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  • 1
    Online Resource
    Online Resource
    Acute Water-Scarcity Monitoring for Africa
    MDPI AG ; 2019
    In:  Water Vol. 11, No. 10 ( 2019-09-21), p. 1968-
    Details
    In: Water, MDPI AG, Vol. 11, No. 10 ( 2019-09-21), p. 1968-
    Abstract: Acute and chronic water scarcity impacts four billion people, a number likely to climb with population growth and increasing demand for food and energy production. Chronic water insecurity and long-term trends are well studied at the global and regional level; however, there have not been adequate systems in place for routinely monitoring acute water scarcity. To address this gap, we developed a monthly monitoring system that computes annual water availability per capita based on hydrologic data from the Famine Early Warning System Network (FEWS NET) Land Data Assimilation System (FLDAS) and gridded population data from WorldPop. The monitoring system yields maps of acute water scarcity using monthly Falkenmark classifications and departures from the long-term mean classification. These maps are designed to serve FEWS NET monitoring objectives; however, the underlying data are publicly available and can support research on the roles of population and hydrologic change on water scarcity at sub-annual and sub-national scales.
    Type of Medium: Online Resource
    ISSN: 2073-4441
    URL: Article
    DOI: 10.3390/w11101968
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2521238-2
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  • 2
    Online Resource
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    A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan
    Copernicus GmbH ; 2022
    In:  Earth System Science Data Vol. 14, No. 7 ( 2022-07-08), p. 3115-3135
    Details
    In: Earth System Science Data, Copernicus GmbH, Vol. 14, No. 7 ( 2022-07-08), p. 3115-3135
    Abstract: Abstract. From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56∘ N, 30–100∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    URL: Article
    DOI: 10.5194/essd-14-3115-2022
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2475469-9
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  • 3
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    Developing an operational rangeland water requirement satisfaction index
    Informa UK Limited ; 2011
    In:  International Journal of Remote Sensing Vol. 32, No. 21 ( 2011-11-10), p. 6047-6053
    Details
    In: International Journal of Remote Sensing, Informa UK Limited, Vol. 32, No. 21 ( 2011-11-10), p. 6047-6053
    Type of Medium: Online Resource
    ISSN: 0143-1161 , 1366-5901
    URL: Article
    DOI: 10.1080/01431161.2010.516028
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2011
    detail.hit.zdb_id: 1497529-4
    detail.hit.zdb_id: 754117-X
    SSG: 14
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  • 4
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    Case Study Comparing Multiple Irrigated Land Datasets in Arizona and Colorado, USA
    Wiley ; 2018
    In:  JAWRA Journal of the American Water Resources Association Vol. 54, No. 2 ( 2018-04), p. 505-526
    Details
    In: JAWRA Journal of the American Water Resources Association, Wiley, Vol. 54, No. 2 ( 2018-04), p. 505-526
    Abstract: While there are currently a number of irrigated land datasets available for the western United States (U.S.), there is uncertainty regarding in how they relate to each other. To help understand the characteristics of available irrigated datasets, we compared (1) the Cropland Data Layer (CDL), (2) Moderate Resolution Imaging Spectroradiometer Irrigated Agriculture Dataset (IAD), (3) Digitized Irrigated Land (DIL), and (4) Consumptive Use for Irrigation (CUI) data in Arizona and Colorado, U.S. These datasets were derived from multiple sources at various spatial resolutions and temporal scales. We found spatial and temporal trends among all of them. The datasets showed decreases in irrigated land area in Arizona during the 2000–2010 time period. The change ranges and ratios were similar in all Arizona datasets. Irrigated land in Colorado decreased in DIL and CUI but increased in IAD and CDL. The agreement within the same type of dataset during different time periods was from 60% to 80% ( R 2 from 0.35 to 0.72) in Arizona and from 50% to 80% ( R 2 from 0.23 to 0.68) in Colorado. DIL had the highest agreement (80%) in both states. The agreement among different datasets acquired at approximately the same time frame ranged from 51% to 63% ( R 2 from 0.14 to 0.31) in Arizona and from 47% to 69% ( R 2 from 0.32 to 0.40) in Colorado. The results from this study support a greater understanding of the multiresolution and multitemporal nature of these datasets for various applications.
