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Sample records for agricultural drought monitoring

  1. Agricultural Productivity Forecasts for Improved Drought Monitoring

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  2. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Suc...

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

    NASA Astrophysics Data System (ADS)

    Zhang, Jie

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

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

  9. 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

  10. [The new method monitoring agricultural drought based on SWIR-Red spectrum feature space].

    PubMed

    Feng, Hai-Xia; Qin, Qi-Ming; Li, Bin-Yong; Liu, Fang; Jiang, Hong-Bo; Dong, Heng; Wang, Jin-Liang; Liu, Ming-Chao; Zhang, Ning

    2011-11-01

    Drought was a chronic, natural disaster, and Remote sensing drought monitoring had become a potential research field. In the present, short-wave infrared and red bands which sensitive to moisture variation were selected to monitor farmland drought conditions by analyzing the spectral characteristics of vegetation and soil. The goal of this paper was to provide a new method of drought monitoring--normalized drought monitoring index (NPDI), based on new constructed spectrum feature space by the difference of SWIR and Red and the sum of SWIR and Red. Field surveyed soil moisture verified NPDI model, and the result showed that NDPI and MPDI model could effectively monitor agricultural drought, and that had high correlation with soil moisture. The R2 was 0.583 and 0.438 with soil water of 10 cm. The monitoring effect of NPDI model was better than the MPDL. This model was further improvement to PDI and MPDI, and it could monitor the drought condition of different vegetation coverage and whole growing season. It has high application potential and popularization value.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  13. Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data

    NASA Astrophysics Data System (ADS)

    Son, N. T.; Chen, C. F.; Chen, C. R.; Chang, L. Y.; Minh, V. Q.

    2012-08-01

    Drought is a complex natural phenomenon, and its impacts on agriculture are enormous. Drought has been a prevalent concern for farmers in the Lower Mekong Basin (LMB) over the last decades; thus, monitoring drought is important for water planning and management to mitigate impacts on agriculture in the region. This study explored the applicability of monthly MODIS normalized difference vegetation index (NDVI) and land surface temperature (LST) data for agricultural drought monitoring in LMB in the dry season from November 2001 to April 2010. The data were processed using the temperature vegetation dryness index (TVDI), calculated by parameterizing the relationship between the MODIS NDVI and LST data. The daily volumetric surface soil moisture from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and monthly precipitation from the Tropical Rainfall Measuring Mission (TRMM) were collected and used for verification of the results. In addition, we compared the efficiency of TVDI with a commonly used drought index, the crop water stress index (CWSI), derived from the MODIS LST alone. The results achieved from comparisons between TVDI and AMSR-E soil moisture data indicated acceptable correlations between the two datasets in most cases. There was close agreement between TVDI and TRMM precipitation data through the season, indicating that TVDI was sensitive to precipitation. The TVDI compared to CWSI also yielded close correlations between both datasets. The TVDI was, however, more sensitive to soil moisture stress than CWSI. The results archived by analysis of TVDI indicated that the moderate and severe droughts were spatially scattered over the region from November to March, but more extensive in northeast Thailand and Cambodia. The larger area of severe drought was especially observed for the 2003-2006 dry seasons compared to other years. The results achieved from this study could be important for drought warnings and irrigation scheduling.

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

    NASA Astrophysics Data System (ADS)

    Ruhoff, Anderson

    2014-05-01

    regional droughts (2005, 2010 and 2012) occurred in Southern Brazil, with similar wetting and drying patterns based on the Standardized Precipitation Index (SPI) and strong correlation with agricultural productivity. Overall, the MODIS remotely sensed drought indices reveal the efficacy and effectiveness for near-real time monitor land surface drought events. Furthermore, understanding and predicting the consequences of drought events on agricultural productivity is emerging as one of the greatest challenges currently due to the increasing global demand for food. Acknowledgements: This work was made possible through the support of the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).

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

    PubMed

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

    2013-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Ryu, J.

    2014-12-01

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

  17. Relative Skills of Soil Moisutre and Vegetation Optical Depth Retrievals for Agricultural Drought Monitoring

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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 Microwave Scanning Radiometer (AMSR-E). This study aims to investigate added skills of VOD in addition to SM for agricultural drought monitoring using monthly LPRM-SM and VOD products from 2002 to 2011. First, the lagged rank cross-correlation between Normalized Difference Vegetation Index (NDVI) and the SM/VOD retrievals is used to evaluate the skills of the SM and VOD for drought monitoring. Interestingly, the highest rank cross-correlation between NDVI and VOD is found with lag of (+1) month (temporally lagged behind ranks of NDVI by 1 month), while the highest rank cross-correlation coefficient of SM is found with lag (-1) month (temporally precedes the ranks of NDVI by 1 month). Lagged responses of plants to the available water capacity in the root zone may explain this lagged peak of correlation of VOD. In order to understand this finding more systematically, additional analysis on the microwave polarization difference index and vertical/horizontal brightness temperature are conducted. Next, different types of observations (SM, VOD and NDVI) and hydrologic model results (Palmer model) are merged to improve predictive power. We adopt two different merging approaches (simple weighting method and auto-regressive model) to quantify the added skills of those different drought-related indices. The results show that adding more information rather than using solely SM observation increases lag (-1) month cross-correlation coefficient with NDVI. This result indicates that different observations/models have independent information to some degree. Therefore further analysis on error-correlations between the observations/model results is also conducted. This study suggests

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

    NASA Astrophysics Data System (ADS)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

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

  19. Quantitative drought monitoring in a typical cold river basin over Tibetan Plateau: An integration of meteorological, agricultural and hydrological droughts

    NASA Astrophysics Data System (ADS)

    Makokha, Godfrey Ouma; Wang, Lei; Zhou, Jing; Li, Xiuping; Wang, Aihui; Wang, Guangpeng; Kuria, David

    2016-12-01

    We introduce a Rainfall, Snow and Glacier melt (RSG) standardized anomaly (SA) index to reflect water availability in cold river basins by taking into account snow and glacier melt that influence seasonal water availability. The study takes advantage of a high-resolution Water and Energy Budget-Based Hydrological Distributed Model with improved snow physics (WEB-DHM-S) at a grid size of 5 km to quantify hydrological regimes in a typical cold river basin in the Tibetan Plateau (Lhasa River basin as a demonstration site) from 1983 to 2012. Standardized anomaly index was utilized as drought Indicator whereby each meteo-hydrological parameter involved in drought quantification was fitted to a distribution pattern on a monthly basis. Akaike Information Criterion and Bayesian Information Criterion were used as selection criteria. Drought indices were computed from the model inputs and outputs, which included RSG for meteorological drought, soil moisture (surface and root-zone) for agricultural drought and discharge and groundwater level for hydrological drought. From spatial and temporal analyses, drought occurred in 1984, 1988, 1995, 1997, 2009 and 2010, with the highest severity in August, September, July, August, June and June, respectively. This study addresses the glacierized cold river basin's dryness by considering the contribution of snow and glacier in drought quantification, an integration of meteorological, agricultural and hydrological was performed to highlight drought hotspots in the Lhasa River Basin. To the best of our knowledge, this is the first drought study in Lhasa River Basin.

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

    NASA Astrophysics Data System (ADS)

    Lessel, J.; Ceccato, P.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  2. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, we evaluates a soil moisture assimilation system for agricultural drought monitoring by benchmarking each component of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputs/output) as the full component. Lagged soil moisture/NDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities and/or complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system. First, the non-linear LPRM retrieval algorithm does not appear to add much additional predictive information for future NDVI compared to the simple linear benchmark model comprised of initial AMSR-E observations (horizontally and vertically polarized brightness temperatures and surface temperature). Second, the Palmer model performed worse than the purely linear prognostic model (Antecedent Precipitation Index model) in predicting future vegetation condition. This result points out that the saturation threshold of soil layers in the modern LSMs for runoff generation hinders maximum utilization of meteorological input information for agricultural drought monitoring. As to the assimilation algorithm, better performance of the

  6. 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

  7. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. 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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  13. Monitoring groundwater drought with GRACE data assimilation

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. 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

  15. 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

  16. The German Drought Monitor

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. 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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Drought monitoring and early warning (M&EW) is an important component of agricultural and silvicultural risk management. Meteorological indicators such as the Standardized Precipitation Index (SPI) are widely used in operational M&EW systems and for drought hazard assessment. Meteorological drought yet does not necessarily equate to agricultural drought given differences in drought susceptibility, e.g. crop-specific vulnerability, soil water holding capacity, irrigation and other management practices. How useful are meteorological indicators such as SPI to assess agricultural drought? Would the inclusion of vegetation indicators into drought M&EW systems add value for the agricultural sector? To answer these questions, it is necessary to investigate the link between meteorological indicators and agricultural impacts of drought. Crop yield or loss data is one source of information for drought impacts, yet mostly available as aggregated data at the annual scale. Remotely sensed vegetation stress data offer another possibility to directly assess agricultural impacts with high spatial and temporal resolution and are already used by some M&EW systems. At the same time, reduced crop yield and satellite-based vegetation stress potentially suffer from multi-causality. The aim of this study is therefore to investigate the relation between meteorological drought indicators and agricultural drought impacts for Europe, and to intercompare different agricultural impact variables. As drought indicators we used SPI and the Standardized Precipitation Evaporation Index (SPEI) for different accumulation periods. The focus regarding drought impact variables was on remotely sensed vegetation stress derived from MODIS NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) data, but the analysis was complemented with crop yield data and text-based information from the European Drought Impact report Inventory (EDII) for selected countries. A correlation analysis

  20. 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

    , 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.

  1. 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

  2. A Landsat Agricultural Monitoring Program

    NASA Technical Reports Server (NTRS)

    Aaronson, A. C.; Buchman, P. E.; Wescott, T.; Fries, R. E.

    1977-01-01

    The paper discusses the Landsat Agricultural Monitoring Program which was developed to identify, observe, and evaluate alarm conditions influencing Iowa corn production in 1976. Used in conjunction with climatic and field reports, studies were made of crop development, crop alarms (such as heavy rainfall, hail, tornadoes, and drought) and estimated crop yield.

  3. 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

  4. Drought, Climate Change and Potential Agricultural Productivity

    NASA Astrophysics Data System (ADS)

    Sheffield, J.; Herrera-Estrada, J. E.; Caylor, K. K.; Wood, E. F.

    2011-12-01

    Drought is a major factor in agricultural productivity, especially in developing regions where the capacity for water resources management is limited and climate variability ensures that drought is recurrent and problematic. Recent events in East Africa are testament to this, where drought conditions that have slowly developed over multiple years have contributed to reduced productivity and ultimately food crises and famine. Prospects for the future are not promising given ongoing problems of dwindling water supplies from non-renewable sources and the potential for increased water scarcity and increased drought with climate change. This is set against the expected increase in population by over 2 billion people by 2050 and rise in food demand, coupled with changes in demographics that affect food choices and increases in non-food agriculture. In this talk we discuss the global variability of drought over the 20th century and recent years, and the projected changes over the 21st century, and how this translates into changes in potential agricultural productivity. Drought is quantified using land surface hydrological models driven by a hybrid reanalysis-observational meteorological forcing dataset. Drought is defined in terms of anomalies of hydroclimatic variables, in particular precipitation, evaporation and soil moisture, and we calculate changes in various drought characteristics. Potential agricultural productivity is derived from the balance of precipitation to crop water demand, where demand is based on potential evaporation and crop coefficients for a range of staple crops. Some regional examples are shown of historic variations in drought and potential productivity, and the estimated water deficit for various crops. The multitude of events over the past decade, including heat waves in Europe, fires in Russia, long-term drought in northern China, southeast Australia, the Western US and a series of droughts in the Amazon and Argentina, hint at the influence of

  5. Forecasts of Agricultural Drought in Sri Lanka

    NASA Astrophysics Data System (ADS)

    Gilligan, J. M.; Gunda, T.; Hornberger, G. M.

    2015-12-01

    As the most frequent natural disaster in Sri Lanka, drought greatly affects crop production and livelihoods. Over half of all agricultural crop damage in Sri Lanka is currently due to drought; the frequency and severity of drought in the country is only expected to increase with the changing climate. Previous work indicates that the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are capable of capturing agricultural drought patterns (between 1881-2010) in the island nation. In this work, PDSI and SPI from 13 long-term meteorological stations will be projected into the future using a combination of artificial neural network and autoregressive integrated moving average models. The impacts of large-scale atmospheric circulation patterns (such as the Niño 3.4 index, a measure of sea surface temperature) and lead times on projection accuracy will also be explored. Model projections will be compared to weather data since 2010 to determine if the 2014 drought could have been forecasted using these methods. Since agricultural systems are strongly influenced by both natural and human systems, it is important to frame these physical findings within a social context. This work is part of an interdisciplinary project that assesses the perceptions of and adaptations to drought by rice farmers in Sri Lanka; disciplines represented in the group include hydrology, social psychology, ethnography, policy, and behavioral economics. Insights from the diverse research perspectives within the group will be drawn upon to highlight the social implications of the physical results.

  6. Forages and Pastures Symposium: assessing drought vulnerability of agricultural production systems in context of the 2012 drought.

    PubMed

    Kellner, O; Niyogi, D

    2014-07-01

    Weather and climate events and agronomic enterprise are coupled via crop phenology and yield, which is temperature and precipitation dependent. Additional coupling between weather and climate and agronomic enterprise occurs through agricultural practices such as tillage, irrigation, erosion, livestock management, and forage. Thus, the relationship between precipitation, temperature, and yield is coupled to the relationship between temperature, precipitation, and drought. Unraveling the different meteorological and climatological patterns by comparing different growing seasons provides insight into how drought conditions develop and what agricultural producers can do to mitigate and adapt to drought conditions. The 2012 drought in the United States greatly impacted the agricultural sector of the economy. With comparable severity and spatial extent of the droughts of the 1930s, 1950s, and 1980s, the 2012 drought impacted much of the U.S. crop and livestock producers via decreased forage and feed. This brief summary of drought impacts to agricultural production systems includes 1) the basics of drought; 2) the meteorology and climatology involved in forecasting, predicting, and monitoring drought with attribution of the 2012 drought explored in detail; and 3) comparative analysis completed between the 2011 and 2012 growing season. This synthesis highlights the complex nature of drought in agriculture production systems as producers prepare for future climate variability.

  7. Probabilistic assessment of agricultural droughts using graphical models

    NASA Astrophysics Data System (ADS)

    Ramadas, Meenu; Govindaraju, Rao S.

    2015-07-01

    Agricultural droughts are often characterized by soil moisture in the root zone of the soil, but crop needs are rarely factored into the analysis. Since water needs vary with crops, agricultural drought incidences in a region can be characterized better if crop responses to soil water deficits are also accounted for in the drought index. This study investigates agricultural droughts driven by plant stress due to soil moisture deficits using crop stress functions available in the literature. Crop water stress is assumed to begin at the soil moisture level corresponding to incipient stomatal closure, and reaches its maximum at the crop's wilting point. Using available location-specific crop acreage data, a weighted crop water stress function is computed. A new probabilistic agricultural drought index is then developed within a hidden Markov model (HMM) framework that provides model uncertainty in drought classification and accounts for time dependence between drought states. The proposed index allows probabilistic classification of the drought states and takes due cognizance of the stress experienced by the crop due to soil moisture deficit. The capabilities of HMM model formulations for assessing agricultural droughts are compared to those of current drought indices such as standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (SC-PDSI). The HMM model identified critical drought events and several drought occurrences that are not detected by either SPEI or SC-PDSI, and shows promise as a tool for agricultural drought studies.

  8. 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

  9. Enhanced Drought Monitoring in the Upper Colorado River Basin

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  10. Drought monitoring: Historical and current perspectives

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Managing the risk of agricultural drought in Africa

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. Drought Monitoring with VegDRI

    USGS Publications Warehouse

    Brown, Jesslyn F.

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2007-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2006-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Greene, C.

    2015-12-01

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

  20. Adapting agriculture to drought and extreme events

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The 2012 drought, the worst during the last 80 years or more, remind us of the dust bowl of the 1930s (Figure 1),and indicates that climate change is a reality rather than a distant threat. The last drought of this magnitude may have occurred more than 800 years ago, and the 2012 drought has been du...

  1. Projections of agricultural droughts in the Southeast Asia

    NASA Astrophysics Data System (ADS)

    Mishra, V.

    2014-12-01

    Southeast Asia is one of the most populated regions in the world, which falls among the food insecure regions. Droughts during the monsoon season hamper crop growth and food production. During the last few decades, rainfall in the monsoon season has been erratic leading to some of the most wide spread droughts in the region. Severity, areal extents, and frequency of droughts are analyzed using the observed data for the period of 1951-2007. Results indicate that frequency of severe drought increased in the Southeast Asia during the recent decades (1980-2007). To assess the variability of hydrologic and agricultural drought in the region, runoff and soil moisture were simulated using the Variable Infiltration Capacity (VIC) model. The model simulated drought variability was compared with drought simulated by the CMIP5 models during the historic period (1951-2005). Most of the CMIP5 models show increased frequency of severe agricultural droughts in the region under the projected future climate. Increased agricultural droughts in the Southeast Asia may put enormous pressure on the efforts towards achieving food security in the region.

  2. Simulating US agriculture in a modern Dust Bowl drought.

    PubMed

    Glotter, Michael; Elliott, Joshua

    2016-12-12

    Drought-induced agricultural loss is one of the most costly impacts of extreme weather(1-3), and without mitigation, climate change is likely to increase the severity and frequency of future droughts(4,5). The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation(6) and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses ∼50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by ∼25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

  3. Simulating US Agriculture in a Modern Dust Bowl Drought

    NASA Technical Reports Server (NTRS)

    Glotter, Michael; Elliott, Joshua

    2016-01-01

    Drought-induced agricultural loss is one of the most costly impacts of extreme weather, and without mitigation, climate change is likely to increase the severity and frequency of future droughts. The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses approx.50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by approx.25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  5. 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

  6. 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

  7. U.S. agriculture in a modern Dust Bowl drought

    NASA Astrophysics Data System (ADS)

    Glotter, M.; Chryssanthacopoulos, J.; Moyer, E. J.; Elliott, J. W.

    2015-12-01

    Drought-induced agricultural loss is one of the leading weather-related harms to the U.S. economy, but little is known about the effects of extreme droughts or of consecutive multi-year drought events on agriculture. Three droughts in the early 1930s make the Dust Bowl era the driest and hottest for agriculture in modern U.S. history and a useful analog to study extreme weather and its impact on human society. Improvements in technology and farm management over the last eight decades have dramatically increased average crop yields in the U.S., but the elimination of most non-climatic crop stresses means rainfed yields are now more tightly linked to climate. To understand how a 1930s-type drought would affect agriculture in the modern U.S., we drive empirical and biophysical process-based crop models with 1930s weather -- with and without increases in mean temperature -- to estimate effects of successive droughts on current and near-future U.S. maize, soy and wheat production. Our results suggest that Dust-Bowl-type droughts today would have unprecedented consequences for agricultural productivity, with single-year losses up to ~50% larger than the central U.S. drought of 2012, one of the most severe for modern agriculture. Sensitivity tests imply that damages at these extremes are highly sensitive to temperature. If extreme drought conditions are even modestly warmer (1-4 oC), single-year losses jump to more than twice the 2012 drought. Assuming that repeated crop failure over a relatively short period is likely to induce changes to land-use and management, we find that a future Dust-Bowl-like drought, especially under higher temperature scenarios, could lead to significant long-term consequences for U.S. agriculture. Changes in climate may increase the severity and frequency of future droughts, so understanding the complex interactions of weather extremes and a changing agricultural system is critical to effective preparation and response if and when the next Dust

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

    NASA Astrophysics Data System (ADS)

    Anderson, W. B.; Zaitchik, B. F.; Hain, C. R.; Anderson, M. C.; Yilmaz, M. T.; Mecikalski, J.; Schultz, L.

    2012-08-01

    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 monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010-2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of

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

    NASA Astrophysics Data System (ADS)

    Anderson, W. B.; Zaitchik, B. F.; Hain, C. R.; Anderson, M. C.; Yilmaz, M. T.; Mecikalski, J.; Schultz, L.

    2012-04-01

    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 monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010-2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of

  10. 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.

  11. Drought monitoring using remote sensing of evapotranspiration

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. 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

  13. Predicting and adapting to the agricultural impacts of large-scale drought (Invited)

    NASA Astrophysics Data System (ADS)

    Elliott, J. W.; Glotter, M.; Best, N.; Ruane, A. C.; Boote, K.; Hatfield, J.; Jones, J.; Rosenzweig, C.; Smith, L. A.; Foster, I.

    2013-12-01

    The impact of drought on agriculture is an important socioeconomic consequence of climate extremes. Drought affects millions of people globally each year, causing an average of 6-8 billion of damage annually in the U.S. alone. The 1988 U.S. drought is estimated to have cost 79 billion in 2013 dollars, behind only Hurricane Katrina as the most costly U.S. climate-related disaster in recent decades. The 2012 U.S. drought is expected to cost about 30 billion. Droughts and heat waves accounted for 12% of all billion-dollar disaster events in the U.S. from 1980-2011 but almost one quarter of total monetary damages. To make matters worse, the frequency and severity of large-scale droughts in important agricultural regions is expected to increase as temperatures rise and precipitation patterns shift, leading some researchers to suggest that extended drought will harm more people than any other climate-related impact, specifically in the area of food security. Improved understanding and forecasts of drought would have both immediate and long-term implications for the global economy and food security. We show that mechanistic agricultural models, applied in novel ways, can reproduce historical crop yield anomalies, especially in seasons for which drought is the overriding factor. With more accurate observations and forecasts for temperature and precipitation, the accuracy and lead times of drought impact predictions could be improved further. We provide evidence that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production in recent decades, adaptations that could be applied elsewhere. This work suggests a new approach to modeling, monitoring, and forecasting drought impacts on agriculture. Simulated (dashed line), observed (solid line), and observed linear trend (dashed straight green line) of national average maize yield in tonnes per hectare from 1979-2012. The red dot indicates the USDA estimate for 2012

  14. Monitoring and seasonal forecasting of meteorological droughts

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  15. Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data.

    PubMed

    Patel, N R; Parida, B R; Venus, V; Saha, S K; Dadhwal, V K

    2012-12-01

    The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from MODIS 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. Economic Drought Impact on Agriculture: analysis of all agricultural sectors affected

    NASA Astrophysics Data System (ADS)

    Gil, M.; Garrido, A.; Hernández-Mora, N.

    2012-04-01

    The analysis of drought impacts is essential to define efficient and sustainable management and mitigation. In this paper we present a detailed analysis of the impacts of the 2004-2008 drought in the agricultural sector in the Ebro river basin (Spain). An econometric model is applied in order to determine the magnitude of the economic loss attributable to water scarcity. Both the direct impacts of drought on agricultural productivity and the indirect impacts of drought on agricultural employment and agroindustry in the Ebro basin are evaluated. The econometric model measures losses in the economic value of irrigated and rainfed agricultural production, of agricultural employment and of Gross Value Added both from the agricultural sector and the agro-industrial sector. The explanatory variables include an index of water availability (reservoir storage levels for irrigated agriculture and accumulated rainfall for rainfed agriculture), a price index representative of the mix of crops grown in each region, and a time variable. The model allows for differentiating the impacts due to water scarcity from other sources of economic losses. Results show how the impacts diminish as we approach the macro-economic indicators from those directly dependent on water abstractions and precipitation. Sectors directly dependent on water are the most affected with identifiable economic losses resulting from the lack of water. From the management perspective implications of these findings are key to develop mitigation measures to reduce drought risk exposure. These results suggest that more open agricultural markets, and wider and more flexible procurement strategies of the agro-industry reduces the socio-economic exposure to drought cycles. This paper presents the results of research conducted under PREEMPT project (Policy relevant assessment of the socioeconomic effects of droughts and floods, ECHO - grant agreement # 070401/2010/579119/SUB/C4), which constitutes an effort to provide

  19. 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.

  20. Analysis of relationship between meteorological and agricultural drought using standardized precipitation index and vegetation health index

    NASA Astrophysics Data System (ADS)

    Ma’rufah, U.; Hidayat, R.; Prasasti, I.

    2017-01-01

    Agricultural drought is closely related to meteorological drought in which the agricultural drought is an impact of meteorological drought. This study aim to understand the duration, spatial extent, severity and lag time of meteorological and agricultural drought during El Niño years. The data used in this study are monthly data of CHIPRS and MODIS. Meteorological drought and agricultural drought are intensified in the El Niño years. The duration of meteorological drought is different in each region but generally occurs during June to November. Agricultural drought mostly occurs from August to November. Spatially, meteorological drought and agricultural drought in 2015 has wider extent and higher severity (SPI <-2 and VHI <10) than in 2002. Agricultural drought generally intensified in areas that have monsoonal rainfall type such as Java, Bali, Nusa Tenggara, Lampung, southern part of Kalimantan, and southern part of Sulawesi. We found that VHI is significantly correlated with SPI-3 reach 58% of the total area of Indonesia. It means rainfall deficit during three months has a significant impact on agricultural drought in Indonesia. In general, SPI-3 and VHI clearly explain the relationship between meteorological drought and agricultural drought in Indonesia.

  1. Monitoring and predicting the 2007 U.S. drought

    NASA Astrophysics Data System (ADS)

    Luo, Lifeng; Wood, Eric F.

    2007-11-01

    Severe droughts developed in the West and Southeast of the U.S. starting early in 2007. The development of the droughts is well monitored and predicted by our model-based Drought Monitoring and Prediction System (DMAPS). Using the North America Land Data Assimilation System (NLDAS) realtime meteorological forcing and the Variable Infiltration Capacity (VIC) land surface model, DMAPS is capable of providing a quantitative assessment of the drought in near realtime. Using seasonal climate forecasts from NCEP's Climate Forecast System (CFS) as one input, DMAPS successfully predicted the evolution of the droughts several months in advance. The realtime monitoring and prediction of drought with the system will provide invaluable information for drought preparation and drought impact assessment at national and local scales.

  2. 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

  3. 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

  4. Global Drought Information System: Influence of Differences in Land Surface Model Dynamics on Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Nijssen, B.; Shukla, S.; Mo, K. C.; Lettenmaier, D. P.

    2014-12-01

    Real-time drought monitoring enables a proactive drought management approach that can lead to timely actions to mitigate the losses due to a drought event. In recent years, the availability of long-term, high quality, satellite and reanalysis based datasets of atmospheric forcings, combined with the development of state-of-the-art hydrologic models have made real-time global drought monitoring feasible. Hydrologic models are invaluable tools for global drought monitoring given the scarcity of long-term moisture observations (e.g. soil moisture, streamflow). However, as valuable as they are for drought monitoring, characteristics of a drought event (i.e. onset, severity and persistence) as estimated by a hydrologic model depend on the model's parameters (e.g. soil and vegetation parameters) and its inherent dynamics that guide the partition of precipitation into evapotranspiration and runoff. One approach to account for the differences in drought estimates due to differences in model dynamics is to use multiple hydrologic models. Each hydrologic model is forced with the same atmospheric forcings to simulate moisture conditions which are converted into objective drought indicators (e.g. soil moisture percentile) with respect to the model's own climatology and then those estimates are combined to provide a multimodel based drought estimates. The University of Washington's Global Drought Information System (GDIS) developed in 2013, is one such prototype drought monitoring system. This system uses the VIC, NOAH and Catchment models. In this presentation we investigate how the differences in the dynamics of the models used in UW's GDIS, influence the drought monitoring estimates. Specifically we answer following questions: 1.What is the level of uncertainties in drought onset, severity and persistence as estimated by different hydrologic models? 2. How do the uncertainties vary spatially and seasonally? 3. What are the sources of the uncertainties?

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Drought, agricultural adaptation, and sociopolitical collapse in the Maya Lowlands

    NASA Astrophysics Data System (ADS)

    Douglas, Peter M. J.; Pagani, Mark; Canuto, Marcello A.; Brenner, Mark; Hodell, David A.; Eglinton, Timothy I.; Curtis, Jason H.

    2015-05-01

    Paleoclimate records indicate a series of severe droughts was associated with societal collapse of the Classic Maya during the Terminal Classic period (∼800-950 C.E.). Evidence for drought largely derives from the drier, less populated northern Maya Lowlands but does not explain more pronounced and earlier societal disruption in the relatively humid southern Maya Lowlands. Here we apply hydrogen and carbon isotope compositions of plant wax lipids in two lake sediment cores to assess changes in water availability and land use in both the northern and southern Maya lowlands. We show that relatively more intense drying occurred in the southern lowlands than in the northern lowlands during the Terminal Classic period, consistent with earlier and more persistent societal decline in the south. Our results also indicate a period of substantial drying in the southern Maya Lowlands from ∼200 C.E. to 500 C.E., during the Terminal Preclassic and Early Classic periods. Plant wax carbon isotope records indicate a decline in C4 plants in both lake catchments during the Early Classic period, interpreted to reflect a shift from extensive agriculture to intensive, water-conservative maize cultivation that was motivated by a drying climate. Our results imply that agricultural adaptations developed in response to earlier droughts were initially successful, but failed under the more severe droughts of the Terminal Classic period.

  8. Drought, agricultural adaptation, and sociopolitical collapse in the Maya Lowlands

    PubMed Central

    Douglas, Peter M. J.; Pagani, Mark; Canuto, Marcello A.; Brenner, Mark; Hodell, David A.; Eglinton, Timothy I.; Curtis, Jason H.

    2015-01-01

    Paleoclimate records indicate a series of severe droughts was associated with societal collapse of the Classic Maya during the Terminal Classic period (∼800–950 C.E.). Evidence for drought largely derives from the drier, less populated northern Maya Lowlands but does not explain more pronounced and earlier societal disruption in the relatively humid southern Maya Lowlands. Here we apply hydrogen and carbon isotope compositions of plant wax lipids in two lake sediment cores to assess changes in water availability and land use in both the northern and southern Maya lowlands. We show that relatively more intense drying occurred in the southern lowlands than in the northern lowlands during the Terminal Classic period, consistent with earlier and more persistent societal decline in the south. Our results also indicate a period of substantial drying in the southern Maya Lowlands from ∼200 C.E. to 500 C.E., during the Terminal Preclassic and Early Classic periods. Plant wax carbon isotope records indicate a decline in C4 plants in both lake catchments during the Early Classic period, interpreted to reflect a shift from extensive agriculture to intensive, water-conservative maize cultivation that was motivated by a drying climate. Our results imply that agricultural adaptations developed in response to earlier droughts were initially successful, but failed under the more severe droughts of the Terminal Classic period. PMID:25902508

  9. Drought, agricultural adaptation, and sociopolitical collapse in the Maya Lowlands.

    PubMed

    Douglas, Peter M J; Pagani, Mark; Canuto, Marcello A; Brenner, Mark; Hodell, David A; Eglinton, Timothy I; Curtis, Jason H

    2015-05-05

    Paleoclimate records indicate a series of severe droughts was associated with societal collapse of the Classic Maya during the Terminal Classic period (∼800-950 C.E.). Evidence for drought largely derives from the drier, less populated northern Maya Lowlands but does not explain more pronounced and earlier societal disruption in the relatively humid southern Maya Lowlands. Here we apply hydrogen and carbon isotope compositions of plant wax lipids in two lake sediment cores to assess changes in water availability and land use in both the northern and southern Maya lowlands. We show that relatively more intense drying occurred in the southern lowlands than in the northern lowlands during the Terminal Classic period, consistent with earlier and more persistent societal decline in the south. Our results also indicate a period of substantial drying in the southern Maya Lowlands from ∼200 C.E. to 500 C.E., during the Terminal Preclassic and Early Classic periods. Plant wax carbon isotope records indicate a decline in C4 plants in both lake catchments during the Early Classic period, interpreted to reflect a shift from extensive agriculture to intensive, water-conservative maize cultivation that was motivated by a drying climate. Our results imply that agricultural adaptations developed in response to earlier droughts were initially successful, but failed under the more severe droughts of the Terminal Classic period.

  10. 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.

  11. 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.

  12. 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

    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.

  13. A Vision of International Drought Monitoring Among Pacific Rim Nations

    NASA Astrophysics Data System (ADS)

    Lawrimore, J. H.; Heim, R. R.

