Warehouse

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

2017-01-01

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

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

PubMed

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

2017-02-01

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

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

NASA Astrophysics Data System (ADS)

Vogt, J.; Singleton, A.; Sepulcre, G.; Micale, F.; Barbosa, P.

2012-12-01

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

The potential of SMAP soil moisture data for analyzing droughts

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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 ...

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 for monitoring crop health during the severe drought events. The presentation will provide results of the investigation into Droughts using time series of coarse resolution daily evapotranspiration produced from the SEBS remote sensing model, on basis of MODIS data. The evapotranspiration will be converted into drought severity using the evapotranspiration deficit index (ETDI). Afterwards the disaggregation to plot scale will be investigated. This disaggregation will be performed as a weighted filtering on basis of crop-coefficient at high resolution. These growth stage of the vegeation (needed for the estimation of the crop coefficients) are estimated on basis of Normalized Difference Vegetation Index (NDVI) using Landsat 5,7 and 8 observations. The final result of the research provides good statistical information about drought resilience and crop health.

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.

7 CFR 759.3 - Abbreviations and definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., as a result of the natural disaster. U.S. Drought Monitor is a system for classifying drought severity according to a range of abnormally dry to exceptional drought. It is a collaborative effort..., outlooks, and drought impacts on a map and in narrative form. This synthesis of indices is reported by the...

7 CFR 759.3 - Abbreviations and definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., as a result of the natural disaster. U.S. Drought Monitor is a system for classifying drought severity according to a range of abnormally dry to exceptional drought. It is a collaborative effort..., outlooks, and drought impacts on a map and in narrative form. This synthesis of indices is reported by the...

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

USDA-ARS?s Scientific Manuscript database

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

Drought monitoring using remote sensing of evapotranspiration

USDA-ARS?s Scientific Manuscript database

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

Drought is considered as one of the major environmental hazards with significant impacts to agriculture, environment, economy and society. This paper addresses drought as a hazard within the risk management framework. Indeed, hazards may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Besides, risk management consists of risk assessment and feedback of the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. In order to ensure sustainability in agricultural production a better understanding of the natural disasters, in particular droughts, that impact agriculture is essential. Droughts may result in environmental degradation of an area, which is one of the factors contributing to the vulnerability of agriculture, because it directly magnifies the risk of natural disasters. This paper deals with drought risk identification, which involves hazard quantification, event monitoring including early warning systems and statistical inference. For drought quantification the Reconnaissance Drought Index (RDI) combined with Vegetation Health Index (VHI) is employed. RDI is a new index based on hydrometeorological parameters, and in particular precipitation and potential evapotranspiration, which has been recently modified to incorporate monthly satellite (NOAA/AVHAA) data for a period of 20 years (1981-2001). VHI is based on NDVI. The study area is Thessaly in central Greece, which is one of the major agricultural areas of the country occasionally facing droughts. Drought monitoring is conducted by monthly remotely sensed RID and VHI images and several drought features are extracted such as severity, duration, areal extent, onset and end time. Drought early warning is developed using empirical relationships of the above mentioned features. In particular, two second-order polynomials are fitted relating severity and areal extend (number of pixels), one for low and other for high severity drought. The two fitted curves offer a forecasting tool on a monthly basis from the beginning of each hydrological year with high severity droughts occurring from October, whereas low severity droughts start in April. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential of drought. The adopted remote sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

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 objective quantification and tracking of their spatial-temporal characteristics. Further we present strategies for merging various sources of information, including bias correction of satellite precipitation and assimilation of remotely sensed soil moisture, which can augment the monitoring in regions where satellite precipitation is most uncertain. Ongoing work is adding a drought forecast component based on a successful implementation over the U.S. and agricultural productivity estimates based on output from crop yield models. The forecast component uses seasonal global climate forecasts from the NCEP Climate Forecast System (CFS). These are merged with observed climatology in a Bayesian framework to produce ensemble atmospheric forcings that better capture the uncertainties. At the same time, the system bias corrects and downscales the monthly CFS data. We show some initial seasonal (up to 6-month lead) hydrologic forecast results for the African system. Agricultural monitoring is based on the precipitation, temperature and soil moisture from the system to force statistical and process based crop yield models. We demonstrate the feasibility of monitoring major crop types across the world and show a strategy for providing predictions of yields within our drought forecast mode.

Remote Assessment of Forest Ecosystem Stress (RAFES): Development of a Real Time Decision Support Tool for the Eastern U.S

NASA Astrophysics Data System (ADS)

Clinton, B.; Vose, J.; Novick, K.; Liu, Y.

2011-12-01

Drier and warmer conditions predicted with climate change models are likely to significantly impact forest ecosystems over the next several decades. The U.S. has experienced significant droughts over the past several years that have increased the susceptibility of forests to insect outbreaks, disease, and wildfire. Weather data collected with traditional approaches provide an indirect measure of drought or temperature stress; however, the significance of short-term or prolonged climate-related stress varies considerably across the landscape as topography, elevations, edaphic condition and antecedent conditions vary. This limits the capacity of land managers to anticipate and initiate management activities that could offset the impacts of climate-related forest stress. Decision support tools are needed that allow fine scale monitoring of stress conditions in forest ecosystems in real time to help land managers evaluate response strategies. To assist land managers in managing the impacts of climate change, we are developing a stress monitoring and decision support system across multiple sites in the eastern U.S. that (1) provides remote data capture of environmental parameters that quantify climate-related forest stress, (2) links remotely captured data with physiologically-based indices of tree water stress, and (3) provides a PC-based analytical tool for land managers to monitor and assess the severity of climate-related stress. Currently the network represents southern coastal plain pine plantation, Atlantic coastal flatwoods mixed pine-hardwood, southern piedmont upland mixed pine-hardwood, southern Appalachian dry ridge and mesic riparian, southern Arkansas managed mature pine, and northern Minnesota mature aspen. The strategy for selecting additional sites for the network will be a focus on at-risk ecosystems deemed particularly vulnerable to the affects of predicted climate change such as those in ecotonal transition regions, or those at the fringes of their ranges. The sensor arrays at each site detect water and temperature stress variables and transmit those data to a field office. Sensors include air and soil temperature, relative humidity, fuel moisture and temperature, xylem sap flux density, soil moisture and matric potential, precipitation, and solar radiation. Data are transmitted in real-time to the NOAA Geostationary Operational Environmental Satellite (GOES). A PC-based software program that downloads monitoring data from the GOES satellite, analyzes the data, and provides the land manager with an assessment of climate-related stress conditions and potential forest health threat levels in real time is under development. Data collection began in early 2010 on most sites, and we have at least one year of data from all nine sites within the network. We are currently comparing estimates of stress levels on our sites with estimates of stress from common drought indices. For this presentation, we are comparing and contrasting four sites representing an environmental gradient within the network.

The role of conservation programs in drought risk adaptation

Treesearch

Steven Wallander; Marcel Aillery; Daniel Hellerstein; Michael Hand

2013-01-01

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

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

USGS Publications Warehouse

Busciolano, Ronald J.

2005-01-01

Ground water is the sole source of water supply for more than 3 million people on Long Island, New York. Large-scale ground-water pumpage, sewering systems, and prolonged periods of below-normal precipitation have lowered ground-water levels and decreased stream-discharge in western and central Long Island. No method is currently (2004) available on Long Island that can assess data from the ground-water-monitoring network to enable water managers and suppliers with the ability to give timely warning of severe water-level declines.This report (1) quantifies past drought- and human-induced changes in the ground-water system underlying Long Island by applying statistical and graphical methods to precipitation, stream-discharge, and ground-water-level data from selected monitoring sites; (2) evaluates the relation between water levels in the upper glacial aquifer and those in the underlying Magothy aquifer; (3) defines trends in stream discharge and ground-water levels that might indicate the onset of drought conditions or the effects of excessive pumping; and (4) discusses the long-term records that were used to select sites for a Long Island drought-monitoring network.Long Island’s long-term hydrologic records indicated that the available data provide a basis for development of a drought-monitoring network. The data from 36 stations that were selected as possible drought-monitoring sites—8 precipitation-monitoring stations, 8 streamflow-gaging (discharge) stations, 15 monitoring wells screened in the upper glacial aquifer under water-table (unconfined) conditions, and 5 monitoring wells screened in the underlying Magothy aquifer under semi-confined conditions—indicate that water levels in western parts of Long Island have fallen and risen markedly (more than 15 ft) in response to fluctuations in pumpage, and have declined from the increased use of sanitary- and storm-sewer systems. Water levels in the central and eastern parts, in contrast, remain relatively unaffected compared to the western parts, although the effects of human activity are discernible in the records.The value of each site as a drought-monitoring indicator was assessed through an analysis of trends in the records. Fifty-year annual and monthly data sets were created and combined into three composite-average hydrographs—precipitation, stream discharge, and ground-water levels. Three zones representing the range of human effect on ground-water levels were delineated to help evaluate islandwide hydrologic conditions and to quantify the indices. Data from the three indices can be used to assess current conditions in the ground-water system underlying Long Island and evaluate water-level declines during periods of drought.

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

USGS Publications Warehouse

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

2016-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

Dilling, L.

2017-12-01

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

Proposal and work plan to calibrate and verify a water-quality model to simulate effects of wastewater discharges to the Red River of the North at drought streamflow near Fargo, North Dakota, and Moorhead, Minnesota

USGS Publications Warehouse

Wesolowski, Edwin A.

2000-01-01

This report presents a proposal for conducting a water-quality modeling study at drought streamflow, a detailed comprehensive plan for collecting the data, and an annual drought-formation monitoring plan. A 30.8 mile reach of the Red River of the North receives treated wastewater from plants at Fargo, North Dakota, and Moorhead, Minnesota, and streamflow from the Sheyenne River. The water-quality modeling study will evaluate the effects of continuous treated-wastewater discharges to the study reach at drought streamflow. The study will define hydraulic characteristics and reaeration and selected reaction coefficients and will calibrate and verity a model.The study includes collecting synoptic water-quality samples for various types of analyses at a number of sites in the study reach. Dye and gas samples will be collected for traveltime and reaeration measurements. Using the Lagrangian reference frame, synoptic water-quality samples will be collected for analysis of nutrients, chlorophyll a, alkalinity, and carbonaceous biochemical oxygen demand. Field measurements will be made of specific conductance, pH, air and water temperature, dissolved oxygen, and sediment oxygen demand. Two sets of water-quality data will be collected. One data set will be used to calibrate the model, and the other data set will be used to verity the model.The DAFLOW/BLTM models will be used to evaluate the effects of the treated wastewater on the water quality of the river. The model will simulate specific conductance, temperature, dissolved oxygen, carbonaceous biochemical oxygen demand, total nitrogen (organic, ammonia, nitrite, nitrate), total orthophosphorus, total phosphorus, and phytoplankton as chlorophyll a.The work plan identifies and discusses the work elements needed for accomplishing the data collection for the study. The work elements specify who will provide personnel, vehicles, instruments, and supplies needed during data collection. The work plan contains instructions for data collection; inventory lists of needed personnel, vehicles, instruments, and supplies; and examples of computations for determining quantities of tracer to be injected into the stream. The work plan also contains an annual drought-formation monitoring plan that includes a 9-month time line that specifies when essential planning actions must occur before actual project start up. Drought streamflows are rare. The annual drought-formation monitoring plan is presented to assist project planning by providing early warning that conditions are favorable to produce drought streamflow. The plan to monitor drought-forming conditions discusses the drought indices to be monitored. To establish a baseline, historic values for some of the drought indices for selected years were reviewed. An annual review of the drought indices is recommended.

GROUND WATER QUALITY SURROUNDING LAKE TEXOMA DURING DROUGHT CONDITIONS

EPA Science Inventory

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

Strategic Planning for Drought Mitigation Under Climate Change

NASA Astrophysics Data System (ADS)

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

2012-12-01

Droughts continue to be a major natural hazard and mounting evidence of global warming confronts society with a pressing question: Will climate change aggravate the risk of drought at local scale? It is important to explore what additional risk will be imposed by climate change and what level of strategic measures should be undertaken now to avoid vulnerable situations in the future, given that tactical measures may not avoid large damage. This study addresses the following key questions on strategic planning for drought mitigation under climate change: What combination of strategic and tactical measures will move the societal system response from a vulnerable situation to a resilient one with minimum cost? Are current infrastructures and their operation enough to mitigate the damage of future drought, or do we need in-advance infrastructure expansion for future drought preparedness? To address these questions, this study presents a decision support framework based on a coupled simulation and optimization model. A quasi-physically based watershed model is established for the Frenchman Creek Basin (FCB), part of the Republic River Basin, where groundwater based irrigation plays a significant role in agriculture production and local hydrological cycle. The physical model is used to train a statistical surrogate model, which predicts the watershed responses under future climate conditions. The statistical model replaces the complex physical model in the simulation-optimization framework, which makes the models computationally tractable. Decisions for drought preparedness include traditional short-term tactical measures (e.g. facility operation) and long-term or in-advance strategic measures, which require capital investment. A scenario based three-stage stochastic optimization model assesses the roles of strategic measures and tactical measures in drought preparedness and mitigation. Two benchmark climate prediction horizons, 2040s and 2090s, represent mid-term and long-term planning, respectively, compared to the baseline of the climate of 1980-2000. To handle uncertainty in climate change projections, outputs from three General Circulation Models (GCMs) with Regional Climate Model (RCM) for dynamic downscaling (PCM-RCM, Hadley-RCM, and CCSM-RCM) and four CO2 emission scenarios are used to represent the various possible climatic conditions in the mid-term (2040's) and long-term (2090's) time horizons. The model results show the relative roles of mid- and long-term investments and the complementary relationships between wait-and-see decisions and here-and-now decisions on infrastructure expansion. Even the best tactical measures (irrigation operation) alone are not sufficient for drought mitigation in the future. Infrastructure expansion is critical especially for environmental conversation purposes. With increasing budget, investment should be shifted from tactical measures to strategic measures for drought preparedness. Infrastructure expansion is preferred for the long term plan than the mid-term plan, i.e., larger investment is proposed in 2040s than the current, due to a larger likelihood of drought in 2090s than 2040s. Thus larger BMP expansion is proposed in 2040s for droughts preparedness in 2090s.

Global drought outlook by means of seasonal forecasts

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Stenzel, J.; Hudiburg, T. W.

2016-12-01

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

Intra-seasonal risk of agriculturally-relevant weather extremes in West African Sudan Savanna

NASA Astrophysics Data System (ADS)

Boansi, David; Tambo, Justice A.; Müller, Marc

2018-01-01

Using household survey data and historical daily climate data for 29 communities across Upper East Ghana and Southwest Burkina Faso, we document climatic conditions deemed major threat to farming in the West African Sudan Savanna and assess risks posed by such conditions over the period 1997-2014. Based on farmers' perception, it is found that drought, low rainfall, intense precipitation, flooding, erratic rainfall pattern, extremely high temperatures, delayed rains, and early cessation of rains are the major threats farmers face. Using first-order Markov chain model and relevant indices for monitoring weather extremes, it is discovered that climatic risk is a general inherent attribute of the rainy season in the study area. Due to recent changes in onset of rains and length of the rainy season, some farmers have either resorted to early planting of drought-hardy crops, late planting of drought-sensitive crops, or spreading of planting across the first 3 months of the season to moderate harm. Each of these planting decisions however has some risk implications. The months of May, June, and October are found to be more susceptible to relatively longer duration of dry and hot spells, while July, August, and September are found to be more susceptible to intense precipitation and flooding. To moderate harm from anticipated weather extremes, farmers need to adjust their cropping calendar, adopt appropriate crop varieties, and implement soil and water management practices. For policy makers and other stakeholders, we recommend the supply of timely and accurate weather forecasts to guide farmers in their seasonal cropping decisions and investment in/installation of low cost irrigation facilities to enhance the practice of supplemental irrigation.

Using NASA UAVSAR Datasets to Link Soil Moisture to Crop Conditions

NASA Astrophysics Data System (ADS)

Davitt, A. W. D.; McDonald, K. C.; Azarderakhsh, M.; Winter, J.

2015-12-01

California and The Central Valley are experiencing one of that region's worst, persistent droughts, which represents the continuation of a prolonged drought that started in the early 2000's. Due to the continued drought, many agricultural regions in The Central Valley have been experiencing water shortages, negatively impacting agricultural production and the socio-economics of the region. Due to these impacts, there has been an increased incentive to find new ways to conserve water for use in irrigation. Recent advances in remote sensing techniques provide the ability for end users to better understand field conditions so they may make more informed decisions on irrigation timing and amounts. However, a good understanding of soil moisture and its role in crop health and yield is lacking to support informed water management decisions. Though known to be important, a robust understanding of the role of the spatio-temporal patterns in soil moisture linked to crop health is lacking. Remote sensing platforms such as NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provide the capacity to obtain within-field measurements to estimate within-field and field-to-field variability in soil moisture. UAVSAR radar images acquired from 2010 to 2014 for Yolo County, California are being examined to determine the suitability of high resolution (field scale) multi-temporal L-band radar backscatter imagery for soil moisture assessment and crop conditions through the growing season. By using such data and linking to in-situ meteorology measurements, modeling (MIMICS), and other remote sensing derived datasets (Sentinel, Landsat, MODIS, and TOPS-SIMS), an integrated monitoring system can potentially support the assessment of agricultural field conditions. This allows growers to optimize the use of limited water supplies through informed water management practices, potentially improving crop conditions and yield in a water stressed region.

