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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. 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...

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  9. 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

  10. 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

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

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

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

  12. The 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. 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...

  15. 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...

  16. 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).

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

    PubMed

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

    2013-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Ryu, J.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  4. 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.

  5. 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.

  6. 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.

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

    PubMed

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

    2013-12-01

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

  8. 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...

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  12. 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.

  13. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. 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 ...

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  19. 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.

  20. Monitoring groundwater drought with GRACE data assimilation

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  1. Risk identification of agricultural drought for sustainable agroecosystems

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

    Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20 year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic

  2. Risk identification of agricultural drought for sustainable Agroecosystems

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

    Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than

  3. 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

  4. 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

  5. Global integrated drought monitoring and prediction system.

    PubMed

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

    2014-01-01

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

  6. 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

  7. 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.

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. Drought monitoring through parallel computing

    SciTech Connect

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

    1993-12-31

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

  15. 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.

  16. 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

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. Drought assessment using MODIS products in an agricultural setting of Mississippi Delta

    NASA Astrophysics Data System (ADS)

    Mukherjee, A.

    2012-12-01

    Early 21st century climate has become erratic in nature and droughts which cause severe damages especially in the agricultural area tends to be a recurrent phenomenon throughout the world. The alluvial plain of Mississippi Delta is well suited for agriculture and a quick drought monitoring technique is needed for better management of resources. Due to the logistical sampling difficulties, it is impractical to conduct field monitoring of droughts. Remote sensing is an attractive alternate method since it is fast and cost effective. It is therefore our purpose in this pilot study to investigate the possibility of using information from the Moderate Resolution Imaging Spectroradiometer (MODIS) products which are free and readily available to monitor seasonal drought in agricultural settings in Mississippi Delta. The objective of this study is to explore and investigate the feasibility of readily available satellite derived data for measuring and monitoring drought in the agricultural area of Mississippi delta. The specific objectives are- 1) to create a MODIS derived normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) time series database, 2) evaluation of the relationship between NDVI, NDWI, and other relevant indices and 3) the generation of a new vegetation drought index, the normalized difference drought index (NDDI) for the study area to compare with the U.S. Drought Monitor (USDM) maps. Interactions among all these parameters which are actually the derivatives of MODIS 8-day 500 meter surface reflectance data (MOD09A1) are being investigated for the purpose of drought assessment. MODIS time series data will be collected, stored, analyzed and the relationships between various drought indices over an agricultural setting in Mississippi delta will be presented.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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

  13. Effective monitoring of agriculture.

    PubMed

    Lindenmayer, David B; Likens, Gene E

    2011-06-01

    An opinion piece published in Nature proposed a global network for agricultural monitoring [J. Sachs, R. Remans, S. Smukler, L. Winowiecki, S. J. Andelman, K. G. Cassman, D. Castle, R. DeFries, G. Denning, J. Fanzo, L. E. Jackson, R. Leemans, J. Leemans, J. C. Milder, S. Naeem, G. Nziguheba, C. A. Palm, J. P. Reganold, D. D. Richter, S. J. Scherr, J. Sircely, C. Sullivan, T. P. Tomich and P. A. Sanchez, Nature, 2010, 466, 558-560.]. Whilst we agree with Sachs et al. that monitoring of agricultural systems is a critically important activity of global significance, especially given increasing problems with global food security and the potential impacts of agriculture on the environment [J. Cribb, The Coming Famine. The Global Food Crisis and What We Can Do to Avoid It, CSIRO Publishing and University of California Press, Melbourne and Oakland, 2010.], we argue in this paper that their generic, mandated monitoring framework has a high probability of failure or at best will be highly inefficient. We base this conclusion on our recently published examination of the factors influencing the success or failure of monitoring programs worldwide [D. B. Lindenmayer and G. E. Likens, Effective Ecological Monitoring, CSIRO Publishing and Earthscan, Melbourne and London, 2010.]. We briefly outline what we believe are three serious flaws in the monitoring framework proposed by Sachs et al. We then suggest an alternative approach that we argue would be more effective, more efficient, and have a greater chance of successfully addressing key issues in sustainable agriculture. PMID:21479312

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  16. 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.

  17. Trends in meteorological and agricultural droughts in Iran

    NASA Astrophysics Data System (ADS)

    Golian, S.; Mazdiyasni, O.; AghaKouchak, A.

    2015-02-01

    The aim of this paper is to investigate characteristics of meteorological and agricultural droughts and their trends in Iran, as well as several subregions with different climate conditions from 1980 to 2013. The Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) are used as the primary indicators of meteorological and agricultural droughts, respectively. This study assesses historical droughts using the Multivariate Standardized Drought Index (MSDI), which provides a composite model of meteorological-agricultural drought. Furthermore, this study discusses the behavior of MSDI relative to the other indices (SPI and SSI) over different climatic conditions ranging from humid, semiarid, and hyperarid regions. The Mann-Kendall trend test shows that the northern, northwestern, and central parts of Iran have experienced significant drying trends at a 95 % confidence level. However, no statistically significant drying trend was observed in the eastern part of Iran. The most severe drought across the country occurred between 1998 and 2001, with approximately 80 % of the country experiencing an exceptional drought (<2 % probability of occurrence). This event coincided with a prolonged cold phase El Niño-Southern Oscillation (La Niña) that led to persistently cold sea surface temperatures in the eastern Pacific and warm sea surface temperatures in the Indian and western Pacific.

  18. Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982-2011 by using PDSI indices and agriculture drought survey data

    NASA Astrophysics Data System (ADS)

    Yan, Hao; Wang, Shao-Qiang; Wang, Jun-Bang; Lu, Hou-Quan; Guo, An-Hong; Zhu, Zai-Chun; Myneni, Ranga B.; Shugart, Herman H.

    2016-03-01

    Inspired by concerns of the effects of a warming climate, drought variation and its impacts have gained much attention in China. Arguments about China's drought persist and little work has utilized agricultural drought survey area to evaluate the impact of natural drought on agriculture. Based on a newly revised self-calibrating Palmer Drought Severity Index (PDSI) model driven with air-relative-humidity-based two-source (ARTS) E0 (PDSIARTS; Yan et al., 2014), spatial and temporal variations of drought were analyzed for 1982-2011 in China, which indicates that there was nonsignificant change of drought over this interval but with an extreme drought event happened in 2000-2001. However, using air temperature (Ta)-based Thornthwaite potential evaporation (EP_Th) and Penman-Monteith potential evaporation (EP_PM) to drive the PDSI model, their corresponding PDSITh and PDSIPM all gave a significant drying trend for 1982-2011. This suggests that PDSI model was sensitive to EP parameterization in China. Annual drought-covered area from agriculture survey was initially adopted to evaluate impact of PDSI drought on agriculture in China during 1982-2011. The results indicate that PDSIARTS drought area (defined as PDSIARTS < -0.5) correlated well with the agriculture drought-covered area and PDSIARTS successfully detected the extreme agriculture drought in 2000-2001 during 1982-2011, i.e., climate factors dominated the interannual changes of agriculture drought area, while PDSITh and PDSIPM drought areas had no relationship with the agriculture drought-covered area and overestimated the uptrend of agriculture drought This study highlights the importance of coupling PDSI with drought survey data in evaluating the impact of natural drought on agriculture.

  19. 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...

  20. 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

  1. 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

  2. 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

  3. 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. PMID:22200944

  4. 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

  5. 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

  6. 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.

  7. Categorisation of Drought Indices Used in Agricultural Meteorology

    NASA Astrophysics Data System (ADS)

    Dunkel, Z.

    2009-09-01

    The research and the operative work use many type of indices in everyday meteorological practice. The goal of present summary is to group the indices used for identification of drought phenomenon in the agricultural meteorology practice. Besides summarising the indices the different drought definitions are evaluated. Drought indices seem to be the simplest tools in drought analysis. The more or less well known and popular indices have been collected and compared not only with the well known simple but more complicated water balance and so called ‘recursive' indices beside few ones use remotely sensed data, mainly satellite born information. The indices are classified into five groups, namely ‘precipitation', ‘water balance', ‘soil moisture', ‘recursive' and ‘remote sensing' indices. For every group typical expressions are given and analysed for their performance and comparability. Taking into consideration that the drought is a compound concept few drought definitions are examined together with the drought indices. As any classification the presented categories have got their limitation but the hope is that as wide review is given as it is possible using mainly meteorological data and information.

  8. Mapping Subfield-Scale Evapotranspiration to Assess Agricultural Drought Sensitivity

    NASA Astrophysics Data System (ADS)

    Zipper, S. C.; Loheide, S. P., III

    2014-12-01

    Assessing crop response to drought on the subfield-scale is critical for efficient agricultural water management and yield forecasting. Evapotranspiration provides a direct physical link between the soil, crop canopy, and the atmosphere, and is hence highly sensitive to changes in water availability. Here, we introduce a new surface energy balance model (High Resolution Mapping of Evapotranspiration; HRMET) that can map ET at very high resolution (meter-scale) requiring only canopy surface temperature, canopy structure, and meteorology as inputs. HRMET can be used in both open and closed canopy conditions. We validate HRMET over two commercial cornfields in the Yahara River Watershed (south-central Wisconsin, USA) and investigate the spatially variable ET response to severe drought conditions during the 2012 growing season. Results show that the magnitude of within-field ET variability is much larger when the drought is more severe. We then introduce a new metric, Relative ET (ETR), which normalizes ET on a field scale and allows for direct comparison across measurement dates, despite differences in meteorological conditions and crop growth stage. Using a novel paired-image technique, we use persistent patterns of ETR identify portions of the field that are most susceptible to drought, and portions that are consistently productive across measurement dates. These results have implications for precision agriculture and irrigation efficiency in addition to water management and yield forecasting, as identification of persistent patterns in crop productivity during low-stress periods allows farmers to direct resources to the most sensitive areas early in droughts.