    2008-05-01

    Drought is an environmental hazard which results in billions of dollars in economic losses as well as societal suffering and increased mortality in many parts of the world each year. No country is immune from its effects and there is documented evidence of an increasing trend in droughts in many regions since the 1970s. There is also a high likelihood of droughts affecting an ever larger proportion of the world as global temperatures continue to rise. This reality along with the wide-ranging societal and economic impacts of drought upon the world's countries calls out for coordinated international drought monitoring and response. A demonstration of the potential for contributions through international collaboration was made through the establishment of a North American Drought Monitor (NADM) partnership between the United States, Mexico, and Canada in 2002. The United States has also recently initiated development of a National Integrated Drought Information System (NIDIS) to coordinate drought monitoring, mitigation, and research activities at federal, state, and local levels within the United States. Building on the successes and lessons learned from these ongoing activities, efforts are now underway to foster linkages with other countries throughout both North and South America and the Pacific region as an early step toward establishment of a global drought early warnings system. Through the Group on Earth Observations (GEO) new partnerships are supporting the development of a drought monitoring system in the Pacific Rim. Countries in this region are linked by the strong influence of El Niño and La Niña, leading to periods of severe, persistent, and widespread drought, alternating with periods of heavy rain and flooding. As such, the Pacific Rim makes an ideal laboratory for addressing the challenge of drought early warning through capacity building supported by improved drought monitoring tools and data sharing principles.

  14. Seasonal comparisons of meteorological and agricultural drought indices in Morocco using open short time-series data

    NASA Astrophysics Data System (ADS)

    Ezzine, Hicham; Bouziane, Ahmed; Ouazar, Driss

    2014-02-01

    Although the preliminary investigations of NDWI demonstrated its sensitivity to vegetation water content, drought indices based on NDWI short time-series are still understudied compared to those derived from NDVI and LST, such as VCI, SVI and TCI. On the basis of the open data, this paper introduces a new index derived from NDWI short time-series, and explores its performance for drought monitoring in Mediterranean semi-arid area. The new index, Standardized Water Index (SWI), was calculated and spatiotemporally compared to both meteorological drought index (TRMM-based SPI) and to agricultural drought index (NDVI-based SVI) for the hydrological years and autumn, winter and spring seasons during a period of 15 years (1998-2012). Furthermore, the response and spatial agreement of the meteorological and agricultural drought indices (SWI, SVI and SPI) were compared over two land use classes, rainfed agriculture and vegetation cover, for the studied years and seasons. The validation of SWI was based on in situ SPI and cereal productions. The analysis of the 336 cross-tables, proportions of concordance and Cohen's kappa coefficients indicate that SWI and SVI are concordant comparing to other combinations for hydrological years and for the three seasons. The study points that the spatial agreements of drought indices over rainfed agriculture and over vegetation cover are different. It is relatively more important in the rainfed agriculture than in the vegetation cover areas. Our results show that the agreement between vegetation drought indices and meteorological drought indices is moderated to low and the SPI is slightly more concordant with SWI when it is compared to SVI in autumn and winter seasons. The validation approach indicates that drought affected area, according to SWI, is highly correlated with cereal production. Likewise, a satisfactory correlation was revealed between SWI and in situ SPI.

  15. Spatial-temporal dynamics of agricultural drought in the tallgrass prairie region of the Southern Great Plains during 2000-2013

    NASA Astrophysics Data System (ADS)

    Zhou, Y.; Xiao, X.; Zhang, G.; Bajgain, R.; Dong, J.; Qin, Y.; Jin, C.; Wagle, P.; Basara, J. B.; McCarthy, H. R.; Anderson, M. C.; Hain, C.; Otkin, J.

    2015-12-01

    Tallgrass prairie is an important ecosystem type and a major feed for beef cattle in the Southern Great Plains (SGP: Kansas, Oklahoma, and Texas). Frequent drought in the SGP affects the production of tallgrass prairie and ultimately the beef cattle production. It is, therefore, necessary to map drought vulnerable areas to help ranchers adapt cattle industry to drought conditions. In this study, we analyzed Land Surface Water Index (LSWI) calculated from near infrared and shortwave infrared bands of Moderate Resolution Imaging Spectroradiometer (MODIS) and quantified the spatial-temporal dynamics of agricultural drought in the tallgrass prairie region of the SGP during 2000-2013. The number of days with LSWI < 0 during the thermal growing season (start and end dates as well as duration of land surface temperature > 5 °C) was defined as the duration of drought to generate drought duration maps for each year. Following the decreasing rainfall gradient from east to west in the SGP, counties in the west experienced whole growing season drought (WGSZ) more (three or more out of 14 years with WGSD), middle counties had one to two months summer drought, and eastern counties experienced less drought (mainly one year with WGSD and less than one month of summer drought). The LSWI-based drought duration map showed similar patterns with Evaporative Stress Index (ESI) and U.S. Drought Monitor (USDM) in wet, summer drought, and whole growing season drought years. Our drought map has identified the vulnerability of counties to different droughts (summer drought and whole growing season drought) in the SGP. This finer resolution (500 m) drought map has the potential to show the drought condition for individual ranch, which can be used to guide drought mitigation activities and livestock production.

  16. Early drought detection, monitoring, and assessment of crop losses from space: global approach

    NASA Astrophysics Data System (ADS)

    Kogan, Felix

    2006-12-01

    With nearly 30 years of the accumulated AVHRR data which were collected from NOAA operational polar-orbiting environmental satellites, the area of their applications expanded in the direction of agricultural production modeling, understanding of climate and global change, resource management, and early and more efficient monitoring of the environmental impacts (especially droughts) on economy and society. This becomes possible due to development of Vegetation Health indices (VHI). This paper discusses utility of AVHRR-based VHI for modeling crop and pasture yield with specific emphasis on early drought warning and estimation of losses in agricultural production.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  18. Climate change impacts on meteorological, agricultural and hydrological droughts in China

    NASA Astrophysics Data System (ADS)

    Leng, Guoyong; Tang, Qiuhong; Rayburg, Scott

    2015-03-01

    Bias corrected daily climate projections from five global circulation models (GCMs) under the RCP8.5 emission scenarios were fed into a calibrated Variable Infiltration Capacity (VIC) hydrologic model to project future hydrological changes in China. The standardized precipitation index (SPI), standardized runoff index (SRI) and standardized soil moisture index (SSWI) were used to assess the climate change impact on droughts from meteorological, agricultural, and hydrologic perspectives. Changes in drought severity, duration, and frequency suggest that meteorological, hydrological and agricultural droughts will become more severe, prolonged, and frequent for 2020-2049 relative to 1971-2000, except for parts of northern and northeastern China. The frequency of long-term agricultural droughts (with duration larger than 4 months) will increase more than that of short-term droughts (with duration less than 4 months), while the opposite is projected for meteorological and hydrological droughts. In extreme cases, the most prolonged agricultural droughts increased from 6 to 26 months whereas the most prolonged meteorological and hydrological droughts changed little. The most severe hydrological drought intensity was about 3 times the baseline in general whereas the most severe meteorological and agricultural drought intensities were about 2 times and 1.5 times the baseline respectively. For the prescribed local temperature increments up to 3 °C, increase of agricultural drought occurrence is predicted whereas decreases or little changes of meteorological and hydrological drought occurrences are projected for most temperature increments. The largest increase of meteorological and hydrological drought durations and intensities occurred when temperature increased by 1 °C whereas agricultural drought duration and intensity tend to increase consistently with temperature increments. Our results emphasize that specific measures should be taken by specific sectors in order to

  19. Beyond the desertification narrative: a framework for agricultural drought in semi-arid East Africa.

    PubMed

    Slegers, Monique F W; Stroosnijder, Leo

    2008-07-01

    In the 20th century, much research was done on desertification. Desertification developed into a complex and vague construct that means land degradation under specific conditions. Projects focusing on land degradation in semiarid East Africa have met with limited success because farmers prioritize drought as the major productivity-reducing problem. Yet studies on long-term rainfall trends have not confirmed that droughts are more frequent. In this article, we combine drought and land degradation effects into an Agricultural Drought Framework, which departs from the farmers' prioritization of drought and accommodates scientists' concern for land degradation. It includes meteorological drought, soil water drought, and soil nutrient drought. The framework increases insight into how different land degradation processes influence the vulnerability of land and farmers to drought. A focus on increased rainwater use efficiency will address both problems of land degradation and drought, thereby improving productivity and food security in semiarid East Africa.

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

    NASA Astrophysics Data System (ADS)

    Kogan, F.

    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.

  1. Drought monitoring in the Northwestern United States

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  2. 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.

  3. Developing New Rainfall Estimates to Identify the Likelihood of Agricultural Drought in Mesoamerica

    NASA Astrophysics Data System (ADS)

    Pedreros, D. H.; Funk, C. C.; Husak, G. J.; Michaelsen, J.; Peterson, P.; Lasndsfeld, M.; Rowland, J.; Aguilar, L.; Rodriguez, M.

    2012-12-01

    The population in Central America was estimated at ~40 million people in 2009, with 65% in rural areas directly relying on local agricultural production for subsistence, and additional urban populations relying on regional production. Mapping rainfall patterns and values in Central America is a complex task due to the rough topography and the influence of two oceans on either side of this narrow land mass. Characterization of precipitation amounts both in time and space is of great importance for monitoring agricultural food production for food security analysis. With the goal of developing reliable rainfall fields, the Famine Early warning Systems Network (FEWS NET) has compiled a dense set of historical rainfall stations for Central America through cooperation with meteorological services and global databases. The station database covers the years 1900-present with the highest density between 1970-2011. Interpolating station data by themselves does not provide a reliable result because it ignores topographical influences which dominate the region. To account for this, climatological rainfall fields were used to support the interpolation of the station data using a modified Inverse Distance Weighting process. By blending the station data with the climatological fields, a historical rainfall database was compiled for 1970-2011 at a 5km resolution for every five day interval. This new database opens the door to analysis such as the impact of sea surface temperature on rainfall patterns, changes to the typical dry spell during the rainy season, characterization of drought frequency and rainfall trends, among others. This study uses the historical database to identify the frequency of agricultural drought in the region and explores possible changes in precipitation patterns during the past 40 years. A threshold of 500mm of rainfall during the growing season was used to define agricultural drought for maize. This threshold was selected based on assessments of crop

  4. [Monitoring of farmland drought based on LST-LAI spectral feature space].

    PubMed

    Sui, Xin-Xin; Qin, Qi-Ming; Dong, Heng; Wang, Jin-Liang; Meng, Qing-Ye; Liu, Ming-Chao

    2013-01-01

    Farmland drought has the characteristics of wide range and seriously affecting on agricultural production, so real-time dynamic monitored has been a challenging problem. By using MODIS land products, and constructing the spectral space of LST and LAI, the temperature LAI drought index (TLDI) was put forward and validated using ground-measured 0-10 cm averaged soil moisture of Ningxia farmland. The results show that the coefficient of determination (R2) of both them varies from 0.43 to 0.86. Compared to TVDI, the TLDI has higher accuracy for farmland moisture monitoring, and solves the saturation of NDVI during the late development phases of the crop. Furthermore, directly using MODIS land products LST and LAI and avoiding the complicated process of using the original MODIS data provide a new technical process to the regular operation of farmland drought monitoring.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. Towards ecohydrological drought monitoring and prediction using a land data assimilation system: A case study on the Horn of Africa drought (2010-2011)

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio

    2016-07-01

    Despite the importance of the ecological and agricultural aspects of severe droughts, no drought monitoring and prediction framework based on a land data assimilation system (LDAS) has been developed to monitor and predict vegetation dynamics in the middle of droughts. In this study, we applied a LDAS that can simulate surface soil moisture, root-zone soil moisture, and vegetation dynamics to the Horn of Africa drought in 2010-2011 caused by the precipitation deficit in two consecutive rainy seasons. We successfully simulated the ecohydrological drought quantified by the model-estimated soil moistures and leaf area index (LAI). The root-zone soil moisture and LAI are good indicators of prolonged droughts because they reflect the long-term effects of past precipitation deficit. The precipitation deficit in 2010 significantly affected the land surface condition of the next rainy season in 2011, which indicated the importance of obtaining accurate initial soil moisture and LAI values for prediction of multiseasonal droughts. In addition, the general circulation model-based seasonal meteorological prediction showed good performance in predicting land surface conditions of the Horn of Africa drought.

  7. Monitoring drought intensity in Illinois with a combined index

    NASA Astrophysics Data System (ADS)

    Feng, Guanling

    Many traditional drought assessments are conducted based on climate and hydrologic data. The availability and precision of data limit the spatial and temporal resolution and accuracy of derived drought indices. In this study, Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) were generated from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The VCI was derived from Normalized Difference Vegetation Index (NDVI) that was calculated with near infrared and visible red band reflectance from MOD09Q1. The TCI was derived from land surface temperature (LST) product MOD11A2. The VCI and TCI were then combined with reference to the vegetation coverage information from MOD44B to generate the modified Vegetation Health Index (VHI). The modified VHI was applied to quantify the intensity of drought that took place in Illinois from 2000 to 2012. The results showed that the modified VHI identified the major droughts that occurred in Illinois from 2000 to 2012, especially the extreme one taking place in 2012. Moreover, the modified VHI led to the spatial distributions and temporal trends of drought severity, which were overall similar to those from the U.S. Drought Monitor (USDM) maps, but had more detailed spatial variability and much higher spatial resolution. The modified VHI also differentiated the drought impacts between the vegetated and non-vegetated areas, being a lack of the original VHI. Thus, the modified VHI takes advantage of spatially continuous and timely data from satellites and can be applied to conduct the monitoring and detection of drought intensity at local, regional, and national scales. The modified VHI can effectively synthesize the drought information of LST and NDVI to differentiate the effects of land use and land cover (LULC) types and provide the detailed spatial variability of drought intensity and thus enhance the understanding of relationship between drought condition and LULC types.

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

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Hao, Cui; Zhang, Jiahua; Yao, Fengmei

    2015-03-01

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

  10. Comparison between Two Methods for agricultural drought disaster risk in southwestern China

    NASA Astrophysics Data System (ADS)

    han, lanying; zhang, qiang

    2016-04-01

    The drought is a natural disaster, which lead huge loss to agricultural yield in the world. The drought risk has become increasingly prominent because of the climatic warming during the past century, and which is also one of the main meteorological disasters and serious problem in southwestern China, where drought risk exceeds the national average. Climate change is likely to exacerbate the problem, thereby endangering Chinaʹs food security. In this paper, drought disaster in the southwestern China (where there are serious drought risk and the comprehensive loss accounted for 3.9% of national drought area) were selected to show the drought change under climate change, and two methods were used to assess the drought disaster risk, drought risk assessment model and comprehensive drought risk index. Firstly, we used the analytic hierarchy process and meteorological, geographic, soil, and remote-sensing data to develop a drought risk assessment model (defined using a comprehensive drought disaster risk index, R) based on the drought hazard, environmental vulnerability, sensitivity and exposure of the values at risk, and capacity to prevent or mitigate the problem. Second, we built the comprehensive drought risk index (defined using a comprehensive drought disaster loss, L) based on statistical drought disaster data, including crop yields, drought-induced areas, drought-occurred areas, no harvest areas caused by drought and planting areas. Using the model, we assessed the drought risk. The results showed that spatial distribution of two drought disaster risks were coherent, and revealed complex zonality in southwestern China. The results also showed the drought risk is becoming more and more serious and frequent in the country under the global climatic warming background. The eastern part of the study area had an extremely high risk, and risk was generally greater in the north than in the south, and increased from southwest to northeast. The drought disaster risk or

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

    NASA Technical Reports Server (NTRS)

    Pozzi, Will; Sheffield, Justin; Stefanski, Robert; Cripe, Douglas; Pulwarty, Roger; Vogt, Jurgen V.; Heim, Richard R., Jr.; Brewer, Michael J.; Svoboda, Mark; Westerhoff, Rogier; vanDijk, Albert I. J. M.; Lloyd-Hughes, Benjamin; Pappenberger, Florian; Werner, Micha; Dutra, Emanuel; Wetterhall, Fredrik; Wagner, Wolfgang; Schubert, Siegfried; Mo, Kingste; Nicholson, Margaret; Bettio, Lynette; Nunez, Liliana; vanBeek, Rens; Bierkens, Marc; deGoncalves, Luis Gustavo Goncalves; deMattos, Joao Gerd Zell; Lawford, Richard

    2013-01-01

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

  12. 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

  13. Drought, Wetland, and Flood Monitoring with Satellite Scatterometer

    NASA Astrophysics Data System (ADS)

    Nghiem, S. V.; Brakenridge, G. R.; Neumann, G.

    2007-05-01

    Monitoring droughts, wetlands, and floods demands large scale and frequent coverage by satellite observations. Launched in 1999, the National Aeronautics and Space Administration (NASA) SeaWinds scatterometer aboard the QuikSCAT (QSCAT) satellite can collect backscatter data over 90% of the world in a day. The satellite scatterometer has acquired about 8 years of data and is currently measuring the Earth in 14 orbits per day. For drought monitoring, QSCAT data can detect surface soil moisture change and corresponding vegetation change. QSCAT identified drought conditions in the Midwest region of the United States in 2003 as the precipitation frequency observed by QSCAT decreases significantly. In Nairobi, Kenya, long-term QSCAT monitoring shows the severe droughts of 2000 and 2005. QSCAT data will be used together with other data types to enhance the U.S. Drought Monitor (USDM) to be transitioned into the National Integrated Drought Information System (NIDIS). At the other extreme, QSCAT data reveal the timing and patterns of surface soil moisture changes associated with winter storms in California in 2005 and with extreme hurricanes such as Ivan in 2004, Katrina, and Rita in 2005. Flood inundated areas are delineated by QSCAT along the Lena River, and such flooding is related to the snowmelt duration. QSCAT observations show that the Flood of Century along the Lena River in 2001 occurred after an excessively rapid spring melt period. QSCAT data are appropriate for wetland monitoring. The dynamics of wetlands in the Mississippi River basin observed by QSCAT include river discharge lagging the wetland change: first excess surface water is measured, and then streamflow increases. QSCAT data also capture the extreme seasonal wetland dynamics over the region of the Sudd swamps along the upper reaches of the White Nile River in southern Sudan. With the QSCAT capability in monitoring drought, wetland, and flood frequently over the world, QSCAT results will be crucial for

  14. Assessing Impacts of Drought on Agriculture Production and Food Security in Karamoja of Northeastern Uganda with Meteorological and NDVI-Based Indices - Some findings and challenges

    NASA Astrophysics Data System (ADS)

    Nakalembe, C. L.; Zhang, J.; Justice, C. O.

    2015-12-01

    Drought monitoring and planning requires spatially and temporally continuous information and its impacts on production and on society can easily be quantified when long-term (both crop production and climate) information is available. Such historical information is scanty and at best qualitative for Karamoja in Northeastern Uganda, a region considered to be most vulnerable to drought. To demonstrate the capabilities of currently available satellite data in filling this data gap in smallholder agricultural regions; this study first characterized agricultural drought at multiple temporal and spatial scales using Normalized Difference Vegetation Index (NDVI) data (1999-2011) and monthly rainfall data (1960-2011). Correlation analyses of the NDVI based drought indicators, Standardized Precipitation Index (SPI) and a global product of Palmer Drought Severity Index (PDSI). Spatial information is derived for the 1999-2000 period using MODIS 250m resolution data. The 12 month SPI (SPI-12) had the highest correlation with the MODIS NDVI record from (1999-2011) derived indices reaffirming the cumulative effect of rainfall on vegetation during the growing season and the utility of NDVI as an indicator of drought. Time-series plots were generated, the droughts were ranked and spatial maps derived for the most severe droughts between 2000- 2011. Temporal drought information is correlated with proxy indicators such as food aid supplies, available historical production data, market prices from within and in neighbouring regions and with to primary data collected through interviews with farmers in Moroto district. This study demonstrates that operationalizing drought monitoring can be realized with remote sensing and further affirms the importance of drought and agriculture monitoring for food security.

  15. Categorical Drought Monitoring and Prediction in the United States Based on NLDAS-2

    NASA Astrophysics Data System (ADS)

    Hao, Z.; Xia, Y.; Hao, F.; Singh, V. P.

    2015-12-01

    Drought is a pervasive natural hazard and is a billion-dollar disaster in the United States, which is comparable to hurricanes and tropical storms with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined. Drought early warning is of critical importance for drought preparedness planning and mitigation efforts to reduce potential impacts of drought, for which drought monitoring and prediction are the essential components. The U.S. Drought Monitor (USDM) has been widely used to track droughts and their impacts. USDM is a composite product that blends quantitative drought indicators and qualitative drought information from multiple sources and classifies drought conditions into different drought categories. Due to the wide application of USDM products, drought monitoring and prediction in the categorical form would be of great importance to aid decision makers to take appropriate measures for drought managements. Based on drought indices from North American Land Data Assimilation System Phase 2 (NLDAS-2), this study proposes a statistical method for the categorical drought monitoring and prediction in the United States. The probabilities of drought conditions falling into different USDM drought categories can be estimated from the proposed method. The method is found to satisfactorily reconstruct historical USDM drought categories and predict future USDM drought categories, and has considerable potential to aid early drought warning in the United States.

  16. Drought Monitoring in Peru as a Climate Service

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. Assessment of agricultural drought in rainfed cereal production areas of northern China

    NASA Astrophysics Data System (ADS)

    Li, Rui; Tsunekawa, Atsushi; Tsubo, Mitsuru

    2017-02-01

    Agricultural drought assessment is an important tool for water management in water-scarce regions such as Inner Mongolia and northeastern China. Conventional methods have difficulty of clarifying long-term influences of drought on regional agricultural production. To accurately evaluate regional agricultural drought, we assessed the performance of drought indices by constructing a new assessment framework with three components: crop model calibration and validation, drought index calculation, and index assessment (standard period setting, mean value and agreement assessments). The Environmental Policy Integrated Climate (EPIC) model simulated well of county-level wheat and maize yields in the nine investigated counties. We calculated a major crop-specific index yield reduction caused by water stress (WSYR) in the EPIC crop model, by relating potential and rainfed yields. Using 26 agricultural drought cases, we compared WSYR with two meteorological drought indices: precipitation (P) and aridity index (AI). The results showed that WSYR had greater agreement (85 %) than either the precipitation (65 %) or aridity index (68 %). The temporal trend of the indices over the period 1962-2010 was tested using three approaches. The result via WSYR revealed a significant increase in the trend of agricultural drought in drought-prone counties, which could not be shown by the precipitation and aridity indices. Total number of dry year via WSYR from 1990s to 2000s increases more sharply than via P or AI. As shown by WSYR, the number of dry years in northeastern China and Inner Mongolia is generally increasing, particularly after the 2000s, in the western part of the study area. The study reveals the usefulness of the framework for drought index assessment and indicates the potential of WSYR and possible drought cases for drought classification.

  18. Assessment of agricultural drought in rainfed cereal production areas of northern China

    NASA Astrophysics Data System (ADS)

    Li, Rui; Tsunekawa, Atsushi; Tsubo, Mitsuru

    2015-10-01

    Agricultural drought assessment is an important tool for water management in water-scarce regions such as Inner Mongolia and northeastern China. Conventional methods have difficulty of clarifying long-term influences of drought on regional agricultural production. To accurately evaluate regional agricultural drought, we assessed the performance of drought indices by constructing a new assessment framework with three components: crop model calibration and validation, drought index calculation, and index assessment (standard period setting, mean value and agreement assessments). The Environmental Policy Integrated Climate (EPIC) model simulated well of county-level wheat and maize yields in the nine investigated counties. We calculated a major crop-specific index yield reduction caused by water stress (WSYR) in the EPIC crop model, by relating potential and rainfed yields. Using 26 agricultural drought cases, we compared WSYR with two meteorological drought indices: precipitation (P) and aridity index (AI). The results showed that WSYR had greater agreement (85 %) than either the precipitation (65 %) or aridity index (68 %). The temporal trend of the indices over the period 1962-2010 was tested using three approaches. The result via WSYR revealed a significant increase in the trend of agricultural drought in drought-prone counties, which could not be shown by the precipitation and aridity indices. Total number of dry year via WSYR from 1990s to 2000s increases more sharply than via P or AI. As shown by WSYR, the number of dry years in northeastern China and Inner Mongolia is generally increasing, particularly after the 2000s, in the western part of the study area. The study reveals the usefulness of the framework for drought index assessment and indicates the potential of WSYR and possible drought cases for drought classification.

  19. Spatiotemporal behavior of floods and droughts and their impacts on agriculture in China

    NASA Astrophysics Data System (ADS)

    Zhang, Qiang; Gu, Xihui; Singh, Vijay P.; Kong, Dongdong; Chen, Xiaohong

    2015-08-01

    China is an agricultural country with the largest population in the world. However, intensification of droughts and floods and amplification of precipitation extremes are having critical negative impacts on agriculture. In this study, flood- and drought-affected, flood- and drought-damaged crop areas, and also flood- and drought-induced agricultural loss from 29 provinces across China are analyzed in both space and time. Results indicate the following: (1) Large parts of China are dominated by intensified floods. Comparatively, spatial ranges dominated by intensifying drought hazards are smaller than those by intensifying flood hazards. (2) Drought intensity is increasing in northwest China with moderate changes in the degree of influence. Increasing flood intensity can be observed in northwest, southwest and central China. However, flood risks are higher in arid regions such as northwest China and drought risks are higher in humid regions such as southwest China. (3) Agreements are identified between abrupt behaviors of flood-affected and -destroyed crop areas. The change points of flood-affected and -destroyed crop areas is in the 1980s in northeast, north and central China and in the 1990s in south and southwest China. Nevertheless, spatial patterns of the change points in the drought-affected and -destroyed crop areas are sporadic but not confirmative. (4) Flood- and drought-induced losses of agricultural production have significant increasing trends in most parts of China. The loss rate and loss magnitude of agriculture before change points are significantly higher than those after change points. (5) Generally, amplifications of precipitation extremes, decreasing consecutive wet days and increasing consecutive dry days in both space and time are the major driving factors behind the changes of drought- and flood-affected, and -destroyed crop areas and their impacts on agriculture across China. These results are theoretically and practically relevant for

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Anderson, W. B.; Hain, C.; Zaitchik, B. F.; Anderson, M. C.; Alo, C. A.; Yilmaz, M. T.

    2011-12-01

    East Africa contains a number of highly drought prone regions, and the humanitarian consequences of drought in those regions can be severe. The severity of these drought impacts combined with a paucity of in situ monitoring networks has given rise to numerous efforts to develop reliable remote drought monitoring systems based on satellite data, physically-based models, or a combination of the two. Here we present the results of a cross-comparison and preliminary integration of three soil moisture monitoring methodologies that, combined, offer the potential for a soil moisture based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa. Three independent methods for estimating soil moisture anomalies, the AMSR-E microwave based satellite sensor, the ALEXI thermal infrared based model and the Noah land surface model, are evaluated using triple collocation error analysis (TCEA). TCEA is used to estimate the reliability of each soil moisture anomaly methodology through statistical cross-comparison-a particularly useful approach given the virtual absence of in situ soil moisture data in this region. While AMSR-E, ALEXI, and Noah each appear to produce reliable soil moisture anomaly estimates over some areas within East Africa, many areas posed significant challenges to one or more methods. These challenges include seasonal cloud cover that hinders ALEXI estimates, dense vegetation that impedes AMSR-E retrievals, and complex hydrology that tests the limits of Noah model assumptions. TCEA allows for assessment of the reliability of each method across seasonal and geographic gradients and provides systematic criteria for merging the three methods into an integrated estimate of spatially distributed soil moisture anomalies for all of East Africa. Results for the period 2007-2011 demonstrate the potential and the limitations of this approach in application to real time drought monitoring.

  2. Droughts in the US: Modeling and Forecasting for Agriculture-Water Management and Adaptation

    NASA Astrophysics Data System (ADS)

    Perveen, S.; Devineni, N.; Lall, U.

    2012-12-01

    More than half of all US counties are currently mired in a drought that is considered the worst in decades. A persistent drought can not only lead to widespread impacts on water access with interstate implications (as has been shown in the Southeast US and Texas), chronic scarcity can emerge as a risk in regions where fossil aquifers have become the primary source of supply and are being depleted at rates much faster than recharge (e.g., Midwestern US). The standardized drought indices on which the drought declarations are made in the US so far consider only the static decision frameworks—where only the supply is the control variable and not the water consumption. If a location has low demands, drought as manifest in the usual indices does not really have "proportionate" social impact. Conversely, a modest drought as indicated by the traditional measures may have significant impacts where demand is close to the climatological mean value of precipitation. This may also lead to drought being declared too late or too soon. Against this fact, the importance of improved drought forecasting and preparedness for different sectors of the economy becomes increasingly important. The central issue we propose to address through this paper is the construction and testing of a drought index that considers regional water demands for specific purposes (e.g., crops, municipal use) and their temporal distribution over the year for continental US. Here, we have highlighted the use of the proposed index for three main sectors: (i) water management organizations, (ii) optimizing agricultural water use, and (iii) supply chain water risk. The drought index will consider day-to-day climate variability and sectoral demands to develop aggregate regional conditions or disaggregated indices for water users. For the daily temperature and precipitation data, we are using NLDAS dataset that is available from 1949 onwards. The national agricultural statistics services (NASS) online database has

  3. Assessment of Meteorological and Agriculture Drought Severity in Barani Areas of Pakistan

    NASA Astrophysics Data System (ADS)

    Haque, Saad Ul

    2016-07-01

    Drought is a natural hazard and part of climatic condition for all regions of the world. It is the condition of moisture deficit caused by a certain climatic conditions occurring at a specific location for a specific duration. Stems from the lack of precipitation, precipitation deficiency for a season, a year or longer and is triggered, when water supplies become insufficient to meet the requirements. Pakistan predominantly consists of arid and semiarid regions with a diversified climate where Agriculture sector plays a vital role in countries economy, as it is the largest sector of Pakistan, accounting for over 20.9 percent of GDP. Nearly 62 percent of the country's rural population and is directly or indirectly linked with agriculture for their livelihood. (Pakistan Economic Survey, 2011). Thus, for such type of landscapes where agriculture mainly depends on the amount of precipitation and there is no use of canal irrigation system, so there is a need to make some immediate interventions in the area of drought hazard management & a proactive planning to mitigate its adverse impacts. In this study drought is assessed on its sequential stages, first of all meteorological conditions that include rainfall data and MODIS Satellite NDVI product, having good temporal resolution for drought assessment in order to identify dry spell period. This whole waterless season leads to agricultural drought as crops and vegetation begin to degrade with low production rate. Some more parameters such as Max. Temperature, Humidity, Solar Radiation, Evapotranspiration were incorporated by assigning suitable weights according to their sensitivity for drought. Severity of Agricultural drought was determine by using NDVI anomaly and crop anomaly pattern. Finally, the correlation regression analysis was performed to identify the effect of different dependent variables on their supporting parameters. The combined drought severity map was generated by overlying the agricultural and

  4. North-south differences in Chinese agricultural losses due to climate-change-influenced droughts

    NASA Astrophysics Data System (ADS)

    Qiang, Zhang; Lanying, Han; Jingjing, Lin; Qingyan, Cheng

    2016-12-01

    One of the effects of global climate change is increase in the frequency and severity of drought, which strongly affects the Chinese agricultural production. In order to cope these changes more effectively, it is important to document and analyze the agricultural losses caused by drought. We collected and analyzed conventional meteorological data and agricultural statistics data, in order to outline trends in drought occurrence and decline in agricultural yield. Data were assembled for the period 1960-2010. The study pays particular attention to regional differences between northern and southern China. Our results show the drought-caused agricultural loss rates (DCALR) in China have increased by approximately 0.5% per decade in the past 50 years. The study area in this paper is for the whole of the People's Republic of China, minus the Qinghai-Tibetan Plateau; when we analyzed regional differences, we found that losses increased by approximately 0.6% per decade in northern China, close to twice the increase in southern China. Moreover, drought risks and agricultural losses are rising faster in northern China. Our results also indicate that the agriculture in northern China is more sensitive to changes in precipitation, whereas the agriculture in southern China is more sensitive to temperature changes.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. Climate Change Impact on Meteorological, Hydrological, and Agricultural Drought: A case study of Central Illinois

    NASA Astrophysics Data System (ADS)

    Cai, X.; Wang, D.; Hejazi, M. I.; Valocchi, A. J.

    2010-12-01

    Regional climate change projections based on dynamic downscaling through regional climate models are used to assess drought frequency, intensity and duration, and the impact propagation from meteorological, hydrological and agricultural sectors. The impact on a meteorological drought index (standardized precipitation index, SPI) is first assessed based on daily climate inputs from RCMs driven by three general circulation models (GCMs) (PCM, HadCM3, CCSM3) with different climate sensitivities. Two emission scenarios, relatively high and low emission, are undertaken for each of the three GCMs and dynamically downscaled through the RCMs. Feeding the climate projections to a calibrated hydro-agronomic model at the watershed scale in Central Illinois, hydrological drought (standardized runoff index, SRI) and agricultural drought (standardized soil water index, SSWI) indices and the economic impacts are assessed. RCMs driven by different GCMs predict different changes of drought properties. From the intensity-density-frequency (IDF) curves of SPI, SSWI, and SRI based on the three GCM-RCMs, as expected, the return period increases with the increase of drought duration for a given drought intensity. However, the change of IDF curves from baseline to future years varies with GCM-RCM and drought indicator. HadCM3-RCM predicts moderate increase of drought frequency and CCSM3-RCM predicts significant increase of drought frequency especially for the SSWI and SRI with moderate drought intensity (I<-1). The combination of climate sensitivity and emission scenarios determines the future drought predictions. In general high sensitivity and high emission level results in more serious droughts, particularly, the increase of the frequency of moderate drought is more significant with high emission scenarios. However, even though the climate sensitivity of HadCM3 is high compared to the other two GCMs, the exceedance probability curves of drought indices from HadCM3-RCM is almost

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

    NASA Astrophysics Data System (ADS)

    El Vilaly, Mohamed Abd salam M.