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 differences in experiences in development and implementation between the two systems in terms of the scientific challenges and the utility of the systems to stakeholders, for whom the information must be relevant to local conditions and needs.

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

NASA Astrophysics Data System (ADS)

Urquijo, Julia; De Stefano, Lucia

2015-04-01

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

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 estimation of the SPI: 1. It is estimated with the standardized index of precipitation used internationally, is special the Drought Monitor Center en Nebraska (E.U.A.) 2. It has as a normal media a historical series of at least 30 years of monthly precipitation. 3. The source code developed was compiled to create a computer program, with which you can derive to a climatic level, historical series of values of the SPI on time scales of 1 to 48 months. 4. The interpolation of values was classified with the current systems accepted internationally. 5. It has as a complement the annual pursuit of the hydrological drought on the level of the basin of the Conchos River through three of the main dams, an index of the deficits of the runof volume is employed and one index of the hydrological drought tendency employed in different parts of the world. Mentioned Literature Nuñez-López D., C.A. Muñoz-Robles, G. Hector, V.M. Reyes-Gómez, 2006. Caractérisation, á diverses échelles de temps, des séquences de sécheresse dans l'état de chihuahua (Mexique). Science et Changements Planétaires - Sécheresse 17(4) : 467-474. McKee, T., N. Doesken, and J. Kleist, "Drought Monitoring with Multiple Time Scales.", Proceedings of the 9th Conference on Applied Climatology, Boston MA, U.S.A., 1995, 233-236 pp. Young, K.C., "A Three-Way Model for Interpolating for Monthly Precipitation Values.", Monthly Weather Review, Vol. 120, Boston, MA. U.S.A., 1992, 2561-2569 pp.

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

NASA Astrophysics Data System (ADS)

Sheffield, Justin

2013-04-01

Droughts arguably cause the most impacts of all natural hazards in terms of the number of people affected and the long-term economic costs and ecosystem stresses. Recent droughts worldwide have caused humanitarian and economic problems such as food insecurity across the Horn of Africa, agricultural economic losses across the central US and loss of livelihoods in rural western India. The prospect of future increases in drought severity and duration driven by projected changes in precipitation patterns and increasing temperatures is worrisome. Some evidence for climate change impacts on drought is already being seen for some regions, such as the Mediterranean and east Africa. Mitigation of the impacts of drought requires advance warning of developing conditions and enactment of drought plans to reduce vulnerability. A key element of this is a drought early warning system that at its heart is the capability to monitor evolving hydrological conditions and water resources storage, and provide reliable and robust predictions out to several months, as well as the capacity to act on this information. At longer time scales, planning and policy-making need to consider the potential impacts of climate change and its impact on drought risk, and do this within the context of natural climate variability, which is likely to dominate any climate change signal over the next few decades. There are several challenges that need to be met to advance our capability to provide both early warning at seasonal time scales and risk assessment under climate change, regionally and globally. Advancing our understanding of drought predictability and risk requires knowledge of drought at all time scales. This includes understanding of past drought occurrence, from the paleoclimate record to the recent past, and understanding of drought mechanisms, from initiation, through persistence to recovery and translation of this understanding to predictive models. Current approaches to monitoring and predicting drought are limited in many parts of the world, and especially in developing countries where national capacity is limited. Evaluation of past droughts and their mechanisms is limited by data availability and especially before the instrumental period of the last 50-100 years, for which there is reliance on incomplete spatial proxy data, such as tree rings. Seasonal predictability is currently mainly limited to tropical and sub-tropical regions through connections with sea surface temperature variations such as ENSO. Predictability in mid-latitudes is low and especially for precipitation, although dynamical model predictions appear to be edging statistical models in many aspects of seasonal prediction. This presentation describes ongoing research on evaluation of drought risk and drought mechanisms at regional to global scales with the eventual goal of developing a seamless monitoring and prediction framework at all time scales. Such a framework would allow consistent assessment of drought from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental global drought monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of drought variability over the 20th century, which forms the background climatology to which current conditions can be assessed and drought mechanisms can be diagnosed. Future drought risk is quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. Current research is focused on several aspects, including: 1) quantifying the uncertainties in historic drought reconstructions; 2) analysis of drought propagation through the coupled hydrological/vegetation system; 3) the utility of new data sources such as on the ground sensors and new satellite products for terrestrial hydrology and vegetation, for improved monitoring and prediction, especially in poorly observed regions; 4) advancing predictive skill for all aspects of drought occurrence through diagnosis of the driving mechanisms and feedbacks of historic droughts; and 5) quantification and reduction of uncertainties in future projections of drought under climate change. The steps towards the development of a seamless framework for analysis and prediction in the context of this research are discussed.

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Global Operational Remotely Sensed Evapotranspiration System for Water Resources Management: Case Study for the State of New Mexico

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Magnuson, M.; John, L.

2017-12-01

An operational system to produce and disseminate remotely sensed evapotranspiration using the PT-JPL model and support its analysis and use in water resources decision making is being integrated into the New Mexico state government. A partnership between the NASA Western Water Applications Office (WWAO), the Jet Propulsion Laboratory (JPL), and the New Mexico Office of the State Engineer (NMOSE) has enabled collaboration with a variety of state agencies to inform decision making processes for agriculture, rangeland, and forest management. This system improves drought understanding and mobilization, litigation support, and economic, municipal, and ground-water planning through interactive mapping of daily rates of evapotranspiration at 1 km spatial resolution with near real-time latency. This is facilitated by daily remote sensing acquisitions of land-surface temperature and near-surface air temperature and humidity from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite as well as the short-term composites of Normalized Difference Vegetation Index (NDVI) and albedo provided by MODIS. Incorporating evapotranspiration data into agricultural water management better characterizes imbalances between water requirements and supplies. Monitoring evapotranspiration over rangeland areas improves remediation and prevention of aridification. Monitoring forest evapotranspiration improves wildlife management and response to wildfire risk. Continued implementation of this decision support system should enhance water and food security.

Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

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

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Multiobjective optimization of urban water resources: Moving toward more practical solutions

NASA Astrophysics Data System (ADS)

Mortazavi, Mohammad; Kuczera, George; Cui, Lijie

2012-03-01

The issue of drought security is of paramount importance for cities located in regions subject to severe prolonged droughts. The prospect of "running out of water" for an extended period would threaten the very existence of the city. Managing drought security for an urban water supply is a complex task involving trade-offs between conflicting objectives. In this paper a multiobjective optimization approach for urban water resource planning and operation is developed to overcome practically significant shortcomings identified in previous work. A case study based on the headworks system for Sydney (Australia) demonstrates the approach and highlights the potentially serious shortcomings of Pareto optimal solutions conditioned on short climate records, incomplete decision spaces, and constraints to which system response is sensitive. Where high levels of drought security are required, optimal solutions conditioned on short climate records are flawed. Our approach addresses drought security explicitly by identifying approximate optimal solutions in which the system does not "run dry" in severe droughts with expected return periods up to a nominated (typically large) value. In addition, it is shown that failure to optimize the full mix of interacting operational and infrastructure decisions and to explore the trade-offs associated with sensitive constraints can lead to significantly more costly solutions.

7 CFR 718.103 - Prevented planted and failed acreage.

Code of Federal Regulations, 2014 CFR

2014-01-01

... prevented-planted acreage was affected by drought, unless: (1) On the final planting date for non-irrigated.... Drought Monitor; and (3) Verifiable information is collected from sources whose business or purpose it is... a lack of water resulting from drought conditions or contamination by saltwater intrusion of an...

7 CFR 718.103 - Prevented planted and failed acreage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... prevented-planted acreage was affected by drought, unless: (1) On the final planting date for non-irrigated.... Drought Monitor; and (3) Verifiable information is collected from sources whose business or purpose it is... a lack of water resulting from drought conditions or contamination by saltwater intrusion of an...

7 CFR 718.103 - Prevented planted and failed acreage.

Code of Federal Regulations, 2013 CFR

2013-01-01

... prevented-planted acreage was affected by drought, unless: (1) On the final planting date for non-irrigated.... Drought Monitor; and (3) Verifiable information is collected from sources whose business or purpose it is... a lack of water resulting from drought conditions or contamination by saltwater intrusion of an...

7 CFR 718.103 - Prevented planted and failed acreage.

Code of Federal Regulations, 2012 CFR

2012-01-01

... prevented-planted acreage was affected by drought, unless: (1) On the final planting date for non-irrigated.... Drought Monitor; and (3) Verifiable information is collected from sources whose business or purpose it is... a lack of water resulting from drought conditions or contamination by saltwater intrusion of an...

7 CFR 718.103 - Prevented planted and failed acreage.

Code of Federal Regulations, 2011 CFR

2011-01-01

... prevented-planted acreage was affected by drought, unless: (1) On the final planting date for non-irrigated.... Drought Monitor; and (3) Verifiable information is collected from sources whose business or purpose it is... a lack of water resulting from drought conditions or contamination by saltwater intrusion of an...

Remotely Sensed Quantitative Drought Risk Assessment in Vulnerable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.

2012-04-01

Hazard may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, economy and society. This paper deals with drought risk assessment, which the first step designed to find out what the problems are and comprises three distinct steps, namely risk identification, risk management which is not covered in this paper, there should be a fourth step to address the need for feedback and to take post-audits of all risk assessment exercises. In particular, quantitative drought risk assessment is attempted by using statistical methods. For the qualification of drought, the Reconnaissance Drought Index (RDI) is employed, which is a new index based on hydrometeorological parameters, such as precipitation and potential evapotranspiration. The remotely sensed estimation of RDI is based on NOA-AVHRR satellite data for a period of 20 years (1981-2001). The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Specifically, the undertaken drought risk assessment processes are specified as follows: 1. Risk identification: This step involves drought quantification and monitoring based on remotely sensed RDI and extraction of several features such as severity, duration, areal extent, onset and end time. Moreover, it involves a drought early warning system based on the above parameters. 2. Risk estimation: This step includes an analysis of drought severity, frequency and their relationships. 3. Risk evaluation: This step covers drought evaluation based on analysis of RDI images before and after each drought episode, which usually lasts one hydrological year (12month). The results of these three-step drought assessment processes are considered quite satisfactory in a drought-prone region such as Thessaly in central Greece. Moreover, remote sensing has proven very effective in delineating spatial variability and features in drought monitoring and assessment.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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 parties.

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

PubMed

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

2014-10-09

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

Joining Forces for Food Security - Linking Earth Observation and Crowd-sourcing for improved Decision-support

NASA Astrophysics Data System (ADS)

Enenkel, M.; Dorigo, W.; See, L. M.; Vinck, P.; Papp, A.

2014-12-01

Droughts statistically exceed all other natural disasters in complexity, spatio-temporal extent and number of people affected. Triggered by crop failure, food insecurity is a major manifestation of agricultural drought and water scarcity. However, other socio-economic precursors, such as chronically low levels of disaster preparedness, hampered access to food security or a lack of social safety nets are equally important factors. We will present the first results of the SATIDA (Satellite Technologies for Improved Drought-Risk Assessment) project, which advances three complementary developments. First, an existing drought indicator is enhanced by replacing in-situ measurements on rainfall and surface air temperature with satellite-derived datasets. We identify the vegetation status via a new noise-corrected and gap-filled vegetation index. In addition, we introduce a soil moisture component to close the gap between rainfall deficiencies, extreme temperature and the first visible impacts of atmospheric anomalies on vegetation. Second, once calibrated, the index is forced with seasonal forecasts to quantify their uncertainty and added value in the regions of interest. Third, a mobile application is developed to disseminate relevant visualizations to decision-makers in affected areas, to collect additional information about socio-economic conditions and to validate the output of the drought index in real conditions. Involving Doctors without Borders (MSF) as a key user, SATIDA aims at decreasing uncertainties in decision-making via a more holistic risk framework, resulting in longer lead times for disaster logistics in the preparedness phase.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2017-01-01

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

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.

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

PubMed Central

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

2017-01-01

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

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. 

Relating the dynamics of climatological and hydrological droughts in semiarid Botswana

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Research on Applicability Analysis of Drought Index in Liaoning Area

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

A Groundwater Resource Index (GRI) for drought monitoring and forecasting in a mediterranean climate

NASA Astrophysics Data System (ADS)

Mendicino, Giuseppe; Senatore, Alfonso; Versace, Pasquale

2008-08-01

SummaryDrought indices are essential elements of an efficient drought watching system, aimed at providing a concise overall picture of drought conditions. Owing to its simplicity, time-flexibility and standardization, the Standardized Precipitation Index (SPI) has become a very widely used meteorological index, even if it is not able to account for effects of aquifers, soil, land use characteristics, canopy growth and temperature anomalies. Many other drought indices have been developed over the years, with monitoring and forecasting purposes, also with the purpose of taking advantage of the opportunities offered by remote sensing and improved general circulation models (GCMs). Moreover, some aggregated indices aimed at capturing the different features of drought have been proposed, but very few drought indices are focused on the groundwater resource status. In this paper a novel Groundwater Resource Index (GRI) is presented as a reliable tool useful in a multi-analysis approach for monitoring and forecasting drought conditions. The GRI is derived from a simple distributed water balance model, and has been tested in a Mediterranean region, characterized by different geo-lithological conditions mainly affecting the summer hydrologic response of the catchments to winter precipitation. The analysis of the GRI characteristics shows a high spatial variability and, compared to the SPI through spectral analysis, a significant sensitivity to the lithological characterization of the analyzed region. Furthermore, the GRI shows a very high auto-correlation during summer months, useful for forecasting purposes. The capability of the proposed index in forecasting summer droughts was tested analyzing the correlation of the GRI April values with the mean summer runoff values of some river basins (obtaining a mean correlation value of 0.60) and with the summer NDVI values of several forested areas, where correlation values greater than 0.77 were achieved. Moreover, its performance was evaluated in forecasting the major historic drought events, finding that the GRI is a better predictor than the SPI in order to predispose adequate actions for facing summer drought, with just one year missed and no false alarms observed.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

National Snow and Ice Data Center |

Science.gov Websites

Temperature Glaciers Ice Sheets Permafrost Sea Ice Soil Moisture Snow ...search for more Scientific Data Web pages Data Sets Drought on the range Drought on the range Using satellite soil moisture data as a tool for drought monitoring. Read more ... SMAP Soil Moisture Active Passive Data (SMAP) NASA SMAP data

Spatial Variations in Drought Persistence in the South-Central U.S.

NASA Astrophysics Data System (ADS)

Leasor, Z. T.; Quiring, S. M.

2016-12-01

Drought is one of the most prominent climatic hazards in the south-central United States. This study examines spatial variations in meteorological drought persistence using high-resolution PRISM gridded precipitation data from 1900-2015. The Standardized Precipitation Index (SPI) is used to represent meteorological drought conditions. The study region covers Texas, Oklahoma, and Kansas. Droughts are first divided into different severity categories using the classification employed by the U.S. National Drought Monitor. The frequency and duration of each drought event is determined and this is used to calculate drought persistence. Our results indicate that drought persistence in the south-central U.S. varies as a function of drought severity. In addition, drought persistence also varies substantially over space and time. The probability of drought termination is a function of drought severity, geographic location and time of the year. In addition, there is evidence that drought persistence is influenced by global teleconnections and land-atmosphere interactions. The results of this drought persistence climatology can benefit seasonal forecasting and the current understanding of drought recovery.

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.

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.

43 CFR 4190.1 - Effect of wildfire management decisions.

Code of Federal Regulations, 2012 CFR

2012-10-01

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

43 CFR 4190.1 - Effect of wildfire management decisions.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

43 CFR 4190.1 - Effect of wildfire management decisions.

Code of Federal Regulations, 2013 CFR

2013-10-01

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

43 CFR 4190.1 - Effect of wildfire management decisions.

Code of Federal Regulations, 2014 CFR

2014-10-01

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

Joining forces for food security - Linking earth observation and crowd-sourcing for improved decision-support to aid organizations

NASA Astrophysics Data System (ADS)

Enenkel, M.; Dorigo, W.; See, L. M.; Vinck, P.; Pham, P.

2013-12-01

Droughts statistically exceed all other natural disasters in spatio-temporal extent, number of people affected or financial loss. Triggered by crop failure, food insecurity is a major manifestation of agricultural drought and water scarcity. However, other socio-economic precursors, such as chronically low levels of disaster preparedness, hampered access to food security or a lack of social safety nets are equally important factors. Consequently, this study is focused on two complementary developments - a new satellite-derived agricultural drought index and a mobile phone application. The Combined Drought Index (CDI) is enhanced by replacing field measurements of temperature and rainfall modelled/assimilated data. The vegetation component is replaced by a smoothed NDVI dataset. A soil moisture component is introduced to close the gap between rainfall deficiencies and the first visible impacts of atmospheric anomalies on vegetation. The mobile phone application enables the validation of drought index outputs and gives aid organizations an opportunity to increase the speed of socio-economic vulnerability assessments. Supported by Doctors without Borders (MSF) this approach aims at decreasing uncertainties in decision-making via a more holistic risk framework.