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

    NASA Astrophysics Data System (ADS)

    Mariotti, A.; Barrie, D.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    1999-03-01

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

  13. 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

  14. 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

    2015-05-01

    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

  15. 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.

  16. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

  18. 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. PMID:26676009

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  2. 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

  3. Integrating effective drought index (EDI) and remote sensing derived parameters for agricultural drought assessment and prediction in Bundelkhand region of India

    NASA Astrophysics Data System (ADS)

    Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.

    2014-11-01

    Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product

  4. Agriculture drought risk assessment of the irrigated agriculture zone in North Henan Plain using HJ-1 and MODIS data

    NASA Astrophysics Data System (ADS)

    He, Haixia; Huang, He; Wang, Ping; Sun, Yinxiang

    2011-12-01

    This paper analyzed the evolution of drought and the spectral response of the crop at different growing seasons focuses on the irrigated agricultural areas of northen Henan using the HJ-1 data and MODIS data,associated with relevant meteologic data, regional geographical data and the social economic data.The Spatial and temporal distribution of the risk of disaster-causing factors and the fragility of the disaster-affected body was conducted and the comprehensive index of agricultral drought risk was built up.Then, trend of the agricultural drought was analyzed and the irrigated agricultural drought risk class was performed and the possible hazard and influence of agricultural drought and the performance of appropriate strategy to reduce agricultral drought have been estimated.At last,verification of the results and improvement of the model have been carried out supported by the historic cases, expert system and the on-site investigation data.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  9. 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

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  12. 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.

  13. 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

  14. 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

  15. Drought vulnerability assessment for the agriculture: a case study for the west part of Slovenia

    NASA Astrophysics Data System (ADS)

    Slejko, M.; Gregorič, G.; Bergant, K.

    2009-04-01

    One of the main aspects of drought adaptation and planning is the assessment of vulnerability. Since agriculture is the primary sector affected by drought and is directly dependent on water availability, we have started with a pilot project in an important agricultural area in the west part of Slovenia. The project is a part of the activities of the Drought Management Centre for Southeastern Europe - DMCSEE. Drought in this area often results in significant economic, environmental, and social impacts. The significance of the impacts of drought on the agricultural sector is assessed taking into account the severity of the drought (magnitude and duration of the drought episode) and the vulnerability of the agricultural system. For that purpose we have developed a general method which can be used as a preliminary tool for assessing drought vulnerability in agriculture and that could be applied on the entire Southeastern Europe region. The approach was based on impact assessment and vulnerability model supported by geographic information system (GIS) software. We found out that factors influencing drought vulnerability were numerous, and the model application might depend on data availability. We have used appropriate and available digital data layers for climate, pedology, solar radiation, land use, irrigation infrastructure and other factors. The final product is a categorical map of agricultural drought vulnerability for the study area, which synthesizes a variety of data and serves as an indicator of areas deserving a detailed drought risk evaluation. It could aid regional decision makers in identifying appropriate mitigation and adaptation actions before the next drought event, lessen impacts of that event and allow sustainable development of the sector.

  16. 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

  17. 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.

  18. 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 .

  19. 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.

  20. 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

  1. Application of Assimilated GRACE Data for Drought Monitoring

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. Adapting irrigated agriculture to drought in the San Joaquin Valley of California

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Webster’s dictionary defines drought as a continuous state of dryness but does not identify a cause for that dryness, just the existence. Irrigated agriculture is in a continuous state of drought by definition, simply because water is supplied by stored surface or groundwater supplies. This results ...

  3. 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/.

  4. 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

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

    USGS Publications Warehouse

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

    2008-01-01

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

  6. 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

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  9. 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

  10. 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

  11. 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

  12. Assessing and Mapping Drought Vulnerability in Agricultural Systems - A case Study for Slovenia

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

    Drought is a recurrent meteorological phenomenon. During recent years there is a rising concern about the increasing frequency of droughts and the ecological, economic and social aspects of their impact, especially because of the possible correlations between droughts and climate change. In the past decade there were four severe agricultural droughts on the territory of Slovenia, which resulted in the damage of most of non-irrigated crops and considerable economic loss. To minimize the impact of such phenomena it is necessary to conduct a drought vulnerability assessment, which could help developing mitigation and adaptation strategies. Development of drought adaptation strategies is one of the core tasks of the Drought Management Centre for South-eastern Europe (DMCSEE). As a part of DMCSEE activities, we started with the pilot project for drought vulnerability assessment for Gori\\vska region in the western part of Slovenia in 2008 with the objective to identify principal impacts of drought and to develop a methodology for drought vulnerability assessment in agriculture. In 2009, we extended the vulnerability assessment area from our pilot region to the entire area of Slovenia. The significance of drought impact on agriculture was evaluated on a five-grade scale based on a number of criteria, which were used according to the availability of the data. We have used the available digital data for soil water-holding capacity, slope, solar radiation, land use and irrigation infrastructure. Vulnerability distributions were arranged according to administrative units - Graphical Units of Agricultural Land (GERK). In the present study, the evaluation grades were assigned subjectively, however, we are introducing objective tools and models to improve the evaluation. In the case of the assessment of the vulnerability of land use for certain types of crops in a specific GERK, we are using an irrigation scheduling model IRRFIB, which estimates water consumption by crops

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  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. 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.

  17. 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.

  18. 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.

  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. 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

  1. Food productivity trend analysis of Raichur district for the management of agricultural drought.

    PubMed

    Swathandran, Sruthi; Aslam, M A Mohammed

    2016-01-01

    Drought is an extreme climatic situation where there is a water shortage arising due to sub-normal rainfall, erratic distribution of precipitation, increased water supply demand, etc. India faced several years of drought in last six decades. As Indian agriculture is largely dependent on the monsoon, a slight change affects production as well as crop yield drastically. Statistical analysis is important for mapping the drought prone areas. Raichur district of the northern interior state of Karnataka is a drought-prone region where the economy is mainly based on agriculture. So, the uneven distribution of rainfall as well as the delay in the arrival of the southwest monsoon adversely affects the growth stage of crops which result in a decline in crop production. The effect of drought on the agriculture for the past decade has been analyzed using crop productivity data. When the production rate of Raichur district was studied for the years 1998 to 2009, it was seen that major crops like rice and jowar faced a decline in its production during the years 2002 and 2003, whereas bajra, maize, etc. mostly decreased in the year 2004. PMID:26718944

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  3. Drought 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.

  4. 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

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

    NASA Astrophysics Data System (ADS)

    Zhang, A.; Jia, G.

    2012-12-01

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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  16. 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/

  17. Exploration of diffusion kernel density estimation in agricultural drought risk analysis: a case study in Shandong, China

    NASA Astrophysics Data System (ADS)

    Chen, W.; Shao, Z.; Tiong, L. K.

    2015-11-01

    Drought caused the most widespread damage in China, making up over 50 % of the total affected area nationwide in recent decades. In the paper, a Standardized Precipitation Index-based (SPI-based) drought risk study is conducted using historical rainfall data of 19 weather stations in Shandong province, China. Kernel density based method is adopted to carry out the risk analysis. Comparison between the bivariate Gaussian kernel density estimation (GKDE) and diffusion kernel density estimation (DKDE) are carried out to analyze the effect of drought intensity and drought duration. The results show that DKDE is relatively more accurate without boundary-leakage. Combined with the GIS technique, the drought risk is presented which reveals the spatial and temporal variation of agricultural droughts for corn in Shandong. The estimation provides a different way to study the occurrence frequency and severity of drought risk from multiple perspectives.

  18. 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

  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. 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

  1. 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

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

    NASA Astrophysics Data System (ADS)

    Roundy, Joshua K.; Santanello, Joseph A.

    2015-04-01

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

  3. 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

  4. 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

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

    NASA Astrophysics Data System (ADS)

    Mariotti, Annarita; Pulwarty, Roger

    2014-05-01

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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Effective monitoring of agriculture: a response.

    PubMed

    Sachs, Jeffrey D; Remans, Roseline; Smukler, Sean M; Winowiecki, Leigh; Andelman, Sandy J; Cassman, Kenneth G; Castle, David; DeFries, Ruth; Denning, Glenn; Fanzo, Jessica; Jackson, Louise E; Leemans, Rik; Lehmann, Johannes; Milder, Jeffrey C; Naeem, Shahid; Nziguheba, Generose; Palm, Cheryl A; Pingali, Prabhu L; Reganold, John P; Richter, Daniel D; Scherr, Sara J; Sircely, Jason; Sullivan, Clare; Tomich, Thomas P; Sanchez, Pedro A

    2012-03-01

    The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. We welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on our earlier paper, "Monitoring the World's Agriculture" (Sachs et al., Nature, 2010, 466, 558-560). In this response, we address their three main critiques labeled as 'the passive approach', 'the problem with uniform metrics' and 'the problem with composite metrics'. We expand on specific research questions at the core of the network design, on the distinction between key universal and site-specific metrics to detect change over time and across scales, and on the need for composite metrics in decision-making. We believe that simultaneously measuring indicators of the three pillars of sustainability (environmentally sound, social responsible and economically viable) in an effectively integrated monitoring system will ultimately allow scientists and land managers alike to find solutions to the most pressing problems facing global food security. PMID:22293996

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  14. Analysing agricultural drought vulnerability at sub-district level through exposure, sensitivity and adaptive capacity based composite index

    NASA Astrophysics Data System (ADS)

    Murthy, C. S.; Laxman, B.; Sesha Sai, M. V. R.; Diwakar, P. G.