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

  8. A multivariate approach for drought monitoring across the continental United States

    NASA Astrophysics Data System (ADS)

    Hao, Z.; Aghakouchak, A.

    2012-12-01

    Drought monitoring is fundamental to decision-making and reducing drought effect. A variety of variables, such as, precipitation, soil moisture and runoff have been used to characterize different forms of drought. Several indices, such as the standardized precipitation index (SPI), soil moisture anomaly, have been used for drought monitoring. Due to the complexity of drought phenomenon in its causation and impact, drought monitoring based on a single variable may not be sufficient for detecting drought condition promptly and reliably. The recently proposed Multivariate Standardized Drought Index (MSDI; Hao and AghaKouchak, 2012) describes droughts based on the states of multiple variables such as precipitation and soil moisture. In this study, MSDI is employed for drought analysis including detecting drought onsite, recession, severity and spatial extent across the continental United States. The results are cross -validated with the U.S. Drought Monitor data as well as the commonly used standardized indices (e.g., SPI). The results show that MSDI provides attractive properties in drought detection and that it is a useful tool for drought monitoring. Reference: Hao Z., AghaKouchak A., 2012, A multivariate multi-index drought modeling framework, Water Resources Research, under review.

  9. 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.

  10. 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

  11. 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.

  12. GRACE satellite monitoring of large depletion in water storage in response to the 2011 drought in Texas

    NASA Astrophysics Data System (ADS)

    Long, Di; Scanlon, Bridget R.; Longuevergne, Laurent; Sun, Alexander Y.; Fernando, D. Nelun; Save, Himanshu

    2013-07-01

    Texas experienced the most extreme one-year drought on record in 2011 with precipitation at 40% of long-term mean and agricultural losses of $7.6 billion. We assess the value of Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage (TWS) change as an alternative remote sensing-based drought indicator, independent of traditional drought indicators based on in situ monitoring. GRACE shows depletion in TWS of 62.3 ± 17.7 km3 during the 2011 drought. Large uncertainties in simulated soil moisture storage depletion (14-83 km3) from six land surface models indicate that GRACE TWS is a more reliable drought indicator than disaggregated soil moisture or groundwater storage. Groundwater use and groundwater level data indicate that depletion is dominated by changes in soil moisture storage, consistent with high correlation between GRACE TWS and the Palmer Drought Severity Index. GRACE provides a valuable tool for monitoring statewide water storage depletion, linking meteorological and hydrological droughts.

  13. Development of a distributed agricultural drought prediction model based on TOPMODEL and GIS

    NASA Astrophysics Data System (ADS)

    Xu, Jingwen; Zhang, Wanchang; Wang, Changquan; Zhu, Xuemei; Chen, Jiongfeng

    2009-07-01

    Drought disasters occur frequently in eastern China and are typical in China and even in the world. Severe droughts seriously affect the agricultural production, social and economic development, ecology and human life. In this paper, a new agricultural drought prediction model was developed based on GIS technology and TOPMODEL, which is a physically based watershed hydrological model that simulates the variable-source-area concept of stream-flow generation and has been widely used to study a variety of research areas. In this study, the original TOPMODEL was extended to be a distributed hydrological model. The watershed is divided into a number of regular grids, corresponding to the grids of DEM, and each grid is viewed as a sub-basin. So the surface runoff production was calculated at each grid. The runoff at each grid is routed along the stream flow direction to the main watershed outlet respectively at different velocity depending on the slop of this grid and watershed-average routing velocity. The soil moisture is predicted using the new distributed hydrological model. Finally, drought prediction is conducted by combining the predicted soil moisture and drought indices. The new model was tested in Linyi watershed, Shandong province, China. The results show that the model performs well in agricultural drought prediction.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Teng, William L.

    1990-01-01

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

  16. Assessing Change in Agricultural Productivity Caused by Drought and Conflict in Northern Syria using Landsat Imagery.

    NASA Astrophysics Data System (ADS)

    Girgin, T.; Ozdogan, M.

    2015-12-01

    Until recently, agricultural production in Syria has been an important source of revenue and food security for the country. At its peak, agriculture in Syria accounted for 25 percent of the country's GDP. In 2014, Syrian agriculture accounted for less than 5 percent of the GDP. This decline in agricultural productivity is the cause of a 3-year long drought that started in 2007, followed by a still-ongoing conflict that started in mid-2011. Using remote sensing tools, this paper focuses on the impact that the 2007-2010 drought had on agricultural production, as well as the impact that the ongoing conflict had on the agricultural production in northern Syria. Remote sensing is a powerful and great solution to study regions of the world that are hard-to-reach due to conflict and/or other limitations. It is particularly useful when studying a region that inaccessible due to an ongoing conflict, such as in northern Syria. Using multi-temporal Landsat 5 and Landsat 8 images from August 2006, 2010 and 2014 and utilizing the neural networks algorithm, we assessed for agricultural output change in northern Syria. We conclude that the ongoing Syrian conflict has had a bigger impact on the agricultural output in northern Syria than the 3-year long drought.

  17. Impact of drought on agriculture in the Indo-Gangetic Plain, India

    NASA Astrophysics Data System (ADS)

    Nath, Reshmita; Nath, Debashis; Li, Qian; Chen, Wen; Cui, Xuefeng

    2017-03-01

    In this study, we investigate the spatiotemporal characteristics of drought in India and its impact on agriculture during the summer season (April-September). In the analysis, we use Standardized Precipitation Evapotranspiration Index (SPEI) datasets between 1982 and 2012 at the six-monthly timescale. Based on the criterion SPEI < -1, we obtain a map of the number of occurrences of drought and find that the humid subtropical Upper Middle Gangetic Plain (UMGP) region is highly drought-prone, with an occurrence frequency of 40%-45%. This UMGP region contributes at least 18%-20% of India's annual cereal production. Not only the probability of drought, but the UMGP region has become increasingly drought-prone in recent decades. Moreover, cereal production in the UMGP region has experienced a gradual declining trend from 2000 onwards, which is consistent with the increase in drought-affected areas from 20%-25% to 50%-60%, before and after 2000, respectively. A higher correlation coefficient (-0.69) between the cereal production changes and drought-affected areas confirms that at least 50% of the agricultural (cereal) losses are associated with drought. While analyzing the individual impact of precipitation and surface temperature on SPEI at 6 month timescale [SPEI (6)] we find that, in the UMGP region, surface temperature plays the primary role in the lowering of the SPEI. The linkage is further confirmed by correlation analysis between SPEI (6) and surface temperature, which exhibits strong negative values in the UMGP region. Higher temperatures may have caused more evaporation and drying, which therefore increased the area affected by drought in recent decades.

  18. 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

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    of M&EW and future aspirations. Different stakeholders clearly have different goals for M&EW, but there are a number of common themes, including a desire to better understand the links between the outputs of large-scale M&EW systems (rainfall, river flow, etc), localised triggers used by decision-makers during drought episodes, and actual impacts of drought. Secondly, we present analyses designed to test the utility of a wide range of drought indicators for their use in UK applications. We demonstrate the suitability of standardised indicators (like the SPI) for use in the UK, addressing the suitability of statistical distributions and using these indicators for drought severity quantification and for understanding propagation from meteorological to hydrological drought; all of which are currently poorly understood aspects that are vital for future monitoring. We then address the extent to which these indicators can be used to predict drought impacts, focusing on several sectors (water supply, agriculture and ecosystems). These analyses test which indicators perform best at predicting drought impacts, and seek to identify indicator thresholds that trigger impact occurrence. Unsurprisingly, we found that no single indicator best predicts impacts, and results are domain, sector and season specific. However, we reveal important linkages between indicators and impacts that could enhance the design and delivery of monitoring and forecasting information and its uptake by decision-makers concerned with drought.

  2. Drought Effects on Agricultural Yield: Comparison Across Regions and Crop Types

    NASA Astrophysics Data System (ADS)

    Daryanto, S.; Wang, L.; Jacinthe, P. A.

    2014-12-01

    Global agricultural production is dominated by rainfed agriculture, and is therefore prone to disruption from climate extreme weathers. These uncertainties become more problematic when considering the projection of increased drought frequency suggested by several climate models for various world regions. Curiously, few regional analyses of drought impact of food production have been attempted. We collated and analyzed data from the last 25 years to disentangle the effects of drought (i.e. timing, intensity and duration) on agricultural production in different eco-regions and with varying crop types. Our preliminary results suggested greater yield reduction in annual (-21.5%) than perennial plants (-16%), in C4 (-21%) compared to C3 crops (-17%), and when drought occurred during generative (i.e. flowering until maturity; -16.5%) than vegetative stage (-15.5%). Although drought caused similar amounts of yield reduction in both tropical and subtropical regions (i.e. -17%), it carries a greater food security risk in the tropics due to inherently low productivity (i.e. less than half than in the subtropical regions). Consequently, cultivating drought-resistant C3 perennial plants (e.g. sweet potato and cassava) in the tropics could prove a viable adaptive strategy to mitigate the effects of climate variability. In addition, these crops have limited input requirements, are well adapted to nutrient-poor Oxisols and Ultisols of the tropics, and generally outyield cereal crops in the region. Our analysis is ongoing and needs to take into account agronomic traits (e.g. water requirement), as well as the energy and nutritional values (e.g. protein, minerals) of alternative crops. Our results could inform the selection and development of new cultivars for the drought-prone regions of the world.

  3. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study

    NASA Astrophysics Data System (ADS)

    Mishra, Ashok K.; Ines, Amor V. M.; Das, Narendra N.; Prakash Khedun, C.; Singh, Vijay P.; Sivakumar, Bellie; Hansen, James W.

    2015-07-01

    Drought is of global concern for society but it originates as a local problem. It has a significant impact on water quantity and quality and influences food, water, and energy security. The consequences of drought vary in space and time, from the local scale (e.g. county level) to regional scale (e.g. state or country level) to global scale. Within the regional scale, there are multiple socio-economic impacts (i.e., agriculture, drinking water supply, and stream health) occurring individually or in combination at local scales, either in clusters or scattered. Even though the application of aggregated drought information at the regional level has been useful in drought management, the latter can be further improved by evaluating the structure and evolution of a drought at the local scale. This study addresses a local-scale agricultural drought anatomy in Story County in Iowa, USA. This complex problem was evaluated using assimilated AMSR-E soil moisture and MODIS-LAI data into a crop model to generate surface and sub-surface drought indices to explore the anatomy of an agricultural drought. Quantification of moisture supply in the root zone remains a gray area in research community, this challenge can be partly overcome by incorporating assimilation of soil moisture and leaf area index into crop modeling framework for agricultural drought quantification, as it performs better in simulating crop yield. It was noted that the persistence of subsurface droughts is in general higher than surface droughts, which can potentially improve forecast accuracy. It was found that both surface and subsurface droughts have an impact on crop yields, albeit with different magnitudes, however, the total water available in the soil profile seemed to have a greater impact on the yield. Further, agricultural drought should not be treated equal for all crops, and it should be calculated based on the root zone depth rather than a fixed soil layer depth. We envisaged that the results of

  4. 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.

  5. 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.

  6. Assessment of Early Season Agricultural Drought Through Land Surface Water Index (lswi) and Soil Water Balance Model

    NASA Astrophysics Data System (ADS)

    Chandrasekar, K.; Sesha Sai, M. V. R.; Behera, G.

    2011-08-01

    An attempt was made to address the early season agriculture drought, by monitoring the surface soil wetness during 2010 cropping seasons in the states of Andhra Pradesh and Tamil Nadu. Short Wave Infrared (SWIR) based Land Surface Water Index (LSWI) and Soil Water Balance (SWB) model using inputs from remote sensing and ancillary data were used to monitor early season agriculture drought. During the crop season, investigation was made on LSWI characteristics and its response to the rainfall. It was observed that the Rate of Increase (RoI) of LSWI was the highest during the fortnights when the onset of monsoon occurred. The study showed that LSWI is sensitive to the onset of monsoon and initiation of cropping season. The second part of this study attempted to develop a simple book keeping - bucket type - water tight soil water balance model to derive the top 30cm profile soil moisture using climatic, soil and crop parameters as the basic inputs. Soil moisture derived from the model was used to compute the Area Conducive for Sowing (ACS) during the sowing window of the cropping season. The soil moisture was validated spatially and temporally with the ground observed soil moisture values. The ACS was compared with the RoI of LSWI. The results showed that the RoI was high during the sowing window whenever the ACS was greater than 50% of the district area. The observation was consistent in all the districts of the two states. Thus the analysis revealed the potential of LSWI for early season agricultural drought management.

  7. 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

  8. Monitoring pathogens from irradiated agriculture products

    NASA Astrophysics Data System (ADS)

    Butterweck, Joseph S.

    The final food and environmental safety assessment of agriculture product irradiation can only be determined by product history. Product history will be used for future research and development, regulations, commercial practices and implementation of agriculture and food irradiation on a regional basis. The commercial irradiator treats large varieties and amounts of products that are used in various environments. It, in time, will generate a large data base of product history. Field product monitoring begins when food irradiation progresses from the pilot/demonstration phase to the commercial phase. At that time, it is important that there be in place a monitoring system to collect and analyze field data. The systems managers, public health authorities and exotic disease specialists will use this information to assess the reduction of food pathogens on the populace and the environment. The common sources of monitoring data are as follows: 1) Host Monitoring a) Medical Diagnosis b) Autopsy c) Serology Surveys 2) Environmental Monitoring a) Sentinel b) Pest Surveys/Microbial Counts c) Sanitary Inspections 3) Food Industries Quality Assurance Monitoring a) End Product Inspection b) Complaints c) Continual Use of the Product

  9. 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

  10. Impacts of the Mid - Summer Drought on Agricultural Activities. Two study cases

    NASA Astrophysics Data System (ADS)

    Conde, C.; Ferrer, R. M.

    2007-05-01

    Mid - summer drought is a known climatic phenomenon for maize producers in the State of Tlaxcala, Mexico.The forecasts delivered by the Autonomous University of Tlaxcala and the National Autonomous University of Mexico during several years included an estimation of the severity of the "canícula", in order that the producers could plan their agricultural activities. The intensity of the mid - summer drought increases during strong EL Niño events (i. e. 1982 - 1983; 1997 - 1998) , that can be also associated to an increase of sudden frosts in autumn that might affect the maize production. In this paper the perception of farmers in Tlaxcala, their needs for specific forecasts and the possibilities of useful climatic information is presented. Also, using an agricultural simulation model, the possible effects on maize yields of a severe mid- summer drought is analyzed. A second study case was performed in Veracruz, were it has been documented that the intensity of the mid - summer drought decreases during strong El Niño events. Possible impacts of this condition on agricultural activities in the state are also presented.

  11. Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation

    NASA Astrophysics Data System (ADS)

    Cheng, C. L.

    2015-12-01

    Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation Chung-Lien Cheng, Wen-Ping Tsai, Fi-John Chang* Department of Bioenvironmental Systems Engineering, National Taiwan University, Da-An District, Taipei 10617, Taiwan, ROC.Corresponding author: Fi-John Chang (changfj@ntu.edu.tw) AbstractIn Taiwan, the population growth and economic development has led to considerable and increasing demands for natural water resources in the last decades. Under such condition, water shortage problems have frequently occurred in northern Taiwan in recent years such that water is usually transferred from irrigation sectors to public sectors during drought periods. Facing the uneven spatial and temporal distribution of water resources and the problems of increasing water shortages, it is a primary and critical issue to simultaneously satisfy multiple water uses through adequate reservoir operations for sustainable water resources management. Therefore, we intend to build an intelligent reservoir operation system for the assessment of agricultural water resources management strategy in response to food security during drought periods. This study first uses the grey system to forecast the agricultural water demand during February and April for assessing future agricultural water demands. In the second part, we build an intelligent water resources system by using the non-dominated sorting genetic algorithm-II (NSGA-II), an optimization tool, for searching the water allocation series based on different water demand scenarios created from the first part to optimize the water supply operation for different water sectors. The results can be a reference guide for adequate agricultural water resources management during drought periods. Keywords: Non-dominated sorting genetic algorithm-II (NSGA-II); Grey System; Optimization; Agricultural Water Resources Management.

  12. 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

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

    PubMed

    Sehgal, Vinay Kumar; Dhakar, Rajkumar

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. Conceptualizing the dynamics of a drought affected agricultural community

    NASA Astrophysics Data System (ADS)

    Kuil, Linda; Carr, Gemma; Viglione, Alberto; Bloeschl, Guenter

    2015-04-01

    Climate and especially water availability and variability play an important role in the development of our societies. This can be seen through the vast investments that are made in reaching water security and the economic impact regions experience when the rains fail. However, the limit of available fresh water is increasingly felt as our population increases and the demand for water continues to rise. But how do we as society respond? Are periods of drought making us more resilient? The answer to this question is sought through the development of a stylized model that is built within the spirit of the Easter Island model by Brander and Taylor and aimed at capturing the essence of the dynamics of water supply and demand. By explicitly incorporating feedbacks, but keeping the framework simple, the model seeks to understand qualitative behavior of our socio-hydrological system as opposed to predicting exact pathways. The model shows that carrying capacity dynamics are a determining factor for continued growth. Future work will explore the underlying relationships further, among others, through examination of case studies.

  17. 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

  18. An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data

    NASA Astrophysics Data System (ADS)

    Carrão, Hugo; Russo, Simone; Sepulcre-Canto, Guadalupe; Barbosa, Paulo

    2016-06-01

    We propose a simple, spatially invariant and probabilistic year-round Empirical Standardized Soil Moisture Index (ESSMI) that is designed to classify soil moisture anomalies from harmonized multi-satellite surface data into categories of agricultural drought intensity. The ESSMI is computed by fitting a nonparametric empirical probability density function (ePDF) to historical time-series of soil moisture observations and then transforming it into a normal distribution with a mean of zero and standard deviation of one. Negative standard normal values indicate dry soil conditions, whereas positive values indicate wet soil conditions. Drought intensity is defined as the number of negative standard deviations between the observed soil moisture value and the respective normal climatological conditions. To evaluate the performance of the ESSMI, we fitted the ePDF to the Essential Climate Variable Soil Moisture (ECV SM) v02.0 data values collected in the period between January 1981 and December 2010 at South-Central America, and compared the root-mean-square-errors (RMSE) of residuals with those of beta and normal probability density functions (bPDF and nPDF, respectively). Goodness-of-fit results attained with time-series of ECV SM values averaged at monthly, seasonal, half-yearly and yearly timescales suggest that the ePDF provides triggers of agricultural drought onset and intensity that are more accurate and precise than the bPDF and nPDF. Furthermore, by accurately mapping the occurrence of major drought events over the last three decades, the ESSMI proved to be spatio-temporal consistent and the ECV SM data to provide a well calibrated and homogenized soil moisture climatology for the region. Maize, soybean and wheat crop yields in the region are highly correlated (r > 0.82) with cumulative ESSMI values computed during the months of critical crop growing, indicating that the nonparametric index of soil moisture anomalies can be used for agricultural drought

  19. Empirically Estimating the Existing Irrigation Adaptation to Future Drought Impacts in Kansas Agriculture

    NASA Astrophysics Data System (ADS)

    Zhang, T.; Lin, X.; Yang, X.

    2014-12-01

    More serious drought has been projected due to the climate change in the Kansas State of the U.S., which might threaten the local agriculture and thus require effective adaptation responses to drought, e.g. better irrigation. But the irrigation adaptation on drought at the current technology-level is poorly quantified, therefore challenges to figure out how much additional efforts are required under more aridity of climate. Here, we collect the irrigation application data for maize, soybean, sorghum and wheat in Kansas, and establish a two-stage model to quantify the crop-specific irrigation application responses to changes in climatic drivers, and further estimate the existing effectiveness of the irrigation to adapt future drought based on the IPCC AR5 ensemble PDSI prediction under RCP4.5 scenario. We find that the three summer season crops (maize, soybean and sorghum) would experience 0 - 20% yield losses depending on county due to more serious drought since 2030s, even though increased irrigation application as the response of drought had saved 0 - 10% yields. At the state level, maize receives most benefits from irrigation, whereas the beneficial effects are least for sorghum among the three crops. To wheat, irrigation adaptation is very weak since irrigation water applied is much less than the above three crops. But wheat yields were projected to have a slight increase in central and eastern regions because climate would become more moisture over the growing season of winter wheat in future. Our results highlight that the existing beneficial effects from irrigation would be surpassed by the negative impact of drought in future, which would cause overall yield reduction in Kansas especially for those summer season crops.

  20. A seasonal agricultural drought forecast system for food-insecure regions of East Africa

    USGS Publications Warehouse

    Shukla, Shraddhanand; McNally, Amy; Husak, Gregory; Funk, Christopher C.

    2014-01-01

     The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall

  1. A seasonal agricultural drought forecast system for food-insecure regions of East Africa

    NASA Astrophysics Data System (ADS)

    Shukla, S.; McNally, A.; Husak, G.; Funk, C.

    2014-03-01

    The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993-2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is

  2. A seasonal agricultural drought forecast system for food-insecure regions of East Africa

    NASA Astrophysics Data System (ADS)

    Shukla, S.; McNally, A.; Husak, G.; Funk, C.

    2014-10-01

    The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agropastoral management decisions, support optimal allocation of the region's water resources, and mitigate socioeconomic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's (FEWS NET) science team. We evaluate this forecast system for a region of equatorial EA (2° S-8° N, 36-46° E) for the March-April-May (MAM) growing season. This domain encompasses one of the most food-insecure, climatically variable, and socioeconomically vulnerable regions in EA, and potentially the world; this region has experienced famine as recently as 2011. To produce an "agricultural outlook", our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios describing the upcoming season. First, we forced the VIC model with high-quality atmospheric observations to produce baseline soil moisture (SM) estimates (here after referred as SM a posteriori estimates). These compared favorably (correlation = 0.75) with the water requirement satisfaction index (WRSI), an index that the FEWS NET uses to estimate crop yields. Next, we evaluated the SM forecasts generated by this system on 5 March and 5 April of each year between 1993 and 2012 by comparing them with the corresponding SM a posteriori estimates. We found that initializing SM forecasts with start-of-season (SOS) (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month and, in some cases, 3-month lead times. Similarly, when the forecast was initialized with midseason (i.e., 5

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

    USGS Publications Warehouse

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

    2014-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields.

  5. Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. 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

  7. Drought Impacts on Ancient Maya Maize Agriculture Inferred from Isotopic Analyses of Plant Biomarkers

    NASA Astrophysics Data System (ADS)

    Douglas, P. M.; Pagani, M.; Eglinton, T. I.; Brenner, M.; Hodell, D. A.; Curtis, J. H.

    2013-05-01

    There is increasing evidence suggesting that a series of droughts in the Maya lowlands of southeastern Mexico and northern Central America coincided with the Terminal Classic decline of the Classic Maya civilization (ca. 1250 to 1000 years BP). However, there is little evidence directly linking climatic change and changes in human activities in this region. In this study we combine plant-wax hydrogen and carbon analyses in two lake sediment cores from the Yucatan and northern Guatemala to develop coupled records of hydroclimate variability and human-driven vegetation change and assess drought impacts on maize agriculture In the Maya lowlands plant-wax hydrogen isotope ratios (δD) are controlled by the isotopic composition of precipitation and evapotranspiration, and are highly sensitive to changes in aridity. In this low-elevation tropical environment plant-wax carbon isotope ratios (δ13C) are largely controlled by the relative abundance of C3 and C4 plants. The ancient Maya practiced widespread maize (C4) agriculture and strongly influenced regional C3-C4 vegetation dynamics. Under natural conditions C4 plant coverage and plant-wax δD would tend to co-vary positively since C4 plants are well adapted for dry conditions. Under ancient Maya land-use, however, this relationship is likely to be decoupled, since drought would have disrupted C4 agriculture. Combined analyses of plant-wax δD and δ13C from two lake sediment cores in the Maya lowlands indicate co-evolving changes in hydroclimate and C4 plant coverage over the past 4000 years. Compound-specific radiocarbon analyses of plant-waxes provide independent chronologies for these plant-wax stable isotope records, and plant-wax δD records developed using these chronologies agree closely with other regional records of hydroclimate change. Trends in plant-wax δD and δ13C diverge following ca. 3500 years BP, around the onset of widespread ancient Maya agriculture. After this time high plant-wax δD values tend

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

    NASA Technical Reports Server (NTRS)

    Estep, Leland

    2007-01-01

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

  9. Development of Combined Drought Indicator in Cereals to use its predictive value in the Agricultural Insurances: CDI_Cereal

    NASA Astrophysics Data System (ADS)

    Jimenez-Donaire, Pilar; Tarquis, Ana M.; Giráldez, Juan V.

    2015-04-01

    The agrometeorological or agricultural drought is one of the most severe problems of agriculture. Drought damage is defined in terms of harvest loss due to precipitation shortage that limits soil moisture availability for the crops, substantially reducing crop yield. A method is proposed to identify the rain fed cereal agricultural drought in several Andalusian regions, based on the combination of three indices or anomalies: (i) standard precipitation index (SPI-3) based on Mishra and Desai (2005), (ii) soil moisture described with a water balance model based on the hydrological model by Brocca et al., 2008, and (iii) the normalized difference vegetation index (NDVI) based on Kogan (1995). Coupling the three anomalies, a Combined Drought Indicator -for rain fed cereals- (CDI) has been obtained. This indicator characterizes different warning levels of agricultural drought, which has been successfully assessed with the data of the period 2003-2013 (Jiménez-Donaire, 2014). The final aim of the proposed CDI is to design a warning system based on its components' combination to forecast the drought risk helping both farmers and agricultural insurance agencies. Keywords: drought, SPI, soil moisture, NDVI. References Brocca, L., Melone, F., Moramarco, T.(2008) On the estimation of antecedent wetness conditions in rainfall-runoff modelling. Hydrol. Process. 22, 629-642. Jiménez-Donaire, M.P. (2014) Indicador combinado de sequía para cereales y su valor predictivo en los seguros agrarios: ICS_CEREAL. Master thesis, UCO (In Spanish). Kogan, F.N., 1995. Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data. Bull. Am. Meteorol. Soc. 76, 655-668. Mishra, A.K., Desai, V.R., 2005. Drought forecasting using stochastic models. Stoch. Environ. Res. Risk Assess. 19, 326-339. Acknowledgements First author acknowledges the Research Grant obtained from CEIGRAM in 2014

  10. Monitoring drought using multi-sensor remote sensing data in cropland of Gansu Province

    NASA Astrophysics Data System (ADS)

    Zeng, Linglin; Shan, Jie; Xiang, Daxiang

    2014-03-01

    Various drought monitoring models have been developed from different perspectives, as drought is impacted by various factors (precipitation, evaporation, runoff) and usually reflected in various aspects (vegetation condition, temperature). Cloud not only plays an important role in the earth's energy balance and climate change, but also directly impacts the regional precipitation and evaporation. As a result, the change of cloud cover and cloud type can be used to monitor drought. This paper proposes a new drought composite index, the Drought Composite Index (DCI), for drought monitoring based on multi-sensor remote sensing data in cropland of Gansu Province. This index combines the cloud classification data (CLS) from FY satellite and Vegetation Condition Index (VCI) which was calculated using the maximum and minimum NDVI values for the same time period from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson correlation was performed to correlate NDVI, VCI, CLS and DCI values to precipitation data and soil moisture (SM) data collected from 20 meteorological stations during the growing season of 2011 and 2012. Better agreement was observed between DCI and precipitation as compared with that between NDVI/VCI and precipitation, especially the one-month precipitation, and there is an obvious time lag in the response of vegetation to precipitation. In addition, the results indicated that DCI well reflected precipitation fluctuations in the study area promising a possibility for early drought awareness necessary and near real-time drought monitoring.

  11. Monitoring of Agricultural Landscape in Norway

    NASA Astrophysics Data System (ADS)

    Wallin, H. G.; Engan, G.

    2012-07-01

    An overall societal aim is to ensure a sustainable use and management of agricultural landscapes. This requires continuous delivery of reliable and up-to-date information to decision-makers. To be able to deliver this information, a monitoring program for agricultural landscapes was initiated in Norway 13 years ago. The program documents and reports on land use / land cover changes from data captured through interpretation of true colour aerial photos using stereo instruments. The monitoring programme is based on a sample of 1000 squares of 1 × 1 km and the entire sample of squares is photographed over a five-year period. Each square is then mapped repeatedly every fifth year to record changes. Aerial photo interpretation is based on a custom classification system which is built up hierarchically, with three levels. The first level comprises seven land type classes: Agricultural land, Bare ground, Semi-natural open vegetation, Unforested wetland vegetation, Forest, Urban areas and Water. These land classes are further divided into 24 land types at level two, and approximately 100 land types at level 3. In addition to land type units we map both line elements like stone fences and point elements like buildings and solitary threes. By use of indicators that describe status and change focusing on themes of particular policy interest, we can report on whether policy aims are being fulfilled or not. Four indicator themes have been in focus hitherto: landscape spatial structure, biological diversity, cultural heritage and accessibility. Our data is stored in databases and most of the data quality check/structure process and analyses are now being made in open source software like PostGIS and PostSQL. To assess the accuracy of the photo-interpretation, ground truthing is carried out on 10 % of the squares. The results of this operation document the benefits of having access to photos of the same area from two different years. The program is designed first and foremost to

  12. Characterization of agricultural drought risk by a two-dimensional copula

    NASA Astrophysics Data System (ADS)

    Vergni, Lorenzo; Todisco, Francesca; Mannocchi, Francesco

    2015-04-01

    In this work, the joint probability distribution of two agricultural drought characteristics (Relative Severity, RS, and Onset, O) has been modeled by a two-dimensional copula. The application is illustrated with reference to a single-station case study (Perugia, Central Italy) and to the crop sunflower, widely grown in Central Italy, usually under rainfed conditions. The 86-year time series of daily precipitation and maximum and minimum temperature from the Perugia station (Central Italy) were used to simulate the soil water dynamics in the root-zone of sunflower. For each year, single seasonal values of RS and O have been quantified by applying the theory of runs to the soil water volume dynamics, with a threshold equal to the crop critical point. RS derives from the summation of the severities (i.e. total water stress) of the drought runs occurred during the growing season. The attribute 'relative' is here used because the severity value is corrected taking into account both the available water capacity of the soil and the growing season length. Thus, RS is a non-dimensional value ranging between 0 (no water stress) and 1 (maximum theoretical water stress for a given growing season length). The characteristic O describes the water stress temporal position (with respect to the growing season length) and it derives from a weighted average of the times of occurrence of the different drought runs (run severities being the weights). O is a non-dimensional value that expresses the temporal position of water stress as percentage of residual growing season, and it ranges between 0 (drought location at harvest) and 1 (drought location at seeding). The information provided by this characteristic can be considered particularly useful in agricultural drought risk management, because, as it is known, the drought impact on crop yield (being equal the severity) can vary substantially with the sensitivity of the growth stages affected by water stress conditions. The analysis

  13. Monitoring the agricultural landscape for insect resistance

    NASA Astrophysics Data System (ADS)

    Casas, Joseph; Glaser, J. A.; Copenhaver, Ken

    Farmers in 25 countries on six continents are using plant biotechnology to solve difficult crop production challenges and conserve the environment. In fact, 13.3 million farmers, which include 90 percent of the farming in developing countries, choose to plant biotech crops. Over the past decade, farmers increased area planted in genetically modified (GM) crops by more than 10 percent each year, thus increasing their farm income by more than 44 billion US dollars (1996-2007), and achieved economic, environmental and social benefits in crops such as soybeans, canola, corn and cotton. To date, total acres of biotech crops harvested exceed more than 2 billion with a proven 13-year history of safe use. Over the next decade, expanded adoption combined with current research on 57 crops in 63 countries will broaden the advantages of genetically modified foods for growers, consumers and the environment. Genetically modified (GM) crops with the ability to produce toxins lethal to specific insect pests are covering a larger percentage of the agricultural landscape every year. The United States department of Agriculture (USDA) estimated that 63 percent of corn and 65 percent of cotton contained these specific genetic traits in 2009. The toxins could protect billions of dollars of loss from insect damage for crops valued at greater than 165 billion US dollars in 2008. The stable and efficient production of these crops has taken on even more importance in recent years with their use, not only as a food source, but now also a source of fuel. It is in the best interest of the United States Environmental Protection Agency (USEPA) to ensure the continued efficacy of toxin producing GM crops as their use reduces pesticides harmful to humans and animals. However, population genetics models have indicated the risk of insect pests developing resistance to these toxins if a high percentage of acreage is grown in these crops. The USEPA is developing methods to monitor the agricultural

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

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

    2015-03-01

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

  17. Putting Current North America Drought Conditions Into a Multi-Century Perspective. Part 2: Using the Blended Product in Operational Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Heim, R. R.; Vose, R. S.; Lawrimore, J. H.; Cook, E. R.