Ecological and meteorological drought monitoring in East Asia

NASA Astrophysics Data System (ADS)

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

2016-12-01

This study aims to how well the ecological drought index can capture the drought status in the East Asia. We estimated the drought severe index (DSI), which uses the evapotranspiration, potential evapotranspiration and the normalized difference vegetation index (NDVI), suggested by Mu et al. (2013) to define the ecological drought. In addition, the meteorological drought index, which is standardized precipitation and evapotranspiration index (SPEI), are estimated and compared to the DSI. The satellite data by moderate resolution imaging spectroradiometer (MODIS) and advanced very-high-resolution radiometer (AVHRR) are used to analyze the DSI and the monthly precipitation and temperature data in the climate research unit (CRU) are applied to estimate the SPEI for 2000-2013 in the East Asia. We conducted the statistical analyses to investigate the drought characteristics of the ecological and meteorological drought indices (i.e. the DSI and SPEI, respectively) and then compared those characteristics drought indices depending on the drought status. We found the DSI did not well captured the drought status when the categories originally suggested by Mu et al. (2013) are applied to divide the drought status in the study area. Consequently, the modified categories for the DSI in this study is suggested and then applied to define the drought status. The modified categories in this study show the great improvement to capture the drought status in the East Asia even though the results cannot be acquired around Taklamakan desert due to the lack of the satellite data. These results illustrate the ecological drought index, such as the DSI, can be applied for the monitoring of the drought in the East Asia and then can give the detailed information of drought status because the satellite data have the relatively high spatial resolutions compared to the observations such as the CRU data. Reference Mu Q, Zhao M, Kimball JS, McDowell NG, Running SW (2013) A remotely sensed global terrestrial drought severity index. Bulletin of the American Meteorological Society 94(1): 83-98. Acknowledgement This study was supported by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. Corresponding Author: yeonjoo.kim@yonsei.ac.kr

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.

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa Under Evolving Climate Conditions to Support Adaptation Strategies

NASA Astrophysics Data System (ADS)

Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.

2014-12-01

The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural, meteorological, and hydrologic drought and flood monitoring products (or indicators) that can enhance the preparedness for extreme climate events and climate change adaptation and mitigation strategies in the GHA. Even though this project is in its first year, the preliminary results and future plans to carry out the objectives will be presented.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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 different scales. One of these is a 15 meter resolution mosaic of the entire Mesoamerican region. This paper gives an overview of the SERVIR project and its associated visualization methods.

Mega drought in the Colorado River Basin, water supply, and adaptive scenario planning for the Phoenix Metropolitan Area; simulations using WaterSim 5.

NASA Astrophysics Data System (ADS)

Sampson, D. A.

2015-12-01

The Decision Center for a Desert City (DCDC), a boundary organization, bridges science and policy (to foster knowledge-based decision making); we study how decisions are made in the face of uncertainty. Our water policy and management model for the Phoenix Metropolitan Area (hereafter "Phoenix"), termed WaterSim, represents one such bridging mechanism. We evaluated the effect of varying the length of drought on water availability for Phoenix. We examined droughts (starting in 2000) lasting 15, 25, and 50 years. We picked a 60-year window of runoff estimates from the paleo reconstruction data for the Colorado River (CO) (1121 through 1180 A.D.), and the two local rivers (1391 through 1450 A.D.), and assumed that the proportional difference in median flow between these periods and the long-term record represented an estimate of potential drought reductions on river flows. This resulted in a 12%, and 19% reduction in flows for the CO River and the Salt-Verde (SV) Rivers, respectively. WaterSim uses 30-year trace periods from the historical flow records to simulate river flow for future projections. We used each 30-year trace from the historical record (1906 to present, CO River; 1945 to present SV Rivers) , and default settings, to simulate 60 year projections of Lake Mead elevation and the accompanying Colorado River water shortages to Phoenix. Overall, elevations for Lake Mead fell below the 1st shortage sharing tier (1075 ft) in 83% of the simulations; 74% of the simulations fell below the 2nd tier (1050 ft), and 64% fell below the 3rd (1025 ft). Length of drought, however, determined the shortage tiers met. Median elevations for droughts ending in 2015, 2025, and 2050 were 1036, 1019, and 967 feet msl, respectively. We present the plausible water futures with adaptive anticipatory scenario planning for the projected reductions in surface water availability to demonstrate decision points for water conservation measures to effectively manage shortage conditions.

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

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Kogan, F.

2012-12-01

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

7 CFR 760.305 - Eligible grazing losses.

Code of Federal Regulations, 2012 CFR

2012-01-01

... grazing losses. (a) A grazing loss due to drought is eligible for LFP only if the grazing loss for the... of grazing land or pastureland for the county, rated by the U.S. Drought Monitor as having a: (i) D2 (severe drought) intensity in any area of the county for at least 8 consecutive weeks during the normal...

7 CFR 760.305 - Eligible grazing losses.

Code of Federal Regulations, 2014 CFR

2014-01-01

... grazing losses. (a) A grazing loss due to drought is eligible for LFP only if the grazing loss for the... of grazing land or pastureland for the county, rated by the U.S. Drought Monitor as having a: (i) D2 (severe drought) intensity in any area of the county for at least 8 consecutive weeks during the normal...

7 CFR 760.305 - Eligible grazing losses.

Code of Federal Regulations, 2011 CFR

2011-01-01

... grazing losses. (a) A grazing loss due to drought is eligible for LFP only if the grazing loss for the... of grazing land or pastureland for the county, rated by the U.S. Drought Monitor as having a: (i) D2 (severe drought) intensity in any area of the county for at least 8 consecutive weeks during the normal...

7 CFR 760.305 - Eligible grazing losses.

Code of Federal Regulations, 2013 CFR

2013-01-01

... grazing losses. (a) A grazing loss due to drought is eligible for LFP only if the grazing loss for the... of grazing land or pastureland for the county, rated by the U.S. Drought Monitor as having a: (i) D2 (severe drought) intensity in any area of the county for at least 8 consecutive weeks during the normal...

Relationship between crown dieback and drought in the southeastern United States

Treesearch

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project

NASA Technical Reports Server (NTRS)

House, P. R.; Lapenta, W.; Schiffer, R.

2008-01-01

Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Identifying Decision Support Tools to Bridge Climate and Agricultural Needs in the Midwest

NASA Astrophysics Data System (ADS)

Hall, B. L.; Kluck, D. R.; Hatfield, J.; Black, C.; Kellner, O.; Woloszyn, M.; Timlin, M. S.

2015-12-01

Climate monitoring tools designed to help stakeholders reduce climate impacts have been developed for the primary Midwest field crops of corn and soybean. However, the region also produces vital livestock and specialty crops that currently lack similar climate monitoring and projection tools. In autumn 2015, the National Oceanic and Atmospheric Administration's (NOAA's) National Integrated Drought Information System (NIDIS) and Midwestern Regional Climate Center (MRCC) partnered with the US Department of Agriculture's Midwest Climate Hub to convene agriculture stakeholders, climate scientists, and climate service specialists to discuss climate impacts and needs for these two, often under-represented, sectors. The goals of this workshop were to (1) identify climate impacts that specialty crops and livestock producers face within the Midwest, (2) develop an understanding of the types of climate and weather information and tools currently available in the Midwest that could be applied to decision making, and (3) discover the types of climate and weather information and tools needed to address concerns of specialty crop and livestock commodities across the Midwest. This presentation will discuss the workshop and provide highlights of the outcomes that developed into strategic plans for the future to better serve these sectors of agriculture in the Midwest.

Risk identification of agricultural drought for sustainable agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-04-01

Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20 year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Development and assessment of Transpirative Deficit Index (D-TDI) for agricultural drought monitoring

NASA Astrophysics Data System (ADS)

Borghi, Anna; Rienzner, Michele; Gandolfi, Claudio; Facchi, Arianna

2017-04-01

Drought is a major cause of crop yield loss, both in rainfed and irrigated agroecosystems. In past decades, many approaches have been developed to assess agricultural drought, usually based on the monitoring or modelling of the soil water content condition. All these indices show weaknesses when applied for a real time drought monitoring and management at the local scale, since they do not consider explicitly crops and soil properties at an adequate spatial resolution. This work describes a newly developed agricultural drought index, called Transpirative Deficit Index (D-TDI), and assesses the results of its application over a study area of about 210 km2 within the Po River Plain (northern Italy). The index is based on transforming the interannual distribution of the transpirative deficit (potential crop transpiration minus actual transpiration), calculated daily by means of a spatially distributed conceptual hydrological model and cumulated over user-selected time-steps, to a standard normal distribution (following the approach proposed by the meteorological index SPI - Standard Precipitation Index). For the application to the study area a uniform maize crop cover (maize is the most widespread crop in the area) and 22-year (1993-2014) meteorological data series were considered. Simulation results consist in maps of the index cumulated over 10-day time steps over a mesh with cells of 250 m. A correlation analysis was carried out (1) to study the characteristics and the memory of D-TDI and to assess its intra- and inter-annual variability, (2) to assess the response of the agricultural drought (i.e., the information provided by D-TDI) to the meteorological drought computed through the SPI over different temporal steps. The D-TDI is positively auto-correlated with a persistence of 30 days, and positively cross-correlated to the SPI with a persistence of 40 days, demonstrating that D-TDI responds to meteorological forcing. Correlation analyses demonstrate that soils characterized by high available water content (AWC) can more easily compensate for a short-term variability in the precipitation pattern, while soils with low AWC are more strictly linked to the SPI variability. Since D-TDI relies both on climate and fine-resolution soil and land cover data, it provides a reliable measure of the evolution of agricultural drought over the territory with respect to that achieved through meteorological drought indices. The accumulation of the index over a 10-day period considering a mesh with cells of 250 m allows to capture the response of the territory to drought at time and spatial scales of interest for stakeholders. Modelling efforts utilizing the D-TDI have potential to shed light on the vulnerability of agricultural areas to drought; future work using the D-TDI as a tool to map drought prone areas could therefore improve the ability of farmers and irrigation district managers to cope with agricultural droughts and set up adaptation actions. Despite D-TDI was used in this study on historical data series, the index has the potential to be applied for real-time or provisional monitoring by incorporating real time or provisional meteorological data, giving the opportunity to stakeholders to promptly cope with droughts.

Bill Would Expand U.S. Drought Monitoring

NASA Astrophysics Data System (ADS)

Zielinski, Sarah

2006-05-01

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

Adaptive Management Methods to Protect the California Sacramento-San Joaquin Delta Water Resource

NASA Technical Reports Server (NTRS)

Bubenheim, David

2016-01-01

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Remote Sensing and Modeling for Improving Operational Aquatic Plant Management

NASA Technical Reports Server (NTRS)

Bubenheim, Dave

2016-01-01

The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

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

PubMed

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

2018-01-01

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

[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.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Drought Water Right Curtailment

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-04-23

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

Agricultural biomass monitoring on watersheds based on remotely sensed data.

PubMed

Tamás, János; Nagy, Attila; Fehér, János

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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;

On the potentials of multiple climate variables in assessing the spatio-temporal characteristics of hydrological droughts over the Volta Basin.

PubMed

Ndehedehe, Christopher E; Awange, Joseph L; Corner, Robert J; Kuhn, Michael; Okwuashi, Onuwa

2016-07-01

Multiple drought episodes over the Volta basin in recent reports may lead to food insecurity and loss of revenue. However, drought studies over the Volta basin are rather generalised and largely undocumented due to sparse ground observations and unsuitable framework to determine their space-time occurrence. In this study, we examined the utility of standardised indicators (standardised precipitation index (SPI), standardised runoff index (SRI), standardised soil moisture index (SSI), and multivariate standardised drought index (MSDI)) and Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water storage to assess hydrological drought characteristics over the basin. In order to determine the space-time patterns of hydrological drought in the basin, Independent Component Analysis (ICA), a higher order statistical technique was employed. The results show that SPI and SRI exhibit inconsistent behaviour in observed wet years presupposing a non-linear relationship that reflects the slow response of river discharge to precipitation especially after a previous extreme dry period. While the SPI and SSI show a linear relationship with a correlation of 0.63, the correlation between the MSDIs derived from combining precipitation/river discharge and precipitation/soil moisture indicates a significant value of 0.70 and shows an improved skill in hydrological drought monitoring over the Volta basin during the study period. The ICA-derived spatio-temporal hydrological drought patterns show Burkina Faso and the Lake Volta areas as predominantly drought zones. Further, the statistically significant negative correlations of pacific decadal oscillations (0.39 and 0.25) with temporal evolutions of drought in Burkina Faso and Ghana suggest the possible influence of low frequency large scale oscillations in the observed wet and dry regimes over the basin. Finally, our approach in drought assessment over the Volta basin contributes to a broad framework for hydrological drought monitoring that will complement existing methods while looking forward to a longer record of GRACE observations. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Co-creating Understanding in Water Use & Agricultural Resilience in a Multi-scale Natural-human System: Sacramento River Valley--California's Water Heartland in Transition

NASA Astrophysics Data System (ADS)

Fairbanks, D. H.; Brimlowe, J.; Chaudry, A.; Gray, K.; Greene, T.; Guzley, R.; Hatfield, C.; Houk, E.; Le Page, C.

2012-12-01

The Sacramento River Valley (SRV), valued for its $2.5 billion agricultural production and its biodiversity, is the main supplier of California's water, servicing 25 million people. . Despite rapid changes to the region, little is known about the collective motivations and consequences of land and water use decisions, or the social and environmental vulnerability and resilience of the SRV. The overarching research goal is to examine whether the SRV can continue to supply clean water for California and accommodate agricultural production and biodiversity while coping with climate change and population growth. Without understanding these issues, the resources of the SRV face an uncertain future. The defining goal is to construct a framework that integrates cross-disciplinary and diverse stakeholder perspectives in order to develop a comprehensive understanding of how SRV stakeholders make land and water use decisions. Traditional approaches for modeling have failed to take into consideration multi-scale stakeholder input. Currently there is no effective method to facilitate producers and government agencies in developing a shared representation to address the issues that face the region. To address this gap, researchers and stakeholders are working together to collect and consolidate disconnected knowledge held by stakeholder groups (agencies, irrigation districts, and producers) into a holistic conceptual model of how stakeholders view and make decisions with land and water use under various management systems. Our approach integrates a top-down approach (agency stakeholders) for larger scale management decisions with a conceptual co-creation and data gathering bottom-up approach with local agricultural producer stakeholders for input water and landuse decisions. Land use change models that combine a top-down approach with a bottom-up stakeholder approach are rare and yet essential to understanding how the social process of land use change and ecosystem function are linked. Data gathered in a survey of agency stakeholder perspectives on how producers operate with respect to crop types, fallowing and water transfers, production components and land changes were compared with monitoring data (1990-2011) covering two drought emergency time periods in the state. Results show that a synthesis is required between top-down and bottom-up approaches to understand land-use dynamics, as decision makers had a limited understanding on water and land-use decisions by land owners at the farm level. A major goal is to create a high level of transparency and stakeholder buy-in by co-developing a model of the system. The approach captures context-based parcel level changes that include the range of variability in natural-human systems such as decisions stakeholders make during drought vs. non-drought years. These decisions are crucial to understanding the tensions that current and future land-use change dynamics will place on the vulnerable hydrological system of the SRV. Knowledge gained through this effort will provide a rigorous conceptual understanding of how the primary land and water stakeholders in the SRV obtain and use water to accommodate competing interests of local agricultural production and resilience, environmental management, and regional and state water needs.

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

USGS Publications Warehouse

Austin, Samuel H.; Nelms, David L.

2017-01-01

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

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.

Risk identification of agricultural drought for sustainable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-09-01

Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote-sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Groundwater quality surrounding Lake Texoma during short-term drought conditions

USGS Publications Warehouse

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

2003-01-01

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

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Technical Reports Server (NTRS)

Rosevelt, Carolyn; Melton, Forrest S.; Johnson, Lee; Guzman, Alberto; Verdin, James P.; Thenkabail, Prasad S.; Mueller, Rick; Jones, Jeanine; Willis, Patrick

2016-01-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Guzman, A.; Verdin, J. P.; Thenkabail, P. S.; Mueller, R.; Jones, J.; Willis, P.

2015-12-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March - September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Weather Indices for Designing Micro-Insurance Products for Small-Holder Farmers in the Tropics

PubMed Central

Díaz Nieto, Jacqueline; Fisher, Myles; Cook, Simon; Läderach, Peter; Lundy, Mark

2012-01-01

Agriculture is inherently risky. Drought is a particularly troublesome hazard that has a documented adverse impact on agricultural development. A long history of decision-support tools have been developed to try and help farmers or policy makers manage risk. We offer site-specific drought insurance methodology as a significant addition to this process. Drought insurance works by encapsulating the best available scientific estimate of drought probability and severity at a site within a single number- the insurance premium, which is offered by insurers to insurable parties in a transparent risk-sharing agreement. The proposed method is demonstrated in a case study for dry beans in Nicaragua. PMID:22737210

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Groundwater vulnerability to drought in agricultural watersheds, S. Korea

NASA Astrophysics Data System (ADS)

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

2017-04-01

Drought can be generally defined by a considerable decrease in water availability due to a deficit in precipitation during a significant period over a large area. In South Korea, the severe drought occurred over late spring to early summer during from 2012 to 2015. In this period, precipitation decreased up to 10-40% compared with a normal one, resulting in reduction of stream flow and reservoir water over the country. It led to a shortage of irrigation water that caused great damage to grow rice plants on early stage. Furthermore, drought resulted in a negative effect on groundwater system with decline of its level. Change of the levels significantly reflects intrinsic characteristics of aquifer system. Identifying drought effects on groundwater system is very difficult because change of groundwater level after hydrological events tends to be delayed. Therefore, quantitative assessment on decline of groundwater level in agricultural watersheds plays an essential role to make customized policies for water shortage since groundwater system is directly affected by drought. Furthermore, it is common to analyze the time-series groundwater data from monitoring wells including hydrogeological characteristics in company with meteorological data because drought effects on groundwater system is site-specific. Currently, a total of 364 groundwater monitoring wells including 210 wells for rural groundwater management network(RGMN) and 154 wells for seawater intrusion monitoring network (SIMN) have been operating in agricultural watersheds in S. Korea. To estimate the effect of drought on groundwater system, monthly mean groundwater level data were obtained from RGMN and SIMN during the periods of 2012 to 2015. These data were compared to their past data in company with rainfall data obtained from adjacent weather stations. In 2012 and 2014, mean groundwater level data in the northern part of the country during irrigation season(April to June), when precipitation was recorded to 10% and 30% of an average one during the past 30 years, decreased up to 1.32 m and 0.71 m compared to that of the normal year, respectively. In 2015, mean groundwater level in the same area with 40% of a normal precipitation decreased up to 0.51-0.77 m. Consequently, total amounts of groundwater in aquifer have decreased due to the effect of periodic drought events during irrigation season. Effective policies should be required to manage groundwater vulnerability by drought in rural areas, South Korea.