    2014-11-01

    Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. A quantitative approach for measuring agricultural drought vulnerability at sub-district level was developed and implemented in the current study, which was carried-out in Andhra Pradesh state, India with the data of main cropping season i.e., kharif. The contributing indicators represent exposure, sensitivity and adaptive capacity components of vulnerability and were drawn from weather, soil, crop, irrigation and land holdings related data. After performing data normalisation and variance based weights generation, component wise composite indices were generated. Agricultural Drought Vulnerability Index (ADVI) was generated using the three component indices and beta distribution was fitted to it. Mandals (sub-district level administrative units) of the state were categorised into 5 classes - Less vulnerable, Moderately vulnerable, Vulnerable, Highly vulnerable and Very highly vulnerable. Districts dominant with vulnerable Mandals showed considerably larger variability of detrended yields of principal crops compared to the other districts, thus validating the index based vulnerability status. Current status of agricultural drought vulnerability in the state, based on ADVI, indicated that vulnerable to very highly vulnerable group of Mandals represent 54 % of total Mandals and about 55 % of the agricultural area and 65 % of the rainfed crop area. The variability in the agricultural drought vulnerability at disaggregated level was effectively captured by ADVI. The vulnerability status map is useful for diagnostic analysis and for formulating vulnerability reduction plans.

  15. An agricultural drought risk-assessment model for corn and soybeans

    NASA Astrophysics Data System (ADS)

    Wu, Hong; Hubbard, Kenneth G.; Wilhite, Donald A.

    2004-05-01

    An agricultural drought risk-assessment model was developed for Nebraska, USA, for corn and soybeans on the basis of variables derived from the standardized precipitation index and crop-specific drought index using multivariate techniques. This model can be used to assess real-time agricultural drought risk for specific crops at critical times before and during the growing season by retaining previous, and adding current, weather information as the crops pass through the various development stages. This model will be helpful to decision makers, ranging from agricultural producers to policy makers and from local to national levels.The results of the model validation using three different datasets show that the risk-assessment accuracy improves as the crop develops. At the end of April, before corn is planted, the average assessment accuracy rate of drought risks on final yield is 60%. At the beginning of July, when corn is at the vegetative stage, the average assessment accuracy rate reaches 76%. In late July, when corn is at the ovule stage, the rate increases to 85%. The rates are 89% in the second half of August and the end of September, when corn is at the reproduction and ripening stages respectively. The model assessment accuracy for soybeans is lower than that for corn at the same growth stages because weather has less impact on soybeans than on corn. A reliable assessment, with 80% assessment accuracy rate, begins at mid-August, when soybeans are at pod formation stage. In early September and October, when soybeans are at pod fill and ripening stages respectively, the model is able to assess risks on soybean yield with 83% and 81% accuracy rates respectively.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  18. 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

  19. 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.

  20. 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

  1. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought assessment is a complex undertaking, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture, groundwater and surface water anomalies reflect deficiencies in mo...

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

    NASA Astrophysics Data System (ADS)

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

    2003-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  5. 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

  6. How could Mosan agriculture be impacted by climate change and future droughts ?

    NASA Astrophysics Data System (ADS)

    Bauwens, A.; Sohier, C.; Deraedt, D.; Degré, A.

    2012-04-01

    Despite the great uncertainties regarding the future climatic context, lots of studies have focused on hydrological effects of climate change on the Meuse catchment. It appears that both winter high flows and summer low flows could be exacerbated. Climate change and its impacts on hydrology will thus affect various socio-economic sectors. High flows have been widely studied compared to low-flows. This poster will put the emphasis on a methodology developed in order to study impacts of droughts on agriculture. Agriculture is among the most impacted sectors due to climate change. The consequences could be both positive as negative in accordance with the range of predicted changes and the adaptation capacity of agricultural systems. Most of the existing studies related to climate change on agriculture focused on specific territory. Within the AMICE Interreg IVB project, a transnational approach has been developed to assess droughts impacts on agriculture through the Meuse basin. The project's previous works gave us a common scenario of climate trends and of the evolution of the hydrology in the Meuse basin. The methodology is based on the use of a physically-based model able to simulate the water-soil-plant continuum (derived from EPIC model). In order to be transferable from one country to another, the methodology proposed used data available at the basin scale. The UE soil data base was complemented with local information on agricultural practices and statistics. Three crops have been studied: maize, wheat and barley. The basic cultural calendar is supposed to be the same for the different countries. The methodology developed permits to study the evolution of yields, leaf area index, crops stress due to excess or lack of water through time under different scenarios build up in the frame of the project. It appears that corn is negatively affected by climate change, and thus despite the CO2 fertilization effect. Wheat and barley have similar behavior and are

  7. 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

  8. 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

  9. A Multi-Sensor Approach for Satellite Soil Moisture Monitoring for Agricultural Climate Risk Assessment

    NASA Astrophysics Data System (ADS)

    Champagne, C.; Cherneski, P.; Hadwen, T. A.; Davidson, A.

    2014-12-01

    Satellite missions specifically dedicated to soil moisture retrieval have become a reality in the past few years, with the launch of SMOS in 2009 and SMAP in 2014. While much of the work on applications around these missions has focussed on data assimilation systems for numerical weather prediction, there is also potential to use the data to support agricultural applications such as drought and flood assessment and yield forecasting. Previous work has examined the potential for using SMOS soil moisture for detecting spatial and temporal patterns of agroclimate risk, such as drought and excess wetness. This research builds upon that work through the examination of a data set with a longer reference period to determine if the dataset can be used as a baseline for detecting anomalies from normal conditions. Surface satellite soil moisture from a multi-sensor climate reference data set (1993 to 2010) and the SMOS surface soil moisture data (2010 - 2014) set were examined in hindsight to detect relevant trends for monitoring the climate conditions in agricultural regions of Canada. Soil moisture and soil moisture anomalies were examined against precipitation and temperature records over the relevant time periods, and compared against agroclimatic drought risk indicators, including the Palmer Drought Severity Index, the Standardized Precipitation Index and the MODIS Normalized Difference Vegetation Condition anomalies. High impact events, including the 2002 drought in the Canadian Prairies, excess wetness in the southern Manitoba in 2009 and 2011 were evaluated in detail. The potential for using these data sets in near real time to support agricultural decision making will be discussed.

  10. 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

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  13. [Spatiotemporal dynamics of maize water suitability and assessment of agricultural drought in Liaoning Province, China from 1981 to 2010].

    PubMed

    Cai, Fu; Zhang, Shu-jie; Ji, Rui-peng; Mi, Na; Wu, Jin-wen; Zhang, Yu-shu

    2015-01-01

    Maize water suitability (MWS) model was developed at growth stage scale. Frequency and severity of drought were evaluated by combining MWS estimates and agricultural meteorological drought indexes. The MWS at each growth stage was calculated by using maize observational data and conventional meteorological data at 52 sites in Liaoning during the period from 1981 to 2010. Based on the climatic trend and abrupt change analysis, spatiotemporal dynamics of MWS were investigated. Meanwhile, occurrence of agricultural drought and its severity were also estimated. The results showed that the variation of MWS largely differed at different growth stages. Climatic abrupt change happened in 1994, 1996 and 1999 at the stages of emergence to seven leaves (II), jointing to tasseling (IV) and physiological maturity to maturity (VI). During the past 30 years, MWS showed an obvious increasing trend at the stages of sowing to emergence(I) , seven leaves to jointing(III), IV and tasseling to physiological maturity(V), while it showed a decreasing trend at the stages of II and VI, and that at VI stage was statistically significant. In addition, the climatic trend of MWS showed apparently spatial variability. The frequencies of drought at different severities varied with maize growth stages. Areas of high variability of MWS were located in the Northwest and South of Liaoning at the stages of I , II , III and VI, where were also the regions of high frequency of mid- and severe-drought. At the stages of IV and V, the frequency of drought was low and only light- and mid-drought occurred in few areas. In conclusion, the regional mean MWS could be capable to reasonably assess the agricultural drought in Liaoning at the regional scale. PMID:25985675

  14. 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.

  15. 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

  16. 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

  17. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Using Thermal Remote Sensing for Drought and Evapotranspiration Monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

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

    PubMed

    Yi, Hang; Wen, Lianxing

    2016-01-01

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

  6. Droughts in Georgia

    USGS Publications Warehouse

    Barber, Nancy L.; Stamey, Timothy C.

    2000-01-01

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

  7. 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.

  8. 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

  9. 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...

  10. 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.

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

    PubMed

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

    2016-05-15

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

  12. 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...

  13. 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

  14. 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

  15. 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

  16. 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

  17. Climate Change, Agriculture and Sustainable Groundwater Management: Groundwater Reserves as a Hedge Against Climate Change and Drought (Invited)

    NASA Astrophysics Data System (ADS)

    Langridge, R.; Fisher, A. T.

    2010-12-01

    In regions of California and the Southwestern United States, climate change is projected to increase the frequency of prolonged drought events. While there is a critical need for proactive strategies to cushion the effects of future water shortages on agriculture, drought planning is essentially reactive, centered on how to manage water shortages after a dry period occurs. Our paper discusses a proactive approach to improve water supply security for agriculture during droughts, the development and maintenance of strategic groundwater reserves. This would involve bringing groundwater basins into hydrologic balance through recharge processes to reduce groundwater level decline rates and maintaining sufficient groundwater levels to sustain a reserve. Recovery of water to satisfy reasonable short-term demand would occur so long as the reserve is maintained. We discuss the physical and institutional opportunities and constraints to developing reserves in several sites along California’s north and central coast where groundwater levels have been declining and communities are particularly vulnerable to future droughts and concomitant water shortages. We examine preliminary hydrologic and social metrics for a reserve, developed on the basis of local and regional conditions, as well as mechanisms and incentives to sustain a reserve.