    2007-12-01

    Drought is an important climatological phenomenon which has significant socioeconomic and environmental impacts. Several drought indices have been developed to quantify drought, and all of them rely on meteorological observations taken at instrumented in situ weather stations. The instrumental record for drought monitoring in the U.S. extends back only about a hundred years, and the record is even shorter in other countries such as Canada and Mexico. As a result, recurrence intervals and water management compacts (for example, the Colorado River Basin domestic or Rio Grande international compacts) based upon such short records may not be built upon the long-term climatology of a region. Reliable drought information can be derived from paleoclimatic data such as tree-rings, thus enabling researchers and decision-makers to assess drought variability and impacts over a multi-century period. Previous work has developed research-quality paleoclimatic drought reconstructions which have been used in retrospective analyses but, until now, such data have not been used comprehensively in operational monitoring. Part 1 of this paper describes the development of the reconstructed paleoclimatic Palmer drought index gridded dataset for North America from tree-ring data. Part 2 of this paper describes how the reconstructed paleoclimatic data base is blended with a 20th century instrumental- based Palmer drought index gridded dataset for operational drought monitoring applications across North America.

  18. 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

  19. Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review.

    PubMed

    Maes, W H; Steppe, K

    2012-08-01

    As evaporation of water is an energy-demanding process, increasing evapotranspiration rates decrease the surface temperature (Ts) of leaves and plants. Based on this principle, ground-based thermal remote sensing has become one of the most important methods for estimating evapotranspiration and drought stress and for irrigation. This paper reviews its application in agriculture. The review consists of four parts. First, the basics of thermal remote sensing are briefly reviewed. Second, the theoretical relation between Ts and the sensible and latent heat flux is elaborated. A modelling approach was used to evaluate the effect of weather conditions and leaf or vegetation properties on leaf and canopy temperature. Ts increases with increasing air temperature and incoming radiation and with decreasing wind speed and relative humidity. At the leaf level, the leaf angle and leaf dimension have a large influence on Ts; at the vegetation level, Ts is strongly impacted by the roughness length; hence, by canopy height and structure. In the third part, an overview of the different ground-based thermal remote sensing techniques and approaches used to estimate drought stress or evapotranspiration in agriculture is provided. Among other methods, stress time, stress degree day, crop water stress index (CWSI), and stomatal conductance index are discussed. The theoretical models are used to evaluate the performance and sensitivity of the most important methods, corroborating the literature data. In the fourth and final part, a critical view on the future and remaining challenges of ground-based thermal remote sensing is presented.

  20. Remotely Sensed Estimates of Evapotranspiration in Agricultural Areas of Northwestern Nevada: Drought, Reliance, and Water Transfers

    NASA Astrophysics Data System (ADS)

    Bromley, Matthew

    irrigation use. These factors result in Lovelock being extremely susceptible to instances of prolonged drought, and exhibiting large fluctuations in annual ET. This work clearly illustrates that agricultural consumptive use is a function of water supply, weather, and land use change, which is useful in distinguishing how prolonged droughts and changing climate will potentially affect different hydrographic areas and agricultural communities in the future.

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

    NASA Astrophysics Data System (ADS)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Sanchao; Li, Wenbo

    2011-12-01

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

  4. A Multiple-player-game Approach to Agricultural Water Use in Regions of Seasonal Drought

    NASA Astrophysics Data System (ADS)

    Lu, Z.

    2013-12-01

    In the wide distributed regions of seasonal drought, conflicts of water allocation between multiple stakeholders (which means water consumers and policy makers) are frequent and severe problems. These conflicts become extremely serious in the dry seasons, and are ultimately caused by an intensive disparity between the lack of natural resource and the great demand of social development. Meanwhile, these stakeholders are often both competitors and cooperators in water saving problems, because water is a type of public resource. Conflicts often occur due to lack of appropriate water allocation scheme. Among the many uses of water, the need of agricultural irrigation water is highly elastic, but this factor has not yet been made full use to free up water from agriculture use. The primary goal of this work is to design an optimal distribution scheme of water resource for dry seasons to maximize benefits from precious water resources, considering the high elasticity of agriculture water demand due to the dynamic of soil moisture affected by the uncertainty of precipitation and other factors like canopy interception. A dynamic programming model will be used to figure out an appropriate allocation of water resources among agricultural irrigation and other purposes like drinking water, industry, and hydropower, etc. In this dynamic programming model, we analytically quantify the dynamic of soil moisture in the agricultural fields by describing the interception with marked Poisson process and describing the rainfall depth with exponential distribution. Then, we figure out a water-saving irrigation scheme, which regulates the timetable and volumes of water in irrigation, in order to minimize irrigation water requirement under the premise of necessary crop yield (as a constraint condition). And then, in turn, we provide a scheme of water resource distribution/allocation among agriculture and other purposes, taking aim at maximizing benefits from precious water resources, or in

  5. 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

  6. Drought severity in intensive agricultural areas by means of the EDI index

    NASA Astrophysics Data System (ADS)

    Procházková, Petra; Chuchma, Filip; Středa, Tomáš

    2016-12-01

    The aim of this work was the evaluation of drought severity development in the Czech Republic for the period 1971-2015 by the means of the Effective Drought Index (EDI). Annual values of the EDI index were determined using the method of effective precipitation for 14 localities spread throughout the Czech Republic (Central Europe). The seven categories were created according to obtained index values for the drought conditions determination for years during the period 1971-2015 through the percentile method. The annual index values were compared with acquired 2nd, 15th, 45th, 55th, 85th and 98th percentiles. Both the years with precipitation unfavourable conditions: 1972, 1973, 1984, 1990, 1991, 1992, 1993 and 2015 and the years with precipitation favourable conditions: 1977, 1987, 1995, 2001, 2002 and 2010 were determined. Precipitation conditions in the growing season from 61st to 180th day of the year were also analysed. This evaluation was conducted during the period 1971-2015 through the ten-day index values which were compared with acquired 2nd, 15th, 45th, 55th, 85th and 98th percentiles. Dry growing seasons occurred in 1973, 1974, 1976 and 1993. Wet growing seasons occurred in 1987, 2006 and 2010. Trend analysis of annual index values was performed through the Mann-Kendall test. Highly statistically significant increasing linear trends (P < 0.01) were found for four localities (Uherský Ostroh, Vysoká, Znojmo-Oblekovice and Žatec); statistically significant increasing trends (P < 0.05) were found for three localities (Brno-Chrlice, Lednice and Lípa). Based on the extrapolation of the trend, a slightly higher effective precipitation can be expected during the year in a substantial part of the country. However, these findings do not necessarily mean an optimal supply of agricultural land with water. Precipitation exhibits considerable unevenness of distribution through time. Given the increasing evapotranspiration demands of the environment their

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Automated system for generation of soil moisture products for agricultural drought assessment

    NASA Astrophysics Data System (ADS)

    Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

    2014-11-01

    Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically

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

    NASA Astrophysics Data System (ADS)

    Norton, M.

    2015-12-01

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

  10. Characterizing and Monitoring Drought in the 21st Century--Issues and Opportunities

    NASA Astrophysics Data System (ADS)

    Brown, J. F.

    2005-12-01

    Droughts originate from precipitation deficiencies resulting in water shortages that affect certain activities or sectors. Since droughts are normal climate phenomena, society has been dealing with their related impacts and consequences for many centuries. Historically, reliable observations of rainfall have been available for about two hundred years, and most meteorological drought indicators incorporate this variable, either alone or combined with other measures. Traditionally, surface observation networks have been the primary sources for drought information. However, common limitations of climate indicators derived from ground-based networks include large gaps in coverage and coarse spatial detail. In addition, decision-makers need information concerning the effects that drought may be having on certain human and natural systems. Specific examples of these effects include declining forage production, lower crop yields, increased wildfire danger, deteriorating soil conditions, diminishing water supplies, and limits on recreation. Droughts differ from other natural hazards in several significant ways. They may be gradual or "creeping" in their development (on the scale of weeks or months, not days). They can last for periods of years and exhibit large variability in both spatial extent and severity. Monitoring and predicting drought conditions are necessary activities of government agencies at State, Federal, and local levels as part of decision support for planning, risk management, and hazard mitigation activities. Satellite remotely-sensed data providing large-area synoptic coverage and finer spatial resolution can fill in the gaps, reinforce, and complement the science framework for characterizing, monitoring, and predicting natural hazards. Earth observations from remote platforms have a unique role to provide information pertinent to all hazards. For drought science, examples of key data sets include satellite rainfall estimates, albedo measurements, soil

  11. Remote sensing experiment in West Africa. [drought effects on desert agriculture and vegetation in Niger

    NASA Technical Reports Server (NTRS)

    Macleod, N. H.

    1974-01-01

    There are substantial needs of the Sahelien Zone to detail the state of regional agricultural resources in the face of a sixth year of serious drought conditions. While most of the work has been done in the Republic of Niger, the principles which have emerged from the analysis seem to be applicable to much of the Sahel. The discussion relates to quite specific rehabilitation and development initiations under consideration in Niger which are based in part upon direct analysis of ERTS imagery of the country, in part on field surveys and on discussions with Nigerian officials and technicians. Again, because the entire Sahelien Zone (including Niger) has large zones of similar ecologic characteristics, modificiations of the approaches suggested for Niger are applicable to the solution of rehabilitation of the desert, the savannah and the woodlands of West Africa in general.

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Yi, Hang; Wen, Lianxing

    2016-01-01

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

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

    PubMed Central

    Yi, Hang; Wen, Lianxing

    2016-01-01

    We use satellite gravity measurements in the Gravity Recovery and Climate Experiment (GRACE) to estimate terrestrial water storage (TWS) change in the continental United States (US) from 2003 to 2012, and establish a GRACE-based Hydrological Drought Index (GHDI) for drought monitoring. GRACE-inferred TWS exhibits opposite patterns between north and south of the continental US from 2003 to 2012, with the equivalent water thickness increasing from −4.0 to 9.4 cm in the north and decreasing from 4.1 to −6.7 cm in the south. The equivalent water thickness also decreases by −5.1 cm in the middle south in 2006. GHDI is established to represent the extent of GRACE-inferred TWS anomaly departing from its historical average and is calibrated to resemble traditional Palmer Hydrological Drought Index (PHDI) in the continental US. GHDI exhibits good correlations with PHDI in the continental US, indicating its feasibility for drought monitoring. Since GHDI is GRACE-based and has minimal dependence of hydrological parameters on the ground, it can be extended for global drought monitoring, particularly useful for the countries that lack sufficient hydrological monitoring infrastructures on the ground. PMID:26813800

  15. 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.

  16. 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.

  17. 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.

  18. Utility of Satellite Data to monitor drought and floods in India

    NASA Astrophysics Data System (ADS)

    Mishra, V.

    2015-12-01

    Extreme hydrologic events such as droughts and floods pose tremendous pressure on society. The damage due to extreme events has increased during the recent decades and it may increase even further under the projected future climate. Real time monitoring of hydrologic extremes is essential to minimize losses to society and infrastructure. However, in many areas, where gauge based observations are not available in timely manner, real-time monitoring of droughts and floods has been challenging. In the absence of in-situ gauge based observations, satellite data from the various platform may provide an useful information for the real-time monitoring. Using the precipitation data from the Tropical Rainfall Measurement Mission (TRMM) a real-time monitor that updates on daily basis was developed for India. The hydrologic variables (soil moisture, runoff, and Evapotranspiration) were simulated using the Variable Infiltration Capacity (VIC) model. The real-time monitor was successfully evaluated for the drought and flood monitoring in India. The monitor provides soil moisture and total runoff conditions at a high resolution. Moreover, the monitor can provide a valuable information on daily streamflow monitoring at the selected gauge stations in India.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Cammalleri, Carmelo; Micale, Fabio; Vogt, Jürgen

    2015-04-01

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

  1. Precipitation monitoring to accurately depict drought conditions on your allotment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Great Basin Rangelands Research Unit of the U.S. Department of Agriculture, Agricultural Research Service has been reading numerous precipitation gauges throughout the Great Basin for more than three decades. State climatologists, land owners and researchers have obtained data from this long-ter...

  2. 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

  3. Water quality monitoring of an agricultural watershed lake: the effectiveness of agricultural best management practices

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Beasley Lake is an oxbow lake located in the Lower Mississippi Alluvial Plain (the Delta), a region of intensive agricultural activity. Due to intensive row-crop agricultural practices, the 915 ha watershed was sediment impaired when monitoring began in 1995 and was a candidate to assess the effect...

  4. Comparing SMMR and AVHRR data for drought monitoring

    NASA Technical Reports Server (NTRS)

    Tucker, Compton J.

    1989-01-01

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

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

    PubMed

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

    2016-05-15

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

  6. Monitoring soil microbial dynamics in agroecosystems during two years of recovery after record drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We monitored soil microbial dynamics in six agroecosystem in the Southern Plains of the U.S. during climatic recovery after four years of record drought. Our previous study provided some of the first information that linked significant reductions in soil enzymatic potential and microbial diversity ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop yield decreases when photosynthesis is limited by heat or drought conditions. Yet farmers do not monitor crop photosynthesis because it is difficult to measure at the field scale in real time. Steady-state chlorophyll fluorescence (Fs) can be used at the field level as an indirect measure of p...

  8. 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

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

    NASA Astrophysics Data System (ADS)

    Enenkel, Markus; Rojas, Oscar; Balint, Zoltan

    2013-04-01

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

  10. Simplified overturn stability monitoring of agricultural tractors.

    PubMed

    Nichol, C I; Sommer, H J; Murphy, D J

    2005-02-01

    Agricultural tractors are the most common source of farm work fatalities in the U.S., with overturns the most common type of incident. For the year 2001, there were 15 tractor-related fatalities in Pennsylvania, 9 of which were due to tractor rollover. A new device using low-cost sensors and microcomputers was developed around a simplified mathematical model of an agricultural tractor to inform the operator of potential tractor instability. This device communicates the current rollover potential, along with a recent history of rollover potential, to the operator of the tractor via a simple bar-graph display. The device uses a single-chip accelerometer to sense the current rollover potential and a small microprocessor to analyze the accelerometer data, compensate for variations due to temperature, and then send this information to a visual display. The use of these low-cost "off the shelf" components enabled the fabrication of a very inexpensive sensor system. Because agricultural tractors have a long service life, it was important to make the device low cost and flexible. This could enable it to be sold as an aftermarket add-on for a variety of tractor models. The device is also capable of interfacing with newer on-board tractor systems via a CAN bus to make it more attractive to tractor manufacturers who may want to incorporate this device into new models. Work is continuing on the development of an improved display to inform the tractor operator of possible instability, including display ergonomic studies, investigation of threshold levels for alerting an operator of potential instability, and investigation into audible warning signals.

  11. Enhancing Drought Early Warning System for Sustainable Water Resources and Agricultural Management through Apllication of Space Science - Nigeria in Perspective

    NASA Astrophysics Data System (ADS)

    Okpara, J. N.; Akeh, L. E.; Anuforom, A. C.; Aribo, P. B.; Olayanju, S. O.

    Enhancing Drought Early Warning System for Sustainable Water Resources and Agriculture Management through Application of Space Science - Nigeria in Perspective BY J N Okpara L E Akeh Anuforom P B Aribo and S O Olayanju Directorate of Applied Meteorological Services Nigerian Meteorological Agency NIMET P M B 615 Garki Abuja Nigeria e-mail underline Juddy Okpara yahoo co uk and underline tonycanuforom yahoo com underline Abstract This paper attempts to highlight the importance of drought early warning system in water resources and agricultural management in Nigeria Various studies have shown that the negative impacts of droughts and other forms of extreme weather phenomena can be substantially reduced by providing early warning on any impending weather extremes X-rayed in this study are the various techniques presently used by the Nigerian Meteorological Agency NIMET in generating information for meteorological Early Warning System EWS which are based on models that make use of ground-based raingauge data and sea surface temperatures SST Komuscu standardized precipitation index SPI inclusive These methods are often limited by such factors as network density of stations limited communication infrastructure human inefficiency etc NIMET is therefore embarking on the development of a new Satellite Agrometeorological Information System SAMIS-Nigeria for famine and drought early warning The system combines satellite data with raingauge data to give a range of

  12. Prediction of agricultural drought for the Canadian prairies using climatic and satellite data

    NASA Astrophysics Data System (ADS)

    Kumar, Vijendra

    1999-11-01

    Wheat export is a significant component of the Canadian economy. In normal (nondrought) years, the export is as high as 30 million tonnes, but it is reduced to about 20 million tomes in drought years. This significant reduction in exports not only reduces direct profits but may also upset export targets and prices that are set in advance, if droughts are not accurately predicted. In this thesis, prediction of agricultural drought is attempted from both long-term and short-term perspectives. The long-term prediction refers to predicting wheat yield (production per unit area) prior to wheat planting; and, under the short-term prediction, wheat yield is estimated around harvesttime. Predictive analysis was performed on five crop districts of Saskatchewan (1b, 3bn, 4b, 6a, and 9a) using climate data (monthly and daily temperature and precipitation) from rune weather stations. In addition, Normalized Difference Vegetation Index values generated from NOAA (National Oceanic and Atmospheric Administration)/AVERR (Advanced Very High Radiometric Resolution) satellite data were used. The long-term prediction was made by fitting various time series techniques (trend, moving average, exponential smoothing, and autoregressive integrated moving average) to the yield series in a district. The technique providing minimum prediction-error was selected. The short-term prediction was made in both qualitative and quantitative forms. The qualitative prediction was attempted using the error correction procedure of pattern recognition. The. quantitative prediction involved modification of the computer program currently being used by the Canadian Wheat Board (CWB) to estimate wheat yield. The CWB program employs only monthly and precipitation and determines a drought index for a weather station. A hybrid model that employs daily climate data and a NDVI-based variable was developed. Among Various NDVI-based variables, the average NDVI during the entire growing period was found to be the

  13. 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.

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

    PubMed

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

    2011-10-01

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

  15. Improving Drought Monitoring and Predictions Using Physically Based Evaporative Demand Estimates

    NASA Astrophysics Data System (ADS)

    Hobbins, M. T.; Wood, A. W.; Werner, K.

    2011-12-01

    Existing drought monitors rely heavily on precipitation (Prcp) and temperature (T) data to derive moisture fluxes at the surface, often using estimates of evaporative demand (Eo) based only on T to derive actual evapotranspiration (ET) from land surface models (LSMs). An example of this is the popular Palmer Drought Severity Index (PDSI). In the analysis of drought trends and dynamics, however, the choice of Eo-driver for LSMs is crucial: it significantly affects both the direction and magnitude of trends in estimated ET and soil moisture, particularly in energy-limited areas (in water-limited areas, ET and soil moisture trends are driven by Prcp trends). All else equal, in the long term, T-based Eo measures result in declining ET estimates (i.e., drying) as T rises, whereas using more appropriate, physically based Eo estimates will more accurately reflect observations of both wetting and drying under warming. With regard to the short-term variabilities more appropriate to monitoring ongoing droughts, we contend that, given that various requirements are met, using an appropriate Eo driver (i) as a drought metric in itself, (ii) to drive drought monitors' LSMs, and (iii) in combination with short-term Eo forecasts will enhance characterization of the evaporative dynamics of ongoing drought and permit more accurate predictions of drought development. The requirements of an appropriate Eo estimate are as follows: that at operationally appropriate time and space scales Eo is diagnostic of ET (i.e., ET and Eo co-vary in a complementary fashion); that the Eo formulation and driving data produce good estimates of Eo (i.e., the model is physically based in that it combines radiative and advective drivers, and produces Eo estimates that are accurate and unbiased with respect to observations from drivers that are available with limited latency on a daily basis) and at operational spatio-temporal resolutions; and that Eo can be forecast at operational time and space scales

  16. Development of drought and/or heat tolerant crop varieties, an adaptation approach to mitigate impact of climate change on agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As global climate change becomes inevitable, the sustainability of agricultural production in US and worldwide faces serious threat from extreme weather conditions, such as drought and high temperature (heat wave). Development of drought and/or heat tolerant crop varieties is one of the most effecti...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Rochon, Gilbert L.

    1989-01-01

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

  1. Drought impact on forest growth and mortality in the southeast USA: an analysis using Forest Health and Monitoring data.

    PubMed

    Klos, Ryan J; Wang, G Geoff; Bauerle, William L; Rieck, James R

    2009-04-01

    Drought frequency and intensity has been predicted to increase under many climate change scenarios. It is therefore critical to understand the response of forests to potential climate change in an effort to mitigate adverse impacts. The purpose of this study was to explore the regional effects of different drought severities on tree growth and mortality. Specifically, we investigated changes in growth and mortality rates across the southeastern United States under various drought and stand conditions using 1991-2005 Forest Health and Monitoring (FHM) plot data from Alabama, Georgia, and Virginia. Drought effects were examined for three species groups (pines, oaks, and mesophytic species) using the Palmer drought severity index (PDSI) as an indicator of drought severity. Stand variables, including total basal area, total tree density, tree species richness, slope, and stand age, were used to account for drought effects under varying stand conditions. The pines and mesophytic species exhibited significant reductions in growth rate with increasing drought severity. However, no significant difference in growth rate was observed within the oak species group. Mean mortality rates within the no-drought class were significantly lower than those within the other three drought classes, among which no significant differences were found, for both pines and mesophytic species. Mean mortality rates were not significantly different among drought classes for oaks. Total basal area, total tree density, and stand age were negatively related to growth and positively related to mortality, which suggests that older and denser stands are more susceptible to drought damage. The effect of basal area on growth increased with drought severity for the oak and mesophytic species groups. Tree species richness was negatively related to mortality for the pine and mesophytic species groups, indicating that stands with more species suffer less mortality. Slope was positively related to mortality

  2. Applying Earth Observation Data to agriculture risk management: a public-private collaboration to develop drought maps in North-East China

    NASA Astrophysics Data System (ADS)

    Surminski, S.; Holt Andersen, B.; Hohl, R.; Andersen, S.

    2012-04-01

    Earth Observation Data (EO) can improve climate risk assessment particularly in developing countries where densities of weather stations are low. Access to data that reflects exposure to weather and climate risks is a key condition for any successful risk management approach. This is of particular importance in the context of agriculture and drought risk, where historical data sets, accurate current data about crop growth and weather conditions, as well as information about potential future changes based on climate projections and socio-economic factors are all relevant, but often not available to stakeholders. Efforts to overcome these challenges in using EO data have so far been predominantly focused on developed countries, where satellite-derived Normalized Difference Vegetation Indexes (NDVI) and the MERIS Global Vegetation Indexes (MGVI), are already used within the agricultural sector for assessing and managing crop risks and to parameterize crop yields. This paper assesses how public-private collaboration can foster the application of these data techniques. The findings are based on a pilot project in North-East China where severe droughts frequently impact the country's largest corn and soybeans areas. With support from the European Space Agency (ESA), a consortium of meteorological experts, mapping firms and (re)insurance experts has worked to explore the potential use and value of EO data for managing crop risk and assessing exposure to drought for four provinces in North-East China (Heilongjiang, Jilin, Inner Mongolia and Liaoning). Combining NDVI and MGVI data with meteorological observations to help alleviate shortcomings of NDVI specific to crop types and region has resulted in the development of new drought maps for the time 2000-2011 in digital format at a high resolution (1x1 km). The observed benefits of this data application range from improved risk management to cost effective drought monitoring and claims verification for insurance purposes

  3. African agricultural subsidy impacts food security, poverty, drought tolerance, and environmental quality

    NASA Astrophysics Data System (ADS)

    Galford, G. L.; Palm, C.; DeFries, R. S.; Nziguheba, G.; Droppelmann, K.; Nkonya, E.; Michelson, H.; Clark, C.; Kathewera, F.; Walsh, M.

    2011-12-01

    Malawi has spearheaded an unprecedented policy change in sub-Saharan Africa (SSA) since 2005 when it started a widespread agricultural inputs subsidy program (AISP) targeting small farmer maize production with mineral fertilizer and improved seeds. Since then, the mean N fertilizer load has increased significantly, from ~ 0 to a modest 35 kg N/ha or 7 times greater than SSA's average 5 kg N/ha average. During the tenure of AISP, Malawi has transitioned from a food aid recipient to an exporter. Maize yields each year of AISP are double the long-term average (0.8 tons/ha/yr, 1960-2005). In 2007, subsidy inputs combined with good rains led to of an unprecedented increase in national average yields of 2.7 tons/ha. National-scale assessments covering, agriculture, poverty, and environment such as this one are required to understand the trade-offs between development, climate and the environment. Environmentally, N2O emissions from fertilizer are a concern. First order estimates put emissions from AISP fertilizers at 2,600 Mg N2O/year (0.81 Tg CO2-e). While globally insignificant, these emissions may be equivalent to 16% of Malawi's annual fossil fuel and deforestation emissions. However, our partial nutrient budgets indicate that crop removal is still higher than N applied and therefore little loss of N to the environment is expected. Mineral fertilizers are a rapid first step to increase soil N after 40 years of serious depletion. Once restored, the soils will support robust agroforestry and other forms of organic inputs produced on-farm. Fertilizer use increases carbon sequestration on agricultural soils and reduces pressure to clear forests, which may partially compensate for the N2O emissions. We find evidence that AISP significantly increases food security and mitigates the impacts of drought on maize production. This is the first work linking the distribution of fertilizer subsidies to local crop yields using government records, remotely-sensed time series of

  4. Water Reform and the Resilience of Small Business People in Drought-Affected Agricultural Communities

    ERIC Educational Resources Information Center

    Schwarz, Imogen; Williams, Pam McRae

    2009-01-01

    The impact of drought on rural communities in Australia has been the subject of considerable research. Less well understood are the impacts of drought on rural small businesses and the mechanisms they use to adapt or cope through extended dry periods. In this study, strategies these businesses draw upon to manage this adversity are identified and…

  5. An integrated approach to monitoring ecosystem services and agriculture: implications for sustainable agricultural intensification in Rwanda.

    PubMed

    Rosa, Melissa F; Bonham, Curan A; Dempewolf, Jan; Arakwiye, Bernadette

    2017-01-01

    Maintaining the long-term sustainability of human and natural systems across agricultural landscapes requires an integrated, systematic monitoring system that can track crop productivity and the impacts of agricultural intensification on natural resources. This study presents the design and practical implementation of a monitoring framework that combines satellite observations with ground-based biophysical measurements and household surveys to provide metrics on ecosystem services and agricultural production at multiple spatial scales, reaching from individual households and plots owned by smallholder farmers to 100-km(2) landscapes. We developed a set of protocols for monitoring and analyzing ecological and agricultural household parameters within two 10 × 10-km landscapes in Rwanda, including soil fertility, crop yield, water availability, and fuelwood sustainability. Initial results suggest providing households that rely on rainfall for crop irrigation with timely climate information and improved technical inputs pre-harvest could help increase crop productivity in the short term. The value of the monitoring system is discussed as an effective tool for establishing a baseline of ecosystem services and agriculture before further change in land use and climate, identifying limitations in crop production and soil fertility, and evaluating food security, economic development, and environmental sustainability goals set forth by the Rwandan government.

  6. 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

  7. Combined hydrogen and carbon isotopes of plant waxes as an indicator of drought impacts on ancient Maya agriculture

    NASA Astrophysics Data System (ADS)

    Douglas, P. M.; Pagani, M.; Eglinton, T. I.; Brenner, M.; Hodell, D. A.; Curtis, J. H.

    2012-12-01

    There is increasing evidence suggesting that a series of droughts in the Yucatan Peninsula coincided with the Terminal Classic decline of the Classic Maya civilization (ca. 1250 to 1000 years BP). However, there is little evidence directly linking climatic change and changes in human activities in this region. In this study we combine plant-wax δD, δ13C, and Δ14C analyses in two lake sediment cores from southeastern Mexico and northern Guatemala to develop coupled records of hydroclimate variability and human-driven vegetation change. Plant-wax specific Δ14C ages indicate a large input of pre-aged plant waxes into lake sediment. Comparison of plant-wax δD records with other regional hydroclimate proxy records suggest that plant-wax ages are evenly distributed around plant-wax radiocarbon ages, and that applying an age model based on plant-wax radiocarbon ages is appropriate for these lake sediments. We evaluate how differences in plant-wax age distributions influence stable isotope records to assess the age uncertainty associated with records of climate and vegetation change derived from plant-wax stable isotopes. In this low-elevation tropical environment plant-wax δ13C is largely controlled by the relative abundance of C3 and C4 plants. The ancient Maya practiced widespread maize (C4) agriculture and strongly influenced regional C3-C4 vegetation dynamics. Under natural conditions C4 plant coverage and plant-wax δ13C would tend to co-vary positively since C4 plants are well adapted for dry conditions. Under ancient Maya land-use, however, this relationship is likely to be decoupled, since drought would have disrupted C4 agriculture. Combined analysis of plant-wax δD and δ13C from both lakes indicates increasingly divergent trends following ca. 3500 years BP, around the onset of widespread ancient Maya agriculture. After this time high plant-wax δD values tend to correspond with low plant-wax δ13C values and vice versa. This pattern is consistent with

  8. 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.

  9. An Application of RFID in Monitoring Agricultural Material Products

    NASA Astrophysics Data System (ADS)

    Du, Jianhui; Li, Peipei; Gao, Wanlin; Wang, Dezhong; Wang, Qing; Zhu, Yilong

    With the development of modern agriculture, more and more agricultural material products are used in it. While how to keep these things safe is a big problem at present, which needs to be paid more attention. This article develops an agricultural material products monitor system based on RFID which gives alarm as soon as possible if there is anything unmoral. Every warehouse exit is equipped with a RFID reader, while each agricultural material product has a tag on them. When passing though, the reader identifies the tag's information and transfer it to the PC, The PC inquiries the database storing all tags' information, and tells which one is not taken out legally by alarming aloud.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  11. 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

  12. 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.

  13. Sixteen years of agricultural drought assessment of the BioBío region in Chile using a 250 m resolution Vegetation Condition Index (VCI)

    NASA Astrophysics Data System (ADS)

    Zambrano, Francisco; Lillo-Saavedra, Mario; Verbist, Koen; Lagos, Octavio

    2016-10-01

    Drought is one of the most complex natural hazards because of its slow onset and long-term impact; it has the potential to negatively affect many people. There are several advantages to using remote sensing to monitor drought, especially in developing countries with limited historical meteorological records and a low weather station density. In the present study, we assessed agricultural drought in the croplands of the BioBio Region in Chile. The vegetation condition index (VCI) allows identifying the temporal and spatial variations of vegetation conditions associated with stress because of rainfall deficit. The VCI was derived at a 250m spatial resolution for the 2000-2015 period with the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 product. We evaluated VCI for cropland areas using the land cover MCD12Q1 version 5.1 product and compared it to the in situ Standardized Precipitation Index (SPI) for six-time scales (1-6 months) from 26 weather stations. Results showed that the 3-month SPI (SPI-3), calculated for the modified growing season (Nov-Apr) instead of the regular growing season (Sept-Apr), has the best Pearson correlation with VCI values with an overall correlation of 0.63 and between 0.40 and 0.78 for the administrative units. These results show a very short-term vegetation response to rainfall deficit in September, which is reflected in the vegetation in November, and also explains to a large degree the variation in vegetation stress. It is shown that for the last 16 years in the BioBio Region we could identify the 2007/2008, 2008/2009, and 2014/2015 seasons as the three most important drought events; this is reflected in both the overall regional and administrative unit analyses. These results concur with drought emergencies declared by the regional government. Future studies are needed to associate the remote sensing values observed at high resolution (250m) with the measured crop yield to identify more detailed individual crop

  14. 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.

  15. Weekly Water Stress Monitoring in a Savannah Environment using a new Data Fusion Drought Index

    NASA Astrophysics Data System (ADS)

    Azmi, M.; Rudiger, C.; Walker, J. P.