Development of a SMAP-Based Drought Monitoring Product

NASA Astrophysics Data System (ADS)

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

2016-12-01

Agricultural drought is defined as a deficit in the amount of soil moisture over a prolonged period of time. Soil moisture information over time and space provides critical insight for agricultural management, including both water availability for crops and moisture conditions that affect management practices such as fertilizer, pesticide applications, and their impact as non-point pollution runoff. Since April of 2015, NASA's Soil Moisture Active Passive (SMAP) mission has retrieved soil moisture using L-band passive radiometric measurements at a 8 day repeat orbit with a swath of 1000 km that maps the Earth in 2-3 days depending on locations. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP soil moisture in terms of probability percentiles for dry (drought) or wet (pluvial) conditions. SMAP observations do result in retrievals that are spatially and temporally discontinuous. Additionally, the short SMAP record length provides a statistical challenge in estimating a drought index and thus drought risk evaluations. In this presentation, we describe a SMAP drought index for the CONUS region based on near-surface soil moisture percentiles. Because the length of the SMAP data record is limited, we use a Bayesian conditional probability approach to extend the SMAP record back to 1979 based on simulated soil moisture of the same period from the Variable Infiltration Capacity (VIC) Land Surface Model (LSM), simulated by Princeton University. This is feasible because the VIC top soil layer (10 cm) is highly correlated with the SMAP 36 km passive microwave during 2015-2016, with more than half the CONUS grids having a cross-correlation greater than 0.6, and over 0.9 in many regions. Given the extended SMAP record, we construct an empirical probability distribution of near-surface soil moisture drought index showing severities similar to those used by the U.S. Drought Monitor (from D0-D4), for a specific SMAP observation. The analysis is done for each of the 8,150 SMAP grids covering the CONUS domain. Comparisons between the SMAP drought index and that from the VIC LSM are presented for selected recent drought events. Issues such as seasonality, robustness of the fitting, regions of poor SMAP-VIC correlations, and extensions to other areas will be discussed.

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 soils. In addition the people's strategy to supply food is mapped through the use of gravity spatial choice models. This leads to the definition of hazard-specific risk zones, upon which to base the allocation of the calculated alerts. The performances of the proposed EWS were evaluated, for a selection of national case studies, with comparable ground-truth data derived from local food security assessments. The system is deployed on a WebGIS platform for its use by the widest possible audience.

Drought monitoring in the Brazilian Semiarid region.

PubMed

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

2017-10-16

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

Testing a new application for TOPSIS: monitoring drought and wet periods in Iran

NASA Astrophysics Data System (ADS)

Roshan, Gholamreza; Ghanghermeh, AbdolAzim; Grab, Stefan W.

2018-01-01

Globally, droughts are a recurring major natural disaster owing to below normal precipitation, and are occasionally associated with high temperatures, which together negatively impact upon human health and social, economic, and cultural activities. Drought early warning and monitoring is thus essential for reducing such potential impacts on society. To this end, several experimental methods have previously been proposed for calculating drought, yet these are based almost entirely on precipitation alone. Here, for the first time, and in contrast to previous studies, we use seven climate parameters to establish drought/wet periods; these include: T min, T max, sunshine hours, relative humidity, average rainfall, number of rain days greater than 1 mm, and the ratio of total precipitation to number of days with precipitation, using the technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. To test the TOPSIS method for different climate zones, six sample stations representing a variety of different climate conditions were used by assigning weight changes to climate parameters, which are then applied to the model, together with multivariate regression analysis. For the six stations tested, model results indicate the lowest errors for Zabol station and maximum errors for Kermanshah. The validation techniques strongly support our proposed new method for calculating and rating drought/wet events using TOPSIS.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2013-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2016-10-07

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

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

2016-01-01

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

Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

NASA Astrophysics Data System (ADS)

Lazrus, H.; Done, J.; Morss, R. E.

2017-12-01

A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.

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.

Streamflow, groundwater, and water-quality monitoring by USGS Nevada Water Science Center

USGS Publications Warehouse

Gipson, Marsha L.; Schmidt, Kurtiss

2013-01-01

The U.S. Geological Survey (USGS) has monitored and assessed the quantity and quality of our Nation's streams and aquifers since its inception in 1879. Today, the USGS provides hydrologic information to aid in the evaluation of the availability and suitability of water for public and domestic supply, agriculture, aquatic ecosystems, mining, and energy development. Although the USGS has no responsibility for the regulation of water resources, the USGS hydrologic data complement much of the data collected by state, county, and municipal agencies, tribal nations, U.S. District Court Water Masters, and other federal agencies such as the Environmental Protection Agency, which focuses on monitoring for regulatory compliance. The USGS continues its mission to provide timely and relevant water-resources data and information that are available to water-resource managers, non-profit organizations, industry, academia, and the public. Data collected by the USGS provide the science needed for informed decision-making related to resource management and restoration, assessment of flood and drought hazards, ecosystem health, and effects on water resources from land-use changes.

The importance of hot drought in providing more useful, and higher confidence, projections of future climatic, hydrologic, and ecosystem impacts.

NASA Astrophysics Data System (ADS)

Overpeck, J. T.; Udall, B. H.

2017-12-01

Often cited as a general guide to future climatic change, "the wet get wetter, and the dry get drier" is a misleading way to look towards the future for many regions of the globe, just as the simple use of multi-model ensemble projections of temperature and precipitation change averaged over many years can also be quite misleading for real-world planning and decision-making. Factors that support these assertions are multi-fold. First, we know with high confidence that warming will continue as long as greenhouse gas emissions continue. Second, continued warming will act to make droughts more frequent, longer and more severe in many regions. Even in the absence of precipitation declines, increases in evaporation and evapotranspiration, among other things, will drive regional drying. It is misleading to suggest to decision-makers that although the future may see an increase in drought risk, a projected increase in mean precipitation will counter-balance the increased drought risk. This counter-balancing will be absent during periods of precipitation-dominated drought. Moreover, projections of precipitation change are usually associated with much less confidence than projections of warming. For example, in places like the headwaters of the Colorado and Rio Grande Rivers, or East Africa, many models suggest we should be seeing an increase in precipitation, when in fact we are only seeing significant warming. Moreover, paleoclimatic evidence suggests that state-of-the-art Earth System Models may underestimate the risk of future multi-decadal droughts, even though these droughts have occurred in many regions during the last 2000 years. This reality suggests that even in regions that do see modest increases in mean precipitation, there will likely be periods in the future characterized by decades of below 20th century mean precipitation coupled with unprecedented warmth. Hot drought may be a much more widespread and serious threat than widely recognized.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Towards an integrated soil moisture drought monitor for East Africa

USDA-ARS?s Scientific Manuscript database

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

The European 2015 drought from a groundwater perspective

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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 the development of SIAM-SERVIR and the plans for the future.

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.

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).

Famine Early Warning System Network (FEWS NET)

USGS Publications Warehouse

Verdin, James P.

2006-01-01

The FEWS NET mission is to identify potentially food-insecure conditions early through the provision of timely and analytical hazard and vulnerability information. U.S. Government decision-makers act on this information to authorize mitigation and response activities. The U.S. Geological Survey (USGS) FEWS NET provides tools and data for monitoring and forecasting the incidence of drought and flooding to identify shocks to the food supply system that could lead to famine. Historically focused on Africa, the scope of the network has expanded to be global coverage. FEWS NET implementing partners include the USGS, National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), United States Agency for International Development (USAID), United States Department of Agriculture (USDA), and Chemonics International.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

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

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

NASA Technical Reports Server (NTRS)

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Return to normal streamflows and water levels: summary of hydrologic conditions in Georgia, 2013

USGS Publications Warehouse

Knaak, Andrew E.; Caslow, Kerry; Peck, Michael F.

2015-01-01

Drought conditions, persistent in the area since 2010, continued into the 2013 WY. In February 2013, Georgia was free of extreme (D3) drought conditions, as defined by the U.S. Drought Monitor, for the first time since August 2010 due to extended periods of heavy rainfall (U.S. Drought Monitor, 2013). According to the Office of the State Climatologist, the city of Savannah recorded 9.75 inches of rain in February 2013, the highest monthly total in February out of 143 years of record. Macon and Columbus also received record rainfalls in February 2013. Above-normal precipitation continued in June 2013, and the cities of Augusta and Savannah recorded the wettest June on record. In July, precipitation for the entire State of Georgia was 3.53 inches above normal (Dunkley, 2013). Above-normal rainfall from February to September 2013 increased streamflow and raised groundwater levels, and lakes and reservoirs were raised to full-pool elevations.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Impact of Initial Condition Errors and Precipitation Forecast Bias on Drought Simulation and Prediction in the Huaihe River Basin

NASA Astrophysics Data System (ADS)

Xu, H.; Luo, L.; Wu, Z.

2016-12-01

Drought, regarded as one of the major disasters all over the world, is not always easy to detect and forecast. Hydrological models coupled with Numerical Weather Prediction (NWP) has become a relatively effective method for drought monitoring and prediction. The accuracy of hydrological initial condition (IC) and the skill of NWP precipitation forecast can both heavily affect the quality and skill of hydrological forecast. In the study, the Variable Infiltration Capacity (VIC) model and Global Environmental Multi-scale (GEM) model were used to investigate the roles of IC and NWP forecast accuracy on hydrological predictions. A rev-ESP type experiment was conducted for a number of drought events in the Huaihe river basin. The experiment suggests that errors in ICs indeed affect the drought simulations by VIC and thus the drought monitoring. Although errors introduced in the ICs diminish gradually, the influence sometimes can last beyond 12 months. Using the soil moisture anomaly percentage index (SMAPI) as the metric to measure drought severity for the study region, we are able to quantify that time scale of influence from IC ranges. The analysis shows that the time scale is directly related to the magnitude of the introduced IC range and the average precipitation intensity. In order to explore how systematic bias correction in GEM forecasted precipitation can affect precipitation and hydrological forecast, we then both used station and gridded observations to eliminate biases of forecasted data. Meanwhile, different precipitation inputs with corrected data during drought process were conducted by VIC to investigate the changes of drought simulations, thus demonstrated short-term rolling drought prediction using a better performed corrected precipitation forecast. There is a word limit on the length of the abstract. So make sure your abstract fits the requirement. If this version is too long, try to shorten it as much as you can.

Evaluating the State of Water Management in the Rio Grande/Bravo Basin

NASA Astrophysics Data System (ADS)

Ortiz Partida, Jose Pablo; Sandoval-Solis, Samuel; Diaz Gomez, Romina

2017-04-01

Water resource modeling tools have been developed for many different regions and sub-basins of the Rio Grande/Bravo (RGB). Each of these tools has specific objectives, whether it is to explore drought mitigation alternatives, conflict resolution, climate change evaluation, tradeoff and economic synergies, water allocation, reservoir operations, or collaborative planning. However, there has not been an effort to integrate different available tools, or to link models developed for specific reaches into a more holistic watershed decision-support tool. This project outlines promising next steps to meet long-term goals of improved decision support tools and modeling. We identify, describe, and synthesize water resources management practices in the RGB basin and available water resources models and decision support tools that represent the RGB and the distribution of water for human and environmental uses. The extent body of water resources modeling is examined from a perspective of environmental water needs and water resources management and thereby allows subsequent prioritization of future research and monitoring needs for the development of river system modeling tools. This work communicates the state of the RGB science to diverse stakeholders, researchers, and decision-makers. The products of this project represent a planning tool to support an integrated water resources management framework to maximize economic and social welfare without compromising vital ecosystems.

USGS integrated drought science

USGS Publications Warehouse

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

2017-06-05

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

Drought Analysis for Kuwait Using Standardized Precipitation Index

PubMed Central

2014-01-01

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

Summary of Hydrologic Conditions in Georgia, 2008

USGS Publications Warehouse

Knaak, Andrew E.; Joiner, John K.; Peck, Michael F.

2009-01-01

The United States Geological Survey (USGS) Georgia Water Science Center (WSC) maintains a long-term hydrologic monitoring network of more than 290 real-time streamgages, more than 170 groundwater wells, and 10 lake and reservoir monitoring stations. One of the many benefits of data collected from this monitoring network is that analysis of the data provides an overview of the hydrologic conditions of rivers, creeks, reservoirs, and aquifers in Georgia. Hydrologic conditions are determined by statistical analysis of data collected during the current water year (WY) and comparison of the results to historical data collected at long-term stations. During the drought that persisted through 2008, the USGS succeeded in verifying and documenting numerous historic low-flow statistics at many streamgages and current water levels in aquifers, lakes, and reservoirs in Georgia. Streamflow data from the 2008 WY indicate that this drought is one of the most severe on record when compared to drought periods of 1950-1957, 1985-1989, and 1999-2002.

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.S. systems poses new challenges, particularly with respect to the generation of meteorological forcings that drive the land surface models. Agricultural and hydrological droughts are inherently defined in the context of a long-term climatology. Changes in observing platforms can be misinterpreted as droughts (or as excessively wet periods). This problem cannot simply be addressed through the addition of more observations or through the development of new observing platforms. Instead, it will require careful (re)construction of long-term records that are updated in near real-time in a consistent manner so that changes in surface meteorological forcings reflect actual conditions rather than changes in methods or sources.

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

USDA-ARS?s Scientific Manuscript database

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

Detecting and monitoring large-scale drought effects on forests: toward an integrated approach

Treesearch

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

2016-01-01

Although drought is recognized as an important and overarching driver of ecosystem change, its occurrence and effects have been difficult to describe over large geographic areas (Hogg and others 2008, Panu and Sharma 2002).

Online investigation of respiratory quotients in Pinus sylvestris and Picea abies during drought and shading by means of cavity-enhanced Raman multi-gas spectrometry.

PubMed

Hanf, Stefan; Fischer, Sarah; Hartmann, Henrik; Keiner, Robert; Trumbore, Susan; Popp, Jürgen; Frosch, Torsten

2015-07-07

Photosynthesis and respiration are major components of the plant carbon balance. During stress, like drought, carbohydrate supply from photosynthesis is reduced and the Krebs cycle respiration must be fueled with other stored carbon compounds. However, the dynamics of storage use are still unknown. The respiratory quotient (RQ, CO2 released per O2 consumed during respiration) is an excellent indicator of the nature of the respiration substrate. In plant science, however, online RQ measurements have been challenging or even impossible so far due to very small gas exchange fluxes during respiration. Here we apply cavity-enhanced multi-gas Raman spectrometry (CERS) for online in situ RQ measurements in drought-tolerant pine (Pinus sylvestris [L.]) and drought-intolerant spruce (Picea abies [L. H. Karst]). Two different treatments, drought and shading, were applied to reduce photosynthesis and force dependency on stored substrates. Changes in respiration rates and RQ values were continuously monitored over periods of several days with low levels of variance. The results show that both species switched from COH-dominated respiration (RQ = 1.0) to a mixture of substrates during shading (RQ = 0.77-0.81), while during drought only pine did so (RQ = 0.75). The gas phase measurements were complemented by concentration measurements of non-structural carbohydrates and lipids. These first results suggest a physiological explanation for greater drought tolerance in pine. CERS was proven as powerful technique for non-consumptive and precise real-time monitoring of respiration rates and respirational quotients for the investigation of plant metabolism under drought stress conditions that are predicted to increase with future climate change.

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 large sectors of Iberia for up to seven months (out of eleven) of the vegetative cycle. While in the case of the drought episode of 2005 the impact on vegetation covered roughly 2/3 of the Iberian Peninsula (Gouveia et al., 2012), whereas in the recent episode of 2012 the deficit in greenness affected a more restrictive area located in central Iberia. The vegetation response to water stress was also analysed and compared for different land cover types. Results revealed a stronger vulnerability to drought events for arable land with severe impacts on cereals crop productions and yield (namely wheat), for Portugal and Spain in both years, however slightly less severe for 2012. In conclusion, and from an operational point of view, our results reveal the ability of the developed methodology to monitor vegetation stress and droughts 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. Gouveia C., Trigo R. M., and DaCamara C. C., 2009: Drought and vegetation stress monitoring in Portugal using satellite data, Nat. Hazards Earth Syst. Sci., 9, 185-195, doi:10.5194/nhess-9-185- 2009. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C., 2012: Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards Earth System Sciences, 12, 3123-3137, 2012, doi:10.5194/nhess-12-3123-2012. Hoerling M., Eischeid J., Perlwitz J., Quan X., Zhang T., Pegion P., 2012: On the Increased Frequency of Mediterranean Drought. J. Climate, 25, 2146-2161. doi: http://dx.doi.org/10.1175/JCLI-D-11-00296.1 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.