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

    PubMed

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

    2011-10-01

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

  19. 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...

  20. A introduction of a Scientific Research Program on Chinese Drought

    NASA Astrophysics Data System (ADS)

    Li, Y.

    2014-12-01

    Drought is one of the major meteorological disasters, with high frequencies, wide distributions and serious conditions. It is one of the biggest impacts on global agricultural productions, ecological environment and socioeconomic sustainable developments. China is particularly one of the countries in the world with serious drought disasters. The goal of this project is improving the capabilities in drought monitoring and forecasting based on an in-depth theories of drought. The project will be implemented in the typical extreme drought area based on comprehensive and systemic observation network and numerical experiments It will show a complete feedback mechanism among the atmospheric, water, biological and other spheres for forming drought. First, the atmospheric droughts that leads to agriculture and hydrologic drought and the possible causes for these disasters will be explored using our observation data sets. Second, the capability of monitoring, forecasting and early warning for drought will be developed with numerical model (regional climate model and land surface model, etc.). Last but not the least, evaluation approaches for the risk of drought and the strategy of predicting/prohibiting the drought at regional scale will be proposed. Meanwhile, service system and information sharing platform of drought monitoring and early warning will be established to improve the technical level of drought disaster preparedness and response in China.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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...

  7. 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

  8. 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

  9. 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

  10. Quantification of agricultural drought occurrence as an estimate for insurance programs

    NASA Astrophysics Data System (ADS)

    Bannayan, M.; Hoogenboom, G.

    2015-11-01

    Temporal irregularities of rainfall and drought have major impacts on rainfed cropping systems. The main goal of this study was to develop an approach for realizing drought occurrence based on local winter wheat yield loss and rainfall. The domain study included 11 counties in the state of Washington that actively grow rainfed winter wheat and an uncertainty rainfall evaluation model using daily rainfall values from 1985 to 2007. An application was developed that calculates a rainfall index for insurance that was then used to determine the drought intensity for each study year and for each study site. Evaluation of the drought intensity showed that both the 1999-2000 and 2000-2001 growing seasons were stressful years for most of the study locations, while the 2005-2006 and the 2006-2007 growing seasons experienced the lowest drought intensity for all locations. Our results are consistent with local extension reports of drought occurrences. Quantification of drought intensity based on this application could provide a convenient index for insurance companies for determining the effect of rainfall and drought on crop yield loss under the varying weather conditions of semi-arid regions.

  11. 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…

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

  15. Probabilistic drought intensification forecasts using temporal patterns of satellite-derived drought indicators

    NASA Astrophysics Data System (ADS)

    Park, Sumin; Im, Jungho; Park, Seonyeong

    2016-04-01

    A drought occurs when the condition of below-average precipitation in a region continues, resulting in prolonged water deficiency. A drought can last for weeks, months or even years, so can have a great influence on various ecosystems including human society. In order to effectively reduce agricultural and economic damage caused by droughts, drought monitoring and forecasts are crucial. Drought forecast research is typically conducted using in situ observations (or derived indices such as Standardized Precipitation Index (SPI)) and physical models. Recently, satellite remote sensing has been used for short term drought forecasts in combination with physical models. In this research, drought intensification was predicted using satellite-derived drought indices such as Normalized Difference Drought Index (NDDI), Normalized Multi-band Drought Index (NMDI), and Scaled Drought Condition Index (SDCI) generated from Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) products over the Korean Peninsula. Time series of each drought index at the 8 day interval was investigated to identify drought intensification patterns. Drought condition at the previous time step (i.e., 8 days before) and change in drought conditions between two previous time steps (e.g., between 16 days and 8 days before the time step to forecast) Results show that among three drought indices, SDCI provided the best performance to predict drought intensification compared to NDDI and NMDI through qualitative assessment. When quantitatively compared with SPI, SDCI showed a potential to be used for forecasting short term drought intensification. Finally this research provided a SDCI-based equation to predict short term drought intensification optimized over the Korean Peninsula.

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

    PubMed

    Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

    2015-01-01

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

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

    PubMed Central

    Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  19. 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.

  20. Developing Earth Observations Requirements for Global Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Whitcraft, A. K.; Becker-Reshef, I.; Vermote, E.; Justice, C. O.

    2013-12-01

    Recognizing the dynamic nature of agricultural cultivation both within and between years and across the globe, the Group on Earth Observations (GEO) is developing an agricultural monitoring (GEO-GLAM) system with the goal of enhancing the availability and use of satellite and in situ Earth observations (EO) for the generation of timely and accurate information on national, regional, and global food supply. One of the key components of the GEO-GLAM system is the coordination of satellite observations so as to ensure sufficient and appropriate data volume and quality for agricultural monitoring. Therefore, it is essential that we develop EO requirements which articulate in a spatially explicit way where, when, how frequently, and at what spatial resolution satellite imagery must be acquired to meet the needs of a variety of agricultural monitoring applications. Accordingly, best-available cropland location information ('where?') in conjunction with ten years of MODIS surface reflectance data have been used to characterize the timing and duration of the agricultural growing season ('when?') in the form of agricultural growing season calendars (GSCs) for all major agricultural areas of the Earth. With respect to temporal resolution, we must first identify the frequency with which we require imagery inputs for monitoring applications such as crop condition, crop type, crop yield estimation, and planted and harvested area estimation. Members of the GEO Agriculture Monitoring Community of Practice - a group of international scientists - have combined their knowledge and expertise to articulate these general requirements. Second, we must determine how cloud cover impacts the ability of optical sensing systems to meet these established temporal resolution requirements. To this end, MODIS Terra (morning; 2000-2011) and Aqua (afternoon; 2002-2011) observations have been analyzed to derive probabilities of a cloud free clear view at different times of day throughout the

  1. A spatially distributed hydroeconomic model to assess the effects of drought on land use, farm profits, and agricultural employment

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Torres, M. O.; Wallender, W. W.; Vosti, S.; Howitt, R.; Rodrigues, L.; Bassoi, L. H.; Panday, S.

    2009-11-01

    In this paper a high-resolution linked hydroeconomic model is demonstrated for drought conditions in a Brazilian river basin. The economic model of agriculture includes 13 decision variables that can be optimized to maximize farmers' yearly net revenues. The economic model uses a multi-input multioutput nonlinear constant elasticity of substitution (CES) production function simulating agricultural production. The hydrologic component is a detailed physics-based three-dimensional hydrodynamic model that simulates changes in the hydrologic system derived from agricultural activity while in turn providing biophysical constraints to the economic system. The linked models capture the effects of the interactions between the hydrologic and the economic systems at high spatial and temporal resolutions, ensuring that the model converges to an optimal economic scenario that takes into account the spatial and temporal distribution of the water resources. The operation and usefulness of the models are demonstrated in a rural catchment area of about 10 km2 within the São Francisco River Basin in Brazil. Two droughts of increasing intensity are simulated to investigate how farmers behave under rain shortfalls of different severity. The results show that farmers react to rainfall shortages to minimize their effects on farm profits, and that the impact on farmers depends, among other things, on their location in the watershed and on their access to groundwater.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  5. 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

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

    PubMed

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

    2004-02-01

    Based on the principle of energy balance, the method for calculating latent evaporation was simplified, and hence, the construction of the drought remote sensing monitoring model of crop water shortage index was also simplified. Since the modified model involved fewer parameters and reduced computing times, it was more suitable for the operation running in the routine services. After collecting the concerned meteorological elements and the NOAA/AVHRR image data, the new model was applied to monitor the spring drought in Guanzhong, Shanxi Province. The results showed that the monitoring results from the new model, which also took more considerations of the effects of the ground coverage conditions and meteorological elements such as wind speed and the water pressure, were much better than the results from the model of vegetation water supply index. From the view of the computing times, service effects and monitoring results, the simplified crop water shortage index model was more suitable for practical use. In addition, the reasons of the abnormal results of CWSI > 1 in some regions in the case studies were also discussed in this paper. PMID:15146625

  7. ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM: AGRICULTURAL PROGRAM REPORT 1993

    EPA Science Inventory

    This document provides a comprehensive report on the EMAP Agricultural Lands 1993 Pilot Field Program, which was conducted in Nebraska. esults of the pilot monitoring effort are presented on land use and cover, crop productivity, and soil quality (physical, chemical, and biologic...

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Heim, R. R.

    2009-12-01

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

  11. 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

  12. 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. PMID:24211568

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. 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.

  16. Multi-scale assessment of water availability and agricultural drought: from field to global scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Given growing pressures on freshwater resources due to increasing populations, evolving landuse and changing climate, there is a need for timely information on water availability and drought over a wide spectrum of spatial scales: from scales of individual farm fields to inform production decisions...

  17. Drought stress and preharvest aflatoxin contamination in agricultural commodity: Genetics, genomics and proteomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Throughout the world, aflatoxin contamination is considered one of the most serious food safety issues concerning health. Chronic problems with preharvest aflatoxin contamination occur in the southern US, and are particularly troublesome in corn, peanut, cottonseed, and tree nuts. Drought stress is...

  18. 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.

  19. 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.