    2015-12-01

    Due to the increasing pressure on water resources, water stress monitoring has become one of the most significant issues in water resources planning and management, especially during periods of extreme climate conditions. The present study compares the performance of four currently used data fusion based drought indices (DFDIs) to evaluate the weekly water stress at the Howard Springs OzFlux Tower in Northern Australia, covering a 3-year period from January 2011 to December 2013. In addition, a new DFDI has been developed and applied to address the individual shortcomings of the traditional indices. The proposed DFDI comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type (water, vegetation etc). Here, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were utilized for the evaluations. To derive the new DFDI, an appropriate set of individual standardized drought indices (SDIs) was derived, that are categorized through an advanced clustering method. For two groups in which the clustered SDIs best reflected the water availability and vegetation conditions, the variables are aggregated based on an averaging between the standardized first principal components of three different multivariate methods of PCA, FA and ICA. Then, considering those aggregated indices as well as the classifications of months into dry/wet and active/non-active, the time series of the proposed DFDI is finalized. A comparison, employing the Spearman correlation coefficient, between the proposed index and the traditional data fusion based indices shows a range of correlations from 0.46 to 0.85. The results underline that the proposed index can be more reliable in compare to the previous indices, due to simultaneously relating hydro-meteorological and ecological concepts to define the actual water stress throughout the study area.

  16. Earth Observations for Early Detection of Agricultural Drought in Countries at Risk: Contributions of the Famine Early Warning Systems Network (FEWS NET) (Invited)

    NASA Astrophysics Data System (ADS)

    Verdin, J. P.; Rowland, J.; Senay, G. B.; Funk, C. C.; Budde, M. E.; Husak, G. J.; Jayanthi, H.

    2013-12-01

    The Group on Earth Observations' Global Agricultural Monitoring (GEOGLAM) implementation plan emphasizes the information needs of countries at risk of food insecurity emergencies. Countries in this category are often vulnerable to disruption of agricultural production due to drought, while at the same time they lack well developed networks of in-situ observations to support early drought detection. Consequently, it is vital that Earth observations by satellites supplement those available from surface stations. The USGS, in its role as a FEWS NET implementing partner, has recently developed a number of new applications of satellite observations for this purpose. (1) In partnership with the University of California, Santa Barbara, a 30+ year time series of gridded precipitation estimates (CHIRPS) has been developed by blending NOAA GridSat B1 geostationary thermal infrared imagery with station observations using robust geostatistical methods. The core data set consists of pentadal (5-daily) accumulations from 1981-2013 at 0.05 degree spatial resolution between +/- 50 degrees latitude. Validation has been recently completed, and applications for gridded crop water balance calculations and mapping the Standardized Precipitation Index are in development. (2) Actual evapotranspiration (ETa) estimates using MODIS Land Surface Temperature (LST) data at 1-km have been successfully demonstrated using the operational Simplified Surface Energy Balance model with 8-day composites from the LPDAAC. A new, next-day latency implementation using daily LST swath data from the NASA LANCE server is in development for all the crop growing regions of the world. This ETa processing chain follows in the footsteps of (3) the expedited production of MODIS 250-meter NDVI images every five days at USGS EROS, likewise using LANCE daily swath data as input since 2010. Coverage includes Africa, Central Asia, the Middle East, Central America, and the Caribbean. (4) A surface water point monitoring

  17. [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.

  18. Agricultural Catchments: Evaluating Policies and Monitoring Adaptive Management

    NASA Astrophysics Data System (ADS)

    Jordan, P.; Shortle, G.; Mellander, P. E.; Shore, M.; McDonald, N.; Buckley, C.

    2014-12-01

    Agricultural management in river catchments must combine the objectives of economic profit and environmental stewardship and, in many countries, mitigate the decline of water quality and/or maintain high water quality. Achieving these objectives is, amongst other activities, in the remit of 'sustainable intensification'. Of concern is the efficient use of crop nutrients, phosphorus and nitrogen, and minimising or offsetting the effects of transfers from land to water - corner-stone requirements of many agri-environmental regulations. This requires a robust monitoring programme that can audit the stages of nutrient inputs and outputs in river catchments and indicate where the likely points of successful policy interventions can be observed - or confounded. In this paper, a catchment, or watershed, experimental design and results are described for monitoring the nutrient transfer continuum in the Irish agricultural landscape against the backdrop of the European Union Nitrates and Water Framework Directives. This Agricultural Catchments Programme experimental design also serves to indicate water quality pressure-points that may be catchment specific as agricultural activities intensify to adapt to national efforts to build important parts of the post-recession economy.

  19. Root-endophytes improve the ecophysiological performance and production of an agricultural species under drought condition.

    PubMed

    Molina-Montenegro, Marco A; Oses, Rómulo; Torres-Díaz, Cristian; Atala, Cristian; Zurita-Silva, Andrés; Ruiz-Lara, Simón

    2016-01-01

    Throughout many regions of the world, climate change has limited the availability of water for irrigating crops. Indeed, current models of climate change predict that arid and semi-arid zones will be places where precipitation will drastically decrease. In this context, plant root-associated fungi appear as a new strategy to improve ecophysiological performance and yield of crops under abiotic stress. Thus, use of fungal endophytes from ecosystems currently subjected to severe drought conditions could improve the ecophysiological performance and quantum yield of crops exposed to drought. In this study, we evaluated how the inoculation of fungal endophytes isolated from Antarctic plants can improve the net photosynthesis, water use efficiency and production of fresh biomass in a lettuce cultivar, grown under different water availability regimes. In addition, we assessed if the presence of biochemical mechanisms and gene expression related with environmental tolerance are improved in presence of fungal endophytes. Overall, those individuals with presence of endophytes showed higher net photosynthesis and maintained higher water use efficiency in drought conditions, which was correlated with greater fresh and dry biomass production as well as greater root system development. In addition, presence of fungal endophytes was correlated with a higher proline concentration, lower peroxidation of lipids and up-/down-regulation of ion homeostasis. Our results suggest that presence of fungal endophytes could minimize the negative effect of drought by improving drought tolerance through biochemical mechanisms and improving nutritional status. Thus, root-endophytes might be a successful biotechnological tool to maintain high levels of ecophysiological performance and productivity in zones under drought.

  20. Root-endophytes improve the ecophysiological performance and production of an agricultural species under drought condition

    PubMed Central

    Molina-Montenegro, Marco A.; Oses, Rómulo; Torres-Díaz, Cristian; Atala, Cristian; Zurita-Silva, Andrés; Ruiz-Lara, Simón

    2016-01-01

    Throughout many regions of the world, climate change has limited the availability of water for irrigating crops. Indeed, current models of climate change predict that arid and semi-arid zones will be places where precipitation will drastically decrease. In this context, plant root-associated fungi appear as a new strategy to improve ecophysiological performance and yield of crops under abiotic stress. Thus, use of fungal endophytes from ecosystems currently subjected to severe drought conditions could improve the ecophysiological performance and quantum yield of crops exposed to drought. In this study, we evaluated how the inoculation of fungal endophytes isolated from Antarctic plants can improve the net photosynthesis, water use efficiency and production of fresh biomass in a lettuce cultivar, grown under different water availability regimes. In addition, we assessed if the presence of biochemical mechanisms and gene expression related with environmental tolerance are improved in presence of fungal endophytes. Overall, those individuals with presence of endophytes showed higher net photosynthesis and maintained higher water use efficiency in drought conditions, which was correlated with greater fresh and dry biomass production as well as greater root system development. In addition, presence of fungal endophytes was correlated with a higher proline concentration, lower peroxidation of lipids and up-/down-regulation of ion homeostasis. Our results suggest that presence of fungal endophytes could minimize the negative effect of drought by improving drought tolerance through biochemical mechanisms and improving nutritional status. Thus, root-endophytes might be a successful biotechnological tool to maintain high levels of ecophysiological performance and productivity in zones under drought. PMID:27613875

  1. Keeping wetlands wet in the western United States: adaptations to drought in agriculture-dominated human-natural systems.

    PubMed

    Downard, Rebekah; Endter-Wada, Joanna

    2013-12-15

    Water is critical to protecting wetlands in arid regions, especially in agriculture-dominated watersheds. This comparative case study analyzes three federal wildlife refuges in the Bear River Basin of the U.S. West where refuge managers secured water supplies by adapting to their local environmental context and their refuge's relationship to agriculture in being either irrigation-dependent, reservoir-adjacent or diked-delta wetlands. We found that each refuge's position confers different opportunities for securing a water supply and entails unique management challenges linked to agricultural water uses. Acquiring contextually-appropriate water rights portfolios was important for protecting these arid region wetlands and was accomplished through various strategies. Once acquired, water is managed to buffer wetlands against fluctuations caused by a dynamic climate and agricultural demands, especially during droughts. Management plans are responsive to needs of neighboring water users and values of the public at large. Such context-specific adaptations will be critical as the West faces climate change and population growth that threaten wetlands and agricultural systems to which they are linked.

  2. Drought stress variability in ancient Near Eastern agricultural systems evidenced by δ13C in barley grain

    PubMed Central

    Riehl, Simone; Pustovoytov, Konstantin E.; Weippert, Heike; Klett, Stefan; Hole, Frank

    2014-01-01

    The collapse and resilience of political systems in the ancient Near East and their relationship with agricultural development have been of wide interest in archaeology and anthropology. Despite attempts to link the archaeological evidence to local paleoclimate data, the precise role of environmental conditions in ancient agricultural production remains poorly understood. Recently, stable isotope analysis has been used for reconstructing site-specific ancient growing conditions for crop species in semiarid and arid landscapes. To open the discussion of the role of regional diversity in past agricultural production as a factor in societal development, we present 1.037 new stable carbon isotope measurements from 33 archaeological sites and modern fields in the geographic area of the Fertile Crescent, spanning the Aceramic Neolithic [10,000 calibrated years (cal) B.C.] to the later Iron Age (500 cal B.C.), alongside modern data from 13 locations. Our data show that drought stress was an issue in many agricultural settlements in the ancient Near East, particularly in correlation with the major Holocene climatic fluctuations, but its regional impact was diverse and influenced by geographic factors. Although cereals growing in the coastal areas of the northern Levant were relatively unaffected by Holocene climatic fluctuations, farmers of regions further inland had to apply irrigation to cope with increased water stress. However, inland agricultural strategies showed a high degree of variability. Our findings suggest that regional differences in climatic effects led to diversified strategies in ancient subsistence and economy even within spatially limited cultural units. PMID:25114225

  3. Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus

    PubMed Central

    2011-01-01

    Background In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach. Results The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1 was present in 85% of the lines, followed by DTY4.1 in 79% and DTY1.1 in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL. Conclusions Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in

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

    NASA Technical Reports Server (NTRS)

    Lawford, Richard; Toll, David; Doorn, Bradley; Entin, Jared; Mocko, David; Svoboda, Mark; Rodell, Matthew; Koster, Randy; Schubert, Siegried; Liang, Xin-Zhong; Cai, Ximing; Wardlow, Brian; Xia, Youlong; Verdin, Jim; Ek, Michael

    2013-01-01

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

  5. When it Rains, It Pours: Drought, Excess Water, and Agricultural Risk Management in the U.S. Corn Belt

    NASA Astrophysics Data System (ADS)

    Baker, J. M.; Anderson, M. C.; Griffis, T. J.; Kustas, W.; Schultz, N. M.

    2012-12-01

    Ever since its inception agriculture has been a risky proposition, with yields subject to losses from insects, diseases, weeds, and weather anomalies. The transition from subsistence farming to production agriculture motivated research that eventually provided tools to combat some of the traditional sources of risk, particularly pests. However, weather-related risk remains resistant to mitigation, except in cases where there has been a fundamental alteration of lands otherwise unsuited for agriculture, e.g. - irrigation of arid lands and drainage of swamps. We have undertaken a multi-faceted analysis of potential avenues to reduce weather-related risk in the central U.S. corn belt, focusing on MN, IA, IL, IN, and OH. Mean annual precipitation has increased across the region over the past 60 years, and mean stream flows have increased as much or more, indicating relatively stable ET. The precipitation increase is consistent with changes predicted by GCMs for the region, while the stable (and even decreasing) regional ET primarily reflects changes in farming, particularly an increase in soybean acreage at the expense of permanent pasture. Unfortunately, the observed increases in precipitation are primarily associated with an increase in spatially and temporally isolated high intensity storms, so transient drought remains a problem. Indeed, analysis of crop insurance indemnities in recent years for the region reveals nearly equal yield losses due to drought and excess water, each totaling roughly $3 billion USD between 2000 and 2011, and jointly accounting for more than two thirds of all payments. County level mapping shows that losses from both causes occur throughout the corn belt, often in the same county in the same year. The ALEXI model, which provides continental-scale estimates of ET on a 10 km grid, was used to map ET anomalies across the region for the same time period. Correspondence between ALEXI output and insurance loss data was reasonably good in drought

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. Global Agricultural Monitoring (GLAM) using MODAPS and LANCE Data Products

    NASA Astrophysics Data System (ADS)

    Anyamba, A.; Pak, E. E.; Majedi, A. H.; Small, J. L.; Tucker, C. J.; Reynolds, C. A.; Pinzon, J. E.; Smith, M. M.

    2012-12-01

    The Global Inventory Modeling and Mapping Studies / Global Agricultural Monitoring (GIMMS GLAM) system is a web-based geographic application that offers Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and user interface tools to data query and plot MODIS NDVI time series. The system processes near real-time and science quality Terra and Aqua MODIS 8-day composited datasets. These datasets are derived from the MOD09 and MYD09 surface reflectance products which are generated and provided by NASA/GSFC Land and Atmosphere Near Real-time Capability for EOS (LANCE) and NASA/GSFC MODIS Adaptive Processing System (MODAPS). The GIMMS GLAM system is developed and provided by the NASA/GSFC GIMMS group for the U.S. Department of Agriculture / Foreign Agricultural Service / International Production Assessment Division (USDA/FAS/IPAD) Global Agricultural Monitoring project (GLAM). The USDA/FAS/IPAD mission is to provide objective, timely, and regular assessment of the global agricultural production outlook and conditions affecting global food security. This system was developed to improve USDA/FAS/IPAD capabilities for making operational quantitative estimates for crop production and yield estimates based on satellite-derived data. The GIMMS GLAM system offers 1) web map imagery including Terra & Aqua MODIS 8-day composited NDVI, NDVI percent anomaly, and SWIR-NIR-Red band combinations, 2) web map overlays including administrative and 0.25 degree Land Information System (LIS) shape boundaries, and crop land cover masks, and 3) user interface tools to select features, data query, plot, and download MODIS NDVI time series.

  8. Economic impacts on irrigated agriculture of water conservation programs in drought

    NASA Astrophysics Data System (ADS)

    Ward, Frank A.

    2014-01-01

    This study analyzes vulnerability, impacts, and adaptability by irrigation to drought.It accounts for economic incentives affecting choices on irrigation technology, crop mix, and water sources.When surface water supplies fall, farmers increase pumping, even when pumping raises production costs.Conservation program subsidies raise the value of food production but can increase crop water depletions.

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  10. 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

  11. 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.

  12. Potentials of polarimetric SAR interferometry for agriculture monitoring

    NASA Astrophysics Data System (ADS)

    Lopez-Sanchez, Juan M.; Ballester-Berman, J. David

    2009-04-01

    This paper is aimed to define the main specifications and system requirements of a future spaceborne synthetic aperture radar (SAR) mission with polarimetric and interferometric capabilities, to be applied in agriculture monitoring. Firstly, a previous discussion concerning the applications of remote sensing to agriculture and the requirements demanded by end users is introduced. Then, a review of polarimetric SAR and interferometric SAR techniques employed in agriculture is performed in order to explore and justify the potential contributions to crop parameter retrieval of polarimetric SAR interferometry (PolInSAR). The current status of the research about PolInSAR when applied to the retrieval of biophysical parameters of agricultural crops is also addressed, covering recent advances in theoretical modeling aspects (both direct and inverse models), the validation carried out so far with indoor data, and complementary information provided by other different but related experiments. From this experience, we describe some system specifications that will be important for the success of this technique. Among them it is emphasized the need of baselines larger than usual, medium-high frequency band, and a mandatory single-pass mode for overcoming temporal decorrelation. Finally, a set of future experiments is also proposed for additional testing and confirmation of observations made so far regarding minimum baseline requirements, temporal evolution of observables and modeling issues, among others.

  13. Backscattering characteristics Analyses of winter wheat covered area and Drought Monitoring Based on active microwave

    NASA Astrophysics Data System (ADS)

    Zhang, C., Sr.; Li, L.

    2015-12-01

    The advantage of active microwave remote sensing on the sensitivity of polarization characteristic, backscatter intensity and phase characteristics to soil moisture demonstrates its potential to map and monitor relative soil moisture changes and drought information with high spatial resolution. However, the existence of soil surface condition and vegetation effects confounds the retrieval of soil moisture from active microwave, and therefore limits its applications on soil moisture retrieval and drought monitoring. To research how to reduce the effect of soil roughness and wheat cover with multi- incident angles and multi polarization active microwave remote sensing data, MIMICS and AIEM models were used to simulate the backscattering coefficient of winter wheat covered field. The interaction between winter wheat at main growth stages and microwave was analyzed. The effects of surface roughness and physical parameters of wheat on the backscattering characteristics and the variation of different incident angles and different polarization conditions are simulated and analyzed emphatically. Then scattering coefficient information of winter wheat covered area at different wheat growth stage was measured with a C band ground-based scattering meter. At the same time, biomass, leaf area index and soil rough degree, soil water content and other related parameters are collected. After comparing and analyzing the measured data and the simulated data at different incident angles and different polarization modes, we propose an approach of using multi polarization and multi angle data to eliminate the soil roughness and wheat vegetation effects and performing the inversion of soil moisture. Using the Radarsat2 satellite SAR data and ground-based scatter data gotten at the same period in 2012, soil moisture information of greater area is obtained, and then the drought information is obtained, which is consistent with the measured results.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. WEBGIS based CropWatch online agriculture monitoring system

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Wu, B.; Zeng, H.; Zhang, M.; Yan, N.

    2015-12-01

    CropWatch, which was developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), has achieved breakthrough results in the integration of methods, independence of the assessments and support to emergency response by periodically releasing global agricultural information. Taking advantages of the multi-source remote sensing data and the openness of the data sharing policies, CropWatch group reported their monitoring results by publishing four bulletins one year. In order to better analysis and generate the bulletin and provide an alternative way to access agricultural monitoring indicators and results in CropWatch, The CropWatch online system based on the WEBGIS techniques has been developed. Figure 1 shows the CropWatch online system structure and the system UI in Clustering mode. Data visualization is sorted into three different modes: Vector mode, Raster mode and Clustering mode. Vector mode provides the statistic value for all the indicators over each monitoring units which allows users to compare current situation with historical values (average, maximum, etc.). Users can compare the profiles of each indicator over the current growing season with the historical data in a chart by selecting the region of interest (ROI). Raster mode provides pixel based anomaly of CropWatch indicators globally. In this mode, users are able to zoom in to the regions where the notable anomaly was identified from statistic values in vector mode. Data from remote sensing image series at high temporal and low spatial resolution provide key information in agriculture monitoring. Clustering mode provides integrated information on different classes in maps, the corresponding profiles for each class and the percentage of area of each class to the total area of all classes. The time series data is categorized into limited types by the ISODATA algorithm. For each clustering type, pixels on the map, profiles, and percentage legend are all linked

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. Analysis of Maize versus Ethanol Production in Nebraska, United States and International Agricultural Droughts: Lessons for Global Food Security

    NASA Astrophysics Data System (ADS)

    Boken, V.; Tenkorang, F.

    2012-04-01

    Nebraska is one of the eight main corn (maize) belt states of the United States. Maize is the major crop of Nebraska with an average annual production of about 38 million tons (about 12% of U.S. production), which contributes billions of dollars to the state's economy. The yield of maize has increased significantly over the past century - from 1.6 t/ha in 1900 to 10.4 t/ha in 2010. While the majority of maize (about 40%) is currently used for animal feed and ethanol production, only about six percent is exported. It is estimated that about one billion people accounting for about 15% population of the world live in chronic hunger because of low agricultural productivity and drought. Most of these people depend on the U.S. for grains including maize. If a greater quantity of maize is diverted to ethanol production, considerably less quantity of maize would be available for export to developing countries where it could be used for human consumption and to mitigate hunger and improve food security. This paper presents analysis of maize production in Nebraska for the past three decades and examines how its commercialization for ethanol production has affected its exports in the face of drought at an international level.

  18. Development of a remotely sensing seasonal vegetation-based Palmer Drought Severity Index and its application of global drought monitoring over 1982-2011

    NASA Astrophysics Data System (ADS)

    Yan, Hao; Wang, Shao-Qiang; Lu, Hou-Quan; Yu, Qin; Zhu, Zai-Chun; Myneni, Ranga B.; Liu, Qiang; Shugart, Herman H.

    2014-08-01

    Vegetation effects are currently disregarded in Palmer Drought Severity Index (PDSI), and the sensitivity of PDSI to the choice of potential evaporation (EP) parameterization is often a concern. We developed a revised self-calibrating PDSI model that replaces EP with leaf area index-based total evapotranspiration (ARTS E0). It also included a simple snowmelt module. Using a unique satellite leaf area index data set and climate data, we calculated and compared ARTS E0, three other types of EP (i.e., Thornthwaite EP_Th, Allen EP_Al, and Penman-Monteith EP_PM), and corresponding PDSI values (i.e., PDSI_ARTS, PDSI_Th, PDSI_Al, and PDSI_PM) for the period 1982-2011. The results of PDSI_ARTS, PDSI_Al, and PDSI_PM show that global land became wetter mainly due to increased precipitation and El Niño-Southern Oscillation (ENSO) effect for the period, which confirms the ongoing intensification of global hydrologic cycle with global temperature increase. However, only PDSI_Th gave a trend of global drying, which confirms that PDSI_Th overestimates the global drying in response to global warming; i.e., PDSI values are sensitive to the parameterizations for Ep. Thus, ARTS E0, EP_Al, and EP_PM are preferred to EP_Th in global drought monitoring. In short, global warming affects global drought condition in two opposite ways. One is to contribute to the increases of EP and hence drought; the other is to increase global precipitation that contributes to global wetting. These results suggest that precipitation trend and its interaction with global warming and ENSO should be given much attention to correctly quantify past and future trends of drought.

  19. Very-Heavy Precipitation in the Greater New York City Region and Widespread Drought Alleviation Tied to Western US Agriculture.

    PubMed

    Andrews, Travis D; Felzer, Benjamin S

    2015-01-01

    Observed intensification of precipitation extremes, responsible for extensive societal impacts, are widely attributed to anthropogenic sources, which may include indirect effects of agricultural irrigation. However quantifying the effects of irrigation on far-downstream climate remains a challenge. We use three paired Community Earth System Model simulations to assess mechanisms of irrigation-induced precipitation trends and extremes in the conterminous US and the effect on the terrestrial carbon sink. Results suggest precipitation enhancement in the central US reduced drought conditions and increased regional carbon uptake, while further downstream, the heaviest precipitation events were more frequent and intense. Specifically, moisture advection from irrigation in the western U.S. and recycling of enhanced local convective precipitation produced very-heavy storm events that were 11% more intense and occurred 23% more frequently in the densely populated greater New York City region.

  20. Very-Heavy Precipitation in the Greater New York City Region and Widespread Drought Alleviation Tied to Western US Agriculture

    PubMed Central

    Andrews, Travis D.; Felzer, Benjamin S.

    2015-01-01

    Observed intensification of precipitation extremes, responsible for extensive societal impacts, are widely attributed to anthropogenic sources, which may include indirect effects of agricultural irrigation. However quantifying the effects of irrigation on far-downstream climate remains a challenge. We use three paired Community Earth System Model simulations to assess mechanisms of irrigation-induced precipitation trends and extremes in the conterminous US and the effect on the terrestrial carbon sink. Results suggest precipitation enhancement in the central US reduced drought conditions and increased regional carbon uptake, while further downstream, the heaviest precipitation events were more frequent and intense. Specifically, moisture advection from irrigation in the western U.S. and recycling of enhanced local convective precipitation produced very-heavy storm events that were 11% more intense and occurred 23% more frequently in the densely populated greater New York City region. PMID:26642049

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  2. Agricultural Drought Assessment In Latin America Based On A Standardized Soil Moisture Index

    NASA Astrophysics Data System (ADS)

    Carrao, Hugo; Russo, Simone; Sepulcre, Guadalupe; Barbosa, Paulo

    2013-12-01

    We propose a relatively simple, spatially invariant and probabilistic year-round Standardized Soil Moisture Index (SSMI) that is designed to estimate drought conditions from satellite imagery data. The SSMI is based on soil moisture content alone and is defined as the number of standard deviations that the observed moisture at a given location and timescale deviates from the long- term normal conditions. Specifically, the SSMI is computed by fitting a non-parametric probability distribution function to historical soil moisture records and then trans- forming it into a normal distribution with a mean of zero and standard deviation of one. Negative standard normal values indicate dry conditions and positive values indicate wet conditions. To evaluate the applicability of the SSMI, we fitted empirical and normal cumulative distribution functions (ECDF and nCDF) to 32-years of averaged soil moisture amounts derived from the Essential Climate Variable (ECV) Soil Moisture (SM) dataset, and compared the root-mean-squared errors of residuals. SM climatology was calculated on a 0.25° grid over Latin America at timescales of 1, 3, 6, and 12 months for the long-term period of 1979-2010. Results show that the ECDF fits better the soil moisture data than the nCDF at all timescales and that the negative SSMI values computed with the non-parametric estimator accurately identified the temporal and geographic distribution of major drought events that occurred in the study area.

  3. Impacts of Shallow Groundwater and Soil Texture on Agricultural Drought Resistance

    NASA Astrophysics Data System (ADS)

    Zipper, S. C.; Soylu, M. E.; Booth, E.; Steven, L. I.

    2015-12-01

    Meeting increasing global food demands while fostering environmental sustainability requires a detailed understanding of the drivers of yield sensitivity within agroecosystems. In this study, we untangle the roles of soil texture and shallow groundwater as simultaneous drivers of corn yield resistance to excessively wet and dry growing seasons. Specifically, we ask (1) does the presence of groundwater in or near the root zone increase/decrease yield?; and (2) how does yield response to water table depth interact with variability in soil texture and growing season weather conditions? We combine a multi-year field study at a commercial corn field in south-central Wisconsin with ecohydrological modeling using AgroIBIS-VSF to assess the yield response to a broad spectrum of groundwater, soil, and weather conditions. We find that shallow groundwater (<1 m) increases yield sensitivity to overly wet growing season conditions, but acts as a stable reservoir of water to increase drought resistance by providing a groundwater yield subsidy during dry years. Modeling results indicate that coarser soils receive a groundwater yield subsidy at shallower water table depths than finer-grained soils, and that the magnitude of the groundwater yield subsidy tends to be larger. We also find that crops growing on soils with different textures experience a comparable response to changes in growing season precipitation and evapotranspiration demands. Overall, we find that the benefits of shallow groundwater (drought resistance) outweigh the negatives (waterlogging and yield loss) at our study site.

  4. Development and testing of crop monitoring methods to improve global agricultural monitoring in support of GEOGLAM

    NASA Astrophysics Data System (ADS)

    Gilliams, S. J. B.; Bydekerke, L.

    2014-12-01

    The SIGMA project (Stimulating Innovation for Global Monitoring of Agriculture) is funded through the EC FPY7 Research programme with the particular aim to contribute to the GEOGLAM Research Agenda. It is a partnership of globally distributed expert organizations, focusses on developing innovative techniques and datasets in support of agricultural monitoring and its impact on the environment in support of GEOGLAM. SIGMA has 3 generic objectives which are: (i) develop and test methods to characterize cropland and assess its changes at various scales; (ii) develop and test methods to assess changes in agricultural production levels; and; (iii) study environmental impacts of agriculture. Firstly, multi-scale remote sensing data sets, in combination with field and other ancillary data, are used to generate an improved (global) agro-ecological zoning map and crop mask. Secondly, a combination of agro-meteorological models, satellite-based information and long-term time series are be explored to better assess crop yield gaps and shifts in cultivation. The third research topic entails the development of best practices for assessing the impact of crop land and cropping system change on the environment. In support of the GEO JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative, case studies in Ukraine, Russia, Europe, Africa, Latin America and China are carried out in order to explore possible methodological synergies and particularities according to different cropping systems. This presentation will report on the progress made with respect to the three topics above.

  5. 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

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The Navajo Nation, located in the southwestern United States, has been increasingly impacted by severe drought events and regional changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring climate and drought are dependent on national-scale monthly drought maps calculated by the Western Regional Climate Center (WRCC). These maps do not provide the spatial resolution needed to examine differences in drought severity across the vast Nation. To better understand and monitor drought regime changes in the Navajo Nation, this project comprises of two main components: 1) a geodatabase of historical climate information necessary to calculate Standardized Precipitation Index (SPI) values and 2) a tool that calculates SPI values for a user-selected area within the study site. The tool and geodatabase use TRMM and GPM observed precipitation data, and Parameter-elevation Relationships on Independent Slopes Model (PRISM) modeled historical precipitation data. These products allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

  8. GEOGLAM Crop Assessment Tool: Adapting from global agricultural monitoring to food security monitoring

    NASA Astrophysics Data System (ADS)

    Humber, M. L.; Becker-Reshef, I.; Nordling, J.; Barker, B.; McGaughey, K.

    2014-12-01

    The GEOGLAM Crop Monitor's Crop Assessment Tool was released in August 2013 in support of the GEOGLAM Crop Monitor's objective to develop transparent, timely crop condition assessments in primary agricultural production areas, highlighting potential hotspots of stress/bumper crops. The Crop Assessment Tool allows users to view satellite derived products, best available crop masks, and crop calendars (created in collaboration with GEOGLAM Crop Monitor partners), then in turn submit crop assessment entries detailing the crop's condition, drivers, impacts, trends, and other information. Although the Crop Assessment Tool was originally intended to collect data on major crop production at the global scale, the types of data collected are also relevant to the food security and rangelands monitoring communities. In line with the GEOGLAM Countries at Risk philosophy of "foster[ing] the coordination of product delivery and capacity building efforts for national and regional organizations, and the development of harmonized methods and tools", a modified version of the Crop Assessment Tool is being developed for the USAID Famine Early Warning Systems Network (FEWS NET). As a member of the Countries at Risk component of GEOGLAM, FEWS NET provides agricultural monitoring, timely food security assessments, and early warnings of potential significant food shortages focusing specifically on countries at risk of food security emergencies. While the FEWS NET adaptation of the Crop Assessment Tool focuses on crop production in the context of food security rather than large scale production, the data collected is nearly identical to the data collected by the Crop Monitor. If combined, the countries monitored by FEWS NET and GEOGLAM Crop Monitor would encompass over 90 countries representing the most important regions for crop production and food security.

  9. The Joint Experiment for Crop Assessment and Monitoring (JECAM) Initiative: Developing methods and best practices for global agricultural monitoring

    NASA Astrophysics Data System (ADS)

    Champagne, C.; Jarvis, I.; Defourny, P.; Davidson, A.

    2014-12-01

    Agricultural systems differ significantly throughout the world, making a 'one size fits all' approach to remote sensing and monitoring of agricultural landscapes problematic. The Joint Experiment for Crop Assessment and Monitoring (JECAM) was established in 2009 to bring together the global scientific community to work towards a set of best practices and recommendations for using earth observation data to map, monitor and report on agricultural productivity globally across an array of diverse agricultural systems. These methods form the research and development component of the Group on Earth Observation Global Agricultural Monitoring (GEOGLAM) initiative to harmonize global monitoring efforts and increase market transparency. The JECAM initiative brings together researchers from a large number of globally distributed, well monitored agricultural test sites that cover a range of crop types, cropping systems and climate regimes. Each test site works independently as well as together across multiple sites to test methods, sensors and field data collection techniques to derive key agricultural parameters, including crop type, crop condition, crop yield and soil moisture. The outcome of this project will be a set of best practices that cover the range of remote sensing monitoring and reporting needs, including satellite data acquisition, pre-processing techniques, information retrieval and ground data validation. These outcomes provide the research and development foundation for GEOGLAM and will help to inform the development of the GEOGLAM "system of systems" for global agricultural monitoring. The outcomes of the 2014 JECAM science meeting will be discussed as well as examples of methods being developed by JECAM scientists.

  10. Agricultural intensification and drought frequency increases may have landscape-level consequences for ephemeral ecosystems.

    PubMed

    Dalu, Tatenda; Wasserman, Ryan J; Dalu, Mwazvita T B

    2017-03-01

    Ephemeral wetlands in arid regions are often degraded or destroyed through poor land-use practice long before they are ever studied or prioritized for conservation. Climate change will likely also have implications for these ecosystems given forecast changes in rainfall patterns in many arid environments. Here, we present a conceptual diagram showing typical and modified ephemeral wetlands in agricultural landscapes and how modification impacts on species diversity and composition.