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

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 humanitarian emergencies, the precipitation is used to monitoring potential drought events in the critical periods of the year. The methods employed and integrated different satellite data (Landsat and NASA-TRMM) in order to generate a proper database for the analysis of the seasonal movements according to climatological variations. Preliminary results will be presented and discussed.

Early warning by near-real time disturbance monitoring (Invited)

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Zeileis, A.; Herold, M.

2013-12-01

Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information illustrating how to apply the method on satellite image time series are available at http://bfast.R-Forge.R-project.org/ and the example section of the bfastmonitor() function within the BFAST package.

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

NASA Astrophysics Data System (ADS)

Crockett, J.; Westerling, A. L.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

Amirataee, Babak; Montaseri, Majid; Rezaie, Hossein

2018-01-15

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Drought and the risk of hospital admissions and mortality in older adults in western USA from 2000 to 2013: a retrospective study

PubMed Central

Berman, Jesse D; Ebisu, Keita; Peng, Roger D; Dominici, Francesca; Bell, Michelle L

2017-01-01

Background Occurrence, severity and geographic extent of droughts are anticipated to increase under climate change, but the health consequences of drought conditions are unknown. We estimate risks of cardiovascular and respiratory-related hospitalization and mortality associated with drought conditions for the western U.S. elderly population. Methods For counties in the western U.S. (N=618) and for the period 2000 to 2013, we use data from the U.S. Drought Monitor to identify: 1) full drought periods; 2) non-drought periods; and 3) worsening drought periods stratified by low- and high-severity. We use Medicare claims to calculate daily rates of cardiovascular admissions, respiratory admissions, and deaths among adults 65 years or older. Using a two-stage hierarchical model, we estimated the percentage change in health risks when comparing drought to non-drought period days controlling for daily weather and seasonal trends. Findings On average there were 2·1 million days and 0·6 million days classified as non-drought periods and drought periods, respectively. Compared to non-drought periods, respiratory admissions significantly decreased by −1·99% (95% posterior interval (PI): −3·56, −0·38) during the full drought period, but not during worsening drought conditions. Mortality risk significantly increased by 1·55% (95% PI: 0·17, 2·95) during the high-severity worsening drought period, but not the full drought period. Cardiovascular admissions did not differ significantly during either drought or worsening drought periods. In counties where drought occurred less frequently, we found risks for cardiovascular disease and mortality to increase during worsening drought conditions. Interpretations Drought conditions increased risk of mortality during high-severity worsening drought, but decreased the risk of respiratory admissions during full drought periods among older adults. Counties that experience fewer drought events show larger risk for mortality and cardiovascular disease. This research describes an understudied environmental association with global health significance. PMID:29057392

Drought and the risk of hospital admissions and mortality in older adults in western USA from 2000 to 2013: a retrospective study.

PubMed

Berman, Jesse D; Ebisu, Keita; Peng, Roger D; Dominici, Francesca; Bell, Michelle L

2017-04-01

Occurrence, severity and geographic extent of droughts are anticipated to increase under climate change, but the health consequences of drought conditions are unknown. We estimate risks of cardiovascular and respiratory-related hospitalization and mortality associated with drought conditions for the western U.S. elderly population. For counties in the western U.S. (N=618) and for the period 2000 to 2013, we use data from the U.S. Drought Monitor to identify: 1) full drought periods; 2) non-drought periods; and 3) worsening drought periods stratified by low- and high-severity. We use Medicare claims to calculate daily rates of cardiovascular admissions, respiratory admissions, and deaths among adults 65 years or older. Using a two-stage hierarchical model, we estimated the percentage change in health risks when comparing drought to non-drought period days controlling for daily weather and seasonal trends. On average there were 2·1 million days and 0·6 million days classified as non-drought periods and drought periods, respectively. Compared to non-drought periods, respiratory admissions significantly decreased by -1·99% (95% posterior interval (PI): -3·56, -0·38) during the full drought period, but not during worsening drought conditions. Mortality risk significantly increased by 1·55% (95% PI: 0·17, 2·95) during the high-severity worsening drought period, but not the full drought period. Cardiovascular admissions did not differ significantly during either drought or worsening drought periods. In counties where drought occurred less frequently, we found risks for cardiovascular disease and mortality to increase during worsening drought conditions. Drought conditions increased risk of mortality during high-severity worsening drought, but decreased the risk of respiratory admissions during full drought periods among older adults. Counties that experience fewer drought events show larger risk for mortality and cardiovascular disease. This research describes an understudied environmental association with global health significance.

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

Campana, P. E.; Zhang, J.; Yao, T.; Melton, F. S.; Yan, J.

2017-12-01

Climate change and drought have severe impacts on the agricultural sector affecting crop yields, water availability, and energy consumption for irrigation. Monitoring, assessing and mitigating the effects of climate change and drought on the agricultural and energy sectors are fundamental challenges that require investigation for water, food, and energy security issues. Using an integrated water-food-energy nexus approach, this study is developing a comprehensive drought management system through integration of real-time drought monitoring with real-time irrigation management. The spatially explicit model developed, GIS-OptiCE, can be used for simulation, multi-criteria optimization and generation of forecasts to support irrigation management. To demonstrate the value of the approach, the model has been applied to one major corn region in Nebraska to study the effects of the 2012 drought on crop yield and irrigation water/energy requirements as compared to a wet year such as 2009. The water-food-energy interrelationships evaluated show that significant water volumes and energy are required to halt the negative effects of drought on the crop yield. The multi-criteria optimization problem applied in this study indicates that the optimal solutions of irrigation do not necessarily correspond to those that would produce the maximum crop yields, depending on both water and economic constraints. In particular, crop pricing forecasts are extremely important to define the optimal irrigation management strategy. The model developed shows great potential in precision agriculture by providing near real-time data products including information on evapotranspiration, irrigation volumes, energy requirements, predicted crop growth, and nutrient requirements.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Developing Novel Reservoir Rule Curves Using Seasonal Inflow Projections

NASA Astrophysics Data System (ADS)

Tseng, Hsin-yi; Tung, Ching-pin

2015-04-01

Due to significant seasonal rainfall variations, reservoirs and their flexible operational rules are indispensable to Taiwan. Furthermore, with the intensifying impacts of climate change on extreme climate, the frequency of droughts in Taiwan has been increasing in recent years. Drought is a creeping phenomenon, the slow onset character of drought makes it difficult to detect at an early stage, and causes delays on making the best decision of allocating water. For these reasons, novel reservoir rule curves using projected seasonal streamflow are proposed in this study, which can potentially reduce the adverse effects of drought. This study dedicated establishing new rule curves which consider both current available storage and anticipated monthly inflows with leading time of two months to reduce the risk of water shortage. The monthly inflows are projected based on the seasonal climate forecasts from Central Weather Bureau (CWB), which a weather generation model is used to produce daily weather data for the hydrological component of the GWLF. To incorporate future monthly inflow projections into rule curves, this study designs a decision flow index which is a linear combination of current available storage and inflow projections with leading time of 2 months. By optimizing linear relationship coefficients of decision flow index, the shape of rule curves and the percent of water supply in each zone, the best rule curves to decrease water shortage risk and impacts can be developed. The Shimen Reservoir in the northern Taiwan is used as a case study to demonstrate the proposed method. Existing rule curves (M5 curves) of Shimen Reservoir are compared with two cases of new rule curves, including hindcast simulations and historic seasonal forecasts. The results show new rule curves can decrease the total water shortage ratio, and in addition, it can also allocate shortage amount to preceding months to avoid extreme shortage events. Even though some uncertainties in historic forecasts would result unnecessary discounts of water supply, it still performs better than M5 curves during droughts.

Dynamics of Individual and Collective Agricultural Adaptation to Water Scarcity

NASA Astrophysics Data System (ADS)

Burchfield, E. K.; Gilligan, J. M.

2016-12-01

Drought and water scarcity are challenging agricultural systems around the world. We draw on extensive field-work conducted with paddy farmers in rural Sri Lanka to study adaptations to water scarcity, including switching to less water-intensive crops, farming collectively on shared land, and turning to groundwater by digging wells. We explore how variability in climate affects agricultural decision-making at the community and individual levels using three decision-making heuristics, each characterized by an objective function: risk-averse expected utility, regret-adjusted expected utility, and prospect theory loss-aversion. We also assess how the introduction of individualized access to irrigation water with wells affects long-standing community-based drought mitigation practices. Results suggest that the growth of well-irrigation may produce sudden disruptions to community-based adaptations, but that this depends on the mental models farmers use to think about risk and make decisions under uncertainty.

Evaluation of Precipitation Indices for Global Crop Modeling and Definition of Drought Response Function to Yields

NASA Astrophysics Data System (ADS)

Kaneko, D.

2017-12-01

Climate change initiates abnormal meteorological disasters. Drought causes climate instability, thus producing poor harvests because of low rates of photosynthesis and sterile pollination. This research evaluates drought indices regarding precipitation and includes this data in global geophysical crop models that concern with evaporation, stomata opening, advection-effects from sea surface temperature anomalies, photosynthesis, carbon partitioning, crop yields, and crop production. Standard precipitation index (SPI) is a useful tool because of related variable not used in the stomata model. However, SPI is not an adequate tool for drought in irrigated fields. Contrary to expectations, the global comparisons of spatial characteristics between stomata opening/evapotranspiration and SPI for monitoring continental crop extremes produced serious defects and obvious differences between evapotranspiration and the small stomata-opening phenomena. The reason for this is that SPI does not include surface air temperature in its analysis. The Penman equation (Epen) describes potential evaporation better than SPI for recent hot droughts caused by climate change. However, the distribution of precipitation is a necessary condition for crop monitoring because it affirms the trend of the dry results computed by crop models. Consequently, the author uses global precipitation data observed by microwave passive sensors on TRMM and GCOM-W satellites. This remote sensing data conveniently supplies spatial distributions of global and seasonal precipitation. The author has designed a model to measure the effects of drought on crop yield and the degree of stomata closure related to the photosynthesis rate. To determine yield effects, the drought injury function is defined by integrating stomata closure during the two seasons from flowering to pollination. The stomata, defined by ratio between Epen and Eac, reflect the effects of drought and irrigation. Stomata-closure model includes the factors of soil moisture or irrigation effects inside the actual evapotranspiration computed using a complimentary model. The evaluation of precipitation indices provides necessary but not sufficient conditions for drought. They supply reference information for the trend/accuracy of an injury response function.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Serving California's Science and Governance Needs through Crisis-driven Collaborations

NASA Astrophysics Data System (ADS)

Bernacchi, L.

2015-12-01

Due to its magnitude, the ongoing drought in California (USA) serves as an experimental space for innovative resource management and will define responses to predicted widespread drought. Due to the magnitude of its effect on humans and natural ecosystems and the water resources on which they depend, governmental programs are granting support to scientifically-valid, locally-produced solutions to water scarcity. Concurrently, University of California Water (UC Water) Security and Sustainability Research Initiative is focused on strategic research to build the knowledge base for better water resources management. This paper examines how a team of transdisciplinary scientists are engaged in water governance and information, providing examples of actionable research successfully implemented by decision makers. From a sociology of science perspective, UC Water scientists were interviewed about their engagement practices with California water decision makers. Their "co-production of knowledge" relationships produce effective responses to climatic, landcover and population changes by expanding from singularly information-based, unidirectional communication to governance-relevant, co-constructed knowledge and wisdom. This is accomplished by serving on decision making organizational boards and developing information in a productive format. The perceived crisis of California's drought is an important impetus in cross-sector collaborations, and in combination with governance and institution parameters, defines the inquiry and decision space. We conclude by describing a process of clear problem-solution definition made possible through transparent communication, salient and credible information, and relevant tools and techniques for interpreting scientific findings.

Probabilistic assessment of phenophase-wise agricultural drought risk under different sowing windows: a case study with rainfed soybean.

PubMed

Dhakar, Rajkumar; Sarath Chandran, M A; Nagar, Shivani; Visha Kumari, V

2017-11-23

A new methodology for crop-growth stage-specific assessment of agricultural drought risk under a variable sowing window is proposed for the soybean crop. It encompasses three drought indices, which include Crop-Specific Drought Index (CSDI), Vegetation Condition Index (VCI), and Standardized Precipitation Evapotranspiration Index (SPEI). The unique features of crop-growth stage-specific nature and spatial and multi-scalar coverage provide a comprehensive assessment of agricultural drought risk. This study was conducted in 10 major soybean-growing districts of Madhya Pradesh state of India. These areas contribute about 60% of the total soybean production for the country. The phenophase most vulnerable to agricultural drought was identified (germination and flowering in our case) for each district across four sowing windows. The agricultural drought risk was quantified at various severity levels (moderate, severe, and very severe) for each growth stage and sowing window. Validation of the proposed new methodology also yielded results with a high correlation coefficient between percent probability of agricultural drought risk and yield risk (r = 0.92). Assessment by proximity matrix yielded a similar statistic. Expectations for the proposed methodology are better mitigation-oriented management and improved crop contingency plans for planners and decision makers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

NASA Technical Reports Server (NTRS)

Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

2013-01-01

In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

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

Climate Change, Drought and Human Health in Canada.

PubMed

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

2015-07-17

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

High resolution multi-scalar drought indices for Iberia

NASA Astrophysics Data System (ADS)

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

2014-05-01

The Iberian Peninsula has been recurrently affected by drought episodes and by adverse associated effects (Gouveia et al., 2009), ranging from severe water shortages to losses of hydroelectricity production, increasing risk of forest fires, forest decline and triggering processes of land degradation and desertification. Moreover, Iberia corresponds to one of the most sensitive areas to current and future climate change and is nowadays considered a hot spot of climate change with high probability for the increase of extreme events (Giorgi and Lionello, 2008). The spatial and temporal behavior of climatic droughts at different time scales was analyzed using spatially distributed time series of multi-scalar drought indicators, such as the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010). This new climatic drought index is based on the simultaneous use of precipitation and temperature fields with the advantage of combining a multi-scalar character with the capacity to include the effects of temperature variability on drought assessment. Moreover, reanalysis data and the higher resolution hindcasted databases obtained from them are valuable surrogates of the sparse observations and widely used for in-depth characterizations of the present-day climate. Accordingly, this work aims to enhance the knowledge on high resolution drought patterns in Iberian Peninsula, taking advantage of high-resolution (10km) regional MM5 simulations of the recent past (1959-2007) over Iberia. It should be stressed that these high resolution meteorological fields (e.g. temperature, precipitation) have been validated for various purposes (Jerez et al., 2013). A detailed characterization of droughts since the 1960s using the 10 km resolution hidncasted simulation was performed with the aim to explore the conditions favoring drought onset, duration and ending, as well as the subsequent short, medium and long-term impacts affecting the environment and the 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.

HYDRAULIC REDISTRIBUTION OF SOIL WATER DURING SUMMER DROUGHT IN TWO CONTRASTING PACIFIC NORTHWEST CONIFEROUS FORESTS

EPA Science Inventory

The magnitude of hydraulic redistribution of soil water by roots and its impact on soil water balance were estimated by monitoring time courses of soil water status at multiple depths and root sap flow during droughted conditions in a dry ponderosa pine ecosystem and a moist Doug...

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.

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

PubMed

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

2013-01-15

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

Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

NASA Astrophysics Data System (ADS)

Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad

2017-12-01

Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.

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 new countries have no local FEWS NET analysts, requiring increased reliance on remote sensing for detection of agricultural drought and potential food insecurity. USGS is increasing its cooperation with NASA, NOAA, and university partners to meet this challenge. New servers for near real time delivery of MODIS NDVI, satellite rainfall estimates, and gridded snow pack estimates are being established. A custom instance of NASA's Land Information System software is also being developed to create a land data assimilation system specifically for FEWS NET domains, data streams, and monitoring and forecast requirements. The system will take better advantage of remote sensing data, including promising new products from the Soil Moisture Active-Passive (SMAP) mission, by integrating them with surface observations for simulation of land surface processes. In this way, the continuous improvement of monitoring and modeling for famine early warning will advance to a new level of sophistication and effectiveness.

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.

Assessing Impacts of National Scale Droughts on Cereal Production

NASA Astrophysics Data System (ADS)

Udmale, P. D.; Ichikawa, Y.

2017-12-01

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

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.

The effects of drought on population structure, activity, and orientation of toads Bufo quercicus and B. terrestris at a temporary pond

USGS Publications Warehouse

Dodd, C.K.

1994-01-01

From 1985 through 1990, I monitored the populations of two species of toads, Bufo quercicus and B. terrestris, at a temporary pond in the xeric uplands of north-central Florida. A drift fence with pitfall traps completely encircled the pond basin; the fence was monitored 5 days per week throughout the year. The 5-year study coincided with a severe regional drought that resulted in generally short hydroperiods at unpredictable times of the year. More than 800 toads were captured. Successful metamorphosis never occurred at the pond although toads continued to visit it throughout the study. The sex ratio was male biased in B. quercicus but not in B. terrestris, although significant variation was observed from one year to the next. Likewise, the size-class structure and length-weight patterns varied among species, sexes, and years. Although fewer toads entered the pond basin as the study progressed, toads may have gone elsewhere to breed or they may have remained in refugia. Thus, decreased capture does not necessarily indicate that a drought-related population decline occurred. Drought may have disrupted normal arrival patterns and length of stay within the pond basin. Drought also could be responsible for variation in annual size-class structure of captured toads. The uncertainty of the hydroperiod both spatially and temporally in adjacent breeding sites, the ability of toads to move long distances with the potential for migration between breeding sites, and the lack of specificity in the choice of breeding sites (i.e. permanent versus different types of temporary wetlands) may lead to the formation of metapopulations in the xeric upland habitats of north-central Florida. Long-term monitoring under a variety of climatic conditions is needed to assess the effects of drought and other types of environmental stresses on toad populations.