    Type of Medium: Online Resource
    ISSN: 1093-474X , 1752-1688
    URL: Issue
    URL: Article
    DOI: 10.1111/jawr.2018.54.issue-2
    DOI: 10.1111/1752-1688.12620
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2090051-X
    SSG: 14
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  • 5
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    Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data
    American Geophysical Union (AGU) ; 2008
    In:  Geophysical Research Letters Vol. 35, No. 22 ( 2008-11-18)
    Details
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 35, No. 22 ( 2008-11-18)
    Type of Medium: Online Resource
    ISSN: 0094-8276
    URL: Article
    DOI: 10.1029/2008GL035772
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2008
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 6
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    A probabilistic approach to assess agricultural drought risk to maize in Southern Africa and millet in Western Sahel using satellite estimated rainfall
    Elsevier BV ; 2014
    In:  International Journal of Disaster Risk Reduction Vol. 10 ( 2014-12), p. 490-502
    Details
    In: International Journal of Disaster Risk Reduction, Elsevier BV, Vol. 10 ( 2014-12), p. 490-502
    Type of Medium: Online Resource
    ISSN: 2212-4209
    URL: Article
    DOI: 10.1016/j.ijdrr.2014.04.002
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
    detail.hit.zdb_id: 2695877-6
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  • 7
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    Better Advance Warnings of Drought: A New NASA Hydrological Forecast System
    American Meteorological Society ; 2020
    In:  Bulletin of the American Meteorological Society Vol. 101, No. 10 ( 2020-10), p. 899-903
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 101, No. 10 ( 2020-10), p. 899-903
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-18-0264.A
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 8
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    Warming of the Indian Ocean threatens eastern and southern African food security but could be mitigated by agricultural development
    Proceedings of the National Academy of Sciences ; 2008
    In:  Proceedings of the National Academy of Sciences Vol. 105, No. 32 ( 2008-08-12), p. 11081-11086
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 105, No. 32 ( 2008-08-12), p. 11081-11086
    Abstract: Since 1980, the number of undernourished people in eastern and southern Africa has more than doubled. Rural development stalled and rural poverty expanded during the 1990s. Population growth remains very high, and declining per-capita agricultural capacity retards progress toward Millennium Development goals. Analyses of in situ station data and satellite observations of precipitation have identified another problematic trend: main growing-season rainfall receipts have diminished by ≈15% in food-insecure countries clustered along the western rim of the Indian Ocean. Occurring during the main growing seasons in poor countries dependent on rain-fed agriculture, these declines are societally dangerous. Will they persist or intensify? Tracing moisture deficits upstream to an anthropogenically warming Indian Ocean leads us to conclude that further rainfall declines are likely. We present analyses suggesting that warming in the central Indian Ocean disrupts onshore moisture transports, reducing continental rainfall. Thus, late 20th-century anthropogenic Indian Ocean warming has probably already produced societally dangerous climate change by creating drought and social disruption in some of the world's most fragile food economies. We quantify the potential impacts of the observed precipitation and agricultural capacity trends by modeling “millions of undernourished people” as a function of rainfall, population, cultivated area, seed, and fertilizer use. Persistence of current tendencies may result in a 50% increase in undernourished people by 2030. On the other hand, modest increases in per-capita agricultural productivity could more than offset the observed precipitation declines. Investing in agricultural development can help mitigate climate change while decreasing rural poverty and vulnerability.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0708196105
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2008
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 9
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    The NASA Hydrological Forecast System for Food and Water Security Applications
    American Meteorological Society ; 2020
    In:  Bulletin of the American Meteorological Society Vol. 101, No. 7 ( 2020-07), p. E1007-E1025
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 101, No. 7 ( 2020-07), p. E1007-E1025
    Abstract: Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing–based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean–land–atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1–5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-18-0264.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 10
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    Evaluation of the Global Land Data Assimilation System (GLDAS) Air Temperature Data Products
    American Meteorological Society ; 2015
    In:  Journal of Hydrometeorology Vol. 16, No. 6 ( 2015-12-01), p. 2463-2480
    Details
    In: Journal of Hydrometeorology, American Meteorological Society, Vol. 16, No. 6 ( 2015-12-01), p. 2463-2480
    Abstract: There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.
    Type of Medium: Online Resource
    ISSN: 1525-755X , 1525-7541
    URL: Article
    DOI: 10.1175/JHM-D-14-0230.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 2042176-X
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