  11. Development of a Demand Sensitive Drought Index and its application for agriculture over the conterminous United States

    NASA Astrophysics Data System (ADS)

    Etienne, Elius; Devineni, Naresh; Khanbilvardi, Reza; Lall, Upmanu

    2016-03-01

    A new drought index is introduced that explicitly considers both water supply and demand. It can be applied to aggregate demand over a geographical region, or for disaggregated demand related to a specific crop or use. Consequently, it is more directly related than existing indices, to potential drought impacts on different segments of society, and is also suitable to use as an index for drought insurance programs targeted at farmers growing specific crops. An application of the index is presented for the drought characterization at the county level for the aggregate demand of eight major field crops in the conterminous United States. Two resiliency metrics are developed and applied with the drought index time series. In addition, a clustering algorithm is applied to the onset times and severity of the worst historical droughts in each county, to identify the spatial structure of drought, relative to the cropping patterns in each county. The geographic relationship of drought severity, drought recovery relative to duration, and resilience to drought is identified, and related to attributes of precipitation and also cropping intensity, thus distinguishing the relative importance of water supply and demand in determining potential drought outcomes.

  12. Development of a Demand Sensitive Drought Index and its Application for Agriculture over the Conterminous United States.

    NASA Astrophysics Data System (ADS)

    Etienne, E.; Devineni, N.; Khanbilvardi, R.; Lall, U.

    2015-12-01

    A new drought index is introduced that explicitly considers both water supply and demand. It can be applied to aggregate demand over a geographical region, or for disaggregated demand related to a specific crop or use. Consequently, it is more directly related than existing indices, to potential drought impacts on different segments of society, and is also suitable to use as an index for drought insurance programs targeted at farmers growing specific crops. An application of the index is presented for the drought characterization at the county level for the aggregate demand of eight major field crops in the conterminous United States. Two resiliency metrics are developed and applied with the drought index time series. In addition, a clustering algorithm is applied to the onset times and severity of the worst historical droughts in each county, to identify the spatial structure of drought, relative to the cropping patterns in each county. The geographic relationship of drought severity, drought recovery relative to duration, and resilience to drought is identified, and related to attributes of precipitation and also cropping intensity, thus distinguishing the relative importance of water supply and demand in determining potential drought outcomes.

  13. 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.

  14. 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. 

  15. Value of Available Global Soil Moisture Products for Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

    2016-04-01

    The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS

  16. A combined deficit index for regional agricultural drought assessment over semi-arid tract of India using geostationary meteorological satellite data

    NASA Astrophysics Data System (ADS)

    Vyas, Swapnil S.; Bhattacharya, Bimal K.; Nigam, Rahul; Guhathakurta, Pulak; Ghosh, Kripan; Chattopadhyay, N.; Gairola, R. M.

    2015-07-01

    The untimely onset and uneven distribution of south-west monsoon rainfall lead to agricultural drought causing reduction in food-grain production with high vulnerability over semi-arid tract (SAT) of India. A combined deficit index (CDI) has been developed from tri-monthly sum of deficit in antecedent rainfall and deficit in monthly vegetation vigor with a lag period of one month between the two. The formulation of CDI used a core biophysical (e.g., NDVI) and a hydro-meteorological (e.g., rainfall) variables derived using observation from Indian geostationary satellites. The CDI was tested and evaluated in two drought years (2009 and 2012) within a span of five years (2009-2013) over SAT. The index was found to have good correlation (0.49-0.68) with standardized precipitation index (SPI) computed from rain-gauge measurements but showed lower correlation with anomaly in monthly land surface temperature (LST). Significant correlations were found between CDI and reduction in agricultural carbon productivity (0.67-0.83), evapotranspiration (0.64-0.73), agricultural grain yield (0.70-0.85). Inconsistent correlation between CDI and ET reduction was noticed in 2012 in contrast to consistent correlation between CDI and reduction in carbon productivity both in 2009 and 2012. The comparison of CDI-based drought-affected area with those from existing operational approach showed 75% overlapping regions though class-to-class matching was only 40-45%. The results demonstrated that CDI is a potential indicator for assessment of late-season regional agricultural drought based on lag-response between water supply and crop vigor.

  17. 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.

  18. Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

    PubMed

    Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

    2010-01-01

    This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

  19. Forest productivity and drought in tropical Africa: observations from the Global Ozone Monitoring Experiment-2

    NASA Astrophysics Data System (ADS)

    Robinson, E. S.; Lee, J. E.; Yang, X.

    2014-12-01

    The impact of seasonal water stress on Africa's tropical regions has yet to be characterized despite drought's potential to cause famine and a reduction of biodiversity across the continent. Through the analysis of a new data set of sun-induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment-2, we demonstrate that fluorescence varies with water availability, particularly over regions with distinctive wet and dry seasons. Water availability was determined via both precipitation (from the Global Precipitation Climatology Project) and daytime canopy water content measurements (from the SeaWinds Scatterometer onboard the QuickSCAT satellite). Variance in SIF values was largely explained by both canopy water content and precipitation, which paralleled one-another. When viewed in the context of the previously defined relationship between fluorescence and gross primary production (GPP) - SIF scales linearly with GPP - our results suggest that photosynthetic activity in tropical Africa is limited by water availability. The characterization of this trend is critical in defining the response of tropical ecosystems to water stress and corroborating similar relationships in other tropical regions (e.g. Amazonia). Ultimately, the viability of Africa's tropical regions amidst a changing climate is rooted in its ecosystem-wide response to water stress; the future of the African tropics is limited by how well plants cope with water stress.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  2. [Planning of monitoring points for agricultural products security based on integrated weighted clustering method].

    PubMed

    Yan, Hui-Chao; Chen, Lian-Cheng; Wang, Lu; Li, Qing; Xue, Yue-Ju; Du, Guo-Ming

    2009-08-01

    Integrated weighted clustering method was applied to plan the monitoring points for agricultural products security. Definite amounts of key monitoring sampling points were mined out from enormous monitoring objects to make the fewer monitoring sampling points cover the product categories, yields, and regions as more as possible. Among the 10172 agricultural products security enterprises all over the China, 2.46% of them were selected. The tested categories, yields, and regions of agricultural safety products covered 32.71%, 44.29%, and 75% of the total, and their coverage increased by 2.80%, 10.85%, 5.56%, respectively, compared with that by using conventional monitoring and management methods, which suggested that it could be more effective to apply integrated weighted clustering method in setting the monitoring points for agricultural products security.

  3. Response to droughts and heat waves of the productivity of natural and agricultural ecosystems in Europe within ISI-MIP2 historical simulations

    NASA Astrophysics Data System (ADS)

    François, Louis; Henrot, Alexandra-Jane; Dury, Marie; Jacquemin, Ingrid; Munhoven, Guy; Friend, Andrew; Rademacher, Tim T.; Hacket Pain, Andrew J.; Hickler, Thomas; Tian, Hanqin; Morfopoulos, Catherine; Ostberg, Sebastian; Chang, Jinfeng; Rafique, Rashid; Nishina, Kazuya

    2016-04-01

    According to the projections of climate models, extreme events such as droughts and heat waves are expected to become more frequent and more severe in the future. Such events are known to severely impact the productivity of both natural and agricultural ecosystems, and hence to affect ecosystem services such as crop yield and ecosystem carbon sequestration potential. Dynamic vegetation models are conventional tools to evaluate the productivity and carbon sequestration of ecosystems and their response to climate change. However, how far are these models able to correctly represent the sensitivity of ecosystems to droughts and heat waves? How do the responses of natural and agricultural ecosystems compare to each other, in terms of drought-induced changes in productivity and carbon sequestration? In this contribution, we use ISI-MIP2 model historical simulations from the biome sector to tentatively answer these questions. Nine dynamic vegetation models have participated in the biome sector intercomparison of ISI-MIP2: CARAIB, DLEM, HYBRID, JULES, LPJ-GUESS, LPJml, ORCHIDEE, VEGAS and VISIT. We focus the analysis on well-marked droughts or heat waves that occured in Europe after 1970, such as the 1976, 2003 and 2010 events. For most recent studied events, the model results are compared to the response observed at several eddy covariance sites in Europe, and, at a larger scale, to the changes in crop productivities reported in national statistics or to the drought impacts on gross primary productivity derived from satellite data (Terra MODIS instrument). The sensitivity of the models to the climatological dataset used in the simulations, as well as to the inclusion or not of anthropogenic land use, is also analysed within the studied events. Indeed, the ISI-MIP simulations have been run with four different historical climatic forcings, as well as for several land use/land cover configurations (natural vegetation, fixed land use and variable land use).

  4. 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

  5. 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

  6. 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

  7. Balancing-out floods and droughts: Opportunities to utilize floodwater harvesting and groundwater storage for agricultural development in Thailand

    NASA Astrophysics Data System (ADS)

    Pavelic, Paul; Srisuk, Kriengsak; Saraphirom, Phayom; Nadee, Suwanchai; Pholkern, Kewaree; Chusanathas, Sumrit; Munyou, Sitisak; Tangsutthinon, Theerasak; Intarasut, Teerawash; Smakhtin, Vladimir

    2012-11-01

    SummaryThailand's naturally high seasonal endowment of water resources brings with it the regularly experienced problems associated with floods during the wet season and droughts during the dry season. Downstream-focused engineering solutions that address flooding are vital, but do not necessarily capture the potential for basin-scale improvements to water security, food production and livelihood enhancement. Managed aquifer recharge, typically applied to annual harvesting of wet season flows in dry climates, can also be applied to capture, store and recover episodic extreme flood events in humid environments. In the Chao Phraya River Basin it is estimated that surplus flows recorded downstream above a critical threshold could be harvested and recharged within the shallow alluvial aquifers in a distributed manner upstream of flood prone areas without significantly impacting existing large-medium storages or the Gulf and deltaic ecosystems. Capturing peak flows approximately 1 year in four by dedicating around 200 km2 of land to groundwater recharge would reduce the magnitude of flooding and socio-economic impacts and generate around USD 250 M/year in export earnings for smallholder rainfed farmers through dry season cash cropping without unduly compromising the demands of existing water users. It is proposed that farmers in upstream riparian zones be co-opted as flood harvesters and thus contribute to improved floodwater management through simple water management technologies that enable agricultural lands to be put to higher productive use. Local-scale site suitability and technical performance assessments along with revised governance structures would be required. It is expected that such an approach would also be applicable to other coastal-discharging basins in Thailand and potentially throughout the Asia region.

  8. Monitoring-based analysis of agriculture in Iraq

    NASA Astrophysics Data System (ADS)

    Tokareva, O.; Pasko, O.; Alshaibi, A.; Mochalov, M.

    2016-09-01

    The paper deals with change in area and structure of Iraq agricultural lands. It revealed the main reasons for the change: crisis (war, sanctions, etc.); economic (swamp and lake drainage, melioration, etc.); weather condition. Land-use intensification as a reason for reduction of agricultural land areas was not proved. The area of cultivated lands proved to correlate significantly with the level of precipitation, wheat productivity -with the average temperature in Iraq.

  9. Comparison between remote-sensing-based drought indices in East Java

    NASA Astrophysics Data System (ADS)

    Febrina Amalo, Luisa; Hidayat, Rahmat; Haris

    2017-01-01

    Drought is natural hazard which has causing several impacts, such as decreasing of air and water quality, land degradation, forest fire, decreasing of agricultural crops production. Drought assessment using drought indices have widely conducted for drought monitoring. Remote-sensing-based indices defined as an index which using remote sensing data for mapping the drought condition in particular area or region. This research aims to compare remote-sensing-based drought indices, namely TCI, VCI and VHI to obtain a better understanding about the differentiation between each index, and their application for monitoring drought in East Java on El Nino year 2015. LST and EVI data were used to construct the indices. The result showed, each index proved to be useful, quick, sufficient and inexpensive tool for drought monitoring. However, each index has its differences. TCI proved to be detected drought sensitively in dry season or months when high temperature occurred. While VCI detected drought more sensitive in wet season as well (December-January-February to May) than TCI and VHI. Meanwhile, VHI which the enhancement of TCI and VHI has combined two indicators to provide better comprehension about drought occurrence.

  10. The Solutions of the Agricultural Land Use Monitoring Problems

    ERIC Educational Resources Information Center

    Vershinin, Valentin V.; Murasheva, Alla A.; Shirokova, Vera A.; Khutorova, Alla O.; Shapovalov, Dmitriy A.; Tarbaev, Vladimir A.

    2016-01-01

    Modern landscape--it's a holistic system of interconnected and interacting components. To questions of primary importance belongs evaluation of stability of modern landscape (including agrarian) and its optimization. As a main complex characteristic and landscape inhomogeneity in a process of agricultural usage serves materials of quantitative and…

  11. New and Improved Remotely Sensed Products and Tools for Agricultural Monitoring Applications in Support of Famine Early Warning

    NASA Astrophysics Data System (ADS)

    Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Pedreros, D.; Husak, G. J.; Bohms, S.

    2011-12-01

    The high global food prices in 2008 led to the acknowledgement that there is a need to monitor the inter-connectivity of global and regional markets and their potential impacts on food security in many more regions than previously considered. The crisis prompted an expansion of monitoring by the Famine Early Warning Systems Network (FEWS NET) to include additional countries, beyond those where food security has long been of concern. Scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the University of California Santa Barbara Climate Hazards Group have provided new and improved data products as well as visualization and analysis tools in support of this increased mandate for remote monitoring. We present a new product for measuring actual evapotranspiration (ETa) based on the implementation of a surface energy balance model and site improvements of two standard FEWS NET monitoring products: normalized difference vegetation index (NDVI) and satellite-based rainfall estimates. USGS FEWS NET has implemented a simplified surface energy balance model to produce operational ETa anomalies for Africa. During the growing season, ETa anomalies express surplus or deficit crop water use which is directly related to crop condition and biomass. The expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) production system provides FEWS NET with a much improved NDVI dataset for crop and rangeland monitoring. eMODIS NDVI provides a reliable data stream with a vastly improved spatial resolution (250-m) and short latency period (less than 12 hours) which allows for better operational vegetation monitoring. FEWS NET uses satellite rainfall estimates as inputs for monitoring agricultural food production. By combining high resolution (0.05 deg) rainfall mean fields with Tropical Rainfall Measuring Mission rainfall estimates and infrared temperature data, we provide pentadal (5-day) rainfall fields suitable for crop

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    USGS Publications Warehouse

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

    2016-01-01

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

  14. Monitoring agricultural water use, water productivity and drought using multi-platform satellite data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To meet the food supply needs of the world’s growing population, global food production will need to roughly double by 2050. This increased production must be accomplished within the constraints of a non-uniform distribution of freshwater resources, an amplifying climate cycle, and concern for env...

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

    NASA Astrophysics Data System (ADS)

    Coates, Austin Reece

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

  16. Satellite-based drought monitoring in Kenya in an operational setting

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    AghaKouchak, Amir

    2015-04-01

    Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness, management, and response decision making. This presentation provides an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using both remote sensing observations and model simulations. Designed as a cyberinfrastructure system, GIDMaPS provides drought information based on a wide range of model simulations and satellite observations from different space agencies. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts, and better management and distribution of water resources among and across different users. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is designed to provide drought information for water resource management, and short-term decision making. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The presentation will highlight how this drought cyberinfrastructure system can be used to improve water

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

    NASA Technical Reports Server (NTRS)

    White, Kristopher D.; Case, Jonathan L.

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2014-01-01

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

  2. Agricultural pest monitoring using fluorescence lidar techniques. Feasibility study

    NASA Astrophysics Data System (ADS)

    Mei, L.; Guan, Z. G.; Zhou, H. J.; Lv, J.; Zhu, Z. R.; Cheng, J. A.; Chen, F. J.; Löfstedt, C.; Svanberg, S.; Somesfalean, G.

    2012-03-01

    The fluorescence of different types of planthopper ( Hemiptera) and moth ( Lepidoptera), which constitute important Chinese agricultural pests, was investigated both in situ in a laboratory setting and remotely using a fluorescence light detection and ranging (lidar) system operating at a range of about 50 m. The natural autofluorescence of different species, as well as the fluorescence from insects that had been dusted with fluorescent dye powder for identification were studied. Autofluorescence spectra of both moths and planthoppers show a maximum intensity peak around 450 nm. Bleaching upon long-time laser illumination was modest and did not affect the shape of the spectrum. A single dyed rice planthopper, a few mm in size, could be detected at 50 m distance by using the fluorescence lidar system. By employing various marking dyes, different types of agricultural pest could be determined. We suggest that lidar may be used in studies of migration and movement of pest insects, including studies of their behavior in the vicinity of pheromone traps and in pheromone-treated fields.

  3. A drought index designed for field-scale water management

    NASA Astrophysics Data System (ADS)

    Kim, Dae-Jun; Kim, Soo-Ock; Kim, Jin-Hee; Shim, Kyo-Moon; Yun, Jin I.

    2015-08-01

    A drought index with respect to the spatio-temporal scale was developed in response to the demand from the agricultural sector in South Korea. The new drought index was calculated based on the soil water balance between the supply and demand of water. The water supply was estimated using the cumulative effective precipitation weighted by the precipitation from two months prior. The water demand was derived from the actual evapotranspiration, which was calculated by applying a crop coefficient to the reference evapotranspiration. The amount of surface runoff on a given soil type was used to calculate the residual soil moisture. The presence of drought was determined based on the probability distribution in the given area. In order to assess the reliability of this index, termed the Agricultural Drought Index (ADI), the amount of residual moisture, which represents the severity of a drought, was compared to the measurements of soil moisture at three experimental sites between July 2012 and December 2013. The results showed that the ADI had greater correlation with measured soil moisture than did the Standardized Precipitation Index (SPI), suggesting that the ADI is a useful indicator of drought. While both the SPI and ADI showed similar trends in the temporal variation of drought conditions at all of the sites, the ADI better detected `severe drought' than did the SPI. The daily relief of severe drought due to precipitation was also better represented by the ADI. Using the high-resolution climatic and spatial data of a small watershed, we produced 270m resolution maps of ADI from week 36 through week 41 of 2013, demonstrating the feasibility of the ADI as an operational drought monitor appropriate for the agricultural environment of South Korea.

  4. Identification of spatiotemporal patterns of biophysical droughts in semi-arid region - a case study of the Karkheh river basin in Iran

    NASA Astrophysics Data System (ADS)

    Kamali, B.; Abbaspour, K. C.; Lehmann, A.; Wehrli, B.; Yang, H.

    2015-06-01

    This study aims at identifying historical patterns of meteorological, hydrological, and agricultural (inclusively biophysical) droughts in the Karkheh River Basin (KRB), one of the nine benchmark watersheds of the CGIAR Challenge Program on Water and Food. Standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture deficit index (SMDI) were used to represent the above three types of droughts, respectively. The three drought indices were compared across temporal and spatial dimensions. Variables required for calculating the indices were obtained from the Soil and Water Assessment Tool (SWAT) constructed for the region. The model was calibrated based on monthly runoff and yearly wheat yield using the Sequential Uncertainty Fitting (SUFI-2) algorithm. Five meteorological drought events were identified in the studied period (1980-2004), of which four corresponded with the hydrological droughts with 1-3 month lag. The meteorological droughts corresponded well with the agricultural droughts during dry months (May-August), while the latter lasted for a longer period of time. Analysis of drought patterns showed that southern parts of the catchment were more prone to agricultural drought, while less influenced by hydrological drought. Our analyses highlighted the necessity for monitoring all three aspects of drought for a more effective watershed management. The analysis on different types of droughts in this study provides a framework for assessing their possible impacts under future climate change in semi-arid areas.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  6. 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.

  7. Challenges and Opportunities for Developing Capacity in Earth Observations for Agricultural Monitoring: The GEOGLAM Experience

    NASA Astrophysics Data System (ADS)

    Whitcraft, A. K.; Di Bella, C. M.; Becker Reshef, I.; Deshayes, M.; Justice, C. O.

    2015-12-01

    Since 2011, the Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) Initiative has been working to strengthen the international community's capacity to use Earth observation (EO) data to derive timely, accurate, and transparent information on agriculture, with the goals of reducing market volatility and promoting food security. GEOGLAM aims to develop capacity for EO-based agricultural monitoring at multiple scales, from national to regional to global. This is accomplished through training workshops, developing and transferring of best-practices, establishing networks of broad and sustainable institutional support, and designing or adapting tools and methodologies to fit localized contexts. Over the past four years, capacity development activities in the context of GEOGLAM have spanned all agriculture-containing continents, with much more work to be done, particularly in the domains of promoting access to large, computationally-costly datasets. This talk will detail GEOGLAM's experiences, challenges, and opportunities surrounding building international collaboration, ensuring institutional buy-in, and developing sustainable programs.

  8. Agriculture

    EPA Pesticide Factsheets

    The EPA Agriculture Resource Directory offers comprehensive, easy-to-understand information about environmental stewardship on farms and ranches; commonsense, flexible approaches that are both environmentally protective and agriculturally sound.

  9. Interactive Effects of Storms, Drought, and Weekly Land Cover Changes on Water Quality Patterns in an Agricultural-dominated Subtropical Catchment in New Zealand

    NASA Astrophysics Data System (ADS)

    Julian, J.; Owsley, B.; de Beurs, K.; Hughes, A.

    2013-12-01

    Rivers are the funnels of landscapes, with the quality of water at the catchment outlet reflecting interactions among geomorphic processes, vegetation characteristics, weather patterns, and anthropogenic land uses. The impacts of changing climate and land cover on water quality are not straightforward; but instead, are set by the interaction of numerous landscape components at multiple spatiotemporal scales. In agricultural-dominated subtropical landscapes such as the Hoteo River Catchment in northern North Island of New Zealand, the land surface can be very dynamic, responding quickly to storms, drought, forest clearings, and grazing practices. In order to capture these short-term fluctuations, we created an 8-day land disturbance index for the catchment using MODIS Nadir BRDF-adjusted reflectance (NBAR) data (500 meter resolution) from 2000 to 2013. We also fused this time-series with Landsat TM/ETM surface reflectance data (30 meter resolution) to more precisely capture the location and extent of these land disturbances. This high-resolution land disturbance time-series was then compared to daily rainfall, daily river discharge, and monthly water samples to assess the effects of changing weather and land cover on a suite of water quality variables including water clarity, turbidity, ammonium (NH4), nitrate (NO3), total nitrogen (TN), dissolved reactive phosphate (DRP), total phosphorus (TP), and fecal coliforms. Forest clearings in the early part of our study period created the most intense land disturbances, which led to elevated turbidity and DRP during subsequent storms. Pasture areas during drought were also characterized by high disturbance indices, particularly in 2013 - the worst drought on record for northern New Zealand. Seasonal effects on land disturbance and water quality were also detected, especially for water clarity and turbidity. From 2011 to 2013, river discharge and turbidity from three sub-catchments were measured at 5-minute intervals to

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  11. Developing and implementing a data acquisition strategy for global agricultural monitoring: an inter-agency initiative

    NASA Astrophysics Data System (ADS)

    Justice, C. O.; Whitcraft, A. K.; Becker-Reshef, I.; Killough, B.

    2013-12-01

    In 2011, in response to global food crises, the G20 Agricultural Ministers launched a satellite-based global agricultural monitoring initiative to develop the Group on Earth Observations Global Agriculture Monitoring (GEOGLAM) system. The GEO is aimed at enhancing the availability and use of both satellite and in situ data for societal benefit. This initiative builds on the observation requirements developed by the GEO Agricultural Community of Practice, the understanding that no one satellite system can currently provide all the data needed for agricultural monitoring and the resulting recommendation for improved acquisition and availability of data by the World's space agencies. Implicit in this recommendation is the fact that certain regions of the Earth are imagery rich while others are imagery poor, leaving knowledge gaps about agricultural processes and food supply for certain areas of the World. In order to respond to these knowledge gaps and to strengthen national, regional, and global agricultural monitoring networks, GEOGLAM is working with the Committee on Earth Observations (CEOS), the space arm of GEO, to develop a coordinated global acquisition strategy. A key component of GEOGLAM is an effort to articulate the temporal and spatial Earth Observation (EO) requirements for monitoring; second, the identification of current and planned missions which are capable of fulfilling these EO requirements; and third, the development of a multi-agency, multi-mission image acquisition strategy for agricultural monitoring. CEOS engineers and GEOGLAM scientists have been collaborating on the EO requirements since 2012, and are now beginning the first implementation phase of the acquisition strategy. The goal is to put in place an operational system of systems using a virtual constellation of satellite-based sensors acquiring data to meet the needs for monitoring and early warning of shortfalls in agricultural production, a goal that was articulated in the 1970's

  12. 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.

  13. Investigation of Spatiotemporal Pattern of Drought in North Korea Using Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Yu, J.; Lee, K. S.

    2015-12-01

    Drought, as one of the severest disasters in the world, have attracted the attention of researchers and general public. Sometimes even short, intense droughts can cause significant damages to the natural environment as well as the economy. In recent years, North Korea (NK) has been suffering severe droughts. Yet, the thorough field investigation of drought disaster conditions in NK is impossible now. Thus, it is necessary to get more information of drought conditions to restore the damaged environment in NK after unification. RS data can be used to monitor vegetation, bare soil conditions, especially in inaccessible regions. This information can be used to derive spatial variation of drought conditions. Thus, the spatiotemporal pattern of drought conditions in NK using multi-sensor RS data and available meteorological data were investigated in this study. The RS data---MODIS NDVI (MOD13A3) and LST (Land Surface Temperature) (MOD11A2) from 2000 to 2014 which obtain the vegetation health conditions were used to derive two operationally used agricultural drought indices: Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). The in-situ precipitation data from 27 weather stations from 1981 to 2014 were used for identifying the relative dry/wet years and acquiring meteorological drought index Standardized Precipitation Index (SPI). The correlations between the agricultural drought indices and metrological drought index were derived. These data were stored in GIS and used for spatial analysis to figure out the spatiotemporal pattern of drought in NK. The spatiotemporal information of NK drought in this study can provide the basic information for restoring the drought damaged field after the unification of Korea.

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

    NASA Astrophysics Data System (ADS)

    Granger, S. L.; Behrangi, A.

    2015-12-01

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

  15. Agriculture and food availability -- remote sensing of agriculture for food security monitoring in the developing world

    USGS Publications Warehouse

    Budde, Michael E.; Rowland, James; Funk, Christopher C.

    2010-01-01

    For one-sixth of the world’s population - roughly 1 billion children, women and men - growing, buying or receiving adequate, affordable food to eat is a daily uncertainty. The World Monetary Fund reports that food prices worldwide increased 43 percent in 2007-2008, and unpredictable growing conditions make subsistence farming, on which many depend, a risky business. Scientists with the U.S. Geological Survey (USGS) are part of a network of both private and government institutions that monitor food security in many of the poorest nations in the world.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  17. 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.

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Okin, G. S.

    2007-12-01

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

  1. 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.

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

    PubMed

    Kampbell, Donald H; An, Youn-Joo; Jewell, Ken P; Masoner, Jason 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.

  3. Responses of tree-ring growth and crop yield to drought indices in the Shanxi province, North China.

    PubMed

    Sun, Junyan; Liu, Yu

    2014-09-01

    In this paper, we analyze the relationships among the tree-ring chronology, meteorological drought (precipitation), agricultural drought (Palmer Drought Severity Index PDSI), hydrological drought (runoff), and agricultural data in the Shanxi province of North China. Correlation analyses indicate that the tree-ring chronology is significantly correlated with all of the drought indices during the main growing season from March to July. Sign test analyses further indicate that the tree-ring chronology shows variation similar to that of the drought indices in both high and low frequencies. Comparisons of the years with narrow tree rings to the severe droughts reflected in all three indices from 1957 to 2008 reveal that the radial growth of the trees in the study region can accurately record the severe drought for which all three indices were in agreement (1972, 1999, 2000, and 2001). Comparisons with the dryness/wetness index indicate that tree-ring growth can properly record the severe droughts in the history. Correlation analyses among agricultural data, tree-ring chronology, and drought indices indicate that the per-unit yield of summer crops is relatively well correlated with the agricultural drought, as indicated by the PDSI. The PDSI is the climatic factor that significantly influences both tree growth and per-unit yield of summer crops in the study region. These results indicate that the PDSI and tree-ring chronology have the potential to be used to monitor and predict the yield of summer crops. Tree-ring chronology is an important tool for drought research and for wider applications in agricultural and hydrological research.

  4. 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

  5. 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

  6. 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.

  7. Monitoring Drought Effects on Mediteranean Conifer Forests Using SPOT-Vegetation NDVI and NDWI Timeseries

    NASA Astrophysics Data System (ADS)

    Karamihalaki, Maria; Stagakis, Stavros; Sykioti, Olga; Kyparissis, Aris; Parcharidis, Issaak

    2016-08-01

    The aim of this study focuses in the investigation of vegetation's responses to precipitation variations and water stress conditions in three Pinus sp. (pine) forests in Greece and in the assessment of NDWI and NDVI in terms of drought and water stress detection capacity for this type of ecosystems. For the purpose of this study, 11-year time series of NDVI and NDWI indices, issued from SPOT - Vegetation data, were constructed and correlated with ground measured precipitation data for the same time period, for all three study sites. Results show a strong relationship between the two indices. Furthermore, NDWI shows a stronger correlation with precipitation than NDVI, indicating a better capacity for investigating the vegetation water status. Generally, high seasonal precipitation variations seem to have a strong effect on both NDVI and NDWI levels, while a smoother precipitation distribution results to a weaker relationship with the two indices.

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

    USGS Publications Warehouse

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

    2015-01-01

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

  9. Building a data set over 12 globally distributed sites to support the development of agriculture monitoring applications with Sentinel-2

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The coming Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10-20...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Network for Monitoring Agricultural Water Quantity and Water Quality in Arkansas

    NASA Astrophysics Data System (ADS)

    Reba, M. L.; Daniels, M.; Chen, Y.; Sharpley, A.; Teague, T. G.; Bouldin, J.

    2012-12-01

    A network of agricultural monitoring sites was established in 2010 in Arkansas. The state of Arkansas produces the most rice of any state in the US, the 3rd most cotton and the 3rd most broilers. By 2050, agriculture will be asked to produce food, feed, and fiber for the increasing world population. Arkansas agriculture is challenged with reduced water availability from groundwater decline and the associated increase in pumping costs. Excess nutrients, associated in part to agriculture, influence the hypoxic condition in the Gulf of Mexico. All sites in the network are located at the edge-of-field in an effort to relate management to water quantity and water quality. The objective of the network is to collect scientifically sound data at field scales under typical and innovative management for the region. Innovative management for the network includes, but is not limited to, variable rate fertilizer, cover crops, buffer strips, irrigation water management, irrigation planning, pumping plant monitoring and seasonal shallow water storage. Data collection at the sites includes quantifying water inputs and losses, and water quality. Measured water quality parameters include sediment and dissolved nitrate, nitrite and orthophosphate. The measurements at the edge-of-field will be incorporated into the monitoring of field ditches and larger drainage systems to result in a 3-tiered monitoring effort. Partners in the creation of this network include USDA-ARS, Arkansas State University, University of Arkansas, University of Arkansas at Pine Bluff, USDA-NRCS and agricultural producers representing the major commodities of the state of Arkansas. The network is described in detail with preliminary results presented.

  12. 33 Years of Near-Global Daily Precipitation from Multisatellite Observations and its Application to Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Ashouri, H.; Hsu, K.; Sorooshian, S.; Braithwaite, D.; Knapp, K. R.; Cecil, L. D.