  20. Nitrogen and phosphorus trend analysis in Latvia agricultural monitoring stations

    NASA Astrophysics Data System (ADS)

    Dimanta, Z.; Vircavs, V.; Veinbergs, A.; Lauva, D.; Ambramenko, K.; Gailuma, A.; VÄ«tola, I.

    2012-04-01

    Water quality depends on human activity. Intensive agriculture is one of the main sources, that cause water quality pollution and eutrophication. The use of fertilizers not only improves soil fertility, crop yield and quality, but also causes water pollution. Human activities, including the use of fertilizer, promote nutrient (nitrogen and phosphorus) concentrations in water. Compared to the 90th agricultural production in Latvia has progressed. Vulnerable zones have been specified in the country. It is situated in the region of Zemgale's south site, within the border Lithuania. There are defined requirements for water and soil protection from agricultural activity that cause nitrate pollution. The EU Nitrates Directive aim is to protect water from nitrate pollution. In Latvia defined nitrate values are: 50 mg/l NO3 or 11.2 mg/l N/NO3 and Ptot - 0.2 mg/l. As agriculture has became intensive and the use of fertilizers has grown, results indicate that the leaching potential and values of N and P has increased. Nutrients leaching in agricultural areas have observed all year in vulnerable zones, but it's values changes depending on season. The highest nutrient concentrations observe in winter and spring periods, particularly in snow and ice melting periods. The lowest values are in summer. Nutrient leaching potencial depends on precipitation, plant vegetation, season, fertilization type and soil cultivation process. N and P leaching can decrease, taking consideration the use time of fertilizers and good agricultural practices. Research objects are monitoring stations Bērze and Mellupīte with tree research scales: drainage fields, small catchments and observation wells. The research analyses N and P concentrations in groundwater (2006-2010) and drain field and small catchment runoff (1995-2010). The aim of the research is to analyze nitrate and phosphorus concentration fluctuations in a time period. To determine nutrient concentrations, water samples were collected

  1. 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.

  2. 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

  3. 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...

  4. 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

  5. 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. PMID:26642049

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Pansharpening Landsat 8 Data For Improved Agricultural Field Monitoring

    NASA Astrophysics Data System (ADS)

    Zhang, H.; Roy, D. P.

    2014-12-01

    Satellite data provide a synoptic view and have been used for agricultural applications including cropland distribution mapping, crop condition monitoring, crop production assessment, and yield prediction. The ability of satellite data to monitor agriculture reliably is dependent on many factors but is fundamentally constrained by the satellite spatial resolution relative to the field spatial dimensions. The recently launched Landsat 8 satellite has improved calibration, radiometric resolution, geometry and global data acquisition frequency over previous Landsat sensors. Pansharpening is an established technique to integrate higher spatial resolution panchromatic information with lower spatial resolution multi-spectral information. A new pansharpening algorithm is presented that is specific to Landsat 8 and that models the sensor spectral response functions to provide a universal algorithm that is computationally efficient and applicable to large volume data. Experiments conducted using Landsat 8 data acquired over agricultural regions with markedly different field dimensions in South Dakota, China, and India, are presented to demonstrate and quantify the utility of the 15m pansharpened Landsat 8 data over conventional 30m data.

  11. Assimilation of Downscaled SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions in Brazil

    NASA Astrophysics Data System (ADS)

    Chakrabarti, S.; Bongiovanni, T. E.; Judge, J.; Principe, J. C.; Fraisse, C.

    2013-12-01

    Reliable soil moisture (SM) information in the root zone (RZSM) is critical for quantification of agricultural drought impacts on crop yields and for recommending management and adaptation strategies for crop management, commodity trading and food security.The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future National Aeronautics and Space Administration-Soil Moisture Active Passive (NASA-SMAP) missions provide SM at unprecedented spatial resolutions of 10-25 km, but these resolutions are still too coarse for agricultural applications in heterogeneous landscapes, making downscaling a necessity. This downscaled near-surface SM can be merged with crop growth models in a data assimilation framework to provide optimal estimates of RZSM and crop yield. The objectives of the study include: 1) to implement a novel downscalingalgorithm based on the Information theoretical learning principlesto downscale SMOS soil moisture at 25 km to 1km in the Brazilian La Plata Basin region and2) to assimilate the 1km-soil moisture in the crop model for a normal and a drought year to understand the impact on crop yield. In this study, a novel downscaling algorithm based on the Principle of Relevant Information (PRI) was applied to in-situ and remotely sensed precipitation, SM, land surface temperature and leaf area index in the Brazilian Lower La Plata region in South America. An Ensemble Kalman Filter (EnKF) based assimilation algorithm was used to assimilate the downscaled soil moisture to update both states and parameters. The downscaled soil moisture for two growing seasons in2010-2011 and 2011-2012 was assimilated into the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model over 161 km2 rain-fed region in the Brazilian LPB regionto improve the estimates of soybean yield. The first season experienced normal precipitation, while the second season was impacted by drought. Assimilation improved yield

  12. 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.

  13. Drought-induced enrichment of soil nitrogen leads to record high nitrate loading to agricultural river networks (Invited)

    NASA Astrophysics Data System (ADS)

    Burgin, A. J.; Loecke, T. D.; Davis, C.; Ward, A. S.; St. Clair, M.; Riveros-Iregui, D.; Thomas, S. A.

    2013-12-01

    Nitrogen (N) fertilization is a cornerstone of modern agriculture, but the practice also leads to eutrophication, hypoxia, and harmful algal blooms in both inland and coastal waters. Several studies identify Iowa, Illinois and Indiana as major source areas of N discharged by the Mississippi River to the Gulf of Mexico where large-scale hypoxia develops annually. Continental-scale management of nitrogen requires a comprehensive understanding of watershed-specific hydrologic dynamics and their consequences for nitrate flushing from agricultural landscapes, as well as quantification of fertilizer export in relation to interannual climate variability. This study addresses the following questions: (1) How do climate and precipitation patterns control the magnitude and timing of nitrate flushing from agricultural landscapes; and (2) How does the stream nitrate pulse change in relation to position within the stream network? We instrumented five streams of varying order (1st to 4th) and watershed size (5 ha to 3240000 ha) with real-time nitrate sensors. We combined this information with 15 existing USGS stations, located throughout the Iowa-Cedar River basin (Iowa, USA). We then coupled 15-min nitrate measurements at selected streams with seasonal (May, July, September) synoptic sampling at 100+ locations through the basin. We demonstrate that drought-induced accumulation of soil N over winter (2012), followed by an unseasonably cool, wet spring (2013) sent record levels of stream N into the Mississippi River. Our results show extreme variations in nitrate concentrations and flux associated with pronounced wet/dry cycles, and rapid shifts in hydrologic connectivity within the same year. Information connecting storm events, antecedent environmental conditions and nutrient dynamics is critical for improving our predictions of nitrate loading to riverine networks under increased climatic variation. Furthermore, our findings clearly demonstrate that understanding and

  14. 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.

  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. Extreme Droughts In Sydney And Melbourne Since The 1850s

    NASA Astrophysics Data System (ADS)

    Dogan, Selim

    2014-05-01

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

  17. 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.

  18. 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.

  19. Probabilistic forecasting of seasonal drought behaviors in the Huai River basin, China

    NASA Astrophysics Data System (ADS)

    Xiao, Mingzhong; Zhang, Qiang; Singh, Vijay P.; Chen, Xiaohong

    2016-01-01

    The Huai River basin is one of the major supplier of agricultural products in China, and droughts have critical impacts on agricultural development. Good knowledge of drought behaviors is of great importance in the planning and management of agricultural activities in the Huai River basin. With the copula functions to model the persistence property of drought, the probabilistic seasonal drought forecasting models have been built in the Huai River basin. In this study, droughts were monitored by the Standardized Precipitation Evapotranspiration Index (SPEI) with the time scales of 3, 6, and 9 months, and their composite occurrence probability has been used to forecast the seasonal drought. Results indicated that the uncertainty related to the predicted seasonal drought is larger when more severe droughts occurred in the previous seasons, and the severe drought which occurs in summer and autumn will be more likely to be persistent in the next season while the severe drought in winter and spring will be more likely to be recovered in the subsequent season. Furthermore, given the different drought statuses in the previous season, spatial patterns of the predicted drought events with the largest occurrence probability have also been investigated, and results indicate that the Huai River basin is vulnerable to the extreme drought in most parts of the basin, e.g., the severe drought in winter will be more likely to be persistent in spring in the central part of the southern Huai River basin. Such persistent drought events pose serious challenges for planning and management of agricultural irrigation, then results of the study will be valuable for the planning of crop cultivation or mitigation of the losses caused by drought in the Huai River basin, China.

  20. 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.

  1. 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.

  2. 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. 

  3. Droughts and water scarcity: facing challenges

    NASA Astrophysics Data System (ADS)

    Pereira, Luis S.

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  5. 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.

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Assessment of drought conditions requires understanding regional historical droughts as well as the impacts on human activities during their occurrences. Traditional methods for drought assessment are mainly based on water supply indices derived from precipitation time-series alone. Thus, the main limitation for developing effective real-time drought monitoring and early warning systems in Africa is the lack of reliable and up-to-date precipitation data in many regions of the continent. A sparse distribution of rain gauges and short or incomplete rainfall historical records pose further problems. This lack of information may lead to significant errors in the estimation of statistical parameters for deriving water supply indices from the precipitation time-series. Procedures for drought detection and assessment have a particular level of uncertainty associated to the data and models used. In order to better understand the extent, severity and impact of a drought in a region, it is first necessary to improve the quality of these procedures by using the best available data, theoretical assumptions and model formulations. The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the Standardized Precipitation Index (SPI) and their impact on the possible level of confidence in drought monitoring in Africa. In order to do this, four different rainfall datasets, each available on a monthly basis, were analysed over four river basins in Africa (Oum-er-Rbia, Limpopo, Niger, and Eastern Nile) as well as at continental level. The four precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 (0.25°x0.25°), the Global Precipitation Climatology Centre (GPCC) gridded precipitation dataset V.5 (0.5°x0.5°), the Global Precipitation Climatology Project (GPCP) Global Monthly Merged Precipitation Analyses (2.5°x2.5°), and the Climate Prediction Center

  10. 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.