Pasture Drought Insurance Based on NDVI and SAVI

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Near Real-Time Monitoring of Global Evapotranspiration and its Application to Water Resource Management

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Jewell, L. A.; Moore, G.; Verma, M.; McDonald, T.; Kim, S.; Muniz, A.

2016-12-01

Water scarcity and its impact on agriculture is a pressing world concern. At the heart of this crisis is the balance of water exchange between the land and the atmosphere. The ability to monitor evapotranspiration provides a solution by enabling sustainable irrigation practices. The Priestley-Taylor Jet Propulsion Laboratory model of evapotranspiration has been implemented to meet this need as a daily MODIS product with 1 to 5 km resolution. An automated data pipeline for this model implementation provides daily data with global coverage and near real-time latency using the Geospatial Data Abstraction Library. An interactive map providing on-demand statistical analysis enables water resource managers to monitor rates of water loss. To demonstrate the application of remotely-sensed evapotranspiration to water resource management, a partnership has been arranged with the New Mexico Office of the State Engineer (NMOSE). The online water research management tool was developed to meet the specifications of NMOSE using the Leaflet, GeoServer, and Django frameworks. NMOSE will utilize this tool to monitor drought and fire risk and manage irrigation. Through this test-case, it is hoped that real-time, user-friendly remote sensing tools will be adopted globally to make resource management decisions informed by the NASA Earth Observation System.

A Framework for Drought Risk Management

NASA Astrophysics Data System (ADS)

Apurv, T.; Cai, X.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The complex influence of ENSO on droughts in Ecuador

NASA Astrophysics Data System (ADS)

Vicente-Serrano, S. M.; Aguilar, E.; Martínez, R.; Martín-Hernández, N.; Azorin-Molina, C.; Sanchez-Lorenzo, A.; El Kenawy, A.; Tomás-Burguera, M.; Moran-Tejeda, E.; López-Moreno, J. I.; Revuelto, J.; Beguería, S.; Nieto, J. J.; Drumond, A.; Gimeno, L.; Nieto, R.

2017-01-01

In this study, we analyzed the influence of El Niño-Southern Oscillation (ENSO) on the spatio-temporal variability of droughts in Ecuador for a 48-year period (1965-2012). Droughts were quantified from 22 high-quality and homogenized time series of precipitation and air temperature by means of the Standardized Precipitation Evapotranspiration Index. In addition, the propagation of two different ENSO indices (El Niño 3.4 and El Niño 1 + 2 indices) and other atmospheric circulation processes (e.g., vertical velocity) on different time-scales of drought severity were investigated. The results showed a very complex influence of ENSO on drought behavior across Ecuador, with two regional patterns in the evolution of droughts: (1) the Andean chain with no changes in drought severity, and (2) the Western plains with less severe and frequent droughts. We also detected that drought variability in the Andes mountains is explained by the El Niño 3.4 index [sea surface temperature (SST) anomalies in the central Pacific], whereas the Western plains are much more driven by El Niño 1 + 2 index (SST anomalies in the eastern Pacific). Moreover, it was also observed that El Niño and La Niña phases enhance droughts in the Andes and Western plains regions, respectively. The results of this work could be crucial for predicting and monitoring drought variability and intensity in Ecuador.

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

USGS Publications Warehouse

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

2017-01-01

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

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

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on 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.

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

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on 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.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Fuzzy rule-based forecast of meteorological drought in western Niger

NASA Astrophysics Data System (ADS)

Abdourahamane, Zakari Seybou; Acar, Reşat

2018-01-01

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

43 CFR 5003.1 - Effect of decisions; general.

Code of Federal Regulations, 2013 CFR

2013-10-01

... risk of wildfire due to drought, fuels buildup, or other reasons, or at immediate risk of erosion or other damage due to wildfire, BLM may make a wildfire management decision made under this part and parts.... Wildfire management includes but is not limited to: (1) Fuel reduction or fuel treatment such as prescribed...

43 CFR 5003.1 - Effect of decisions; general.

Code of Federal Regulations, 2012 CFR

2012-10-01

... risk of wildfire due to drought, fuels buildup, or other reasons, or at immediate risk of erosion or other damage due to wildfire, BLM may make a wildfire management decision made under this part and parts.... Wildfire management includes but is not limited to: (1) Fuel reduction or fuel treatment such as prescribed...

43 CFR 5003.1 - Effect of decisions; general.

Code of Federal Regulations, 2014 CFR

2014-10-01

... risk of wildfire due to drought, fuels buildup, or other reasons, or at immediate risk of erosion or other damage due to wildfire, BLM may make a wildfire management decision made under this part and parts.... Wildfire management includes but is not limited to: (1) Fuel reduction or fuel treatment such as prescribed...

43 CFR 5003.1 - Effect of decisions; general.

Code of Federal Regulations, 2011 CFR

2011-10-01

... risk of wildfire due to drought, fuels buildup, or other reasons, or at immediate risk of erosion or other damage due to wildfire, BLM may make a wildfire management decision made under this part and parts.... Wildfire management includes but is not limited to: (1) Fuel reduction or fuel treatment such as prescribed...

Pioneers: A Simulation of Decision-Making on a Wagon Train.

ERIC Educational Resources Information Center

Wesley, John

This simulation allows students to participate in situations and events similar to those experienced by pioneers who headed west in early wagon trains. Students face problems such as floods, droughts, blocked trails, snakes, Indians, and the lack of food. Students must make numerous individual and small-group decisions that provide them with a…

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

Continuously increasing number of drought studies published in scientific journals reflects the attention of the scientific community paid to drought. The fundamental works among many others were published by Yevjevich (1967), Zelenhasic and Salvai (1987), later by Tallaksen and van Lanen Eds. (2004). The aim of the paper was to analyze the response of surface and groundwater to meteorological drought occurrence in the upper and middle part of the Topla River Basin, Slovakia. This catchment belongs to catchments with unfavourable hydrogeological conditions, being built of rocks with quite low permeability. The basin is located in the north-eastern part of Slovakia covering the area of 1050.05 km2. The response was analyzed using precipitation data from the Bardejov station (long-term annual average of 662 mm in 1981 - 2012) and discharge data from two gauging stations - Bardejov and Hanusovce nad Toplou. Data on groundwater head from eight observation wells, located in the catchment, were also used, covering the same observation period. Meteorological drought was estimated using characterisation of the year humidity and SPI index. Hydrological drought was evaluated using the threshold level method and method of sequent peak algorithm, both with the fixed and also variable thresholds. The centroid method of the cluster analysis with the squared Euclidean distance was used for clustering data according to occurrence of drought periods, lasting for 100 days and more. Results of the SPI index showed very good applicability for drought periods identification in the basin. The most pronounced dry periods occurred in 1982 - 1983, 1984, 1998 and 2012 being classified as moderately dry, and also in 1993 - 1994, 2003 - 2004 and 2007 evolving from moderately to severely dry years. Short-term drought prevailed in discharges, only three periods of drought longer than 100 days occurred during the evaluated period in 1986 - 1987, 1997 and 2003 - 2004. Discharge drought in the upper gauging station in Bardejov lasts usually longer than in Hanusovce nad Toplou station being located downstream. Higher number of short-term droughts was estimated for groundwater head in one monitoring well with the smallest depth of groundwater head below the surface. In this case, the influence of evapotranspiration could be the reason. More long-term droughts were estimated by TLM method for groundwater heads in other seven monitoring wells. Those droughts lasted for tens of weeks since summer until the spring of the next year. No regularity in temporal groundwater head drought propagation downstream the Topla River was discovered. However, results of the cluster analysis showed some common features of long-term drought periods (more than 100 days) occurrence for two groups of wells. Different hydrogeological conditions in two evaluated wells were also reflected in drought periods number and severity. The research was financially supported by APVV-0089-12 project (principal investigator Miriam Fendekova).

Investigation of drought-vulnerable regions in North Korea using remote sensing and cloud computing climate data.

PubMed

Yu, Jinhang; Lim, Joongbin; Lee, Kyoo-Seock

2018-02-08

Drought is one of the most severe natural disasters in the world and leads to serious challenges that affect both the natural environment and human societies. North Korea (NK) has frequently suffered from severe and prolonged droughts since the second half of the twentieth century. These droughts affect the growing conditions of agricultural crops, which have led to food shortages in NK. However, it is not easy to obtain ground data because NK is one of the most closed-off societies in the world. In this situation, remote sensing (RS) techniques and cloud computing climate data (CCCD) can be used for drought monitoring in NK. RS-derived drought indices and CCCD were used to determine the drought-vulnerable regions in the spring season in NK. After the results were compared and discussed, the following conclusions were derived: (1) 10.0% of the total area of NK is estimated to be a drought-vulnerable region. The most susceptible regions to drought appear in the eastern and western coastal regions, far from BaekDu-DaeGan (BDDG), while fewer drought regions are found near BDDG and the Nahngrim Mountains. The drought-vulnerable regions are the coastal regions of South Hamgyong Province, North Hamgyong Province, South Pyongan Province, and South Hwanghae Province. The latter region is the food basket of NK. (2) In terms of land cover, the drought-vulnerable regions mainly consisted of croplands and mixed forest.

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.

Assessing the remote sensing derived evaporative stress index with ground observations of crop conditions to advance drought early warning

USDA-ARS?s Scientific Manuscript database

Drought has significant impacts over broad spatial and temporal scales, and information about the timing and extent of such conditions is of critical importance to many end users in the agricultural and water resource management communities. The ability to accurately monitor effects on crops, and p...

Trends in snag populations in drought-stressed mixed-conifer and ponderosa pine forests (1997-2007)

Treesearch

Joseph L. Ganey; Scott C. Vojta

2012-01-01

Snags provide important biological legacies, resources for numerous species of native wildlife, and contribute to decay dynamics and ecological processes in forested ecosystems. We monitored trends in snag populations from 1997 to 2007 in drought-stressed mixed-conifer and ponderosa pine (Pinus ponderosa Dougl. ex Laws) forests, northern Arizona. Median snag density...

Biomass measurement from LANDSAT: Drought and energy applications

NASA Technical Reports Server (NTRS)

Maxwell, E. L.

1981-01-01

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

Science and Systems in Support of Multi-hazard Early Warnings and Decisions

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2015-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

Designing basin-customized combined drought indices via feature extraction

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

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

Groundwater Change in Storage Estimation by Using Monitoring Wells Data

NASA Astrophysics Data System (ADS)

Flores, C. I.

2016-12-01

In present times, remarkable attention is being given to models and data in hydrology, regarding their role in meeting water management requirements to enable well-informed decisions. Water management under the Sustainable Groundwater Management Act (SGMA) is currently challenging, due to it requires that groundwater sustainability agencies (GSAs) formulate groundwater sustainability plans (GSPs) to comply with new regulations and perform a responsible management to secure California's groundwater resources, particularly when droughts and climate change conditions are present. In this scenario, water budgets and change in groundwater storage estimations are key components for decision makers, but their computation is often difficult, lengthy and uncertain. Therefore, this work presents an innovative approach to integrate hydrologic modeling and available groundwater data into a single simplified tool, a proxy function, that estimate in real time the change in storage based on monitoring wells data. A hydrologic model was developed and calibrated for water years 1970 to 2015, the Yolo County IWFM, which was applied to generate the proxy as a study case, by regressing simulated change in storage versus change in head for the cities of Davis and Woodland area, and obtain a linear function dependent on heads variations over time. Later, the proxy was applied to actual groundwater data in this region to predict the change in storage. Results from this work provide proxy functions to approximate change in storage based on monitoring data for daily, monthly and yearly frameworks, being as well easily transferable to any spreadsheet or database to perform simply yet crucial computations in real time for sustainable groundwater management.

Linking regional initiatives to improve predictions of drought impacts on living marine resources in the U.S. Southeast: Apalachicola Bay oyster fishery as a potential test case

NASA Astrophysics Data System (ADS)

Petes, L.; McNutt, C.; Burkett, V.; Jones, S.

2009-12-01

In 2007, the U.S. Southeast experienced one of the worst droughts on record. Since 1970, moderate-to-severe droughts in the Southeast have increased by 12-14% and annual average temperature has risen over 1°C. Several global climate models also project warming across the Southeast and an increased rate of warming through the end of the century. The Southeast has also undergone unprecedented growth, with some counties of Florida and Georgia populations increasing by over 500% in the last several decades, further increasing the demand for water resources during times of drought. Two regional efforts are currently underway to help inform constituents about adaptation to climate variability and change in the Southeast region. The first effort is the National Integrated Drought Information System (NIDIS), led by NOAA. NIDIS serves as an early warning system for drought through the consolidation of physical/hydrological and socioeconomic impact data, engages those affected by drought, integrates observing networks, and delivers decision-support tools to end-users. The second effort is the USGS’ National Climate Change and Wildlife Science Center, which will facilitate linking global and regional climate models to ecological and biological responses at spatial and temporal resolutions that will inform resource management decisions. Both efforts will be operating in the Apalachicola-Chattahoochee-Flint (ACF) River Basin. During the 2007 drought, one of the most publicized impacts was on the oyster fishery in Apalachicola Bay. Reduced regional precipitation along with associated higher demands for water uses in the ACF reduced downstream flow into the Bay, producing harmful effects on the oyster fishery and associated ecosystem. Changes in estuarine salinity resulting from alterations in streamflow can lead to impacts on species abundance and community composition. Drought can also lead to changes in predator-prey interactions, as marine predators typically move into estuaries when salinity is high. Experiments have shown that Apalachicola oysters suffer significant mortality due to increased disease load and higher predation pressure under high-salinity, drought conditions. There is currently little information, however, on how drought will influence species interactions, distributions, and abundances in estuarine ecosystems, and how this in turn will affect biodiversity and ecosystem function. Improved linking of hydrologic and climatic models to biological systems is needed in order for resource managers to better predict and mitigate ecosystem changes resulting from drought and climate change. There now exists an opportunity to link the NIDIS and USGS regional efforts to gain a better understanding of how interrelated factors, such as competing demands for water resources in the ACF Basin, changes in the frequency and duration of drought, and management of the reservoirs will affect downstream ecosystems such as the estuarine environment and the oyster fishery in Apalachicola Bay.

Informing climate change adaptation with insights from famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J. P.

2010-12-01

Famine early warning systems provide a unique viewpoint for understanding the implications of climate change on food security, identifying the locations and seasons where millions of food insecure people are dependent upon climate-sensitive agricultural systems. The Famine Early Warning Systems Network (FEWS NET) is a decision support system sponsored by the Office of Food for Peace of the U.S. Agency for International Development (USAID), which distributes over two billion dollars of food aid to more than 40 countries each year. FEWS NET identifies the times and places where food aid is required by the most climatically sensitive and consequently food insecure populations of the developing world. As result, FEWS NET has developed its own "climate service", implemented by USGS, NOAA, and NASA, to support its decision making processes. The foundation of this climate service is the monitoring of current growing conditions for early identification of agricultural drought that might impact food security. Since station networks are sparse in the countries monitored, FEWS NET has a tradition (dating back to 1985) of reliance on satellite remote sensing of vegetation and rainfall. In the last ten years, climate forecasts have become an additional tool for food security assessment, extending the early warning perspective to include expected agricultural outcomes for the season ahead. More recently, research has expanded to include detailed analyses of recent observed climate trends, combined with diagnostic ocean-atmosphere studies. These studies are then used to develop interpretations of GCM scenarios and their implications for future patterns of precipitation and temperature, revealing trends towards warmer/drier climate conditions and increases in the relative frequency of drought. In some regions, like Eastern Africa, such changes seem to be already occurring, with an associated increase in food insecurity. Sub-national analyses for Kenya, for example, point to the need for adaptation through improved agricultural practices, so that increased yields can offset the impacts of rising temperatures and declining rainfall. Future work will focus on assessing temperature-PET linkages, and evaluating pathways for agricultural development.

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.; Hooten, Mevin B.; Dubovsky, James A.; Drewien, Roderick C.

2015-01-01

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment.Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression.Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect.Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond.Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

Nauditt, Alexandra; Metzke, Daniel; Ribbe, Lars

2017-04-01

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

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

Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with 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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Contrasting dynamics of leaf potential and gas exchange during progressive drought cycles and recovery in Amorpha fruticosa and Robinia pseudoacacia.

PubMed

Yan, Weiming; Zheng, Shuxia; Zhong, Yangquanwei; Shangguan, Zhouping

2017-06-30

Leaf gas exchange is closely associated with water relations; however, less attention has been given to this relationship over successive drought events. Dynamic changes in gas exchange and water potential in the seedlings of two woody species, Amorpha fruticosa and Robinia pseudoacacia, were monitored during recurrent drought. The pre-dawn leaf water potential declined in parallel with gas exchange in both species, and sharp declines in gas exchange occurred with decreasing water potential. A significant correlation between pre-dawn water potential and gas exchange was observed in both species and showed a right shift in R. pseudoacacia in the second drought. The results suggested that stomatal closure in early drought was mediated mainly by elevated foliar abscisic acid (ABA) in R. pseudoacacia, while a shift from ABA-regulated to leaf-water-potential-driven stomatal closure was observed in A. fruticosa. After re-watering, the pre-dawn water potential recovered quickly, whereas stomatal conductance did not fully recover from drought in R. pseudoacacia, which affected the ability to tightly control transpiration post-drought. The dynamics of recovery from drought suggest that stomatal behavior post-drought may be restricted mainly by hydraulic factors, but non-hydraulic factors may also be involved in R. pseudoacacia.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Hydrologic modeling for monitoring water availability in Africa and the Middle East

NASA Astrophysics Data System (ADS)

McNally, A.; Getirana, A.; Arsenault, K. R.; Peters-Lidard, C. D.; Verdin, J. P.