    2013-12-01

    PERSIANN Climate Data Record (PERSIANN-CDR) is a new retrospective satellite-based precipitation data set that is constructed for long-term hydrological and climate studies. The PERSIANN-CDR is a near-global (60°S-60°N) long-term (1980-2012), multi-satellite, high-resolution precipitation product that provides rain rate estimates at 0.25° and daily spatiotemporal resolution. PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high resolution precipitation data set for studying the spatial and temporal variations and changes of precipitation patterns, particularly in a scale relevant to climate extremes at the global scale. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data from the International Satellite Cloud Climatology Project (ISCCP). PERSIANN-CDR is adjusted using the Global Precipitation Climatology Project (GPCP) monthly precipitation to maintain consistency of two data sets at 2.5° monthly scale throughout the entire reconstruction period. PERSIANN-CDR daily precipitation data demonstrates considerable consistency with both GPCP monthly and GPCP 1DD precipitation products. Verification studies over Hurricane Katrina show that PERSIANN-CDR has a good agreement with NCEP Stage IV radar data, noting that PERSIANN-CDR has better spatial coverage. In addition, the Probability Density Function (PDF) of PERSIANN-CDR over the contiguous United States was compared with the PDFs extracted from CPC gauge data and the TMPA precipitation product. The experiment also shows good agreement of the PDF of PERSIANN-CDR with the PDFs of TMPA and CPC gauge data. The application of PERSIANN-CDR in regional and global drought monitoring is investigated. Consisting of more than three decades of high-resolution precipitation data, PERSIANN-CDR makes us capable of long-term assessment of droughts at a higher resolution (0.25°) than previously possible. The results will be presented at the meeting.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

  15. Monitoring stream sediment loads in response to agriculture in Prince Edward Island, Canada.

    PubMed

    Alberto, Ashley; St-Hilaire, Andre; Courtenay, Simon C; van den Heuvel, Michael R

    2016-07-01

    Increased agricultural land use leads to accelerated erosion and deposition of fine sediment in surface water. Monitoring of suspended sediment yields has proven challenging due to the spatial and temporal variability of sediment loading. Reliable sediment yield calculations depend on accurate monitoring of these highly episodic sediment loading events. This study aims to quantify precipitation-induced loading of suspended sediments on Prince Edward Island, Canada. Turbidity is considered to be a reasonably accurate proxy for suspended sediment data. In this study, turbidity was used to monitor suspended sediment concentration (SSC) and was measured for 2 years (December 2012-2014) in three subwatersheds with varying degrees of agricultural land use ranging from 10 to 69 %. Comparison of three turbidity meter calibration methods, two using suspended streambed sediment and one using automated sampling during rainfall events, revealed that the use of SSC samples constructed from streambed sediment was not an accurate replacement for water column sampling during rainfall events for calibration. Different particle size distributions in the three rivers produced significant impacts on the calibration methods demonstrating the need for river-specific calibration. Rainfall-induced sediment loading was significantly greater in the most agriculturally impacted site only when the load per rainfall event was corrected for runoff volume (total flow minus baseflow), flow increase intensity (the slope between the start of a runoff event and the peak of the hydrograph), and season. Monitoring turbidity, in combination with sediment modeling, may offer the best option for management purposes.

  16. A County-level Crop Specific Drought Severity-Coverage Index

    NASA Astrophysics Data System (ADS)

    Leelaruban, N.; Akyuz, A.; Padmanabhan, G.; Shaik, S.

    2012-12-01

    Understanding drought severity, frequency, duration and spatial extent is critical in drought mitigation, planning and decision making. A county-level approach to addressing drought is ideal since most agricultural management is best administered at county level in the USA. This study sought to apply spatiotemporal drought characteristics at reduced areal extents, namely, at county level for an entire state (North Dakota, USA) using a derived weekly non-dimensional index, Drought Severity and Coverage Index (Isc) based on a stepwise approach. Isc was calculated from weekly percentages of areal coverage values of drought intensity values published by the "U.S. Drought Monitor", DM. DM is published weekly as a joint project by the National Drought Mitigation Center (NDMC), U.S. Department of Agriculture (USDA), and the National Atmospheric and Oceanic Administration (NOAA). In order to facilitate application at the county level, the variation of the drought based on Isc was mapped in county level for state of North Dakota, and drought events were categorized into classes based on weekly Isc to analyze drought frequency. The number of occurrences of drought events were then determined for each county and climate division based on derived classes. The drought frequency analyses showed clear demarcation of counties in an observable dichotomy. Impact of drought on crop yield was also analyzed using USDA National Agricultural Statistics Service (NASS) county level yield, developed Isc values, drought intensity categories of areal coverage values for selected crops such as barley, corn, durum wheat, hay-alfalfa, hay, oats, and spring wheat. This research uses alternative panel statistical procedures instead of the usual time series analysis procedures to account for temporal and spatial variations to accurately model the relationship between exogenous and endogenous drought variables. In alternative panel procedures, two-way random effects model was used which accounts for

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

    USGS Publications Warehouse

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

    2008-01-01

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

  18. Water for food and nature in drought-prone tropics: vapour shift in rain-fed agriculture.

    PubMed Central

    Rockström, Johan

    2003-01-01

    This paper quantifies the eco-hydrological challenge up until 2050 of producing food in balance with goods and services generated by water-dependent ecosystems in nature. Particular focus is given to the savannah zone, covering 40% of the land area in the world, where water scarcity constitutes a serious constraint to sustainable development. The analysis indicates an urgent need for a new green revolution, which focuses on upgrading rain-fed agriculture. Water requirements to produce adequate diets for humans are shown to be relatively generic irrespective of hydro-climate, amounting to a global average of 1,300 m(3) cap(-1) yr(-1). Present food production requires an estimated 6,800 km(3) yr(-1) of consumptive green water (5,000 km(3) yr(-1) in rain-fed agriculture and 1,800 km(3) yr(-1) from irrigated crops). Without considering water productivity gains, an additional 5,800 km(3) yr(-1) of water is needed to feed a growing population in 2,050 and eradicate malnutrition. It is shown that the bulk of this water will be used in rain-fed agriculture. A dynamic analysis of water productivity and management options indicates that large 'crop per drop' improvements can be achieved at the farm level. Vapour shift in favour of productive green water flow as crop transpiration could result in relative water savings of 500 km(3) yr(-1) in semi-arid rain-fed agriculture. PMID:14728794

  19. Web-Based Image Viewer for Monitoring High-Definition Agricultural Images

    NASA Astrophysics Data System (ADS)

    Kobayashi, Kazuki; Toda, Shohei; Kobayashi, Fumitoshi; Saito, Yasunori

    This paper describes a Web-based image viewer which was developed to monitor high-definition agricultural images. In the cultivation of crops, physiological data and environmental data are important to increase crop yields. However, it is a burden for farmers to collect such data. Against this backdrop, the authors developed a monitoring system to automatically collect high-definition crop images, which can be viewed on a specialized Web-based image viewer. Users can easily observe detailed crop images over the Internet and easily find differences among the images. The authors experimentally installed the monitoring system in an apple orchard and observed the apples growing there. The system has been operating since August 11, 2009. In this paper, we confirm the ability of the monitoring system to perform detailed observations, including tracing the progress of a disease that affects the growth of an apple.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  2. 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).

  3. Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production

    USGS Publications Warehouse

    Leslie, Colin R.; Serbina, Larisa O.; Miller, Holly M.

    2017-03-29

    Executive SummaryThe use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.  Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:Estimating Crop Production.—Provides an overview of how Landsat satellite imagery is used to estimate crop production, including the spectral bands most frequently utilized in this application.Monitoring Consumptive Water Use.—Highlights the role of Landsat imagery in monitoring consumptive water use for agricultural production. Globally, a significant amount of agricultural production relies on irrigation, so monitoring water resources is a critical component of agricultural monitoring. National Agricultural Statistics Service—Cropland Data Layer.—Highlights the use of Landsat imagery in developing the annual Cropland Data Layer, a crop-specific land cover classification product that provides information on more than 100 crop categories grown in the United States. Foreign Agricultural Service—Global Agricultural Monitoring.—Highlights Landsat’s role in monitoring global agricultural

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

    NASA Astrophysics Data System (ADS)

    Rossato, L.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  6. Characterization of drought and its assessment over Sindh, Pakistan during 1951-2010

    NASA Astrophysics Data System (ADS)

    Adnan, Shahzada; Ullah, Kalim; Gao, Shouting

    2015-10-01

    Drought is one of the complex meteorological disasters affecting water resources, agriculture, livestock, and socioeconomic patterns of a region. Although drought prediction is difficult, it can be monitored based on climatological information. In this study, we provide high spatiotemporal resolution drought climatology, using observational, gridded precipitation data (0.5°×0.5°) from the Global Precipitation Climatological Center and soil moisture data from the Climate Prediction Center for the 60-yr period 1951-2010. The standardized precipitation index (SPI) based on a fitted Gamma distribution and Run method has been calculated from the regional drought identification model (ReDIM) for 3, 6, 9, 12, and 24 months. The results show strong temporal correlations among anomalies of precipitation, soil moisture, and SPI. Analysis of long-term precipitation data reveals that the drought vulnerability concentrates on monsoon season (July-September), which contributes 72.4% and 82.1% of the annual precipitation in northern and southern Sindh, respectively. Annual and seasonal analyses show no significant changes in the observed precipitation. The category classification criteria are defined to monitor/forecast drought in the selected area. Further analysis identifies two longest episodes of drought, i.e., 1972-1974 and 2000-2002, while 1969, 1974, 1987, and 2002 are found to be the most severe historical drought years. A drought hazard map of Sindh was developed, in which 10 districts are recognized as highly vulnerable to drought. This study helps to explain the time, duration, intensity, and frequency of meteorological droughts over Sindh as well as its neighboring regions, and provides useful information to disaster management agencies and forecasters for assessing both the regional vulnerability of drought and its seasonal predictability in Pakistan.

  7. Characterization of Drought and Its Assessment over Sindh, Pakistan During 1951-2010

    NASA Astrophysics Data System (ADS)

    Adnan, Shahzada

    2016-07-01

    Drought is one of the complex meteorological disasters, which can affect water resources, agriculture, livestock, and socioeconomic patterns of a region. Although drought prediction is difficult, it can be monitored based on climatological information. In this study, we provide high spatial and temporal resolution drought climatology, using observational, gridded precipitation data (0.5°X 0.5°) from the Global Precipitation Climatological Center and soil moisture from the Climate Prediction Centre for the 60-yr period 1951-2010. The standardized precipitation index (SPI) based on a fitted Gamma distribution and Run Method has been calculated from the regional drought identification model (ReDIM) on 3, 6, 9, 12 and 24 months. The results show strong temporal correlations among anomalies of precipitation, soil moisture, and SPI. Analysis of long-term precipitation data reveals that the drought vulnerability concentrates on monsoon season (July-September), which contributes 72.4% and 82.1% of annual precipitation in northern and southern Sindh, respectively. Annual and seasonal analyses show no significant changes in the observed precipitation. The category classification criteria are defined to monitor/forecast drought in the selected area. Further analysis identifies two longest episodes of drought, i.e., 1972-1974 and 2000-2002, while 1969, 1974, 1987, and 2002 are found to be the most severe historical drought years. A drought hazard map of Sindh was developed, in which 10 districts are recognized as highly vulnerable to drought. This study helps in explaining the time, duration, intensity, and frequency of meteorological droughts over Sindh as well as its neighboring regions, and provides useful information to disaster management agencies and forecasters for assessing both the regional vulnerability of drought and its seasonal predictability in Pakistan.

  8. NASA's NI-SAR Observing Strategy and Data Availability for Agricultural Monitoring and Assessment

    NASA Astrophysics Data System (ADS)

    Siqueira, P.; Dubayah, R.; Kellndorfer, J. M.; Saatchi, S. S.; Chapman, B. D.

    2014-12-01

    The monitoring and characterization of global crop development by remote sensing is a complex task, in part, because of the time varying nature of the target and the diversity of crop types and agricultural practices that vary worldwide. While some of these difficulties are overcome with the availability of national and market-derived resources (e.g. publication of crop statistics by the USDA and FAO), monitoring by remote sensing has the ability of augmenting those resources to better identify changes over time, and to provide timely assessments for the current year's production. Of the remote sensing techniques that are used for agricultural applications, optical observations of NDVI from Landsat, AVHRR, MODIS and similar sensors have historically provided the majority of data that is used by the community. In addition, radiometer and radar sensors, are often used for estimating soil moisture and structural information for these agricultural regions. The combination of these remote sensing datasets and national resources constitutes the state of the art for crop monitoring and yield forecasts. To help improve these crop monitoring efforts in the future, the joint NASA-ISRO SAR mission known as NI-SAR is being planned for launch in 2020, and will have L- and S-band fully polarimetric radar systems, a fourteen day repeat period, and a swath width on the order of several hundred kilometers. To address the needs of the science and applications communities that NI-SAR will support, the systems observing strategy is currently being planned such that data rate and the system configuration will address the needs of the community. In this presentation, a description of the NI-SAR system will be given along with the currently planned observing strategy and derived products that will be relevant to the overall GEOGLAM initiative.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  10. The use of PROBA-V data for Global Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Bydekerke, Lieven; Gilliams, Sven; Kempeneers, Pieter; Piccard, Isabelle; Deronde, Bart; Eerens, Herman; Gobin, Anne

    2015-04-01

    Land conversion, forest cutting, urban growth, agricultural expansion, take place at an unprecedented rate and scale such that they have a strong economic and environmental impact. Understanding and measuring dynamics becomes a prerequisite for companies, governments, agencies, NGO's, research institutes and society in general. In many cases the temporal frequency of the information is a requirement to detect phenomena that can occur within a few days and at a certain geographic scale. For example frequent updates on crop condition and projected production are needed to stabilise agricultural markets. Large initiatives such as the GEOGLAM AMIS (Group on Earth Observations Global Agricultural Monitoring - Agricultural Market Information System) respond to this increased need. Observations over large areas are available through satellites, however, the following challenges remain: • obtaining frequent and consistent observations at sufficient level of detail to identify spatial phenomena. At present, no single mission is capable of providing near daily information of any place in the world at scales appropriate to detect land cover/use changes in a consistent manner. • the need for a historical reference. For agricultural monitoring and early warning purposes the comparison of the actual data with a historical reference is of the utmost importance. The PROBA-V mission is an important attempt to overcome these challenges. From its design and within the GIO-Global Land component a lot of work has been done to ensure the consistency between the PROBA-V data and the 15 years historical archive of SPOT-VEGETATION. In this respect PROBA-V observations are comparable with the SPOT-VEGETATION historical baseline and will therefore ensure the continuation of the standard agricultural monitoring products. Next to this integration with the historical archive, PROBA -V also provides an increase in spatial resolution from 1km to 300m and even 100m. The latter ensures a global

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  12. An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

    NASA Astrophysics Data System (ADS)

    Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

    2014-05-01

    Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are

  13. 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.

  14. Monitoring changes in soil carbon resulting from intensive production, a non-traditional agricultural methodology.

    SciTech Connect

    Dwyer, Brian P.

    2013-03-01

    New Mexico State University and a group of New Mexico farmers are evaluating an innovative agricultural technique they call Intensive Production (IP). In contrast to conventional agricultural practice, IP uses intercropping, green fallowing, application of soil amendments and soil microbial inocula to sequester carbon as plant biomass, resulting in improved soil quality. Sandia National Laboratories role was to identify a non-invasive, cost effective technology to monitor soil carbon changes. A technological review indicated that Laser Induced Breakdown Spectroscopy (LIBS) best met the farmers objectives. Sandia partnered with Los Alamos National Laboratory (LANL) to analyze farmers test plots using a portable LIBS developed at LANL. Real-time LIBS field sample analysis was conducted and grab samples were collected for laboratory comparison. The field and laboratory results correlated well implying the strong potential for LIBS as an economical field scale analytical tool for analysis of elements such as carbon, nitrogen, and phosphate.

  15. Modeling the hydrologic responses of the Pampanga River basin, Philippines: A quantitative approach for identifying droughts

    NASA Astrophysics Data System (ADS)

    Jaranilla-Sanchez, Patricia Ann; Wang, Lei; Koike, Toshio

    2011-03-01

    Drought in the Philippines has been monitored for agricultural and economic losses, but spatial and temporal characterization at the basin scale has not been quantified. The relationship between different drought types, and how these can be integrated into timely water-resource-management planning in the agriculture and water sector of the Pampanga River basin, were considered. Specifically, the objectives of this study are as follows: (1) to propose a standardized anomaly (SA) index for assessing different types of drought impacts at the basin scale; (2) to quantify vulnerability of the agriculture and water sectors using physically consistent hydrological parameters with temporal variation and spatial heterogeneity; (3) to develop a method for combining the drought index calculated from the inputs and outputs of WEB-DHM on the basis of sturdy algorithms for the physics of water and energy movement in the basin using monthly and seasonal differences of various drought types; and (4) to combine hydrological parameters with crop production to determine its effects on rice. The SA was calculated for the variables related to each drought type: rainfall (meteorological), streamflow and groundwater (hydrological), and soil moisture (agricultural) during 1983, 1987, 1990-1992, and 1998 droughts. El Niño is one of the major driving forces leading to drought in the country. The drought intensified on the second year of the average two-year El Niño Southern-Oscillation (ENSO) composites with a 1 to 7 month time lag between parameters and hot spots in the upland and central plains of the basin. Recommended adaptation strategies include crop scheduling, crop/livelihood substitutes, and alternative water sources.

  16. Coping with historic drought in California rangelands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The current drought in California is of historic proportion, both in its intensity and its effect on agriculture. Although storms of the 2015-16 winter rainfall season have provided modest drought relief, their effects on alleviating the multi-year drought are unknown. Short- and mid-term forecasts...

  17. The Use of Proba-V data for Global Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Gilliams, S. J. B.; Bydekerke, L.; Smets, B.; De Ronde, B.

    2014-12-01

    Land conversion, forest cutting, urban growth, agricultural expansion, take place at scales which are unprecedented in history and at such a pace that they are not only subject of scientific studies but also have a strong economic impact. Understanding and measuring dynamics becomes a prerequisite for companies, governments, agencies, NGO's, research institutes and society in general. In many of these cases the temporal frequency of the information is a clear requirement to detect phenomena that can occur within a few days (related to crops, forests and other ecosystems) and at a certain geographic scale. For example frequent updates on crop condition and production is needed to stabilize agricultural markets. This is already being picked up by large initiatives like the GEOGLAM AMIS system. Observations over large areas are available through satellites, however challenges remain; on the one hand side obtaining frequent and consistent observations at sufficient level of detail to identify spatial phenomena. At present, no single mission is capable of providing near daily information of any place in the world at scales in which changes in land cover/use can be identified in a consistent manner. On the other hand side the need for a historical reference. For agricultural monitoring and early warning purposes the comparison of the actual data with the historical reference is of the utmost importance. The Proba-V mission is a first attempt to overcome these challenges. From its design and within the GIO-Global Land component a lot of work has been done to ensure the integration of the Proba-V data with the 15 years historical archive of SPOT-VEGETATION. In this respect Proba-V observation will be intercomparable with the SPOT-VGT historical baseline which will ensure the continuation of the standard agricultural monitoring products. Next to this integration with the historical archive, Proba-V also ensures an increase in spatial resolution of the data sets, from 1km to

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  19. Agriculture: Climate Change

    EPA Pesticide Factsheets

    Climate change affects agricultural producers because agriculture and fisheries depend on specific climate conditions. Temperature changes can cause crop planting dates to shift. Droughts and floods due to climate change may hinder farming practices.

  20. The Monitoring Erosion of Agricultural Land and spatial database of erosion events

    NASA Astrophysics Data System (ADS)

    Kapicka, Jiri; Zizala, Daniel

    2013-04-01

    In 2011 originated in The Czech Republic The Monitoring Erosion of Agricultural Land as joint project of State Land Office (SLO) and Research Institute for Soil and Water Conservation (RISWC). The aim of the project is collecting and record keeping information about erosion events on agricultural land and their evaluation. The main idea is a creation of a spatial database that will be source of data and information for evaluation and modeling erosion process, for proposal of preventive measures and measures to reduce negative impacts of erosion events. A subject of monitoring is the manifestations of water erosion, wind erosion and slope deformation in which cause damaged agriculture land. A website, available on http://me.vumop.cz, is used as a tool for keeping and browsing information about monitored events. SLO employees carry out record keeping. RISWC is specialist institute in the Monitoring Erosion of Agricultural Land that performs keeping the spatial database, running the website, managing the record keeping of events, analysis the cause of origins events and statistical evaluations of keeping events and proposed measures. Records are inserted into the database using the user interface of the website which has map server as a component. Website is based on database technology PostgreSQL with superstructure PostGIS and MapServer UMN. Each record is in the database spatial localized by a drawing and it contains description information about character of event (data, situation description etc.) then there are recorded information about land cover and about grown crops. A part of database is photodocumentation which is taken in field reconnaissance which is performed within two days after notify of event. Another part of database are information about precipitations from accessible precipitation gauges. Website allows to do simple spatial analysis as are area calculation, slope calculation, percentage representation of GAEC etc.. Database structure was designed

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

    NASA Astrophysics Data System (ADS)

    Neri, C.; Magaña Rueda, V.

    2013-05-01

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

  2. Geomorphic response to historic drought in northern California

    NASA Astrophysics Data System (ADS)

    Bennett, Georgina; Roering, Joshua; Mackey, Ben; Handwerger, Alexander; Guillod, Benoit; Schmidt, David

    2016-04-01

    California declared a state of drought emergency in early 2014 with a recent study showing that 2012 - 2015 constitutes a drought unprecedented in the state's historical record. Much has been reported on the drought's devastating impacts on water supply, agriculture and wildfire occurrence as well as its possible origins, including the role of anthropogenic climate change. However, its geomorphic impact has been given little attention. We address this gap by assessing the response of earthflows to drought in the Eel River in northern California. Despite their slow-moving nature, earthflows contribute ~50% of erosion in the region and are a constant threat to transport routes, making their behavior important to understand. We used pixel tracking in the program COSI CORR to measure velocities of 98 earthflows for the periods 2009 - 2012 and 2012 - 2015 from 0.5 m resolution Worldview satellite imagery. Putting these measurements in the context of velocities manually measured from aerial photographs dating back to the 1950s indicates that whilst earthflows have decelerated significantly in the ensuing drought this is part of a slowing trend commencing around 2000. We show that decadal earthflow velocities are closely correlated with the Palmer Drought Severity Index (PDSI), which in turn is correlated with North American Land Data Assimilation System (NLDAS)-modeled soil moisture. Slowing of earthflows since 2000 is coincident with a reduction of soil moisture, starting with the 2000 - 2001 drought from which earthflows have not yet returned to their pre-drought values and which set the stage for the slowest mean velocities observed in recent decades during the current drought. It will be important to continue to monitor these earthflows as rains return, particularly given the hypothesis that extreme drying may increase pathways for future runoff into earthflows.

  3. The drought impact on satellite solar-induced chlorophyll fluorescence in China during 2007-2015

    NASA Astrophysics Data System (ADS)

    Li, Ruitao

    2016-04-01

    the dynamics of vegetation functioning, which seems a large advantage for agricultural drought early warning. Therefore, all analyses indicate that the emerging satellite SIF potentially provides a new way to monitor agricultural drought.

  4. Agricultural Land Use mapping by multi-sensor approach for hydrological water quality monitoring

    NASA Astrophysics Data System (ADS)

    Brodsky, Lukas; Kodesova, Radka; Kodes, Vit

    2010-05-01

    The main objective of this study is to demonstrate potential of operational use of the high and medium resolution remote sensing data for hydrological water quality monitoring by mapping agriculture intensity and crop structures. In particular use of remote sensing mapping for optimization of pesticide monitoring. The agricultural mapping task is tackled by means of medium spatial and high temporal resolution ESA Envisat MERIS FR images together with single high spatial resolution IRS AWiFS image covering the whole area of interest (the Czech Republic). High resolution data (e.g. SPOT, ALOS, Landsat) are often used for agricultural land use classification, but usually only at regional or local level due to data availability and financial constraints. AWiFS data (nominal spatial resolution 56 m) due to the wide satellite swath seems to be more suitable for use at national level. Nevertheless, one of the critical issues for such a classification is to have sufficient image acquisitions over the whole vegetation period to describe crop development in appropriate way. ESA MERIS middle-resolution data were used in several studies for crop classification. The high temporal and also spectral resolution of MERIS data has indisputable advantage for crop classification. However, spatial resolution of 300 m results in mixture signal in a single pixel. AWiFS-MERIS data synergy brings new perspectives in agricultural Land Use mapping. Also, the developed methodology procedure is fully compatible with future use of ESA (GMES) Sentinel satellite images. The applied methodology of hybrid multi-sensor approach consists of these main stages: a/ parcel segmentation and spectral pre-classification of high resolution image (AWiFS); b/ ingestion of middle resolution (MERIS) vegetation spectro-temporal features; c/ vegetation signatures unmixing; and d/ semantic object-oriented classification of vegetation classes into final classification scheme. These crop groups were selected to be

  5. National Drought Policy: Shifting the Paradigm from Crisis to Risk-based Management

    NASA Astrophysics Data System (ADS)

    Wilhite, D. A.; Sivakumar, M. K.; Stefanski, R.

    2011-12-01

    Drought is a normal part of climate for virtually all of the world's climatic regimes. To better address the risks associated with this hazard and societal vulnerability, there must be a dramatic paradigm shift in our approach to drought management in the coming decade in the light of the increasing frequency of droughts and projections of increased severity and duration of these events in the future for many regions, especially in the developing world. Addressing this challenge will require an improved awareness of drought as a natural hazard, the establishment of integrated drought monitoring and early warning systems, a higher level of preparedness that fully incorporates risk-based management, and the adoption of national drought policies that are directed at increasing the coping capacity and resilience of populations to future drought episodes. The World Meteorological Organization (WMO), in partnership with other United Nations' agencies, the National Drought Mitigation Center at the University of Nebraska, NOAA, the U.S. Department of Agriculture, and other partners, is currently launching a program to organize a High Level Meeting on National Drought Policy (HMNDP) in March 2013 to encourage the development of national drought policies through the development of a compendium of key policy elements. The key objectives of a national drought policy are to: (1) encourage vulnerable economic sectors and population groups to adopt self-reliant measures that promote risk management; (2) promote sustainable use of the agricultural and natural resource base; and (3) facilitate early recovery from drought through actions consistent with national drought policy objectives. The key elements of a drought policy framework are policy and governance, including political will; addressing risk and improving early warnings, including vulnerability analysis, impact assessment, and communication; mitigation and preparedness, including the application of effective and

  6. Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites

    NASA Astrophysics Data System (ADS)

    Bajgain, Rajen; Xiao, Xiangming; Wagle, Pradeep; Basara, Jeffrey; Zhou, Yuting

    2015-10-01

    Vegetation growth is one of the important indicators of drought events. Greenness-related vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) are often used for the assessment of agricultural drought. There is a need to evaluate the sensitivity of water-related vegetation indices such as Land Surface Water Index (LSWI) to assess drought and associated impacts. Moderate-Resolution Imaging Spectroradiometer (MODIS) derived time series NDVI, EVI and LSWI data during 2000-2013 were compared for their sensitivity to drought at two tallgrass prairie sites in the Oklahoma Mesonet (Marena and El Reno). Each site has continuous soil moisture measurements at three different depths (5, 25 and 60 cm) and precipitation data for the study period (2000-2013) at 5-min intervals. As expected, averaged values of vegetation indices consistently lower under drought conditions than normal conditions. LSWI decreased the most in drought years (2006, 2011 and 2012) when compared to its magnitudes in pluvial years (2007, 2013), followed by EVI and NDVI, respectively. Because green vegetation has positive LSWI values (>0) and dry vegetation has negative LSWI values (<0), much longer durations of LSWI < 0 were found in the summer periods of drought years rather than in pluvial years. A LSWI-based drought severity scheme (LSWI > 0.1; 0 < LSWI ⩽ 0.1; -0.1 < LSWI ⩽ 0; LSWI ⩽ -0.1) corresponded well with the drought severity categories (0; D0; D1: D2; D3 and D4) defined by the United States Drought Monitor (USDM) at these two study sites. Our results indicate that the number of days with LSWI < 0 during the summer and LSWI-based drought severity scheme can be simple, effective and complementary indicator for assessing drought in tallgrass prairie grasslands at a 500-m spatial resolution.

  7. Monitoring of nitrates in drinking water from agricultural and residential areas of Podravina and Prigorje (Croatia).

    PubMed

    Nemčić-Jurec, Jasna; Konjačić, Miljenko; Jazbec, Anamarija

    2013-11-01

    Nitrates are the most common chemical pollutant of groundwater in agricultural and suburban areas. Croatia must comply with the Nitrate Directive (91/676/EEC) whose aim is to reduce water pollution by nitrates originating from agriculture and to prevent further pollution. Podravina and Prigorje are the areas with a relatively high degree of agricultural activity. Therefore, the aim of this study was, by monitoring nitrates, to determine the distribution of nitrates in two different areas, Podravina and Prigorje (Croatia), to determine sources of contamination as well as annual and seasonal trends. The nitrate concentrations were measured in 30 wells (N = 382 samples) in Prigorje and in 19 wells (N = 174 samples) in Podravina from 2002 to 2007. In Podravina, the nitrate content was 24.9 mg/l and 6% of the samples were above the maximum available value (MAV), and in Prigorje the content was 53.9 mg/l and 38% of the samples above MAV. The wells were classified as correct, occasionally incorrect and incorrect. In the group of occasionally incorrect and incorrect wells, the point sources were within 10 m of the well. There is no statistically significant difference over the years or seasons within the year, but the interaction between locations and years was significant. Nitrate concentrations' trend was not significant during the monitoring. These results are a prerequisite for the adjustment of Croatian standards to those of the EU and will contribute to the implementation of the Nitrate Directive and the Directives on Environmental Protection in Croatia and the EU.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. Wet acid deposition in Chinese natural and agricultural ecosystems: Evidence from national-scale monitoring

    NASA Astrophysics Data System (ADS)

    Yu, Haili; He, Nianpeng; Wang, Qiufeng; Zhu, Jianxing; Xu, Li; Zhu, Zhilin; Yu, Guirui

    2016-09-01

    Acid deposition in precipitation has received widespread attention. However, it is necessary to monitor the acid deposition in Chinese agricultural and natural ecosystems because data derived from traditional urban/suburban observations might overestimate it to some extent. In this study, we continuously measured the acid deposition through precipitation (pH, sulfate (SO42-), and nitrate (NO3-)) in 43 field stations from 2009 to 2014 to explore the spatial patterns and the main influencing factors of acid deposition in Chinese agricultural and natural ecosystems. The results showed that the average precipitation pH at the 43 stations varied between 4.10 and 8.25 (average: 6.2) with nearly 20% of the observation sites being subjected to acid precipitation (pH < 5.6). The average deposition of SO42- and NO3- was 115.99 and 32.93 kg ha-1 yr-1, respectively. An apparent regional difference of acid deposition in Chinese agricultural and natural ecosystems was observed, which was most serious in south and central China and less serious in northwest China, Inner Mongolia, and Qinghai-Tibet. The level of economic development and amount of precipitation could explain most of the spatial variations of pH, SO42-, and NO3- depositions. It is anticipated that acid deposition might increase further, although the current level of acid deposition in these Chinese agricultural and natural ecosystems was found to be less serious than projected from urban/suburban data. The control of energy consumption should be strengthened in future to prevent an increase of acid deposition in China.

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

  11. Drought Dynamics and Food Security in Ukraine

    NASA Astrophysics Data System (ADS)

    Kussul, N. M.; Kogan, F.; Adamenko, T. I.; Skakun, S. V.; Kravchenko, O. M.; Kryvobok, O. A.; Shelestov, A. Y.; Kolotii, A. V.; Kussul, O. M.; Lavrenyuk, A. M.

    2012-12-01

    In recent years food security became a problem of great importance at global, national and regional scale. Ukraine is one of the most developed agriculture countries and one of the biggest crop producers in the world. According to the 2011 statistics provided by the USDA FAS, Ukraine was the 8th largest exporter and 10th largest producer of wheat in the world. Therefore, identifying current and projecting future trends in climate and agriculture parameters is a key element in providing support to policy makers in food security. This paper combines remote sensing, meteorological, and modeling data to investigate dynamics of extreme events, such as droughts, and its impact on agriculture production in Ukraine. Two main problems have been considered in the study: investigation of drought dynamics in Ukraine and its impact on crop production; and investigation of crop growth models for yield and production forecasting and its comparison with empirical models that use as a predictor satellite-derived parameters and meteorological observations. Large-scale weather disasters in Ukraine such as drought were assessed using vegetation health index (VHI) derived from satellite data. The method is based on estimation of green canopy stress/no stress from indices, characterizing moisture and thermal conditions of vegetation canopy. These conditions are derived from the reflectance/emission in the red, near infrared and infrared parts of solar spectrum measured by the AVHRR flown on the NOAA afternoon polar-orbiting satellites since 1981. Droughts were categorized into exceptional, extreme, severe and moderate. Drought area (DA, in % from total Ukrainian area) was calculated for each category. It was found that maximum DA over past 20 years was 10% for exceptional droughts, 20% for extreme droughts, 50% for severe droughts, and 80% for moderate droughts. Also, it was shown that in general the drought intensity and area did not increase considerably over past 10 years. Analysis

  12. Drought impact functions as intermediate step towards drought damage assessment

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    provinces with good data availability. Impact functions representing localized drought impacts are more challenging to construct given that less data is available, yet may provide information that more directly addresses stakeholders' needs. Overall, our study contributes insights into how drought intensity translates into ecological and socioeconomic impacts, and how such information may be used for enhancing drought monitoring and early warning.

  13. Analytical Results for Agricultural Soils Samples from a Monitoring Program Near Deer Trail, Colorado (USA)

    USGS Publications Warehouse

    Crock, J.G.; Smith, D.B.; Yager, T.J.B.