  11. Altered Water Extraction and Hydraulic Redistribution of Agricultural Crop Soybean at Daily Time Scales in Open-Air Elevation of CO2 under Drought

    NASA Astrophysics Data System (ADS)

    Schmitz, P. G.; Gray, S. B.; Bernacchi, C.; Leakey, A. D.; Kumar, P.; Long, S. P.

    2010-12-01

    Corn-soy land, at 70 Mha is arguably the largest single ecosystem type in the contiguous 48 states. It is anticipated that global climate change will lead to an increasing occurrence of hydrologic extremes such as droughts at the regional and local scale, significantly altering the availability of soil water to agricultural crops. By contrast rising CO2 through its suppression of stomatal conductance may counteract this. The response of this ecosystem to increase in atmospheric CO2, to the expected mid-century levels (550 μmol mol-1) has been shown at field scale using Free Air Concentration Enrichment (FACE) to decrease ET by 9-16%, for soybean (Glycine max), relative to controls. However, the feedback of soil-moisture to reduction in ecosystem ET has not been tested when increased drought and CO2 are combined in the open. While drought will lead to a reduction of volumetric water content (VWC) along the soil moisture profile, the distribution of this reduction will be innately driven by both patterns of water uptake and hydraulic redistribution by the rooting system. The ability of the crop to dynamically alter soil moisture through these strategies feed back on crop rooting strategy and the ability to extract moisture for transpiration. To examine the extent to which crops are capable of dynamically altering the distribution of soil moisture in response to both drought and elevated atmospheric CO2, soybean was grown in field conditions under ambient (approximately 385 μmol CO2 mol-1 air) and elevated [CO2] (approximately 550 μmol mol-1) using FACE. Four replicated blocks each contained a 20m diameter elevated CO2 plot and a similar control plot. Within each plot, were nested ambient precipitation and drought sub-plots (approximately 60% precipitation reduction, p textless 0.05). Drought was imposed by, the use of rain interception, canopies that were automatically deployed during night-time precipitation events and by the use of sub-surface soil

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  14. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. Global Drought Watch from Space.

    NASA Astrophysics Data System (ADS)

    Kogan, Felix N.

    1997-04-01

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

  17. 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

  18. 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

  19. 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

  20. From LACIE to GEOGLAM: Integrating Earth Observations into Operational Agricultural Monitoring Systems

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Earth observation data, owing to their synoptic, timely and repetitive coverage, have long been recognized as an indispensible tool for agricultural monitoring at local to global scales. Research and development over the past several decades in the field of agricultural remote sensing has led to considerable capacity for crop monitoring within the current operational monitoring systems. These systems are relied upon nationally and internationally to provide crop outlooks and production forecasts as the growing season progresses. This talk will discuss the legacy and current state of operational agricultural monitoring using earth observations. In the US, the National Aeronautics and Space Administration (NASA) and the US Department of Agriculture (USDA) have been collaborating to monitor global agriculture from space since the 1970s. In 1974, the USDA, NASA and National Oceanic and Atmospheric Administration (NOAA) initiated the Large Area Crop Inventory Experiment (LACIE) which demonstrated that earth observations could provide vital information on crop production, with unprecedented accuracy and timeliness, prior to harvest. This experiment spurred many agencies and researchers around the world to further develop and evaluate remote sensing technologies for timely, large area, crop monitoring. The USDA and NASA continue to closely collaborate. More recently they jointly initiated the Global Agricultural Monitoring Project (GLAM) to enhance the agricultural monitoring and the crop-production estimation capabilities of the USDA Foreign Agricultural Service by using the new generation of NASA satellite observations including from MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments. Internationally, in response to the growing calls for improved agricultural information, the Group on Earth Observations (partnership of governments and international organizations) developed the Global Agricultural Monitoring (GEOGLAM) initiative which was adopted

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

    Drought is a common phenomenon in the Limpopo River basin. In essence, droughts are long-term hydro-meteorological events affecting vast regions and causing significant non-structural damages. In the interest of riparian states' joint integrated water resources development and management of the Limpopo basin, inter regional drought severity and its impacts should be understood. The study focussed on case studies in the basin which is subdivided into four homogeneous regions owing to topographic and climate variations based on the previous work of the same authors. Using the medium range time series of the Standardized Precipitation Index (SPI) as an indicator of drought, for each homogeneous region monthly and annual Severity-Area-Frequency (SAF) curves and maps of probability of drought occurrence were constructed. The results indicated localized severe droughts in higher frequencies, while only moderate to severe low frequency droughts may spread over wider areas in the basin. The region-level Drought-Severity Indices can be used as indicators for planning localized interventions and drought mitigation efforts in the basin. The approach can also be used to develop improved drought indicators, to assess the relationship between drought hazard and vulnerability and to enhance the performance of methods currently used for drought forecasting. Results on the meteorological drought linkage with hydrological and vegetation or agricultural drought indices are presented as means of validation of the specific drought regimes and their localized impact in each homogeneous region. In general, this preliminary investigation reveals that the western part of the basin will face a higher risk of drought when compared to other regions of the Limpopo basin in terms of the medium-term drought. The Limpopo basin is water stressed and livelihood challenges remain at large, thus impacts of droughts and related resilience options should be taken into account in the formulation of

  3. 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

  4. Satellite Observations of the Epic California Drought

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  5. 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.

  6. 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

  7. 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, ...

  8. 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

  9. 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.

  10. 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.

  11. 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.

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

    USGS Publications Warehouse

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

    2011-01-01

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

  13. 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...

  14. 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

  15. 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.

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

    PubMed

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

    2014-01-01

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

  17. 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.

  18. 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.

  19. [Impact of Vegetation Structure on Drought Indices Based on MODIS Spectrum].

    PubMed

    Du, Ling-tong; Tian, Qing-jiu; Wang, Lei

    2015-04-01

    The drought indices based on MODIS spectral reflectance data are widely used for drought characterization and monitoring in agricultural context. Based on the PROSAIL model and MODIS observational data in Shandong in 2010, the present paper studied the impact of vegetation structure of leaf area index and physiological growth cycle on MODIS spectral drought index. The results showed that the reflectance of three MODIS bands in spectrum of near-infrared and shortwave infrared changes significantly with leaf water content of vegetation. Therefore, the five kinds of MODIS spectral drought index constructed by those MODIS bands can be used to monitor the leaf water content of vegetation. However, all drought indices are affected by leaf area index. In general, the impact is serious in the case of low LAI values and is weakened with the increase in LAI value. The study found that physiological vegetation growth cycle also affects the magnitude of MODIS spectral drought indices. In conclusion, the impact of vegetation structure must be carefully considered when using MODIS spectral drought indices to monitor drought. The conclusion of this study provides a theoretical basis for remote sensing of drought monitoring. PMID:26197587

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

    PubMed

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

    2015-10-01

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

  1. 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.

  2. 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.

  3. Drought prediction using GRACE observation and NOAH model simulation

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  4. 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

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

    NASA Astrophysics Data System (ADS)

    Raper, Tyson B.

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

  6. 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

  7. 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.

  8. 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.

  9. 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

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

    USGS Publications Warehouse

    U.S. Geological Survey

    2012-01-01

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

  11. 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.

  12. 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

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

    PubMed

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

    2015-07-01

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

  14. 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.

  15. 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. PMID:24162181

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Developing drought tolerant plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought and heat are major environmental factors that limit agricultural productivity. Decreased availability of arable land for agricultural production, increased water demand for urban use, and declining aquifer levels are the primary constraints placed on food and fiber production now and in the ...

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

    NASA Astrophysics Data System (ADS)

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

    2008-11-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  4. 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...

  5. Monitoring Agricultural Production in Primary Export Countries within the framework of the GEOGLAM Initiative

    NASA Astrophysics Data System (ADS)

    Becker-Reshef, I.; Justice, C. O.; Vermote, E.

    2012-12-01

    Up to date, reliable, global, information on crop production prospects is indispensible for informing and regulating grain markets and for instituting effective agricultural policies. The recent price surges in the global grain markets were in large part triggered by extreme weather events in primary grain export countries. These events raise important questions about the accuracy of current production forecasts and their role in market fluctuations, and highlight the deficiencies in the state of global agricultural monitoring. Satellite-based earth observations are increasingly utilized as a tool for monitoring agricultural production as they offer cost-effective, daily, global information on crop growth and extent and their utility for crop production forecasting has long been demonstrated. Within this context, the Group on Earth Observations developed the Global Agricultural Monitoring (GEOGLAM) initiative which was adopted by the G20 as part of the action plan on food price volatility and agriculture. The goal of GEOGLAM is to enhance agricultural production estimates through the use of Earth observations. This talk will explore the potential contribution of EO-based methods for improving the accuracy of early production estimates of main export countries within the framework of GEOGLAM.

  6. Drought-responsive protein profiles reveal diverse defense pathways in corn kernels under field drought atress

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drought stress is a major factor which contributes to disease susceptibility and yield loss in agricultural crops. To identify drought responsive proteins and explore metabolic pathways involved in maize tolerance to drought stress, two lines (B73 and Lo964) with contrasting drought sensitivity were...