2015-12-01

Drought impacts water resources required by crops and communities, in turn threatening lives and livelihoods. Early warning systems, which rely on inputs from hydro-climate models, are used to help manage risk and provide humanitarian assistance to the right place at the right time. However, translating advancements in hydro-climate science into action is a persistent and time-consuming challenge: scientists and decision-makers need to work together to enhance the salience, credibility, and legitimacy of the hydrological data products being produced. One organization that tackles this challenge is the Famine Early Warning Systems Network (FEWS NET), which has been using evidence-based approaches to address food security since the 1980s.In this presentation, we describe the FEWS NET Land Data Assimilation System (FLDAS), developed by FEWS NET and NASA hydrologic scientists to maximize the use of limited hydro-climatic observations for humanitarian applications. The FLDAS, an instance of the NASA Land Information System (LIS), is comprised of land surface models driven by satellite rainfall inputs already familiar to FEWS NET food security analysts. First, we evaluate the quality of model outputs over parts of the Middle East and Africa using remotely sensed soil moisture and vegetation indices. We then describe derived water availability indices that have been identified by analysts as potentially useful sources of information. Specifically, we demonstrate how the Baseline Water Stress and Drought Severity Index detect recent water availability crisis events in the Tigris-Euphrates Basin and the Gaborone Reservoir, Botswana. Finally we discuss ongoing work to deliver this information to FEWS NET analysts in a timely and user-friendly manner, with the ultimate goal of integrating these water availability metrics into regular decision-making activities.

Using FRET for Drought Mitigation

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed Central

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

2016-01-01

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

Desert tortoise (Gopherus agassizii) survival at two eastern Mojave Desert sites: Death by short-term drought?

USGS Publications Warehouse

Longshore, Kathleen M.; Jaeger, Jef R.; Sappington, J. Mark

2003-01-01

Survival of adult Desert Tortoises (Gopherus agassizii) appears related to site-specific variation in precipitation and productivity of annual plants. We studied adult tortoise survival rates at two closely situated, but physiographically different, sites in the eastern Mojave Desert over a nine-year period (spring 1992 to spring 2001). Survival rates were initially derived from population surveys conducted over a three-year period and by radio-telemetry monitoring over a seven-year period beginning in 1994. After a period of initial stability, survival rates on the two sites diverged over the study period, and seven-year survival rates estimated from radio-telemetry monitoring were 0.900 and 0.269, respectively. A die-off in 1996 on the latter site appears to have been triggered by a period of drought, which began in the summer of 1995, coupled with a failure of annual vegetation production in 1996. Depressed survival rates on this site were associated with drought conditions during three of four years. Although the decline had the appearance of an epizootic, there were no clinical signs of disease. Relatively short-term drought, combined with little or no annual biomass, appears to have caused severe reductions in tortoise survival. If periods of drought-induced low survival are common over relatively small areas, then source-sink population dynamics may be an important factor determining tortoise population densities.

New drought indices from the assimilation of satellite data

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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 the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Drought impact functions as intermediate step towards drought damage assessment

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Drought allocations using the Systems Impact Assessment Model: Klamath River

USGS Publications Warehouse

Flug, M.; Campbell, S.G.

2005-01-01

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

Water-resources optimization model for Santa Barbara, California

USGS Publications Warehouse

Nishikawa, Tracy

1998-01-01

A simulation-optimization model has been developed for the optimal management of the city of Santa Barbara's water resources during a drought. The model, which links groundwater simulation with linear programming, has a planning horizon of 5 years. The objective is to minimize the cost of water supply subject to: water demand constraints, hydraulic head constraints to control seawater intrusion, and water capacity constraints. The decision variables are montly water deliveries from surface water and groundwater. The state variables are hydraulic heads. The drought of 1947-51 is the city's worst drought on record, and simulated surface-water supplies for this period were used as a basis for testing optimal management of current water resources under drought conditions. The simulation-optimization model was applied using three reservoir operation rules. In addition, the model's sensitivity to demand, carry over [the storage of water in one year for use in the later year(s)], head constraints, and capacity constraints was tested.

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

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

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

USGS Publications Warehouse

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

2005-01-01

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

How rural land use management facilitates drought risk adaptation in a changing climate - A case study in arid northern China.

PubMed

Lei, Yongdeng; Zhang, Hailin; Chen, Fu; Zhang, Linbo

2016-04-15

Under a warming climate, frequent drought and water scarcity in northern China have severely disrupted agricultural production and posed a substantial threat to farmers' livelihoods. Based on first-hand data collected through in-depth interviews with local managers and farmer households, this study evaluated the effectiveness of rural land use management in mitigating drought risk, ensuring food security and improving farmers' livelihoods. Our findings indicate that a) reforestation on low-yield cropland not only can improve the eco-environment but can also prominently mitigate the production risk to local farmers; b) replacing the traditional border irrigation with sprinkler irrigation has substantially curbed agricultural water usage and increased the per unit of output; and c) in recent years, instead of planting water-intensive grain crops, local farmers cultivated more forage crops to raise animals, which greatly diversified their income sources and reduced the drought risk of agricultural production. By performing an empirical case study in drought-prone Inner Mongolia, this study provides decision-makers with insights into how to strategically adapt to drought risk and reduce rural poverty within the broader context of climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Ruhoff, Anderson

2014-05-01

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

Comparison of Historically Severe Droughts and the Vulnerability of Agroecosystems in Mid-Continent USA: Lessons Learned

NASA Astrophysics Data System (ADS)

Olson, C.; Rippey, B.

2016-12-01

Extreme climatic events, drought, flooding, severe storms, tropical cyclones and winter storms have cost the USA billions of dollars. Although among major natural disasters in the last 100 years, severe drought occurrences are lower in terms of discrete events than that for other extreme events, the average cost per drought event exceeds all but those of severe storms and tropical cyclones and has significantly impacted the US agroecosystems upon which much of the domestic and export food markets depend1. The impacts from the 2012, 1988, and 1950's droughts are compared with the effects on cropland in the Mid-Continent US. Drought severity in 2012 and in 1988 were similar in terms of economic agricultural loss, 40 and 31 billion in cost-adjusted dollars, respectively. The 2012 drought covered a geographic areal extent similar to that of an earlier drought in the 1950's; roughly 2/3 of the central USA was impacted. However, the 2012 drought developed relatively rapidly in less than a year whereas the drought of the 1950's was marked by multiple years of extreme heat and lack of precipitation. Each of these severe droughts has resulted in significant losses, but the 2012 drought, while costly, could have been a larger economic disaster had the same conditions occurred in the 1950's or 1988. Investment in new technology, improvements in irrigation efficiency and advanced drainage systems, targeted soil conservation practices, and flexibility to adapt to conditions have improved the resilience of agroecosystems to drought in the intervening years. Droughts continue to occur, so a better understanding of climate and available climate services along with sustained investment in new technology will improve drought tolerance. The recent establishment of USDA Regional Climate Hubs to translate and deliver science-based, region-specific information for individual natural resource managers will enable climate-smart decision-making. Implementation is now possible at scales appropriate to identify regional and potentially local vulnerabilities and rapidly assess needs and capabilities. Downscaled climate projections developed by USDA partners and tailored to regional needs will become essential tools for future drought resilience. 1. Data trends derived from www.ncdc.noaa.gov/billions/summary-stats

Implications of the 2015 European drought on groundwater storage

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Hydraulic redistribution of soil water during summer drought in two contrasting Pacific Northwest coniferous forests.

Treesearch

J. Renee Brooks; Frederick C. Meinzer; Rob Coulombe; Jillian Gregg

2002-01-01

The magnitude of hydraulic redistribution of soil water by roots and its impact on soil water balance were estimated by monitoring time courses of soil water status and multiple depths and root sap flow under drought conditions in a dry ponderosa pine (Pinus ponderosa Dougl. ex Laws) ecosystem and in a moist Douglas-fir (Pseudotsuga...

Trends in snag populations in Northern Arizona mixed-conifer and ponderosa pine forests, 1997-2012

Treesearch

J. L. Ganey; S. C. Vojta

2014-01-01

We monitored snag populations in drought-stressed mixed-conifer and ponderosa pine (Pinus ponderosa) forests, northern Arizona, at 5-yr intervals from 1997-2012. Snag density increased from 1997-2007 in both forest types, with accelerated change due to drought-related tree mortality during the period 2002-2007. Snag density declined non-significantly from 2007-2012,...

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

The relative influence of climate and catchment properties on hydrological drought

NASA Astrophysics Data System (ADS)

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

2014-05-01

Studying hydrological drought (a below-normal water availability in groundwater, lakes and streams) is important to society and the ecosystem, but can also reveal interesting information about catchment functioning. This information can later be used for predicting drought in ungauged basins and to inform water management decisions. In this study, we used an extensive Austrian dataset of discharge measurements in clusters of catchments and combine this dataset with thematic information on climate and catchment properties. Our aim was to study the relative effects of climate and catchment characteristics on drought duration and deficit and on hydrological drought typology. Because the climate of the region is roughly uniform, our hypothesis was that the effect of differences of catchment properties would stand out. From time series of precipitation and discharge we identified droughts with the widely-used threshold level approach, defining a drought when a variable falls below a pre-defined threshold representing the regime. Drought characteristics that were analysed are drought duration and deficit. We also applied the typology of Van Loon & Van Lanen (2012). To explain differences in drought characteristics between catchments we did a correlation analysis with climate and catchment characteristics, based on Pearson correlation. We found very interesting patterns in the correlations of drought characteristics with climate and catchment properties: 1) Droughts with long duration (mean and maximum) and composite droughts are related to catchments with a high BFI (high baseflow) and a high percentage of shallow groundwater tables. 2) The deficit (mean and maximum) of both meteorological droughts and hydrological droughts is strongly related to catchment humidity, in this case quantified by average annual precipitation. 3) The hydrological drought types that are related to snow, i.e. cold snow season drought and snow melt drought, occur in catchments that are have a high elevation, steep slopes, a high percentage of crystalline rock, bare rock and glacier. The conclusion of our research is that it is not straightforward to separate the effects of climate and catchment properties on drought, since they are interrelated. This is especially true for mountainous regions where temperature and precipitation are strongly dependent on altitude. We did however see that the duration of drought is more related to catchment storage (catchment properties) and the severity of drought (represented by the drought deficit) is more related to catchment wetness (climate). Van Loon, A.F., and Van Lanen, H.A.J.: A process-based typology of hydrological drought, Hydrology and Earth System Science, 16, p. 1915-1946, doi: 10.5194/hess-16-1915-2012, 2012

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 in the development of SIAM-SERVIR and the plans for the future.

A soil water based index as a suitable agricultural drought indicator

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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

PubMed

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

2016-09-12

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

Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

NASA Astrophysics Data System (ADS)

Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

2017-01-01

The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit regional decision makers.

Compilation of 1991 Annual Reports of the Navy ELF Communications System Ecological Monitoring Program. Volume 2: Tabs C-F

DTIC Science & Technology

1992-08-01

I I I 4. Abstract: 3 Four of the years prior to 1991 were drought years (i.e. 1986 to 1989) while 1990 was moderately dry. The as vet 3 incomplete...in the 1986 to 1989 drought . 3 This is in contrast with the 1984 and 1985 growing seasons, in which abundant rainfall took place and the population...as was the case in previous years. Of course the fluctuations were not as dramatic for the drought seasons, as they were in 1984 and 1985. Growth

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

NASA Astrophysics Data System (ADS)

Sinha, D.; Syed, T. H.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

Herrera, D. A.; Ault, T.

2016-12-01

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

Vulnerability analysis for a drought Early Warning System

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Demarchi, Alessandro; Perez, Francesca

2014-05-01

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

Remote sensing monitoring the spatio-temporal changes of aridification in the Mongolian Plateau based on the general Ts-NDVI space, 1981-2012

NASA Astrophysics Data System (ADS)

Cao, Xiaoming; Feng, Yiming; Wang, Juanle

2017-06-01

This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981-2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981-2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.

Evaluating the Financial Vulnerability of a Major Electric Utility in the Southeastern U.S. to Drought under Climate Change and an Evolving Generation Mix.

PubMed

Kern, Jordan D; Characklis, Gregory W

2017-08-01

There is increasing recognition of the vulnerability of electric power systems to drought and the potential for both climate change and a shifting generation mix to alter this vulnerability. Nonetheless, the considerable research in this area has not been synthesized to inform electric utilities with respect to a key factor that influences their decisions about critical infrastructure: financial risk for shareholders. This study addresses this gap in knowledge by developing a systems framework for assessing the financial exposure of utilities to drought, with further consideration of the effects of climate change and a shifting generation mix. We then apply this framework to a major utility in the Southeastern U.S. Results suggest that extreme drought could cause profit shortfalls of more than $100 million if water temperature regulations are strictly enforced. However, even losses of this magnitude would not significantly impact returns for shareholders. This may inadvertently reduce pressure internally at utilities to incorporate drought vulnerability into long-term strategic planning, potentially leaving utilities and their customers at greater risk in the future.

The Challenges from Extreme Climate Events for Sustainable Development in Amazonia: the Acre State Experience

NASA Astrophysics Data System (ADS)

Araújo, M. D. N. M.

2015-12-01

In the past ten years Acre State, located in Brazil´s southwestern Amazonia, has confronted sequential and severe extreme events in the form of droughts and floods. In particular, the droughts and forest fires of 2005 and 2010, the 2012 flood within Acre, the 2014 flood of the Madeira River which isolated Acre for two months from southern Brazil, and the most severe flooding throughout the state in 2015 shook the resilience of Acrean society. The accumulated costs of these events since 2005 have exceeded 300 million dollars. For the last 17 years, successive state administrations have been implementing a socio-environmental model of development that strives to link sustainable economic production with environmental conservation, particularly for small communities. In this context, extreme climate events have interfered significantly with this model, increasing the risks of failure. The impacts caused by these events on development in the state have been exacerbated by: a) limitations in monitoring; b) extreme events outside of Acre territory (Madeira River Flood) affecting transportation systems; c) absence of reliable information for decision-making; and d) bureaucratic and judicial impediments. Our experience in these events have led to the following needs for scientific input to reduce the risk of disasters: 1) better monitoring and forecasting of deforestation, fires, and hydro-meteorological variables; 2) ways to increase risk perception in communities; 3) approaches to involve more effectively local and regional populations in the response to disasters; 4) more accurate measurements of the economic and social damages caused by these disasters. We must improve adaptation to and mitigation of current and future extreme climate events and implement a robust civil defense, adequate to these new challenges.

Use of AIRS, OMI, MLS, and TES Data in Assessing Forest Ecosystem Exposure to Ozone

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.

2007-01-01

Ground-level ozone at high levels poses health threats to exposed flora and fauna, including negative impacts to human health. While concern is common regarding depletion of ozone in the stratosphere, portions of the urban and rural United States periodically have high ambient levels of tropospheric ozone on the ground. Ozone pollution can cause a variety of impacts to susceptible vegetation (e.g., Ponderosa and Jeffrey pine species in the southwestern United States), such as stunted growth, alteration of growth form, needle or leaf chlorosis, and impaired ability to withstand drought-induced water stress. In addition, Southern Californian forests with high ozone exposures have been recently subject to multiyear droughts that have led to extensive forest overstory mortality from insect outbreaks and increased incidence of wildfires. Residual forests in these impacted areas may be more vulnerable to high ozone exposures and to other forest threats than ever before. NASA sensors collect a wealth of atmospheric data that have been used recently for mapping and monitoring regional tropospheric ozone levels. AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), MLS (Microwave Limb Sounder), and TES (Tropospheric Emission Spectrometer) data could be used to assess forest ecosystem exposure to ozone. Such NASA data hold promise for providing better or at least complementary synoptic information on ground-level ozone levels that Federal agency partners can use to assess forest health trends and to mitigate the threats as needed in compliance with Federal laws and mandates. NASA data products on ozone concentrations may be able to aid applications of DSTs (decision support tools) adopted by the USDA FS (U.S. Department of Agriculture Forest Service) and by the NPS (National Park Service), such as the Ozone Calculator, in which ground ozone estimates are employed to assess ozone impacts to forested vegetation.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Spatiotemporal analysis of hydro-meteorological drought in the Johor River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Chua, Vivien P.; Li, Cheng; Brindha, K.

2018-02-01

Assessment of historical hydro-meteorological drought is important to develop a robust drought monitoring and prediction system. This study aims to assess the historical hydro-meteorological drought of the Johor River Basin (JRB) from 1975 to 2010, an important basin for the population of southern Peninsular Malaysia and Singapore. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were selected to represent the meteorological and hydrological droughts, respectively. Four absolute homogeneity tests were used to assess the rainfall data from 20 stations, and two stations were flagged by these tests. Results indicate the SPI duration to be comparatively low (3 months), and drier conditions occur over the upper JRB. The annual SSI had a strong decreasing trend at 95% significance level, showing that human activities such as reservoir construction and agriculture (oil palm) have a major influence on streamflow in the middle and lower basin. In addition, moderate response rate of SSI to SPI was found, indicating that hydrological drought could also have occurred in normal climate condition. Generally, the El Niño-Southern Oscillation and Madden Julian Oscillation have greater impacts on drought events in the basin. Findings of this study could be beneficial for future drought projection and water resources management.