    2009-01-01

    Since late 1993, Metro Wastewater Reclamation District of Denver (Metro District, MWRD), a large wastewater treatment plant in Denver, Colorado, has applied Grade I, Class B biosolids to about 52,000 acres of nonirrigated farmland and rangeland near Deer Trail, Colorado, USA. In cooperation with the Metro District in 1993, the U.S. Geological Survey (USGS) began monitoring groundwater at part of this site. In 1999, the USGS began a more comprehensive monitoring study of the entire site to address stakeholder concerns about the potential chemical effects of biosolids applications to water, soil, and vegetation. This more comprehensive monitoring program has recently been extended through 2010. Monitoring components of the more comprehensive study include biosolids collected at the wastewater treatment plant, soil, crops, dust, alluvial and bedrock groundwater, and stream bed sediment. Soils for this study were defined as the plow zone of the dry land agricultural fields - the top twelve inches of the soil column. This report presents analytical results for the soil samples collected at the Metro District farm land near Deer Trail, Colorado, during three separate sampling events during 1999, 2000, and 2002. Soil samples taken in 1999 were to be a representation of the original baseline of the agricultural soils prior to any biosolids application. The soil samples taken in 2000 represent the soils after one application of biosolids to the middle field at each site and those taken in 2002 represent the soils after two applications. There have been no biosolids applied to any of the four control fields. The next soil sampling is scheduled for the spring of 2010. Priority parameters for biosolids identified by the stakeholders and also regulated by Colorado when used as an agricultural soil amendment include the total concentrations of nine trace elements (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc), plutonium isotopes, and gross

  14. Monitoring agricultural rodenticide use and secondary exposure of raptors in Scotland.

    PubMed

    Hughes, J; Sharp, E; Taylor, M J; Melton, L; Hartley, G

    2013-08-01

    Despite the documented risk of secondary poisoning to non-target species by anticoagulant rodenticides there is no statutory post-approval monitoring of their use in the UK. This paper presents results from two Scottish monitoring schemes for the period 2000-2010; recording rodenticide use on arable farms and the presence of residues in raptor carcasses. More than three quarters of arable farms used anticoagulant rodenticides; predominately the second generation compounds difenacoum and bromadiolone. There was widespread exposure to anticoagulant rodenticides in liver tissues of the raptor species tested and the residues encountered generally reflected agricultural use patterns. As found in other studies, Red Kites (Milvus milvus) appeared to be particularly vulnerable to rodenticide exposure, 70 % of those sampled (n = 114) contained residues and 10 % died as a result of rodenticide ingestion. More unexpectedly, sparrowhawks (Accipiter nisus), which prey almost exclusively on birds, had similar exposure rates to species which prey on rodents. Although, with the exception of kites, confirmed mortality from rodenticides was low, the widespread exposure recorded is concerning. Particularly when coupled with a lack of data about the sub-lethal effects of these compounds. This raises questions regarding whether statutory monitoring of use is needed; both to address whether there are deficiencies in compliance with approval conditions or whether the recommended risk management procedures are themselves adequate to protect non-target wildlife.

  15. Agricultural crop harvest progress monitoring by fully polarimetric synthetic aperture radar imagery

    NASA Astrophysics Data System (ADS)

    Yang, Hao; Zhao, Chunjiang; Yang, Guijun; Li, Zengyuan; Chen, Erxue; Yuan, Lin; Yang, Xiaodong; Xu, Xingang

    2015-01-01

    Dynamic mapping and monitoring of crop harvest on a large spatial scale will provide critical information for the formulation of optimal harvesting strategies. This study evaluates the feasibility of C-band polarimetric synthetic aperture radar (PolSAR) for monitoring the harvesting progress of oilseed rape (Brassica napus L.) fields. Five multitemporal, quad-pol Radarsat-2 images and one optical ZY-1 02C image were acquired over a farmland area in China during the 2013 growing season. Typical polarimetric signatures were obtained relying on polarimetric decomposition methods. Temporal evolutions of these signatures of harvested fields were compared with the ones of unharvested fields in the context of the entire growing cycle. Significant sensitivity was observed between the specific polarimetric parameters and the harvest status of oilseed rape fields. Based on this sensitivity, a new method that integrates two polarimetric features was devised to detect the harvest status of oilseed rape fields using a single image. The validation results are encouraging even for the harvested fields covered with high residues. This research demonstrates the capability of PolSAR remote sensing in crop harvest monitoring, which is a step toward more complex applications of PolSAR data in precision agriculture.

  16. Implementation monitoring temperature, humidity and mositure soil based on wireless sensor network for e-agriculture technology

    NASA Astrophysics Data System (ADS)

    Sumarudin, A.; Ghozali, A. L.; Hasyim, A.; Effendi, A.

    2016-04-01

    Indonesian agriculture has great potensial for development. Agriculture a lot yet based on data collection for soil or plant, data soil can use for analys soil fertility. We propose e-agriculture system for monitoring soil. This system can monitoring soil status. Monitoring system based on wireless sensor mote that sensing soil status. Sensor monitoring utilize soil moisture, humidity and temperature. System monitoring design with mote based on microcontroler and xbee connection. Data sensing send to gateway with star topology with one gateway. Gateway utilize with mini personal computer and connect to xbee cordinator mode. On gateway, gateway include apache server for store data based on My-SQL. System web base with YII framework. System done implementation and can show soil status real time. Result the system can connection other mote 40 meters and mote lifetime 7 hours and minimum voltage 7 volt. The system can help famer for monitoring soil and farmer can making decision for treatment soil based on data. It can improve the quality in agricultural production and would decrease the management and farming costs.

  17. Prime agricultural land monitoring and assessment component of the California Integrated Remote Sensing System

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Tinney, L. R. (Principal Investigator); Streich, T.

    1981-01-01

    The use of digital LANDSAT techniques for monitoring agricultural land use conversions was studied. Two study areas were investigated: one in Ventura County and the other in Fresno County (California). Ventura test site investigations included the use of three dates of LANDSAT data to improve classification performance beyond that previously obtained using single data techniques. The 9% improvement is considered highly significant. Also developed and demonstrated using Ventura County data is an automated cluster labeling procedure, considered a useful example of vertical data integration. Fresno County results for a single data LANDSAT classification paralleled those found in Ventura, demonstrating that the urban/rural fringe zone of most interest is a difficult environment to classify using LANDSAT data. A general raster to vector conversion program was developed to allow LANDSAT classification products to be transferred to an operational county level geographic information system in Fresno.

  18. Using continuous monitoring of physical parameters to better estimate phosphorus fluxes in a small agricultural catchment

    NASA Astrophysics Data System (ADS)

    Minaudo, Camille; Dupas, Rémi; Moatar, Florentina; Gascuel-Odoux, Chantal

    2016-04-01

    Phosphorus fluxes in streams are subjected to high temporal variations, questioning the relevance of the monitoring strategies (generally monthly sampling) chosen to assist EU Directives to capture phosphorus fluxes and their variations over time. The objective of this study was to estimate the annual and seasonal P flux uncertainties depending on several monitoring strategies, with varying sampling frequencies, but also taking into account simultaneous and continuous time-series of parameters such as turbidity, conductivity, groundwater level and precipitation. Total Phosphorus (TP), Soluble Reactive Phosphorus (SRP) and Total Suspended Solids (TSS) concentrations were surveyed at a fine temporal frequency between 2007 and 2015 at the outlet of a small agricultural catchment in Brittany (Naizin, 5 km2). Sampling occurred every 3 to 6 days between 2007 and 2012 and daily between 2013 and 2015. Additionally, 61 storms were intensively surveyed (1 sample every 30 minutes) since 2007. Besides, water discharge, turbidity, conductivity, groundwater level and precipitation were monitored on a sub-hourly basis. A strong temporal decoupling between SRP and particulate P (PP) was found (Dupas et al., 2015). The phosphorus-discharge relationships displayed two types of hysteretic patterns (clockwise and counterclockwise). For both cases, time-series of PP and SRP were estimated continuously for the whole period using an empirical model linking P concentrations with the hydrological and physic-chemical variables. The associated errors of the estimated P concentrations were also assessed. These « synthetic » PP and SRP time-series allowed us to discuss the most efficient monitoring strategies, first taking into account different sampling strategies based on Monte Carlo random simulations, and then adding the information from continuous data such as turbidity, conductivity and groundwater depth based on empirical modelling. Dupas et al., (2015, Distinct export dynamics for

  19. Evaluating drought in the United States using the emissivity difference vegetation index

    NASA Astrophysics Data System (ADS)

    Hirani, Hanisha K.

    As monitoring vegetation and crops becomes increasingly important due to climate change, there arises the need for a monitoring scheme that places more weight on water availability as an indication of vegetation health and vitality. The Emissivity Difference Vegetation Index (EDVI) is the first step towards that type of monitoring scheme. With the potential for diurnal studies, there are applications towards agriculture monitoring, wildfire monitoring, and much more. EDVI is a synergetic product retrieved from microwave, visible, and infrared satellite measurements, as well as reanalysis. Since microwave measurements are more sensitive to vegetation water content, EDVI has the potential to capture intrinsic changes in vegetation. A new drought index is developed from EDVI, the Emissivity Vegetation Condition Index (EVCI). The high temporal sampling of EVCI will make it one of the more dynamic attempts to measure and investigate drought impacts on vegetation and crops on short-term scales. This new drought index will be compared to presently operational drought indices including the Palmer drought indices, the Vegetation Condition Index (VCI), and the Vegetation Health Index (VHI) for the period between 2009-2011 in the United States. The focus will be on improving the methodology of the EDVI retrieval and then examining two periods of identified drought, one in the Southern Great Plains in 2011, and one short-term drought in the Great Lakes region in 2010. The results indicate an agreement between ECVI and precipitation, and the drought episodes in 2010 and 2011 are resolved by EVCI. With a dataset beyond the three years used for this study it would be possible to correct more accurately for climatology.

  20. Scientific Insights for Managing Droughts in California

    NASA Astrophysics Data System (ADS)

    Lund, J. R.; Medellin-Azuara, J.; Howitt, R. E.; MacEwan, D.; Sumner, D. A.

    2015-12-01

    Droughts stress water systems and provide important opportunities to learn about vulnerabilities and motivate improvements in water systems. Current and past droughts in California show that this highly-engineered system is highly robust and resilient to droughts, as agriculture and urban water needs are mostly fulfilled and recover quickly following drought. However, environmental systems remain highly vulnerable and have shown less resilience to drought, with each drought bringing additional native species closer to extinction, often with little recovery following the drought. This paper reviews the impacts of California's ongoing 4-year drought and its importance for better understanding its ecological and water supply systems, as well as motivating improvements in water management and scientific work.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  2. Distinguishing warming-induced drought from drought-induced warming

    NASA Astrophysics Data System (ADS)

    Roderick, M. L.; Yin, D.

    2015-12-01

    It is usually observed that temperatures, especially maximum temperatures are higher during drought. A very widely held public perception is that the increase in temperature is a cause of drought. This represents the warming-induced drought scenario. However, the agricultural and hydrologic scientific communities have a very different interpretation with drought being the cause of increasing temperature. In essence, those communities assume the warming is a surface feedback and their interpretation is for drought-induced warming. This is a classic cause-effect problem that has resisted definitive explanation due to the lack of radiative observations at suitable spatial and temporal scales. In this presentation we first summarise the observations and then use theory to untangle the cause-effect relationships that underlie the competing interpretations. We then show how satellite data (CERES, NASA) can be used to disentangle the cause-effect relations.

  3. Sensor-based soil water monitoring to more effectively manage agricultural water resources in coastal plain soils

    NASA Astrophysics Data System (ADS)

    Bellamy, Christopher A.

    Cotton (Gossypium hirsutum L.) is widely grown in the United States with 5.7 million ha grown nationally and 1.2 million ha grown in the humid southeastern states in 2005. From 1969 to 2003, agricultural irrigated farmland acreage and total water applied increased by over 40% and 11% respectively to include a total of 55.3 million acres in 2002. Combined with recent and more frequent drought periods and legal water conflicts between states, there has been an increased interest in more effective southeastern water management, thus making the need to develop improved irrigation scheduling methods and enhanced water use efficiency of cotton cultivars. Several irrigation scheduling methods (soil moisture monitoring, pan evaporation, and climate based) tested at Clemson and elsewhere have shown that sensor-based irrigation significantly increased cotton yields and provided a monetary savings compared to other methods. There is however limited information on capacitance based soil moisture analysis techniques in the southeastern coastal plain soils and also limited locally developed crop coefficients used in scheduling the ET based treatments. The first objective of this study was to determine and improve the feasibility of utilizing sensor-based soil water monitoring techniques in Southeastern Coastal Plain soils to more effectively manage irrigation and increase water use efficiency of several cotton cultivars. The second objective was to develop two weighing lysimeters equipped with wireless data acquisition system to determine a crop coefficient for cotton under southeastern humid conditions. Two multi-sensor capacitance probes, AquaSpy(TM) and Sentek EnviroSCAN RTM, were calibrated in this study. It was found that positive linear calibrations can be used to describe the relationship between the soil volumetric moisture content (VMC) and sensor readings found for both probes and that multi-sensor capacitance probes can be used to accurately measure volumetric soil

  4. General mechanisms of drought response and their application in drought resistance improvement in plants.

    PubMed

    Fang, Yujie; Xiong, Lizhong

    2015-02-01

    Plants often encounter unfavorable environmental conditions because of their sessile lifestyle. These adverse factors greatly affect the geographic distribution of plants, as well as their growth and productivity. Drought stress is one of the premier limitations to global agricultural production due to the complexity of the water-limiting environment and changing climate. Plants have evolved a series of mechanisms at the morphological, physiological, biochemical, cellular, and molecular levels to overcome water deficit or drought stress conditions. The drought resistance of plants can be divided into four basic types-drought avoidance, drought tolerance, drought escape, and drought recovery. Various drought-related traits, including root traits, leaf traits, osmotic adjustment capabilities, water potential, ABA content, and stability of the cell membrane, have been used as indicators to evaluate the drought resistance of plants. In the last decade, scientists have investigated the genetic and molecular mechanisms of drought resistance to enhance the drought resistance of various crops, and significant progress has been made with regard to drought avoidance and drought tolerance. With increasing knowledge to comprehensively decipher the complicated mechanisms of drought resistance in model plants, it still remains an enormous challenge to develop water-saving and drought-resistant crops to cope with the water shortage and increasing demand for food production in the future.

  5. Challenges of agricultural monitoring: integration of the Open Farm Management Information System into GEOSS and Digital Earth

    NASA Astrophysics Data System (ADS)

    Řezník, T.; Kepka, M.; Charvát, K.; Charvát, K., Jr.; Horáková, S.; Lukas, V.

    2016-04-01

    From a global perspective, agriculture is the single largest user of freshwater resources, each country using an average of 70% of all its surface water supplies. An essential proportion of agricultural water is recycled back to surface water and/or groundwater. Agriculture and water pollution is therefore the subject of (inter)national legislation, such as the Clean Water Act in the United States of America, the European Water Framework Directive, and the Law of the People's Republic of China on the Prevention and Control of Water Pollution. Regular monitoring by means of sensor networks is needed in order to provide evidence of water pollution in agriculture. This paper describes the benefits of, and open issues stemming from, regular sensor monitoring provided by an Open Farm Management Information System. Emphasis is placed on descriptions of the processes and functionalities available to users, the underlying open data model, and definitions of open and lightweight application programming interfaces for the efficient management of collected (spatial) data. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture pollution monitoring. The final part of the paper deals with the integration of the Open Farm Management Information System into the Digital Earth framework.

  6. Assessing and monitoring soil quality at agricultural waste disposal areas-Soil Indicators

    NASA Astrophysics Data System (ADS)

    Doula, Maria; Kavvadias, Victor; Sarris, Apostolos; Lolos, Polykarpos; Liakopoulou, Nektaria; Hliaoutakis, Aggelos; Kydonakis, Aris

    2014-05-01

    The necessity of elaborating indicators is one of the priorities identified by the United Nations Convention to Combat Desertification (UNCCD). The establishment of an indicator monitoring system for environmental purposes is dependent on the geographical scale. Some indicators such as rain seasonality or drainage density are useful over large areas, but others such as soil depth, vegetation cover type, and land ownership are only applicable locally. In order to practically enhance the sustainability of land management, research on using indicators for assessing land degradation risk must initially focus at local level because management decisions by individual land users are taken at this level. Soils that accept wastes disposal, apart from progressive degradation, may cause serious problems to the surrounding environment (humans, animals, plants, water systems, etc.), and thus, soil quality should be necessarily monitored. Therefore, quality indicators, representative of the specific waste type, should be established and monitored periodically. Since waste composition is dependent on their origin, specific indicators for each waste type should be established. Considering agricultural wastes, such a specification, however, could be difficult, since almost all agricultural wastes are characterized by increased concentrations of the same elements, namely, phosphorous, nitrogen, potassium, sulfur, etc.; contain large amounts of organic matter; and have very high values of chemical oxygen demand (COD), biochemical oxygen demand (BOD), and electrical conductivity. Two LIFE projects, namely AgroStrat and PROSODOL are focused on the identification of soil indicators for the assessment of soil quality at areas where pistachio wastes and olive mill wastes are disposed, respectively. Many soil samples were collected periodically for 2 years during PROSODOL and one year during AgroStrat (this project is in progress) from waste disposal areas and analyzed for 23 parameters

  7. Hydrological drought typology: temperature-related drought types and associated societal impacts

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

    For drought management and prediction, knowledge of causing factors and socio-economic impacts of hydrological droughts is crucial. Propagation of meteorological conditions in the hydrological cycle results in different hydrological drought types that require separate analysis. In addition to the existing hydrological drought typology, we here define two new drought types related to snow and ice. A snowmelt drought is a deficiency in the snowmelt discharge peak in spring in snow-influenced basins and a glaciermelt drought is a deficiency in the glaciermelt discharge peak in summer in glacierised basins. In 21 catchments in Austria and Norway we studied the meteorological conditions in the seasons preceding and at the time of snowmelt and glaciermelt drought events. Snowmelt droughts in Norway were mainly controlled by below-average winter precipitation, while in Austria both temperature and precipitation played a role. For glaciermelt droughts the effect of below-normal summer temperature was dominant, both in Austria and Norway. Subsequently, we investigated the impacts of temperature-related drought types (i.e. snowmelt and glaciermelt drought, but also cold and warm snow season drought and rain-to-snow-season drought). In historical archives and drought databases for the US and Europe many impacts were found that can be attributed to these temperature-related hydrological drought types, mainly in the sectors agriculture and electricity production (hydropower). However, drawing conclusions on the frequency of occurrence of different drought types from reported impacts is difficult, mainly because of reporting biases and the inevitably limited spatial and temporal scales of the information. This study shows that the combination of quantitative analysis of causing factors and qualitative analysis of impacts of temperature-related droughts is a promising approach to identify relevant drought types in other regions, especially if more data on drought impacts become

  8. A prototype Global Drought Information System based on multiple land surface models

    NASA Astrophysics Data System (ADS)

    Nijssen, Bart; Shukla, Shrad; Lin, Chi-Yu; Lettenmaier, Dennis

    2013-04-01

    Droughts are pervasive natural hazards, which cause large economic losses and human suffering. While the absolute magnitude of these losses is greatest in the developed world, the relative impact is much higher in the developing world. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited. This ability is of particular importance in estimating regional crop production and thus current and future prices of agricultural commodities, as well as the implementation of emergency measures in areas where the effects of drought threaten lives and livelihoods. We describe the implementation of a multi-model drought monitoring system, which provides near real-time estimates of soil moisture conditions for the global land areas between 50S and 50N with a latency of about one day. The system is an extension of similar systems developed by both the University of Washington and the National Centers for Environmental Prediction for use in the U.S. Drought Monitor. Global application of the protocols used in the U.S. systems poses new challenges, particularly with respect to the generation of meteorological forcings with which to drive the land surface models used in such a system. The global system we describe uses satellite-based precipitation (as contrasted with gridded station data in the U.S. systems) as well as temperature estimates based on global weather model analysis fields to track the evolution of soil moisture in near real-time at a spatial resolution of 0.5 degree using multiple land surface models. By comparing the modeled, near real-time soil moisture values with the results from long-term retrospective simulations, the model estimates can be placed in historic context (as soil moisture percentiles) and used to monitor the development of droughts around the world. We evaluate the performance of our system for historic droughts, and compare with other drought analyses and analytical

  9. Biological monitoring of organophosphorus pesticide exposure among children of agricultural workers in central Washington State.

    PubMed Central

    Loewenherz, C; Fenske, R A; Simcox, N J; Bellamy, G; Kalman, D

    1997-01-01

    Children up to 6 years of age who lived with pesticide applicators were monitored for increased risk of pesticide exposure: 48 pesticide applicator and 14 reference families were recruited from an agricultural region of Washington State in June 1995. A total of 160 spot urine samples were collected from 88 children, including repeated measures 3-7 days apart. Samples were assayed by gas chromatography flame photometric detector for dimethylphosphate metabolites. Dimethylthiophosphate (DMTP) was the dominant metabolite. DMTP levels were significantly higher in applicator children than in reference children (p = 0.015), with median concentrations of 0.021 and 0.005 microg/ml, respectively; maximum concentrations were 0.44 and 0.10 microg/ml, respectively. Percentages of detectable samples were 47% for applicator children and 27% for reference children. A marginally significant trend of increasing concentration was observed with decreasing age among applicator children (p = 0.060), and younger children within these families had significantly higher concentrations when compared to their older siblings (p = 0.040). Applicator children living less than 200 feet from an orchard were associated with higher frequency of detectable DMTP levels than nonproximal applicator children (p =0.036). These results indicate that applicator children experienced higher organophosphorus pesticide exposures than did reference children in the same community and that proximity to spraying is an important contributor to such exposures. Trends related to age suggest that child activity is an important variable for exposure. It is unlikely that any of the observed exposures posed a hazard of acute intoxication. This study points to the need for a more detailed understanding of pesticide exposure pathways for children of agricultural workers. Images Figure 1. Figure 2. Figure 3. PMID:9405329

  10. AgriSense-STARS: Advancing Methods of Agricultural Monitoring for Food Security in Smallholder Regions - the Case for Tanzania

    NASA Astrophysics Data System (ADS)

    Dempewolf, J.; Becker-Reshef, I.; Nakalembe, C. L.; Tumbo, S.; Maurice, S.; Mbilinyi, B.; Ntikha, O.; Hansen, M.; Justice, C. J.; Adusei, B.; Kongo, V.

    2015-12-01

    In-season monitoring of crop conditions provides critical information for agricultural policy and decision making and most importantly for food security planning and management. Nationwide agricultural monitoring in countries dominated by smallholder farming systems, generally relies on extensive networks of field data collectors. In Tanzania, extension agents make up this network and report on conditions across the country, approaching a "near-census". Data is collected on paper which is resource and time intensive, as well as prone to errors. Data quality is ambiguous and there is a general lack of clear and functional feedback loops between farmers, extension agents, analysts and decision makers. Moreover, the data are not spatially explicit, limiting the usefulness for analysis and quality of policy outcomes. Despite significant advances in remote sensing and information communication technologies (ICT) for monitoring agriculture, the full potential of these new tools is yet to be realized in Tanzania. Their use is constrained by the lack of resources, skills and infrastructure to access and process these data. The use of ICT technologies for data collection, processing and analysis is equally limited. The AgriSense-STARS project is developing and testing a system for national-scale in-season monitoring of smallholder agriculture using a combination of three main tools, 1) GLAM-East Africa, an automated MODIS satellite image processing system, 2) field data collection using GeoODK and unmanned aerial vehicles (UAVs), and 3) the Tanzania Crop Monitor, a collaborative online portal for data management and reporting. These tools are developed and applied in Tanzania through the National Food Security Division of the Ministry of Agriculture, Food Security and Cooperatives (MAFC) within a statistically representative sampling framework (area frame) that ensures data quality, representability and resource efficiency.

  11. California's Drought - Stress test for the future

    NASA Astrophysics Data System (ADS)

    Lund, J. R.

    2014-12-01

    The current California drought is in its third dry years, with this year being the third driest years in a 106-year record. This drought occurs at a time when urban, agricultural, and environmental water demands have never been greater. This drought has revealed the importance of more quantitative evaluation and methods for water assessment and management. All areas of water and environmental management are likely to become increasingly stressed, and have essentially drought-like conditions, in the future, as California's urban, agricultural, and environmental demands continue to expand and as the climate changes. In the historical past, droughts have pre-viewed stresses developing in the future and helped focus policy-makers, the public, and stakeholders on preparing for these developing future conditions. Multi-decade water management strategies are often galvinized by drought. Irrigation was galvanized by California droughts in the 1800s, reservoir systems by the 1928-32 drought, urban water conservation by the 1976-77 drought, and water markets by the 1988-92 drought. With each drought, demands for tighter accounting, rights, and management have increased. This talk reviews the prospects and challenges for increased development and use of water data and systems analysis in the service of human and environmental water demands in California's highly decentralized water management system, and the prospects if these challenges are not more successfully addressed.

  12. Stimulating innovation for global monitoring of agriculture and its impact on the environment in support of GEOGLAM

    NASA Astrophysics Data System (ADS)

    Bydekerke, Lieven; Gilliams, Sven; Gobin, Anne

    2015-04-01

    There is an urgent need to ensure food supply for a growing global population. To enable a sustainable growth of agricultural production, effective and timely information is required to support decision making and to improve management of agricultural resources. This requires innovative ways and monitoring methods that will not only improve short-term crop production forecasts, but also allow to assess changes in cultivation practices, agricultural areas, agriculture in general and, its impact on the environment. The G20 launched in June 2011 the "GEO Global Agricultural Monitoring initiative (GEOGLAM), requesting the GEO (Group on Earth Observations) Agricultural Community of Practice to implement GEOGLAM with the main objective to improve crop yield forecasts as an input to the Agricultural Market Information System (AMIS), in order to foster stabilisation of markets and increase transparency on agricultural production. In response to this need, the European Commission decided in 2013 to fund an international partnership to contribute to GEOGLAM and its research agenda. The resulting SIGMA project (Stimulating Innovation for Global Monitoring of Agriculture), a partnership of 23 globally distributed expert organisations, focusses on developing datasets and innovative techniques in support of agricultural monitoring and its impact on the environment in support of GEOGLAM. SIGMA has 3 generic objectives which are: (i) develop and test methods to characterise cropland and assess its changes at various scales; (ii) develop and test methods to assess changes in agricultural production levels; and; (iii) study environmental impacts of agriculture. Firstly, multi-scale remote sensing data sets, in combination with field and other ancillary data, will be used to generate an improved (global) agro-ecological zoning map and crop mask. Secondly, a combination of agro-meteorological models, satellite-based information and long-term time series will be explored to assess crop

  13. Adaptation of an ambient ion monitor for detection of amines in gas and particulate agricultural emissions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Volatile amines are emitted from many sources including agricultural facilities. Recent work has shown that amines may be important players in secondary aerosol formation. Because amine emissions are significantly lower than ammonia, previous measurements and emission studies at agricultural facilit...

  14. 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.

  15. Operational 333m Biophysical Products of the Copernicus Global Land Service for Agriculture Monitoring

    NASA Astrophysics Data System (ADS)

    Lacaze, R.; Smets, B.; Baret, F.; Weiss, M.; Ramon, D.; Montersleet, B.; Wandrebeck, L.; Calvet, J.-C.; Roujean, J.-L.; Camacho, F.

    2015-04-01

    The Copernicus Global Land service provides continuously a set of bio-geophysical variables describing, over the whole globe, the vegetation dynamic, the energy budget at the continental surface and some components of the water cycle. These generic products serve numerous applications including agriculture and food security monitoring. The portfolio of the Copernicus Global Land service contains Essential Climate Variables like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, the Land Surface Temperature, the soil moisture, the burnt areas, the areas of water bodies, and additional vegetation indices. They are generated every hour, every day or every 10 days on a reliable automatic basis from Earth Observation satellite data. Beside this timely production, the available historical archives have been processed, using the same innovative algorithms, to get consistent time series as long as possible. All products are accessible, free of charge after registration through FTP/HTTP (A Unified Cropland Layer at 250-m for global agriculture monitoring

    USGS Publications Warehouse

    Waldner, François; Fritz, Steffen; Di Gregorio, Antonio; Plotnikov, Dmitry; Bartalev, Sergey; Kussul, Nataliia; Gong, Peng; Thenkabail, Prasad S.; Hazeu, Gerard; Klein, Igor; Löw, Fabian; Miettinen, Jukka; Dadhwal, Vinay Kumar; Lamarche, Céline; Bontemps, Sophie; Defourny, Pierre

    2016-01-01

    Accurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and permits isolation of the agricultural component to focus on food security and impacts of various climatic scenarios. However, despite its critical importance, accurate information on the spatial extent, cropland mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification and collection of existing land cover maps, a multi-criteria analysis was designed at the country level to evaluate the fitness of a cropland map with regards to four dimensions: its timeliness, its legend, its resolution adequacy and its confidence level. As a result, a Unified Cropland Layer that combines the fittest products into a 250 m global cropland map was assembled. With an evaluated accuracy ranging from 82% to 95%, the Unified Cropland Layer successfully improved the accuracy compared to single global products.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    As the world's water resources come under increasing tension due to the dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. However, direct validation of ET models is challenging due to lack of available observations that are sufficiently representative at the model grid scale (10-100 km). Prognostic land-surface models require accurate information about observed precipitation, soil moisture storage, groundwater, and artificial controls on water supply (e.g., irrigation, dams, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared remote sensing of land-surface temperature (LST) as a boundary condition. One such method, the Atmosphere Land Exchange Inverse (ALEXI) model provides estimates of surface energy fluxes through the use of mid-morning change in LST and radiation inputs. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil evaporation and canopy transpiration. Additionally, the Evaporative Stress Index (ESI) representing anomalies in the ratio of actual-to-potential ET has shown to be a reliable indicator of drought. ESI maps over the continental US show good correspondence with standard drought metrics and with patterns of precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Furthermore, ESI is a measure of actual stress rather than potential for stress, and has physical relevance to projected crop development. Because precipitation is not used in construction of the ESI, it provides an independent assessment of drought conditions and has particular utility for real-time monitoring in regions with sparse rainfall data or

  17. 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.

  18. Monitoring agricultural crops using a light-weight hyperspectral mapping system for unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Kooistra, Lammert; Suomalainen, Juha; Franke, Jappe; Bartholomeus, Harm; Mücher, Sander; Becker, Rolf

    2014-05-01

    Remote sensing has been identified as a key technology to allow near real-time detection and diagnosis of crop status at the field level. Although satellite based remote sensing techniques have already proven to be relevant for many requirements of crop inventory and monitoring, they might lack flexibility to support anomaly detection at specific moments over the growing season. Imagery taken from unmanned aerial vehicles (UAV) are shown to be an effective alternative platform for crop monitoring, given their potential of high spatial and temporal resolution, and their high flexibility in image acquisition programming. In addition, several studies have shown that an increased spectral resolution as available from hyperspectral systems provide the opportunity to estimate biophysical properties like leaf-area-index (LAI), chlorophyll and leaf water content with improved accuracies. To investigate the opportunities of unmanned aerial vehicles (UAV) in operational crop monitoring, we have developed a light-weight hyperspectral mapping system (< 2 kg) suitable to be mounted on small UAVs. Its composed of an octocopter UAV-platform with a pushbroom spectrometer consisting of a spectrograph, an industrial camera functioning as frame grabber, storage device, and computer, a separate INS and finally a photogrammetric camera. The system is able to produce georeferenced and georectified hyperspectral data cubes in the 400-1000 nm spectral range at 10-50 cm resolution. The system is tested in a fertilization experiment for a potato crop on a 12 ha experimental field in the South of the Netherlands. In the experiment UAV-based hyperspectral images were acquired on a weekly basis together with field data on chlorophyll as indicator for the nitrogen situation of the crop and leaf area index (LAI) as indicator for biomass status. Initially, the quality aspects of the developed light-weight hyperspectral mapping system will presented with regard to its radiometric and geometric

  19. Predictors of Ips confusus Outbreaks During a Record Drought in Southwestern USA: Implications for Monitoring and Management

    NASA Astrophysics Data System (ADS)

    Santos, Maria J.; Whitham, Thomas G.

    2010-02-01

    In many ecosystems the effects of disturbance can be cryptic and disturbance may vary in subtle spatiotemporal ways. For instance, we know that bark beetle outbreaks are more frequent in temperate forests during droughts; however, we have little idea about why they occur in some locations and not others. Understanding biotic and abiotic factors promoting bark beetle outbreaks can be critical to predicting and responding to pest outbreaks. Here we address the environmental factors which are associated with Ips confusus outbreaks during the 2002 widespread drought within the distribution range of pinyon pine woodlands in Arizona. We used univariate statistics to test if whether tree characteristics, other herbivores, stand properties, soil type, wind, and topography were associated with I. confusus outbreak, and logistic regression to create a predictive model for the outbreaks. We found that I. confusus attacks occur in low elevation stands on steeper slopes, where favorable winds for I. confusus dispersion occur. I. confusus se