  7. Drought Risk Assessment based on Natural and Social Factors

    NASA Astrophysics Data System (ADS)

    Huang, Jing; Wang, Huimin; Han, Dawei

    2015-04-01

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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. New drought indices from the assimilation of satellite data

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Application of Landsat data to map and monitor agricultural land cover

    NASA Astrophysics Data System (ADS)

    Erdenee, B.; Tana, Gegen; Tateishi, Ryutaro

    2010-11-01

    Agriculture is one of the major economic sectors of Mongolia and the country's economy is very much dependent on the development of agricultural production. Being the rural and poorest conditions of Mongolia, 60-90% of its labor force employed in agriculture and agricultural sector has a prominent economic role. Mongolian agriculture has been successful in increasing food grains production in the past, guided by the goals of self-sufficiency in the country. The satellite imagery has been effectively utilized for classifying land cover types and detecting land cover conditions. Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. Objective of this study to monitor in the agricultural land cover changes in the Tov aimag, as there is important agricultural producing area in Mongolia. We have developed approaches to map and monitor land cover and land use change across in the Tov aimag using multi-spectral image data. In this study, maximum likelihood supervised classification was applied to Landsat TM and ETM images acquired in 1989 and 2000, respectively, to map cropland area cover changes in the Tov aimag of Mongolia. A supervised classification was carried out on the six reflective bands (bands 1-5 and band 7) for the two images individually with the aid of ground based agricultural monitoring data. Results were then tested using ground check data.

  14. Application of Landsat data to map and monitor agricultural land cover

    NASA Astrophysics Data System (ADS)

    Erdenee, B.; Tana, Gegen; Tateishi, Ryutaro

    2009-09-01

    Agriculture is one of the major economic sectors of Mongolia and the country's economy is very much dependent on the development of agricultural production. Being the rural and poorest conditions of Mongolia, 60-90% of its labor force employed in agriculture and agricultural sector has a prominent economic role. Mongolian agriculture has been successful in increasing food grains production in the past, guided by the goals of self-sufficiency in the country. The satellite imagery has been effectively utilized for classifying land cover types and detecting land cover conditions. Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. Objective of this study to monitor in the agricultural land cover changes in the Tov aimag, as there is important agricultural producing area in Mongolia. We have developed approaches to map and monitor land cover and land use change across in the Tov aimag using multi-spectral image data. In this study, maximum likelihood supervised classification was applied to Landsat TM and ETM images acquired in 1989 and 2000, respectively, to map cropland area cover changes in the Tov aimag of Mongolia. A supervised classification was carried out on the six reflective bands (bands 1-5 and band 7) for the two images individually with the aid of ground based agricultural monitoring data. Results were then tested using ground check data.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  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. Agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agriculture within the United States is varied and produces a large value ($200 billion in 2002) of production across a wide range of plant and animal production systems. Because of this diversity, changes in climate will likely impact agriculture throughout the United States. Climate affects crop, ...

  20. Multilevel drought reanalysis over France with Safran-Isba-Modcou hydrometeorological suite

    NASA Astrophysics Data System (ADS)

    Vidal, J.-P.; Martin, E.; Franchistéguy, L.; Soubeyroux, J.-M.; Baillon, M.; Blanchard, M.

    2009-04-01

    From a physics point of view, droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc.) on specific components of this cycle prevent one from deriving a universal drought index. Drought monitoring thus requires having indices related to meteorological, agricultural, and hydrological droughts. This paper proposes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on Safran-Isba-Modcou (SIM) hydrometeorological suite. First, a high-resolution (hourly, 8km) gridded atmospheric reanalysis based on both ground observations and large-scale ECMWF atmospheric model archives was performed with Safran mesoscale analysis system for the period August 1958-July 2008. Analysed near-surface variables were then used to force the Isba land surface scheme which computes the surface water and energy budgets. The evolution of aquifers and river flows was furthermore simulated by Modcou hydrogeological model. Meteorological droughts are characterized by computing a Standardized Precipitation Index (SPI) at time scales varying from 1 to 24 months. Agricultural and hydrological droughts are identified by applying a similar standardizing method to Soil Wetness Index (SWI) and streamflow respectively. Such an approach provides a consistent way to assess the propagation of droughts through the land surface hydrological cycle, by considering normally distributed indices derived from water contents in each component. Similarities and differences between different types of drought are highlighted by examining the severity, duration and areal extension of drought events, from multi-year precipitation deficits (1989-1990) to short hot and dry periods (2003). This multilevel drought climatology will serve as a basis for assessing the impacts of climate change on droughts in France.

  1. Drought Prediction in Iran during Next 30 Years

    NASA Astrophysics Data System (ADS)

    Khazanedari, L.; Zabol Abbasi, F.; Ghandhari, Sh.; Kouhi, M.; Malbousi, Sh.

    2009-09-01

    The effects of climate changes, especially due to increasing of greenhouse gasses, caused a lot of problems that affect different sections of society. One of the most important of these effects is the increasing of natural disasters such as flood, drought, tropical cyclones, raising sea level, dust storm, etc. Drought and flood are the most prevalent of these disasters in Iran. Because of the geographical location of Iran and the synoptic systems that affect this region, it is clear that dry is one of the characteristics of this region, and drought is one of the most important of natural disaster that affect this country. Drought affects the different sectors of society such as water resources, agriculture, industry, economy, health, etc therefore drought monitoring is necessary for planning in future. For this purpose, the climate data should be simulated for future period by using outputs of Atmospheric-Ocean General Circulation Model. In this paper precipitation data during 2010-2039 is simulated by downscaling via LARS-WG model. Then, drought situation is estimated according to DI and SPI, by using these data in Iran. The results of this study have showed that during next 30 years, drought conditions will be increase in Iran, and it confirms climate change event in this region. In addition, the most parts of Iran will experience severe and extreme drought in 2011, 2025, 2032, 2034, 2035, 2039, and among these years 2039 will have more critical drought situation. Keywords: Atmospheric General Circulation Models, Downscaling, LARS-WG, Drought, Decile Index, Standard Precipitation Index.

  2. Monitoring agricultural burning in the Mississippi River Valley region from the moderate resolution imaging spectroradiometer (MODIS).

    PubMed

    Korontzi, Stefania; McCarty, Jessica; Justice, Christopher

    2008-09-01

    The 2003 active fire observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), on board NASA's Terra and Aqua satellites, were analyzed to assess burning activity in the cropland areas of the Mississippi River Valley region. Agricultural burning was found to be an important contributor to fire activity in this region, accounting for approximately one-third of all burning. Agricultural fire activity showed two seasonal peaks: the first, smaller peak, occurring in June during the spring harvesting of wheat; and the second, bigger peak, in October during the fall harvesting of rice and soy. The seasonal signal in agricultural burning was predominantly evident in the early afternoon MODIS Aqua fire detections. A strong diurnal agricultural fire signal was prevalent during the fall harvesting months, as suggested by the substantially higher number (approximately 3.5 times) of fires detected by MODIS Aqua in the early afternoon, compared with those detected by MODIS Terra in the morning. No diurnal variations in agricultural fire activity were apparent during the springtime wheat-harvesting season. The seasonal and diurnal patterns in agricultural fire activity detected by MODIS are supported by known crop management practices in this region. MODIS data provide an important means to characterize and monitor agricultural fire dynamics and management practices. PMID:18817116

  3. Satellite Solar-induced Chlorophyll Fluorescence Reveals Drought Onset Mechanisms: Insights from Two Contrasting Extreme Events

    NASA Astrophysics Data System (ADS)

    Sun, Y.; Fu, R.; Dickinson, R. E.; Joiner, J.; Frankenberg, C.; Gu, L.; Xia, Y.; Fernando, N.

    2015-12-01

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

  4. Development and implementation of the Norwegian monitoring programme for agricultural landscapes.

    PubMed

    Dramstad, W E; Fjellstad, W J; Strand, G H; Mathiesen, H F; Engan, G; Stokland, J N

    2002-01-01

    This paper describes the development and implementation of the Norwegian monitoring programme for agricultural landscapes--the '3Q programme'. The main objective of the scheme is to indicate development trends in the agricultural landscape, and their consequences for spatial structure, biodiversity, cultural heritage and accessibility. The monitoring programme aims to give policy feedback and provide data to fulfill international reporting requirements. This paper describes the background to the programme and reasons behind the choice of methods. Results are presented to show the accuracy of the methods employed and the range of indicator values recorded in the programme. Strengths and limitations of the monitoring programme are discussed, and potential future improvements and developments are outlined. Although there remains a potential for methodological improvement, we stress the importance of establishing a baseline to enable the detection of development trends in a rapidly changing environment. PMID:11876074

  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. 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.

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

    PubMed

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

    2011-03-01

    A thinning experiment stand at Avoca, Ballinvalley, on the east coast of the Republic of Ireland was used to test a developed methodology aimed at monitoring drought stress, based on the analysis of growth rings obtained by coring. The stand incorporated six plots representing three thinning regimes (light, moderate and heavy) and was planted in the spring of 1943 on a brown earth soil. Radial growth (early- and latewood) was measured for the purpose of this study. A multidisciplinary approach was used to assess historic tree response to climate: specifically, the application of statistical tools such as principal component and canonical correlation analysis to dendrochronology, stable isotopes, ring density proxy, blue reflectance and forest biometrics. Results showed that radial growth was a good proxy for monitoring changes to moisture deficit, while maximum density and blue reflectance were appropriate for assessing changes in accumulated temperature for the growing season. Rainfall also influenced radial growth changes but not significantly, and was a major factor in stable carbon and oxygen discrimination, mostly in the latewood formation phase. Stable oxygen isotope analysis was more accurate than radial growth analysis in drought detection, as it helped detect drought signals in both early- and latewood while radial growth analysis only detected the drought signal in earlywood. Many studies have shown that tree rings provide vital information for marking past climatic events. This work provides a methodology to better identify and understand how commonly measured tree proxies relate to environmental parameters, and can best be used to characterize and pinpoint drought events (variously described using parameters such as like moisture deficit, accumulated temperature, rainfall and potential evaporation). PMID:21411433

  11. 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.