Pinus sylvestris switches respiration substrates under shading but not during drought

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

PubMed

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

2016-11-01

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

Experimental evidence for drought induced alternative stable states of soil moisture

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Experimental evidence for drought induced alternative stable states of soil moisture

PubMed Central

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

2016-01-01

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

Characterizing Agricultural Impacts of Recent Large-Scale US Droughts and Changing Technology and Management

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Glotter, Michael; Ruane, Alex C.; Boote, Kenneth J.; Hatfield, Jerry L.; Jones, James W.; Rosenzweig, Cynthia; Smith, Leonard A.; Foster, Ian

2017-01-01

Process-based agricultural models, applied in novel ways, can reproduce historical crop yield anomalies in the US, with median absolute deviation from observations of 6.7% at national-level and 11% at state-level. In seasons for which drought is the overriding factor, performance is further improved. Historical counterfactual scenarios for the 1988 and 2012 droughts show that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production by about 25% in the intervening years. Finally, we estimate the economic costs of the two droughts in terms of insured and uninsured crop losses in each US county (for a total, adjusted for inflation, of $9 billion in 1988 and $21.6 billion in 2012). We compare these with cost estimates from the counterfactual scenarios and with crop indemnity data where available. Model based measures are capable of accurately reproducing the direct agro-economic losses associated with extreme drought and can be used to characterize and compare events that occurred under very different conditions. This work suggests new approaches to modeling, monitoring, forecasting, and evaluating drought impacts on agriculture, as well as evaluating technological changes to inform adaptation strategies for future climate change and extreme events.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Drought causes reduced growth of trembling aspen in western Canada.

PubMed

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

2017-07-01

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

Tree mortality in drought-stressed mixed-conifer and ponderosa pine forests, Arizona, USA

Treesearch

Joseph L. Ganey; Scott C. Vojta

2011-01-01

We monitored tree mortality in northern Arizona (USA) mixed-conifer and ponderosa pine (Pinus ponderosa Dougl. ex Laws) forests from 1997 to 2007, a period of severe drought in this area. Mortality was pervasive, occurring on 100 and 98% of 53 mixed-conifer and 60 ponderosa pine plots (1-ha each), respectively. Most mortality was attributable to a suite of forest...

DCERP Annual Technical Report 4: March 2010 - February 2011

DTIC Science & Technology

2011-05-01

of monitoring may be necessary to fully characterize and model the impact of major climatic events (e.g., tropical cyclones, major droughts ) and...stressors (past, present, and future) at local and regional scales; take account of extreme climatic events (e.g., hurricanes, droughts ); and integrate...the longleaf pine ( Pinus palustris), savannas, and pocosins (shrub bog) that dominate MCBCL’s terrestrial environments. Variation in the biota and

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.

An overview of crop growing condition monitoring in China agriculture remote sensing monitoring system

NASA Astrophysics Data System (ADS)

Huang, Qing; Zhou, Qing-bo; Zhang, Li

2009-07-01

China is a large agricultural country. To understand the agricultural production condition timely and accurately is related to government decision-making, agricultural production management and the general public concern. China Agriculture Remote Sensing Monitoring System (CHARMS) can monitor crop acreage changes, crop growing condition, agriculture disaster (drought, floods, frost damage, pest etc.) and predict crop yield etc. quickly and timely. The basic principles, methods and regular operation of crop growing condition monitoring in CHARMS are introduced in detail in the paper. CHARMS can monitor crop growing condition of wheat, corn, cotton, soybean and paddy rice with MODIS data. An improved NDVI difference model was used in crop growing condition monitoring in CHARMS. Firstly, MODIS data of every day were received and processed, and the max NDVI values of every fifteen days of main crop were generated, then, in order to assessment a certain crop growing condition in certain period (every fifteen days, mostly), the system compare the remote sensing index data (NDVI) of a certain period with the data of the period in the history (last five year, mostly), the difference between NDVI can indicate the spatial difference of crop growing condition at a certain period. Moreover, Meteorological data of temperature, precipitation and sunshine etc. as well as the field investigation data of 200 network counties were used to modify the models parameters. Last, crop growing condition was assessment at four different scales of counties, provinces, main producing areas and nation and spatial distribution maps of crop growing condition were also created.

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.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

Hydraulic Function in Australian Tree Species during Drought-Induced Mortality

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The Effects of High Temperature on Seasonal and Diurnal Cycles of Photosynthetic Water Use Efficiency of Southern California Native Shrubs

NASA Astrophysics Data System (ADS)

Pesqueira, A.; Pivovaroff, A. L.; Sun, W.; Seibt, U.

2016-12-01

"Hot drought," or drought that occurs in conjunction with warmer temperatures due to climate change, is driving regional vegetation die-off worldwide. We examined how water use efficiency (WUE), or the ratio of carbon assimilation to transpiration, varies with changes in temperature. We use flow-through chambers at Stunt Ranch, a University of California Natural Reserve System (UCNRS) site located in the Southern California Santa Monica Mountains. We focused on four woody, native species with contrasting adaptations to seasonal drought, including Heteromeles arbutifolia, Malosma laurina, and Quercus agrifolia which are evergreen chaparral shrubs/trees, and Salvia leucophylla which is a drought-deciduous coastal sage scrub shrub. For the four species, we continuously monitored fluxes of carbon and water to calculate WUE. WUE was higher in the relatively cool, wet spring months for all species, but declined with the onset of the seasonal drought and warmer summer temperatures. We observed the highest WUE values in the temperature range from 10°C to 25°C. During the summer months, all species have the highest WUE during the morning, taking advantage of the lower evaporative demand before the temperature increases during midday and afternoon. The species with the highest WUE, M. laurina, also typically has the deepest roots at the site. Ongoing monitoring will allow us to investigate how WUE will continue to respond to water stress and high temperatures combined with intensifying water stress during the hot, dry summer months.

Socioeconomic Drought in a Changing Climate: Modeling and Management

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

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

System robustness analysis for drought risk management in South Florida

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Climate Change Impacts on Hydrology and Water Management of the San Juan Basin

NASA Astrophysics Data System (ADS)

Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.

2005-12-01

Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.

Drought Prediction for Socio-Cultural Stability Project

NASA Technical Reports Server (NTRS)

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

Season-ahead Drought Forecast Models for the Lower Colorado River Authority in Texas

NASA Astrophysics Data System (ADS)

Block, P. J.; Zimmerman, B.; Grzegorzewski, M.; Watkins, D. W., Jr.; Anderson, R.

2014-12-01

The Lower Colorado River Authority (LCRA) in Austin, Texas, manages the Highland Lakes reservoir system in Central Texas, a series of six lakes on the Lower Colorado River. This system provides water to approximately 1.1 million people in Central Texas, supplies hydropower to a 55-county area, supports rice farming along the Texas Gulf Coast, and sustains in-stream flows in the Lower Colorado River and freshwater inflows to Matagorda Bay. The current, prolonged drought conditions are severely taxing the LCRA's system, making allocation and management decisions exceptionally challenging, and affecting the ability of constituents to conduct proper planning. In this work, we further develop and evaluate season-ahead statistical streamflow and precipitation forecast models for integration into LCRA decision support models. Optimal forecast lead time, predictive skill, form, and communication are all considered.

The necessary burden of involving stakeholders in agent-based modelling for education and decision-making

NASA Astrophysics Data System (ADS)

Bommel, P.; Bautista Solís, P.; Leclerc, G.

2016-12-01

We implemented a participatory process with water stakeholders for improving resilience to drought at watershed scale, and for reducing water pollution disputes in drought prone Northwestern Costa Rica. The purpose is to facilitate co-management in a rural watershed impacted by recurrent droughts related to ENSO. The process involved designing "ContaMiCuenca", a hybrid agent-based model where users can specify the decisions of their agents. We followed a Companion Modeling approach (www.commod.org) and organized 10 workshops that included research techniques such as participatory diagnostics, actor-resources-interaction and UML diagrams, multi-agents model design, and interactive simulation sessions. We collectively assessed the main water issues in the watershed, prioritized their importance, defined the objectives of the process, and pilot-tested ContaMiCuenca for environmental education with adults and children. Simulation sessions resulted in debates about the need to improve the model accuracy, arguably more relevant for decision-making. This helped identify sensible knowledge gaps in the groundwater pollution and aquifer dynamics that need to be addressed in order to improve our collective learning. Significant mismatches among participants expectations, objectives, and agendas considerably slowed down the participatory process. The main issue may originate in participants expecting technical solutions from a positivist science, as constantly promoted in the region by dole-out initiatives, which is incompatible with the constructivist stance of participatory modellers. This requires much closer interaction of community members with modellers, which may be hard to attain in the current research practice and institutional context. Nevertheless, overcoming these constraints is necessary for a true involvement of water stakeholders to achieve community-based decisions that facilitate integrated water management. Our findings provide significant guidance for improving the trans-generational engagement of stakeholders in participatory modeling processes in a context of limited technical skills and information, research expectative mismatches, and poor multi-stakeholder interaction for decision-making.

Monitoring Agricultural Drought Using Geographic Information Systems and Remote Sensing on the Primary Corn and Soybean Belt in the United States

NASA Astrophysics Data System (ADS)

Al-Shomrany, Adel

The study aims to evaluate various remote sensing drought indices to assess those most fitting for monitoring agricultural drought. The objectives are (1) to assess and study the impact of drought effect on (corn and soybean) crop production by crop mapping information and GIS technology; (2) to use Geographical Weighted Regression (GWR) as a technical approach to evaluate the spatial relationships between precipitation vs. irrigated and non-irrigated corn and soybean yield, using a Nebraska county-level case study; (3) to assess agricultural drought indices derived from remote sensing (NDVI, NMDI, NDWI, and NDII6); (4) to develop an optimal approach for agricultural drought detection based on remote sensing measurements to determine the relationship between US county-level yields versus relatively common variables collected. Extreme drought creates low corn and soybean production where irrigation systems are not implemented. This results in a lack of moisture in soil leading to dry land and stale crop yields. When precipitation and moisture is found across all states, corn and soybean production flourishes. For Kansas, Nebraska, and South Dakota, irrigation management methods assist in strong crop yields throughout SPI monthly averages. The data gathered on irrigation consisted of using drought indices gathered by the national agricultural statistics service website. For the SPI levels ranging between one-month and nine-months, Kansas and Nebraska performed the best out of all 12-states contained in the Midwestern primary Corn and Soybean Belt. The reasoning behind Kansas and Nebraska's results was due to a more efficient and sustainable irrigation system, where upon South Dakota lacked. South Dakota was leveled by strong correlations throughout all SPI periods for corn only. Kansas showed its strongest correlations for the two-month and three-month averages, for both corn and soybean. Precipitation regression with irrigated and non-irrigated maize (corn) and soybean levels show yields as a function of precipitation. The GWR models predicted that yields were significantly better than OLS performances for maize (corn) and soybean. The OLS regression model when used showed a general trend of correlation between observed yields and long-term mean precipitation totals, with 84% and 63% of the variability in mean yield explained by the mean annual precipitation for the non-irrigated crops. The GWR technique performance in predicting yields was significantly better than OLS performances. For instance in the months of June, July, and August precipitations had greater impacts on maize (corn) yields than soybeans under non-irrigated conditions as a result of the greater sensitivity maize (corn) had to water stress. SPI is capable of offering various time-scales enabling it to show initial warning signs of drought conditions and accompanying severity levels. SPI calculation techniques used for various locations are reflected upon the precipitation records acquired during those periods. Over the 3, 6, and 9-month periods, NDII6 performed the best out of all of the MODIS indices as shown in its results in monitoring vegetation moisture and drought detection. NDII6 performed the best due to its detection abilities. The 9-month SPI provides an indication of inter-seasonal precipitation patterns over medium timescale duration. A new approach used is to average corn and soybean yields for all counties of the study area in comparison with average anomalies of the MODIS indices for the growing season between May through September from 2006-2012. There was a strong correlation between average corn yields versus MODIS NDII6 averages for these years with R2 equaling 0.62. That means NDII6 is the best indicator to show drought conditions and vegetation moisture monitoring. There was a weak correlation with R2 = 0.16 between averages of soybean yields and averages of precipitation. Irrigation and management systems, technological improvements from hybrids, producer management techniques, and other management practices have an impact on crop yield productions. (Abstract shortened by ProQuest.).

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations.

PubMed

Gerber, Brian D; Kendall, William L; Hooten, Mevin B; Dubovsky, James A; Drewien, Roderick C

2015-09-01

1. Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. 2. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. 3. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. 4. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. 5. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Monitoring Wildlife Interactions with Their Environment: An Interdisciplinary Approach

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

Charles-Smith, Lauren E.; Domnguez, Ignacio X.; Fornaro, Robert J.

In a rapidly changing world, wildlife ecologists strive to correctly model and predict complex relationships between animals and their environment, which facilitates management decisions impacting public policy to conserve and protect delicate ecosystems. Recent advances in monitoring systems span scientific domains, including animal and weather monitoring devices and landscape classification mapping techniques. The current challenge is how to combine and use detailed output from various sources to address questions spanning multiple disciplines. WolfScout wildlife and weather tracking system is a software tool capable of filling this niche. WolfScout automates integration of the latest technological advances in wildlife GPS collars, weathermore » stations, drought conditions, and severe weather reports, and animal demographic information. The WolfScout database stores a variety of classified landscape maps including natural and manmade features. Additionally, WolfScout’s spatial database management system allows users to calculate distances between animals’ location and landscape characteristics, which are linked to the best approximation of environmental conditions at the animal’s location during the interaction. Through a secure website, data are exported in formats compatible with multiple software programs including R and ArcGIS. The WolfScout design promotes interoperability in data, between researchers, and software applications while standardizing analyses of animal interactions with their environment.« less

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Early indications of drought impacts on forests in the southeastern United States

Treesearch

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

2015-01-01

In the southeastern United States, drought can pose a significant threat to forests by reducing the  amount of available water, thereby stressing trees. Destructive changes in crown conditions provide the first visible  indication of a problem in a forested area, making it a useful indicator for problems within an  ecosystem. Forest Health and Monitoring (FHM) and...

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

The implications of drought and water conservation on the reuse of municipal wastewater: Recognizing impacts and identifying mitigation possibilities.

PubMed

Tran, Quynh K; Jassby, David; Schwabe, Kurt A

2017-11-01

As water agencies continue to investigate opportunities to increase resilience and local water supply reliability in the face of drought and rising water scarcity, water conservation strategies and the reuse of treated municipal wastewater are garnering significant attention and adoption. Yet a simple water balance thought experiment illustrates that drought, and the conservation strategies that are often enacted in response to it, both likely limit the role reuse may play in improving local water supply reliability. For instance, as a particular drought progresses and agencies enact water conservation measures to cope with drought, influent flows likely decrease while influent pollution concentrations increase, particularly salinity, which adversely affects wastewater treatment plant (WWTP) costs and effluent quality and flow. Consequently, downstream uses of this effluent, whether to maintain streamflow and quality, groundwater recharge, or irrigation may be impacted. This is unfortunate since reuse is often heralded as a drought-proof mechanism to increase resilience. The objectives of this paper are two-fold. First, we illustrate-using a case study from Southern California during its most recent drought- how drought and water conservation strategies combine to reduce influent flow and quality and, subsequently, effluent flow and quality. Second, we use a recently developed regional water reuse decision support model (RWRM) to highlight cost-effective strategies that can be implemented to mitigate the impacts of drought on effluent water quality. While the solutions we identify cannot increase the flow of influent or effluent coming into or out of a treatment plant, they can improve the value of the remaining effluent in a cost-effective manner that takes into account the characteristics of its demand, whether it be for landscaping, golf courses, agricultural irrigation, or surface water augmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptation measures to drought in Mongolian rangeland: The long-distant movement of people and livestock

NASA Astrophysics Data System (ADS)

Kakinuma, K.; Kanae, S.

2015-12-01

Coping with droughts are one of the most important issues in arid and semi-arid regions. Mongolia, where are located in central Asia, are concerned the increase of droughts in the future (IPCC 2014). Mongolia has long history of livestock grazing. Herders have developed the mobile grazing systems to use spatiotemporal variable vegetation. Especially, they often take a rapid and long-distant movement to avoid drought condition ("otor" in Mongolia). The movement is a main adaptation measure to droughts for herders, and it would be applicable to other regions where will be increase the frequency of droughts in the future. However there are few knowledge about processes and actual conditions of the long-distant movement of herders and livestock across Mongolia. Therefore our objective is to discuss the long-distance movement as adaptation measures to droughts. Mongolia has a climatic gradient along the latitude; rainfall variability in southern regions are higher than that in northern regions. Previous theoretical studies predicted that rainfall variability affect the grazing strategies. Based on them, we established two hypotheses about the relationship between climatic variability and the form of long distant movement. (1) The long-distance movement likely occur in southern regions because the frequency of drought are higher in southern regions than in northern regions (2) Cooperation among herders, such as acceptance of livestock that from other prefectures, are likely occur in southern regions while exclusive management are likely occur in northern regions. We interviewed to local herders, decision makers about the long-distant movement, and investigated the number of livestock that across the border of prefectures in recent year across Mongolia. We will discuss long-distant movements as an adaptation measure to drought thorough these results.