  12. 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.

  13. 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.

  14. 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. PMID:27315128

  15. 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.

  16. 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

  17. 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

  18. Spatio-Temporal Drought Analysis on Example of the Central European Gridded Dataset

    NASA Astrophysics Data System (ADS)

    Stepanek, P.; Trnka, M.; Zahradníček, P.; Semerádová, D.; Hlavinka, P.

    2014-12-01

    Drought may have severe impacts on many human activities. Understanding its spatio-temporal variations is thus very important in many research fields. On example of the Central Europe dataset we analyzed and compared some products based on drought analyses, which may help to answer important questions for impact studies: 1) evaluation of the added value coming from inclusion of spatial aspect (not only temporal one) in the drought analysis; 2) comparison of drought indices calculated from various number of available input meteorological elements (backwards into history less and less meteorological elements are available); 3) linking together meteorological drought with agriculture one. Basis for the study was production of gridded dataset of basic meteorological elements (daily minimum and maximum temperature, precipitation, sunshine duration, relative humidity and wind speed). From the station location time series in the period 1961-2013, gridded dataset was created applying geostatistical methods using both spatial and temporal aspects of the data (spacetime package under R). From such gridded dataset, SPEI (standardized precipitation evaporation index) was calculated using various approaches: Thornthwaite (potential evapotranspiration), Hargreaves and Penman-Monteith (reference evapotranspiration). The outputs were gridded datasets of the SPEIs that were then analyzed for the Central Europe both from temporal (based on station data) and spatial aspects. In order to estimate how this meteorological drought analysis may contribute to drought impact analysis (in our case we chose agriculture), we compared the results with the analysis coming from the agrometeorological drought monitoring system (based on SoilClim - dynamical model of soil water content) which is now used for drought monitoring and analysis in the Central Europe. Such comparison is important either for drought analysis in the past (when soil observations are not available) or also for future climate

  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. 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

  1. 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.

  2. Monitoring Indicators for Mediterranean Wetland and Agricultural Area Using ALOS Data

    NASA Astrophysics Data System (ADS)

    Alexandridis, T. K.; Topaloglou, C. A.; Pardalis, I.; Tsakoumis, G.; Vogiatzis, M.; Andrianopoulos, A.; Takavakoglou, V.; Vougioukas, S.; Bochtis, D.; Zalidis, G. C.; Silleos, N. G.

    2008-11-01

    Agricultural and other human activities are a pressure to several Mediterranean wetland ecosystems. Monitoring the pressures and the state of the ecosystem is an important input to management activities. The aim of this work was to select and implement indicators for monitoring the natural and agricultural environment of a Mediterranean wetland using Earth Observation (EO), and specifically the recently launched ALOS satellite images. Multiple levels of data were collected and integrated: remote sensing data (ALOS AVNIR-2 and PALSAR), unmanned aerial vehicle (UAV) images, and observations during field surveys. EO and GIS methods used during monitoring of the study area involved preprocessing of the satellite images, enhancement of information, information extraction, and derivation of indicators. Geographic overlay comparison with results derived from the area in 2003 using a Terra/ASTER image was used to identify the changes that occurred during the last years. The methodology was applied in the wetland and surrounding agricultural area of Ramsar Convention site "lakes Koronia-Volvi" (Greece). Resulting thematic maps revealed and quantified the intensity of pressures in the vicinity of the protected wetland, the state of the wetland ecosystem, as well as the seasonal and long term temporal trends.

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

    NASA Astrophysics Data System (ADS)

    Livneh, B.; Hoerling, M. P.

    2014-12-01

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

  4. 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.

  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. Drought description

    USGS Publications Warehouse

    Matalas, N.C.

    1991-01-01

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

  7. 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.

  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. 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.

  10. 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.

  11. 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

  12. 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

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Sun, Ying; Fu, Rong; Dickinson, Robert; Joiner, Joanna; Frankenberg, Christian; Gu, Lianhong; Xia, Youlong; Fernando, Nelun

    2015-11-01

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

  17. Monitoring and APEX modeling of no-till and reduced-till in tile drained agricultural landscapes for water quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The evaluation of agricultural practices through monitoring and modeling is necessary for the development of more effective conservation programs and policies. No-till and reduced-till are both agricultural conservation practices widely promoted for their proven ability to conserve water and reduce ...

  18. 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.

  19. Biological and biochemical soil indicators: monitoring tools of different agricultural managements

    NASA Astrophysics Data System (ADS)

    Scotti, Riccardo; Sultana, Salma; Scelza, Rosalia; Marzaioli, Rossana; D'Ascoli, Rosaria; Rao, Maria A.

    2010-05-01

    The intensive agricultural managements, increased in the last twenty years, have resulted in a decrease in fertility of soils, representing a serious threat to agricultural productivity due to both the increase in production cost, mainly for intensive use of mineral fertilizers, and the loss of the quality of crops themselves. Organic matter content is closely related to the soil fertility and its progressive reduction in cultivates soils, without a satisfactory recovery, could make agriculture untenable, resulting in a high detrimental effect on environment. But an appropriate soil management practices can improve soil quality by utilizing organic amendments as alternative to mineral fertilizers to increase soil quality and plant growth. In this context, demand of suitable indicators, whose are able to assess the impact of different agricultural managements on soil quality, has increased. It has shown that soil biological and biochemical properties are able to respond to small changes in soil conditions, thus providing information on subtle alterations in soil quality. Aim of this study was to evaluate the use of soil biological and biochemical properties as fertility indicators in agricultural soils under different agricultural managements, sited in Campania Region (Southern Italy). After a preliminary monitoring phase of soil fertility on different farms sited in five agricultural areas of Campania Region, we have selected two farms in two different study areas to assess the effect on soil quality of different organic amendments. In particular, a compost from municipal solid waste and wood from scraps of poplars pruning were supplied in different doses and ratios. Soil samplings after one month from the amendment addition and then every 4 months until a year were carried out. All collected soil samples were characterized by main physical, chemical, biochemical and biological properties. In general, the use of different organic amendments showed a positive effect

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. Groundwater in times of droughts

    NASA Astrophysics Data System (ADS)

    Attinger, Sabine; Kumar, Rohini; Musuuza, Jude; Samaniego, Luis

    2014-05-01

    Droughts are characterized as sustained and regionally extensive occurrences of below-average natural water availability. They affect all components of the water cycle: from deficits in soil moisture (agricultural droughts) through reduced groundwater recharge and groundwater levels to low streamflows or dried-up rivers (hydrological droughts). Groundwater discharge is a significant component of streamflow, with groundwater contributing as much as 90 percent of annual streamflow volume in some parts of the U.S., Canada and Europe (Beck et al., 2013). And groundwater systems strongly control the hydrological drought characteristics all over the world (van Lanen et al., 2013). Making use of large scale hydrological models van Lanen demonstrated that groundwater systems substantially affect the duration, particularly of the more extreme drought events. The responsiveness of the groundwater system is as important as climate for hydrological drought development. This urges for an improvement of subsurface modules in conceptual hydrological models to be more useful for water resources assessments. In this talk, we will discuss different subsurface modeling approaches ranging from spatially distributed groundwater models to simpler reservoir-type modeling approaches and the implications the chosen model has on modelled groundwater droughts and base flow characteristics. In particular, we discuss a standardized groundwater drought index (SGI) to characterize the groundwater deficit and the groundwater head anomalies. Based on SGI, we investigate different statistics (severity, area and duration) of individual drought events for the different model approaches. These results will be related to locally measured groundwater data.

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  5. 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.

  6. 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

  7. 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.

  8. 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. PMID:25336153

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

    PubMed Central

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

    2008-01-01

    developed in the study was able to provide a better alternative to increase the accuracy of drought monitoring for agricultural administration and farming.

  10. Towards the construction of a Drought Early Warning System in México

    NASA Astrophysics Data System (ADS)

    Neri, C.; Magaña, V. O.

    2011-12-01

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

  11. 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

  12. Drought processes, modeling, and mitigation

    NASA Astrophysics Data System (ADS)

    Mishra, Ashok K.; Sivakumar, Bellie; Singh, Vijay P.

    2015-07-01

    Accurate assessment of droughts is crucial for proper planning and management of our water resources, environment, and ecosystems. The combined influence of increasing water demands and the anticipated impacts of global climate change has already raised serious concerns about worsening drought conditions in the future and their social, economic, and environmental impacts. As a result, studies on droughts are currently a major focal point for a broad range of research communities, including civil engineers, hydrologists, environmentalists, ecologists, meteorologists, geologists, agricultural scientists, economists, policy makers, and water managers. There is, therefore, an urgent need for enhancing our understanding of droughts (e.g. occurrence, modeling), making more reliable assessments of their impacts on various sectors of our society (e.g. domestic, agricultural, industrial), and undertaking appropriate adaptation and mitigation measures, especially in the face of global climate change.

  13. Drought tolerance

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. 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...

  15. 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.

  16. 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

  17. 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. PMID:23595554

  18. 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